The Griff(is)(es)(ith) Patrilineal Line of Descent: The Shape and Movement of the G Phylogenetic Tree through Time

This story focuses on looking at the phylogenetic tree of the Griff(is)(es)ith) patrilineal line of descent and the migratory route of the Griffis family Y-DNA in the long term genealogical time layer.

Y-DNA phylogenetic trees provide an effective, graphic portrayal of human genetic history and genealogy. They offer insights into paternal lineage, population migrations and a complimentary image to discuss anthropological research and genealogical connections. Phylogenetic trees are also known as an evolutionary tree, cladogram, or tree of life. [1]

The use of phylogenetic trees provide a skeletal outline of the specific evolutionary path of the patrilineal genetic line of the Griff(is)(es)(ith) family. The family genetic patrilineal line is part of Haplogroup G. The G haplogrup is a Y-chromosomal lineage originating in the eastern Anatolian-Armenian-western Iranian region. From aproximately 10,000 BCE to 3,000 BCE it was a predominant YDNA haplogrup in Europe. Thereafter, it lost its predomance and became a minorty among YDNA haplogroups in Europe.

Looking Backward in Time: The Present European Y-DNA Phylogenetic Tree

In 2013 FamilyTreeDNA (FTDNA) released the advanced Big Y test and since then the company analyzed 32,000 Y chromosomes in ultra-high resolution. This has allowed the ability to identify hundreds of thousands of unique Y chromosome mutations. In 2019, the company created the Y-700 YDNA test and detected over 500,000 unique mutations in 32,000 Big Y testers. In May 2019, the Y-DNA haplotree passed 20,000 branches. The branches are defined by over 150,000 unique mutations. [2]

Illustration one below represents a circular phylogenetic Y-DNA haplogroup tree based on the testing results of FTDNA in 2019. It is a visual representation that shows evolutionary relationships between paternal lineages. The tree structure displays branches that represent genetic mutations and divergence over time. Time flows from the center outward, with older lineages near the center and younger ones at the periphery. Each branching point represents a most recent common ancestor – a genetic mutation (SNP) that created a new haplogroup. [3] Related haplogroups are grouped together in adjacent branches, showing their evolutionary relationship. Branch length indicates genetic distance or time between the genetic mutations.

Illustration One: FamilyTreeDNA Circular Phyogenetic YDNA Tree of Haplogroups Based on the Y-700 Test Results

Click for Larger View | Source: Big Y-700: The Forefront of y Chromosome, 7 Jun 2019, FamilyTreeDNA Blog, https://blog.familytreedna.com/human-y-chromosome-testing-milestones/

A review of the ‘pie chart’ or circular phylogenetic tree in illustration one reveals the predominance of the R haplogroup. Haplogroup R represents about half the men who have completed FamilyTreeDNA Y-700 DNA tests and has several major subbranches. Haplogroups I and J present roughly one third of the men tested. The Griff(is)(es)(ith) family lineage is part of haplogroup G, which is an older haplogroup with fewer branches and fewer test results.

While this circular phylogenetic tree represents the 2019 population of FTDNA Y-700 DNA tests kits, it has a vague proportional resemblance of the YDNA composition of Europe.

We know that two-thirds of all European men descend from just three ancestors who lived in the late Neolithic.” [4]

This quote is an attention grabber. It has been quoted in a number of genealogical sources. In most regions of Europe, the Neolithic period generally ended around 3000 BCE, marking the transition to the Bronze Age. The exact time frame can vary depending on the geographical location with some areas seeing the Neolithic last until around 2000 BC. [5]

This remarkable genetic pattern emerged during a massive population explosion that occurred across Europe during the Bronze Age, spanning from the Balkans to the British Isles. The population expansion occurred between 2,000 and 4,000 years ago, particularly affecting males across a continuous region from Greece to Scandinavia. These dominant males, likely associated with Bronze Age cultures, established lineages that became prevalent throughout European populations. [6]

This YDNA genetic legacy differs from patterns seen in mitochondrial DNA which is passed down through mothers. Research of mtDNA genetic patterns shows much older population growth patterns, suggesting this was a male-specific phenomenon tied to Bronze Age social structures. [7]

Going back to the original quote regarding those three ancestors, the statement requires some clarification. Genetic studies show that approximately sixty-four percent of European men can trace their Y-chromosome lineages back to just three male ancestors who lived between 3,500 and 7,300 years ago. These haplogroup lineages are identified as I1, R1a, and R1b and are identified in illustration five by three ‘standing male’ symbols. [8]

By counting the number of mutations that have accumulated within each branch over the generations, it is estimated that these three men lived at different times between 3,500 and 7,300 years ago. The lineages of each seem to have exploded in the centuries following their lifetimes to dominate Europe. The Bronze age is identified by a dotted elliptical circle in the illustration. Within that enclircled time era, the idenification of a proliferaion of lineages is evident in the I and R haplogroups.

Illustration Two: Phylogeny and Geographical Distribution of European Lineages

Click for Larger View | Source: Modified version of Figure 1 in Batini, C., Hallast, P., Zadik, D. et al. Large-scale recent expansion of European patrilineages shown by population resequencing. Nat Commun 6, p. 7152 (2015). https://doi.org/10.1038/ncomms8152

The spread of these Y-chromosome patterns depicted in illustration two may be linked to the influence of the Yamnaya people. They were nomadic, pastoral herders from the steppes of modern-day Ukraine and Russia. They entered Europe around 4,500 years ago. They brought with them technological innovations including horses, the use of wheel driven transportation, and distinctive burial practices. Dominant males linked with these cultures could be responsible for the Y chromosome patterns we see today. [9]

The complete genetic heritage of modern Europeans is complex, involving at least three distinct ancestral populations and represented by a number of YDNA and mtDNA Haplogroups: West European Hunter-Gatherers, Ancient North Eurasian and Early European Farmers. This genetic mixing occurred within the last 7,000 years, creating the modern European gene pool. [10]

Overview of the Migratory Path

As a background to discussing the patrilineal line of descent, the video below is an animated version of the estimated migratory path of the genetic Y-DNA descendants of the Griff(is)(es)(ith) family line. It is a singular path based on my Y-700 YDNA test results. It starts with the root Y-DNA source in Africa, often referred to as “Y-chromosomal Adam,” the most recent common ancestor of all living males. [11]

Animated Video of Estimated Migratory YDNA Path for the Griff(is)(es)(ith) Paternal Line

Source: Migratory Rendition for Griffis Family Y-DNA Migratory path, Globetrekker, FamilyTreeDNA

The animated video provides an inuitive rendition of over 200,000 years of the successive mutations in Y-DNA for the family paternal line. It provides a graphic portrayal of the general path of migration that ultimately led to the English Isle. The animation depicts lands that are now submerged (e.g. Doggerland [12] ) and the extent of the ice age in context of the migration. Illustration one below is a graphic portrayal the migratory path of the G haplogroup starting around 26,000 BCE.

Illustration One: Snapshot of Migratory Path of G Haplogroup and Griff(is)(es)(ith) Family Descendants

Click for Larger View | Source: Modified version of a snapshop of the Migratory Rendition for Griffis Family Y-DNA Migratory path, Globetrekker, FamilyTreeDNA

Haplogroup G-M201 likely originated in a region spanning eastern Anatolia, Armenia, and western Iran around 26,000 BCE.. The earliest G-M201 carriers were linked to pre-Neolithic populations, but its diversification in other subclades accelerated during the Neolithic transition (around 10,000 BCE). The G-P303 sub-clade, which accounts for the majority of European G lineages, diverged during this period, with sub-clades like G-L497 (Europe-specific) and G-U1 (Near Eastern/Caucasus) reflecting later regional adaptations. [13]. Haplogroups G2a and J-M172, which originated in Anatolia, spread westward alongside early farming communities.  [14]

Haplogroup G2a spread across Europe primarily through the Neolithic agricultural expansion from the Near East (Anatolia) into Europe, roughly between 9,000 and 5,000 years ago. This migration involved early farming communities moving westward, introducing agriculture, domesticated animals, and pottery cultures into regions previously inhabited by hunter-gatherers. The Neolithic Revolution began in the Levant and Anatolia, where domestication of crops like wheat, barley, and legumes, alongside animals such as sheep and goats, laid the foundation for sedentary lifestyles. [15]

The Two Routes of G Haplogroup Migration

As depicted in illustation two below, the spread of the G haplogroup occurred via two main routes: the Mediterranean Coastal Route (“Maritime Route”) and the Central European Inland Route (“Danubian Route”).

Illustration Two: The Two Main Routes of Migration for Neolithic Farmers

Click for Larger View | Source: Spinney, Laura, When the First Farmers Arrived in Europe, Inequality Evolved, 1 Jul 2020, online Scientific American, https://www.scientificamerican.com/article/when-the-first-farmers-arrived-in-europe-inequality-evolved/ , Originally published as “How Farmers Conquered Europe” in Scientific American Magazine Vol. 323 No. 1 (July 2020)

The Mediterranean route took early Neolithic farmers carrying haplogroup G2a along the Mediterranean coastline, establishing settlements in Greece, Italy, southern France, Spain, and Portugal. This migration is associated with the Cardium Pottery culture, characterized by pottery decorated with shell impressions. Ancient DNA evidence from Neolithic sites in southern France (such as the Treilles group around 3000 BCE) confirms a high prevalence of G2a ( individuals who descended from populations originating in Anatolia or the Aegean region. [16]

Another major route was inland via the Danube River valley into Central Europe. This is the route that the Griff(is)(es)(ith Paternal genetic line of descent took in migranting westward in Europe. This dispersal is associated with the Linear Pottery culture (LBK) (approximately 5500–4500 BCE), which introduced agriculture to Central Europe. Ancient DNA analyses of LBK archaeological sites in Germany and Hungary show a high frequency of haplogroup G2a among early farmers. [17]

By 7000 BCE, these practices spread northwestward into southeastern Europe, marking the start of the Continental Route. The Starčevo culture (6000–5400 BCE) in present-day Serbia and Hungary served as the initial bridge between Anatolian farmers and the Danube Basin, establishing agro-pastoral communities that later influenced the LBK. [18]

The G haplogroup associated with this ‘Danbian route’ in central Europe shows a frequency peak in the Danube basin associated with the G-L497 haplogroup, aligning with the Linear Pottery Culture (LBK) expansion. [19] The European origin of G-L497 makes it particularly valuable for tracing secondary migration patterns, such as the Griff(is)(es)(ith) paternal line, and population movements within Europe following the initial Neolithic expansion.

G Haplogroup Decline, Absorption and Refuge

Despite its widespread initial distribution, along with the J Haplogroup, during Europe’s Neolithic period, haplogroup G2a significantly declined in frequency after 3000 BCE due to migrations of pastoralist populations from the Eurasian steppe (such as the Yamnaya culture), who carried different Y-DNA haplogroups like R1b and R1a. These migrations largely replaced or assimilated earlier farming populations. [20]

The R haplogroup pastoralists expanded through the Pontic-Caspian steppe corridor, moving westward into Europe from their eastern origins. These steppe populations were genetically distinct from both European hunter-gatherers and early farmers. The expansion of these pastoralist groups led to massive population turnover in Europe, with substantial genetic input from steppe populations arriving after 3000 BCE. [21]

While many G2a lineages were largely replaced by Indo-European expansions, some G2a-L140 subclades appear to have been assimilated into Proto-Indo-European societies associated with the R haplogroups. These lineages, including certain L497-derived groups, joined R1b and R1a tribes in their subsequent migrations. This suggests a complex interaction between the descendants of Neolithic farmers and the expanding Indo-European populations rather than simple replacement. [22]

These “Indo-Europeanized G2a lineages”, such as the Griff(is)(es)(ith) line, belonged to deep clades of G2a-L140, including subclades like L13 and Z1816. While the original Neolithic G2a populations were dramatically reduced, some were incorporated into the expanding Indo-European groups, allowing certain G-L497 lineages to spread alongside R1a and R1b haplogroups during later migrations.

Today, haplogroup G2a descendants remain present at lower frequencies throughout Europe but have higher concentrations in isolated regions like Sardinia and parts of the Caucasus, reflecting remnants of these ancient Neolithic expansions. The Griffis)(es)(ith) paternal line is part of this minorty haplogroup in modern times.

Haplogroups and Phylogenetic Trees

Y-DNA haplogroups serve as markers of historical population movements. A haplogroup is a group of people who share a common ancestor and similar genetic markers. The Y chromosome’s lack of recombination allows SNPs (single nucleotide polymorphisms) to accumulate linearly over generations, making them valuable markers for tracing paternal lineages.

Human phylogenetics is the study of evolutionary relationships between ancient and present humans based on their genetic material, specifically through DNA and RNA sequencing. Phylogenetic relationships are typically visualized through phylogenetic trees, which use branches and nodes to show the chronology of genetic mutations. These trees can be either rooted, showing a hypothetical common ancestor, or unrooted, making no assumptions about ancestral lines. [23]

Classifying the accumulated SNPs generation by generation make it possible to retrace the genealogical tree of humanity with great accuracy, to detect patterns in the distribution of shared historical lineages and to retrace historical migrations of male lineages.[24]

Y-DNA phylogenetic trees are visual representations of the evolutionary relationships between different paternal lineages in human populations based on mutations in the Y chromosome. These trees illustrate the hierarchical structure of Y-DNA haplogroups, which are groups of men sharing specific mutations on their Y chromosome inherited from common paternal ancestors.

Paleolithic lineages that underwent serious population bottlenecks for thousands of years sometimes have a series of over one hundred defining SNPs or SNP variants (e.g. haplogroups G and I1 each have over 300 defining SNPs). Generally speaking the number of accumulated SNPs between a haplogroup and its direct subclade correlates roughly to the number of generations elapsed.[25]

The average number of years between Y-chromosomal SNP mutations is a parameter for estimating timelines in genetic genealogy, population genetics, and anthropological studies. Based on current research and commercial testing methodologies, this interval typically ranges from 83 to 144 years per SNP, depending on the sequencing technology, genomic regions analyzed, and mutation rate calculations. [26]

Branch lengths in a YDNA phylogenetic tree can be interpreted as measures of time, but there is significant scientific debate about the exact temporal relationships. [27] In phylogenetic studies (the study of evolutionary relationships between human remains or tests based on genetic material), branch lengths are considered proportional to time when evolution rates are uniform across lineages. [28] For Y-chromosomes, this has allowed researchers to create phylogenies where branch lengths can be used to estimate the timing of population divergences. [29]

Y-DNA Phylogenetic Trees

The phylogenetic tree starts with a root, often referred to as “Y-chromosomal Adam” [30], the most recent common ancestor of all living males. Haplogroups are labeled with letters A through T, with further subclades denoted by numbers and lowercase letters. The Y Chromosome Consortium (YCC) developed a naming system for major haplogroups and their subclades. [31]

Illustration Three: Major Clades of Y-DNA Phylogenetic Tree

Click for Larger View | Source: Modified version of illustration in Hallast, P., Agdzhoyan, A., Balanovsky, O. et al. A Southeast Asian origin for present-day non-African human Y chromosomes. Hum Genet 140, 299–307 (2021). https://doi.org/10.1007/s00439-020-02204-9

Phylogenetic trees contextualize these haplogroups within historical and geographical frameworks, revealing how subclades diverged during key migratory periods. The combination of Y-DNA trees with archaeological findings has clarified debates over human migratory patterns. Each branch represents a distinct lineage defined by specific single-nucleotide polymorphisms (SNPs). The tree’s depth indicates the time since divergence with deeper branches representing older lineages. New mutations are continually discovered, leading to regular updates and the increased resolution of the tree. [32]

Illustration Four: Chronological Development of Main Western Eurasian Y-DNA Haplogroup Subclades from the Late Paleolithic to the Iron Age

Click for Larger View | Source: Maciamo Hay, Chronological development of main Western Eurasian Y-DNA haplogroups from the Late Paleolithic to the Iron Age, Feb 2017, Eupedia, https://www.eupedia.com/genetics/phylogenetic_trees_Y-DNA_haplogroups.shtml

Y-DNA phylogenetic trees provide a number of advantages for genealogical studies, forensic applications and population genetics. They can resolve paternal lineages and surname correlations, validate and extend surname clusters, enhance foresensc and kinship analysis, advance methodological innovations, and reconstruct ancient migrations and population histories. [33]

These trees can integrate short tandem repeats (STRs) and SNPs to resolve relationships across both recent, mid range and deep historical time scales. By dating branch points using mutation rates, researchers estimate the timing of population splits. Classiying SNPs and STRs into a genealogical order is known as phylogenentics. [34]

Y-DNA phylogenetic trees excel in connecting individuals who share recent common ancestors through STR markers, which mutate relatively quickly, and deeper ancestral links through slower-mutating SNPs.  For example, STR-based clusters (e.g., 37-marker or 111-marker STR haplotypes) can identify related individuals within a genealogical timeframe in the last 500 years, while SNP-defined haplogroups (for example, the G-L497 haplogroup) trace lineage splits dating to the Neolithic or Bronze Age. This dual resolution allows surname projects to corroborate paper trails with genetic evidence, particularly for patrilineal lines where records are sparse in the short term and mid range genealogical time layers. [35]

The Most Recent Common Ancestor and Phylogenetic Trees

The ‘nodes’ in phylogenetic trees represent estimated birth dates of the most recent common ancestors for subsequent lineages. The ages of the most recent common ancestors (tMRCA) in Y-DNA phylogenetic trees are calculated primarily through statistical methods that incorporate genetic data and historical information.

Rather than focus on the order of the branch tips on a phylogenetc tree (i.e., which lineage goes to the right and which goes to the left), this ordering is not meaningful at all. Instead, the key to understanding genetic relationships in phylogenetic trees is common ancestry. Common ancestry refers to the fact that distinct descendent lineages have the same ancestral lineage in common with one another, as shown in illustration five.

Determining the dates of tMRCA for Y-DNA haplogroups involves several steps and assumptions, which also come with certain limitations. While SNP-based calculations provide a powerful tool for estimating tMRCA dates, they are subject to limitations related to mutation rate variability, data quality, and the assumptions underlying the models used to estimated their respective dates.

Illustration Five: the Most Recent Common Ancestor

Variability of tMRCA Estimates

Current calculations for TMRCA in Y-DNA phylogenetic trees rely on counting genetic mutations (SNPs and STRs), using probabilistic models that integrate multiple data types, and adjusting results based on historical context and demographic factors. [36]

As with any historical calculations, there are a number of inherent limitations associated with the estimation process. The mutation rate is not perfectly uniform and can vary between different parts of the Y chromosome. This variability can lead to inaccuracies in MRCA date estimates. [37] Random mutations can skew results, especially when comparing individual Big Y results. Anomalies in variant counts can lead to discrepancies in estimated dates. [38]

The calculations rely on assumptions about mutation rates and the models used. Different models or assumptions can yield different estimates, and there is ongoing debate about the most accurate methods. [39] Historical events like bottlenecks or gene flow can affect the genetic diversity of Y-DNA haplogroups, potentially altering the apparent MRCA date. [40]

An example of the variability associated with establishing estimated dates for MRCAs is provided below. Illustration six depicts an high level phylogenetic tree that covers part of my Y-DNA ancestral genetic path. Some of my intermediate MRCAs are not shown in the tree. The tree starts with haplogroup G-L140. The shaded arrow in the illustration depicts the path of my YDNA genetic mutations from haplogroup G-L140 to haplogrop G-Y8903.

Illustration Six: A Philogenetic Tree of haplgroup G2a-L140

Click for Larger View | Source: Modified phylogenetic chart found at Maciamo, Hay, Phylogeny of G2a, Haplogroup G2a, July 2023, Eupedia, https://www.eupedia.com/europe/Haplogroup_G2a_Y-DNA.shtml

Based on the genetic path of haplogroup group mutations shown in the phylogenetic tree, I have chosen four MRCAs shown in table one. The table provides an estimated birth date of each of the MRCAs associated with the unique Y-DNA mutations. Based on the calucations used by FamilyTreeDNA, the table also provides statistical confidence ranges or intervals of the 99, 95 and 68 percent likelihood of the birth dates to fall within a given time range.

Table One: Selected Most Recent Common Ancestors and Estimated Births

MRCA
Estimated
Birth
(Mean)
Estimated
Birth
Date
99 %
Confidence
Interval (CI) of when MRCA was born (Calendar
Date)
95 % CI
Calendar
Date
Range
65 % CI
Calendar
Date
Range
L1404,587 BCE3615 – 1650 BCE3256 – 1958 BCE2913 – 2255 BCE
L4977,549 BCE7220 – 4051 BCE6642 – 4549 BCE6090 – 5028 BCE
Z18175,133 BCE4279 – 2094 BCE3880 – 2437 BCE3499 – 2766 BCE
Y8903 /
FGC477
4,279 BCE3374 – 1307 BCE2989 – 1625 BCE2624 – 1933 BCE
Source: Scientific Details for Selected FamilyTreeDNA Haplogroups, 8 Mar 2025, FamilyTreeDNA Discover Reports

The wide variations associated with each estimate of birth for the MRCAs underscore the wide variation of age estimates.

A graphic portrayal of the confidence intervals for estimating the birthdate for the MRCA associated with the G-L497 haplogroup is provided in illustration eight. The common ancestor associated with G-L497 is likely to have been born around the year 5524 BCE, but there is a significant range of his estimated birth. There is a 99 percent change that this person could have been born anywhere between around 7220 BCE and 4051 BCE, a variance of 3,169 years. Narrower bands of probability of when this person was born are provided for 95 percent and 68 percent chances.

Illustration Eight: Confidence Interval Ranges for Estimating Birth Date for MRCA for Haplogroup G-L497

Click for Larger View | Source: Scientific Details for Haplogroup G-L497, familyTreeDNA, 8 Mar 2025 – “The FamilyTreeDNA Time to Most Recent Common Ancestor (TMRCA) estimate is calculated based on SNP and STR test results from many present-day DNA testers. The uncertainty in the molecular clock and other factors is represented in this probability plot, which shows the most likely time when the common ancestor was born amongst the other statistical possibilities.”

What Do Patterns of Subclades in Phylogenetic Trees Tell Us

Different haplogroup clades or sub-branches within the Y-chromosome phylogeneic trees show distinct patterns. The G haplogroup has experienced both the expansion and contraction of subclades through its westward European migratory path.

Illustration Nine

Click for Larger View | Source: Hay, Maciamo, Phylogenetic tree of haplogroup E-V13, May 2018, Phylogenetic trees of Y-chromosomal haplogroups, Eupedia, https://www.eupedia.com/genetics/phylogenetic_trees_Y-DNA_haplogroups.shtml

A haplotree with many subclades occurring in a short time period typically indicates a period of rapid population growth. When a Y-DNA phylogenetic tree displays numerous subclades emerging within a short timeframe, this pattern reveals important insights about our ancestral history. This phenomenon, known as a “rapid radiation” or “burst” of lineages, represents a significant demographic event that can tell us much about historical population dynamics and human migrations.

Illustration nine provides an example of this expansion in an E haplogroup branch.

These rapid diversification events often coincide with favorable historical conditions that supported population growth, such as:

  • Technological innovations that improved survival rates;
  • Expansion into new, resource-rich territories;
  • Climate changes that created more favorable living conditions;
  • Periods of relative peace and prosperity;
  • Agricultural developments supporting larger populations; and
  • Many rapid subclade formations correlate with important cultural transitions, such as the adoption of agriculture, metallurgy, or other technological advances that enabled population growth.

The biological mechanism behind rapid subclade formation involves multiple male lineages successfully reproducing around the same time period. Since Y-DNA mutations occur at relatively slow rates, a cluster of branches occurring closely together in evolutionary time suggests numerous male lineages were simultaneously successful in passing on their Y chromosomes. [41]

Typically, approximately every third or fourth generation, a son is born with a SNP that makes him unique and slightly different from his father”. When many such lineages survive in a short time period, it creates a characteristic ‘star-like pattern’ in the phylogenetic tree, with numerous branches emanating from a single ancestral node or MRCA.

This pattern creates an imbalance where larger ‘child’ clades or haplogroup branches receive statistically more mutations than smaller child clades. The mutations occurring early in the expansion become defining features of the larger subsequent subclades. [42]

This clustering of subclades in time can sometimes cause statistical challenges in dating the exact age of these closely-spaced subclades as there may be too few mutations separating parent clades from child clades to establish precise timing of the most recent common ancestor.

This statistical artifact of clustering subclades is evident when looking at the Griff(is)(es)(ith) family lineage in Table Two below. I have noted this by annotating the time passed between subclades in red.

Illustration Ten

Click for Larger View | Source: Hay, Maciamo, Phylogenetic tree of haplogroup E-V13, May 2018,

Periods of rapid subclade formation stand in stark contrast to periods of slower diversification. When a phylogenetic tree shows a long branch with many accumulated mutations before diversification occurs, this suggests a lineage survived through challenging conditions before eventually flourishing. When a Y-DNA phylogenetic tree displays few subclades over a long stretch of time, this pattern represents what geneticists call a “long branch” – a significant period where little apparent diversification occurred in the paternal lineage. This phenomenon has several important biological, demographic, and methodological implications.

A haplotree with few subclades is provided in illustration ten. Haplogroup E-Y19508 a major branch that has the same most recent common ancestor that is associated with the branch in E-Z5017 in illustration nine. However, the phylogenetic tree associated with the E-Y19508 branch is long and narrow. This is an example of an E haplogroup branch spread over a long time period. This typically indicates slower population growth and more stable demographic conditions.

A primary explanation for long branches with minimal subclade formation is a severe reduction in male effective population size. Studies have documented a pronounced decline in male effective population sizes worldwide around 3000-5000 years ago that was not observed in female lineages. This genetic bottleneck would naturally result in the elimination of many Y-chromosome lineages, leaving fewer surviving male lines to develop subclades. [43]

Geographic isolation and natural barriers can contribute to this pattern by creating separate, isolated populations with limited genetic exchange. The slow accumulation of branches can also result from limited population growth, reduced genetic diversity, or selective pressures affecting Y-chromosome variation. [44]

Long branches with few subclades may also reflect cultural practices that influenced male reproductive success.  In segmentary patrilineal systems, closely related males cluster together in descent groups. Combined with variance in reproductive success between groups, this can substantially reduce Y-chromosome diversity without requiring violence between groups. [45] In some societies, particularly after the development of agriculture and herding, a small number of males may have had disproportionate reproductive success, limiting the diversity of Y lineages. [46]

When interpreting long branches in the Y-DNA tree, several technical factors must be considered. Long branches may be dueto sampling limitations. Current phylogenetic trees are based on available samples which may not represent all historical populations. For example, the R haplogroup shows 16 times more branching than the G haplogroup despite G being almost twice as old. This could be partly due to sampling biases in European populations. [47] There is a phylogenetic artifact, long branch attraction, where distantly related lineages with significant accumulated changes (YDNA variant mutations) appear to be closely related when they are not. This can create false relationships in analyses of long branches. [48]

Some branches of its subclades have long branches and deep-rooting nodes (ancestors). This is reflected in in two notable historic periods that are associated with my Y-DNA lineage, such as the G-PF3345 and G-FGC7515 haplogroups (see illustration elevin).

Illustration Elevin: G Haplogroups with Long Branches

The expansion and contraction of Y-chromosomal subclades across Europe reflect a complex interplay of demographic migrations, cultural transitions, and genetic drift. Over millennia, paternal lineages associated with haplogroups such as G2a, R1b, R1a, I2a, and N1c1 underwent rapid geographical expansion due to founder effects, male-mediated population movements, and technological innovations. These expansions were often tied to transformative periods in European prehistory, including post-glacial recolonization, the Neolithic Revolution, and Bronze Age pastoralist migrations.

Phylogenetic Comparisons Between European Haplogroups

Phylogenetic resolution refers to how accurately and specifically a phylogenetic tree depicts the evolutionary relationships between tMRCAs. A ‘fully resolved’ tree shows clear, bifurcating relationships with each internal node (most recent common ancestor) having two descendants, while a tree with polytomies (multiple branches emerging from a single node) indicates unresolved relationships. [49]

The phylogenetic resolution of haplogroup G is relatively limited compared to other major European Y-DNA haplogroups, such as haplogroups I and R1a, primarily due to differences in demographic history, geographic dispersal patterns, and population dynamics. Haplogroup G had fewer subclades and limited branching, localized pockets of distribution, strong founder effects and limited genetic diversity, and cultural isolation or assmilation into other cultures through time.

Table Two: Comparison of Phylogenetic Characeristics between Haplogroups G, I and R1a

AspectHaplogroup GHaplogroup IHaplogroup R1a
Phylogenetic
Resolution
Moderate to low; fewer subclades identified, limited branching complexity [50]High; clearly defined subclades with distinct geographic distributions [51]High; extensive branching and detailed substructure characterized [52]
Geographic
Distribution
Localized pockets (e.g., Alps, Sardinia, Crete); isolated populations with limited gene flow [53] Widespread across Europe, multiple geographically distinct subclades (e.g., Scandinavia vs. Balkins). [54] Widely dispersed across Europe and Asia; clear regional substructure (e.g., Z280 in Europe, Z93 in Asia) [55]
Founder Effects /
Bottlenecks
Strong founder effects due to Neolithic agricultural expansions from Near East into Europe; limited initial genetic diversity carried forward [56]Postglacial recolonization from multiple refuge areas; distinct expansions from diverse source populations. [57] Multiple expansions from Near East/Central Asia; diversification events well-documented through ancient migrations. [58]
Geographic
Distribution
Concentrated pockets e.g., Tyrol, Sardinia, Crete; limited clinal patterns; indicative of isolation by distance. [59]Clear geographic gradients and distinct regional peaks (Scandinavia, Dinaric Alps); clinal patterns evident. [60]Extensive geographic distribution with clear regional differentiation; basal branches found primarily in Iran/Turkey region. [61]
Cultural/
Demographic
Factors
Strongly associated with early Neolithic agricultural expansions; founder effects and cultural isolation restricted diversification. [62] Associated with postglacial recolonization events and subsequent demographic expansions; multiple regional founder effects created distinct branches. [63]Associated with Bronze Age Indo-European migrations; rapid expansions from small founder populations allowed clear substructure development [64] .

Limitations Associated with the Use and Interpretation of Y-DNA Phylogenetic Trees

The reconstruction of Y-DNA phylogenetic trees has revolutionized our understanding of paternal lineage evolution, population migrations, and historical demographic processes. However, these analyses are constrained by several technical, methodological, and biological limitations. Y-DNA phylogenies must be interpreted with caution, acknowledging their inherent uncertainties and contextualizing findings within broader genomic and historical frameworks.

Key challenges include variability in mutation rates across haplogroups, biases in sequencing and sampling, limitations of analytical models, and the inherent complexities of the Y chromosome’s non-recombining structure. Additionally, factors such as homoplasy in short tandem repeats (STRs) [65] , evolving nomenclature systems, and population-specific historical events further complicate the interpretation of Y-DNA phylogenies. 

A foundational assumption in Y-DNA phylogenetic dating is that mutation rates remain constant across lineages. However, empirical evidence demonstrates significant inter-haplogroup variation in mutation rates. For instance, studies analyzing whole-genome sequences from over 1,700 males revealed up to an 83 percent difference in somatic mutation rates between haplogroups, correlating with phylogenetic branch length heterogeneity. [66] These discrepancies distort time to most recent common ancestor (TMRCA) estimates, as branches with slower mutation rates appear artificially elongated, while rapidly mutating lineages seem younger than their true age. [67]

The reliance on “evolutionary rates” derived from population data or pedigree studies introduces additional uncertainty. [68] This is exacerbated by the tendency of certain STRs to undergo backmutations, which obscure true phylogenetic relationships and inflate TMRCA estimates. [69]

Most Y-DNA data derive from modern populations, with limited ancient DNA representation. This temporal gap complicates efforts to resolve historical migration events or validate putative branching orders. For example, the coalescence time of R1a-M417 (approiximately 5,800 years ago) relies heavily on modern sequences, which may not capture extinct subclades that diversified during the Neolithic or Bronze Age. [70] This may be the case with many of the haplogrous associated with the Griff(is)(es)(ith) patrlineal genetic line.

Source:

Feature Banner: The banner at the top of the story is a portrayal of two phylogenetic trees that depict portions of the G haplogroup migratory route for my terminal haplogroup in Wales.

The phylogenetic tree on the left hand side reflects the phylogenetic tree of Haplogroup G2a-L140. The haplgroup G2a-L140 is most commonly found in Europe, particularly in northern and western regions. The haplogroup is believed to have entered Europe during the Neolithic period, associated with the spread of agriculture. The upstream mutations include M201 > L89 > P15 > L1259 > L30 > L141 > P303 > L140. See Hay, Maciamo, Phylogeny of G2a, Haplogroup G2a, July 2023, Eupedia, https://www.eupedia.com/europe/Haplogroup_G2a_Y-DNA.shtml

The hylogenetic tree on the right is a continuation of the haplogroups linked from one of the common ancestors associated with haplogroup G-Y8903 / FGC477 that is indicated in the phylogenetic tree on the left. The descendant asociated with this haplogroup was born around 2250 BCE. The tree on the right is based on YDNA FamilyTreeDNA test kit results. Names that appear on this chart indicate persons whose YDNA testing results identified a new branch. These SNP branches are hundreds or thousands of years old and each may  include many other surnames besides those shown in the chart. Source: Rolf Langland and Mauricio Catelli, Haplogroup G –L497 Chart D: FGC477 Branch, 30 Jan 2025, https://drive.google.com/file/d/1iizSCGkw_8x2cAqm2Evv-b_ZSxY40E1j/view

It is noted that my Y-700 DNA test results identified a new branch, as reflected in the phylogenetic tree. Click here for larger version of the banner image

[1] Zou Y, Zhang Z, Zeng Y, Hu H, Hao Y, Huang S, Li B. Common Methods for Phylogenetic Tree Construction and Their Implementation in R. Bioengineering (Basel). 2024 May 11;11(5):480. doi: 10.3390/bioengineering11050480. PMID: 38790347; PMCID: PMC11117635, https://pmc.ncbi.nlm.nih.gov/articles/PMC11117635/

Understanding phylogenies, Understanding Evolution, Evolution 101, University of California Berkley https://evolution.berkeley.edu/evolution-101/the-history-of-life-looking-at-the-patterns/understanding-phylogenies/

Phylogenetic tree, Wikipedia, This page was last edited on 26 February 2025, https://en.wikipedia.org/wiki/Phylogenetic_tree

Boudreau, Sarah, What’s the difference between a cladogram and a phylogenetic tree?, 28 Apr 2023, Visible Body, https://www.visiblebody.com/blog/phylogenetic-trees-cladograms-and-how-to-read-them

[2] Big Y-700: The Forefront of y Chromosome, 7 Jun 2019, FamilyTreeDNA Blog, https://blog.familytreedna.com/human-y-chromosome-testing-milestones/

Caleb Davis, Michael Sager, Göran Runfeldt, Elliott Greenspan, Arjan Bormans, Bennett Greenspan, and Connie Bormans, Big Y-700 White Paper, 22 Mar 2019, https://blog.familytreedna.com/wp-content/uploads/2019/03/big-y-700-white-paper_compressed.pdf

[3] A most recent common ancestor (MRCA) is the closest individual from whom all members of a specified group of people are directly descended. In genetic genealogy, this concept applies to both biological organisms and groups of genes (haplotypes).

Estes, Roberta, What Does MCRA (MRCA) Really Mean??, 6 Aug 2012, DNAeXplained – Genetic Genealogy, https://dna-explained.com/2012/08/06/what-does-mcra-really-mean/

Most recent common ancestor, International Society of Genetic Genealogy Wiki, This page was last edited on 31 January 2017,https://isogg.org/wiki/Most_recent_common_ancestor

Most common recent ancestor, Wikipedia, This page was last edited on 12 February 2025, https://en.wikipedia.org/wiki/Most_recent_common_ancestor

[4] Spencer, Rob, Data Source and SNP Dates, Discussion, SNP Tracker, https://scaledinnovation.com/gg/snpTracker.html

Batini, C., Hallast, P., Zadik, D., Maisano Delser, P., Benazzo, A., Ghirotto, S., Arroyo-Pardo, E., Cavalleri, G.L., de Knijff, P., Myhre Dupuy, B., Eriksen, H.A, King, T.E., López de Munain, A., López-Parra, A.M., Loutradis, A., Milasin, J., Novelletto, A., Pamjav, H., Sajantila, A., Tolun, A., Winney, B., and JOBLING, M.A. (2015) Large-scale recent expansion of European patrilineages shown by population resequencing. Nature Comm., 6, 7152. doi:10.1038/ncomms8152, (PubMed) https://pubmed.ncbi.nlm.nih.gov/25988751/

Hallast, P., Batini, C., Zadik, D., Maisano Delser, P., Wetton, J.H., Arroyo-Pardo, E., Cavalleri, G.L., de Knijff, P., Destro Bisol, G., Myhre Dupuy, B., Eriksen, H.A, Jorde, L.B., King, T.E., Larmuseau, M.H., López de Munain, A., López-Parra, A.M., Loutradis, A., Milasin, J., Novelletto, A., Pamjav, H., Sajantila, A., Schempp, W., Sears, M., Tolun, A., Tyler-Smith, Van Geystelen, A., Watkins, S., Winney, B., and JOBLING, M.A. (2015) The Y-chromosome tree bursts into leaf: 13,000 high-confidence SNPs covering the majority of known clades. Mol. Biol. Evol., 32, 661–673. doi: 10.1093/molbev/msu327 , (PubMed). https://pubmed.ncbi.nlm.nih.gov/25988751/

Zeng, T.C., Aw, A.J. and Feldman, M.W., 2018. Cultural hitchhiking and competition between patrilineal kin groups explain the post-Neolithic Y-chromosome bottleneck. Nature communications, 9(1), p.2077.

[5] Violatti, Christian Neolithic Period , World History Encyclopedia, 2 Apr 2018  https://www.worldhistory.org/Neolithic/

[6] Zeng, T.C., Aw, A.J. & Feldman, M.W. Cultural hitchhiking and competition between patrilineal kin groups explain the post-Neolithic Y-chromosome bottleneck. Nat Commun 9, 2077 (2018), page1, https://doi.org/10.1038/s41467-018-04375-6

[7] Ibid

[8] Miller, Mark, Most European Men are Descended from just Three Bronze Age Warlords, New Study Reveals, 25 may 2015, Ancient Origins, https://www.ancient-origins.net/news-evolution-human-origins/most-european-men-are-descended-just-three-bronze-age-warlords-new-020361

Batini, C., Hallast, P., Zadik, D. et al. Large-scale recent expansion of European patrilineages shown by population resequencing. Nat Commun 6, 7152 (2015). https://doi.org/10.1038/ncomms8152

[9] Abrams, Joel, A handful of Bronze-Age men could have fathered two thirds of Europeans, 21 May 2015, The Conversation, https://theconversation.com/a-handful-of-bronze-age-men-could-have-fathered-two-thirds-of-europeans-42079

Curry, Andrew, The First Europeans Weren’t Who Your Might Think, National Geographic Magazine, August 2019, online: https://www.nationalgeographic.com/culture/article/first-europeans-immigrants-genetic-testing-feature

[10] Hay, Maciamo, Phylogenetic trees of Y-chromosomal haplogroups, May 2017, Eupedia, https://www.eupedia.com/genetics/phylogenetic_trees_Y-DNA_haplogroups.shtml

Curry, Andrew, The First Europeans Weren’t Who Your Might Think, National Geographic Magazine, August 2019, online: https://www.nationalgeographic.com/culture/article/first-europeans-immigrants-genetic-testing-feature

Howard III, William and Frederic R. Schwab, Dating Y-DNA Haplotypes on a Phylogentic Tree: Tying the Genealogy of Pedigrees and Surname Clusters into Genetic Time Scales, Journal of Genetic Genealogy, Volume 7, Number 1 (Fall 2011) Reference Number: 71.005, https://jogg.info/wp-content/uploads/2021/09/71.005.pdf

[11] The animation was produced by a FamilyTreeDNA (FTDNA) online program called Globetrekker TM. It is a specialized mapping tool developed by FTDNA as an exclusive feature for their Big Y-DNA test customers. It visualizes ancestral migration paths on a global scale, tracing paternal lineage journeys from “Y-Adam” (the earliest common paternal ancestor, approximately 200,000 years ago) to the most recent known locations of direct paternal ancestors. Globetrekker employs phylogenetic algorithms that factor in geographical topography, historical sea levels, land elevations, and ice age glaciation patterns to determine likely ancestral migration routes.

The following are key features of the Globetrekker program:

Integrated Phylogenetic Tree Browser: An integrated tree browser allows the use to view specific migratory paths based on a chosen terminal haplogroup.

Extensive Data: Globetrekker utilizes the largest Y-DNA tree and a comprehensive database of high-resolution DNA samples, including detailed paternal ancestral information.

Advanced Algorithms: It employs sophisticated phylogenetic algorithms that incorporate topographical data, historical global sea levels, land elevation, and ice age glaciation to accurately reconstruct ancient migration routes.

Historical Maps: The tool provides interactive world maps depicting ancient sea levels and landforms, such as Doggerland during the Last Glacial Maximum.

Personalized Animation: Users receive a customized animation illustrating 200,000 years of their paternal lineage history.

Extensive Migration Paths: Globetrekker currently includes over 48,000 paternal line migration paths covering every populated continent, with new paths regularly added.

Globetrekker’s main limitation is the relatively small number of available Big Y-DNA samples. As more individuals participate in Big Y testing, the accuracy and granularity of migration paths are expected to improve significantly over time. The video is based on the migration mapping for the terminal haplogroup for G-Y132505.

Estes, Roberta, Globetrekker – A New Feature for Big Y Customers from FamilyTreeDNA, 4 Aug 2023, DNAeXplained – Genetic Genealogy, https://dna-explained.com/2023/08/04/globetrekker-a-new-feature-for-big-y-customers-from-familytreedna/

Runfeldt, Goran , Globertrekker, Part 1: A NewFamilyTreeDNA Discover™ Report that Puts Big Y on the Map, 31 Jul 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-discover-report/

Maier, Paul, Globetrekker, Part 2: Advancing the Science of Phylogeography, 15 Aug 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-analysis/

Vilar, Miguel, Globetrekker, Part 3: We Are Making History, 26 Sep 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-history/

[12] Doggerland was a vast landmass that once connected the British Isles to mainland Europe, encompassing areas now submerged beneath the North Sea and the English Channel. Named after Dogger Bank, a submerged sandbank frequented by Dutch fishing vessels known as “doggers,” Doggerland existed primarily during the Late Pleistocene and Early Holocene periods, approximately 10,000 to 6,500 years ago.

Click for Larger View | Source: Continental Europe above sea level, Europe’s Lost Frontiers, Universtiy of Bradford, https://www.bradford.ac.uk/archaeological-forensic-sciences/research/europes-lost-frontiers/

Doggerland, Wikipedia, This page was last edited on 10 March 2025, https://en.wikipedia.org/wiki/Doggerland

James Walker, Vincent Gaffney, Simon Fitch, Merle Muru, Andrew Fraser, Martin Bates and Richard Bates, A great wave: the Storegga tsunami and the end of Doggerland?, Antiquity , Volume 94 , Issue 378 , December 2020 , pp. 1409 – 1425 DOI: https://doi.org/10.15184/aqy.2020.49 , https://www.cambridge.org/core/journals/antiquity/article/great-wave-the-storegga-tsunami-and-the-end-of-doggerland/CB2E132445086D868BF508041CC1B827#article

Urbanus, Jason, Mapping a Vanished Landscape, Archaelogy magazine, March/April 2022, https://archaeology.org/issues/march-april-2022/letters-from/doggerland-mesolithic-submerged-landscape/ 

De Abreu, Kristine, Exploration Mysteries: Doggerland, 13 Feb 2024, Explorersweb, https://explorersweb.com/exploration-mysteries-doggerland/

[13] Balaresque P, Bowden GR, Adams SM, Leung HY, King TE, Rosser ZH, Goodwin J, Moisan JP, Richard C, Millward A, Demaine AG, Barbujani G, Previderè C, Wilson IJ, Tyler-Smith C, Jobling MA. A predominantly neolithic origin for European paternal lineages. PLoS Biol. 2010 Jan 19;8(1):e1000285. doi: 10.1371/journal.pbio.1000285. PMID: 20087410; PMCID: PMC2799514, PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC8228294/

Semino O, Magri C, Benuzzi G, Lin AA, Al-Zahery N, Battaglia V, Maccioni L, Triantaphyllidis C, Shen P, Oefner PJ, Zhivotovsky LA, King R, Torroni A, Cavalli-Sforza LL, Underhill PA, Santachiara-Benerecetti AS. Origin, diffusion, and differentiation of Y-chromosome haplogroups E and J: inferences on the neolithization of Europe and later migratory events in the Mediterranean area. Am J Hum Genet. 2004 May;74(5):1023-34. doi: 10.1086/386295. Epub 2004 Apr 6. PMID: 15069642; PMCID: PMC1181965, (PubMed)https://pmc.ncbi.nlm.nih.gov/articles/PMC1181965

Genetic history of Europe, Wikipedia, This page was last edited on 24 February 2025, https://en.wikipedia.org/wiki/Genetic_history_of_Europe

Rootsi, S., Myres, N., Lin, A. et al. Distinguishing the co-ancestries of haplogroup G Y-chromosomes in the populations of Europe and the Caucasus. Eur J Hum Genet 20, 1275–1282 (2012). https://doi.org/10.1038/ejhg.2012.86

E.K. Khusnutdinova, N.V. Ekomasova, M.A. Dzhaubermezov, L.R. Gabidullina, Z.R. Sufianova1, I.M. Khidiyatova, A.V. Kazantseva, S.S. Litvinov, A.Kh. Nurgalieva, D.S. Prokofieva, Distribution of Haplogroup G-P15 of the Y-chromosome Among Representatives of Ancient cultures and Modern Populations of Northern Eurasia, Opera Med Physiol. 2023. Vol. 10 (4), 57-72, doi: 10.24412/2500-2295-2023-4-57-72, https://operamedphys.org/system/tdf/pdf/06_DISTRIBUTION%20OF%20HAPLOGROUP%20G-P15_0.pdf?file=1&type=node&id=555&force=0

Maciamo, Hay, Phylogeny of G2a, Haplogroup G2a, July 2023, Eupedia, https://www.eupedia.com/europe/Haplogroup_G2a_Y-DNA.shtml

[14] The Neolithic agricultural expansion, also known as the Neolithic Revolution, was a pivotal period in human history marked by the transition from hunter-gatherer lifestyles to settled agricultural communities, starting around 10,000 years ago.  Agricultural and husbandry practices originated 10,000 years ago in a region of the Near East known as the Fertile Crescent. According to the archaeological record this phenomenon, known as “Neolithic”, rapidly expanded from these territories into Europe.

Main Archaeological Sites of the Pre-Pottery Neolithic period, BCE c. 7500, in the “Fertile Crescent”

Click for Larger View | Source: Translation added to Bjoertvedt, Fertile crescent Neolithic B circa 7500 BC, 8 Aug 2008, Wikimedia Commons, https://commons.wikimedia.org/wiki/File:Fertile_Crescent_7500_BC_NOR.PNG

Source: Neolithic Revolution, Wikipedia, This page was last edited on 1 March 2025, https://en.wikipedia.org/wiki/Neolithic_Revolution

Mesolithic Tribes and the Origins of Agriculture in the Near East (9000-7000 BCE)

Click for Larger View | Source: Hay, Maciamo, Mesolithic tribes and the origins of agriculture in the Near East (9000-7000 BCE), Nov 2015, Maps of Neolithic & Bronze Age migrations around Europe, Eupedia, https://www.eupedia.com/europe/neolithic_europe_map.shtml

[15] Neolithic, Wikipedia, This page was last edited on 18 March 2025, https://en.wikipedia.org/wiki/Neolithic

[16] Ancient DNA from the Treilles group in southern France (c. 3000 BCE) revealed that nintey percent of male remains belonged to G2a, with mitochondrial DNA (mtDNA) showing affinity to Neolithic Aegean populations. This genetic profile supports a maritime migration route linking Anatolia to Iberia via Crete and the Adriatic. Notably, the absence of the N1a mtDNA haplogroup—common in Central European Neolithic groups—in Treilles samples underscores the genetic distinctiveness of Mediterranean versus Danubian Neolithic expansions.

M. Lacan, C. Keyser, F. Ricaut, N. Brucato, F. Duranthon, J. Guilaine, E. Crubézy, & B. Ludes, Ancient DNA reveals male diffusion through the Neolithic Mediterranean route, Proc. Natl. Acad. Sci. U.S.A. 108 (24) 9788-9791,https://doi.org/10.1073/pnas.1100723108 (2011)

Fort, J., Pérez-Losada, J. Interbreeding between farmers and hunter-gatherers along the inland and Mediterranean routes of Neolithic spread in Europe. Nat Commun 15, 7032 (2024). https://doi.org/10.1038/s41467-024-51335-4

Anna Szécsényi-Nagy , Guido Brandt , Wolfgang Haak , Victoria Keerl , János Jakucs , Sabine Möller-Rieker , Kitti Köhler , Balázs Gusztáv Mende , Krisztián Oross , Tibor Marton , Anett Osztás , Viktória Kiss , Marc Fecher , György Pálfi , Erika Molnár , et al, Tracing the genetic origin of Europe’s first farmers reveals insights into their social organization, 22 Apr 2015, Volume 282, Issue 1805, Proceedings of the royal Society Biological Sciences, https://royalsocietypublishing.org/doi/10.1098/rspb.2015.0339

[17] Fort, J., Pérez-Losada, J. Interbreeding between farmers and hunter-gatherers along the inland and Mediterranean routes of Neolithic spread in Europe. Nat Commun 15, 7032 (2024). https://doi.org/10.1038/s41467-024-51335-4

Anna Szécsényi-Nagy , Guido Brandt , Wolfgang Haak , Victoria Keerl , János Jakucs , Sabine Möller-Rieker , Kitti Köhler , Balázs Gusztáv Mende , Krisztián Oross , Tibor Marton , Anett Osztás , Viktória Kiss , Marc Fecher , György Pálfi , Erika Molnár , et al, Tracing the genetic origin of Europe’s first farmers reveals insights into their social organization, 22 Apr 2015, Volume 282, Issue 1805, Proceedings of the royal Society Biological Sciences, https://royalsocietypublishing.org/doi/10.1098/rspb.2015.0339

Myres NM, Rootsi S, Lin AA, Järve M, King RJ, Kutuev I, Cabrera VM, Khusnutdinova EK, Pshenichnov A, Yunusbayev B, Balanovsky O, Balanovska E, Rudan P, Baldovic M, Herrera RJ, Chiaroni J, Di Cristofaro J, Villems R, Kivisild T, Underhill PA. A major Y-chromosome haplogroup R1b Holocene era founder effect in Central and Western Europe. Eur J Hum Genet. 2011 Jan;19(1):95-101. doi: 10.1038/ejhg.2010.146. Epub 2010 Aug 25. PMID: 20736979; PMCID: PMC3039512, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC3039512/

[18] Szécsényi-Nagy A, Brandt G, Haak W, Keerl V, Jakucs J, Möller-Rieker S, Köhler K, Mende BG, Oross K, Marton T, Osztás A, Kiss V, Fecher M, Pálfi G, Molnár E, Sebők K, Czene A, Paluch T, Šlaus M, Novak M, Pećina-Šlaus N, Ősz B, Voicsek V, Somogyi K, Tóth G, Kromer B, Bánffy E, Alt KW. Tracing the genetic origin of Europe’s first farmers reveals insights into their social organization. Proc Biol Sci. 2015 Apr 22;282(1805):20150339. doi: 10.1098/rspb.2015.0339. PMID: 25808890; PMCID: PMC4389623, PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC4389623/

[19] Myres NM, Rootsi S, Lin AA, Järve M, King RJ, Kutuev I, Cabrera VM, Khusnutdinova EK, Pshenichnov A, Yunusbayev B, Balanovsky O, Balanovska E, Rudan P, Baldovic M, Herrera RJ, Chiaroni J, Di Cristofaro J, Villems R, Kivisild T, Underhill PA. A major Y-chromosome haplogroup R1b Holocene era founder effect in Central and Western Europe. Eur J Hum Genet. 2011 Jan;19(1):95-101. doi: 10.1038/ejhg.2010.146. Epub 2010 Aug 25. PMID: 20736979; PMCID: PMC3039512, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC3039512/

Hay, Maciamo, Haplogroup G2a (Y-DNA), July 2023, Eupeda, https://www.eupedia.com/europe/Haplogroup_G2a_Y-DNA.shtml

[20] Chiaroni J, Underhill PA, Cavalli-Sforza LL. Y chromosome diversity, human expansion, drift, and cultural evolution. Proc Natl Acad Sci U S A. 2009 Dec 1;106(48):20174-9. doi: 10.1073/pnas.0910803106. Epub 2009 Nov 17. Erratum in: Proc Natl Acad Sci U S A. 2010 Jul 27;107(30):13556. PMID: 19920170; PMCID: PMC2787129, PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC2787129/

Myres NM, Rootsi S, Lin AA, et al, A major Y-chromosome haplogroup R1b Holocene era founder effect in Central and Western Europe. Eur J Hum Genet. 2011 Jan;19(1):95-101. doi: 10.1038/ejhg.2010.146. Epub 2010 Aug 25. PMID: 20736979; PMCID: PMC3039512, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC3039512/

[21] Penske, S., Rohrlach, A.B., Childebayeva, A. et al. Early contact between late farming and pastoralist societies in southeastern Europe. Nature 620, 358–365 (2023). https://doi.org/10.1038/s41586-023-06334-8

Haak W, Lazaridis I, Patterson N, Rohland N, Mallick S, Llamas B, Brandt G, Nordenfelt S, Harney E, Stewardson K, Fu Q, Mittnik A, Bánffy E, Economou C, Francken M, Friederich S, Pena RG, Hallgren F, Khartanovich V, Khokhlov A, Kunst M, Kuznetsov P, Meller H, Mochalov O, Moiseyev V, Nicklisch N, Pichler SL, Risch R, Rojo Guerra MA, Roth C, Szécsényi-Nagy A, Wahl J, Meyer M, Krause J, Brown D, Anthony D, Cooper A, Alt KW, Reich D. Massive migration from the steppe was a source for Indo-European languages in Europe. Nature. 2015 Jun 11;522(7555):207-11. doi: 10.1038/nature14317. Epub 2015 Mar 2. PMID: 25731166; PMCID: PMC5048219, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC5048219/

[22] Hay, Maciamo, Haplogroup G2a (Y-DNA), Jul 2023,  Eupedia, https://www.eupedia.com/europe/Haplogroup_G2a_Y-DNA.shtml

Lamnidis, T.C., Majander, K., Jeong, C. et al. Ancient Fennoscandian genomes reveal origin and spread of Siberian ancestry in Europe. Nat Commun 9, 5018 (2018). https://doi.org/10.1038/s41467-018-07483-5

[23] Hay, Maciamo, Phylogenetic trees of Y-chromosomal haplogroups, May 2017, Eupedia, https://www.eupedia.com/genetics/phylogenetic_trees_Y-DNA_haplogroups.shtml#IntroductionHuman Y-chromosome DNA haplogroup, Wikipedia, This page was last edited on 31 December 2024, https://en.wikipedia.org/wiki/Human_Y-chromosome_DNA_haplogroup

Dunn, Casey W., Chapter 9 Phylogenies and time, Phylogenetic Biology, 28 Oct 2024, Text for course, Phylogenetic Biology (Yale EEB354), licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. It is available to read online for free at https://dunnlab.org/phylogenetic_biology/phylogenies.html#trees-branch-lengths

Hay, Maciamo, Phylogenetic trees of Y-chromosomal haplogroups, May 2017, Eupedia, https://www.eupedia.com/genetics/phylogenetic_trees_Y-DNA_haplogroups.shtml#Introduction

[24] Batini, C., Hallast, P., Zadik, D. et al. Large-scale recent expansion of European patrilineages shown by population resequencing. Nat Commun 6, 7152 (2015). https://doi.org/10.1038/ncomms8152

[25] Hay, Maciamo, Phylogenetic trees of Y-chromosomal haplogroups, May 2017, Eupedia, https://www.eupedia.com/genetics/phylogenetic_trees_Y-DNA_haplogroups.shtml#IntroductionHuman Y-chromosome DNA haplogroup, Wikipedia, This page was last edited on 31 December 2024, https://en.wikipedia.org/wiki/Human_Y-chromosome_DNA_haplogroup

[26] These estimates derive from large-scale sequencing datasets, pedigree studies, and comparative analyses of haplogroup differentiations. Key factors influencing this range include the coverage of the male-specific Y chromosome (MSY) region, the mutation rate per base pair, and the statistical models used to account for uncertainties in SNP counting and temporal calibration. [26a]

Mutation rate estimates differ across sequencing technologies. There are three notable testing platforms. The FamilyTreeDNA (FTDNA) Big Y-700 test analyzes approximately 14.6 million base pairs, yielding an average mutation rate of 83–85 years per SNP. This estimate, derived from YDNA Warehouse data, reflects high-coverage regions deemed reliable for genealogical applications. [26b] The FTDNA BigY-500 test covers 9.3 million base pairs, resulting in a slower rate of 131 years per SNP due to reduced coverage compared to BigY-700. [26c] The YFull (ComBed) coverage test uses 8.5 million base pairs and reports 144 years per SNP, prioritizing conservative regions (comBED) to minimize false positives. [26d] 

Based on academic and ‘consensus’ estimates, evolutionary rates, calibrated using ancient DNA or historical events, suggest 0.75–0.89 substitutions per billion base pairs per year (equivalent to 83–89 years/SNP for typical sequencing lengths). Genealogical (pedigree) rates, observed in father-son studies, are slightly faster due to shorter generational intervals. Iain McDonald’s analysis of 15 million base pairs estimates 83–186 years per SNP, with higher values reflecting conservative adjustments for regions with variable coverage. [26e] 

[26a] Irvine, James M., Y-DNA SNP-Based TMRCA Calculations for Surname Project Administrators, Journal of Genetic Genealogy, Volume 9, Number 1 (Fall 2021), Reference Number: 91.007, https://jogg.info/wp-content/uploads/2021/12/91.007-Article.pdf

SNP Dating, Genomic Genealogy Research, University of Strathclyde Glasgow, https://www.strath.ac.uk/studywithus/centreforlifelonglearning/genealogy/geneticgenealogyresearch/snpdating/

Balanovsky O. Toward a consensus on SNP and STR mutation rates on the human Y-chromosome. Hum Genet. 2017 May;136(5):575-590. doi: 10.1007/s00439-017-1805-8. Epub 2017 Apr 28. PMID: 28455625, (PubMed) https://pubmed.ncbi.nlm.nih.gov/28455625/

[26b] SNP Dating, Genomic Genealogy Research, University of Strathclyde Glasgow, https://www.strath.ac.uk/studywithus/centreforlifelonglearning/genealogy/geneticgenealogyresearch/snpdating/

[26c] McDonald, Ian, SNP-based age analysis methodology: a summary

Summarised description of the age analysis pipeline, June 2017, https://www.jb.man.ac.uk/~mcdonald/genetics/pipeline-summary.pdf

[26d] Ibid

[26e] Balanovsky O. Toward a consensus on SNP and STR mutation rates on the human Y-chromosome. Hum Genet. 2017 May;136(5):575-590. doi: 10.1007/s00439-017-1805-8. Epub 2017 Apr 28. PMID: 28455625, (PubMed) https://pubmed.ncbi.nlm.nih.gov/28455625/

McDonald, Ian, SNP-based age analysis methodology: a summary, Summarised description of the age analysis pipeline, June 2017, https://www.jb.man.ac.uk/~mcdonald/genetics/pipeline-summary.pdf

[27] The interpretation of branch lengths depends heavily on mutation rate calculations. The standard deviation in branch lengths from high-coverage sequences is relatively low (around 4 percent). This allows for precise temporal estimates. High-coverage DNA sequencing has identified mutation rates of approximately 2-3 base pairs per generation.

Jeanson, Nathaniel, 4 Dec, 2019, Answers Research Journal (ARJ), 12: 405-423, https://answersresearchjournal.org/human-y-chromosome-molecular-clock/

There is ongoing disagreement about the temporal interpretation of Y-chromosome branch lengths. Some researchers argue for a longer timescale of 120-156 thousand years to the most recent common ancestor while others propose much shorter timescales of just a few thousand years. See:

Jeanson, Nathaniel, 4 Dec, 2019, Answers Research Journal (ARJ), 12: 405-423, https://answersresearchjournal.org/human-y-chromosome-molecular-clock/

Poznik GD, Henn BM, Yee MC, Sliwerska E, Euskirchen GM, Lin AA, Snyder M, Quintana-Murci L, Kidd JM, Underhill PA, Bustamante CD. Sequencing Y chromosomes resolves discrepancy in time to common ancestor of males versus females. Science. 2013 Aug 2;341(6145):562-5. doi: 10.1126/science.1237619. PMID: 23908239; PMCID: PMC4032117, https://pmc.ncbi.nlm.nih.gov/articles/PMC4032117/

[28] Dunn, Casey W., Chapter 9 Phylogenies and time, Phylogenetic Biology, 28 Oct 2024, Text for course, Phylogenetic Biology (Yale EEB354), licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. It is available to read online for free at http://dunnlab.org/phylogenetic_biology/

[29] Poznik GD, et al, Sequencing Y chromosomes resolves discrepancy in time to common ancestor of males versus females. Science. 2013 Aug 2;341(6145):562-5. doi: 10.1126/science.1237619. PMID: 23908239; PMCID: PMC4032117, https://pmc.ncbi.nlm.nih.gov/articles/PMC4032117/

[30] Cruciani F, Trombetta B, Massaia A, Destro-Bisol G, Sellitto D, Scozzari R. A revised root for the human Y chromosomal phylogenetic tree: the origin of patrilineal diversity in Africa. Am J Hum Genet. 2011 Jun 10;88(6):814-818. doi: 10.1016/j.ajhg.2011.05.002. Epub 2011 May 27. PMID: 21601174; PMCID: PMC3113241, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC3113241/

[31] Y Chromosome Consortium. A nomenclature system for the tree of human Y-chromosomal binary haplogroups. Genome Res. 2002 Feb;12(2):339-48. doi: 10.1101/gr.217602. PMID: 11827954; PMCID: PMC155271, 9PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC155271/

Human Y-chromosome DNA haplogroup, Wikipedia, This page was last edited on 31 December 2024, https://en.wikipedia.org/wiki/Human_Y-chromosome_DNA_haplogroup

[32] Hay, Maciamo, Phylogenetic trees of Y-chromosomal haplogroups, May 2017, Eupedia, https://www.eupedia.com/genetics/phylogenetic_trees_Y-DNA_haplogroups.shtml#Introduction

[33] Tunde I. Huszar, Mark A. Jobling, Jon H. Wetton,
A phylogenetic framework facilitates Y-STR variant discovery and classification via massively parallel sequencing, Forensic Science International: Genetics, Volume 35, 2018, Pages 97-106, ISSN 1872-4973, https://doi.org/10.1016/j.fsigen.2018.03.012.
(https://www.sciencedirect.com/science/article/pii/S1872497318300279 )

Phylogenetics, Wikipedia, This page was last edited on 12 February 2025,  https://en.wikipedia.org/wiki/Phylogenetics

[34] Rowe-Schurwanz, Katy, How Y-DNA Testing Works, 3 Jun 2024, FamilyTreeDNA Blog, https://blog.familytreedna.com/how-y-dna-testing-works/

Y chromosome DNA tests, International Society of Genetic Genealogy Wiki, This page was last edited on 6 September 2024, https://isogg.org/wiki/Y_chromosome_DNA_tests

[35] William E. Howard III and Frederic R. Schwab, Dating Y-DNA Haplotypes on a Phylogenetic Tree: Tying the Genealogy of Pedgrees and Surname Clusters into Genetic Time  Scales, Journal of Genetic Genealogy, Volume 7, Number 1 (Fall 2011) Reference Number: 71.005, https://jogg.info/wp-content/uploads/2021/09/71.005.pdf

Köksal Z, Børsting C, Gusmão L, Pereira V. SNPtotree-Resolving the Phylogeny of SNPs on Non-Recombining DNA. Genes (Basel). 2023 Sep 22;14(10):1837. doi: 10.3390/genes14101837. PMID: 37895186; PMCID: PMC10606150, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC10606150/

Tunde I. Huszar, Mark A. Jobling, Jon H. Wetton, A phylogenetic framework facilitates Y-STR variant discovery and classification via massively parallel sequencing, Forensic Science International: Genetics, Volume 35, 2018, Pages 97-106, ISSN 1872-4973,
https://doi.org/10.1016/j.fsigen.2018.03.012

Hay, Maciamo, Phylogenetic trees of Y-chromosomal haplogroups, May 2017, Eupedia, https://www.eupedia.com/genetics/phylogenetic_trees_Y-DNA_haplogroups.shtml 

[36] Determination of MRCA Dates”

Calculation Models: The coalescence age (time to MRCA) is calculated using probabilistic models that consider the number of mutations and the mutation rate. These models can be refined with more data and improved algorithms 14.

Mutation Rate: The process relies on the concept of a’ molecular clock’, which assumes that mutations occur at a relatively constant rate over time. This rate is typically measured in mutations per base pair per year. For Y-DNA, mutations are often counted as Single Nucleotide Polymorphisms (SNPs) 12.

SNP Counting: Full Y-DNA sequencing tests, such as those from Full Genomes Corp. or FamilyTreeDNA’s Big Y, identify novel SNPs. The number of these SNPs, combined with the mutation rate, helps estimate the time to the MRCA. Different tests may yield different mutation rates; for example, Full Genomes Corp. suggests a mutation every 88 years, while Big Y suggests one every 150 years2.

McDonald Ian. Improved Models of Coalescence Ages of Y-DNA Haplogroups. Genes (Basel). 2021 Jun 4;12(6):862. doi: 10.3390/genes12060862. PMID: 34200049; PMCID: PMC8228294, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC8228294/

Irvine, James M., Y-DNA SNP-Based TMRCA Calculations for Surname Project Administrators, Journal of Genetic Genealogy, Volume 9, Number 1 (Fall 2021), Reference Number: 91.007, https://jogg.info/wp-content/uploads/2021/12/91.007-Article.pdf

FamilyTreeDNA Enhances TMRCA Estimates for Improved Family History Research, 9 Sep 2022, FamilyTreeDNA Blog, https://blog.familytreedna.com/tmrca-age-estimates-update/

Walsh B. Estimating the time to the most recent common ancestor for the Y chromosome or mitochondrial DNA for a pair of individuals. Genetics. 2001 Jun;158(2):897-912. doi: 10.1093/genetics/158.2.897. PMID: 11404350; PMCID: PMC1461668, https://pmc.ncbi.nlm.nih.gov/articles/PMC1461668/

Cummings, Karen, Y-DNA: New Tools from FamilyTreeDNA, Professional family History, https://www.professionalfamilyhistory.co.uk/blog/new-y-dna-new-tools-from-familytreedna

Estes, Roberta, The Big Y-700 Test Marries Science to Genealogy, 11 Jul 2024, DNAeXplained – Genetic Genealology, https://dna-explained.com/category/mrca-most-recent-common-ancestor/

Karmin M, Saag L, Vicente M, Wilson Sayres MA, et all A recent bottleneck of Y chromosome diversity coincides with a global change in culture. Genome Res. 2015 Apr;25(4):459-66. doi: 10.1101/gr.186684.114. Epub 2015 Mar 13. PMID: 25770088; PMCID: PMC4381518, https://pmc.ncbi.nlm.nih.gov/articles/PMC4381518/

Bruce Walsh, Estimating the Time to the Most Recent Common Ancestor for the Y chromosome or Mitochondrial DNA for a Pair of Individuals, Genetics, Volume 158, Issue 2, 1 June 2001, Pages 897–912, https://doi.org/10.1093/genetics/158.2.897

Qian, X., Hou, J., Wang, Z. et al. Next Generation Sequencing Plus (NGS+) with Y-chromosomal Markers for Forensic Pedigree Searches. Sci Rep 7, 11324 (2017). https://doi.org/10.1038/s41598-017-11955-x

[37] McDonald Ian. Improved Models of Coalescence Ages of Y-DNA Haplogroups. Genes (Basel). 2021 Jun 4;12(6):862. doi: 10.3390/genes12060862. PMID: 34200049; PMCID: PMC8228294, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC8228294/

[38] McDonald Ian. Improved Models of Coalescence Ages of Y-DNA Haplogroups.

Irvine, James M., Y-DNA SNP-Based TMRCA Calculations for Surname Project Administrators, Journal of Genetic Genealogy, Volume 9, Number 1 (Fall 2021), Reference Number: 91.007, https://jogg.info/wp-content/uploads/2021/12/91.007-Article.pdf

[39] Poznik GD, Henn BM, Yee MC, Sliwerska E, Euskirchen GM, Lin AA, Snyder M, Quintana-Murci L, Kidd JM, Underhill PA, Bustamante CD. Sequencing Y chromosomes resolves discrepancy in time to common ancestor of males versus females. Science. 2013 Aug 2;341(6145):562-5. doi: 10.1126/science.1237619. PMID: 23908239; PMCID: PMC4032117, https://pmc.ncbi.nlm.nih.gov/articles/PMC4032117/

McDonald Ian. Improved Models of Coalescence Ages of Y-DNA Haplogroups. Genes (Basel). 2021 Jun 4;12(6):862. doi: 10.3390/genes12060862. PMID: 34200049; PMCID: PMC8228294, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC8228294/

Irvine, James M., Y-DNA SNP-Based TMRCA Calculations for Surname Project Administrators, Journal of Genetic Genealogy, Volume 9, Number 1 (Fall 2021), Reference Number: 91.007, https://jogg.info/wp-content/uploads/2021/12/91.007-Article.pdf

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[41] Hodișan R, Zaha DC, Jurca CM, Petchesi CD, Bembea M. Genetic Diversity Based on Human Y Chromosome Analysis: A Bibliometric Review Between 2014 and 2023. Cureus. 2024 Apr 18;16(4):e58542. doi: 10.7759/cureus.58542. PMID: 38887511; PMCID: PMC11182565, PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC11182565/

[42] McDonald I. Improved Models of Coalescence Ages of Y-DNA Haplogroups. Genes (Basel). 2021 Jun 4;12(6):862. doi: 10.3390/genes12060862. PMID: 34200049; PMCID: PMC8228294

[43] Guyon, L., Guez, J., Toupance, B. et al. Patrilineal segmentary systems provide a peaceful explanation for the post-Neolithic Y-chromosome bottleneck. Nat Commun 15, 3243 (2024). https://doi.org/10.1038/s41467-024-47618-5

Karmin M, Saag L, Vicente M, Wilson Sayres MA, et all A recent bottleneck of Y chromosome diversity coincides with a global change in culture. Genome Res. 2015 Apr;25(4):459-66. doi: 10.1101/gr.186684.114. Epub 2015 Mar 13. PMID: 25770088; PMCID: PMC4381518, https://pmc.ncbi.nlm.nih.gov/articles/PMC4381518/

[44] Chiaroni J, Underhill PA, Cavalli-Sforza LL. Y chromosome diversity, human expansion, drift, and cultural evolution. Proc Natl Acad Sci U S A. 2009 Dec 1;106(48):20174-9. doi: 10.1073/pnas.0910803106. Epub 2009 Nov 17. Erratum in: Proc Natl Acad Sci U S A. 2010 Jul 27;107(30):13556. PMID: 19920170; PMCID: PMC2787129, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC2787129/

McDonald I. Improved Models of Coalescence Ages of Y-DNA Haplogroups. Genes (Basel). 2021 Jun 4;12(6):862. doi: 10.3390/genes12060862. PMID: 34200049; PMCID: PMC8228294, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC8228294/

Rootsi, S., Myres, N., Lin, A. et al. Distinguishing the co-ancestries of haplogroup G Y-chromosomes in the populations of Europe and the Caucasus. Eur J Hum Genet 20, 1275–1282 (2012). https://doi.org/10.1038/ejhg.2012.86

[45] Guyon, L., Guez, J., Toupance, B. et al. Patrilineal segmentary systems provide a peaceful explanation for the post-Neolithic Y-chromosome bottleneck. Nat Commun 15, 3243 (2024). https://doi.org/10.1038/s41467-024-47618-5

[46] Linda Hellborg, Hans Ellegren, Low Levels of Nucleotide Diversity in Mammalian Y Chromosomes, Molecular Biology and Evolution, Volume 21, Issue 1, January 2004, Pages 158–163, https://doi.org/10.1093/molbev/msh008

[47] McDonald I. Improved Models of Coalescence Ages of Y-DNA Haplogroups. Genes (Basel). 2021 Jun 4;12(6):862. doi: 10.3390/genes12060862. PMID: 34200049; PMCID: PMC8228294, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC8228294/

[48] Long branch attraction, Wikipedia, This page was last edited on 9 March 2025, https://en.wikipedia.org/wiki/Long_branch_attraction

[49] Hoelzer, Gary A. and Don J. Meinick, Patterns of speciation and limits to phylogenetic resolution, Trends in Ecology & Evolution, Volume 9, Issue 3, 1994, Pages 104-107,
https://doi.org/10.1016/0169-5347(94)90207-0 , https://www.sciencedirect.com/science/article/pii/0169534794902070

Swenson, Nathan, Phylogenetic Resolution and Quantifying the Phylogenetic Diversity and Dispersion of Communities, , PLoS ONE, February 2009, Volume 4, Issue 2, e4390, https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0004390

[50] Haplogroup G-M201, Wikipeda, This page was last edited on 24 January 2025 ,Haplogroup_G-M201

Rootsi, S., Myres, N., Lin, A. et al. Distinguishing the co-ancestries of haplogroup G Y-chromosomes in the populations of Europe and the Caucasus. Eur J Hum Genet 20, 1275–1282 (2012). https://doi.org/10.1038/ejhg.2012.86

Sims LM, Garvey D, Ballantyne J. Improved resolution haplogroup G phylogeny in the Y chromosome, revealed by a set of newly characterized SNPs. PLoS One. 2009 Jun 4;4(6):e5792. doi: 10.1371/journal.pone.0005792. PMID: 19495413; PMCID: PMC2686153

[51] Rootsi S, et al Phylogeography of Y-chromosome haplogroup I reveals distinct domains of prehistoric gene flow in europe. Am J Hum Genet. 2004 Jul;75(1):128-37. doi: 10.1086/422196. Epub 2004 May 25. PMID: 15162323; PMCID: PMC1181996, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC1181996/

[52] Underhill, P., Poznik, G., Rootsi, S. et al. The phylogenetic and geographic structure of Y-chromosome haplogroup R1a. Eur J Hum Genet 23, 124–131 (2015). https://doi.org/10.1038/ejhg.2014.50

[53] Haplogroup G-M201, Wikipeda, This page was last edited on 24 January 2025 ,Haplogroup_G-M201

Rootsi, S., Myres, N., Lin, A. et al. Distinguishing the co-ancestries of haplogroup G Y-chromosomes in the populations of Europe and the Caucasus. Eur J Hum Genet 20, 1275–1282 (2012). https://doi.org/10.1038/ejhg.2012.86

[54] Rootsi S, et al, Phylogeography of Y-chromosome haplogroup I reveals distinct domains of prehistoric gene flow in europe. Am J Hum Genet. 2004 Jul;75(1):128-37. doi: 10.1086/422196. Epub 2004 May 25. PMID: 15162323; PMCID: PMC1181996, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC1181996/

[55] Underhill, P., Poznik, G., Rootsi, S. et al. The phylogenetic and geographic structure of Y-chromosome haplogroup R1a. Eur J Hum Genet 23, 124–131 (2015). https://doi.org/10.1038/ejhg.2014.50

[56] Rootsi, S., Myres, N., Lin, A. et al. Distinguishing the co-ancestries of haplogroup G Y-chromosomes in the populations of Europe and the Caucasus. Eur J Hum Genet 20, 1275–1282 (2012). https://doi.org/10.1038/ejhg.2012.86

[57] Rootsi S, et al . Phylogeography of Y-chromosome haplogroup I reveals distinct domains of prehistoric gene flow in europe. Am J Hum Genet. 2004 Jul;75(1):128-37. doi: 10.1086/422196. Epub 2004 May 25. PMID: 15162323; PMCID: PMC1181996, PubMed)

[58] Underhill, P., Poznik, G., Rootsi, S. et al. The phylogenetic and geographic structure of Y-chromosome haplogroup R1a. Eur J Hum Genet 23, 124–131 (2015). https://doi.org/10.1038/ejhg.2014.50

[59] Haplogroup G-M201, Wikipeda, This page was last edited on 24 January 2025 ,Haplogroup_G-M201

Rootsi, S., Myres, N., Lin, A. et al. Distinguishing the co-ancestries of haplogroup G Y-chromosomes in the populations of Europe and the Caucasus. Eur J Hum Genet 20, 1275–1282 (2012). https://doi.org/10.1038/ejhg.2012.86

[60] Rootsi S, et al . Phylogeography of Y-chromosome haplogroup I reveals distinct domains of prehistoric gene flow in europe. Am J Hum Genet. 2004 Jul;75(1):128-37. doi: 10.1086/422196. Epub 2004 May 25. PMID: 15162323; PMCID: PMC1181996, PubMed)

[61] Underhill, P., Poznik, G., Rootsi, S. et al. The phylogenetic and geographic structure of Y-chromosome haplogroup R1a. Eur J Hum Genet 23, 124–131 (2015). https://doi.org/10.1038/ejhg.2014.50

[62] Rootsi, S., Myres, N., Lin, A. et al. Distinguishing the co-ancestries of haplogroup G Y-chromosomes in the populations of Europe and the Caucasus. Eur J Hum Genet 20, 1275–1282 (2012). https://doi.org/10.1038/ejhg.2012.86

Sims LM, Garvey D, Ballantyne J. Improved resolution haplogroup G phylogeny in the Y chromosome, revealed by a set of newly characterized SNPs. PLoS One. 2009 Jun 4;4(6):e5792. doi: 10.1371/journal.pone.0005792. PMID: 19495413; PMCID: PMC2686153, (PubMed) https://pmc.ncbi.nlm.nih.gov/articles/PMC2686153/

[63] Rootsi S, et al . Phylogeography of Y-chromosome haplogroup I reveals distinct domains of prehistoric gene flow in europe. Am J Hum Genet. 2004 Jul;75(1):128-37. doi: 10.1086/422196. Epub 2004 May 25. PMID: 15162323; PMCID: PMC1181996, PubMed)

[64] Underhill, P., Poznik, G., Rootsi, S. et al. The phylogenetic and geographic structure of Y-chromosome haplogroup R1a. Eur J Hum Genet 23, 124–131 (2015). https://doi.org/10.1038/ejhg.2014.50

[65] In the context of short tandem repeats (STRs), homoplasy refers to the situation where identical STR genotypes (or haplotypes) arise independently, meaning they are not necessarily inherited from a common ancestor, but rather due to repeated mutations or other processes. STRs are highly polymorphic, meaning they vary significantly between individuals, making them useful for forensic and genealogical studies. However, the high rate of mutation and the potential for homoplasy can complicate the interpretation of STR data, especially when comparing populations that diverged in the distant past.

Bret A. Payseur, Asher D. Cutter, Integrating patterns of polymorphism at SNPs and STRs, Trends in Genetics, Volume 22, Issue 8, 2006, Pages 424-429, ISSN 0168-9525, https://doi.org/10.1016/j.tig.2006.06.009, https://www.sciencedirect.com/science/article/pii/S0168952506001776

Boattini, A., Sarno, S., Mazzarisi, A.M. et al. Estimating Y-Str Mutation Rates and Tmrca Through Deep-Rooting Italian Pedigrees. Sci Rep 9, 9032 (2019). https://doi.org/10.1038/s41598-019-45398-3

[66] Qiliang Ding, Ya Hu, Amnon Koren, Andrew G Clark, Mutation Rate Variability across Human Y-Chromosome Haplogroups, Molecular Biology and Evolution, Volume 38, Issue 3, March 2021, Pages 1000–1005, https://doi.org/10.1093/molbev/msaa268

[67] Boattini, A., Sarno, S., Mazzarisi, A.M. et al. Estimating Y-Str Mutation Rates and Tmrca Through Deep-Rooting Italian Pedigrees. Sci Rep 9, 9032 (2019). https://doi.org/10.1038/s41598-019-45398-3

Qiliang Ding, Ya Hu, Amnon Koren, Andrew G Clark, Mutation Rate Variability across Human Y-Chromosome Haplogroups, Molecular Biology and Evolution, Volume 38, Issue 3, March 2021, Pages 1000–1005, https://doi.org/10.1093/molbev/msaa268

[68] Boattini, A., Sarno, S., Mazzarisi, A.M. et al. Estimating Y-Str Mutation Rates and Tmrca Through Deep-Rooting Italian Pedigrees. Sci Rep 9, 9032 (2019). https://doi.org/10.1038/s41598-019-45398-3

[69] Boattini, et al, Estimating Y-Str Mutation Rates and Tmrca Through Deep-Rooting Italian Pedigrees

[70] Underhill, P., Poznik, G., Rootsi, S. et al. The phylogenetic and geographic structure of Y-chromosome haplogroup R1a. Eur J Hum Genet 23, 124–131 (2015). https://doi.org/10.1038/ejhg.2014.50

Human Y-chromosome DNA haplogroup, Wikipedia, This page was last edited on 31 December 2024,, https://en.wikipedia.org/wiki/Human_Y-chromosome_DNA_haplogroup

The Orientation of Family Narratives Across Time Layers : Part Three

The analysis of Y-DNA or mtDNA data provides the foundation for mapping out one’s haplogroup or ‘family’ lineage in the long term and mid range time layers. Genetic genealogy is the thread of continuity in all three periods of genealogical time. However, each time layer has its unique properties and rely on predominant forms of contextual evidence to fill in a family narrative.

In order to add historical information to the analysis of Y-DNA or mtDNA evidence, the long term and mid range ancestry genealogical time layers rely on paleo-genomic and anthropological macro level sources of evidence. These two general sources of research can provide an historical background or context for interpreting DNA test results. Their respective advantages in adding meaning to a story, however, have notable limitations as well.

Each of the three layers of genealogical time rely upon different methods of gathering evidence and interpreting evidence in context of social and cultural factors. Illustration one depicts the predominant orientation in narrating family stories in each of the specific layers of genealogical time.

Illustration One: Orientation of Family Stories Based on Genealogical Time Period

The short range genealogical time period predominately relies on traditional research methods and historical sources associated with social history. Autosomal DNA tests might also be used to verify or discover family relationships within the past seven or so generations. mtDNA (mitochondrial DNA) [1] and Y-DNA tests [2] may also play a supplementary role in fleshing out evidence in the short range time layer.

The mid range genealogical time layer utilizes mtDNA and both SNP and STR Y-DNA data to discover ‘family’ haplogroups. The use of Y-STR data can provide novel discoveries of haplogroup formation when surnames emerged in Europe. As previously stated, the analysis and comparison of individual Y-STR results with other Y-STR test kit results can help delineate lineages and tease out branches within the haplotree family, fine-tuning relationships between ‘mutations’ or people within the tree. [3] The results from genetic DNA tests can be placed into an historical context in the mid range time palyer through anthropoligical and macor cultural research and paleo genetic studies.

The long term time layer relies primarily on SNP and haplogroup data. Genetic data can be interpreted through the lens of long-term, slow-moving macro level social structures, genetic demographic changes and patterns, geographical and climatic influences, and macro level cultural and anthropological history.

I have discussed the creation of family stories in the short range or traditional genealogical time layer in a prior story. This story focuses on the use of the paleo-genetic and anthropological / macro cultural orientations for providing background information when developing family stories within the mid range and long range time layers.

As discussed in prior stories, the Griff(is)(es)(ith) family surname can be traced to William Griffis who was born in Huntington, Long Island New York in 1736. He is the ‘brick wall’ in our traditional family research. Through the use of Y-DNA testing, I have been able to link the Griff(is)(es)(ith) family patrilineal genetic line through a migratory path of the G-haplogroup. I also have evidence that the patrilineal line probably came from the southern area of Wales before immigrating to the American colonies.

The Paleo-Genomic or Paleo-Genetic Orientation

In conjunction with test results from Y-DNA and mtDNA, the discoveries and accumulated research from paleogenomics provide a complimentary base of evidence to document the historical context of migratory patterns of family lineages in the earlier time periods.

Paleogenomics provides powerful insights into human migration patterns through several key analytical approaches. Ancient DNA sequencing allows researchers to directly examine genetic material from historical remains, revealing detailed information about population movements and interactions. This technique can track genetic changes across thousands of years, providing a timeline of human migrations. The ability to analyze both modern and ancient genomes helps reconstruct migration routes, genetic diversification events, and genetic admixture among various groups.

The key applications of paleogenomics for genealogy are, among others, the detection of genetic drift [4] and ancient population migrations and on the analysis of haplogroup features across geographic regions. Modern paleo-genomic techniques have allowed research scientists to reconstruct ancient ecological communities and study adaptive evolution across deep time. [5]

Paleogenomics is the science of reconstructing and analyzing genomic information from extinct species and ancient organisms. This field involves extracting and studying ancient DNA (aDNA) from various sources including museum artifacts, ice cores, archaeological sites, bones, teeth, mummified tissues, and hair. [6]

During the past decade technological advances have made it cost effective and efficiently possible to sequence the entire genome of humans who lived tens of millions of years ago. The result has been an explosion of new information that has fueled an emerging academic field of paleo-genetics or paleo-genomics that is transforming archaeology and the mapping of deep ancestry at a macroscopic level.

Illustration Two: Samples of Whole Genome Data Generated since 2010

Source: David Reich, Who We are and How We got Here, Ancient DNA and the New Science of the Human Past, New York: Vintage Books, 2018, Page xvi Click for larger view.

This technology has revolutionized the ability to decode complex biological systems. High-throughput sequencing has revolutionized the study of Y chromosome variation in ancient human DNA (aDNA). High-throughput sequencing (HTS), also known as next-generation sequencing (NGS), represents a paradigm shift in genomic research by enabling rapid, cost-effective, and large-scale analysis of DNA and RNA. [7]

The research using this technology has provided insights into male-specific genetic variation throughout history. The study of aDNA allows scientists to directly examine which SNPs and haplotypes were present at different time periods, rather than relying solely on inferences from modern populations. This provides concrete evidence of population movements and genetic changes over time. [8]

In 2018 alone, the genomes of more than a thousand prehistoric humans were determined, mostly from bones dug up years ago and preserved in museums and archaeological labs. [9]

As illustration three indicates, ancient DNA labs are now producing data on ancient human artifacts so quickly that the time lag between data production and publication of the results is longer than the time it takes to double the data production in the field. David Reich published the chart in illustration two in 2018.

In the matter of two years, Reich updated the chart (illustration three) [10] to reflect the dramatic increase in the number of completed whole genome sequencing of ancient remains. He referred to the dramatic increase in sampling of ancient genome data as “Moore’s Law of Ancient DNA”. [11]

Illustration Three: Growth of Genome Sequencing of Ancient Remains

Paleogenomic studies have revealed that non-African populations resulted from the diversification of an ancestral metapopulation that left Africa around 45,000-55,000 years ago.  This migration carried a subset of African genetic diversity to other continents, with subsequent population movements creating the genetic diversity we see today. [12]

Now scientists are delivering new answers to the question of who Europeans really are and where they came from. Their findings suggest that the continent has been a melting pot since the Ice Age. Europeans living today, in whatever country, are a varying mix of ancient bloodlines hailing from Africa, the Middle East, and the Russian steppe.

The evidence comes from archaeological artifacts, from the analysis of ancient teeth and bones, and from linguistics. But above all it comes from the new field of paleogenetics. [13]

The M168 YDNA genomic mutation represents a crucial milestone in human genetic history, marking one of the most significant events in human male lineage (see illustration four). This Y-chromosome marker originated approximately 50,000-60,000 years ago in northeastern Africa. The M168 mutation appeared in a man who geneticists sometimes refer to as “Out of Africa Adam.” His descendants were among the first humans to migrate out of Africa, carrying this genetic marker with them. This mutation is present in all modern non-African Y-chromosome haplogroups (C through R) and separates these lineages from the earlier African haplogroups A and B. [14]

Illustration Four: Simplified Phylogenetic Tree of Major Y Haplogroups and their Respecrtive Ancestry-Informative Markers (AIMs) in Europe

Click for Larger View | Adapted diagram originally found in B. Navarro‑Lopez, E. Granizo‑Rodrguez, L. Palencia‑Madrid, C. Raffone, M. Baeta, M. M. de Pancorbo, Phylogeographic review of Y chromosome haplogroups in Europe, International Journal of Legal Medicine (2021) 135:1675–1684, https://doi.org/10.1007/s00414-021-02644-6

The ancestry-informative marker (AIM) “M168” defines the macro-haplogroup CT and represents the ancestral lineage of all non-African Y-chromosome haplogroups, as well as some African lineages. [15] Every male living today, except those belonging to haplogroups A and B (found exclusively in Africa), carries this genetic marker.

Haplogroup G, which represents the Griff(is)(es)(ith) patenal line, originated in southwestern Asia or the Caucasus region. The estimated date of the G-M201 mutation has been debated, with several different timeframes proposed.

Recent research suggests that the first man to carry haplogroup G-M201 lived between 46,000 and 54,000 years ago in southwestern Asia or the Caucasus region. The National Geographic Society previously estimated its origins in the Middle East 30,000 years ago. Two other studues have suggested 17,000 years ago and a much more recent date of 9,500 years ago. The 9,500-year-old origin date for G-M201 was proposed by Cinnioglu et al. in their 2004 study. However, this estimate appears to be an outlier compared to other research findings and is not well-supported by current evidence. [16]

FamilyTreeDNA estimates the most recent common ancestor associated with the G-M201 haplgroup was born 25,735 BCE rounded to 26,000 BCE. With a 95 percent probability, the most recent common ancestor of all members of this haplogroup was born between the years 29,661 BCE and 22,295 BCE. [17]

The geographic origin of haplogroup G-M201 is most likely located somewhere near eastern Anatolia, Armenia, or western Iran. (See illustration five.) After remaining relatively isolated during the Ice Age, the haplogroup began expanding significantly around 11,500 years ago with the advent of farming and warmer climate conditions.

Illustration Five: Early Migratory Path of Most Recent Common Ancestors of the G Haplogroup in Anatolia Area

Click for Larger View | Source: Migratory Path of G Haplogroup Using Terminal Haplogroup G-Y132505 Rendered with Globe Trekker, FamilyTreeDNA, 12 February 2025, https://discover.familytreedna.com/y-dna/G-BY211678/path

The Y chromosome has been widely explored for the study of human migrations. Due to its paternal inheritance, the Y chromosome polymorphisms are helpful tools for understanding the geographical distribution of populations all over the world and for inferring their origin, which is really useful in forensics. The remarkable historical context of Europe, with numerous migrations and invasions, has turned this continent into a melting pot. For this reason, it is interesting to study the Y chromosome variability and how it has contributed to improving our knowledge of the distribution and development of European male genetic pool as it is today.” [18]

Anthropological – Macro Cultural Orientation

The anthropological – macro cultural approaches can add historical context to the genealogical discoveries associated with mid range and long term time layers. This macro approach helps bridge genetic data with an anthropological and sociological understanding, as genetic identities are often juxtaposed with socio-political contexts and dynamics. This creates a more complete picture of human population history while acknowledging both biological and cultural factors in human variation. [19]

Understanding how social and cultural processes affect the genetic patterns of human populations over time has brought together anthropologists, geneticists and evolutionary biologists, and the availability of genomic data and powerful statistical methods widens the scope of questions that analyses of genetic information can answer.” [20]

The anthropological – macro cultural orientation in genetic genealogy represents a comprehensive approach that combines traditional anthropological and demographic methods with modern genetic analysis to understand human populations and their histories at a broader scale. Genetic anthropology examines DNA sequences across diverse populations to determine shared geographical origins and migration patterns. This macro-level analysis helps reconstruct human population histories and relationships between different groups, moving beyond individual genetic ancestry to understand larger historical demographic patterns. [21]

The approach examines and documents broad cultural, political, and economic forces that shape communities and individuals in different time periods. It emphasizes studying the larger structural forces and systems that influence human behavior, moving beyond individual-level analysis to understand societal level patterns, institutions and customs.

The field employs both traditional macromorphoscopic trait analysis and modern genetic testing to create a robust scientific framework. [22] This includes examining population-wide genetic markers (Ancestry Informative Markers – AIMs) , demographic history patterns, DNA derived from ancient populations (aDNA), and social adaptation patterns across groups. [23]

Through their research, genetic anthropologists can determine population relationships, historical fluctuations in size, and admixture patterns between different groups. This helps reconstruct complex migration histories and evolutionary adaptations of human populations. [24]

Several key discoveries have emerged from studying genetic genealogy haplogroups through sociocultural and anthropological approaches. These findings demonstrate how social and cultural practices have been crucial factors in shaping human genetic diversity through their effects on genetic drift and population structure.

For example, the practice of patrilocality [25] has created distinct patterns in genetic diversity between male and female lineages. [26] Cultural organization has significantly impacted genetic patterns, particularly in nomadic populations where tribal-clan structures regulate social order and maintain bloodlines and agricultural communities where different patterns of inheritance and succession emerge. [27] 

Historical cultural expansions have had varying genetic impacts. For example, one study found that the Arab Islamic expansion introduced cultural changes but left minimal genetic impact. Conversely, the Mongol expansion achieved significant genetic success while having limited cultural influence. [28]

Different social structures have created distinct genetic patterns in kinship systems. Patrilineal kin groups show accelerated genetic drift and loss of Y-chromosome diversity. Corporate kin groups demonstrate clustering of genetic lineages due to intergroup competition. [29] 

Two studies, for example, have found that the mode of subsistence has been more influential than geography in shaping genetic landscapes. Settled agricultural communities show different genetic patterns compared to nomadic populations. Population size in villages affects genetic heterogeneity, with smaller communities showing greater between-village variation. [30] 

Click for Larger View | Cover illustration is by Zosia Rostomian, Geneome Research, April 2015,https://genome.cshlp.org/content/25/4.cover-expansion

A 2015 study utilizing an anthropological – macro cultural orientation by Monika Karmin and colleagues presents several significant findings. The researchers analyzed 456 geographically diverse high-coverage Y chromosome sequences, including 299 newly reported samples. Using ancient DNA calibration, they dated the Y-chromosomal most recent common ancestor (MRCA) in Africa at approximately 254,000 years ago. [31]

The study detected a cluster of major non-African founder haplogroups within a narrow time interval of 47-52 thousand years ago (kya), which supports a model of rapid initial colonization of Eurasia and Oceania following the out-of-Africa bottleneck.

Another key discovery from the Karmin et al study was the detection of a second strong bottleneck in Y-chromosome lineages dating to the last 10,000 years, which contrasts with demographic reconstructions based on mitochondrial DNA (mtDNA). The researchers hypothesize that this recent bottleneck was caused by cultural changes that affected the variance of reproductive success among males. The G haplogroup was impacted by his bottleneck.

The decline in the male effective population size during the Neolithic period was approximately one-twentieth of its original level in various regions of the world. In the same study, mitochondrial sequences indicated a continual increase in population size from the Neolithic to the present, suggesting extreme divergences between the demographic size of male and female populations in the bottleneck period. See illustration six below. Two encircled areas in the illustration graphically identify the growth differences in each of the YDNA and mtDNA graphs.

Illustration Six: Bottleneck of Y Chromosome Diversity Coincides with a Global Change in Culture

Click for Larger View | Source: Karmin M, et al, A recent bottleneck of Y chromosome diversity coincides with a global change in culture. Genome Res. 2015 Apr;25(4):459-66,doi: 10.1101/gr.186684.114, PubMed:https://pmc.ncbi.nlm.nih.gov/articles/PMC4381518/

Zeng et al.’s 2018 article in Nature Communications presents an intriguing sociocultural hypothesis to explain this post-Neolithic Y-chromosome bottleneck. The authors propose that the formation of patrilineal kin groups and competition between these groups led to a significant reduction in Y-chromosomal diversity through a process called ‘cultural hitchhiking’.

The outlines of that idea came to Tian Chen Zeng, a Stanford undergraduate in sociology, after spending hours reading blog posts that speculated – unconvincingly, Zeng thought – on the origins of the “Neolithic Y-chromosome bottleneck,” as the event is known. He soon shared his ideas with his high school classmate Alan Aw, also a Stanford undergraduate in mathematical and computational science.[32]

Click for Larger View | Source: Nature Communications is a peer-reviewed, open access, scientific journal published by Nature Portfolio since 2010. Image from Nature Communications, Wikipedia, This page was last edited on 30 August 2024, https://en.wikipedia.org/wiki/Nature_Communications

The pair of students took their idea to Marcus Feldman, a professor of biology in Stanford’s School of Humanities and Sciences and the rest is history. The authors contend that two cultural mechanisms of Y diversity reduction came into play. Patrilineal kin groups naturally produce high levels of Y-chromosomal homogeneity within each group (due to common descent) and high levels of between-group variation. Violent intergroup competition between patrilineal groups resulted in casualties clustering among related males, sometimes leading to the extinction of entire lineages and their unique Y-chromosomes. [33]

After the onset of farming and herding around 12,000 years ago, societies grew increasingly organized around extended kinship groups, many of them patrilineal clans – a cultural fact with potentially significant biological consequences. The key is how clan members are related to each other. While women may have married into a clan, men in such clans are all related through male ancestors and therefore tend to have the same Y chromosomes.

To explain why even between-clan variation might have declined during the bottleneck, the researchers hypothesized that wars, if they repeatedly wiped out entire clans over time, would also wipe out a good many male lineages and their unique Y chromosomes in the process.” [34]

The bottleneck coincides with the post-Neolithic period when societies were at an “intermediate social scale”, after the adoption of agriculture but before the emergence of hierarchical institutions. The authors argue that patrilineal descent groups were most politically salient in these post-Neolithic societies where the social structures were characteristzed as being without a formal leader or governing body. [35]

Cick for Larger View | Undergraduates Tian Chen Zeng, left, and Alan Aw, right, worked with Marcus Feldman, a professor of biology, to show how social structure could explain a genetic puzzle about humans of the Stone Age. (Image credit: Courtesy Marcus Feldman) Source:Collins, Nathan, Wars and clan structure may explain a strange biological event 7,000 years ago, Stanford researchers find , 30 May 2018, Stanford Report, Stanford University, https://news.stanford.edu/stories/2018/05/war-clan-structure-explain-odd-biological-event

The bottleneck ended in each region of the Old World during periods that coincided with the rise of regional polities, chiefdoms, and states, which reduced the prominence of corporate kin groups as units of mobilization in intergroup competition.

Genetic and Cultural Hitchhiking

The interplay between genetic and cultural evolution has shaped human diversity in profound ways. Two critical mechanisms—genetic hitchhiking and cultural hitchhiking—explain how neutral or non-adaptive traits can propagate through populations due to their association with advantageous traits – hitchhiking traits. While both processes reduce genetic diversity and leave distinct signatures in the genome, their mechanisms, transmission pathways, and evolutionary implications differ significantly. Hitchhiking models in socially structured populations describe processes where selection on one trait affects the frequency of other traits or genetic elements.

Genetic hitchhiking represents a powerful evolutionary force that can significantly shape haplogroup diversity patterns, sometimes creating genetic signatures that persist long after the original selective events occurred. Genetic hitchhiking, also called genetic drift or the hitchhiking effect, occurs when an allele changes frequency not because it is under natural selection itself, but because it is physically linked to another gene undergoing a selective sweep. [36]

Illustration Seven: Genetic Hitchhiking

Click for Larger View | Source: Hashem, Ihab & Telen, Dries & Nimmegeers, Philippe & Van Impe, Jan. (2018). The Silent Cooperator: An Epigenetic Model for Emergence of Altruistic Traits in Biological Systems. Complexity. 2018. 1-16. 10.1155/2018/2082037

Genetic hitchhiking: the frequency of a gene could increase in the population due to lying at the same chromosome of another advantageous gene. In these “domino organisms,” the top gene, the number of dots, represents a trait that is advantageous to its carrier, such as resistance to toxins or diseases. Hence, as the domino organisms with the highest dot number get positively selected, their bottom genes, which have no influence on their fitness, also spread in the population.” [37]

Nearby neutral or even slightly deleterious alleles that are in linkage with the selected gene “hitchhike” along with it. The closer a polymorphism is to the gene under selection, the stronger the hitchhiking effect due to less opportunity for recombination. Examples of selective sweeps in humans are in variants affecting lactase persistence, [38] and adaptation to high altitude. [39].

Cultural hitchhiking, originally proposed by Hal Whitehead in 1998 [40], describes how neutral genetic diversity is shaped by cultural selection. Unlike genetic hitchhiking, this process involves the transmission of culturally advantageous traits (e.g., agricultural practices or social norms) that indirectly influence the frequency of genetically neutral alleles through mate choice, social learning, or demographic shifts. Examples of mechanisms and cultural drivers are provided in table one. Examples of the cultural drivers and the resultant genomic and cultural signatures of cultural hitchhiking are provided signatures are provided in table one.

Table One: Examples of Cultural Drivers, Cultural Signatures and Genomic Patterns

Mechanisms and Cultural DriversDescription
Postmarital Residence RulesPatrilocal or matrilocal societies influence genetic admixture. For example, patrilocal postmarital residence in farming communities may reduce Y-chromosome diversity due to male-biased migration and cultural resocialization [41]
Cultural SelectionAdaptive cultural traits (e.g., slash-and-burn horticulture) alter selection pressures on genes. The spread of farming practices in Neolithic societies increased malaria incidence, favoring the S allele for sickle cell anemia. [42]
Genomic and Cultural Signatures:
Cultural hitchhiking leaves distinct genomic patterns
Description
Mitochondrial and Y-Chromosome BottlenecksReduced diversity in uniparentally inherited loci due to sex-biased cultural practices (e.g., patrilocality) [43]
Association with Cultural ArtifactsNeutral traits (e.g., pottery styles) spread alongside adaptive technologies (e.g., agriculture) due to social learning. [44]

Cultural hitchhiking occurs when neutral genes ‘hitchhike’ to higher frequencies alongside adaptive cultural traits. This process requires specific conditions. Genetic and cultural variants must be transmitted symmetrically (typically vertically from parent to offspring) . Cultural traits must create heritable variation in reproductive success or survival between different groups . Cultures must be stable and not frequently transfer between population segments. [45]

A related process called culturally mediated migration occurs when culture creates barriers within a population that inhibit dispersal and mating. This process reduces diversity of both neutral and functional genes through bottlenecks and selection ; can interact with competitive social dynamics, as seen in patrilineal kin groups ; and requires cultures that affect dispersal patterns and remain relatively stable. [46]

These models are significant because they help explain how social structure and cultural transmission can shape genetic diversity in both human and non-human populations.

Beware of Imputing Cause and Correlation between Genetic and Cultural Genealogical Orientations

The relationship between genetic and cultural inheritance is complex and bidirectional. Genetic propensities influence what cultural elements individuals learn, while culturally transmitted information affects selection pressures, such as marriage traditions, on populations. 

Genes and culture represent two streams of inheritance that for millions of years have flowed down the generations and interacted. Genetic propensities, expressed throughout development, influence what cultural organisms learn. Culturally transmitted information, expressed in behaviour and artefacts, spreads through populations, modifying selection acting back on populations.” [47]

Cultural and genetic genealogy are two distinct but related aspects of genealogy. Various migratory patterns associated with Y-DNA haplogroups do not necessarily imply that they coincide with macro-level, cultural geographical patterns or movements of people. Migratory patterns of Y-DNA Haplogroups undoubtably contained a mix of haplogroups. The migratory groups undoubtably were characterized by various cultural patterns, ptrsctices and behaviors. But Y-DNA haplogroups also were represented in various historical cultures. Many cultures invariably contained genetic mixtures of haplogroups at various periods of time.

Various theories have been formed that describe large cultural groups and major population movements where most of the members of a genetic haplogroup may have lived and traveled. Common genetic ancestors with matches from these time periods can be mapped and described but any information about where these ancestors lived and migrated is gained from these studies doe not necessaily mean that they are connected to our family history. 

There is no direct evidence that our individual ancestors were part of the same culture or migration patterns that are documented in paleogenomics and gnetic anthropological studies. We can not definitively associate deep ancestry haplogroups with historical cultures. However, the results of these multidisciplinary studies can provide a backdrop for interpreting or providing meaning and context to our haplogroup tree.

Ecological Fallacies Can Emerge When Analyzing Y-DNA Migration Patterns

An ecological fallacy is a logical error that occurs when conclusions about individuals are incorrectly drawn from group-level or aggregate data. This fallacy arises when characteristics of a population as a whole are mistakenly attributed to individuals within that population without demonstrating any real connection. [48]

The ecological fallacy can significantly impact the interpretation of Y-DNA migration patterns and haplotree analyses in several key ways. The primary ecological fallacy occurs when making inferences about individual migrations based on population-level Y-DNA patterns. Just because a haplogroup shows a particular geographic distribution pattern at the population level does not necessarily mean that our individual ancestors followed those exact migration routes. [49]

Two major temporal fallacies can emerge when comparing DNA composition with present day patterns and historic patterns. . The presence of a haplogroup in a modern population does not necessarily indicate when that lineage first arrived in a region. High frequencies of particular SNPs in current populations may not reflect historical frequencies, as ancient populations could have had different distributions. [50]

The assumption that current geographic distributions of Y-DNA haplogroups directly map to ancient migration routes can be fallacious. Population bottlenecks, founder effects, and later migrations can dramatically reshape haplogroup distributions. [51]

A reliable way to overcome ecological fallacies is to supplement population-level data with individual-level evidence. This requires integrating archaeological, historical, and genetic data at multiple scales of analysis. [52]

As genetic processes are inherently stochastic, patterns of genetic variation only indirectly reflect demographic histories, requiring careful inferential approaches. Lisa Loog’s 2020 article underscors this point by reviewing fundamental models and assumptions that underlie common approaches for inferring past demographic events from genetic data. All inferential approaches require assumptions about the data and underlying demographic processes, which significantly affect the interpretation of results. [53]

Loog discusses several important methodological issues:

  • Phylogenetic Analysis Limitations: Events in phylogenetic trees based on single loci do not directly correspond to population-level events due to their stochastic nature. Different demographic scenarios can produce similar gene trees (equifinality).
  • Principal Component Analysis (PCA) Issues: PCA, an approach used in many paleogenomic studies lacks an underlying population genetic model, making it problematic for demographic inference. Similar distributions of samples on PCs can result from entirely different demographic histories.
  • Clustering Method Problems: Statistical clusters are often mistakenly interpreted as evidence of “ancestral” or “source” populations when multiple distinct demographic histories could explain such clusters.

Loog’s article highlights how non-random sampling can significantly affect demographic inference. Archaeological specimens and museum collections are particularly susceptible to sampling bias due to preservation issues and non-random excavation patterns.

Loog’s analysis emphasizes that robust demographic inference requires formal comparison of alternative hypotheses formulated as different demographic scenarios. This allows assessment of the importance of different processes in population history.

Dangers of Attributing Cultural Factors with Haplogroups

Attributing ancient cultural traits to haplogroup migratory paths involves several potential fallacies and misconceptions. While genetic data provides valuable insights into human history, attributing cultural traits solely to haplogroup migrations oversimplifies complex historical processes. Cultural transmission, sociocultural practices, selection, drift, and non-random mating patterns all contribute to the complex relationship between genes and culture. A more nuanced approach recognizes that genetic and cultural histories, while sometimes parallel, often follow independent paths.

Genes and culture are not necessarily aligned. They follow different evolutionary trajectories. Languages and cultural practices evolve differently than genes, and while they may sometimes indicate common ancestry, they often develop independently6. Cultural innovations can significantly influence genetic diversity patterns without requiring population replacement. [54]

The relationship between genetic markers and cultural traits is rarely straightforward. Archaeological evidence often shows that contact between culturally distinct groups (like farmers and hunter-gatherers) led to substantial cultural changes without corresponding genetic shifts. Cultural diffusion can occur without significant genetic admixture, and vice versa. [55]

The presence of a haplogroup in multiple regions doesn’t necessarily indicate a single migration event or cultural connection. Haplogroups can arise before migration events and spread through multiple independent pathways . For example, if a haplogroup originated 20,000 years ago but a migration occurred 10,000 years ago, the haplogroup could potentially be found on both sides of the migration route. [56]

Sociocultural practices like postmarital residence patterns, linguistic exogamy, and gender-specific roles can dramatically shape genetic diversity independent of large-scale migrations. Studies of Native American populations show that sociocultural factors have played a more important role than language or geography in determining genetic structure. [57]

The coincidence of genetic and cultural changes doesn’t necessarily imply a causal relationship. For instance, the Avar migration into East Central Europe demonstrates how perceptions of people as “Avars” in historical texts, cultural unification, and genetic admixture did not follow analogous rhythms, leading to diverse genetic ancestry in different local communities despite shared cultural identity [58]

Many historical migrations show sex-biased patterns, with different male and female genetic histories. For example, in Native American populations, European admixture occurred primarily between European men and indigenous women4, creating discrepancies between mitochondrial DNA and Y-chromosome patterns. [59]

Genetic markers can be affected by natural selection and genetic drift, which can create patterns that mimic migration effects. These processes can lead to complicated cline shapes in marker frequencies that are unrelated to cultural diffusion. [60]

Human reproduction is not a uniform random process but is channeled through kinship systems, marriage rules, and social meanings of birth8. Even when different groups share cultural practices, their reproductive choices may maintain genetic differences rather than lead to homogenization. [61]

Admixture Events Complicate Attribution of Cultural Traits to Specific Haplogroups

Admixture events create complex genetic landscapes that make simple haplogroup-culture associations problematic. When populations merge, the resulting genetic profile becomes a mosaic of different ancestral contributions, with some individuals carrying haplogroups from one ancestral population while adopting cultural practices from another. For example, the genetic composition of present-day Europeans reflects multiple prehistoric migrations and admixture events, making it impossible to attribute specific cultural developments solely to particular haplogroups.

Admixture events typically involve cultural exchange that operates independently from genetic exchange. When populations meet and mix, cultural traits can be selectively adopted, modified, or rejected regardless of genetic inheritance patterns. The spread of farming across Europe illustrates this complexity – while there was some genetic contribution from Near Eastern farmers, the cultural practice of agriculture spread more widely than the genetic signature, as local hunter-gatherers adopted farming without complete genetic replacement.

The timing of genetic admixture and cultural change often does not align. Cultural traits may be adopted long before or after genetic admixture occurs, creating a ‘temporal disconnect’ that makes attributing cultural traits to specific haplogroups problematic. For instance, the adoption of Indo-European languages in Europe did not always coincide with significant genetic changes, as evidenced by regions where language shifted while genetic composition remained relatively stable. [62]

Genetic material and cultural traits follow different inheritance patterns. While haplogroups are inherited strictly through biological lines (Y-chromosome haplogroups paternally and mtDNA haplogroups maternally), cultural traits can be transmitted horizontally across populations and vertically between generations through non-genetic means. This fundamental difference means that cultural traits can spread widely without corresponding genetic changes.

Many historical admixture events show strong sex biases, with genetic contributions predominantly from males or females of one population. These sex-biased patterns create discrepancies between different genetic markers (autosomal DNA, Y-chromosome, mtDNA) and further complicate cultural attributions.

Source:

Feature Banner: The banner at the top of the story is an amalgam of two illustrations.

The illustration on the left is part of a chart that represents an haplotree of paternal descent. The blue lines represent the path or lineage of Y-SNP mutations of Y-DNA tests. The other lines represent lineages that have been undiscovered. On the left hand side of the haplotree are two bar graphs that illustrate how far back Y-STR and Y-SNP test results can be utilized to analyze lineages. The bottom of the illustration reflect the extent to which traditional family trees reach in the past. This illustration was created by Mike Walsh, project administrator of the FamilyTreeDNA R1b-L513 working group. It is presented in Vance’s introductory YourTube discussion of Y-DNA. J. David Vance, Transcript of DNA Concepts for Genealogy Y-DNA, 2019,  Page 11, https://drive.google.com/file/d/1CdUB4AmB1UYff5fmKtoKiqp6nG_gom37/view

The right hand portion of the banner is a chart that depicts the predominant orientation of a genealogical narrative in each layer of time.

[1] Mitochondrial DNA (mtDNA) testing analyzes DNA found in the mitochondria of cells, which is passed down exclusively from mothers to their children. This type of DNA testing provides specific information about a person’s maternal ancestry and has several distinctive characteristics. mtDNA exists separately from nuclear DNA, representing one of two genomes in mammalian cells. Both males and females inherit mtDNA, but only females can pass it to their children. Maternal relatives across multiple generations share identical mtDNA sequences, barring mutation.

Amorim A, Fernandes T, Taveira N. Mitochondrial DNA in human identification: a review. PeerJ. 2019 Aug 13;7:e7314. doi: 10.7717/peerj.7314. PMID: 31428537; PMCID: PMC6697116, https://pmc.ncbi.nlm.nih.gov/articles/PMC6697116/

Mitochondrial DNA tests, This page was last edited on 13 February 2021, International Society of Genetic Gnealogists Wiki, https://isogg.org/wiki/Mitochondrial_DNA_tests

[2] Y-DNA testing analyzes genetic information on the Y chromosome, which passes exclusively from fathers to sons. Y chromosome passes unchanged from father to son through generations. Only males possess and can pass on Y-DNA, making it useful for tracing paternal lineages. Unlike other chromosomes, Y-DNA undergoes minimal genetic recombination during reproduction.

[3] See my story: Y-DNA and the Griffis Paternal Line Part Three: The One-Two Punch of Using SNPs and STRs February 23, 2023

[4] Genetic drift is a fundamental evolutionary mechanism where random chance causes changes in the frequency of gene variants (alleles) within a population over time. This process occurs through random sampling of genes passed from one generation to the next, rather than through natural selection. This randomness can lead to some genetic variants becoming more common while others disappear entirely from the population.

Genetic drift has a stronger impact on smaller populations. In small groups, the loss or increase of particular genetic variants happens more quickly and dramatically than in larger populations.

Population bottlenecks are a type of geneetic drift. They occur when a population’s size is suddenly and dramatically reduced, such as through a natural disaster or overhunting. The surviving individuals may carry only a fraction of the original population’s genetic diversity.

Another example of genetic drift is a founder effect. Founder effects occur when a small group separates from a larger population to establish a new colony, they carry only a subset of the original population’s genetic diversity. This limited genetic pool becomes the foundation for the new population.

Rotimi, Charles, Genetic Drift, National Human Genome Research Institute, https://www.genome.gov/genetics-glossary/Genetic-Drift

Andrews, Christine A. (2010) Natural Selection, Genetic Drift, and Gene Flow Do Not Act in Isolation in Natural Populations. Nature Education Knowledge 3(10):5, https://www.nature.com/scitable/knowledge/library/natural-selection-genetic-drift-and-gene-flow-15186648/

Genetic Drift, Wikipedia, This page was last edited on 29 January 2025, https://en.wikipedia.org/wiki/Genetic_drift

Bohonak, Andrew J., Genetic Drift in Human Populations, Genetic Drift in Human Populations. In: Encyclopedia of Life Sciences (ELS), John Wiley & Sons, Ltd: Chichester. April 2018, DOI: 10.1002/9780470015902.a0005440.pub2, https://biology.sdsu.edu/pub/andy/Bohonak2008.pdf

[5] David Reich, Who We are and How We got Here, Ancient DNA and the New Science of the Human Past, New York: Vintage Books, 2018

Kivisild T. The study of human Y chromosome variation through ancient DNA. Hum Genet. 2017 May;136(5):529-546. doi: 10.1007/s00439-017-1773-z. Epub 2017 Mar 4. Erratum in: Hum Genet. 2018 Oct;137(10):863. doi: 10.1007/s00439-018-1937-5. PMID: 28260210; PMCID: PMC5418327, https://pmc.ncbi.nlm.nih.gov/articles/PMC5418327/

[6] Paleogenomics, Wikipedia, This page was last edited on 16 December 2023, https://en.wikipedia.org/wiki/Paleogenomics

High-throughput sequencing (HTS) is a revolutionary technology that enables rapid, parallel sequencing of millions of DNA and RNA molecules simultaneously13. This massively parallel approach represents a significant advancement over traditional Sanger sequencing methods, offering unprecedented speed, scale, and cost-effectiveness

[7] High-throughput sequencing (HTS) is a technology that enables rapid, parallel sequencing of millions of DNA and RNA molecules simultaneously. This massively parallel approach represents a significant advancement over traditional Sanger sequencing methods, offering unprecedented speed, scale, and cost-effectiveness in analying human genomes.

High-Throughput Sequencing: Definition, Technology, Advantages, Application and Workflow, CD Genomics, https://www.cd-genomics.com/resource-comprehensive-overview-high-throughput-sequencing.html

Churko JM, Mantalas GL, Snyder MP, Wu JC. Overview of high throughput sequencing technologies to elucidate molecular pathways in cardiovascular diseases. Circ Res. 2013 Jun 7;112(12):1613-23. doi: 10.1161/CIRCRESAHA.113.300939. PMID: 23743227; PMCID: PMC3831009, https://pmc.ncbi.nlm.nih.gov/articles/PMC3831009/

Tamang, Sanju, ed., Aryal, Sager, High Throughput Sequencing (HTS): Principle, Steps, Uses, Diagram, 9 Sep 2024, Microbe Notes, https://microbenotes.com/high-throughput-sequencing-hts/

What is next-generation sequencing?, Illumina, https://www.illumina.com/science/technology/next-generation-sequencing.html

Imanian, B., Donaghy, J., Jackson, T. et al. The power, potential, benefits, and challenges of implementing high-throughput sequencing in food safety systems. npj Sci Food 6, 35 (2022). https://doi.org/10.1038/s41538-022-00150-6 

Lee JY. The Principles and Applications of High-Throughput Sequencing Technologies. Dev Reprod. 2023 Apr;27(1):9-24. doi: 10.12717/DR.2023.27.1.9. Epub 2023 Mar 31. PMID: 38075439; PMCID: PMC10703097, https://pmc.ncbi.nlm.nih.gov/articles/PMC10703097/

[8] Kivisild, Toomas, The study of human Y chromosome variation through ancient DNA. Hum Genet. 2017 May;136(5):529-546. doi: 10.1007/s00439-017-1773-z. Epub 2017 Mar 4. Erratum in: Hum Genet. 2018 Oct;137(10):863. doi: 10.1007/s00439-018-1937-5. PMID: 28260210; PMCID: PMC5418327, https://pubmed.ncbi.nlm.nih.gov/28260210/

[9] David Reich, Who We are and How We got Here, Ancient DNA and the New Science of the Human Past, New York: Vintage Books, 2018

Michael Hofreiter, Johanna L. A. Paijmans, Helen Goodchild, Camilla F. Speller, Axel Barlow, Gloria G. Fortes, Jessica A. Thomas, Arne Ludwig and Matthew J. Collins, The future of ancient DNA: Technical advances and conceptual shifts, Bio Essays 37 (3) Nov 2015. original publication Nov 21 2014,  https://www.researchgate.net/publication/268579140_The_future_of_ancient_DNA_Technical_advances_and_conceptual_shifts 

Chinese Academy of Sciences, Researchers chart advances in ancient DNA technology July 21 2022, Phys.orghttps://phys.org/news/2022-07-advances-ancient-dna-technology.html 

Lorelei Verlhac, DNA and New Technologies: Is Paleogenomics the Future of Archiealology?, Byacardia,https://www.byarcadia.org/post/dna-and-new-technologies-is-paleogenomics-the-future-of-archaeology

Tsosie KS, Begay RL, Fox K, Garrison NA. Generations of genomes: advances in paleogenomics technology and engagement for Indigenous people of the Americas. Curr Opin Genet Dev. 2020 Jun;62:91-96  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7484015/

Evan K Irving-Pease, Rasa Muktupavela, Michael Dannermann, Fernando Racimo, Quantitative Human Paleogenetics: What can Ancient DNA Tell Us About Complex Trait Evolution?, Frontiers in Genetics, Aug 2021, Volume 12 Article 703541, https://www.frontiersin.org/articles/10.3389/fgene.2021.703541/full

Hodan, George, Most European men descend from a handful of Bronze Age forefathers, 19 May 2015, Phys.org, https://phys.org/news/2015-05-european-men-descend-bronze-age.html

Forbes. Peter, What Ancient DNA says about us, 2 Jul 2018, New Humanist, https://newhumanist.org.uk/articles/5335/what-ancient-dna-says-about-us

[10] Reich, David, Ancient DNA and the New Science of the Human Past, 3 Mar 2021, Simon’s Foundation Presidential Lectures, https://www.simonsfoundation.org/event/ancient-dna-and-the-new-science-of-the-human-past/

[11] Moore’s Law refers to Gordon Moore’s perception that the number of transistors on a microchip doubles every two years, though the cost of computers is halved. Moore’s Law states that we can expect the speed and capability of our computers to increase every couple of years, and we will pay less for them. Another tenet of Moore’s Law asserts that this growth is exponential.

Moore’s Law, Wikipedia, page last updated 23 Sep 2022, https://en.wikipedia.org/wiki/Moore%27s_law

For a related discussion on the improvements in DNA sequencing technologies and data-production pipelines in recent years, see:

Kris A. Wetterstrand, DNA Sequencing Costs: Data, 2022, National Humane Genome Research Institute, https://www.genome.gov/about-genomics/fact-sheets/DNA-Sequencing-Costs-Data

[12] Paleogenomics, Wikipedia, This page was last edited on 16 December 2023, https://en.wikipedia.org/wiki/Paleogenomics

[13] Curry, Andrew, The First Europeans Weren’t Who Your Might Think, National Geographic Magazine, August 2019, online: first-europeans-immigrants-genetic-testing-feature

[14] Karafet, T., Mendez, F., Sudoyo, H. et al. Improved phylogenetic resolution and rapid diversification of Y-chromosome haplogroup K-M526 in Southeast Asia. Eur J Hum Genet23, 369–373 (2015). https://doi.org/10.1038/ejhg.2014.106

Haplogroup CT, Wikipedia, This page was last edited on 5 July 2024, https://en.wikipedia.org/wiki/Haplogroup_CT

[15] Scozzari R, Massaia A, D’Atanasio E, Myres NM, Perego UA, Trombetta B, et al. (2012) Molecular Dissection of the Basal Clades in the Human Y Chromosome Phylogenetic Tree. PLoS ONE 7(11): e49170. https://doi.org/10.1371/journal.pone.0049170

[16] Haplogroup G-M201, Wikipedia, This page was last edited on 24 January 2025, https://en.wikipedia.org/wiki/Haplogroup_G-M201

“Atlas of the Human Journey: Haplogroup G (M201)”, National Geographic. Archived from the original on 5 February 2011. Retrieved 25 March 2023

Ancestral Path Chart for Haplogroup BY211678, G-M201 Haplogroup, FamilyTreeDNA, 22 Feb 2025, https://discover.familytreedna.com/y-dna/G-BY211678/path

Cinnioğlu C, King R, Kivisild T, Kalfoğlu E, Atasoy S, Cavalleri GL, Lillie AS, Roseman CC, Lin AA, Prince K, Oefner PJ, Shen P, Semino O, Cavalli-Sforza LL, Underhill PA. Excavating Y-chromosome haplotype strata in Anatolia. Hum Genet. 2004 Jan;114(2):127-48. doi: 10.1007/s00439-003-1031-4. Epub 2003 Oct 29. PMID: 14586639, https://pubmed.ncbi.nlm.nih.gov/14586639/

Semino O, Passarino G, Oefner PJ, Lin AA, Arbuzova S, Beckman LE, De Benedictis G, Francalacci P, Kouvatsi A, Limborska S, Marcikiae M, Mika A, Mika B, Primorac D, Santachiara-Benerecetti AS, Cavalli-Sforza LL, Underhill PA (November 2000). “The genetic legacy of Paleolithic Homo sapiens sapiens in extant Europeans: a Y chromosome perspective”. Science. 290 (5494): 1155–9. Bibcode:2000Sci…290.1155S. doi:10.1126/science.290.5494.1155. PMID 11073453

[17] Haplogroup G-M201, Wikipedia, This page was last edited on 24 January 2025, https://en.wikipedia.org/wiki/Haplogroup_G-M201

Ancestral Path Chart for Haplogroup BY211678, G-M201 Haplogroup, FamilyTreeDNA, 22 Feb 2025, https://discover.familytreedna.com/y-dna/G-BY211678/path

[18] B. Navarro‑L.pez, E. Granizo‑Rodr.guez, L. Palencia‑Madrid, C. Raffone . M. Baeta, M. M. de Pancorbo, Phylogeographic review of Y chromosome haplogroups in Europe, International Journal of Legal Medicine (2021) 135:1675–1684, https://doi.org/10.1007/s00414-021-02644-6

[19] Moreira, Ricardo Gomes, Human population genetics and the idea of ancestry: an anthropological perspective (part 2), 12, Jun 2023, Ancestry Traveler, https://ancestrytraveller.i3s.up.pt/human-population-genetics-and-the-idea-of-ancestry-an-anthropological-perspective-part-2/

Elia T. Ben-Ari, Molecular biographies: Anthropological geneticists are using the genome to decode human history, BioScience, Volume 49, Issue 2, February 1999, Pages 98–103, https://doi.org/10.2307/1313533

Kass, Mikala, 23 Apr 2019, Anthropology meets genetics to tell our collective story, ASU News, Arizona State University, https://news.asu.edu/20190423-discoveries-dna-anthropology-genetics

Crawford, Michael, Anthropological Genetics, Cambridge: Camridge University Press, 2007, http://ndl.ethernet.edu.et/bitstream/123456789/52369/1/104.pdf

Benn Torres J. Anthropological perspectives on genomic data, genetic ancestry, and race. Am J Phys Anthropol. 2020 May;171 Suppl 70:74-86. doi: 10.1002/ajpa.23979. Epub 2019 Dec 14. PMID: 31837009, https://pubmed.ncbi.nlm.nih.gov/31837009/

[20] Zeng, T.C., Aw, A.J. & Feldman, M.W. Cultural hitchhiking and competition between patrilineal kin groups explain the post-Neolithic Y-chromosome bottleneck. Nat Commun 9, 2077 (2018), page1, https://doi.org/10.1038/s41467-018-04375-6

[21] Deng, Nancy, Unearthing our past: The crucial role of genetic anthropology in rewriting history’s narrative, 2 Oct 2024, Vanderbilt Vanguard, https://vanderbiltvanguard.com/unearthing-our-past-the-crucial-role-of-genetic-anthropology-in-rewriting-historys-narrative/

“Genetic anthropology.” International Society of Genetic Genealogy Wiki. https://isogg.org/wiki/Genetic_anthropology#:~:text=Genetic%20anthropology%20is%20an%20emerging,how%20did%20we%20get%20here%3F%22.  

Kass, Mikala. “Anthropology meets genetics to tell our collective story.” ASU News, 23 April 2019, https://news.asu.edu/20190423-discoveries-dna-anthropology-genetics.

[22] While genetic markers provide direct DNA-based evidence, macromorphoscopic traits serve as proxies for genetic data to measure relatedness and locality. The Macromorphoscopic Databank (MaMD) contains data from over 2,400 individuals worldwide to support these assessments.

Macromorphoscopic traits are morphological features of the human cranium that are assessed by their presence, development, or absence, rather than through measurements. These traits reflect soft-tissue differences in living individuals and are used primarily in forensic anthropology for ancestry estimation.

Researchers are now working to combine macromorphoscopic trait data with genetic markers (including mitochondrial DNA, Y-chromosomes, and single nucleotide polymorphisms) to create more comprehensive ancestry estimations. This integration aims to provide multiple lines of evidence for more accurate classifications.

Some researchers question whether macromorphoscopic traits truly reflect microevolutionary processes or serve as suitable genetic proxies for population structure. This has led to ongoing discussions about the most appropriate methods for ancestry estimation in forensic anthropology.

Miller, Mackenzie, “Accuracy of Ancestry Estimation in Forensic Anthropology: An Examination of Select Nonmetric Methods” (2023). All ETDs from UAB. 79.
https://digitalcommons.library.uab.edu/etd-collection/79,

Plemons A, Hefner JT. Ancestry Estimation Using Macromorphoscopic Traits. Acad Forensic Pathol. 2016 Sep;6(3):400-412. doi: 10.23907/2016.041. Epub 2016 Sep 1. PMID: 31239915; PMCID: PMC6474543, https://pmc.ncbi.nlm.nih.gov/articles/PMC6474543/

DiGangi, EA, Bethard JD. Uncloaking a Lost Cause: Decolonizing ancestry estimation in the United States. Am J Phys Anthropol. 2021 Jun;175(2):422-436. doi: 10.1002/ajpa.24212. Epub 2021 Jan 18. PMID: 33460459; PMCID: PMC8248240, https://pmc.ncbi.nlm.nih.gov/articles/PMC8248240/

Hinkes M. Book Review: Atlas of Human Cranial Macromorphoscopic Traits. Acad Forensic Pathol. 2018 Dec;8(4):xii–xiii. doi: 10.1177/1925362118821514. Epub 2018 Dec 19. PMCID: PMC6491539, https://pmc.ncbi.nlm.nih.gov/articles/PMC6491539/

[23] Bernardi, Laura, An Introduction to Anthropological Demography, MPIDR Working Paper WP 2007-031, Max Planck Institute for Demographic Research, https://www.demogr.mpg.de/papers/working/wp-2007-031.pdf

Sample records for anthropology human genetics, Topics by Sience.gov, Science.gov, https://www.science.gov/topicpages/a/anthropology+human+genetics.html

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Elhaik, Eran; Greenspan, Elliott; Staats, Sean; Krahn, Thomas; Tyler-Smith, Chris; Xue, Yali; Tofanelli, Sergio; Francalacci, Paolo; Cucca, Francesco; Pagani, Luca; Jin, Li; Li, Hui; Schurr, Theodore G.; Greenspan, Bennett; Spencer Wells, R, The GenoChip: A New Tool for Genetic Anthropology, the Genographic Consortium, Genome Biol Evol. 2013; 5(5): 1021–1031. Published online 2013 May 9. doi: 10.1093/gbe/evt066 https://pmc.ncbi.nlm.nih.gov/articles/PMC3673633/

Huckins, L., Boraska, V., Franklin, C. et al. Using ancestry-informative markers to identify fine structure across 15 populations of European origin. Eur J Hum Genet 22, 1190–1200 (2014). https://doi.org/10.1038/ejhg.2014.1

Yu JH, Taylor JS, Edwards KL, Fullerton SM. What are our AIMs? Interdisciplinary Perspectives on the Use of Ancestry Estimation in Disease Research. AJOB Prim Res. 2012;3(4):87-97. doi: 10.1080/21507716.2012.717339. PMID: 25419472; PMCID: PMC4238888, https://pmc.ncbi.nlm.nih.gov/articles/PMC4238888/

[24] Elia T. Ben-Ari, Molecular biographies: Anthropological geneticists are using the genome to decode human history, BioScience, Volume 49, Issue 2, February 1999, Pages 98–103, https://doi.org/10.2307/1313533

Shyamalika Gopalan , Samuel Pattillo Smith , Katharine Korunes , Iman Hamid , Sohini Ramachandran and Amy Goldberg, Human genetic admixture through the lens of population genomics, Philosphical Transactions of the Royal Society Biological Sciences, 18 April 2022, https://doi.org/10.1098/rstb.2020.0410

Manjusha Chintalapati Nick Patterson Priya Moorjani (2022) The spatiotemporal patterns of major human admixture events during the European Holocene,  eLife 11:e77625, https://doi.org/10.7554/eLife.77625

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Shriner D. Overview of admixture mapping. Curr Protoc Hum Genet. 2013;Chapter 1:Unit 1.23. doi: 10.1002/0471142905.hg0123s76. PMID: 23315925; PMCID: PMC3556814, https://pmc.ncbi.nlm.nih.gov/articles/PMC3556814/

Daniel Wegmann, Raphael Eckel, Human evolution: When admixture met selection, Current Biology, Volume 33, Issue 7, 2023, Pages R259-R261, ISSN 0960-9822,
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[25] Patrilocality is the practice where a newly married couple resides with or near the husband’s family, meaning the wife moves to live close to her husband’s parents after marriage, typically found in societies that emphasize strong male lineage and family ties; it is the opposite of matrilocality where the couple lives near the wife’s family. 

[26]  Deborah A. Bolnick, Daniel I. Bolnick, David Glenn Smith, Asymmetric Male and Female Genetic Histories among Native Americans from Eastern North America, Molecular Biology and Evolution, Volume 23, Issue 11, November 2006, Pages 2161–2174, https://doi.org/10.1093/molbev/msl088

Giovanni Destro-Bisol, Francesco Donati, Valentina Coia, Ilaria Boschi, Fabio Verginelli, Alessandra Caglià, Sergio Tofanelli, Gabriella Spedini, Cristian Capelli, Variation of Female and Male Lineages in Sub-Saharan Populations: the Importance of Sociocultural Factors, Molecular Biology and Evolution, Volume 21, Issue 9, September 2004, Pages 1673–1682, https://doi.org/10.1093/molbev/msh186

[27] Zhabagin, M., Balanovska, E., Sabitov, Z. et al. The Connection of the Genetic, Cultural and Geographic Landscapes of Transoxiana. Sci Rep 7, 3085 (2017). https://doi.org/10.1038/s41598-017-03176-z 

[28] Ibid

[29] Zeng, T.C., Aw, A.J. & Feldman, M.W. Cultural hitchhiking and competition between patrilineal kin groups explain the post-Neolithic Y-chromosome bottleneck. Nat Commun 9, 2077 (2018). https://doi.org/10.1038/s41467-018-04375-6

[30] Zhabagin, M., Balanovska, E., Sabitov, Z. et al. The Connection of the Genetic, Cultural and Geographic Landscapes of Transoxiana. Sci Rep 7, 3085 (2017). https://doi.org/10.1038/s41598-017-03176-z 

Chiaroni J, Underhill PA, Cavalli-Sforza LL. Y chromosome diversity, human expansion, drift, and cultural evolution. Proc Natl Acad Sci U S A. 2009 Dec 1;106(48):20174-9. doi: 10.1073/pnas.0910803106. Epub 2009 Nov 17. Erratum in: Proc Natl Acad Sci U S A. 2010 Jul 27;107(30):13556. PMID: 19920170; PMCID: PMC2787129, https://pmc.ncbi.nlm.nih.gov/articles/PMC2787129/

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[32] Collins, Nathan, Wars and clan structure may explain a strange biological event 7,000 years ago, Stanford researchers find , 30 May 2018, Stanford Report, Stanford University, https://news.stanford.edu/stories/2018/05/war-clan-structure-explain-odd-biological-event

[33] Zeng, T.C., Aw, A.J. & Feldman, M.W. Cultural hitchhiking and competition between patrilineal kin groups explain the post-Neolithic Y-chromosome bottleneck. Nat Commun9, 2077 (2018). https://doi.org/10.1038/s41467-018-04375-6

[34] Collins, Nathan, Wars and clan structure may explain a strange biological event 7,000 years ago, Stanford researchers find , 30 May 2018, Stanford Report, Stanford University, https://news.stanford.edu/stories/2018/05/war-clan-structure-explain-odd-biological-event

[35] Davidski , Cultural hitchhiking and competition between patrilineal kin groups may have led to the post-Neolithic Y-chromosome bottleneck (Zeng et al. 2018) , Friday, May 25, 2018 , Eurogenes Blog, https://eurogenes.blogspot.com/2018/05/cultural-hitchhiking-and-competition.html#google_vignette

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[36] In genetics, a selective sweep is the process through which a new beneficial mutation that increases its frequency and becomes fixed (i.e., reaches a frequency of 1) in the population leads to the reduction or elimination of genetic variation among nucleotide sequences that are near the mutation.”

Selective sweep, Wikipedia, This page was last edited on 1 February 2025, https://en.wikipedia.org/wiki/Selective_sweep

Genetic hitchhiking, Wikipedia, This page was last edited on 10 February 2025, https://en.wikipedia.org/wiki/Genetic_hitchhiking

[37] Hashem, Ihab & Telen, Dries & Nimmegeers, Philippe & Van Impe, Jan. (2018). The Silent Cooperator: An Epigenetic Model for Emergence of Altruistic Traits in Biological Systems. Complexity. 2018. 1-16. 10.1155/2018/2082037

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[40] Cultural hitchhiking, Wikipedia, This page was last edited on 23 October 2024, https://en.wikipedia.org/wiki/Cultural_hitchhiking

Whitehead, Hal; Vachon, Felicia; Frasier, Timothy R. (May 2017). “Cultural Hitchhiking in the Matrilineal Whales”. Behavior Genetics47 (3): 324–334. doi:10.1007/s10519-017-9840-8. PMID 28275880. S2CID 3866892, https://doi.org/10.1007/s10519-017-9840-8

[40] Premo, L. S.. “Hitchhiker’s guide to genetic diversity in socially structured populations.” Current Zoology, vol. 58, no. 2, Apr. 2012, pp. 287-297. https://doi.org/10.1093/czoolo/58.2.287

[41] Carrignon, Simon, Encrico R Crema, Anne Kandler, Stephen Shennan, Postmarital residence rules and transmission pathways in cultural hitchhiking, 18 Nov 2024, PNAS, Vol 121 No 48 https://www.pnas.org/doi/10.1073/pnas.2322888121

Whitehead, Hal; Vachon, Felicia; Frasier, Timothy R. (May 2017). “Cultural Hitchhiking in the Matrilineal Whales”. Behavior Genetics47 (3): 324–334. doi:10.1007/s10519-017-9840-8. PMID 28275880. S2CID 3866892, https://doi.org/10.1007/s10519-017-9840-8

[42] Fogarty L, Otto SP. Signatures of selection with cultural interference. Proc Natl Acad Sci U S A. 2024 Nov 26;121(48):e2322885121. doi: 10.1073/pnas.2322885121. Epub 2024 Nov 18. PMID: 39556724; PMCID: PMC11621839, https://pmc.ncbi.nlm.nih.gov/articles/PMC11621839/

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Fogarty L, Otto SP. Signatures of selection with cultural interference. Proc Natl Acad Sci U S A. 2024 Nov 26;121(48):e2322885121. doi: 10.1073/pnas.2322885121. Epub 2024 Nov 18. PMID: 39556724; PMCID: PMC11621839, https://pmc.ncbi.nlm.nih.gov/articles/PMC11621839/

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[47] Laland Kevin N. Exploring gene-culture interactions: insights from handedness, sexual selection and niche-construction case studies. Philos Trans R Soc Lond B Biol Sci. 2008 Nov 12;363(1509):3577-89. doi: 10.1098/rstb.2008.0132. PMID: 18799415; PMCID: PMC2607340, https://pmc.ncbi.nlm.nih.gov/articles/PMC2607340/

One a approach, niche construction theory (NCT), describes how organisms actively modify their own and other species’ evolutionary environments through their activities and behaviors1. This process goes beyond passive adaptation to environments, as organisms create systematic changes that affect natural selection pressures on themselves and future generations. [a]

Rather than viewing evolution as a one-way process, NCT presents it as a dynamic feedback system where organisms modify their environments, modified environments create new selection pressures, and these pressures influence subsequent evolution. This perspective transforms evolutionary theory from focusing solely on organismal evolution to examining the co-evolution of organisms with their environments. [b]

[47a] Laland K, Matthews B, Feldman MW. An introduction to niche construction theory. Evol Ecol. 2016;30:191-202. doi: 10.1007/s10682-016-9821-z. Epub 2016 Feb 3. PMID: 27429507; PMCID: PMC4922671, https://pmc.ncbi.nlm.nih.gov/articles/PMC4922671/

Niche construction, Wikipedia, This page was last edited on 6 January 2025, https://en.wikipedia.org/wiki/Niche_construction

[47b] Kevin Laland, John Odling-Smee and ohn Endler, Niche construction, sources of selection and trait coevolution, Interface Focus, 18 August 2017, https://doi.org/10.1098/rsfs.2016.0147

[48] Ecological Fallacy, Wikipedia, This page was last edited on 21 September 2024, https://en.wikipedia.org/wiki/Ecological_fallacy

[49] Spatial Aggregation and the Ecological Fallacy. Chapman Hall CRC Handb Mod Stat Methods. 2010;2010:541-558. doi: 10.1201/9781420072884-c30. PMID: 25356440; PMCID: PMC4209486, https://pmc.ncbi.nlm.nih.gov/articles/PMC4209486/

[50] See for example, Parahu, Ancient DNA from Ethiopia, 11 Mar 2023, Land of Punt, https://landofpunt.wordpress.com/2023/03/11/ancient-dna-from-ethiopia-2/

[51] Templeton, Alan R., Genetics and Recent Human Evolution, 19 Apr 2007, Perspective: The Society for the Study of Evolution, Evolution 61-7 : 1507–1519, https://www.sfu.ca/biology/courses/bisc441/Course_Materials/Readings/13-(Lect8)Templeton2007.pdf

Guha P, Srivastava SK, Bhattacharjee S, Chaudhuri TK. Human migration, diversity and disease association: a convergent role of established and emerging DNA markers. Front Genet. 2013 Aug 9;4:155. doi: 10.3389/fgene.2013.00155. PMID: 23950760; PMCID: PMC3738866 https://pmc.ncbi.nlm.nih.gov/articles/PMC3738866/

[52] Spatial Aggregation and the Ecological Fallacy. Chapman Hall CRC Handb Mod Stat Methods. 2010;2010:541-558. doi: 10.1201/9781420072884-c30. PMID: 25356440; PMCID: PMC4209486, https://pmc.ncbi.nlm.nih.gov/articles/PMC4209486/

[53] Loog L. Sometimes hidden but always there: the assumptions underlying genetic inference of demographic histories. Philos Trans R Soc Lond B Biol Sci. 2021 Jan 18;376(1816):20190719. doi: 10.1098/rstb.2019.0719. Epub 2020 Nov 30. PMID: 33250022; PMCID: PMC7741104, https://pmc.ncbi.nlm.nih.gov/articles/PMC7741104/

[54] Ainash Childebayeva, Adam Benjamin Rohrlach, Rodrigo Barquera, Maïté Rivollat, Franziska Aron, András Szolek, Oliver Kohlbacher, Nicole Nicklisch, Kurt W. Alt, Detlef Gronenborn, Harald Meller, Susanne Friederich, Kay Prüfer, Marie-France Deguilloux, Johannes Krause, Wolfgang Haak, Population Genetics and Signatures of Selection in Early Neolithic European Farmers, Molecular Biology and Evolution, Volume 39, Issue 6, June 2022, msac108, https://doi.org/10.1093/molbev/msac108

Arias L, Schröder R, Hübner A, Barreto G, Stoneking M, Pakendorf B. Cultural Innovations Influence Patterns of Genetic Diversity in Northwestern Amazonia. Mol Biol Evol. 2018 Nov 1;35(11):2719-2735. doi: 10.1093/molbev/msy169. PMID: 30169717; PMCID: PMC6231495, https://pmc.ncbi.nlm.nih.gov/articles/PMC6231495

Deborah A. Bolnick, Daniel I. Bolnick, David Glenn Smith, Asymmetric Male and Female Genetic Histories among Native Americans from Eastern North America, Molecular Biology and Evolution, Volume 23, Issue 11, November 2006, Pages 2161–2174, https://doi.org/10.1093/molbev/msl088

[55] Chyleński, M., Makarowicz, P., Juras, A. et al. Patrilocality and hunter-gatherer-related ancestry of populations in East-Central Europe during the Middle Bronze Age. Nat Commun 14, 4395 (2023). https://doi.org/10.1038/s41467-023-40072-9

[56] See for example Estes, Roberta, New Native American Mitochondrial DNA Haplogroups, 2 mar 217, DNAeXplained – Genetic Genealogy, https://dna-explained.com/2017/03/02/new-native-american-mitochondrial-dna-haplogroups/

[57] See for example:

Arias L, Schröder R, Hübner A, Barreto G, Stoneking M, Pakendorf B. Cultural Innovations Influence Patterns of Genetic Diversity in Northwestern Amazonia. Mol Biol Evol. 2018 Nov 1;35(11):2719-2735. doi: 10.1093/molbev/msy169. PMID: 30169717; PMCID: PMC6231495

Deborah A. Bolnick, Daniel I. Bolnick, David Glenn Smith, Asymmetric Male and Female Genetic Histories among Native Americans from Eastern North America, Molecular Biology and Evolution, Volume 23, Issue 11, November 2006, Pages 2161–2174, https://doi.org/10.1093/molbev/msl088

[58] Wang, K., Tobias, B., Pany-Kucera, D. et al. Ancient DNA reveals reproductive barrier despite shared Avar-period culture. Nature 638, 1007–1014 (2025). https://doi.org/10.1038/s41586-024-08418-5

[59] Deborah A. Bolnick, Daniel I. Bolnick, David Glenn Smith, Asymmetric Male and Female Genetic Histories among Native Americans from Eastern North America, Molecular Biology and Evolution, Volume 23, Issue 11, November 2006, Pages 2161–2174, https://doi.org/10.1093/molbev/msl088

Arias L, Schröder R, Hübner A, Barreto G, Stoneking M, Pakendorf B. Cultural Innovations Influence Patterns of Genetic Diversity in Northwestern Amazonia. Mol Biol Evol. 2018 Nov 1;35(11):2719-2735. doi: 10.1093/molbev/msy169. PMID: 30169717; PMCID: PMC6231495, https://pmc.ncbi.nlm.nih.gov/articles/PMC6231495/

[60] Isern, N., Fort, J. & de Rioja, V.L. The ancient cline of haplogroup K implies that the Neolithic transition in Europe was mainly demic. Sci Rep 7, 11229 (2017). https://doi.org/10.1038/s41598-017-11629-8

[61] Wang, K., Tobias, B., Pany-Kucera, D. et al. Ancient DNA reveals reproductive barrier despite shared Avar-period culture. Nature 638, 1007–1014 (2025). https://doi.org/10.1038/s41586-024-08418-5

[62] There are several documented instances where Indo-European languages were adopted without corresponding significant genetic changes in European populations.

The Hungarians represent one of the most studied cases of language-genetic mismatch in Europe. While they speak a Uralic language (not Indo-European), they are genetically similar to their Indo-European speaking neighbors. This population preserved the language brought by the Magyars who conquered the Carpathian Basin in the ninth century CE, while becoming genetically assimilated to their Indo-European-speaking neighbors over time. [a]

The Maltese present another interesting case. They speak an Afro-Asiatic language with lexical influences from Italian and English, making them the only Afro-Asiatic speakers in Europe. Their genetic profile can be described as a mix of ancestries from throughout the Mediterranean basin, being genetically close to Eastern Sicilians while sharing genetic relatedness with Indo-European speakers from the Balkans. [b]

More recent European examples where language and genes do not match include the spread of Slavic languages across the Balkans and elsewhere. These cases demonstrate that language adoption can occur through cultural processes rather than genetic replacement. [c]

In Greece, archaeological and genetic evidence indicates that Indo-European languages spread without major population replacement. Studies show that steppe ancestry (associated with early Indo-European speakers) was present at relatively low levels of about in both elite and non-elite individuals in ancient Greece4[d] Unlike northern Europe, where steppe-descended peoples replaced up to 90% of the native population, in Greece the steppe migrants became integrated both socially and genetically into Aegean societies rather than dominating them.

Concept of Language Shift

The concept of language sift has been utilized as an attempt to explain one aspecet of the relationship between genetics and culture. Language shifts can occur through elite dominance rather than mass migration.

The “elite recruitment” model suggests that Indo-European languages likely spread through the actions of “Indo-European chiefs” and their “ideology of political clientage” rather than through complete population replacement. Small elite groups have successfully imposed their languages in various historical contexts without significantly altering the genetic makeup of the local population. [e]

David Anthony, who proposed a “revised Steppe hypothesis,” argues that Indo-European languages spread not through “chain-type folk migrations” but through this elite recruitment process, where ritual and political elites introduced these languages and were then emulated by larger groups.

As David Anthony explains, “Language shift can be understood best as a social strategy through which individuals and groups compete for positions of prestige, power, and domestic security.” A relatively small immigrant elite population can encourage widespread language shift among numerically dominant indigenous populations if they employ specific combinations of encouragements and punishments. [f]

However, some scholars like Axel Kristinsson question the elite dominance model, noting that historically, it is often the conquerors who adopt the language of the conquered rather than vice versa. He points out that for elite dominance to effectively cause language shift, it typically requires additional elements like a centralized state, which did not exist in the fourth millennium BCE when Indo-European languages began spreading. [g]

Correlations between genetic and linguistic diversity across European populations

A 2015 study by Longobardi et al. revealed significant correlations between genetic and linguistic diversity across European populations. The research employed innovative linguistic comparison tools: a refined list of Indo-European cognate words and a novel method estimating linguistic diversity from a universal inventory of grammatical polymorphisms. [h]

Click for Larger View | Source: Giuseppe Longobardi, Silvia Ghirotto, Cristina Guardiano, Francesca Tassi, Andrea Benazzo, Andrea Ceolin, Guido Barbujani, Across language families: Genome diversity mirrors linguistic variation within Europe, Physical Anthropology, 157 (4) Aug 2015: 630-640, online: https://onlinelibrary.wiley.com/doi/full/10.1002/ajpa.22758

The study found that populations speaking different languages are more likely to have different genetic makeup. The degree of genetic diversity between two European populations was proportional to their linguistic diversity.

Contrary to previous observations, language proved to be a better predictor of genetic differences than geographical distribution. Both lexical and syntactic distances showed higher correlations with genetic distances than genes did with geography

The research by Longobardi et al suggests that migrating populations carried their genes alongside their language, rather than just experiencing cultural diffusion of linguistic features. Inferred episodes of genetic admixture following major population splits had convincing correlates in the linguistic realm.

Research has shown significant correlations between genomic and linguistic diversity in Europe, with language sometimes proving to be a better predictor of genomic differences than geography.  However, these correlations do not necessarily imply that language shifts always coincide with genetic changes.

The debate about Indo-European language origins continues, with competing theories placing their birthplace either in Anatolia (with the first farmers) or on the Eurasian steppe. Recent genetic evidence supports the steppe hypothesis, identifying the Caucasus Lower Volga people as the likely originators of Proto-Indo-European around 6,500 years ago.  [i]

The spread of these languages throughout Europe likely involved both migration and cultural adoption processes, with varying degrees of genetic impact in different regions.

[a] Barbieri, Chaiara, Damián E. Blasi, Epifanía Arango-Isaza, and Kentaro K. Shimizu,  A global analysis of matches and mismatches between human genetic and linguistic histories, 21 Nov 2022, PNAS, 119 (47), https://www.pnas.org/doi/10.1073/pnas.2122084119

[b] Ibid

[c] Alberto González, Origins and spread of Indo-European languages: an alternative view, 8 Dec 2024, Ancient DNA Era, https://adnaera.com/2024/12/08/origins-and-spread-of-indo-european-languages-an-alternative-view/

[d] Shaw, Jonathan, Seeking the First Speakers of Indo-European Language, 25 Aug 2022, Harvard Magazine, https://www.harvardmagazine.com/2022/08/indo-european-languages

Iosif Lazaridis et al. ,The genetic history of the Southern Arc: A bridge between West Asia and Europe, Science 377, eabm4247 (2022). DOI:10.1126/science.abm4247, https://www.science.org/doi/10.1126/science.abm4247

Language shift, Wikipedia, This page was last edited on 23 December 2024, https://en.wikipedia.org/wiki/Language_shift

Indo-European migrations, Wikipedia, This page was last edited on 21 February 2025, https://en.wikipedia.org/wiki/Indo-European_migrations

[e] Language shift, Wikipedia, This page was last edited on 23 December 2024, https://en.wikipedia.org/wiki/Language_shift

[f] Language shift, Wikipedia, This page was last edited on 23 December 2024, https://en.wikipedia.org/wiki/Language_shift

[g] Kristinsson, Axel, Indo-European Expansion Cycles, The Journal of Indo-European Studies , Volume 40, Number 3 & 4, Fall/Winter 2012, https://www.axelkrist.com/docs/Indo-European_Expansion_Cycles.pdf

[h] Giuseppe Longobardi, Silvia Ghirotto, Cristina Guardiano, Francesca Tassi, Andrea Benazzo, Andrea Ceolin, Guido Barbujani, Across language families: Genome diversity mirrors linguistic variation within Europe, Physical Anthropology, 157 (4) Aug 2015: 630-640, online: https://onlinelibrary.wiley.com/doi/full/10.1002/ajpa.22758

[i] Giuseppe Longobardi, Silvia Ghirotto, Cristina Guardiano, Francesca Tassi, Andrea Benazzo, Andrea Ceolin, Guido Barbujani, Across language families: Genome diversity mirrors linguistic variation within Europe, Physical Anthropology, 157 (4) Aug 2015: 630-640, online: https://onlinelibrary.wiley.com/doi/full/10.1002/ajpa.22758

DeSmith, Christy, Ancient-DNA Study Identifies Originators of Indo-European Language Family, 5 Feb 2025, Harvard Gazette, https://hms.harvard.edu/news/ancient-dna-study-identifies-originators-indo-european-language-family

Lazaridis, I., Patterson, N., Anthony, D. et al. The genetic origin of the Indo-Europeans. Nature (2025). https://doi.org/10.1038/s41586-024-08531-5

Dutchen, Stephanie, A Steppe Forward: Ancient DNA challenges popular theory of Indo-European language arrival in Europe, 2 mar 2015, News & Research, Harvard Medical School, https://hms.harvard.edu/news/steppe-forward

Dutchen, Stephanie, Old Mysteries: New Insights Ancient DNA illuminates 15,000 years of history at Europe-Asia crossroads, News & Research, 25 Aug 2022, Harvard Medical School, https://hms.harvard.edu/news/old-mysteries-new-insights