deep ancestry – Griffis Family

January 4, 2025January 6, 2025

Different Layers of Genealogical Time – Part One

Genealogical time takes on different meanings and reality depending on which methods are utilized to analyze evidence. Our terminology consequently changes and the focus of our story changes as we go back in time. We gradually start looking at our respective family descendants not in terms of their family roles as father, uncle, and great grand mother but in terms of genetic mutations.

The concept of generations morphs into genetic distance. [1] Our focus on the family tree branches and families shifts to the analysis of genetic lineages and haplogroups. [2] Our individually identified descendants such as a great⁴ grandfather or our great⁴ grandmother are shifted to identifying the Most Recent Common Ancestors (tMRCA). [3]

Genealogical time shifts our focus on ethnic backgrounds and origins obtained from autosomal DNA tests to analyzing migratory patterns of haplogroups and determining the presence of ancient cultures that might correlate with where our genetic descendants may have lived. The analysis of Y-DNA or mtDNA extends genetic links backward in time thousands of years. The notion of ‘ethnic origin or composition’ becomes less important since ethnicity is largely the product of cultural patterns dependent upon historic time and location.

“As a scientist, I find questions of identity and ethnicity to be simplistic and naïve. The answer depends on “which branch?” and “when?”. In my case, if when = now, I’d say a retiree from Connecticut. If when = 1800 on my paternal line, I’d say a farmer from Vermont. If when = 1600, then a sheep herder in Bedfordshire England. In the Roman era, probably north central Europe; in Mesolithic era, in the Balkans. And if when = 35,000 years ago or before, then my ancestors were African hunter-gatherers, like all of us.” [4]

Genetic genealogy introduces a different view of time and the analysis of ‘genealogical facts’ through different layers of time. The notion of time radically expands in scope and changes how we perceive and measure change and time and view genealogical evidence.

This story presents a view that the different approaches and related methodologies for conducting genealogical research depict three different interrelated historical layers of time. While each historical layer has distinctive properties, the boundaries between each are not clearly defined and can shift on the basis of genealogical discoveries. Each layer has different rhythms of time. Each historical layer has different conceptions of reality as perceived by the genealogist and also exhibits different properties of reality.

Among the many influences on my views on genealogical layers of time, there are three individuals that are notable. Two of the three are genetic genealogists J.David Vance and Rob Spencer. The third influence is an historian Fernand Braudel, who was an historian from the Annales School of French historiography and social history. [5] In addition to traditional notions of history, Braudel introduced the concepts of longue durée and conjunctures to analyze historical cycles. [6]

Vance’s View of Genealogy as Having Three Historical Phases

J. David Vance is a prominent genetic genealogist with over 35 years of traditional genealogy experience and has been actively involved in genetic genealogy projects and organizations since 2005. At the time of writing this post, he served as the Senior Vice President and General Manager at FamilyTreeDNA.

Vance advocates for a more inclusive approach to family research that combines traditional genealogical methods with genetic testing, acknowledging both biological and non-biological family connections. His work particularly emphasizes helping traditional genealogists transition to incorporating DNA evidence in their research, while maintaining a balanced perspective that values both documentary and genetic evidence in family history research. [7]

Vance’s Continuum of Genealogical Time Through Y-DNA Testing

Vance is known for developing innovative approaches and technical contributions [8] to understanding genetic genealogy, including his metaphor comparing traditional genealogy to building a mansion with portraits, and genetic genealogy to adding stained-glass windows with DNA patterns. [9] His ‘three phases of genealogy’ has had a major impact on my thinking about the relationship between traditional and genetic genealogy and the strategy of using both in genealogical research.. [10]

Illustration One: The Three Phases of Genealogy

David Vance uses the term ‘genealogy‘ to demarcate a period of time where generations of named ancestors have been documented through traditional records research and possible DNA testing. DNA tests are just another source or corroborating type of genealogical record.

Beyond this period is a time which is beyond many of our “brick walls” of genealogy. This is where we cannot trace our family tree further into the past. Vance calls this netherworld time period as the period of lineages. The line of demarkation between lineages and genealogy is not hard fast period of time and it can change based on genealogical discoveries.

“. . . (I)n between deep ancestry and the genealogy of named ancestors (traditional genealogy), we have what (are) “lineages” for lack of a better term. These are genealogies if you will but of unnamed ancestors over a period of time when you have known (genetic) interconnections.

“The generations may be estimated, the timeframes may be estimated, but you know that the connections happened because the Y-DNA tells you that there were mutations that were passed on by men who lived in those time periods and those men had descendants who had further mutations and so you can map the family relationships between those men even if you can’t ever name them. ” [11]

This period is still within historical times where one can amass enough DNA information about the timeframe in which the DNA matches lived to possibly develop strong working hypotheses about unnamed ancestors. It is possible to isolate the region where several generations of unnamed ancestors lived, what possible surnames they had, or identify what emerging country or ethnic group that may have been part of in that particular geographical area.

“Lineages are a way that Y-DNA (or mtDNA) can extend our knowledge of our ancestry beyond we would have thought possible in ‘regular’ genealogy – we can learn about our ancestry even before the time of records. We can map the branching points between ours and our matches’ lines and understand the order and approximate time frame in which our common ancestors lived. We can collect the known information about all the descendant lines from these ‘lineage ancestors’ and draw conclusions about where and perhaps how they lived.” [12]

At some point in time the period of lineages end. However, genetic genealogical testing and research can help bridge the gap to go even further back in time. The period beyond lineages is what Vance calls ‘deep ancestry‘. Deep ancestry is characterized by the mapping of haplogroups based on genetic mutations. These are various haplogroups of descendants that are connected by a common Y-DNA or mtDNA mutation that occurred in a common ancestor, the most recent common ancestor (tMRCA). These mutations can be mapped out in what is known as a haplotree. [13] While Haplogroups can be defined during the time of lineages and genealogies, in the era of deep ancestry it is the only information that might be available for one’s ancestral lineage.

Spencer’s View of Three Different Research Levels

The other genealogist that has influenced my view of geological time is Rob Spencer. Spencer specializes in analyzing genealogical genetic and historic data at the macroscopic level. His main interests are the exploration of genetic genealogy and population genetics at the macro level. His work specifically focuses on analyzing ‘monoparental’ SNPs (mutations in Y and mitochondrial DNA) to trace ancestral migration patterns from prehistoric times to the present. His emphasis is getting the most out of Y-DNA data by applying original algorithms to create informative graphics. [14]

Spencer’s talent and expertise is reflected in the creation of online mathematical modeling tools to analyze large samples of genetic test results and historical data. (See illustration two.) He provides innovative ways to analyze data and graphically portray results in intuitive and elegant ways. He actively shares his knowledge and mathematical applications through presentations and online documentation. [15]

Illustration Two: Spencer’s Online Tools and Data Sources

I have utilized many of Spencer’s online mathematical tools to analyze Y-STR and Y-SNP test results and his map modeling of surname distributions in Wales. Two of his more popular online programs are the SNP Tracker, a tool that helps genealogists track and map the migration paths of Y-SNP genetic mutations through time, and the Y STR Clustering and Dendrogram Generation tool, which provides a graphic portrayal of the genetic distance of between Y-DNA testers.

The SNP tracker is particularly useful when tracking Y-DNA SNP lineages in Vance’s Deep Ancestry phase and the Period of Lineages. Illustration three depicts the general mogratory path of my Y-DNA linneage in the past 10,000 years.

Illustration Three: Example of Results of Spencer’s SNP Tracker Using My Lineage of SNP Mutations from my DNA Test Results

The STR Clustering and Dendrogram Generation Tool is very useful in visualizing genetic distance between Y-DNA testers in the context Vance’s Period of Lineages and the Period of Traditional Genealogy. (See iIllustration four.) [16]

Illustration Four: Example of Using Spencer’s STR Clustering and Dendrogram Generation Tool with FTDNA Y-DNA Test Kit Results that are part of the G-Z648 Haplogroup Branch

Similar to David Vance’s three periods of ancestry, Rob Spencer provides a graphic portrayal of tracing one’s ancestor’s based on three levels of research (illustration five).

Traditional genealogical paper trails and research can provide information in the recent past. Beyond 300 years, the paper trail tends to thin out and evaporate. In this research level, genetic genealogy is often used to confirm or refute traditional paper evidence. [17]

Ancestry between 300 and about 1000 years ago depicts a period where surnames may exist but paper trails are not available. For certain European areas on the British Isles, extended Y-DNA genetic lineages with different surnames can be located fairly accurately by date.

Illustration Five: Three Levels of Genealogical Research

The research strategy for genetic genealogy beyond 1,000 years can utilize Y SNP DNA to document genetic lineages through SNP mutations and can be expressed as a haplotree, essentially a family tree that branches at SNP mutations.

“A variety of methods (ancient skeletal DNA, modern tester citations, surnames and census data, and mathematical modeling) can be used to locate SNP events in space and time across the globe, after which simply knowing one’s most recent SNP suffices to reveal a personal paternal journey. Several examples illustrate the great diversity of our paths and origins. The Y haplotree is now so detailed that the SNP trail frequently overlaps paper genealogic records, providing a complete path from paleolithic Africa to the modern era.” [18]

Spencer has documented the utility of analyzing Y STR genetic pair-wise data test results to tease out the genealogical evidence between what he calls your ancestry, your clan, and your migration history levels of research. The illustration provides a good graphic relationship between traditional and DNA based genealogical research.

The use of Y-DNA research can help trace unknown ancestors prior to the use of surnames, pinpoint possible regional areas where ancestors lived, and provide possible links to the recent past. Y-DNA research, coupled with archaeological and paleo-genomic discoveries can also shed light on macro level connections to migration patterns that can be associated with genetic ancestors. [19]

Braudel’s three periods of historical time

As indicated in a previous story, social historians and micro-historians have influenced my approach in developing stories of ancestors. All of these stories involve family subject matter that occurred within the last 10 generations or roughly 300 years ago.

The writings of French historian Fernand Braudel have influenced my way of thinking in another way. Braudel’s work underscores the importance of long-term rhythms and multiple temporal cycles and scales in understanding human history and placing genealogical analysis in this broader view. Ferdinand Braudel’s all encompassing historical method has provided a conceptual historical framework akin to the quest for a unified theory of physics. He has been referred to as “ a grand panjandrum—slightly emeritus—of history.” [20]

Notwithstanding his critics, [21] Fernand Braudel was an extraordinary figure in the field of history. His extensive historical research, unique approach, and innovative concepts have left a lasting impact on the way civilizations as well as everyday people in specific time periods can be understood. His work also highlights the role of geography and time in shaping human agency. Braudel revolutionized historical analysis by introducing a three-tiered approach to understanding historical time, moving away from traditional history focused on political events and “great men”. [22]

Braudel rejected simple chronological time in favor of three interrelated layers of historical duration: [23]

The longue durée focused on slow-moving geographical, environmental, and structural patterns. The slowest and most fundamental level involves environmental and geographical changes, characterized by slow, almost imperceptible shifts and recurring cycles. This forms the backdrop against which all human activity takes place, including the relationship between people and their environment.
Medium-term conjunctures covers economic cycles and social trends. The intermediate level encompasses long-term social, economic, and cultural patterns, typically spanning from a number of generations to two to three centuries. This includes phenomena like economic cycles, demographic shifts, changes in state level dimensions, and Industrial and agrarian growth patterns.
Short-term events (histoire événementielle) deals with surface-level political events and individuals. The most immediate level deals with individual actions, political events, and ‘surface-level’ occurrences. Braudel considered this the least significant level for understanding deeper historical processes.

Illustration Six: A Depiction of Braudel’s Three Layers of Time

Braudel broke from traditional narrative history by rejecting the focus on political elites and “great men” in favor of examining marginal people like slaves, serfs, and the urban poor. He also believed in integrating multiple social sciences into historical analysis. His historical analysis emphasized objective forces over individual human agency in shaping history. For Braudel, the subject matter of history is influenced based on the scale of time that is used to analyze the past. The rise and fall of states, and the short-lived and dramatic moments of the lives of “great men” are replaced by the long-term rhythms of material life.

Braudel’s examination of material life between 1400-1800 in Europe demonstrated how daily life and progress were shaped by these temporal rhythms. His approach combined multiple disciplines, particularly geography and economics, to create a comprehensive view of historical development. [24]

His historical work is impressive with great detail on the wide range of material elements of daily life that influence the how history unfolds at the the individual level and throughout various social levels (local, national, regional , etc). This method allowed him to demonstrate how trading routes, sailing patterns, and economic structures influenced societies over extended periods.

His innovative perspective transformed historical study from focusing solely on political events and “great men” to examining the deeper, more persistent patterns of human civilization. This approach particularly emphasized how material conditions and environmental factors created enduring structures that shaped human possibilities and constraints over centuries. [25]

Braudel also demonstrated quite clearly that history does not exist independently of the historian’s perspectives and prejudices. As with specialists in other disciplines, the historian intervenes at every stage in the making of history.

“All historical work is concerned with breaking down time past, choosing among its chronological realities according to more or less conscious preferences and exclusions. Traditional history. with its concern for the short time span, for the individual and the event, has long accustomed us to the headlong, dramatic. breathless rush of its narrative.

“The new economic and social history puts cyclical movements in the forefront of its research and is committed to the time span. … side by side with traditional narrative history, there is an account of conjunctures which lay open large sections of the past, ten, twenty, fifty years at a stretch ready for … examination.

“Far beyond this second account we find a history capable of traversing even greater distances. a history to be measured in centuries … the longue durée. ” [26]

There is a long litany of scholarly articles and debates on Braudel’s work and the utility of what are the various periods of historical time. I wish to deflect the path of discussion to what his work inspires when it comes to doing genealogical research. I might be oversimplifying or misconstruing his model of historical method so I beg forgiveness in advance. Nevertheless, I share the opinion that the three temporalities of genealogy and history is a useful methodological framework to guide research.

“The longue durée is simply the most stable temporal relation of the longest duration in the problem under consideration. It forms the stabilizing ground against which cyclical variations of other temporal structures are established, and it allows the ordering of historical inquiry.

“It is, in the final analysis, a methodological tool that is constructed for the analysis of particular problems. It is based on a particular focus of one’s research and not necessarily an objective time period that stand alone.” [27]

The ‘longue durée or the long duration for Braudel forms the stabilizing ground against which cyclical variations of other temporal structures or influences are established. It allows the ordering of historical inquiry.

“It is simply the most stable temporal relation of the longest duration in the problem under consideration. It forms the stabilizing ground against which cyclical variations of other temporal structures are established, and it allows the ordering of historical inquiry.” [28]

A Model of Genealogical Time

On the surface, there are strong similarities between the three layer concept of genealogy between Vance and Spencers’ perspectives. Each of their respective genealogical layers or stages of genealogy and research involve similar boundaries of time between traditional genealogy, the period of lineages or clans, and deep ancestry or migration history. References to the Longue Durée have been alluded to in genetic studies. [29]

Braudel’s three temporal layers can provide a comprehensive framework for integrating traditional and genetic genealogical research. The Longue Durée, the foundational layer, can provide an understanding of the correlation between haplogrop migration and the geographical location with:

ancient cultural groups that existed in specific geographical areas;
long-term climate and landscape changes that affected areas where haplogroups lived and migrated; and
geographic patterns of DNA distribution across regions that shaped ancestral migrations. [30]

Braudel’s middle or conjuncture layer of time reveals long historical cycles that can be correlated with historical events in time. This middle layer of time can also be viewed within a genetic genealogical perspective that focuses on Y-STR mutations within Vance’s period of lineages or Spencer’s period of clans. The middle historical time layer can be viewed in terms of tracing SNP and STR Y-DNA mutations in lineages and haplogroups. This historical time layer focuses on:

demographic shifts and genetic lineage patterns across multiple generations;
economic cycles and other social structural patterns that can be identified with migration patterns and movement of lineages and haplgroups;
cultural groups that can be correlated with the location of lineages and clan groupings; and
the identification of surname formation among lineage groups.

Braudel’s ‘event’ layer aligns with traditional genealogical research. Historical events can be identified with family historical stories in the context of the four structural levels identified in a prior story. DNA matches showing recent common ancestors in the last 10 generations can also be aligned with traditional genealogical research. .

By combining these layers, genealogists can contextualize genealogical evidence within broader social and environmental patterns; use genetic data to confirm documentary evidence; and connect individual family events to larger historical forces that shaped ancestral patterns. [31]

This multi-layered approach to genealogical time helps overcome research barriers by providing alternative perspectives when one type of evidence is lacking. The resultant model based on the three major influences discussed above is reflected in illustration seven.

Illustration Seven: Chronological Influences on Genealogical Research

Continuation of the Story

The second part of this story on genealogical time discusses how family history stories that incorporate the three layers of genealogical time will draw on different sources of evidence. The orientation of the narrative of a story will be uniquely tailored based on the sources of evidence..

Sources

Feature Image: The image is a collage of illustrations of genealogical and historical time based on models provided by J. David Vance, Rob Spencer and Fernand Braudel.

[1] Genetic distance measures the number of differences or mutations between two individuals’ DNA test results.

For Y-DNA analysis, a genetic distance of zero indicates an exact match between two people’s DNA results, while higher numbers indicate more genetic differences. It counts the number of mutations between two men’s Y-chromosome DNA results. Each genetic marker difference contributes to the total genetic distance. For example, if one person has a value of 10 at DYS454 and another has 11, this contributes a genetic distance of 1. DYS stands for DNA Y-chromosome Segment in genetic research. It refers to a short tandem repeat (STR) found on the Y chromosome.

For autosomal DNA research, genetic distance measures the length of shared DNA segments in centiMorgans. It is used to determine relationships between any two people, regardless of gender.

Genetic distance is not a direct measure of generations between individuals, but rather indicates genetic divergence. A smaller genetic distance suggests: closer genetic relationship between individuals, a more recent common ancestor, and an higher likelihood of genealogical connection.

The interpretation of genetic distance values varies depending on the number of markers tested in Y-DNA tests, with different significance levels for 37-marker, 111-marker, and Big Y (700 marker) tests.

Genetic Distance, International Society of Genetic Genealogists Wiki, This page was last edited on 31 January 2017, https://isogg.org/wiki/Genetic_distance

Estes, Roberta, Concepts – Genetic Distance, 29 Jun 2016, DNAeXplained – Genetic Genealogy, https://dna-explained.com/2016/06/29/concepts-genetic-distance/

Genetic Distance, Wikipedia, This page was last edited 25 Oct 2024, https://en.wikipedia.org/wiki/Genetic_distance

Understanding Y-DNA Genetic Distance, FamilyTreeDNA Help Center, https://help.familytreedna.com/hc/en-us/articles/6019925167631-Understanding-Y-DNA-Genetic-Distance

Mohler, Melanie, Genetic Distance | YDNA Matches, 3 Jan 2023, Your DNA Guide, https://www.yourdnaguide.com/ydgblog/genetic-distance

[2] A genetic lineage encompasses all descendants of a specific genetic sequence that typically emerges after a new mutation. This concept differs from an allele as it includes descendants with additional mutations while excluding cases where different mutations create the same allele. An allele is a variant form of a DNA sequence at a specific location (locus) on a chromosome. Humans inherit two alleles for each gene. Alleles can differ through single nucleotide polymorphisms (SNPs) or have insertions and deletions of thousands of base pairs. While most allelic variations cause little change in gene function, some can result in different observable traits.

A haplogroup is a genetic population group of people who share a common ancestor and specific genetic mutations. These groups are defined by shared inherited genetic markers that are passed down through either the paternal line (Y-DNA) or maternal line (mitochondrial DNA).

Lineage (genetic), Wikipedia, This page was last edited on 28 August 2024, https://en.wikipedia.org/wiki/Lineage_(genetic)

Haplogroups are identified by initial letters of the alphabet, with refinements using additional number and letter combinations (e.g., A → A1 → A1a). They form a nested hierarchy, where each haplogroup remains part of a preceding haplogroup.

Haplogroups help trace human migration patterns and evolutionary history, connecting modern populations to their ancient ancestors. They originated in Africa and diversified as humans migrated across continents, developing new mutations that created distinct regional patterns.

Haplogroup, Wikipedia, This page was last edited on 8 December 2024, https://en.wikipedia.org/wiki/Haplogroup

Haplgroup, International Society of Genetic Genealogy Wiki, This page was last edited on 1 November 2024, https://isogg.org/wiki/Haplogroup

Estes, Roberta, What is a Haplogroup?, DNAeXplained – Genetic Genealogy, https://dna-explained.com/2013/01/24/what-is-a-haplogroup/

[3] In genealogy research, the “most recent common ancestor” (MRCA) refers to the most recent individual from whom two or more people are directly descended, essentially the point in a family tree where two lineages converge and share a common ancestor; it is the closest ancestor that two individuals share based on their genetic lineage.

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 Recent Common Ancestor, Wikipedia, This page was last edited on 5 November 2024, https://en.wikipedia.org/wiki/Most_recent_common_ancestor

[4] Spencer, Rob, Welcome , Footnote on home pageTracking Back, https://scaledinnovation.com/gg/gg.html?nm=welcome

[5] The Annales School is a French historical movement founded in the early 20th century that revolutionized historical research by emphasizing long-term social history over traditional political and military narratives. Marc Bloch and Lucien Febvre established the movement in 1929 by founding the journal “Annales d’histoire economique et sociale”. The Annales School transformed historical research by expanding its scope beyond traditional political narratives to include the study of ordinary people, social structures, and long-term historical patterns.

The school developed several innovative approaches to historical study. The Annales School emphasized social and economic themes over political or diplomatic history. They introduced the concept of “longue durée” – analyzing historical structures over hundreds of years. They developed “histoire totale” (total history) – a comprehensive approach to studying historical problems. The school also incorporated methods from multiple disciplines including anthropology, geography, sociology, and psychology.

Annales School, Wikipdia, This page was last edited on 18 December 2024, https://en.wikipedia.org/wiki/Annales_school

Yorty, Eric, The Annales School, Metahistory, https://unm-historiography.github.io/metahistory/essays/modern/annales-school.html

Wesseling, H. L. 1978. “The Annales School and the Writing of Contemporary History.” Review (Fernand Braudel Center) 1 (3/4): 185–94

Burke, Peter, The French Historical Revolution: The Annales School, 1929–2014. Cambridge: Polity, 2015

[6] Buckridge, Autumn,Fernand Braudel, Guide to Historiography, https://unm-historiography.github.io/metahistory/essays/modern/fernand-braudel.html

Fernand Braudel, Wikipedia, This page was last edited on 21 November 2024, https://en.wikipedia.org/wiki/Fernand_Braudel

Forster, Robert. “Achievements of the Annales School.” The Journal of Economic History, vol. 38, no. 1, 1978, pp. 58–76. JSTOR, http://www.jstor.org/stable/2119315

Harsgor, Michael. “Total History: The Annales School.” Journal of Contemporary History, vol. 13, no. 1, 1978, pp. 1–13. JSTOR, http://www.jstor.org/stable/260089

Trevor-Roper, H. R. “Fernand Braudel, the Annales, and the Mediterranean.” The Journal of Modern History, vol. 44, no. 4, 1972, pp. 468–79. JSTOR, http://www.jstor.org/stable/1876805

Wesseling, H. L. “The Annales School and the Writing of Contemporary History.” Review (Fernand Braudel Center), vol. 1, no. 3/4, 1978, pp. 185–94. JSTOR, http://www.jstor.org/stable/40240779

Aurell, Jaume, Autbiographical Texts as Historiographical Sources: Reading Fenand Braudel and Annie Kriegel, Biography, vol. 29, no. 3, 2006, pp. 425–45. JSTOR, http://www.jstor.org/stable/23540525.

For works of Braudel:

Braudel, Fernand, The Structures of Everyday Life The Limits of the Possible. Volume I. Civilization and Capitalism 15th-18th Century. Translation from the French Revised by Sian Reynolds. Illustrated. 623 pp. New York: Harper & Row., 1979, https://archive.org/details/fernand-braudel-the-structure-of-everyday-life

Braudel. F. 1972 The Mediterranean and the Mediterranean and the Mediterranean World in the Age of’ Philip II (translated by Sian Reynolds). 2 vols. New York: Harper and Row.

Braudel, Fernand, On History, translated by Sarah Matthews, Chicago: University of Chicago Press, 1980

Braudel, Fernand. “History and the Social Sciences: The Longue Durée.” Review 32, 2 (2009): 171-203

[7] J. David Vance, DNA Concepts for Genealogy: Y-DNA Testing Part 1, 10 Oct 2019, https://youtu.be/RqSN1A44lYU

Part 1 of a 3-part introduction series to Y-DNA for genealogists. This first video focuses on “Why?” use Y-DNA for genealogy – what benefits does it offer and why should genealogists consider using Y-DNA as part of their research?

J. David Vance, DNA Concepts for Genealogy: Y-DNA Testing Part 2, 3 Oct 2019 https://www.youtube.com/watch?v=mhBYXD7XufI&t=355s

Part 2 of a 3-part introduction series to Y-DNA for genealogists. This second video focuses on “What?” for Y-DNA for genealogy – what are STRs and SNPs, what is genetic distance, what is the haplotree, and other related questions

J. David Vance, DNA Concepts for Genealogy: Y-DNA Testing Part 3, 10 Oct 2019 https://www.youtube.com/watch?v=03hRXVg9i1k&t=4s

Part 3 of a 3-part introduction series to Y-DNA for genealogists. This third video focuses on “How?” for Y-DNA for genealogy – how do I use the information provided by Y-DNA tests to advance my genealogy and/or my lineages?

J David Vance, The Genealogist Guide to Genetic Testing, 2020 https://www.amazon.com/Genealogists-Guide-Testing-Genetic-Genealogy/dp/B085HQXF4Z/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=&sr=

[8] Vance created the SAPP (Still Another Phylogeny Program), a tool for automating and visualizing genetic trees. The SAPP is a type of mutation history tree that uses FTDNA data and creates a Y-DNA phylogenetic tree. The program is relatively easy to use and graphically provides an intuitive approach to visualize the possible genetic relationships between various DNA test results. The program is referred to as the SAPP analysis (Still Another Phylogeny Program). The current version that was used in my analysis was SAPP Tree Generator V4.25.

I have used his SAPP to confirm genetic relationships I have previously found through traditional genealogical research. The SAPP results have also documented genetic ties in the lineage period with Y-DNA test kits.

See: Griffis, Jim, Y-DNA and the Griffis Paternal Line Part Four: Teasing Out Genetic Distance & Possible Genetic Matches, 24 Feb 2023, Griffis Family: Selected Stories from the Past, https://griffis.org/y-dna-and-the-griffis-paternal-line-part-four-teasing-out-genetic-distance-possible-genetic-matches-from-str-tests/

For information on the SAPP, see:

David Vance, The Life of Trees (Or: Still Another Phylogeny Program),SAPP Tree Generator V4.25, http://www.jdvsite.com

Dave Vance, Y-DNA Phylogeny Reconstruction using likelihood-weighted phenetic and cladistic data – the SAPP Program, 2019, academia.edu, https://www.academia.edu/38515225/Y-DNA_Phylogeny_Reconstruction_using_likelihood-weighted_phenetic_and_cladistic_data_-_the_SAPP_Program

Y-DNA tools, International Society of Genetic Genealology Wiki, This page was last edited on 30 June 2022, https://isogg.org/wiki/Y-DNA_tools

Sennet Family Tree Blog, The SAPP is up and running: a phylogenetic analysis of Sennett surname project members, 8 May 2021, https://sennettfamilytree.wordpress.com/2021/05/08/the-sapp-is-up-and-running-a-phylogenetic-analysis-of-sennett-surname-project-members/

[9] Vance, David, Group Project Administration Series: Shifting Your Mindset on Genealogy, 3 Apr 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/growing-panes/

[10] Vance, David, Y-DNA: Three Periods of History, Page 13 of a readable transcript of the narration in a YouTube video at https://drive.google.com/open?id=1CdU…, The video is by J. David Vance, DNA Concepts for Genealogy: Y-DNA Testing Part 1, 10 Oct 2019, https://youtu.be/RqSN1A44lYU

Vance, J. David, Figure 4-8 The Three “Phases” of our Ancestry where Y-DNA can help, Genealogist’s Guide to Y-DNA Testing for Genetic Genealogy, Self Published, 2014, Page 41 of ebook.

[11] Page 13-14 of a readable transcript of the narration in a YouTube at https://drive.google.com/open?id=1CdU…, the video is by J. David Vance, DNA Concepts for Genealogy: Y-DNA Testing Part 1, 10 Oct 2019, https://youtu.be/RqSN1A44lYU

[12] J. David Vance, The Genealogist’s Guide to Y-DNA Testing for Genetic Genealogy. N.p: J. David Vance, 2020. Page 41

[13] A haplotree is a branching diagram that shows evolutionary relationships between biological species based on their genetic characteristics. It specifically illustrates how different genetic lineages are connected through common ancestors, with two main types being Y-DNA (paternal) and mtDNA (maternal) haplotrees. Haplogroups are represeted as branches in the haplotree. Haplogroups are labeled with letters A to Z, though the naming order is based on discovery rather than genetic relationships. Each haplogroup can be further divided into subclades using combinations of numbers and letters (e.g., A → A1 → A1a). The haplotree serves as a tool for visualizing genetic relationships between different human populations; understanding human migration patterns and evolutionary history; and connecting individuals to their genetic ancestors.

A haplotype is a group of alleles in an organism (i.e. a person) that are inherited together from a single parent, and a haplogroup is a group of similar haplotypes (i.e. a group of people) that share a common ancestor with a single-nucleotide polymorphism mutation.

For Y-DNA, a haplogroup may be shown in the long-form nomenclature established by the Y Chromosome Consortium, or it may be expressed in a short-form using a deepest-known single-nucleotide polymorphism (SNP).

See for example:

Building the Y-DNA Haplotree, FamilyTreeDNA Blog, https://help.familytreedna.com/hc/en-us/articles/6189226252815-Building-the-Y-DNA-Haplotree

Runfedt, Goran, Introducing the Discover™ Classic Tree for Y-DNA, 5 June 2024, FamilyTreeDNA Blog, https://blog.familytreedna.com/classic-tree-for-y-dna/

Haplogroup, Wikipedia, page was last edited on 12 August 2022, https://en.wikipedia.org/wiki/Haplogroup

Haplogroup, International Society of Genetic Genealogy Wiki, This page was last edited on 27 June 2022, https://isogg.org/wiki/Haplogroup

[14] Spencer, Rob, Case Studies in Macro Genealology, Presentation for the New York Genealogical and Biographical Society, Slide Three, July 2021, http://scaledinnovation.com/gg/ext/NYG&B_webinar.pdf

[15] See the following:

Spencer, Rob, The Big Picture of Y STR Patterns 22-24 Mar 2019, 14th International Conference on Genetic Genealogy, Houston, https://scaledinnovation.com/gg/ext/RWS-Houston-2019-WideAngleView.pdf

Spencer, Rob, “Convergence” Understood, 22-24 Mar 2019, 14th International Conference on Genetic Genealogy, Houston, https://scaledinnovation.com/gg/ext/RWS-Houston-2019-Convergence.pdf

MacGregor, Keith, Maurice Gleeson, Susan Miller and Rob Spencer, The High Road to Scotland is Paved with DNA, Scottish North American Leadership Conference, 4-6 Dec 2020, https://scaledinnovation.com/gg/ext/st/HighRoadSlides.html

Spencer, Rob, Case Studies in Macro Genealogy, New York Genealogical and Biographical Society, Jul 2021, https://scaledinnovation.com/gg/ext/NYG&B_webinar.pdf

Spencer, Rob, Putting Ancestors’ SNPs on the Map by Rob Spencer, Videoconference for the Genealogical Forum of Oregon, 27 Jan 2024, YouTube, https://www.youtube.com/watch?v=xQFim70AU3c

PDF of Slide Presentation: https://scaledinnovation.com/gg/ext/Portland-Jan2024.pdf

Spencer, Rob, Extending Time Horizons with DNA, RootsTech The 2022 Sessions, https://scaledinnovation.com/gg/ext/rt22/index.html

Video of March 3, 2022 Presentation: https://youtu.be/wppXD1Zz2sQ
Slides for the Three Sessions, https://scaledinnovation.com/gg/ext/rt22/rt22slides.pdf

Spencer, Rob, Research Reports Tracking Back, https://scaledinnovation.com/gg/gg.html?nm=reports

The following reports can be found at this web link:

Introduction to Distance Dendrograms
Why use STR data and not SNP data?
STR Clades
STR Dates and Founders
Extinctions and Bottlenecks
Convergence
Distributions of tMRCAs
Extending STRs into Deep Time
Neolithic Migrations Differ by Gender
Mitochondrial DNA
Contingencies
Historic Figures
Surnames and Patronymy
Searching for Models
Frontier Demographics
Highway Maintenance
Ancient Sites
Clans and SNPs
Surname Similarity by Deep Ancestry
Finding Boundaries
Locating SNPs with Census Data
Superclades in Surname Projects
County Clustering by Surname
Surname Diffusion
Hearth Tax Records
STR Date Refinements
Internal Migration in Victorian Britain
History in the Maps of Surnames
Revisiting the N/2 Rule
Surnames and the Y Haplotree
Ancient Sites, Revisited
STR to SNP Prediction
A Goldilocks Problem
A Quantitative Look at mtDNA
City Growth
Frontier Migration

[16] The dendrogram is similar to a family tree. The individual DNA testers are the dots at the right of the diagram. On a traditional family tree, branch points are ancestors. On the dendrogram branch points are not people but points in time when genetic changes occurred.

Time moves backward to the left. Time is measured in generations which roughly equates to 31 years per generation. I have added how many years before present (ybp) and the approximate year each given generation mark represents. Each Line represents a Y-DNA test kit. The defined haplogroup for each test kit is listed. Depending on the type of D-DNA test completed, some of the haplogroups are very detailed while others are very general. The name of the paternal ancestor that was provided by each individual who completed the Y-DNA test is also listed.. I have also highlighted an area that depicts the range of time where the use of surnames became part of family tradition.

[17] Spencer, Rob, The Big Picture of Y STR Patterns 22-24 Mar 2019, 14th International Conference on Genetic Genealogy, Houston, https://scaledinnovation.com/gg/ext/RWS-Houston-2019-WideAngleView.pdf

[18] Spencer, Rob, Extending Time Horizons with DNA, 3 Mar 2022, RootsTech 2022 session, https://scaledinnovation.com/gg/ext/rt22/index.html

[19] Spencer, Rob, The Big Picture of Y STR Patterns 22-24 Mar 2019, 14th International Conference on Genetic Genealogy, Houston, https://scaledinnovation.com/gg/ext/RWS-Houston-2019-WideAngleView.pdf

Spencer, Rob, Case Studies in Macro Genealogy, New York Genealogical and Biographical Society, Jul 2021, https://scaledinnovation.com/gg/ext/NYG&B_webinar.pdf

[20] Shenker, Israel, Historian’s ‘Three Movements’ Method Acclaimed and Censured, 14 Jun 1976, New York Times, Page 36, https://www.nytimes.com/1976/06/14/archives/historians-three-movements-method-acclaimed-and-censured.html

[21] Several key criticisms were leveled at Braudel’s approach to historical time layers. His emphasis on continuity and his resistance to discontinuity was problematic. Critics noted that Braudel was uncomfortable with the notion of ruptures and discontinuities in history, preferring to stress inertia and long-term continuities.

His view diminished human agency. J.H. Elliott criticized that “Braudel’s Mediterranean is a world unresponsive to human control” where “Braudel’s mountains move his men, but never his men the mountains”. This led to questionable conclusions, such as attributing the expulsion of Jews from Spain primarily to overpopulation rather than human decisions.

Many criticized his views that diminished human agency in making historic changes. His position espoused in his writing implied that history lies beyond individual consciousness and actions.

His focus on long-range structures caused him to treat significant disruptive events superficially. This preference for objective explanations and deep structures sometimes came at the expense of understanding important historical turning points and human decisions

Robinson, Paul, In the Basement of History, 16 May 1982, The New York Times Book Review, Section 7, Page 9, https://www.nytimes.com/1982/05/16/books/in-the-basement-of-history.html

Harris, Olivia. “Braudel: Historical Time and the Horror of Discontinuity.” History Workshop Journal, vol. 57, 2004, p. 161-174. Project MUSE, https://muse.jhu.edu/article/169717.

Shenker, Isreal, Historian’s ‘Three Movements’ Method Acclaimed and Censured, 14 Jun 1976, New York Times, Page 36, https://www.nytimes.com/1976/06/14/archives/historians-three-movements-method-acclaimed-and-censured.html

Rao, O.R., Review of “A History of Civilizations”, Fernand Braudel, Journal of KrishNamurti school, Issue 1, https://www.journal.kfionline.org/issue-1/review-of-a-history-of-civilizations-fernand-braudel-2

Elliott, John H. (3 May 1973), “Mediterranean Mysteries”, The New York Review of Books, 20 (7): 25–28, https://www.nybooks.com/articles/1973/05/03/mediterranean-mysteries/

Mulroney, Kelly A. “Discovering Fernand Braudel’s Historical Context.” History and Theory, vol. 37, no. 2, 1998, pp. 259–69. JSTOR, http://www.jstor.org/stable/2505469

McNeill, William H. “Fernand Braudel, Historian.” The Journal of Modern History, vol. 73, no. 1, 2001, pp. 133–46. JSTOR, https://doi.org/10.1086/319882

[22] Most discussions of Braudel’s work reference his discussions of three layers of historical time. However Braudel, at times, discusses four hierarchical levels of temporal change.

One level, referred to as events, concern the individual actions that Braudel (1972: 21) calls “traditional history”: kings, battles, treaties, etc..

Braudel. F. , The Mediterranean and the Mediterranean and the Mediterranean World in the Age of’ Philip II (translated by Sian Reynolds). 2 vols. New York: Harper and Row. 1972, Page 21

The second level, conjuncture, is Braudel’s term for two intermediate levels of historical duration. Braudel calls the study of conjunctures “social history, the history of groups and groupings” . Braudel divided conjunctures into two kinds: intermediate-term conjuncture., which include wage and price cycles, rates of industrialization. and wars; and long-term conjunctures, which refer to secular changes like “long-term demographic movements. the changing dimensions of states and empires (the geographical conjuncture as it might be called), the presence or absence of social mobility in a given society. [and] the intensity of industrial growth“

Braudel. F., The Mediterranean and the Mediterranean and the Mediterranean World in the Age of’ Philip II (translated by Sian Reynolds). 2 vols. New York: Harper and Row, 1972, Pages 20 and 899

Y-DNA and the Griffis Paternal Line Part Four: Teasing Out Genetic Distance & Possible Genetic Matches

This is part four of a story on utilizing Y-DNA tests to gain knowledge or leads on the patrilineal line of the Griff(is)(es)(ith) family. This part of the story focuses on the analysis of Y-STR test results to possibly locate genetic ancestors.

Working with Y-STRs (and Y-SNPs) and the various types of tests and Y-DNA tools requires covering the topics of genetic distance, modal haplotypes, ancestral haplotypes and the Most Recent Common Ancestor.

Most Common Ancestor: A Peculiar Concept

A number of genetic studies argue that all humans are related genealogically to each other over what can be considered as surprisingly short time scales. [1] Few of us have knowledge of family histories more than a few generations back. Moreover, these ancestors often do not contribute any genetic material to us [2] .

In 2004 mathematical modeling and computer simulations by a group of statisticians indicated that our most recent common ancestor probably lived no earlier than 1400 B.C. and possibly as recently as A.D. 55. Additional simulations, taking into account the geographical separation of continents and islands and less random patterns of mating in real life suggest that some populations are separated by up to a few thousand years, with a most recent common ancestor perhaps 76 generations back (about 336 BCE), though some highly remote populations may have been isolated for somewhat longer [3]

The most recent common ancestor of a group of men and the most common ancestor of man are concepts used in genetic genealogy. Their definition and explanation are not entirely intuitive. They can be difficult to comprehend and what do they actually mean. For most of us it is a bit difficult to accept or even comprehend concepts that rest on mathematics or statistics and not hard data. Archaeologists, genealogists, or historians will never uncover ancient artifacts or documentation that identify your most recent common ancestor.

The idea of a genealogical common ancestor resists attempts to demonstrate its existence with a genetic, DNA equivalent. As special as either of ‘these recent individuals’ are within our genealogy, it is very likely that most living people have inherited no DNA from these individuals at all.

This may seem like a paradox: a genealogical ancestor of everybody, from whom most of us have inherited no DNA. It reminds us that genetic and genealogical relationships are different from each other. Many close genealogical relatives are nonetheless genetically and culturally very different from each other. Fifth cousins are not far apart genealogically, but they sometimes share no DNA from their common genealogical ancestors at all. [4]

The following video provides an excellent overview of the interplay between different concepts of genealogy and their implications. The video also touches on the concept of common ancestor, identical ancestors point (IAP), or all common ancestors (ACA) point, or genetic isopoint, and the most recent ancestor. [5]

Genetic Distance

While I brought up the concept of most common ancestor for discussion, our main concern is really with something that is more manageable to comprehend in terms of genetic distance: genetic distance based on the most recent common ancestor. It still might be confusing but not mind blowing.

Genetic distance, is a concept used more as an operational concept by FamilyTree DNA (FTDNA). It is a concept that ranks individual test kits according to how close they appear to be to each other based on the number of allele differences on designated short tandem repeats (STRs).

Genetic distance can also be calculated using Single-nucleotide polymorphisms (SNPs) by comparing the time distance between different haplogroup branches. For the most part the concept is used in the context of comparing genetic test results between two or more Y-STR test kits to determine if they are genetically ‘closely related’. [6]

Genetic distance is based on the analysis of STR data, is the result of calculating the number of mutation events which have occurred between two or more individuals in their respective haplotypes. The more STR’s sampled and compared, the more reliable is the estimate of genetic distance.

Most Common Recent Ancestor

In genetic genealogy, the most recent common ancestor (tMRCA) of any set of individuals is the most recent individual from which all the people in the group are directly descended. [7] Estimating TMRCAs is not an exact science. Because it is not an exact science, questions and answers regarding TMRCA should be phased in general terms. For example, is the MRCA likely to be within the time of surnames or is the MRCA more likely to be in the 1`700’s or the 1600’s. Generally, TMRCA concept can be used to give a working theory or hypothesis about which general time frame the common ancestor may have lived.

The results of various type of analyses that calculate genetic distance will point to the most recent common ancestor of a group of men.

The information in Table One was introduced in Part Three of this story and will be used as a basis for discussing my path of discovery for genetic ancestors using the concept of genetic distance and tMRCA. The table displays Y-Chromosome DNA (Y-DNA) STR results for testers in the L-497 Haplogroup project. As reflected in Illustration One, twelve test kits were grouped together based on how they tested for specific SNPs associated with branches in the haplotree.

Illustration One: The One Two Punch of SNP then STR Analysis

Specifically, Table One provides STR data on my haplotype (STR signature), which is highlighted in the table, for 111 sampled STR values. My results are grouped with eleven other men based on our similarity in our respective STR haplotype signatures. We also share similarities in SNP tests and have been grouped in the G-BY211678 haplogroup.

Table One: 111 STR Results for G-L497 Working Group Members within the G-BY211678 Haplotree Branch

Source: FTDNA DNA Results for Y-DNA Group Members of Haplogroup L-497 within the FY211678 haplotree branch | **Click for Larger View**

The table provides the modal haplotype for the twelve individuals (re: third row) and the minimum and maximum values for each of the STRs listed in the table. FTDNA uses the concept of genetic distance (GD) to compare and evaluate genetic resemblance of two or more STR haplotypes. It is at this point we start to compare STRs among potential test kits.

Genetic Distance: What Does It Mean, How is it Used & How to Portray It

A haplotype (haploid genotype) is a group of alleles in an organism that are inherited together from a single parent. [8]

Unlike other chromosomes, Y chromosomes generally do not come in pairs. Every human male (excepting those with XYY syndrome) has only one copy of that chromosome. This means that there is not any chance variation of which copy is inherited, and also (for most of the chromosome) not any shuffling between copies by recombination. Unlike autosomal haplotypes, there is effectively not any randomization of the Y-chromosome haplotype between generations. A human male should largely share the same Y chromosome as his father, give or take a few mutations; thus Y chromosomes tend to pass largely intact from father to son, with a small but accumulating number of mutations that can serve to differentiate male lineages.

Haplotypes in Y-DNA testing typically compare the results of Y-25, Y37, Y-67, or Y-111 STR tests. Table Two is an example of my haplotype for the Y-111 test. The haplotype basically represents the unique string of values for each of the STRs that compose the test. They number essentially do not mean much by themselves. They take on meaning when you compare them with other testers or pool my results with others to concoct dendrograms and higher level statistical analyses.

Table Two: Example of the Y-111 Haplotype for James Griffis

Y-111 Haplotype of James Griffis | **Click for Larger View.**

A modal haplotype is an ancestral haplotype derived from the DNA test results of a specific group of people, using genetic genealogy. Within each FTDNA work group that is based on haplogroups, surnames, geographical area, or other categories, typically test results are grouped on the basis of the most recent common ancestor that is based on a modal haplogroup. [9]

The modal haplotype is found on the third row of the table One. My results are found on the fourth row of the table for Kit number 851614. Click on the image for a viewable version. The table also provides the minimal allele values for each STR marker and the maximum allele values for each marker for comparison.

The ancestral haplotype is the haplotype of a most recent common ancestor (tMRCA) deduced by comparing descendants’ haplotypes and eliminating mutations. A minimum of three lines, as distantly related as possible, is recommended for deducing the ancestral haplotype. This process is known as triangulation. For FTDNA testing, ancestral haplotype basically refers to the haplotype of the tMost Recent Common Ancestor (tMRCA). In genetic genealogy, the Most Recent Common Ancestor (tMRCA) is the ancestor shared most recently between two individuals. [10]

For Y-DNA, the Most Recent Common Ancestor (tMRCA) is defined as the closest direct paternal ancestor that two males have in common . One of the questions all genealogists seek to answer is when a mutation occurs. We want to know when a mutation occurs and how closely we are related to others that have similar SNP or STR mutations. Unfortunately, that question, without traditional genealogical ancestral information, is very difficult to answer.

For the past two decades, many researchers have attempted to reliably answer that question. The key word here is ‘reliably’. The general consensus is that the occurrence of a SNP is someplace, on average, between 80 and roughly 140 years. The topic is hotly debated, and many factors can play into SNP age calculations. [11]

Since STRs mutate faster than SNPs and can also have a likelihood of mutating back to an original configuration, the estimate of the age of a STR mutation is challenging and depends on the specific STR since they each mutate at different rates. Given the nature STRs, the strategy for locating tMCRA with STRs relies on the concept of genetic generations (e.g. genetic distance). Translating genetic distance to years relies on statistical probabilities based on (a) the specific STR markers tested and (2) the number of STR markers used in calculations.

FTDNA Genetic Distance and Y-DNA STRs: Individual Matches

The main feature of FamilyTreeDNA’s Y-STR tests (Y-37 through Y-111) are finding Y-DNA matches. Like most DNA tests for genealogy, the test is most useful when compared to other people. The key question is, “When was the last common ancestor with this match?” When that is not obvious from comparing known genealogies, the genetic distance is the metric used to compare and estimate how far back in time the connection goes to identity the Most Recent Common Ancestor (tMRCA). Is the connection in recent times, just behind that genealogical brick wall, or in ancient, prehistoric times?

The FTDNATiP™ Report (TiP for Time Predictor) translates the Genetic Distance (GD) statistic into a time unit in predicted ‘years ago’. Depending on the average rate of mutation for sampled marker STRs, the number of differences between two samples (individuals) grows larger as the number of generations back to a common ancestor increases. FTDNA uses this idea to limit the number of matches shown in their match reports. As reflected in Table Three, if you have a 12 marker test (Y-12 STR test), their cut off is a genetic distance of one (one mutation difference), for their Y-37 marker tests the report cut off is at a genetical distance of 4, at 67 markers it is 7, and at 111 markers the report cut off is 10. [12]

Table Three: FTDNA Limits on Genetic Distance Based on Level of STR Test

Test Level	GD Limit for Matches
Y-12	0 or 1 if they are in the same working group project
Y-25	2
Y-37	4
Y-67	7
Y-111	10

In general, the closer the match in haplotypes between two individuals, the shorter the time back to a most recent common ancestor. For instance, if two individuals share the allele values for 35 out of 37 STR markers, they almost certainly share a more recent common ancestor than two individuals who share 25 out of 37 markers.

When it comes to calculating the genetic distance of a common ancestor, which STRs are different between the two individuals is more important that how many differences there are. This is due to the fact that STRs can behave differently from their expected mutation rates and because some STRs mutate faster than others. Regardless of whether one takes a 12 37, or 111 STR marker test, a distance of four matters more based on the mutation rates for each of the four markers that are different.

The following tables indicate the mutation rates for each of the STRs that are used for the various STR tests. [13]

Table Four: Mutation Rates for STRs 1 Through 37

STRs 1 through 37 | Click for Larger View

Table Five: Mutation Rates for STRs 38 – 67

Table Six: Mutation Rates for STRs 68 – 111

As mentioned earlier, calculating the Time to Most Recent Common Ancestor is based on probability and is not an exact science. We can identify the most likely time that a common ancestor might have lived, but there will always be a degree of uncertainly. It is better to think of “the Most Recent Common Ancestor” (tMRCA) as a range of time rather than a point in time. [14]

The following four charts show (noted by the dark line) the average number of generations that Y-DNA matches will share a common ancestor based on genetic distance. The statistical confidence levels are based large population samples and the two lighter lines show a band or range in which 95 percent of the matches will fall. The charts indicate where the FTDNA ‘cut off’ occurs. Notice that as you test more STR markers, the genetic distances also go up for the same number generations. For the Y chromosome these rates assume a 31 year generation and basing years ago from a 1955 “present date”. [15]

As illustrated in the following four illustrations, the statistical variabiability in determining the range of generations based on the concept of genetic distance can vary widely. Even comparing genetic distance with 111 STR test results, one will have a wide statistical variance. A genetic distance of 2 for a Y-111 comparison will mean that the match is within a 95 percent confidence interval of 2-10 generations. If a generation is around 31 years, then the match is equivalent to 62 – 320 years. Translating this range to ‘years before present would be 1955-62= 1893 CE and 1955-320= 1635 CE. That can be a wide range if you are looking for genetical matches. [16]

Illustration Two: Relationship of Genetic Distance to Generations at Y 12

Illustration Three: Relationship of Genetic Distance to Generations at Y37

Illustration Four: Relationship of Genetic Distance to Generations at Y67

Illustration Five: Relationship of Genetic Distance to Generations at Y111

Up until very recently, there were two methods to determine the GD.: the Step-Wise Mutation Model and the Infinite Allele Model. [17] In 2022, FTDNA released Age Estimates based on the Big Y-700 test. test results The millions of slow-mutating Y-SNP markers tested by Big Y together with the faster-mutating but fewer Y-STR markers derived revised the Time to Most Recent Common Ancestor (TMRCA) estimates of each branch on the Y-DNA haplotree. [18] Also in 2022, FTDNA updated FTDNATiP™ Report using Big Y haplotree TMRCA estimates from hundreds of thousands of pairs of Y-STR results from Big Y testers and built models to predict the most likely TMRCA ranges for each Y-STR marker level and genetic distance. [19]

Most mutations only cause a single repeat within a STR marker to be added or lost. For these markers, the Step-Wise Mutation Model is used. For example in Table Seven, comparing my results (Kit Number 851614) with Kit number 125476, who also lists a William Griffis as a Paternal Ancestor, the values of two STR markers differed by one value (see below), which means our GD is 2.

Table Seven: Comparison of Two STR Markers

Kit Number	DYS389ii Allele Value	DYS576 Allele Value
851614	28	18
125476	29	17

In some cases, an entire marker is added or deleted instead of a single repeat within a marker. This is believed to represent a single mutation in the same way that the addition or subtraction of a repeat is a single mutation event. For this reason, FTDNA uses the Infinite Allele Model in these cases. When an STR simply does not exist in an individual, this is called a null value. When a marker is missing, the value is listed as 0.

Multi-copy STR markers appear in more than one place on the Y chromosome. These are reported as the value found at each location, separated by hyphens. For example, in table one you may see DYS464= 12-13-13-13 or 12-12-13-13-13 or 12-13-13-13-13-13 . This means that the STR marker DYS464 has a unique number of repeats in each location. These locations are usually referred to as DYS464a, DYS464b, DYS464c, etc.

An example of this situation is illustrated in Table Eight by comparing my STR results in Table One (Kit Number 851614) with Kit Number 31454 (whose Paternal Ancestor is William Wamsley) and 285488 (whose self reported paternal ancestor was George Williams).:

Table Eight: Comparison of Multi-Copy STR Markers

Kit Number	DYS 464a	DYS 464b	DYS 464c	DYS 464d	DYS 464e	DYS 464f	Total GD
851614	12	13	13	13
31454	12	12	13	13	13		2
285488	12	13	13	13	13	13	2

Within multi-copy markers, there are two types of mutations, or changes, that can occur: marker changes and copy changes. Marker changes (changes in how many repeats are within a marker) are counted with the Step-Wise Mutation Model. Copy changes (changes in the number of markers, regardless of how many repeats are in each) are counted with the Infinite Allele Model.

In the example illustrated in Table Eight, if we compare Kit 31454 to my kit 851614, the allele value for DYS464b is different by one (marker change) and also 31454 has an additional copy (DYS464e), which totals to a genetic distance of 2. Comparing kit 285488 with my kit reveals no marker changes in DYS464a-d but two additional copy changes (DYS464e-f), which totals to a GD of two.

Adding together the GD for each marker in two people provides the overall GD for those two people. When a GD becomes ‘too great’, it is unlikely that the two people share a common ancestor within a ‘genealogical timeframe’, so FTDNA establishes a upper level limit for reporting matched based on GD.

Table Nine provides a practical example of FTDNA’s strategy of comparing the differences between haplotypes of individual test results based on similar haplogroups. I have listed the surname of each of the testers and the STR test they completed (re: Y-37, Y-67, Y-111, or Big Y 700 test. The table also provides information on the most recent haplogroup branch their respective tests were able to document. A Big Y 700 test provides results for 700 STR and therefore can provide the most granular test results for haplogroup designation. The table also indicates the self reported earliest known paternal ancestor for the tester.

Table Nine: STR Haplotype Matches with James Griffis Based on Y-37 Test

Kit No.	Surname	STR Markers Tested	Genetic Distance (GD)	Likely Common Ancestor (Genera- tons) [12]	MRCA Based on GD [12]	Earlest Known Ancester
125476	Griffith	37	2 Steps	8 (2-20)	1650 CE	William Griffis
39633	Compton	37	2 Steps	8 (2-20)	1650 CE	Unknown
154471	Williams	111	4 Steps	3(7-15)	1700 CE	William Williams
285488	Williams	700	4 Steps	3(7-15)	1700 CE	George Williams
294448	Williams	111	4 Steps	3(7-15)	1700 CE	George Williams
285458	Williams	111	4 Steps	3(7-15)	1700 CE	George Williams
36706	Williams	67	4 Steps	11(4-22)	1500 CE	William Williams
149885	Gough	37	4 Steps	14(6-28)	1300 CE	Gough

Source: FTDNA myFTDNA Y-DNA Match Results for James Griffis

As illustrated in Table Nine, although the tester whose last name is Griffith (first. row of the table) only tested for the Y-37 test, his test results are 2 steps different from my test results. If we look at Illustration Three above, this means I and Mr. Griffith share a common ancestor around 8 generations ago or between 2 to 20 generations.. Eight generations would be around the revolutionary war period.

There is another test kit that is 2 steps different from my test kit results. The test kit 39633, who has a surname of Compton appears to be as close as Mr. Griffith. I do not have any traditional genealogical documentation that references an individual with the last name of Compton. Rather than dismiss the results, one needs to look ‘outside the box’ in terms of critically analyzing the results. I may need to reach out to this gentleman to see what potential connections we might have. Also, based on the statistical confidence levels associated with the Y-32 STR tests, the MRCA may be as far back as 20 generations or 620 years ago which is around 1400 CE.

The remaining six testers are four steps different from my test results. While I know there are no individuals who are related in the past three generations, perhaps 15 to 22 generations back there might be a common ancestor. The outer range would be around 682 years ago or around 1340 CE. which would be before the use of surnames.

Based on the results, further research into the background of Mr. Griffith, whose earliest known ancestor was a ‘William Griffis from Hungton, NY” may lead to promising results! 12 generations would be around the early colonial era (1650). It may also be worthwhile to look into the Williams’ connections!

Phylogenetic Trees: Graphic View of Genetic Distance at the Lineage Level

In addition to analyzing and providing Y-DNA test results, FTDNA provides a wide platform of ways in which DNA results are analyzed and the results are packaged for consumers to identify possible genetic matches. There are also a number of analytical tools that have been developed by individuals that compliment or enhance the ability to assess genetic distance.

I can complement the second stage of an analysis by reviewing the results of genetic distance that we just discussed in a number of program generated mutation history trees. These types of programs give a pictorial representation of how the different members of a lineage may be related.

The branching pattern derived from the DNA mutations may very well correspond to the branching pattern that one might see in a traditional family history tree if we were able to trace it all the way back with documentary evidence to the MRCA (Most Recent Common Ancestor). The Mutation History Tree can give us important clues regarding which individuals are likely to be on the same branch of the overall tree, and who is more closely related to whom. This in turn can help focus further documentary research.

One type of mutation history tree has been developed by David Vance that uses FTDNA data that creates a Y-DNA phylogenetic tree. The program is relatively easy to use and graphically provides an intuitive approach to visualize the possible genetic relationships between various DNA test results. The program is referred to as the SAPP analysis (Still Another Phylogeny Program). The current version that was used in my analysis was SAPP Tree Generator V4.25. [20]

The program uses STRs from any of the STR tests (e.g., Y25, Y37, Y67, Y111), to construct a Y-DNA phylogenetic tree. It also has the ability to incorporate the SNPs found in BigY tests to fine-tune the genetic links and estimated times to the most common recent ancestor. The program can also incorporate known names and birth dates of ancestors to further fine-tune the analysis.

The program provides:

STR Table. This table is included to verify the STR input. It starts with the calculated Group Modal Haplotype for your input set followed by all the input kits with the off-modals colored.
Original Genetic Distance Table. This table calculates genetic distances (GDs) from the input STR results. It should match closely with GD calculations from other tools and commercial companies.
Adjusted Genetic Distance Table. This table re-calculates the GDs based on the tree that SAPP has just calculated. It will correct for any convergence that may have occurred in the calculated tree.
Kit to SNP/Genealogy Cross-Reference. This table summarizes the input SNP and Genealogy data showing the +. -. or ? status against the various kits.
The Image or Web version of the Tree File. The program creates a downloadable file containing the phylogenetic tree. Normally the tree is drawn as a graphic, as indicated in Illustration Six.

Illustration Six: Explanation of the SAPP Phylogenetic Tree

Utilizing the STR results, SNP data, and self reported paternal ancestor information for the 12 tests kits found in Table One, the following phylogenetic tree was created (click on the image of the thumbnail of the tree to be able to actually see the table). I have provided a PDF version of the Phylogenetic Chart which allows you to enlarge the image to get a better view.

Illustration Seven: Phylogenetic Tree Results for FTDNA STR Test Results for Individuals within the G-BY211678 Haplogroup (Click for Larger View)

The phylogenetic tree reveals three major genetic groupings of the 12 test kit results. One of those groupings tie my results (FTDNA Kit Number 851614) with an individual whose surname is Griffith (FTDNA Kit Number 285458) and claims the same paternal ancestor, William Griffis see Illustration Eight.

Illustration Eight: Close Up of Phylogenetic Tree

The following are the original and adjusted genetic distance tables generated by the SAPP program. The number of STRs tested are listed on the diagonal in blue. Cell colors refer to the number of STRs tested – cells of different colors are not directly comparable.
Red numbers indicate where adjusted genetic distances are different from original calculation.

Table Ten: SAPP Generated Original Genetic Distance between the 12 Test Kits.

Table Eleven : SAPP Generated Original Genetic Distance between the 12 Test Kits.

Based on the SAPP results, consistent with the FTDNA analysis, it is estimated that the most recent common ancestor between me and Mr. Griffith is approximately 8 generations or 248 years ago (estimating a generation to be 31 years) which would mean the MRCA was born around 1772. The birth date of William Griffis was 1736.

The results of the SAPP analysis suggests that there possibly may be an additional three haplotree branches, based on differences between STR haplotypes among the twelve test kits.

The phylogenetic chart indicates that the MRCA for all of the twelve test kits is estimated at 23 generations. The MRCA was born around 1500 CE for the G-BY211678 haplogroup. The Node #13 of which I and Mr. Griffith are representatives has the strongest connection in the tree. M=Test kits that indicates the ancestral person as William Williams or William Walmsley appear to have a MRCA 3 generations ago (born around 1850).

Genetic Distance at the Macro Level: Distance Dendrograms

The creation of dendrogram is another tool to use when analyzing STR data. Dendrograms can provide insights into macroscopic patterns in Y-DNA genetics and possible genetic matches of present day Y-DNA testers. The diagram based approach of a dendrogram is visually intriguing. Distance dendrograms are software-generated diagrams that convey relationships based on distance measured either in years or generations. Statistically, the dendrograpms used in the present context for genealogy are constructed by hierarchic clustering and the UPGMA method and are more focused on macroscopic genetic patterns. They complement other tools that focus on family level matches. [21]

Up until this point in the story we have discussed computing tMRCA based on the concept of genetic distance (GD). This sort of pairwise tMRCA analysis is subject to a signfiicant range of statistical uncertainty (as reflected in the above tables for generational distance).

A tMRCA can also be calculated between a single DNA tester and the estimate pattern of a chosen ancestor using a modal haplotype. If you have a large enough set of DNA test kits to sample, the ancestral haplotype will be close to that unknowable MRCA. However, this type of averaging still creates a wide level of variance for individual contemporary testers to compare their results with this ‘statistical archetype’.

The dendrograms generated in Rob Spencer’s model is based on a ‘whole-clade’ estimation of the MRCA. The MRCA for an entire clade (haplogroup branch) can be determined based on a common ancestor or a target SNP. The distribution of pairwise MRCA’s for a number of selected DNA kits in a given clade can be fit into a statistical curve fitting process (e.g. lognormal distribution). This curve fitting process is done on a specific group of DNA kits using statistical methods that are way above my pay grade. [22]

The scale of the data and graphics can reveal large scale, high-level patterns of when one person became the descendant of all others (single founder clades), patterns of descent from a single colonial founder in the America (typically one person is the descendant of all in America), and other demographic patterns that are not apparent using other methods of presenting DNA test results.

Dendrograms are ‘close cousins’ to family trees. The Y-STR Dendrogram is a diagram similar to a family tree. Individual DNA testers are the dots at the right (if the dendrogram is horizontal) or at the bottom (if the Dendrogram is vertical). Time moves backward to the left (if horizontally depicted) or down and up( vertically presented). On a traditional family tree, branch points are actual ancestors. In the dendrogram the branch points are generally not specific people but points in time when genetic mutations or changes occurred. In some cases, with good paper genealogy, branch points can be matched to specific ancestors. [23]

Looking at dendrograpm from another angle, they are graphic renderings of a statistical analysis which compares the differences of STR allele values between a group of DNA testers to determine the most recent common ancestors (tMRCA) between a group of testers. One of the key properties of a distance dendrogram is that if the input distances are accurate and consistent, then the graphic will completely and correctly represent a family tree. If we had a sufficient set of testers who had done DNA tests and tMRCAs could be calculated for all pairs with complete accuracy, then the dendrogram would be an accurate family tree.

You can demonstrate the relatiohsip between dendrograms and family trees for yourself with the Distance Tree Introduction interactive tool, and also for larger and more realistic family trees with the Family Simulator, both created by Rob Spencer.

The major limitation to the accuracy of the dendrogram trees is the statistical and random nature of STR mutations. In general, dendrograms constructed from Y12 or Y37 data will be reliable, while those built with Y111 or Big Y700 data data will be sufficient to see large-scale patterns (“macro genetics”) and in many cases can be close approximations to the true family tree. [24]

One important difference between a dendrogram and a family tree is that a dendrogram defines only the “leaf nodes”. A dendrogram does not “know” that there are other nodes that represent people on the diagram. The joining nodes or points are mathematical constructs. Every joining-point or “T” junction in the diagram corresponds to a specific genetic ancestor.

“(Dendograms) are very reliable for exclusion: you can say with very high confidence that two people are not related if there is a strong mismatch of their STR patterns. This is the forensic use of DNA: it’s very powerful in proving innocence while less decisive about proving guilt.” [25]

“Most of us use Y STR data locally to explore personal matches and to help in building family trees. But STRs can tell us much more when we sit back and take a long look. In this talk we use an efficient way to visualize thousands of kits at once. The large-scale patterns explain “convergence”, illuminate ancient, feudal, and colonial expansions, pick apart Scottish clans, identify American immigrant families, allow accurate relative clade dating, let us see the onset of surnames, and reveal the power law distribution of lineages.” [26]

Utilizing STR and SNP data, dendrograms can spot American Immigrant families based on the shape of the dendrogram. Typically there is a gap of 10 plus generations to the next ancestor and an expansion around 5-15 generations ago. [27] Similarly, the advent of surname usage can appear in dendrogram renditions of Y-DNA data. You should expect a common surname only for branches with a tMRCA 25-30 generations ago. Otherwise connections between branches with surnames are essentially random. [28]

Illustration Nine provides a dendrogram of the entire group of FTDNA test kits for the L-497 Haplogroup work group. It includes testers who have minimally completed a Y37 STR test. The L-497 subclade, of which the Griff(is)(es)(ith) paternal line is a part, genetically branched off around 8900 BCE, the man who is the most recent common ancestor of this line is estimated to have been born around 5300 BCE. There are about 1,760 FTDNA based DNA tested descendants, and they specified that their earliest known origins are from Germany, England, United States, and 53 other countries. I included the entire group of test results to show the general shape and patterns revealed in the dendrogram.

STR distance dendrograpms usually contain clear and distinct clades, which are sets of men with a common ancestor. Such clades are characterized by a curved top boundary. in the dendrogram. This is what gives the dendrogram its characteristic ‘slope shape’. If we had test results of all family members the dendrogram would be more square shaped and resemble a family tree. Since that is impossible, there are obviously gaps and the sloping tops for respective clades of the dendrogram is due to the statistical range of the STR mutations and the history of a given haplogroup. .

While the G haplogroup was one of the dominant lineages of Neolithic farmers and herders who as a second wave into Europe, migrated from Anatolia to Europe between 9,000 and 6,000 years ago, they were overtaken by the R Haplogroup as part of a third wave of human migration into Europe and are consequently are presently a minority genetic group in Europe. The male lineages represented by the G haplogroup line are diminished and this is represented in dendrograms with long thin lines through time representing fewer male descendants.

I have highlighted distinctive clades in Illustration Nine as well as indicating the relative position of two possible descendants of William Griffis. To get a better view of this long Dendrogram, I have included a PDF version which allows one to increase the magnification of the image.

Illustration Nine: Dendrogram of FTDNA Y37 to Big Y Test Results for Members of the L-497 D-DNA Group

Y-DNA Dendrogram: L-497 Work Group Y37 and up
**Click for larger View**

If we look a bit closer at the results that are roughly highlighted in Illustration Nine, we can still see the “slope of an approximately family genetic clade structure” for individuals that have a Williams surname. This is reflected in illustration 10. My line of patrilineal descendants have a MRCA with this Williams clade around 14 generations ago. This MRCA was born would be about 434 years before present or about 1488 CE.

Illustration Ten: Dendrogram of FTDNA Y37 – Big Y Test Results for Members of the L-497 D-DNA Group – Blow-Up Portion Where My Test Kit is Located

The dendrogram reinforced the connection with Mr. Griffith’s test kit. The dendrogram shows that we have a common ancestor about 8 generations ago. I highlighted our two kits in the dendrogram.

An alternative view of the dendrogram in Illustration Ten is provided by tightening the generational time scale, is provided in Illustration Eleven. It is the same data but the horizontal scale of the dendrogram has been shortened.

Illustration Eleven: Dendrogram of FTDNA Y37 – Big Y Test Results for Members of the L-497 D-DNA Group – Blow-Up Portion Where My Test Kit is Located, Shortened Time Horizontal the scale

Comparing the SAPP and dendrogram results with the Genetic Distance results reveal similarities. They both point to a genetic relationship with Kit 285458 (Griffith) with my Kit (285614). Both analyses point to a MRCA between our kits at 8 generations.

What’s Next

The next part of the story provides the results of corroborating a Griff(is)(es)(ith) relative, Henry Vieth Griffith, through the analysis of Y-DNA STRs!

Sources

Feature Image of the story is a dendrogram of comparing test kits results of Y-STR tests. Dendrograms are software-generated diagrams that convey relationships based on distance measured in generations. The dendrogram graphically portrays th genetic distance between individuals who are genetically related to me in the past 20 gnerations (e.g. the past 660 years). It is a graphic and mathematical confrmation of my conneection with Henry Vieth Griffith.

[1] Chang J (1999) Recent common ancestors of all present-day individuals. Advances in Applied Probability 31: 1002–1026.

Rohde DLT, Olson S, Chang JT (2004) Modelling the recent common ancestry of all living humans. Nature 431: 562–566.

Rohde DL, Olson S, Chang JT; Olson; Chang (September 2004). “Modelling the recent common ancestry of all living humans” (PDF). Nature. 431 (7008): 562–66. Bibcode:2004Natur.431..562R. CiteSeerX 10.1.1.78.8467. doi:10.1038/nature02842. PMID 15457259. S2CID 3563900

[2] Kevin P Donnelly, The probability that related individuals share some section of genome identical by descent. Theoretical Population Biology Vol 23: Issue 1, 1983, Pages 34–63. https://www.sciencedirect.com/science/article/pii/0040580983900047

[3] Rohde DLT, Olson S, Chang JT (2004) Modelling the recent common ancestry of all living humans. Nature 431: 562–566.

[4] John Hawks, When did humankind’s last common ancestor live? A surprisingly short time ago, 10 Jul 2022, John Hawks Weblog, https://johnhawks.net/weblog/when-did-humankinds-last-common-ancestor-live/

[5] Identical ancestors point , Wikipedia, This page was last edited on 17 December 2022, https://en.wikipedia.org/wiki/Identical_ancestors_point

[6] Genetic Distance, Wikipedia, This page was last updated 7 Dec 2022, https://en.wikipedia.org/wiki/Genetic_distance

Genetic distance, International Society of Genetic Genealology, Page was last updated 31 Jan 2017, https://isogg.org/wiki/Genetic_distance

Understanding Y-DNA Genetic Distance, FTDNA Help Center, https://help.familytreedna.com/hc/en-us/articles/6019925167631-Understanding-Y-DNA-Genetic-Distance

[7] The Most Recent Common Ancestor, International Society of Genetic Genealology Wiki, This page was last editd on 31 Jan 2017, https://isogg.org/wiki/Most_recent_common_ancestor

David Vance, Chapter 16, Estimating Ages to Common Ancestors, David Vance, The Genealogist Guide to Genetic Testing, 2020

[8] Haplotype, Wikipedia, This page was last edited on 11 February 2023, https://en.wikipedia.org/wiki/Haplotype

[9] Modal Haplotype, Wikipedia, This page was last edited on 6 April 2020, https://en.wikipedia.org/wiki/Modal_haplotype

[10] Ancestral Haplotype, International Society of Genetic Genealology Wiki, This page was last edited on 31 January 2017, https://isogg.org/wiki/Ancestral_haplotype

[11] Most Recent Common Ancestor, Glossary of Terms, FTDNA Help Center , https://help.familytreedna.com/hc/en-us/articles/4418230173967-Glossary-Terms-#m-0-12

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

Most recent common ancestor, Wikipedia, page was last edited on 20 October 2022, https://en.wikipedia.org/wiki/Most_recent_common_ancestor

What is YFull’s subclade age methodology, page accessed 9 Aug 2022, https://www.yfull.com/faq/how-does-yfull-determine-formed-age-tmrca-and-ci/

The results and methodology used for determining ages from Big-Y SNPs can also be found in Iain McDonald’s U106 analysis. Read the PDF version at http://www.jb.man.ac.uk/~mcdonald/genetics.html which are updated several times a year.

Iain McDonald, Improved Models of Coalescence Ages of Y-DNA Haplogroups. Genes. 2021; 12(6):862. https://doi.org/10.3390/genes12060862

Poznik, G., Xue, Y., Mendez, F. et al. Punctuated bursts in human male demography inferred from 1,244 worldwide Y-chromosome sequences. Nat Genet 48, 593–599 (2016). https://doi.org/10.1038/ng.3559 for PDF version: https://pure.mpg.de/rest/items/item_2307728/component/file_2307727/content

Shigeki Nakagome, Gorka Alkorta-Aranburu, Roberto Amato, Bryan Howie, Benjamin M. Peter, Richard R. Hudson, Anna Di Rienzo, Estimating the Ages of Selection Signals from Different Epochs in Human History, Molecular Biology and Evolution, Volume 33, Issue 3, March 2016, Pages 657–669, https://doi.org/10.1093/molbev/msv256

Kun Wang, Mahashweta Basu, Justin Malin, Sridhar Hannenhalli, A transcription-centric model of SNP-Age interaction, PLOS Genetics doi: 10.1371/journal.pgen.1009427 , bioRxiv 2020.03.02.973388; doi: https://doi.org/10.1101/2020.03.02.973388

Zhou, J., Teo, YY. Estimating time to the most recent common ancestor (TMRCA): comparison and application of eight methods. Eur J Hum Genet 24, 1195–1201 (2016). https://doi.org/10.1038/ejhg.2015.258.

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

Most recent common ancestor, Wikipedia, page was last edited on 20 October 2022, https://en.wikipedia.org/wiki/Most_recent_common_ancestor

For specific information on history of the haplotree and related nomenclature, see also: International Society of Genetic Genealogy, Y-DNA Haplogrouptree 2019 – 2020, Version: 15.73 Date: 11 July 2020, https://isogg.org/tree/

YFull has a documented system to estimate SNP ages. This is how to get their estimate:

Go to YFull’s SNP search page; 2) Enter a SNP name and click the Search button; 3) A green hyperlink, labeled with a haplotree branch name (e.g., “R-L47”), should be displayed. Click on it; 4) You should now see a branch of the haplotree. Typically, this branch will have two dates: (a) The “formed” date is an estimate of when this branch began to diverge from its surviving siblings. (Extinct siblings are unknowable and therefore ignored.) (b) The “TMRCA” date is an estimate of when this branch’s surviving children began to diverge from each other. (Again, extinct lineages are ignored.)

[12] The GD estimates and estimated number of Generations is based on FTDNATiP™ Reports, Most Recent Common Ancestor Time Predictor based on Y-STR Genetic Distance

Understanding Y-DNA Genetic Distance, FTDNA Help Center, https://help.familytreedna.com/hc/en-us/articles/6019925167631-Understanding-Y-DNA-Genetic-Distance

Concepts – Genetic Distance, DNAeXplained – Genetic Genealogy,, Blog, 29 June 2016, https://dna-explained.com/2016/06/29/concepts-genetic-distance/

[13] J David Vance, The Genealogist Guide to Genetic Testing, 2020 , Chapter 5, https://www.amazon.com/Genealogists-Guide-Testing-Genetic-Genealogy/dp/B085HQXF4Z/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=&sr=

[14] Ibid.

[15] These illustrations of the relationship between genetic distance and generations are from: David Vance, The Genealogist Guide to Genetic Testing, 2020 , Chapter 5

The statistical analyses were based on:

J. Douglas McDonald, TMRCA Calculator, Oct 2014 version, Clan Donald, USA website, Https://clandonaldusa.org/index.php/tmrca-calculator

[16] “For the Y chromosome these rates assume a 31 year generation.”

J. Douglas McDonald, TMRCA Calculator, Oct 2014 version, Clan Donald, USA website, Https://clandonaldusa.org/index.php/tmrca-calculator

[17] “The original FTDNATiP™ Report was based on research by Bruce Walsh, Professor at the University of Arizona, and his 2001 paper in Genetics. Walsh used a theoretical approach to model STR mutation rates and estimate when two people’s’ paths diverged in the Y-DNA haplotree. He used an infinite allele model, which theoretically accounts for markers mutating more than once, which can obscure the true mutation rate.”

Introducing the New FTDNATiP™ Report for Y-STRs, FTDNA Blog, 16 Feb 2023, https://blog.familytreedna.com/ftdnatip-report/

[18] Big Y Age Estimates: Updates and the Battle of Falkirk, FTDNA Blog, 9 Sep 2022, https://blog.familytreedna.com/tmrca-age-estimates-update/

Phylogenetic age estimation, otherwise known as “divergence dating,” has a long and rich history that began in the 1960s. Two general classes of methods have emerged: a strict molecular clock, and a relaxed clock. Sep 19, 2022, FTDNA Blog, https://blog.familytreedna.com/tmrca-age-estimates-scientific-details/

The Group Time Tree: A New Big Y Tool for FamilyTreeDNA Group Projects, FamilyTreeDNA Blog, 15 Feb 2023, https://blog.familytreedna.com/group-time-tree/

[19] Introducing the New FTDNATiP™ Report for Y-STRs, FTDNA Blog, 16 Feb 2023, https://blog.familytreedna.com/ftdnatip-report/

[20] David Vance, The Life of Trees (Or: Still Another Phylogeny Program),SAPP Tree Generator V4.25, http://www.jdvsite.com

Y-DNA tools, International Society of Genetic Genealology Wiki, This page was last edited on 30 June 2022, https://isogg.org/wiki/Y-DNA_tools

[21] Introduction to Distance Dendrograms, Tracking Back: A Website for Genetic Genealology Tools, experimentation, and discussion, http://scaledinnovation.com/gg/gg.html?rr=ddintro

Michael Drout and Leah Smith, How to read a Dedrogram, Wheaton college, https://wheatoncollege.edu/wp-content/uploads/2012/08/How-to-Read-a-Dendrogram-Web-Ready.pdf

Tim Bock, What is a Dendrogram, DisplayR blog, no date, https://www.displayr.com/what-is-dendrogram/

Dendrograpm, Wikipedia, page was last edited on 7 September 2022 , https://en.wikipedia.org/wiki/Dendrogram

Prasad Pai Hierarchical clustering explained, Towards Data Science, 7 May 2021, https://towardsdatascience.com/hierarchical-clustering-explained-e59b13846da8

Tom Tullis, Bill Albert, Hierarchical Cluster Analysis, in Measuring the User Experience (Second Edition), 2013 https://www.sciencedirect.com/topics/computer-science/hierarchical-cluster-analysis

Rob Spencer, Simple Distance Tree, Tracking Back – a website for genetic genealogy tools, experimentation, and discussion, 2023-01-28, ,http://scaledinnovation.com/gg/treeDemo.html

Rob Spencer, Family Tree and Y-DNA Simulator, Tracking Back – a website for genetic genealogy tools, experimentation, and discussion, http://scaledinnovation.com/gg/familySimulator.html

[22] Rob Spencer, Y STR Clustering and Dendrogram Drawing, Click on Discussion Tab, Tracking Back Click – a website for genetic genealogy tools, experimentation, and discussion, http://scaledinnovation.com/gg/clustering.html

[23] Introduction to Distance Dendrograms, Tracking Back: A Website for Genetic Genealology Tools, experimentation, and discussion, http://scaledinnovation.com/gg/gg.html?rr=ddintro

[24] Rob Spencer, The Big Picture of Y STR Patterns, The 14th International Conference on Genetic Genealogy, Houston, TX March 22-24, 2019, http://scaledinnovation.com/gg/ext/RWS-Houston-2019-WideAngleView.pdf Page 28

[25].Rob Spencer, Introduction to Distance Dendrograms, Tracking Back: A Website for Genetic Genealology Tools, experimentation, and discussion, http://scaledinnovation.com/gg/gg.html?rr=ddintro

[26] Rob Spencer, The Big Picture of Y STR Patterns, The 14th International Conference on Genetic Genealogy, Houston, TX March 22-24, 2019, http://scaledinnovation.com/gg/ext/RWS-Houston-2019-WideAngleView.pdf

[27] Rob Spencer, The Big Picture of Y STR Patterns, The 14th International Conference on Genetic Genealogy, Houston, TX March 22-24, 2019, http://scaledinnovation.com/gg/ext/RWS-Houston-2019-WideAngleView.pdf Page 12

Source: Rob Spencer **Click for Larger View**

[28] Rob Spencer, The Big Picture of Y STR Patterns, The 14th International Conference on Genetic Genealogy, Houston, TX March 22-24, 2019, http://scaledinnovation.com/gg/ext/RWS-Houston-2019-WideAngleView.pdf Page 11