Tag: deep ancestry

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 

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

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

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

---

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 

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

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/

[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

[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

This is part three of a four part story on utilizing Y-DNA tests to gain knowledge or leads on the patrilineal line of the Griff(is)(es)(ith) family.

The One-Two Punch of Using SNPs and STRs 

SNP testing is the new age of genetic ancestry. This is primarily due to the technological advances associated with Y-DNA ‘string ‘ and ‘snip’ testing, the relatively straightforward interpretation of SNPs and dating of STR mutations, the increase of SNP discoveries and the explosive growth of Y-DNA database results.

STR testing and analysis represents the advances of genetic genealogy in the ‘early years’ of genetic gnealology (e.g. 2003 – 2014). However, both continue to provide unique strengths for genetic genealogical research.

During the ‘early years’ of Y-DNA testing, at the turn of the millenium, the popularity of obtaining Y-12, Y-25, and Y-37 STR tests increased. The results were generally reliable but oftentimes their results were mixed when compared with potential corroborating results obtained from traditional paper genealogical sources. A variety of statistical errors were documented such as “convergence” and “back mutation”. Through improvements in statistical analysis, the issues related to the statistical reliability of results were relatively increased and understood.

With Y-111 STR level testing common today, many of the accuracy problems noted in the first decade of the new millenium have been lessened. With more STR markers tested, it is possible to end up with matching or closely matching Y-DNA marker results in individuals who do not share a “recent” common ancestor on the male line. Convergence is more plausible in individuals belonging to common haplogroups. [1]

The use of SNPs are a fairly straightforward process of figuring out where a male lands on a current or possibly new branch of the Y-DNA haplotree. The results of SNP tests are intuitive and easy in analyzing a group of other testers because they uniquely identify the haplogroup branches of descent. You can group testers in branches of a haplotree depending on whether their tests confirm or predict specific SNP mutations that represent specific branches of the haplotree. 

In 2020, FamilyTreeDNA added 15,000 new high-coverage Big Y results to the Haplotree analysis, almost 5,000 academic results from present-day men in addition to thousands of ancient DNA results. This resulted in the addition of over 12,500 branches to “The Great Tree of Mankind”. Over 200,000 new unique SNPs were discovered. The growth rate has continued in the past two years. [2]

As indicated in illustration 1, the “One-Two” punch of testing involves using SNPs to provide a general location of Y-DNA testers on the Y-DNA haplotree based on nested haplogroups. Then, ‘the second punch’, if they are available, the use of Y-STR test results can help group test results within recent haplogroup branches and assist in analyzing potential individual matches. The analysis and comparison of individual Y-STR haplotypes can help delineate lineages and tease out branches within the haplotree, fine-tuning relationships between people within the tree.

Illustration 1: Using SNP and STR Results

The accuracy of haplogroup prediction based on Y-STR haplotypes (as opposed to SNP values) depends mainly on the number of STR values that are tested. Haplogroup predictions based on low-resolution Y-12 to Y-25 STR test haplotypes have a low value of confidence and convergence can be a problem. For many older haplogroups, the Y-STR 25 to Y-STR 37 tests have an acceptable confidence level while for some young haplogroups that emerged with rapid diversification and expansion, the tests do not have enough to discriminate the correct sub-lineage with statistical confidence.

With the growth of next generation sequencing (NGS) tests and whole genome sequencing which report on both STRs and SNPs in a single test, the use of STR-based tests and the need for haplogroup prediction tools is in decline. [3] DNA companies, such as Family Tree DNA (FTDNA) provide NGS tests that predict haplogroup identification as well as identify potential matches with other DNA testers. However, the rub is judging how close are those identified potential matches. The ability to discriminate the accuracy of those matches is still an art form in this mathematically oriented field of genetic ancestry. While FTDNA has developed mathematical strategies to evaluate genetic distance between genetic matches, it is still useful to use other Y-DNA modeling tools to evaluate Y-DNA results.

While STR based haplogroup and genetic prediction tools may be on the decline, they are still helpful in refining and judging potential genetic matches as well as evaluating and discovering the general genetic patterns among the Y-DNA results. SNP data provides information on ancestral male lineage with precision because there are potentially millions of them for comparison and they mutate so slowly that random reversing (“back”) mutations are essentially nonexistent. Neutral SNPs (those not under selection pressure) provide a molecular clock that is good for millions of years that are useful to determine ancient ancestral splits and migrations. STR data, on the other hand, can provide guidance (not necessarily proof) of ancestry in more recent patterns because of their rapid mutation rates. [4]

I have used a number of Y-SNP and Y-STR tools and reports to help with my process of discovery (see Table One). In addition to the FTDNA reports, I have used tools created by individual genealogists that provide creative renditions of the data. For example, assuming there are sufficient testers to compare STR results, mutation history trees and dendrograms can be created illustrate genetic distance and graphically reveal genetic branches from hundreds of years back to the recent past ( fine-tune the smaller branches, ‘twigs’, in a genetic tree).  The STR tools are highly effective if used in tandem with SNP data and traditional genealogical information (hence, “the one-two punch”). 

Table One : Y-SNP & Y-STR Tools Used in Y-DNA Research

STR / SNP Tool	Creator	Description
SNP Tracker	Spencer	Creates a map based on SNP data which traces paternal line from human origins
Britain & Ireland SNP & Surname Mapper	Spencer	Based on Surname or SNP input, provides historic British census countywide data and maps
Y STR Clustering and Dendrogram Drawing	Spencer	Generate circular/ linear dendrograms from FTDNA data. The tool provides quick and incisive graphic depictions of relationships between test kits on STR values and genetic distance.
FTDNA Admin Utilities	Spencer	SNP Breadcrumbs; Find Common Ancestor;  Export Tree Text; ISOGG Y-SNP Synonyms;
Still Another Phylogeny Program SAPP	Vance	Import Y-STR and Y-SNP data to create phylogenetic tree. This is a great program to use in conjunction with SNP results that group test results in a major SNP rant. The tool can then map out possible lines between testers based on STR values.
Y-DNA Matches	FTDNA	Lists Matches based on Y 12, 25, 37, 67, 111, and Big Y 700 STR tests
Y-DNA Haplotree	FTDNA	Lists haplotree based on confirmed terminal haplogroup, lists all SNPs tested positive or presumed positive
Y-STR Results	FTDNA	Lists the specific test results for Y-111 and Big Y 700 STR tests
Big Y BlockTM Tree	FTDNA	A vertical-block visual diagram of Y-DNA haplotree showing Big Y testers. This tool helps you visualize how the paternal lineages are related to each other. Also provides Paternal Countries of Origin and other information.
Haplogroup Story	FTDNA	Part of FamilyTreeDNA Discover™ series reports. Based on SNP input, provides estimated time of when haplogroup was born. when did your paternal ancestor live and where are his descendants found today.
FTDNATiP™ Report	FTDNA	Provides Genetic Distance estimates for potential Y-DNA STR matches

---

While STR tests are used by individual testers to discover possible Y-DNA genetic matches with other testers, the results of STR tests can also provide insights into macroscopic demographic properties that can shed light on lineages and clans – well before the time of surnames. Y- STRs have a time window that runs back to the late Bronze Age.

“STRs … tell us about demography — specifically about bottlenecks and subsequent expansions, namely “founder events.” While SNPs tell us when they were created, STRs tell us about when the population burgeoned after a founding mutation. That SNP and STR clades have a fundamentally different interpretation has caused considerable confusion, but once understood, the methods are very useful complements.” [5]

STRs have been viewed as having limited use in estimating dates beyond about 50-100 generations. However, there have been studies that indicate STR data can be utilized to for genealogical analysis into the Paleolithic era. [6]

Support from Y-DNA Working Group Projects

Coupled with the Y-STR tests, Family Tree DNA offers a wide variety of Y-DNA Group Projects to help further research goals. The group projects are associated with specific branches of the haplotree, geographical areas, surnames, or other unique identifying criteria. Based on their respective area of focus, the research groups have access to and the ability to compare Y-DNA results of fellow project members to determine if they are related. These projects are run by volunteer administrators who specialize in the haplogroup, surname, or geographical region that one may be researching. 

FTDNA supports a network of over 11,000 Group Projects to assist and support individuals who are interested in pursuing information about a specific topic related to their genealogy. The projects base research on members’ DNA testing results and to join a project one must test with, manage, or transfer results to FamilyTreeDNA. These working group projects are based on Y-DNA or mtDNA test results and are related to a surname, geographical area of interest, or haplogroup. Illustration 2 provides a graphic example of how a typical Haplogroup project manages Y-SNP and Y-STR test results. [7]

Illustration 2: Structure of a Typical Haplogroup Project

Typically, one of the group project administrators will review your test results (STRs and well as SNPs), known matches and ancestry. The work group administrators will then place your tests in a subgroup within the project. The subgroups are usually based on individuals who have common actual or predicted lower level SNPs. They can then help in calculating the modal haplotype for STRs for the smaller subgroup of testers which can help with the development of a mutation history tree.

For my research on the Griff(is)(es)(ith) family, I joined five Y-DNA Family Tree DNA based projects to assist in my ongoing research:

1. The GRIFFI(TH,THS,N,S,NG…etc) surname project is intended to provide an avenue for connecting the many branches of Griffith, Griffiths, Griffin, Griffis, Griffing and other families with derivative surnames. The Welsh patronymic naming system, practiced into the latter 18th century, makes this task more difficult. Evan, Thomas, John, Rees, Owen, Williams and many other common Welsh names may share common male ancestors. (820 members as of the date of this article).
2. The G-L497 project includes men with the L497 SNP mutation or reliably predicted to be G-L497+ on the basis of certain STR marker values. The L-497 is a branch or subclade of the G-haplogroup (M201+). The project also welcomes representatives of L497 males who are deceased, unavailable or otherwise unable to join, including females as their representatives and custodians of their Y-DNA. The primary goal of the project is to identify new subgroups of haplogroup G-L497 which will provide better focus to the migration history of our haplogroup G-L497 ancestors. (2,326 members as of the date of this article.)
3. The G-Z6748 project is a Y-DNA Haplogroup Project for a specific branch that is a more recent, ‘downstream’ branch from the L-497 branch of the G haplotree. It is a project work group that is a subset of the L497 work group. The G-Z6748 subclade or brand appears to be a largely Welsh haplogroup, though extending into neighboring parts of England. (33 members as of the date of the article)
4. The Welsh Patronymics project is designed to establish links between various families of Welsh origin with patronymic style surnames. Because the patronymic system (father’s given name as surname) continued until the 19th century in some parts of Wales, the working group is not limited to a single surname. (1,572 members as of the date of this article.)
5. The Wales Cymru DNA project collects the DNA haplotypes of individuals who can trace their Y-DNA and/or mtDNA lines to Wales. Tradition holds that the Celts retreated as far west in Wales as possible to escape invading populations. This project seeks to determine the validity of the theory. This project is open to descendants from all of Wales. (842 members as of the date of this article.)
6. The New York State DNA project is a project I recently joined. It is open to all men and women who live in New York State or who can trace their ancestors to New York State. (There are over 3,000 members in this project.)

Two of the six working groups, the G-L497 and the G-Z6748 Haplogroup projects, have been notably helpful in my research with genetic ancestry. The G-L497 working group has a large contingency of test results and a relatively large number of group administrators to help group participants in their research efforts. The administrators of the L-497 working group also provide a wide range of links to reference material associated with the L-497 haplogroup.

The G-Z6748 Haplogroup is a relatively new group and is an offshoot of the L-497 work group. It is a very small group of FTDNA testers that can trace their G- Haplogroup Y-DNA to the British Isles, particularly in the area of Wales.

SNPs, Haplotrees and Haplogroups: Deep Ancestry and Lineages

Illustration 3 is an highly simplified example of a branch in a Y-DNA haplotree that shows SNP mutations between generations of descendants. It provides a simple approach for understanding the development of the Y-DNA haplotree with SNP data. [8]

The male at the top of the tree exhibits “mutation one” (M1). This means all of his descendants will exhibit the same mutation. This same nucleotide could change again but the odds are it will not change and it will continue through his lineage. In subsequent generations other male descendants may exhibit single nucleotide changes in other areas of the DNA strand but will continue to exhibit the M1 mutation.

Illustration 3: Example of SNP Mutations and Genealogical Paths

In this illustration, we have two branches in the genetic haplotree where on one side a descendant exhibits “mutation 5” and on the other branch a descendant exhibits “mutation 2”. Each of their respective male descendants will respectively exhibit or test positive for M1 / M7 (in the left branch) and M1 / M2 (in the right hand branch) SNP mutations respectively. Descendent 1, at the bottom of the illustration, will test positive for M1, M5. M6. and M7 mutations and negative for M2, and M4 mutations. Descendants 2 and 3 will test positive for M1, M2 and M4 and negative for M5, M6, and M7. Descendant 3 will test positive for M1 and M2 and negative for M4 through M7.

The key to this exercise is one can trace the SNP mutations through successive genetic lines thereby creating a genetic family tree. SNPs are referred to as M1 through M7 in the illustration. Obviously, SNP testing is a bit more complex. SNPs are actually named with a major capital letter(s) and then with a number. [9]

A haplogroup, as previously indicated, is a genetic population group of people who share a common ancestor on the patriline or the matriline. Top-level haplogroups are assigned letters of the alphabet and deeper branches or subclades are labeled depending on what different nomenclature system is used.

The above illustration also greatly simplifies how many SNPs are associated with major branches in the haplotree and does no discuss the number of years between identified branches in the haplotree. Many of the haplotree branches actually represent mutations in various male descendants spanning thousands of years. Also, each branch is typically represented by an accumulation of SNPs that define or are associated with a given branch of the tree.

Illustration 4 below provides a graphic depiction of the relationship between SNPs and haplogroups within the Y-DNA Haplotree. The illustration uses the G haplogroup, as an example. The Griff(is)(es)(ith) paternal line is a part of the G-M201 haplogroup.

Illustration 4: SNPs in Relation to the Haplotree and Haplogroups

Illustration 5 provides a high level view of the structure of the Y-DNA haplotree. The Griff(is)(es)(with) Y-DNA line of descent is part of the Y-DNA G haplogroup that emerged approximately 45,000years ago.

Illustration 5: High Level View of the Y-DNA Haplotree

The major Eurasian Y-DNA-haplogroups (E1b, G2a, I1, I2, J1, J2, N, O, R1a, R1b, etc.) formed over tens of thousands of years, typical African Y-haplogroups like A, B and C have even deeper roots.

Haplogroup G descends from haplogroup F, which is thought to represent the second major migration of homo sapiens out of Africa, at least 60,000 years ago. While the earlier migration of haplogroups C and D had followed the coasts of South Asia as far as Oceania and the Far East, haplogroup F penetrated through the Arabian peninsula and settled in the Middle East. Its main branch, macro-haplogroup IJK would become the ancestor of 80 percent of modern Eurasian descendants.

Haplogroup G formed approximately 40-50,000 years ago as a side lineage of haplogroup IJK. Haplogroup G had a slow start in terms of migration, evolving in isolation for tens of thousands of years, possibly in the Near East, cut off from the wave of migration of Eurasia.

Paleolithic lineages (roughly 2.5 million years ago to 10,000 BCE) that underwent serious population bottlenecks, for thousands of years sometimes, have a series of over one hundred defining SNPs in their root branches The root branch (M201) of the G haplogroup of which the Griffis lineage is a descendant has over 300 defining SNPs, confirming that this paternal lineage experienced a bottleneck before splitting into haplogroups G1 and G2 (see footnote 18).

The sub-branch G1 might have originated around modern Iran at the start of the Last Glacial Maximum (LGM), approximately 26,000 years ago. G2 developed around the same time in West Asia. At that time humans in Europe were part of earlier haplogroups and were hunter-gatherers and living in small nomadic or semi-nomadic tribes. Members of haplogroup G2 appear to have been closely linked to the development of early agriculture in the Fertile Crescent, starting 11,500 years before present. The G2a branch expanded to Anatolia (modern day Turkey), the Caucasus and Europe, while G2b diffused from Iran across the Fertile Crescent and east to Pakistan. [10]

Organizational Differences Between Y-DNA Haplotrees

Since 2002, the nomenclature and structure of the Y-DNA haplotree has evolved with various modifications. As indicated in part one of this story, there are four major Y-DNA haplogroup trees managed by various groups. The most widely used versions are managed by (1) the DNA company Family Tree DNA (FTDNA), and two DNA research organizations : (2) YFULL, and (3) the International Society of Genetical Genealology (ISOGG). Each of the companies or organizations have different representations of the tree.  They also do not uniformly use the same branches or SNP names. [11]

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 version, using a deepest-known SNP. [12] Since 2012 many scholars, companies and genetic genealogists agreed to use what is called a Shorthand – SNP nomenclature Haplotree system to avoid naming confusion for the future. Family Tree DNA also merged to this system. [13] An example of this nomenclaure is found in Illustration 6 for the G haplogroup. The highlighted areas in the illustration trace the Y-DNA line for the Griff(is)(es)(ith) family.

Illustration 6: Example of Basic Hierarchy for Shorthand System Nomenclature for Beginning of the G Haplogroup

The differences between the three primary Y-DNA haplotrees is apparent when comparing my Y-DNA SNP results. Changes in the haplotrees can occur frequently based on incorporating new Y-DNA test results. New test results are not uniformly accepted by each of the three organizations. The differences between the three haplotrees are based on the nomenclature of the specific haplotree, what SNPs are accepted by a particular haplotree, and what SNPs are selected from the same equivalent block of SNPs to identify a particular branch of the Y-DNA haplotree. It makes you cross-eyed trying to follow all of this.

At this point in time, it is noteworthy that my test results put me on the cutting edge of new discoveries in genetic genealogy for the G haplogroup in the British Isles. as new Y-DNA test results are incorporate into the Haplotree, they can have an impact on my position in the Haplotree. Also, not all of FTDNA have been incorporated into the results of the YFULL and ISOGG haplotrees. In the FTDNA haplotree, as reflected in illustration 7 below, my SNP and STR results have been designated as a private SNP haplotree branch, as a subclade off of branch BY211678 along with another subclade branch G-FT119236.

Based on the results of my Big Y-700 FTDNA test, my Terminal SNP (branch or subclade) is G-BY211678. Basically, this means I am the descendant of a male who is the most recent common ancestor (MRCA) of this genetic line who was born ‘around’ 1500 CE with 95 percent statistical confidence variance of being born between 1283 CE and 1684 CE. [14]

Illustration 7 represents the ‘smallest branches and leaves’ of my Haplotree path. The data is from FTDNA’s Block Tree of Big Y test kits. It is a few branches down from the G-P303 branch and the L-497 branch which are most frequent and widespread G sub-haplogroups in Europe. The sub-clades of P-303 have more localized distribution with the U1-defined branch largely restricted to Near/Middle Eastern and the Caucasus and the L497 lineages essentially occur in Europe where they likely originated. [15] The man whose genetic SNP mutations created the G-6748 branch was born around 700 CE.

Illustration 7: Rendition of Portion of FTDNA Big Y Block Tree^TM of G- Haplogroup Starting with the G-Z6748 Sub-Branch

Looking at the haplotree from the view of testing for specific SNPs, as indicated Illustration 8, from G-Z6748, the following branches G-Y38335 > G-FGC486 > G-Z40857 > G-Y132505 trace down to G-BY211678. Since I have tested positive for this SNP, FTDNA has provided a new name for this terminal SNP in 2020: G-BY211678. I am presently the only one that is directly tied to this public SNP. The others have tested for a new downstream branch from this SNP and have formed their own subbranch G-FT119236.

Illustration 8: FTDNA Big Y 700 Y-DNA Test Confirmed Terminal Branch for James Griffis

The direct match to the FTDNA newly formed branch BY211678 is not documented in the International Society of Genetic Genealology (ISOGG) or the YFULL haplotrees. Both of these organizations consider my terminal SNP as a private (individual) SNP variant at this moment in time. A new branch is not recognized by ISOGGZ or YFULL until at least two individuals are found to have similar positive test results for the SNPs. However, one step up the haplotree branches, ISOGG has documented G-Y132505 which in long form is G2a2b2a1a1b1a1b1a2b. A designation that one certainly cannot remember! The YFULL haplotree also lists G-BY211678 as a SNP variant under the G-Y132505 branch rather than a subclade branch in the haplotree under G-Y132505. [16]

Given the number of newly discovered SNPs that have formed new branches in the Y-DNA tree, many of these new variant SNPs are yet to be confirmed by ISOGG and YFULL. Most of these new FTDNA SNP variants are considered as private SNPs by the other organizations unil other testers test positive or negative for the SNP. Accordingly, their names will reflect FTDNA names and numbers for the newly identified SNPs.  

In the FTDNA haplotree, the ‘Y132505″ branch, is two branches above my terminal SNP position. As of January 2023, my termnial SNP position has been labeled FT48097. The ‘FT’ is an ISOGG based prefix referring to a result from FTDNA Big Y testing. The Y132505 branch is found in the FTDNA, YFULL, and ISOGG haplotrees. The “Y” refers to the source of this SNP’s discovery (YFULL team using published and commercial next generation testing results).

Illustrations 9 and 10 reflect the relative position of my SNP/STR results in the YFULL and ISOGG haplotrees.

Illustration 9: YFULL Haplotree G-Y132505 Branch

The YFULL haplotree defines the BY211678 SNP as a private individual variant as opposed to a sepate subbranch to G-Y132505.

Illustration 10: ISOGG Haplotree G-Y132505 Branch

The ISOGG haplotree portrays G-Y132505 as the terminal SNP, with no mention of G-BY211678 or G-Y132506.

Equivalent SNPs and Y-DNA Haplotree Branches

Equivalent or variant SNPs are mutations observed in the same block of SNPs for a specific branch or haplogroup. They are equivalent in the sense that they can all be used to describe a haplogroup branch since it is impossible to define the chronological order (time of occurrence) of the SNPs in one haplogroup. [17]

Many haplogroups and subclades in the Y-DNA Haplotree are defined by more than one SNP. All of the Y-DNA public haplotrees are developed from research of ancient human artifacts and by the continuous analysis of test results of men completing Y-DNA tests and developing a SNP mutation history that shows how their ancestors branched from each other. Because many branches have died out long before modern day, any group of tested men will only show a fraction of all branches that actually occurred. Picking a SNP to identify a given branch may not be straightforward if there are more than one available SNP since the chronological order of each SNP may not be known.

Nearly every SNP on every public Y-DNA haplogroup tree is just one label for a block of equivalent SNPS. The equivalent SNPS are different physical mutations so they represent successive mutational genetic generations of men.  They are only equivalent as long as the haplotree remains the same and there are no discoveries of descendants associated with a given SNP to differentiate the chronological order. They represent a long series of generations of paternal ancestors who have no other descendants living today who have tested their Y-DNA except for the different groups who descend from different ancestors at the bottom of an equivalent block of SNPS.  Any new tester may create a previously unknown branch which descends from a different ancestor inside this long series of generations or block of equivalent SNPs. 

“Y-DNA and mtDNA lineages go extinct all of the time. About 80% of all lines have gone extinct through most of recorded history; this is how surnames vanish… . A ‘founder’ event occurs when a line almost goes extinct but then recovers, which leaves a clear imprint on descendants’ DNA.” – Rob Spencer

Generally speaking the number of accumulated SNPs between a haplogroup and its direct subclade correlates roughly to the number of genetic generations elapsed between the two branches. It is highly unlikely that only one genetic generation (e.g. 33 years) can be used as a multiplying factor for gaging time between two branched based on the number of equivalent SNPs associated with the older branch.

Illustration 10 provides an example of some of the major branches or subclades (SNP mutations ) of the G haplogroup of which the Y-DNA of Griff(is)(es)(ith) family can be traced. The illustration also indicates the number of variant or equivalent SNPS associated with a particular branch. For a list of all the equivalent SNPs in the Griff(is)(es)(ith) line, see footnote [18]. Illustration 10 also indicates the approximate date of when the branch occurred (e.g. when a male exhibited a specific SNP mutation).

Illustration 10: SNP mutations and the Patrilineal Line for Griffis Family

The Griff(is)(es)(ith) Patrilineal Y-DNA Line: The Big Picture

Based on the results of my Big Y 700 SNP test from FamilyTree DNA, Table Two provides a general outline of the major SNPs that represent major mutations in my Y-DNA line of genetic ancestors. Each of these SNPs represent a common ancestor that had a Unique Event Polymporhism (UEP) which represents the beginning of a new Y-DNA branch in the haplotree. The table traces major mutations from the beginning of of the G Haplogroup all the way to my most recent common Y-DNA ancestor G-BY211678 through the G Haplogroup.

Table Two: Griff(is)(es)(ith) Y-DNA Lineage on the Family Tree DNA (FTDNA) Haplotree

FTDNA Y Branch Subclade Main SNPs	Age Estimate	Time Passed (Years) From Preceding Branch	Phylo- genetic Sub- clades	SNP Branch Variants / Equiv- alent SNPS	Down Stream Branches ~ 2022	Number of Descendants in FTDNA Database 01-14-22
GHIJK- F1329	46,000 BCE	< 1,000	2			214,467
G-M201	26,000 BCE	20,000	2	318	1,731	9,658
G-L89	24,000 BCE	20,000	2	112	1,623	6,133
G-L156	20000 BCE	4,000	2	62	1,621	6,103
G-P15	16000 BCE	4,000	2	57	1,541	5,748
G-L1259	16000 BCE	< 1,000	2	7	1,403	5,007
G-L30	13000 BCE	3,000	2	47	1,226	4,519
G-L141	12000 BCE	1,000	2	14	1,018	3,806
G-P303	9700 BCE	2,300	3	38	959	3,629
G-L140	9000 BCE	700	3	14	907	3,298
G-PF3346	8950 BCE	< 100	2	1	896	3,167
G-PF3345	8900 BCE	< 100	11	3	889	3,145
G-L497	5300 BCE	3,600	2	49	456	1,747
G-CTS9737	4400 BCE	900	2	12	449	1,632
G-Z1817	3000 BCE	3,000	2	15	436	1,575
G-Z727	2450 BCE	550	3	8	431	1,464
G-FGC477	2100 BCE	300	5	2	52	113
G-Z6748	700 CE	2,800	2	29	22	49
G-Y38335	750 CE	< 100	2	21	2	43
G-Z40857	1000 CE	250	3	5	19	41
G-Y132505	1250 CE	250	3	2	2	7
G-BY211678	1500 CE	250	2	4	1	5

---

One can get a sense of the general characteristics of genetic change at the macroscopic level in a given haplogroup line of descent by reviewing specific aspects of when major SNP mutations occurred and the elapsed time between a given haplogroup and its ancestral haplogroup. In general, the Y-DNA line for the Griff(is)(es)(ith) paternal line suggests an historical line of descent that encountered a high rate of male line extinction. Look at the numbers in column 4. The number of new genetic branches are relatively small. Look at the numbers in column 3. The number of years between branches are large. I have identified the figures in bold in column 3.

The G haplogroup and my specific genetic line of descent survived a succession of ‘genetic hardships’ for survival. With the exception of two points in time, the average number of new phylogenetic subclades or the number of immediate descendants with UEP SNP mutations typically reflected only 2 new branches. Despite having a number of equivalent SNPs at each of the major branches, there were not many genetic branches that survived. Around 8,900 BCE the subclade BCE G-PF3345 had 11 branches and around 2,100 BCE the branch G-FGC477 had 5 subclades, suggesting some genetic proliferation at this time period.

Because many branches have died out long before modern day, many of the branches of the haplotree will only show a fraction of all the branches that actually occurred. The extinction of Y-DNA lines is the result of a number of cultural (war, patrilineal competition), environmental (famine, disease, climate), and biological factors (no male offspring) and is one facet of the overall growth, contraction and expansion of human population.

“Three major movements of people, it now seems clear, shaped the course of European prehistory. Immigrants brought art and music, farming and cities, domesticated horses and the wheel. They introduced the Indo-European languages spoken across much of the continent today. They may have even brought the plague. The last major contributors to western and central Europe’s genetic makeup—the last of the first Europeans, so to speak—arrived from the Russian steppe as Stonehenge was being built, nearly 5,000 years ago. ” [19]

While each of these 3 waves of migration were composed of a mix of genetic haplotypes, each were represented by one or two major genetic haplogroups.

Illustration Eleven: The Three Waves of Human Migration to Europe

Illustration 12: DNA Legacy of Europe

About 45,000 years ago, the first modern humans ventured into Europe. The first wave of modern Europeans lived as hunters and gatherers in small, nomadic bands. They followed the rivers into western and central Europe. 45,000 years ago. Their DNA indicates they mixed with the Neanderthals. As Europe was gripped by the Ice Age, the modern humans inhabited the ice-free areas of Southern Europe. About 14,500 years ago, as Europe began to warm, humans followed the retreating glaciers into Northern Europe.

The second wave is associated with the migration of Neolithic farmers from the Anatola region. The G-Haplogroup was part of this second wave. They brought not only their DNA but sheep, cattle and wheat to Europe. Within a thousand years the “Neolithic revolution” spread north through Anatolia and into southeastern Europe. By about 6,000 years ago, there were farmers and herders all across Europe.

The third wave, which is predominantly represented by the Yamnaya and are part of the R-Haplogroup, emanated from the Steppes. By 2800 B.C, archaeological excavations show the Yamnaya had begun moving west out of the Steppes. As they proceeded westward, things stated to change. All across Europe, thriving Neolithic settlements shrank or disappeared altogether. The dramatic decline has puzzled scientists from various fields of study and there are various hypotheses that attempt to explain this genetic decline and replacement by the R-haplogroup.

Within a few centuries, the presence of Yamnaya DNA had spread as far as the British Isles. In Britain, similar to other European areas, hardly any of the farmers who lived in Europe survived the onslaught from the east. Until then, farmers had been thriving in Europe for millennia. The second wave of human had settled from Bulgaria all the way to Ireland, often in complex villages that housed hundreds or even thousands of people.

One of many possible theories of the dramatic decline of G-Haplogroup along with other genetic haplogroups associated with the Neolithic farmers is the discovery that some of DNA samples of the Yamnaya contained an early form of Yersinia pestis—the plague microbe that killed roughly half of all Europeans in the 14th century. [20] Unlike that flea-borne Black Death, this early variant had to be passed from person to person. The steppe nomads apparently had lived with the disease for centuries, perhaps building up immunity or resistance. Similar to the history of smallpox and other diseases that ravaged Native American populations, the plague, once introduced by the first Yamnaya, might have spread rapidly through crowded Neolithic villages. That provides a plausible explanation of collapse and the rapid spread of Yamnaya DNA.

While it is a cogent explanation, this theory begs the question of whether there is evidence to substantiate the presence of plague DNA in ecological finds. It has only recently been documented in ancient Neolithic skeletons, and so far, no one has found anything like the plague pits full of diseased skeletons left behind after the Black Death. If a plague wiped out most of Europe’s Neolithic farmers and the G-Haplogroup, it left little trace.

There is strong evidence of major founder events at the end of the Neolithic period. It has been stated that two-thirds of all European men from the R-haplogroup descend from just three ancestors who lived in the late Neolithic.  [21] The G-Haplogroup migrated into Western Europe prior to the R-Haplogroup but had similar genetic / demographic impacts at two different time periods, as mentioned above.

Changes in genetic variation are driven not only by genetic processes, but can also be causes or be correlated with cultural or social changes. An abrupt population bottleneck specific to human males has been inferred across several Old World (Africa, Europe, Asia) populations between 5000–7000 BP (5,000 BCE – 3000 BCE). [22]

Combining anthropological theory, population genomic studies and mathematical models, a number of studies have proposed a general sociocultural hypothesis involving the formation of patrilineal kin groups and intergroup competition among these groups as having led to a reduction of Y chromosomal diversity. This reduction was much greater than the reduction in male population size, while keeping the female population size stable.. Various analyses of DNA data show that this sociocultural hypothesis can explain the inference of the population bottleneck in this time period. [23]

Using Rob Spencer’s SNP Tracker to provide illustrative examples of the migratory paths of various haplogroups [24], I compared (Illustration 13) the migratory path of my haplogroup (part of the second wave) with the migratory path of one of the major R-haplogroups, the R1b-M269 haplogroup (part of the third wave). Why compare my haplogroup with this uniquely named haplogroup? The R1b-M269 is a branch of the R-haplogroup that has been associated with the Beaker Culture that was prominent in Western Europe and eventually migrated to Scotland.

Illustration 13: Estimated Migratory Paths for R1b-M269 Haplogroup and the G-BY211678 Haplogroup

As you can see in the illustration, there is some geographical overlap with the two migratory paths in Western Europe of these two haplogroups. My hunch, (“I did stay at the Holiday Express“) is that my Haplogroup descendants were part of the second wave migration into Europe and eventually were in areas now considered as Germany between 5000 BCEto 2350 BCE and then migrated further westward to what is now northern France and the migrated to the British isle.

As discussed in Part Two of the story, cultural and genetic genealogy are two logically distinct aspects of genealogy. Similarly, various migratory patterns associated with Haplogroups do not necessarily imply that they coincide with cultural geographical patterns or movements. Migratory patterns of Y-DNA Haplogroups undoubtably contained a mix of haplogroups. Y-DNA haplogroups also were represented in various historical cultures. Many cultures invariably contained genetic mixtures of Haplogroups at various periods of time.

Illustration 14 provides a map that ties Y-DNA haplogroups with early Bronze age cultures that were present in Europe. [25] This approximates the time period where I believe the Griff(is)(es)(ith) G-Haplogroup line may have intersected with the R-Haplogroup and were both part of the Beaker and Corded Ware Cultures.

Illustration 14: Associations of Early Bronze Age Cultures with Y-DNA Haplogroups

The Griff(is)(es)(ith) patrilineal descendants may have encountered the third wave’ of European migrants in the northwest Europe perhaps around 2,500 BCE . They survived a possible plague as well as any possible socio-cultural kinship battles and assimilated into the evolving culture of the times and remained in Northern/Western European area until around or before the Norman invasion (1100 CE). At that time it would appear our descendants migrated to the British Isles, utlimately to Wales.

Using STR Results to Clarify Lineages Before the Advent of Surnames

As stated, the analysis of SNP and STR test results provide a one-two punch in mapping Y-DNA lines of descent. As reflected in the above discussion, the use of SNP data is relatively straightforward. Your placement on the Y-DNA haplotree is based on which SNPs test positive in your Y-DNA tests.

There are a number of Y-DNA tools that can be used to analyze Y-DNA STR results. [26] A mutation history tree portrays the likely haplotype of a most recent common ancestor and the most likely series of STR mutations which occurred in the descendant branches to arrive at the haplotypes of the present day testers (ancestral haplotype).

Comparing STR test results require “more mathematical work” to be useful, and are highly dependent on the number STRs tested.  Since STRs mutate at variable rates more frequently than SNPs, one must eliminate the effects of convergence and the mathematically incorporate the differential effects of mutation rates on STR markers.

” . . . (A)ll STR data — Y12 to Y111 — 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.” [27]

FTDNA provides a number of Y-DNA tools and organizational strategies for analyzing Y-DNA results that facilitate “the two-punch process”. SNP results are first used to figure out where one is situated in the Y-DNA haplotree. Depending on the type of Y-DNA tests that are completed, a tester can determine their relative position on the Y-DNA haplotree. The more detailed the test, the more accurate and reliable are the results of placement on the haplotree. The Y12 through Y67 tests will give you a general idea of your haplogroup while the Y111 test will place in one of the more defined branches of the tree. The Big Y700 test will identify the specific ‘twig’ or leaf’ of the tree. STRs can then be used to compare testers that are grouped by haplogroup to discover possible genetic matches or fine tune the branches of the haplotree.

This is where things can get interesting in terms of potential genetic matches and teasing out one’s genetic lineages before the use of surnames.

For genealogy within the most recent fifteen to twenty generations (about 500 to 660 years ago), STR markers help define paternal lineages and patterns around the advent of the use of surnames. For Welsh descendants the number of generations will be closer in terms of when surnames were routinely used. STR analysis is an excellent approach to document genetic lineages before the use of surnames and into a period in which surname of genetically matched test kits could be different. For patrilineal lines a descent with Welsh surnames, this is important. The likelihood of finding genetic matches with test kits associated with different surnames is highly likely! [28]

Illustration 13: Genetic Matches and Surnames

Y-STR analysis can also identify patterns which suggest the structure of American colonial families. Typically there will be a gap of 10 or more genetic generations followed by an expansion of family ties. [29].

Illustration 12: Spot the American Immigrant Families

The information in Table Three displays Y-Chromosome DNA (Y-DNA) STR results for testers in the L-497 Haplogroup project. Specifically, it 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 Three: 111 STR Results for G-L497 Working Group Members within the G-BY211678 Haplotree Branch 

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 test results among potential test kits to determine if I find any genetic relatives!

What’s Next

Working with Y-STRs and Y-SNPs requires covering the topics of genetic distance,  modal, ancestral haplotypes and the Most Recent Common Ancestor. In the context of these concepts, I will demonstrate the use of some of the Y-SNP & Y-STR Tools listed in Table One.

Sources

Feature Image of the story is a modified version of a featured image from Human Genomic Variation, National Human Genome Research Institute, National Institute of Health (NIH), Page last updated: April 6, 2018, https://www.genome.gov/dna-day/15-ways/human-genomic-variation . It is a visual depiction of comparing SNP mutations between two DNA testers. Aside from the image itself, the article is a good read.

[1] “People usually submit DNA samples in hopes of finding relatives they didn’t know about; just one or two matches might help to complete a family tree or resolve an old debate. However, some men doing Y DNA tests find themselves with an unexpected problem: they’re deluged with dozens to hundreds of “matches” who don’t share a common surname. With further effort they find that these matches are completely unrelated. It appears that somehow all of these men, though unrelated, have converged on a common DNA pattern”

The table below summarizes risk level of convergence. The values are the percent of modern descendants that you would see as matches, using FTDNA’s criterion for the Most Recent Common Ancestor (tMRCA) of less than 21 generations, despite having no family structure other than one founder event.

It is notable that even as recent as 15 generations ago, a high percentage of testers will likely be identified as related because all descendants who share a founder event more recent than 21 generations will be marked as matches. This is frequently seen for emigration-driven founder events such as European emigration to North America and all occurred more recently. While these matches really reflect recent shared ancestry, it makes it difficult to reveal family details.

Rob Spencer, Convergence, Tracking Back: a website for genetic genealogy tools, experimentation, and discussion, no date, page accessed 3 May 2022.

Maurice Gleeson, Convergence – what is it?, 25 May 2017, DNA and Family Tree Research, https://dnaandfamilytreeresearch.blogspot.com/2017/05/convergence-what-is-it.html

Maurice Gleeson, Convergence – quantifying Back & Parallel Mutations (Part 1), 1 June 2017, DNA and Family Tree Research, https://dnaandfamilytreeresearch.blogspot.com/2017/06/convergence-quantifying-back-parallel.html

J David Vance, The Genealogist Guide to Genetic Testing, 2020, Chapter 6

See, Convergence, International Society of Genetic Genealogy Wiki, Page last updated 6 Dec 2018

Rob Spencer has a cogent explanation of convergence: See quote below and reference: Robert W. Spencer , Tracking Back: a website for genetic genealogy tools, experimentation, and discussion, no date, page accessed 3 May 2022.

“The men in question actually are related — this is key — but in a particular way and usually long before the genealogical time span of a couple of hundred years. A group of modern descendants might not care if they have a common ancestor who lived in 1000 AD — but it really matters.”

[2] Y-STR Results Guide, FamilyTree DNA Help Center, https://help.familytreedna.com/hc/en-us/articles/4408063356303-Y-STR-Results-Guide-#panel-4-48-60–0-4

Caleb Davis, Michael Sager, Göran Runfeldt, Elliott Greenspan, Arjan Bormans, Bennett Greenspan, and Connie Bormans, Big Y 700 White paper, March 27, 2019, https://blog.familytreedna.com/wp-content/uploads/2018/06/big_y_700_white_paper_compressed.pdf

Marty Brady, Y Chromosomes and the SNPs STRs, May 16 2020 Presentation, Albuquerque Genealogical Society, Ychromosome_slides.pdf

Ian McDonald, Exploring new Y-DNA Horizons with Big Y-700  19 Oct 2019, presentation was originally given as part of Genetic Genealogy Ireland 2019. https://familytreewebinars.com/webinar/exploring-new-y-dna-horizons-with-big-y-700/]

[3] 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

Rob Spencer, Deep STR Time, Tracking Back: a website for genetic genealogy tools, experimentation, and discussion, http://scaledinnovation.com/gg/gg.html?rr=deeptime

[4] Rob Spencer, Case Studies in Macro Genealogy, Presentation for the New York Genealogical and Biographical Society, July 2021, Slide 12, http://scaledinnovation.com/gg/ext/NYG&B_webinar.pdf

[5] Rob Spencer, STR Clades, Tracking Back: a website for genetic genealogy tools, experimentation, and discussion, http://scaledinnovation.com/gg/gg.html?rr=strclades

[6] Rob Spencer, Why use STR data and not SNP data?, Tracking Back: a website for genetic genealogy tools, experimentation, and discussion, http://scaledinnovation.com/gg/gg.html?rr=whystr

[7] Introduction to Group Projects, Family Tree DNA Center, https://help.familytreedna.com/hc/en-us/articles/4503173806351-Introduction-to-Group-Projects-

Group Projects, Family Tree DNA Learning Center, https://learn.familytreedna.com/topics/group-projects/

Should I Join A Group Project, Family Tree DNA Blog, Aug 10 2018, https://blog.familytreedna.com/should-i-join-a-group-project/

FamilyTreeDNA Group Projects, Family Tree DNA, https://www.familytreedna.com/group-project-search?browse=true

[8] This example is taken from J David Vance, The Genealogist Guide to Genetic Testing, 2020

[9] SNPs are given names based on an abbreviation that indicates the lab or research team that discovered the SNP and a number that indicates the order in which it was discovered. The prefix, the first letter or group of letters after the main alpha Haplogroup letter identifies the lab or analysis company which first discovered the SNP or was really the first to decide that the mutation at that position on the Y- chromosome was worthy of a name. 

SNPs development indicated by beginning letters:
A = Thomas Krahn, MSc (Dipl.-Ing.), YSEQ.net, Berlin, Germany
ACT = Ancient-Tales Institute of Anthropology, Enlighten BioTech Co., Ltd., Shanghai, China
AD = Dr. Mohammed Al Sharija, Ministry of Education (Kuwait)
AF = Fernando Mendez, Ph.D., University of Arizona, Tucson, Arizona
ALK = Ahmad Al Khuraiji
AM or AMM = Laboratory of Forensic Genetics and Molecular Archaeology, UZ Leuven, Leuven, Belgium
B = Estonian Genome Centre
BY = Big Y testing (next generation sequencing) discovered with the BigY-500, Family Tree DNA, Houston, Texas
BZ = Q-M242 Project, Family Tree DNA, Houston, TX. SNPs named in honor of Barry Zwick.
CTS = Chris Tyler-Smith, Ph.D., The Wellcome Trust Sanger Institute, Hinxton, England
DC = Dál Cais, an Irish group believed to be descended from Cas, b. CE 347, related to SNP R-L226; Dennis Wright
DF = anonymous researcher using publicly available full-genome-sequence data, including 1000 Genomes Project data; named in honor of the DNA-Forums.org genetic genealogy community
E = Bulat Muratov
F = Li Jin, Ph.D., Fudan University, Shanghai, China
F* = Chuan-Chao Wang, Hui Li, Fudan University, Shanghai, China (Beginning letter F; second letter Haplogroup, i.e. FI is Fudan Haplogroup I)
FGC = Full Genomes Corp. of Virginia and Maryland
FT = Big Y testing (next generation sequencing)discovered with the Big Y-700, Family Tree DNA, Houston, Texas
G = Verónica Gomes, IPATIMUP Instituto de Patologia e Imunologia Molecular da Universidade do Porto (Institute of Molecular Pathology and Immunology of the University of Porto)
GG=Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
IMS-JST = Institute of Medical Science-Japan Science and Technology Agency
JD = David Stedman using Big Y and other NGS sources.
JFS = John Sloan
JN = Jakob Nortsedt-Moberg
K = Youngmin JeongAhn, Ph.D; Education: Seoul National University and the University of Arizona
KHS = Functional Genomics Research Center, Korea Research Institute of Bioscience and Biotechnology
KL = Key Laboratory of Contemporary Anthropology, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
KMS = Segdul Kodzhakov; Albert Katchiev; Anatole Klyosov; Astrid Krahn; Thomas Krahn; Bulat Muratov; Chris Morley; Ramil Suyunov; Vadim Sozinov; Pavel Shvarev; SF “National clans DNA project”; EHP “Suyun” Ph.D. of Technical Science; Prof. Elsa Khusnutdinova, Sc.D. of Biological Sciences, Laboratory of Molecular Human Genetics, Institute of Biochemistry and Genetics, Ufa Research Centre, Russian Academy of Sciences
L = Thomas Krahn, MSc (Dipl.-Ing.) formerly of Family Tree DNA’s Genomics Research Center; snps named in honor of the late Leo Little
M = Peter Underhill, Ph.D. of Stanford University
MC = Christopher McCown, University of Florida; Thomas Krahn, MSc (Dipl.-Ing.), YSEQ.net, Berlin, Germany
MF = 23mofang BioTech Co., Ltd., Chengdu, China
MPB = Thomaz Pinotti and Fabrício R. Santos, Laboratório de Biodiversidade e Evolução Molecular (LBEM), Universidade Federal de Minas Gerais, Brazil
MZ = Hamma Bachir, Ph.D., E-M183 Project
N = The Laboratory of Bioinformatics, Institute of Biophysics, Chinese Academy of Sciences, Beijing
NWT = Northwest Territory, Theodore G. Schurr, Ph.D., Laboratory of Molecular Anthropology, University of Pennsylvania, Philadelphia, PA
P = Michael Hammer, Ph.D. of University of Arizona
Page, PAGES or PS = David C. Page, Whitehead Institute for Biomedical Research
PF = Paolo Francalacci, Ph.D., Università di Sassari, Sassari, Italy
PH = Pille Hallast, Ph.D., University of Leicester, Department of Genetics, United Kingdom
PK = Biomedical and Genetic Engineering Laboratories, Islamabad, Pakistan
PLE = Stanislaw Plewako, M. Sci, Baltic Sea DNA Project.
PR = Primate (gorilla and chimpanzee), Thomas Krahn’s WTTY. Some sources have not provided new names when same mutation found independently in humans.
RC = Major Rory Cain, BA(hons), BEd, BSc.
S = James F. Wilson, D.Phil. at Edinburgh University
SA = South America, Theodore G. Schurr, Ph.D., Laboratory of Molecular Anthropology, University of Pennsylvania, Philadelphia, PA
SK = Mark Stoneking, Ph.D., Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
SUR = Southern Ural; SF “National clans DNA project”; B.A. Muratov; EHP “Suyun” Ph.D. of Technical Sciences; Ramil Suyunov; Prof. E.K. Khusnutdinova, Sc.D. of Biological Sciences, Laboratory of Molecular Human Genetics, Institute of Biochemistry and Genetics, Ufa Research Centre Russian Academy of Sciences; Alexander Zolotarev; Igor Rozhanskii; Bayazit Yunusbaev, Institute of Biochemistry and Genetics, Ufa Research Centre, Russian Academy of Sciences
TSC = Gudmundur A. Thorisson and Lincoln D. Stein, The SNP Consortium, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
U = Lynn M. Sims, University of Central Florida; Dennis Garvey, Ph.D. Gonzaga University; and Jack Ballantyne, Ph.D., University of Central Florida
V = Rosaria Scozzari and Fulvio Cruciani, Dipartimento di Biologia e Biotecnologie “Charles Darwin” , Sapienza Università di Roma, Rome, Italy.
VK = Viacheslav Kudryashov.
VL = Vladimir Volkov, Tomsk University, Russia
Y = Y Full Team (Russian) using data from published and commercial next-generation sequencing samples
YP = SNPs identified by citizen scientists from genetic tests, then submitted to the Y Full team for verification.
YSC = Thomas Krahn, MSc (Dipl.-Ing.) formerly of Family Tree DNA’s Genomics Research Center
Z = Gregory Magoon, Ph.D., Richard Rocca, Vince Tilroe, David F. Reynolds, Bonnie Schrack, Peter M. Op den Velde Boots, Ray H. Banks, Roman Sychev, Victar Mas, Steve Fix, Christian Rottensteiner, Alexander R. Williamson, Ph.D., John Sloan and an anonymous individual, independent researchers of publicly available whole genome sequence datasets, and Thomas Krahn, MSc (Dipl.-Ing.), with support from the genetic genealogy community.
ZP = Peter M. Op den Velde Boots, David Stedman using Big Y and other NGS sources.
ZQ = Gabit Baimbetov, Nurbol Baimukhanov “ShejireDNA project” and other members of the project.
ZS = Gregory Magoon, Ph.D., Aaron Salles Torres from samples from Full Genomes and the Big Y.
ZW = Michael W. Walsh using Big Y.
ZZ = Alex Williamson. Mutations in palindromic regions. Each ZZ prefix represents two possible SNP locations.

Source: Y-DNA Haplogroup Tree 2019-2020, version 15.73, 11 July 2020, Internal Society of Genetic Genealogy, https://isogg.org/tree/

A SNP discovered or identified by YFull starts with a “Y”; a SNP starting with a “BY” or “FT” was named by Family Tree DNA, a “FGC” SNP was named by Full Genomes Corporation, and an “A” SNP was named by YSEQ. An ‘M’ stands for the Human Population Genetics Laboratory at Stanford University.

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

See also: Y-DNA: FamilySearch, How SNPs Are Added to the Y Haplotree, YouTube Video, Feb 2022, https://www.youtube.com/watch?v=CGQaYcroRwY

[10] Maciamo Hay, Haplogroup G2a, (Y-DNA), Eupedia, Jan 2021, https://www.eupedia.com/europe/Haplogroup_G2a_Y-DNA.shtml

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

[11] Some of the reasons for the differences between the various haplogroup trees are: 

• Different databases: The databases of the tested men differ between companies and groups. The different databases reflect the SNPs and order of those SNPs that have been found through their analysis of that database. The different companies and analysis groups use different sources for there SNPs: their own testers (YFull does not test), academic databases, historical sources archeological site analysis. 
• Synomyn SNPs: Different companies may select different synonyms for the same SNP even though  the mutation may appear in same place on each of their Y-DNA haplotrees it may not have the same name. Oftentimes different labs or analysis companies will discover the same SNP and provide independent names for the SNP. Different companies may select different SNPs from the same equivalent block of SNPs that are part of a branch to represent a particular branch of the Y-DNA haplotree.
• Equivalent SNPS: Each of these haplogroup trees are developed by analyzing a group of tested men and developing a SNP mutation history that shows how these ancestors branched from each other. Many branches have died out before present day men were tested. As more men are tested, mutations will be found that are new but related to specific older branches. If a number of men who are tested by a given company and found to have new mutations they may form a new branch. However, the results from this one company may be viewed by other companies who manage other haplotrees as ‘private’ SNPs and therefore will not be viewed as a new branch. 
• Selection Criteria: The companies also have different criteria for testing quality, region of the chromosome, for which SNPs belong on their haplogroup tree. SNPs which may be selected by one company may not be acceptable to another.

The three major organizations that manage Y-DNA haplogroups and haplotrees are:

• ISOGG Y-SNP tree
• FamilyTreeDNA Y-haplotree
• The YFull version of the Y-SNP tree

[12] In 2002 the Y Chromosome Consortium (YCC) proposed two widely accepted nomenclature systems for Y-DNA haplogroups: an hierarchical system and a short hand system. Other systems have subsequently been developed and used.

Major haplogroups are labeled with large capital letters (A–T).

• Hierarchical system:  The hierarchical system is based on characteristics of set theory. The capital letters (A–R) are used to identify the major clades and constitute the front symbols of all subsequent subclades. Subclades nested within each major haplogroup are defined by alternating numbers “1” and “2” and lowercase letters “a” and “b”. An example would be: G2a2b2a1a1b1a1b1a2b.
• Shorthand – SNP system:  This system is more robust to changes in topology but widespread SNPs have often up to three synonymous names. Additionally different corporations/labs in many cases select an equivalent SNP for the same haplogroup as primary/defining (example G-M201). For seldom and new terminal SNPs there is also the risk that they are not unique (recurrent, unstable) or not detectable with all lab methods.
• Basic Hierarchy + Shorthand system: since 2013 this system is used by some publications to show the basic hierarchy under a main haplogroup combined with a SNP of a subclade deeper down then the listed hierarchy: example G2a (P15, U5, L31/S149). Especially for unknown SNP names this allows easier recogniation of the basal position.
• Paragroups are distinguished from haplogroups by using the * (star) symbol, which represents chromosomes belonging to a clade but not its researched subclades defined in the same publication.

Y-DNA project help, International Society of Genetical Genealogy Wiki, This page was last edited on 28 October 2022, https://isogg.org/wiki/Y-DNA_project_help

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

Karafet TM, Mendez FL, Meilerman MB, Underhill PA, Zegura SL, Hammer MF (2008-05). “New binary polymorphisms reshape and increase resolution of the human Y chromosomal haplogroup tree”. Genome Research. doi:10.1101/gr.7172008. Retrieved 2012-04-12

[13] Let’s All Start Using Terminal SNP Labels Instead of Y Haplogroup Subclade Names, Okay? http://www.yourgeneticgenealogist.com/2012/09/lets-all-start-using-terminal-snp.html

Family Tree DNA, Y-DNA: How SNPs Are Added to the Y Haplotree, YouTube Video, Feb 2022, https://www.familysearch.

[14] The FamilyTreeDNA (FTDNA) Time to Most Recent Common Ancestor (TMRCA) estimate (Beta) is calculated based on SNP and STR test results from present-day DNA testers. The uncertainty in the molecular clock and other factors is represented in this probability plot, which shows the statistical probability of the reliability of the birth date in statistical stand deviations, e.g. the most likely time when the common ancestor was born among statistical possibilities.

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

[16a] Big Y Block Tree Introduction, FTDNA Help Center, https://help.familytreedna.com/hc/en-us/articles/4402744197647-Big-Y-Block-Tree-Introduction#accessing-the-block-tree-0-0

[16] See Line 1135 column  S and T in 2019-2020 Haplogroup G TreeY-DNA Haplogroup Tree 2019-2020, International Society of Genetic Genealoloy (ISSOG), Version: 15.73   Date: 11 July 2020 https://docs.google.com/spreadsheets/d/111Iqo0vRt-sr8MJT7pavKQ0qoWxYSc1P7hnMRq3GijU/edit#gid=0

For YFULL SNP designations in their haplotree:

Q: How does YFull determine my Terminal Hg?

A: YFull seeks to place your sample in the YTree as near to the present as is possible by comparing your path of SNP mutations with the paths of SNP mutations of other samples in its database. A “path of mutations” is a list of mutations ranked by the estimated age of each mutation.

If your mutations exactly match those of another sample in the database, your sample will be placed in the same subclade as the other sample and this will be the Terminal Hg (or subclade) of both samples.

In some cases a sample may include an * (asterisk) to indicate that YFull was not able to match the sample with another sample beyond the specified location in the YTree.

At the time you pay your fee to YFull, the location of your sample in the YTree is temporary. When the next version of the YTree is released your Terminal Hg may change. Also, as more samples are added to the YFull database, your Terminal Hg may continue to change.

YFULL FAQ, Last updated on March 28, 2018.  https://www.yfull.com/faq/how-my-sample-located-on-ytree/ also https://www.yfull.com/faq/

[17] Y-DNA project help, International Society of Genetic Genealogy Wiki, This page was last edited on 28 October 2022, https://isogg.org/wiki/Y-DNA_project_help

J David Vance, The Genealogist Guide to Genetic Testing, 2020, Chapter 7

[17a] Rob Spencer, Additional Information for the RootsTech 2022 session “Extending Time Horizons with DNA”, Tracking Back, http://scaledinnovation.com/gg/ext/rt22/info.html?rt

[17b] Rober Spencer, Additional Information for the RootsTech 2022 session “Extending Time Horizons with DNA”, Extinction of Lineages and Surnames, http://scaledinnovation.com/gg/ext/rt22/info.html?rt

[18] The following reflect all of the SNPS associated with the FTDNA G Haplogroup SNPS that I have either tested positive or are presumed positive for the following equivalent variants for each Y-DNA branch. Each SNP mutation represents an individual that is a direct ancestor.

G-M201 root branch: 318 variants

M201, BY21262, BY21263, BY21264, BY2378, CTS10026, CTS1010, CTS1013, CTS10280, CTS1029, CTS10393, CTS10706, CTS10721, CTS10723, CTS10824, CTS10945, CTS11185, CTS11228, CTS11331, CTS1137, CTS1139, CTS11400, CTS11529, CTS11584, CTS11670, CTS11702, CTS11907, CTS11911, CTS12040, CTS12240, CTS12309, CTS1259, CTS12600, CTS12654, CTS1270, CTS12704, CTS12731, CTS1283, CTS12949, CTS13035, CTS1437, CTS1574, CTS1577, CTS1612, CTS1613, CTS1624, CTS1705, CTS1726, CTS175, CTS1750, CTS1768, CTS189, CTS1997, CTS2016, CTS2120, CTS2125, CTS2126, CTS2136, CTS2174, CTS2215, CTS2251, CTS2271, CTS2357, CTS2506, CTS2517, CTS2624, CTS282, CTS34, CTS3693, CTS373, CTS3752, CTS4101, CTS4238, C50S440, CTS4479, CTS4523, CTS4613, CTS4749, CTS4761, CTS4887, CTS5317, CTS5414, CTS5498, CTS5504, CTS5640, CTS5658, CTS5699, CTS5757, CTS5837, CTS6073,CTS635, CTS6483, CTS670, CTS6807, CTS6894, CTS692, CTS6936, CTS6957, CTS7092, CTS7269, CTS7388, CTS7674, CTS7929, CTS8023, CTS827, CTS8531, CTS8717, CTS9011, CTS9190, CTS9593, CTS9641, CTS9707, CTS9710, CTS9894, CTS995, FGC77405, FGC77406, FGC77410, FGC77412, FGC77414, FGC77417, FGC77418, FGC78561, FGC79229, FGC79248, FT32, FT32899, L109, L116, L1258, L1342, L1407, L154, L204, L269, L382, L402, L519, L520, L521, L522, L523, L524, L605, L769, L770, L836, L837, M3438, M3453, M3468, M3489, M3569, M3598, M3601, P257, PF2788, PF2790, PF2791, PF2793, PF2796, PF2802, PF2804, PF2805, PF2806, PF2808, PF2809, PF2815, PF2816, PF2817, PF2819, PF2821, PF2827, PF2831, PF2832, PF2836, PF2837, PF2844, PF2857, PF2858, PF2859, PF2861, PF2862, PF2865, PF2866, PF2867, PF2868, PF2869, PF2871, PF2872, PF2873, PF2874, PF2875, PF2876, PF2877, PF2878, PF2879, PF2880, PF2881, PF2884, PF2888,PF2889, PF2890, PF2894, PF2896, PF2901, PF2902, PF2908, PF2910, PF2914, PF2915, PF2917, PF2918, PF2919, PF2920, PF2921, PF2932, PF2949, PF2954, PF2956, PF2958, PF3022, PF3045, PF3046, PF3048, PF3049, PF3050,PF3052, PF3053, PF3054, PF3057, PF3059, PF3061, PF3063, PF3065, PF3067, PF3068, PF3069, PF3070, PF3071, PF3074, PF3075, PF3076, PF3077, PF3080, PF3083, PF3085, PF3087, PF3088, PF3092, PF3094, PF3103, PF3117, PF3118, PF3121, PF3122, PF3123, PF3134, PF3265, S13661, S13716, S14351, S8863, U17, U2, U20, U21, U3, U33, U7, Y226, Y229, Y231, Y235, Y239, Y245, Y246, Y258, Y271, Y303, Y309, Y332, Y345, Y351, Y375, Y383, Y390, Z3030, Z3067, Z3069, Z3078, Z3080, Z3081, Z3097, Z3104, Z3107, Z3117, Z3135, Z3136, Z3144, Z3145, Z3239, Z3246, Z3247, Z3248, Z3250, Z3262, Z3477, Z3482, Z3485, Z3539, Z6041, Z6116, Z6133, Z6138, Z6324, Z6472

Variants haplogroup G-L89 branch: 32 variants

L89, CTS10089, CTS11196, CTS120, CTS1868, CTS2593, CTS4413, F3198, FGC7254, FGC79817, L142.1, L79.1, M3579, M3614, P287, PF2792, PF2794, PF2795, PF2807, PF2810, PF2830, PF2835, PF2860, PF2864, PF2887, PF2891, PF2895, PF2909, PF3093, PF3119, Z3060, Z3063

Variants haplogroup G-L156 branch: 62 variants

L156, CTS11016, CTS1900, CTS2406, CTS4136, CTS4242, CTS4264, CTS4703, CTS6316, CTS6692, CTS6742, CTS7430, CTS7662, CTS9885, F1239, F1496, F3070, F3220, F3226, FGC37627, FGC77409, L496, PF2785, PF2787, PF2789, PF2797, PF2800, PF2803, PF2814, PF2820, PF2839, PF2840, PF2893, PF2897, PF2898, PF2904, PF2905, PF2912, PF3007, PF3047, PF3091, PF3095, PF3120, PF3125, S13969, V1943, Y125206, Y1415, Y222, Y237, Y238, Y255, Y289, Y321, Y360, Y380, Z3042, Z3056, Z3112, Z3499, Z6105, Z6292

Variants haplogroup G-P15 branch: 57 variants

P15, CTS11463, CTS11627, CTS1879, CTS211, CTS32, CTS5416, CTS5666, CTS6026, CTS6314, CTS6630, CTS6753, CTS8673, CTS9318, F1554, F1975, F1980, F2274, F2301, F2529, F3734, F4086, FGC77420, FGC77421, FGC78558, FGC79059, L149, L31, M3348, M3392, PF2798, PF2799, PF2833, PF2903, PF2911, PF2972, PF2993, PF3034, PF3043, PF3051, PF3056, PF3060, PF3066, PF3073, PF3078, PF3079, PF3082, PF3084, PF3086, U5, Y244, Y251, Y298, Y384, Z3114, Z3506, Z6125

Variants haplogroup G-L1259 branch: 7 variants

L1259, CTS2951, FGC77407, FGC77411, FT81076, PF2824, PF2826

Variants haplogroup G-L30 branch: 47 variants

L30, CTS10449, CTS1093, CTS11324, CTS11434, CTS1180, CTS12810, CTS376, CTS4227, CTS5463, CTS574, CTS7992, CTS90, CTS9763, F1136, F1733, F3139, F788, FGC81433, FGC81737, L1257, L1260, L190, L32, PF2811,  PF2838, PF2870, PF2913, PF3028, PF3089, PF3090, PF3254, PF3270, PF3276, PF3277, PF3278, PF3280, PF3281, Y359, Z3047, Z3051, Z3086, Z3103, Z3238, Z3260, Z3465, Z3487

Variants haplogroup G-L141 branch: 14 Variants 

L141, CTS1891, CTS2488, CTS8143, CTS9605, CTS9957, F2121, FGC81432, PF2813, PF2818, PF3275, Y378, Z3058, Z3074

Variants haplogroup G-P303 branch: 38 variants 

P303, CTS10366, CTS10725, CTS1949, CTS424, CTS4454, CTS6719, CTS688, CTS7698, CTS946, FGC81739, FGC82651, PAGES00098, PF3329, PF3330, PF3332, PF3333, PF3339, PF3342, PF3343, S8782, Y125207, Y253, Y270, Y350, Y354, Y382, Z3481, Z3488, Z3489, Z3490, Z3491, Z3492, Z3493, Z3494, Z3495, Z3496, Z6136

Variants haplogroup G-L140: branch 14 variants

L140, CTS12570, CTS12891, CTS796, PF2823, PF3331, PF3337, Y307, Y324, Z3155, Z3220, Z3245, Z3501, Z767

Variants haplogroup G-PF3346 branch: 1 variant

PF3346

Variants haplogroup G-PF3345 branch: 3 variants

PF3345, FGC799, Z3065

Variants haplogroup G-CTS342 branch: 5 variants

CTS342, CTS2821, Z3039, Z3049, Z723

Variants haplogroup G-L497 branch: 49 variants

L497, BY34319, CTS12867, CTS12895, CTS1899, CTS4197, CTS5351, CTS5762, CTS6235, CTS7111, CTS8596, F3464, FGC470, FGC472, FGC81738, FGC81741, FGC8301, FGC85467, PF6850, PF6852, S10780, Z1822, Z3041, Z3108, Z3147, Z3149, Z3160, Z3169, Z3173, Z3181, Z3207, Z3212, Z3283, Z3390, Z3480, Z3513, Z3528, Z6379, Z730, Z731, Z732, Z733, Z734, Z736, Z737, Z744, Z749, Z750, Z756

Variants haplogroup G-CTS9737 branch: 12 variants

CTS9737, CTS11194, CTS5089, CTS6711, CTS7012, CTS730, Z1900, Z3035, Z3205, Z6380, Z729, Z735

Variants haplogroup G-Z1817 branch: 15 variants

Z1817, CTS11352, CTS11605, CTS3226, CTS8701, FGC475, S25662, Z1821, Z3141, Z3442, Z6900, Z6901, Z742, Z747, Z755

Variants haplogroup G-Z727 branch: 8 variants

Z727, CTS2100, CTS7142, Y3102, Z16776, Z3195, Z725, Z753

Variants haplogroup G-FGC477 branch: 2 variants

FGC477, FGC7516

Variants haplogroup G-Z6748 branch:   29 variants

Z6748, BY8142, FGC476, FGC479, FGC481, FGC482, FGC483, FGC484, FGC485, FGC487, FGC488, FGC490, FGC496, FGC498, FGC499, FGC500, FGC502, FGC504, FGC505, FGC506, FGC507, FGC509, FGC511, FGC512, FGC516, FGC517, FGC518, FT73641, Y172988 

Variants haplogroup G-Y38335 branch: 2 variants

Y38335, Y132516

Variants haplogroup G-FGC486 branch: 5 variants

FGC486, FGC492, FGC494, FGC497, FGC7517

Variants haplogroup G-Z40857 branch: 5 variants

Z40857, FGC510, Y132533, Z40860, Z5838

Variants haplogroup G-Y132505 branch: 2 variants

Y132505, FT47083

Variants haplogroup G-BY211678 brach: 4 variants

BY211678, BY151390, FT47770, Y13253

[19] Andrew Curry, The first Europeans weren’t who you might think, National Geographic, August 2019, https://www.nationalgeographic.com/culture/article/first-europeans-immigrants-genetic-testing-feature

See also:

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

Early European Farmers, Wikipedia, This page was last edited on 5 February 2023, https://en.wikipedia.org/wiki/Early_European_Farmers

Reich, David Who We are and how We Got Here: Ancient DNA and the New Science of the Human Past. Oxford University Press. 2018

Lazaridis, Iosif; et al. (July 25, 2016). “Genomic insights into the origin of farming in the ancient Near East”. Nature. Nature Research. 536(7617): 419–424. Bibcode:2016Natur.536..419L. doi:10.1038/nature19310. PMC 5003663. PMID 27459054 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5003663/

González-Fortes, Gloria; et al. (June 19, 2017). “Paleogenomic Evidence for Multi-generational Mixing between Neolithic Farmers and Mesolithic Hunter-Gatherers in the Lower Danube Basin”. Current Biology. Cell Press. 27 (12): 1801–1810. doi:10.1016/j.cub.2017.05.023. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5483232/

Lazaridis, Losif (December 2018). “The evolutionary history of human populations in Europe”. Current Opinion in Genetics & Development. Elsevier. 53: 21–27. arXiv:1805.01579. doi:10.1016/j.gde.2018.06.007https://www.sciencedirect.com/science/article/abs/pii/S0959437X18300583

Shennan, Stephen (2018). The First Farmers of Europe: An Evolutionary Perspective. Cambridge World Archaeology. Cambridge University Press. doi:10.1017/9781108386029. ISBN 9781108422925

Nikitin, Alexey G.; et al. (December 20, 2019). “Interactions between earliest Linearbandkeramik farmers and central European hunter gatherers at the dawn of European Neolithization”. Scientific Reports. Nature Research. 9 (19544): 19544. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6925266/

[20] “Before Present (BP) years, also known as “time before present” or “years before present“, is a time scale used mainly in archaeology, geology and other scientific disciplines to specify when events occurred relative to the origin of practical radiocarbon dating in the 1950s. Because the “present” time changes, standard practice is to use 1 January 1950 as the commencement date (epoch) of the age scale.”

Before Present, Wikipedia, This page was last edited on 29 January 2023, https://en.wikipedia.org/wiki/Before_Present

Regarding the bottleneck, see the following articles:

Karmin, M. et al. A recent bottleneck of Y chromosome diversity coincides with a global change in culture. Genome Res. 25, 459–466 (2015), https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4381518/

Premo, L. S. Hitchhiker’s guide to genetic diversity in socially structured populations. Curr. Zool. 58, 287–297 (2012).

Batini, C. et al. Large-scale recent expansion of European patrilineages shown by population resequencing. Nat. Commun. 6, 7152 (2015).

Poznik, G. D. et al. Punctuated bursts in human male demography inferred from 1,244 worldwide Y-chromosome sequences. Nat. Genet. 48, 593–599 (2016).

[21] Caril Zimmer, In Ancient DNA, Evidence of Plague Much Earlier Than Previously Known, NY Times, Oct 22, 2015, https://www.nytimes.com/2015/10/23/science/in-ancient-dna-evidence-of-plague-much-earlier-than-previously-known.html.

Rasmussen S, Allentoft ME, Nielsen K, Orlando L, et al, Early divergent strains of Yersinia pestis in Eurasia 5,000 years ago. Cell. 2015 Oct 22;163(3):571-82. doi: 10.1016/j.cell.2015.10.009. Epub 2015 Oct 22. PMID: 26496604; PMCID: PMC4644222. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4644222/

Pooja Swali1, Rick Schulting, Alexandre Gilardet, et al, Yersinia pestis genomes reveal plague in Britain 4,000 years ago, January 26, 2022, bioRXiv, https://www.biorxiv.org/content/10.1101/2022.01.26.477195v1.full.pdf

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

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

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

James McNish, The Beaker people: a new population for ancient Britain, Natural History Museum, 22 Feb 2018, https://www.nhm.ac.uk/discover/news/2018/february/the-beaker-people-a-new-population-for-ancient-britain.html

Bell Beaker culture, Wikipedia, This page was last edited on 5 February 2023, https://en.wikipedia.org/wiki/Bell_Beaker_culture

[24] Rob Spencer, SNP Tracker, Tracking Back: A Website for Genetic Genealology Tools, experimentation, and discussion, http://scaledinnovation.com/gg/snpTracker.html

[25] Maps of Neolithic & Bronze Age Migrations Around Europe, Eupedia, https://www.eupedia.com/europe/neolithic_europe_map.shtml

[26] Y-DNA Tools, International Organization of Genetic Genealology Wiki, This page was last edited on 30 June 2022, https://isogg.org/wiki/Y-DNA_tools

[27] 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

[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

[29] 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