My Ongoing Discoveries from Autosomal DNA Tests

I completed a variety of autosomal (atDNA) tests from various genealogy companies to determine if I could find unknown living genetic relatives and to provide additional information on our common ancestors.

Autosomal DNA testing can accurately trace ancestry back approximately 5-6 generations and provide information on living relatives. These tests can provide added information and facts on completing family trees for generations that contain both living and deceased relatives and the younger generations that virtually contain all living relatives.

Illustration One: Benefits of atDNA Testing

There are different strategies for comparing DNA results from different companies. [1] I simply took atDNA tests from each of the sampled companies to compare differences in estimating ethnicity descent results and to determine if here were any matches with unknown living genetic relatives in each of their respective DNA databases.

I have completed atDNA tests with the following DNA companies: ancestry.com (AncestryDNA), 23andMe, LivingDNA, FamilyTreeDNA, and CriGenetics. [2] The most promising results were obtained from AncestryDNA and 23andMe.

As indicated in the first part of this story, the DNA companies analyze hundreds of thousands of single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosomes. These SNPs are specific locations in the genome where genetic variation commonly occurs between individuals. The companies use different proprietary algorithms and imputation methods to analyze the DNA. The DNA match results can vary between companies based on the software and micro chip technology utilized, the selection and number of SNPs tested, and the size of company’s database .

The atDNA tests may result in hundreds of ‘matches’. Each of the companies compare the SNP data between two individuals to identify segments of DNA that appear to be identical. These matching segments indicate DNA that are likely to be inherited from a common ancestor. [3]

The length of matching SNP segments is measured in centimorgans (cM). (See illustration two below.) [4] The amount of shared cMs is compared to expected ranges for different relationships to predict how two people may be related. Close relationships like parent/child or full siblings have very distinct amounts of shared DNA, while more distant relationships have overlapping ranges or shared DNA or cMs.

Illustration Two: CentiMorgans in a Physical Map

Click for Larger View | Source: Eric Green, Physical Map, National Human Genome Research Institute, https://www.genome.gov/genetics-glossary/Physical-Map ; Rotimi, Charles, Genetic Map, National Human Genome Research Institute, https://www.genome.gov/genetics-glossary/Genetic-Map

Where the individual being tested, such as myself, has a number of shared SNPs and a number of consecutive SNPs in common with another tested individual in the company’s database, it can be inferred that we share a segment of DNA at that part of our respective genomes. If the segment is longer than a threshold amount set by the testing company, then we are considered to be a match. [5]

Clarifying Relationships: The Number of Shared cMs and Length of cMs

Two central or key statistics for interpreting atDNA matches are the number of shared cM segments and the length of the shared cM segments (or the percentage of the genome that is shared). When looking at atDNA comparisons, the “shared cM” is the total length of the DNA one shares with another person. The “shared segments” are how many blocks the matching atDNA is broken into. Longer block segments generally indicate a closer relationship. Companies set minimum thresholds for segment length and total shared DNA to be considered a match. [6]

To put the concept of cMs in perspective, an individual typically receives approximately 3,400-3,700 cMs from each biological parent.  Each person has about 6,800 cMs in total. [7]

As indicated in the first part of this story, the random nature of genetic inheritance leads to variability in how much DNA is shared through successive generations. This is known as variable expressivity. [8] When moving through successive generations, the amount of DNA inherited from each ancestor roughly halves with each generation, meaning you inherit approximately 50% from your parents, 25% from each grandparent, 12.5% from each great-grandparent, and so on. As you move further back in generations, the percentage of DNA inherited from each ancestor decreases exponentially.

The process of genetic recombination during meiosis ensures that the exact DNA segments inherited from each parent are randomized, leading to variation even between siblings in the next generation. [9] For example, full siblings may share anywhere from about 35% to 65% of their DNA or 1613 cMs to 3488 cMs. First cousins typically share around 12.5% of their DNA or about 866 cMs but the actual range can vary significantly between 396 to 1397 cMs. This variability increases with more distant relationships, making it harder to precisely determine the degree of relatedness based solely on shared atDNA percentages.

“(S)ome genuine genealogical third cousins will not show up as a match because, although both cousins will have inherited DNA from their common ancestors they do not share any overlapping DNA segments. Beyond about five or six generations we will have some genealogical ancestors with whom we share no DNA. They are our genealogical ancestors but not our genetic ancestors.  If we go back 450 years we have over 32,000 genealogical ancestors but we will have DNA from only around 1000 of these ancestors.” [10]

The diminishing amount of cMs shared with relatives can be depicted in charts that display information using centimorgans. A notable “shared cM chart,” which is used to visualize the likelihood of a relationship based on the amount of shared DNA measured, is called the “The Shared cM Project 4.0 tool chart”. It can be accessed through the DNA Painter platform. [11] (See illustration three.)

Illustration Three: Chart of Matching Relationships and Their Respective Average cM and Ranges of cMs to an atDNA Tester

Click for Larger View | Source: Johnny Perl, Introducing the updated shared cM tool, 27 Mar 2020, DNA Painter Blog, https://dnapainter.com/blog/introducing-the-updated-shared-cm-tool/

The Shared cM Project 4.0 tool chart graphically illustrates the range of cMs and overlap that are associated with specific genetic relationships. The chart provides information on the average cMs and the range of cM values from low to high for each genetic relationship. The values are derived from a collaborative data collection and analysis project created to understand the ranges of shared cMs associated with various known relationships. Version four of this project is based on shared cM data for nearly 60,000 known relationships. [12]

The Shared cM Project is a collaborative data collection and analysis project that helps genealogists understand potential relationships between DNA matches based on shared genetic material. The project was created by Blaine Bettinger to understand the ranges of shared centimorgans (cM) associated with various known family relationships. The table one below indicates the range of cMs that are associated with ten groupings of relationships that were part of the Shared cM Project. [13] The table provides the number of samples in each group and the average value, min and max values, the standard deviation (which can be used to determine the frequency curve of the values), and the expected cM value for each group.

Table One: Centimorgan Groupings by Relationship in the Shared cM Project

Click for Larger View | Source: Bettinger, Blaine, Version 4.0! March 2020 Update to the Shared cM Project!, The full PDF for Version 4.0 of the Shared cM Project Paage 7,The Genetic Genealogist,
https://thegeneticgenealogist.com/wp-content/uploads/2020/03/Shared-cM-Project-Version-4.pdf

The following example (illustration four) depicts the variability of inheriting autosomal DNA and the utility of using the number of shared cM segments and the length of the shared cM segments to determine possible relationships. Illustration four below shows 22 lines that symbolize the 22 autosomal chromosomes that were inherited from one parent for a fictitious person. The darker color in each of the lines represents the segments of cMs that were inherited from the parent. In this example, the person has inherited 3524 cMs and 22 segments from one parent. The individual has inherited 22 segments in 22 chromosomes. They are really long segments. In fact, 16 of the 22 segments reflect entire chromosomes. In addition, the child inherited 3524 cMs, well within the cM range of 2400 – 3700 cMs for a parent – child relationship, as depicted in table one.

Illustration Four: Example of Inherited cMs from One Parent

Click for Larger View | Source: Modified version of an illustration found in Nguyen, Tiffany, What’s the difference between shared centimorgans and shared segments?, 11 Nov 2019, The Tech Interactive, https://www.thetech.org/ask-a-geneticist/articles/2019/centimorgans-vs-shared-segments/

Illustration five below is an example of a grandparent – grandchild match for the same person (the grandchild). In the example, the number of shared segments is very similar to the number shared segments found in illustration three with the parent. In fact there is one more segment than that found in the parent relationship. However, the length of the segments are all shorter than the segments shared between parent and child. In addition, the total number of cMs are significantly less than that found with the parent.

Illustration Five: Example of Inherited cMs from One Grandparent

Click for Larger View | Source: Modified version of an illustration found in Nguyen, Tiffany, What’s the difference between shared centimorgans and shared segments?, 11 Nov 2019, The Tech Interactive, https://www.thetech.org/ask-a-geneticist/articles/2019/centimorgans-vs-shared-segments/

The total number of centimorgans that an atDNA tester shares with a match is typically a good indicator of how closely related they are to someone else. However, shared cMs cannot always indicate exactly how that tester is related to a match. Different types of relationships may share similar amounts of DNA.

In the grandparent – grandchild example above, the furthest back you might need to go to find common ancestors for a match of 1518cM is the grandparent level. If you are uncertain of the actual relationship of the match and limited to just reading the cM results of a test, the connection may be closer. Depending on the tester’s family, this match could be a close younger generation relative, such as the descendant of the tester’s sibling if he or she had one or more siblings.

Based on the ranges of cMs associated with specific family relationships, 1518 cMs could point to a grandparent, aunt or uncle, a half sibling, a niece or nephew or a grandchild. This is illustrated by plugging in the 1518 cM value in the Shared cM Project 4.0 tool. (See illustration six).

Illustration Six: Expected Relationships Based on Shared cMs

Click for Larger View | Source: Johnny Perl, Introducing the updated shared cM tool, 27 Mar 2020, DNA Painter Blog, https://dnapainter.com/blog/introducing-the-updated-shared-cm-tool/

Comparison of Results from Different DNA Companies

As indicated in the first part of this story, my experience with atDNA tests have largely resulted in the initial discovery of many living second and third generational cousins. This fact alone is amazing. However, many of the matches fail to document their respective lines of descent. The lack of this additional genealogical information makes it difficult to document where our common distant family connections are located.

The ability to analyze and comprehend the sheer number of autosomal DNA matches from the various DNA tests is daunting. As reflected in table two, there are thousands of ‘possible’ matches based on my atDNA results provided by four DNA companies..

Table Two: Number of atDNA Matches for My Test Results by DNA Company

DNA CompanyNumber of Genetic
Matches with
Shared DNA
Maximin
cM Match
Value
Minimum
cM Match
Value
Ancestry DNA17,11834798
23andMe 1,5001586 [14] 16
FamilyTreeDNA3,639497
LivingDNA3024311

Testing companies compare your DNA profile to their database of test results from other customers. They search for other individuals who share significant DNA segments with you. Each company has specific threshold values associated with cMs and cM length. (See table four in the first part of this story.) [15] The size and pattern of shared DNA is used to predict the likely relationship. Relationships are typically detected confidently for third cousins or closer, with decreasing probability for more distant relations.

Depending on the DNA company, as reflected in table three, the predicted relationship is depicted by different measures: the total percentage of shared DNA, the number of shared segments, the length of the shared segments, the longest block of cMs. Different companies may also provide slightly different relationship estimates due to variations in their testing algorithms and reference databases. Despite the different presentation of match results, comparing results between different compamies is possible.

Table Three: Type of Matching Results Provided by DNA Company

DNA
Company
Total
cMs
Percent
of cMs
Shared
Number
of Shared
Segments
Longest
cM
Block
AncestryDNAXX
23andMeXX
FamilyTreeDNAXX
LivingDNAXXX

Separating the Wheat from the Chaff

DNA Match Filtering Criteria

It would be very tedious to comb through all of the matches identified by the four DNA companies. I also believe the majority of match results will not yield many true matches. There is a need to utilize filtering criteria to reduce the large number of potential matches to a manageable number and focus on matches that may lead to legitimate family relationships.

Based on my review of research strategies associated with autosomal testing, I have employed two criteria in recursive order. The first involves establishing a cut off value for cMs shared. The second criteria is focusing on matches that provide family tree information.

Many researches have documented that it was less likely of discovering a kinship relationship with match cases that shared less than 15 cMs. [16]

While it may seem at first that all shared segments of DNA could constitute genealogical evidence, unfortunately some small segments are … creating “false positive” matches for reasons other than recent ancestry. These segments sometimes match because of lack of phasing, phasing errors, or a variety of other reasons. One thing, however, is clear: there is no debate in the genetic genealogy community that many small segments are false positive matches. There IS debate, however, regarding the rate of false positive matches, and what that means for the use of small segments as genealogical evidence. [17]

Most people are unable to trace all of their ancestral lines back ten generations or beyond. The common ancestral couple cannot therefore be identified through atDNA testing. Even if a shared ancestral couple can be identified, without tracing all the other ancestral lines in your family tree you cannot eliminate the possibility of shared ancestry on other as yet undocumented lines. [18]

Many matches under 15 cMs will share ancestry more than five or more generations ago and will be mostly beyond the reach of genealogical records. Therefore, I have summarily eliminated matches that are 15 cMs or less. Based on estimates derived from the Shared cM Project Tool, a match of 15cM has a wide range of remote, possible relationships. (See illustration sseven.) The connection may be within 4th-Great-Grandparent level, but the common ancestors could also be more generations back. [19]

illustration Seven: Expected Relationships Based on 15 Shared cMs or Less

Click for Larger View | Source: Johnny Perl, Introducing the updated shared cM tool, 27 Mar 2020, DNA Painter Blog, https://dnapainter.com/blog/introducing-the-updated-shared-cm-tool/

There are other professional genealogists, such as Blaine Bettinger, that lower the bar to above 5 cMs.

“(T)he very first thing I do with the spreadsheet is sort it by size and delete every segment smaller than 5 cM. For me, there is too much uncertainty surrounding small segments to base any conclusion on them.” [20]

I call small segments (which I usually classify as 5 cM or less) as POISON because it is currently impossible to decipher between which are real segments and which are not.” [21]

According to population genetics theory all individuals have common ancestry in the distant past, and we all have what are called short, old IBD segments in common. [22] Identity By Descent (IBD) segments are stretches of DNA that two or more individuals have inherited from a common ancestor without any recombination occurring within that segment. The probability of an IBD segment persisting decreases exponentially over generations due to recombination. [23]

In general, the larger the shared segments the more likely that the match is valid. Valid segments under 7 cM cannot be reliably detected with the currently available genetic genealogy tests. [24]  

For the purposes of genetic genealogy the focus is on detecting large IBD segments within a genealogical timeframe (effectively within the last ten generations) where there is a possibility of identifying the common ancestor through documentary records. In general terms, the larger the segment the closer the relationship, but the frequency of the segment also needs to be taken into account. High-frequency IBD segments are more likely to be a signal of distant sharing at the population level whereas a segment that is only observed in two independently sampled individuals is more likely to be IBD. [25]

Although there is only a low chance of sharing enough DNA with a specific distant cousin for the relationship to be detected, we have a large number of distant cousins and so many of these more distant cousins will appear in our match lists.” [26]

The following table four shows the expected number of cousins at different degrees of relationship, the expected amount of cMs for each degree of cousin and the percent of detecting the relationship. [27]. The trend indicates an high probability or even chance of discovering first through fourth cousins. This would imply matches above 60 cM are less likely to be influenced by false positive matches and matches between 15 and 60 have a ‘fifty-fifty’ chance of being real or reflect the back ground noise of distance common ancestors.

Table Four: Chance of Detecting Cousins

Degree of
Cousin
Expected
Amount
of IBD (cM)
Percent
Chance of
Detecting
First900100%
Second225100%
Third5688.7
Fourth1445.9
Fifth3.514.9
Sixth0.884.1
Secventh0.221.1
Eighth0.0550
Nineth0.0140
Tenth0.00340
Source: Henn, Brenna M, Hon L, Macpherson JM, Eriksson N, Saxonov S, Pe’er I, et al. (Apr 3 2012) Cryptic Distant Relatives Are Common in Both Isolated and Cosmopolitan Genetic Samples. PLoS ONE 7(4): e34267. https://doi.org/10.1371/journal.pone.0034267

As reflected in table five, my match results from the four DNA companies have isolated 3,047 matches above the 15 cM level. This number of potential matches is still unreasonable to comb through and assess their fruitfulness of establishing a genetic relationship. I considered initially tightening the cM limit to 90 cMs.

Table Five: Number of Genetic Matches Based on cMs

Company 10 cM
& Less
15-11 cm15-89Greater
than
90
AncestryDNA985065157609
23andMe0014964
FamilyTreeDNA118519395150
LivingDNA4352630
Total110398489303413

The furthest back you might need to go to find common ancestors for a match of 90cM is 4th-Great-Grandparent level or generation 7 on your pedigree chart. [28]

Once I have assessed the fruitfulness of establishing a kinship relation with matches above 90 cMs, I figure I can look at the other matches at successive lower cM levels.

The second filtering criteria that I have used is the availability of family tree information found with specific matches over 90 cMs. As indicated in table six below, three of the four DNA companies that I have completed atDNA tests provide the ability or option to either add family tree information or, at the minimum, family surnames.

Table Six: The Option to Add Family Tree or Surname Information with atDNA Results

CompanyFamily
Tree
Infor-
mation
Family
Sur-
names
Infor-
mation
Parents’s
Birth-
place
Grand-
parents’
Birth-
place
Other ancestors’ birth-
place
Identify
Common Ancestor
AncestryDNAYesYes***Yes
23andMeYesYesYesYesYes
FamilyTree
DNA
YesYes***Yes
LivingDNANoNoNoNoNoNo
* This information can be found if a tester provides information on their family tree. It is not a separate category of information .

My AncestryDNA and 23and Me Matches: Close Family

The largest group of match results and the largest number of confirmed matches is from AncestryDNA. As of October 2024, the atDNA results in the AncestryDNA data base identified 854 possible matches on both sides (paternal and maternal) of my family. Of those 854, there are four DNA testers that are identified as ”Close Family”. An additional five are identified as “Extended Family”. The remaining 845 matches are categorized as “Distant Family”. [29]

In the early 2000’s, based on my suggestions, my father and paternal aunt completed autosomal tests. More recently, my aunt’s grandson, also completed an AncestryDNA test. As depicted in illustration seven, their results confirm their respective genetic ties to me.

Illustration Eight: My Results from AncestryDNA

Click for Larger View | Source: AncestryDNA

The DNA results for my father confirmed the accuracy of the DNA testing process. The range of matching cMs associated with my match with my father corresponds with the cM range of parent/child. [30] The match results for my paternal aunt also confirm the accuracy of the atDNA match for aunt/uncle. (See illustration nine.)

Illustration Nine: Average cMs for an Aunt

Click for Larger View | Source: Inputting the cM value of 1575 into the Share cM Project Tool found at Bettinger, Blaine,, The Shared cM Project 4.0 Tool v4, Mar 2020, DNA Painter, https://dnapainter.com/tools/sharedcmv4

The results for James were also spot on as my first cousin once removed (the son of one of my first cousins).

Illustration Ten: Average cMs for a First Cousin Once Removed

Source: Inputting the cM value of 359 into the Shared cM Project Tool found at Bettinger, Blaine,, The Shared cM Project 4.0 Tool v4, Mar 2020, DNA Painter, https://dnapainter.com/tools/sharedcmv4

The filtering match displays for AncestryDNA and 23andMe are a bit different. While AncestryDNA provides total shared cMs and the percent of shared DNA, 23andMe provides percent of DNA shared and number of shared segments. There are two ways to convert 23andMe matches to centimorgans (cMs). You can use the Shared cM Project tool at DNA Painter and enter the percentage of shared DNA in the percentage box on the online tool. The tool will show you the number of cMs. [31]

If I use the 90 cM are an initial cut off for viewing matches, I need to convert percent shared cMs to an estimate of the amount of cMs shared.

There were two 23andMe matches that were above the 90 cM filtering criteria. The first was Christopher G who shared an estimated 641 cMs or 8.62 percent of shared cMs with me. As indicated in illustration eleven, 23andMe predicted that Christopher is my first cousin once removed. The second match was with Alexandra G. who shared an estimated 494 cMs or 6.64 percent of shared cMs with me. 23andMe predicted that Alexandra is my second cousin.

Illustration Eleven: 23andMe Close Family Matches

Click for Larger View | Source: 23andMe

Utilizing the Shared cM Project tool for Christopher’s 8.62 percent shared cMs and Alexandra’s 6.64 percent indicates that the furthest back I might need to go to find common ancestors for each match is my 2nd-Great-Grandparent level or generation 5 on my pedigree chart. For Christopher.

As indicated in table seven, the inputted cM values in the Shared cM Project Tool also predict that there is a57 percent chance that Chritopher is my first cousin once removed. The inputted cM values in the Shared cM Project Tool predict that there i a 90 percent chance that Alexandra is my first cousin once removed, contrary to 23andMe’s prediction.

Table Seven: Probability of Expected cM Relationship based on Percentage of Shared DNA

MatchPercent of
Shared DNA
Probability of
Relationship
Expected Relationship
Christopher8.62%57%2Great-Aunt /Uncle,
Half Great-Aunt Uncle
Half 1C
1C1R
Half Great-Niece/ Nephew
Great-Great-Niece Nephew
Christopher8.62%43%Great-Grandparent
Great-Aunt/Uncle
Half Aunt/Uncle
1C
Half Niece/Nephew
Great-Niece/Nephew
Great-Grandchild 
Alexandra6.64%90 %Great-Great-Aunt/Uncle
Half Great-Aunt Uncle
Half 1C
1C1R
Half Great-Niece/Nephew 2 Great Niece/Nephew
Source: The Shared cM Project Tool found at Bettinger, Blaine,, The Shared cM Project 4.0 Tool v4, Mar 2020, DNA Painter, https://dnapainter.com/tools/sharedcmv4

Both Christopher and Alexandra are son and daughter respectively of one of my paternal cousins. As such, they are both first cousins once removed.

Continuation

A continuation of my discussion of atDNA matches continues in the next part of “Ongoing Discoveries from Autosomal DNA Tests”. The continuation will discuss AncestryDNA “extended family” matches and 23andMe match results.

Sources

Feature Image: An amalgam of three different images: (1) The network image of individuals is from Woodbury, Paul, “Who Is This?” 6 Steps to Determine Genetic Relationships of Your DNA Matches, April 2019, LegacyTree Genealogists, https://www.legacytree.com/blog/determine-genetic-relationships . (2) The Colorized chart from Johny Perl, Introducting the updated shared cM tool, 27 Mar 2020, DNA Painter Blog, https://dnapainter.com/blog/introducing-the-updated-shared-cm-tool/ and (3) A Diagram depicting the relationship of a third cousin from 23andMe..

[1] Estes, Roberta, DNA Testing and Transfers – What’s Your Strategy?, 9 Apr 2019 , DNAeXplained – Genetic Genealogy, https://dna-explained.com/2019/04/09/dna-testing-and-transfers-whats-your-strategy/

Estes, Roberta, Comparing DNA Results – Different Tests at the Same Testing Company, 18 May 2023, DNAeXplained – Genetic Genealogy, https://dna-explained.com/2023/05/18/comparing-dna-results-different-tests-at-the-same-testing-company/

[2] With the exception of CriGenetics, each of the companies provide atDNA matches that correspond to family relationships within six geneations. I did not purchase the ‘premium’ level of testing with CriGenetics which included possible DNA matches from their database.

[3] Autosomal DNA Statistics, International Society of Genetic Genealogy Wiki, , This page was last edited on 17 October 2022, https://isogg.org/wiki/Autosomal_DNA_statistics

Our Autosomal DNA Test (Family Finder™), FamilyTreeDNA Help Center, https://help.familytreedna.com/hc/en-us/articles/4411203169679-Our-Autosomal-DNA-Test-Family-Finder

[4] Centimorgan, Wikipedia, This page was last edited on 1 May 2024,https://en.wikipedia.org/wiki/Centimorgan

Centimorgan, National Human Genome Research Institiue, https://www.genome.gov/genetics-glossary/Centimorgan

centiMorgan, International Society of Genetic Genealogy Wiki ,This page was last edited on 15 August 2024, https://isogg.org/wiki/CentiMorgan

[5] Estes, Roberta, Concepts – CentiMorgans, SNPs, and Pickin’ Crab, 30 Mar 2016, DNAeXplained – Genetic Genealogy, https://dna-explained.com/2016/03/

Autosomal DNA match thresholds, International Society of Genetic Genealogy Wiki, This page was last edited on 31 August 2024, https://isogg.org/wiki/Autosomal_DNA_match_thresholds

[6] Autosomal DNA Statistics, International Society of Genetic Genealogy, This page was last edited on 17 October 2022, https://isogg.org/wiki/Autosomal_DNA_statistics

Fully identical region, International Society of Genetic Genealogy, This page was last edited on 1 April 2022, https://isogg.org/wiki/Fully_identical_region

Half-identical region, International Society of Genetic Genealogy, This page was last edited on 2 June 2017, https://isogg.org/wiki/Half-identical_region

Identical by descent International Society of Genetic Genealogy, This page was last edited on 14 September 2023, https://isogg.org/wiki/Identical_by_descent

Johny Perl, Introducing the updated shared cM tool, 27 Mar 2020, DNA Painter Blog, https://dnapainter.com/blog/introducing-the-updated-shared-cm-tool/

Autosomal DNA match thresholds, International Society of Genetic Genealogy Wiki, This page was last edited on 31 August 2024, https://isogg.org/wiki/Autosomal_DNA_match_thresholds

Pereira, Rita, Pietro Biroli, Stephanie Von Hinke, Hans Van Kippersluis, Titus Galama, Niels Rietveld, and Kevin Thom. 2022. “Gene-environment Interplay in the Social Sciences.” OSF Preprints. March 4. doi:10.31219/osf.io/d96z3

[7] Nguyen, Tiffany, What’s the difference between shared centimorgans and shared segments? Understanding Genetics, 11 November 2019, The Tech Interactive, https://www.thetech.org/ask-a-geneticist/articles/2019/centimorgans-vs-shared-segments/

[8] What are reduced penetrance and variable expressivity?, MedlinePlus, https://medlineplus.gov/genetics/understanding/inheritance/penetranceexpressivity/

Miko, Iiona,  Phenotype variability: penetrance and expressivity. Nature Education 1(1):137 , 2008, https://www.nature.com/scitable/topicpage/phenotype-variability-penetrance-and-expressivity-573/

Expressivity (genetics), Wikipedia, This page was last edited on 9 October 2024, https://en.wikipedia.org/wiki/Expressivity_(genetics)

[9] Genetic Recombination, Wikipedia, This page was last edited on 5 October 2024, https://en.wikipedia.org/wiki/Genetic_recombination

Woodbury, Paul, The Journey of DNA’s Inheritance Paths: X-DNA and Autosomal DNA, LegacyTree, https://www.legacytree.com/blog/x-dna-autosomal-dna-inheritance-paths

Understanding Inheritance, AncestryDNA, https://support.ancestry.com/s/article/Understanding-Inheritance

[10] Autosomal DNA Statistics, International Society of Genetic Genealogists Wiki ,This page was last edited on 17 October 2022,, https://isogg.org/wiki/Autosomal_DNA_statistics

[11] Perl, Johnny, Introducing the updated shared cM tool, 27 Mar 2020, DNA Painter Blog, https://dnapainter.com/blog/introducing-the-updated-shared-cm-tool/

Perl, Johnny, Help: What is DNA Painter?, DNA Painter, https://dnapainter.com/help

Bettinger, Blaine, The Shared cM Project, 29 May 2015, The Genetic Genealogist, https://thegeneticgenealogist.com

Bettinger, Blaine, Version 4.0! March 2020 Update to the Shared cM Project!, The Genetic Genealogist, https://thegeneticgenealogist.com/2020/03/27/version-4-0-march-2020-update-to-the-shared-cm-project/

Bettinger, Blaine, Version 4.0! March 2020 Update to the Shared cM Project!, The full PDF for Version 4.0 of the Shared cM Project ,The Genetic Genealogist, https://thegeneticgenealogist.com/wp-content/uploads/2020/03/Shared-cM-Project-Version-4.pdf

[12] Bettinger, Blaine, Version 4.0! March 2020 Update to the Shared cM Project!, The full PDF for Version 4.0 of the Shared cM Project ,The Genetic Genealogist, https://thegeneticgenealogist.com/wp-content/uploads/2020/03/Shared-cM-Project-Version-4.pdf

[13] Ibid, Page 7

[14] 23andMe provides their match results in two forms: percentage of DNA shared and the number of cM segments. There are two ways to convert 23andMe matches to centimorgans (cM), you can use the Shared cM Project tool at DNA Painter:

  1. Go to the Shared cM Project tool at DNA Painter
  2. Enter the percentage of shared DNA in the percentage box
  3. The tool will show you the cMs

Bettinger, Blaine,, The Shared cM Project 4.0 Tool v4, Mar 2020, DNA Painter, https://dnapainter.com/tools/sharedcmv4

You can also use a ‘quick and dirty’ approach to convert the percentage into centimorgans by just multiplying your percentage by 68.

Cooke, Lisa, What’s a CentiMorgan, Anyway? How DNA Tests for Family History Measure Genetic Relationships, 23 Oct 2017, Genealogy Gems,  https://lisalouisecooke.com/2017/10/23/genetic-relationships-centimorgans/

[15] Autosomal Match Thresholds, International Society of Genetic Genealogists Wiki, This page was last edited on 31 August 2024, https://isogg.org/wiki/Autosomal_DNA_match_thresholds

[16] Bettinger, Blaine, Small Matching Segments – Friend or Foe?, The Genetic Genealogist, https://thegeneticgenealogist.com/2014/12/02/small-matching-segments-friend-foe/

[17] One source indicates that any match with 15 cM has a 60 percent chance of being a sixth cousin, sixth cousin once removed, fifth cousin, sixth cousin twice removed, fourth cousin once removed, fifth cousin once removed, seventh cousin, half third cousin twice removed, fourth cousin twice removed, fifth cousin twice removed, seventh cousin once removed, third cousin three times removed, fourth cousin three times removed, fifth cousin three times removed, eighth cousin, and more distance relationships.

See: Bettinger, Blaine,, The Shared cM Project 4.0 Tool v4, Mar 2020, DNA Painter, https://dnapainter.com/tools/sharedcmv4

Another source indicates that there is a remote change of finding a kinship tie with a match at 14 cM or less.

See: Henn, Brenna M, Hon L, Macpherson JM, Eriksson N, Saxonov S, Pe’er I, et al. (Apr 3 2012) Cryptic Distant Relatives Are Common in Both Isolated and Cosmopolitan Genetic Samples. PLoS ONE 7(4): e34267. https://doi.org/10.1371/journal.pone.0034267

Identical by descent, International Society of Genetic Genealogy Wiki, This page was last edited on 14 September 2023, https://isogg.org/wiki/Identical_by_descent

Another source cautions the use of matches less than 5 cMs to avoid false positive results.

See: Bettinger, Blaine, Small Matching Segments – Friend or Foe?, The Genetic Genealogist, https://thegeneticgenealogist.com/2014/12/02/small-matching-segments-friend-foe/

Bettinger, Blaine, The Danger of Distant Matches, 6 Jan 2017, The Genetic Genealogist, https://thegeneticgenealogist.com/2017/01/06/the-danger-of-distant-matches/

For other references, see also:

Identical by descent, International Society of Genetic Genealogy Wiki, This page was last edited on 14 September 2023, https://isogg.org/wiki/Identical_by_descent

Identical by state, International Society of Genetic Genealogy Wiki, This page was last edited on 7 August 2022, https://isogg.org/wiki/Identical_by_state

Autosomal DNA Statistics, International Society of Genetic Genealogy Wiki, https://isogg.org/wiki/Autosomal_DNA_statistics

[18] Identical by descent, International Society of Genetic Genealogy Wiki, This page was last edited on 14 September 2023, https://isogg.org/wiki/Identical_by_descent

[19] Identical by descent, International Society of Genetic Genealogy Wiki, This page was last edited on 14 September 2023, https://isogg.org/wiki/Identical_by_descent

See also:

Ralph P, Coop G (2013). The Geography of Recent Genetic Ancestry across Europe. PLOS Biology 11(5):e1001555. https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001555

Browning SR, Browning BL. Identity by descent between distant relatives: detection and applications. Annu Rev Genet. 2012;46:617-33. doi: 10.1146/annurev-genet-110711-155534. Epub 2012 Sep 17. PMID: 22994355. https://pubmed.ncbi.nlm.nih.gov/22994355/

Bettinger, Blaine, Small Matching Segments – Friend or Foe?, The Genetic Genealogist, https://thegeneticgenealogist.com/2014/12/02/small-matching-segments-friend-foe/

Bettinger, Blaine, The Danger of Distant Matches, 6 Jan 2017, The Genetic Genealogist, https://thegeneticgenealogist.com/2017/01/06/the-danger-of-distant-matches/

Identical by state, International Society of Genetic Genealogy Wiki, This page was last edited on 7 August 2022, https://isogg.org/wiki/Identical_by_state

[20] Bettinger, Blaine, Small Matching Segments – Friend or Foe?, The Genetic Genealogist, https://thegeneticgenealogist.com/2014/12/02/small-matching-segments-friend-foe/

[21] Bettinger, Blaine, The Danger of Distant Matches, 6 Jan 2017, The Genetic Genealogist, https://thegeneticgenealogist.com/2017/01/06/the-danger-of-distant-matches/

[22]In genetic genealogy, the identical ancestors point (IAP), or all common ancestors (ACA) point, or genetic isopoint, is the most recent point in a given population’s past such that each individual alive at that point either has no living descendants, or is the ancestor of every individual alive in the present. This point lies further in the past than the population’s most recent common ancestor(MRCA).

Identical ancestors point, Wikipedia, This page was last edited on 20 October 2024,  https://en.wikipedia.org/wiki/Identical_ancestors_point

We find that a pair of modern Europeans living in neighboring populations share around 2 12 genetic common ancestors from the last 1,500 years, and upwards of 100 genetic ancestors from the previous 1,000 years. These numbers drop off exponentially with geographic distance, but since these genetic ancestors are a tiny fraction of common genealogical ancestors, individuals from opposite ends of Europe are still expected to share millions of common genealogical ancestors over the last 1,000 years. There is also substantial regional variation in the number of shared genetic ancestors.

Ralph, Peter and Graham Coop, The Geography of Recent Genetic Ancestry across Europe, PLOS Biology 11(5): e1001555. doi:10.1371/journal.pbio.1001555, 2013, https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.1001555&type=printable

Koonin EV, Wolf YI. The common ancestry of life. Biol Direct. 2010 Nov 18;5:64. doi: 10.1186/1745-6150-5-64. PMID: 21087490; PMCID: PMC2993666. https://pmc.ncbi.nlm.nih.gov/articles/PMC2993666/

[23] Identity by Decent, Wikipedia, This page was last edited on 27 September 2024, https://en.wikipedia.org/wiki/Identity_by_descent

Kecong Tang, Ardalan Naseri, Yuan Wei, Shaojie Zhang, Degui Zhi, Open-source benchmarking of IBD segment detection methods for biobank-scale cohorts, GigaScience, Volume 11, 2022, giac111, https://doi.org/10.1093/gigascience/giac111

Browning SR, Browning BL. Probabilistic Estimation of Identity by Descent Segment Endpoints and Detection of Recent Selection. Am J Hum Genet. 2020 Nov 5;107(5):895-910. doi: 10.1016/j.ajhg.2020.09.010. Epub 2020 Oct 13. PMID: 33053335; PMCID: PMC7553009. https://pmc.ncbi.nlm.nih.gov/articles/PMC7553009/

Ringbauer H, Huang Y, Akbari A, Mallick S, Patterson N, Reich D. ancIBD – Screening for identity by descent segments in human ancient DNA. bioRxiv [Preprint]. 2023 Mar 9:2023.03.08.531671. doi: 10.1101/2023.03.08.531671. Update in: Nat Genet. 2024 Jan;56(1):143-151. doi: 10.1038/s41588-023-01582-w. PMID: 36945531; PMCID: PMC10028887. https://pmc.ncbi.nlm.nih.gov/articles/PMC10028887

Nait Saada, J., Kalantzis, G., Shyr, D. et al. Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations. Nat Commun 11, 6130 (2020). https://doi.org/10.1038/s41467-020-19588-x 

Ringbauer, H., Huang, Y., Akbari, A. et al. Accurate detection of identity-by-descent segments in human ancient DNA. Nat Genet 56, 143–151 (2024). https://doi.org/10.1038/s41588-023-01582-w 

[24] Doug Speed and David J. Balding, Relatedness in the post-genomic era:

is it still useful?, Nov 2014, Nature Reviews Genetics | AOP, published online Nov 2014; doi:10.1038/nrg3821, http://dougspeed.com/wp-content/uploads/nrg_relatedness.pdf 

Durand EY, Eriksson N, McLean CY. Reducing pervasive false positive identical-by-descent segments detected by large-scale pedigree analysis. Molecular Biology and Evolution advance access publication online 30 April 2014. https://watermark.silverchair.com/msu151.pdf

[25] Browning SR, Browning BL. Identity by descent between distant relatives: detection and applications. Annu Rev Genet. 2012;46:617-33. doi: 10.1146/annurev-genet-110711-155534. Epub 2012 Sep 17. PMID: 22994355. https://pubmed.ncbi.nlm.nih.gov/22994355/

[26] Cousin Statistics, International Society of Genetic Genealogy Wiki, This page was last edited on 27 February 2022, https://isogg.org/wiki/Cousin_statistics

[27] Henn, Brenna M, Hon L, Macpherson JM, Eriksson N, Saxonov S, Pe’er I, et al. (Apr 3 2012) Cryptic Distant Relatives Are Common in Both Isolated and Cosmopolitan Genetic Samples. PLoS ONE 7(4): e34267. https://doi.org/10.1371/journal.pone.0034267

[28] This is the result of inputting 90 cMs into the The Shared cM Project 4.0 tool v4. 90 cMs is approximately equal to 1.21 percent of the total % shared with a match.

Bettinger, Blaine T., The Shared cM Project 4.0 tool v4, Mar 2020, DNA Painter, https://dnapainter.com/tools/sharedcmv4

[29] AncestryDNA has 7 different groups for predicted relationships: Parent/Child, Immediate Family (full siblings), Close Family (half siblings, grandparent/grandchild, aunt/uncle/niece/nephew), 1st cousin, 2nd cousin, 3rd cousin, 4th cousin, Distant Cousin.

Understanding Your AncestryDNA Matches , August 2018, LegacyTree Genealogists, ttps://www.legacytree.com/blog/understanding-ancestrydna-matches 

[30] Bettinger, Blaine T., The Shared cM Project 4.0 tool v4, Mar 2020, DNA Painter, https://dnapainter.com/tools/sharedcmv4

[31] Ibid

Autosomal DNA Tests: Estimating Genetic Relationships and Discovering Relatives

In prior posts, I discussed the utility of Y-DNA tests as a possible avenue to gain insights and possible leads on identifying information about tracing the lineage associated with family surnames for the Griffis(ith)(es) family. [1] I have not discussed my experience of using autosomal DNA tests for genealogical and family research.

There are perhaps two unique things that atDNA tests can provide. They can:

  • identify unknown living relatives and their possible relationships; and
  • identify a possible relationship of a common ancestor that you share with a living relative.

My experience with atDNA tests have largely resulted in the initial discovery of many living third to fifth generational cousins. However, all of these distant cousins fail to document their respective lines of descent in various DNA company databases. The lack of this additional genealogical information makes it difficult to document where our common distant family connections are located.

A few of the genetic connections from the atDNA tests have provided documentation on common family connections. Based on their information, I have been able to identify a few distant connections. On two other occasions, I have discovered two half brothers.

This three part story focuses on the merits and limitations as well as my personal experience of using autosomal DNA (atDNA) tests for documenting genetic kinship ties in the Griffis family. This part provides general background to make sense of the DNA results. The second part of the story discusses my ongoing DNA discoveries from these tests. As such, the information can change in the future. The third part is devoted to my profound discovery of having two half siblings David and Greg.

General Comparison of DNA Tests

Depending on the DNA test, they tell you how much of their DNA you have inherited from unspecified ancestors on each side of your family or how far back you can trace genetic lineages through a maternal or paternal line. Genetic genealogy or results from DNA tests do not tell you where each member on your family tree lived or provide information on their specific family relationships.

DNA results can identify matches of living individuals and their possible shared kinship relationships. These estimates are based on the amount of shared DNA segments between the match and you. When it comes to identifying specific individuals and verifying kinship relationships, traditional genealogical research is typically required for interpretation of the results. [2]

There are basically three types of genetic tests used in genealogical research. Autosomal ancestry (atDNA), Y-DNA, and mitochondrial DNA (mtDNA) tests (see illustration one below). Autosomal tests can analyze a broader range of genetic family network ties than the Y-DNA or mtDNA tests. Y-DNA and mtDNA tests respectively trace the paternal and maternal sides of one’s genetic history. The atDNA tests are broader in their ability to trace genetic relatives on both sides of your family tree. However, their effectiveness of tracing ancestors is limited in terms of how many generations back they can effectively provide results. Another unique characteristic of the atDNA tests is matching living test takers through the amount of shared autosomal DNA.

Illustration One: Three Types of DNA Tests

Click for Larger View | Source: Modified version of an image found at Edward Sweeney, Types of DNA Test, MacDugall DNA Research Project, https://macdougalldna.org/types-of-dna-test-b/

As indicated in table one, while limited to the paternal line of descent, Y-DNA tests can effectively track male genetic descendants back around 300,000 years. Mitochondrial testing of the matrilineal line can also provide results that go back over 140 thousands of years. The popular atDNA ‘ethnicity’ tests can trace back through a limited number of generations. While women have two X chromosomes, DNA testing of the X-DNA is usually tested along with other chromosomes as part of an atDNA test. [3]

Table 1: Type of DNA Testing

CharacteristicAutosomal
DNA (atDNA)
Y – DNA (YDNA)Mitochondrial
DNA (mtDNA)
What does it test?All autosomal chromosomesY chromosomeMitochondria
Available toBoth males and
females
Only males can
take test
Both males and
females
How far back?5 – 9 generations~155,000 Years~200,000+ years
Source of TestingAutosomal
Chromosomes
Y ChromosomeX Chromosom
found in Mitochondria
What genealogical lines tested?All ancestry linesOnly Paternal (father’s
father’s father, etc)
Maternal (mother’s
mother’s mother, etc.)
Benefits – utilityFinding relatives within
a few generations, determining broader
ethnicity estimations,
identifying potential
matches across both sides
Tracing direct
paternal lines, surnames,
identifying specific
paternal lineages and haplogroups,
studying deep paternal ancestry
Tracing a direct
maternal line,
identifying maternal haplogroups,
analyzing ancient
ancestry patterns
Available from
the following
companies:
– ancestry.com
– Family Tree DNA
– 23andMe
– Myheritage
– Living DNA
– Family Tree DNA
– 23andME (high level)
– YSEQ
– Full Genome Corp
– Family Tree DNA
– 23andMe
– YSEQ
– Full Genome Corp

Autosomal DNA tests are useful for finding relatives, such as unknown relatives, clarifying uncertain family relationships and identifying distant relatives. Typically DNA companies identify matches up to six generations. The Y-DNA and mtDNA tests, while limited to only tracing paternal lines or maternal lines respectively, can trace genetic lineage back over 150,000 years.

Popularity of Autosomal DNA Tests

“For about a hundred dollars, it is now possible to spit into a tube, drop it in the mail, and within a couple of months gain access to a list of likely relatives. If you have any colonial American ancestors, the first thing you realize, taking a DNA test for genealogical purposes, is that potential sixth cousins are a whole lot easier to come by than you ever imagined. Even fifth cousins — people with whom you share a fourth great-grandparent — aren’t a particular scarcity.” [4]

These tests provide information about an individual’s ancestral roots, and they can help to connect people with their relatives, sometimes as distantly related as fourth or fifth cousins. Such information can be particularly useful when a person does not know their genealogical ancestry (eg. many adoptees and the descendants of forced migrants). [5]

The direct-to-consumer genetic testing market has shown significant growth in recent years, but there are indications of a recent slowdown in sales in 2023.

As many people purchased consumer DNA tests in 2018 as in all previous years combined. [6] Combined with prior years of personal consumer testing, more than 26 million consumers had added their DNA to ostensibly four leading commercial ancestry and health databases.

Chart One: atDNA Database Growth

Click for Larger View | Source: 23andMe Has More Than 10 Million Customers, April 8, 2019, The DNA Geek Blog, https://thednageek.com/23andme-has-more-than-10-million-customers/

In late 2019, there were signs of declining sales. Ancestry and 23andMe saw drops in direct website sales of 38% and 54% respectively compared to 2018. [7]

“Less than five years ago, consumer DNA tests were being hailed as the innovative technology of the future—but today, declining sales have forced several companies in the field to scale back their workforces and adjust their business strategies.” [8]

Market data from DNA companies suggest that the market continues to grow, albeit at a slower rate than the initial boom years. Projections include all type of DNA tests (e.g. genetic relatedness, ancestry, lifestyle wellness, reproductive health, personalized medicine, sports nutrition, reproductive health, diagnostics and others). Factors like market saturation among early adopters and privacy concerns may be contributing to the moderation in growth rates.

Despite the decade-long rise in sales, in 2020 there was a sudden decline in interest. Two of the leading companies, 23andMe and AncestryDNA, experienced declines in sales of DNA ancestry kits of 54 and 38 percent, respectively. The decline was attributed to market saturation, economic recession related to the COVID-19 pandemic, and privacy concerns. [9]

Since 2021, 23andMe, a prominent direct-to-consumer genetic testing company, has faced significant financial challenges that have raised concerns about its future and the security of customer data. The company’s financial situation has deteriorated rapidly. Its stock price has plummeted, losing over 97% of its value since going public in 2021. 23andMe is reportedly on the verge of bankruptcy and has never turned a profit.  In 2023, the company suffered a major data breach affecting nearly 7 million users. The company has had turnover of board members and internal dissension between board members and executive management. [10]

This situation surrounding 23andMe serves as a cautionary tale about the risks associated with entrusting sensitive genetic information to private companies and highlights the need for robust data protection measures in the rapidly evolving field of consumer genomics. It also underscores the need to have back up contingencies of one’s DNA data. [10a]

What do atDNA Tests Measure?

Autosomal DNA tests basically measure five things.

  1. Genetic Markers: atDNA tests look at hundreds of thousands of genetic markers in a DNA sample called single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosome pairs. More on SNPs later in this story. These sampled SNPs represent DNA sequences that can be used to efficiently identify genetic differences and similarities between individuals.
  2. Inheritance Patterns: The tests examine the autosomal DNA inherited from both parents, which includes genetic contributions from all recent ancestors. This allows for connections to be made with relatives on all “recent” branches of a family tree, not just direct paternal or maternal lines in the past six or so generations.
  3. Genetic Relatives: The tests identify shared DNA segments between the test taker and other individuals in the DNA test company’s database, allowing for the discovery of genetic relatives that are living and linking each matched DNA tester to past generations.
  4. Ethnicity Estimates: By comparing an individual’s genetic markers to reference populations maintained by a DNA test company, autosomal DNA tests can provide estimates of a person’s ancestral origins and ethnic background.
  5. Health Traits: Many atDNA testing companies also include screening for certain inherited health conditions or physical traits that can play in one’s life to identify certain genetic code that could affect health.

The Genetic Influence of Autosomal DNA

An atDNA test is a measurement of sampled parts of your 22 autosomal chromosomes. Everyone (with rare exceptions) is born with a set of 23 pairs of chromosomes. The twenty-third chromosome is the sex chromosome. In most cases, we inherit an X chromosome from our mother and a Y or X chromossome from our father to determine our sex differentiation. (See illustration two).

Illustration Two: Karyotype of Human Chromosomes [11]

Click for Larger View | Source: Karyotype, National Genome Human Genome Research Institute, https://www.genome.gov/genetics-glossary/Karyotype

We inherit half of our chromosomes from our mother and the other half from our father. Two of those pairs are usually sex chromosomes (for most cases, XX in females and XY in males). The remaining 22 pairs of chromosomes are autosomal chromosomes or autosomes. For example, as illustrated below, chromosomes from the depicted mother are labeled in purple, and chromosomes from the depicted father are labeled in teal. (See illustration three).  [12]

Illustration Three: Inheritance of Parental Chromosomes

Click for Larger View| Source: Human Genomic Variation, Fact Sheet, National Human Genome Research Institute, 1 Feb 2023, https://www.genome.gov/about-genomics/educational-resources/fact-sheets/human-genomic-variation

The genetic inheritance patterns associated with autosomal chromosomes become more complex and diluted over generations due to recombination and variable inheritance patterns. [13] Illustration four shows the average amount of atDNA inherited by all close relations up to the third cousin level. The illustration uses the maternal side as a an example. The percentages can be replicated for the paternal side. [14] As reflected in the chart, fifty percent of one’s atDNA is inherited from each parent and roughly equally portions from grandparents to about 3x great-grandparents. 

Illustration Four: Percent of Autosomal Genetic Inheritance from Descendants

Click for Larger View | Source: Dimario, A chart illustrating the different types of cousins, including genetic kinship marked within boxes in red which shows the actual genetic degree of relationship (gene share) with ‘self’ in percentage (%), 27 April 2010, Wikimedia Commons, https://commons.wikimedia.org/wiki/File:Cousin_tree_(with_genetic_kinship).png

During meiosis [15], genetic recombination occurs, shuffling segments of DNA from each of the parents. This means that siblings may inherit different combinations of DNA segments from their parents; and with each generation, the specific segments inherited become more randomized. As a result, the amount of shared DNA between relatives decreases exponentially with each generation, making it more challenging to detect distant relationships through autosomal testing.

The random nature of genetic inheritance leads to variability in how much DNA is shared between relatives, especially for more distant relationships. This is known as variable expressivity. [16] For example, as indicated in table two, full siblings may share anywhere from about 35% to 65% of their DNA; and first cousins typically share around 12.5% of their DNA, but the actual range can vary significantly. This variability increases with more distant relationships, making it harder to precisely determine the degree of relatedness based solely on shared DNA percentages (see table two).  [17]

Table Two: Average Percent of Autosomal DNA Shared Between Selected Relatives

RelationshipAverage Percent
of DNA Shared
Range of DNA
Shared
Identical Twin100%N/A
Parent-Child50% (but 47.5% for father-son relationships)N/A
Full Sibiling50%38% – 61%
Half Sibling
Grandparent / Grandchild
Aunt / Uncle
Niece / Nephew
25%17% – 34%
1st Cousin
Great-grandparent
Great-grandchild
Great-Uncle / Aunt
Great Nephew / Niece
12.5%4% – 23%
1st Cousin once removed
Half first cousin
6.25%2% – 11.5%
2nd Cousin3.13%2% – 6%
2nd Cousin once removed
Half second cousin
1.5%0.6% – 2.5%
3rd Cousin0.78%0% – 2.2%
4th Cousin0.20%0% – 0.8%
5th Cousin
to Distant Cousin
0.05%
Source: Average Percent DNA Shared Between Relatives, 23andMe Customer Care, Tools, 23andMe, https://customercare.23andme.com/hc/en-us/articles/212170668-Average-Percent-DNA-Shared-Between-Relatives

While autosomal DNA testing has become increasingly accurate, there are still limitations in the context of estimating genetic relations and finding relatives. Current testing methods typically analyze only a subset of genetic markers. In addition, the interpretation of results relies on comparison to reference populations, which may not fully represent all ancestral groups. In the end, as previously stated, traditional genealogical research brings atDNA results into focus.

Genetic Variants: The Genetic Basis of atDNA Testing

genome is the complete set of DNA instructions found in every cell. [18] As discussed in a prior story, the human cell is a masterpiece of data compression. [19] Its nucleus, just a few microns wide, contains (if you ‘spell’ it out) six feet of genetic code comprised in a double helix called the DNA: deoxyribonucleic acid (see illustration five).

Illustration Five: Structure of Deoxyribonucleaic Acid (DNA)

Source: Modified image of DNA as found in Ruairo J Mackenie, DNA vs. RNA – 5 Key Differences and Comparison, 18 Dec 2020, updated 24 Jan 2024, Technology Networks, Genomics Research, https://www.technologynetworks.com/genomics/lists/what-are-the-key-differences-between-dna-and-rna-296719

The DNA helical molecules string together some three billion pairs of nucleotides that are comprised of proteins, sugar (deoxyribose), a phosphate and four types of nitrogenous bases which are represented by an initial: A (adenine), C (cytosine), G (guanine), and T (thymine). Nucleotides are the fundamental building blocks that make up the DNA strands. The sequence of nucleotides along the DNA strand encodes genetic information and regulates when codes are activated. [20]

The nucleotides form base pairs and are the cornerstone of genetic testing. (See illustration six.) They are the foundation of the programming language of our genetic code. Whenever a particular base is present on one side of a strand of the DNA, its complementary base is found on the other side. Guanine always pairs with cytosine. Thymine always pairs with adenine. So one can write the DNA sequence by listing the bases along either one of the two sides or strands. When DNA companies perform their tests, they essentially separate the two stands of the helix and use one side of the helix as the template or coding strand when they map out an individual’s DNA results.

Illustration Six: Relationship between Nucleotides, Base Pairs, Chromosomes, Genes, and DNA

Approximately 2% of our genome encodes proteins – this is where gene strands are located (illustration seven).  Coding “gene” DNA makes up only about one to three percent of the human genome, while noncoding DNA comprises approximately 97-99% of our total genetic material. This distribution shows that the vast majority of our genome consists of noncoding sequences. [21]

Genes are the basic unit of inherited DNA and carry information for making proteins, which perform important functions in your body. The coded regions of the genome produce proteins with structural, functional, and regulatory roles in cells and to a larger extent the human body. The remainder of our genome is made of noncoding DNA, sometimes called “junk DNA”, which is a misnomer. It is estimated that between 25% and 80% of non-coding DNA regulates gene expression (e.g. when, where, and for how long a gene is turned on to make a protein). [22] The non-coding DNA that does not regulate gene activity is composed either of deactivated genes that were once useful for our non-human ancestors (like a tail) or parasitic DNA from virus that have entered our genome and replicated themselves hundreds or thousands of times over the generations, or generally serve no purpose in the host organism.

Illustration Seven: Coding and Non-Coding Regions of the Genome

Clck for Larger View | Source: Modified version of graphic found at – Non-Coding DNA, AncestryDNA Learning Hub, https://www.ancestry.com/c/dna-learning-hub/junk-dna

Out of 3.2 billion DNA letters or nucleotides, there are only a ‘handful of places’ on the DNA ribbon that might be different between individuals. Humans share a very high percentage of their DNA. The exact figure is subject to some debate and depends on how it is measured. The commonly cited figure is that humans are 99.9% genetically identical. More recent research suggests a slightly lower, but still very high, level of similarity. Humans share a very high percentage of their DNA – roughly 99.4% to 99.9%. The small differences of 0.1 and 0.6 between individuals are crucial for understanding human diversity and health. [23]

As indicated in illustration eight, there are multiple types of genomic variants that comprise 0.4 percent of the genome.. The smallest genomic variants are known as single-nucleotide variants (SNVs). Each SNV reflects a difference in a single nucleotide (or letter) in the DNA chain. For a given SNV, the DNA letter at that genomic position might be a C in one person but a T in another person as reflected in illustration nine. [24]

Illustration Eight: Potential Sources of Genetic Variants for atDNA Testing

Click for Larger View | Source: Modification of a chart found at – Chart Human Genomic Variation, Fact Sheet, National Human Genome Research Institute, 1 Feb 2023, https://www.genome.gov/about-genomics/educational-resources/fact-sheets/human-genomic-variation

Single-nucleotide variants (SNVs) are differences of one nucleotide at a specific location in the genome. An individual may have different nucleotides at a specific location on each chromosome (getting a different one from each parent), such as with Person 1 in illustration nine. An individual may also have the same nucleotide at such a location on both chromosomes, such as with Person 2 and Person 3 in the illustration.

Illustration Nine: An Example of a single-nucleotide variant (SNV)

Click for Larger View | Source: Human Genomic Variation, Fact Sheet, National Human Genome Research Institute, 1 Feb 2023, https://www.genome.gov/about-genomics/educational-resources/fact-sheets/human-genomic-variation

As reflected in illustration ten below, there are also a small group of genetic variants that are called insertions and deletions of nucleotides.

“Insertion/deletion variants reflect extra or missing DNA nucleotides in the genome, respectively, and typically involve fewer than 50 nucleotides. Insertion/deletion variants are less frequent than SNVs but can sometimes have a larger impact on health and disease (e.g., by disrupting the function of a gene that encodes an important protein).” [25]

One of the most common types of insertion/deletion variants are tandem repeats. [26] Tandem Repeats are short stretches of nucleotides that are repeated multiple times and are highly variable among people. Different chromosomes can vary in the number of times such short nucleotide stretches are repeated, ranging from a few times to hundreds of times.

Each person has a collection of different genomic variants. For example, in illustration ten below, Person 1 has an insertion variant; Person 2 has a SNV and deletion variant; and Person 3 has an insertion, SNV, and deletion variant. All three people have different tandem repeats. Different variants can be inherited from different parents as reflected in the illustration.

Illustration Ten: Examples of Other Types of Genetic Variants

Click for Larger View | Source: Human Genomic Variation, Fact Sheet, National Human Genome Research Institute, 1 Feb 2023, https://www.genome.gov/about-genomics/educational-resources/fact-sheets/human-genomic-variation

As indicated in illustration seven above, the third general type of genomic variations are structural variants (SVs). Structural variants extend beyond small stretches of nucleotides to larger chromosomal regions. These large-scale genomic differences involve at least 50 nucleotides and as many as thousands of nucleotides that have been inserted, deleted, inverted or moved from one part of the genome to another. [27]

Tandem repeats that contain more than 50 nucleotides are considered structural variants. In fact, such large tandem repeats account for nearly half of the structural variants present in human genomes. When a structural variant reflects differences in the total number of nucleotides involved, it is called a copy number variant (CNV). CNVs are distinguished from other structural variants, such as inversions and translocations, because the latter types often do not involve a difference in the total number of nucleotides. [28]

Cornerstone of atDNA Testing: Single Nucleotide Polymorphisms (SNPs)

A subtype of SNVs is the single-nucleotide polymorphism (SNP), pronounced as “snip” for short. To be considered a SNP, a SNV must be present in at least 1% of the human population. As such, a SNP is more common than the rare single-nucleotide differences.  [29]

Among the genetic variants, SNPs are relatively common, occurring approximately once every 500-1000 base pairs in the human genome. This translates to about 4 to 5 million SNPs in an individual’s genome. Scientists have found more than 600 million SNPs in populations around the world. The combination of technical feasibility, scientific reliability, and analytical power makes SNPs the optimal choice for autosomal DNA testing in genealogical and ancestry applications. [30]

Ancestry information markers refers to locations in the genome that have varied sequences at that location and the relative abundance of those markers differs based on the continent from which individuals can trace their ancestry. So by using a series of these ancestry information markers, sometimes 20 or 30 more, and genotyping an individual you can determine from the frequency of those markers where their great, great, great, great ancestors may have come from. [31]

SNPs represent natural variations that make individuals unique while being common enough to be reliable DNA test markers. Their high frequency makes them ideal markers for genetic analysis. The vast majority of SNPs have no effect on health or development. SNPs are generally found in the DNA between genes rather than within genes themselves. [32]

While other genetic markers exist, SNPs are preferred ancestry information markers. SNPs are used for genetic testing based on their reliability and accuracy. SNPs are stable genetic markers that are passed down through generations. SNPs offer more detailed information about both recent and ancient ancestry. They also allow for fairly precise ethnic profiling and ancestral location inference.[33]

How atDNA Tests Figure Out Genetic Relationships

In a “Nutshell”: How do DNA companies Figure Out Genetic Relationships

Analyzing SNPs: DNA companies analyze hundreds of thousands of single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosomes. [34]

The results from different atDNA test companies can vary. The variance is based on a number of factors. All major DNA testing companies use equipment that analyze DNA specimens with what are called ‘chips’ that use DNA microarray technology supplied by a company named Illumina. However, different companies use different versions of the Illumina chip and each version tests different sets of SNP (Single Nucleotide Polymorphism) locations.

Illustration Ten: How DNA Microarray Technology Analyzes Autosomal DNA

Source: Bergström, Ann-Louise and Lasse Folkersen , DNA microarray, 15 May 2020, Moving Science, https://movingscience.dk/dna-microarray/

Companies can specify their own “other” locations to be included on their chip. The number of markers tested varies significantly by company. FamilyTreeDNA uses a customized Illumina chip. 23andMe and AncestryDNA use a customized Illumina Global Screening Array (GSA) chip. Living DNA uses an Affymetrix Axiom microarray (Sirius) chip. My Heritage uses an Illumina GSA chip. [35]

Illustration of Illumina Microarray Chips

Source: Web Graphic Array with GE Inserts, Illumina, Powerfully Informative Microarrays, Illumina,https://www.illumina.com/techniques/microarrays.html

“Each DNA testing company purchases DNA processing equipment. Illumina is the big dog in this arena. Illumina defines the capacity and structure of each chip. In part, how the testing companies use that capacity, or space on each chip, is up to each company. This means that the different testing companies test many of the same autosomal DNA SNP locations, but not all of the same locations. … This means that each testing company includes and reports many of the same, but also some different SNP locations when they scan your DNA. …  In addition to dealing with different file formats and contents from multiple DNA vendors, companies change their own chips and file structure from time to time. In some cases, it’s a forced change by the chip manufacturer. Other times, the vendors want to include different locations or make improvements.” [36]

When DNA companies change DNA chips, a different version of the company’s own file may contain different positions. DNA testing companies have to “fill in the blanks” for compatibility, and they do this using a technique called imputation. Illumina forced their customers to adopt imputation in 2017 when they dropped the capacity of their chip. [37]

Identify Matching Segments: The DNA test software for respective DNA companies compare the SNP data between two individuals to identify segments of DNA that appear to be identical or similar. These matching DNA segments indicate the likelihood of DNA inherited from a common ancestor. [38]

The ability to identify DNA matches between individuals is largely influenced by the size of database tests and the SNPs that were sampled to atDNA tests. As indicated, there are main differences between atDNA tests from various companies (e.g. 23andMe, Ancestry.com, FamilyTree DNA, LivingDNA, MyHeritage) regarding SNPs that are tested and the relative size of their respective database results.

Each company maintains its own proprietary reference databases and matching algorithms. As indicated in table three below, AncestryDNA has a larger customer database (over 20 million) compared to 23andMe (about 12 million). This gives AncestryDNA an advantage for finding genetic relatives.

Table Three: Data Base Size and Number of SNPs Tested by DNA Company in 2024

DNA
Company
Data Base Size of
atDNA Test Results
No. of Autosome
SNPs Tested
23andMe14 Million630,`132
FamilyTreeDNA1.7 million612,272
AncestryDNA25 million637,639
My Heritage8.5 million576,157
Living DNA300,000683,503
Source: Autosomal DNA testing comparison chart, International Society of Genetic Genalogy Wiki, This page was last edited on 8 October 2024, https://isogg.org/wiki/Autosomal_DNA_testing_comparison_chart

Measuring Segment Length: The length of matching segments of SNPs is measured in centimorgans (cM). Centimorgans measure the likelihood of genetic recombination between two markers on a chromosome. One centimorgan represents a one percent chance that two genetic markers will be separated by a recombination event in a single generation. This measurement helps geneticists and genealogists estimate how close two individuals are genetically related. [39]

Centimorgans (cM) are a crucial unit of measurement in genetic atDNA testing. It is used to quantify genetic distance and determine relationships between individuals based on shared DNA. The more centimorgans two people share, the more likely they are related. in addition to the number of cMs shared, longer segments generally indicate a closer relationship.

One cM corresponds on the average to about 1 million base pairs in humans. The total human genome is approximately 7400 cM long. A parent-child relationship typically shares about 3400-3700 cM. More distant relatives share fewer cMs. However, there can be overlap in cM ranges for different relationship types, so additional genealogical research is often needed to determine exact relationships.

(A centiMorgan) is less of a physical distance and more of a measurement of probability. It refers to the DNA segments that you have in common with others and the likelihood of sharing genetic traits. The ends of shared segments are defined by points where DNA swapped between two chromosomes, and the centimorgan is a measure of the probability of getting a segment that large when these swaps occur.” [40]

Chart One: Ranges of Shared centiMorgans with Family

Click for Larger View | Source: Bettinger, Blaine, Version 4.0! March 2020 Update to the Shared cM Project!, 27 Mar 2020, The Genetic Genealogist, https://thegeneticgenealogist.com/2020/03/27/version-4-0-march-2020-update-to-the-shared-cm-project/

When you take an atDNA test, the testing company compares your DNA to others in their database. The amount of DNA you share with a match is reported in centimorgans. Generally, the more centimorgans you share with someone, the more closely you are related to this other person. Shared centimorgan ranges can often indicate how many generations separate two people. Certain shared cM values can also suggest possible half-sibling or half-first cousin relationships as opposed to full relatives.

Calculating Total Shared DNA: The total amount of shared DNA is calculated by summing up the lengths of all matching segments, typically expressed in cMs or as a percentage of the total amount of shared SNPs sampled. [41]

Applying Thresholds: Each company sets minimum thresholds for segment length and total shared DNA to be considered a match. For example, FamilyTree DNA requires at least one segment of 9 cM or more.

Table Four: Different cM Thresholds for atDNA Matches Across DNA Companies

DNA CompanyCriteria for matching segments
23andMe9 cMs and at least 700 SNPs for one half-identical region

5 cMs and 700 SNPs with at least two half-identical regions being shared
FamilyTreeDNAAll matching segments must be at least 6 cMs in length. almost all matching segments contain at least 800 SNPs & all matching segments contain at least 600 SNPs.
AncestryDNA6 cMs per segment before the Timber algorithm is applied and a total of at least 8 cMs after Timber is applied.
My Heritage8 cM for the first matching segment and at least 6 cMs for the 2nd matching segment; 12 cM for the first matching segment in people whose ancestry is at least 50% Ashkenazi Jewish
Living DNA9.46 cMs for the first segment
Source: Autosomal DNA testing comparison chart, International Society of Genetic Genalogy Wiki, This page was last edited on 8 October 2024, https://isogg.org/wiki/Autosomal_DNA_testing_comparison_chart

Relationship Prediction: The amount of shared DNA is compared to expected ranges for different relationships to predict how two people may be related. Close relationships like parent/child or full siblings have very distinct amounts of shared DNA, while more distant relationships have overlapping ranges. [42]

Special Considerations: Some of the DNA companies use phasing algorithms to improve accuracy, especially for analyzing smaller shared segments. Some also apply special algorithms for populations with higher rates of endogamy, like Ashkenazi Jews. [43]

Moving Onward

I imagine all of this makes total sense. I, however, believe, all of this is totally confusing. To walk away with some semblance of understanding, I would focus on the following observations:

  • DNA tests can only provide so much information. Traditional genealogical research brings atDNA results into focus. Genetic and traditional research strategies can work hand in hand.
  • atDNA tests have the ability to trace living genetic relatives on both sides of your family tree. However, their effectiveness is limited in terms of how many generations back they can effectively provide results.
  • While autosomal DNA testing has become increasingly accurate, there are still limitations in the context of estimating genetic relations and finding relatives.
  • When looking at atDNA matches, centimorgans (cM) are the key unit of measurement in genetic atDNA testing. It is used to determine relationships between individuals based on shared DNA. The more centimorgans two people share, the more likely they are related. in addition to the number of cMs shared, longer segments generally indicate a closer relationship.

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Feature image: The image depicts a branch from a massive family tree that shows 6,000 relatives spanning seven generations.  It is part of a study that links 13 million people related by genetics or marriage.  Source: Jocelyn Kaiser, Thirteen million degrees of Kevin Bacon: World’s largest family tree shines light on life span, who marries whom, Science, 1 Mar 2018, https://www.science.org/content/article/thirteen-million-degrees-kevin-bacon-world-s-largest-family-tree-shines-light-life-span 

[1] See the following stories:

[2] Bettinger, Blaine, Everyone Has Two Family Trees – A Genealogical Tree and a Genetic Tree, 10 Nov 2009, The Genetic Genealogist, https://thegeneticgenealogist.com/2009/11/10/qa-everyone-has-two-family-trees-a-genealogical-tree-and-a-genetic-tree/

Understanding genetic ancestry testing, International Society of Genetic Genealogy Wiki, This page was last edited on on 25 August 2015, https://isogg.org/wiki/Understanding_genetic_ancestry_testing

[3] Human Y-chromosome DNA haplogroup, Wikipedia, This page was last edited on 5 October 2024,, https://en.wikipedia.org/wiki/Human_Y-chromosome_DNA_haplogroup

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Rowe, Katy, Genealogy’s Secret Weapon: How Using mtDNA Can Solve Family Mysteries, 10 May 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/mtdna/

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[4] Newton, Maud, America’s Ancestry Craze: Making sense of our family-tree obsession, June 2014, Harper’s Magazine, https://harpers.org/archive/2014/06/americas-ancestry-craze/

[5] Jorde LB, Bamshad MJ. Genetic Ancestry Testing: What Is It and Why Is It Important? JAMA. 2020 Mar 17;323(11):1089-1090. doi:10.1001/jama.2020.0517 PMID: 32058561; PMCID: PMC8202415 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8202415/

[6] Antonio Regalodo, More than 26 million people have taken an at-home ancestry test, MIT Technology Review, 11 Feb 2019, https://www.technologyreview.com/2019/02/11/103446/more-than-26-million-people-have-taken-an-at-home-ancestry-test/

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[7] Has the consumer DNA test boom gone bust?, Feb 20, 2020, updated Jul 28, 2024, Advisory Board, https://www.advisory.com/daily-briefing/2020/02/20/dna-tests 

[8] Ibid

[9] Krimsky Sheldon, The Business of DNA Ancestry, in: Understanding DNA Ancestry. Understanding Life. Cambridge University Press; 2021, Pages 8-16.

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[11] A karyotype is a visual representation of an individual’s complete set of chromosomes, displaying their number, size, and structure, typically arranged in pairs and ordered by size.

“A karyotype is the general appearance of the complete set of chromosomes in the cells of a species or in an individual organism, mainly including their sizes, numbers, and shapes. … A karyogram or idiogram is a graphical depiction of a karyotype, wherein chromosomes are generally organized in pairs, ordered by size and position of centromere for chromosomes of the same size.”

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[12] Autosomes are the non-sex chromosomes found in the cells of organisms. Autosomes are any chromosomes that are not sex chromosomes (allosomes). In humans, there are 22 pairs of autosomes, numbered from 1 to 22. They come in identical pairs in both males and females. They are numbered based on size, shape, and other properties. They contain genes that control the inheritance of all traits except sex-linked ones.

[13] Recombination is a process by which pieces of DNA are broken and recombined to produce new combinations of nucleotides or alleles. Recombination primarily happens between homologous chromosomes, which are paired chromosomes with similar genetic information, allowing for the exchange of corresponding DNA segments.

During meiosis, when homologous chromosomes pair up, a process called “crossing over” occurs where DNA strands break and rejoin, swapping genetic material between the chromosomes. This recombination process creates genetic diversity at the level of genes that reflects differences in the DNA sequences of different organisms. 

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[18] The genome is the entire set of DNA instructions found in a cell. In humans, the genome consists of 23 pairs of chromosomes located in the cell’s nucleus, as well as a small chromosome in the cell’s mitochondria. A genome contains all the information needed for an individual to develop and function.

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[26] CNVs are typically defined as DNA segments that are: larger than 1,000 base pairs (1 kilobase); usually less than 5 megabases in length; and  can include both duplications (additional copies) and deletions (losses) of genetic material. 

CNVs are remarkably common in human genomes. They account for approximately 5 to 9.5% of the human genome. They affect more base pairs than other forms of mutation when comparing two human genomes. They play crucial roles in evolution, population diversity, and disease development. 

Copy number variation, Wikipedia, This page was last edited on 24 September 2024, https://en.wikipedia.org/wiki/Copy_number_variation

Pös O, Radvanszky J, Buglyó G, Pös Z, Rusnakova D, Nagy B, Szemes T. DNA copy number variation: Main characteristics, evolutionary significance, and pathological aspects. Biomed J. 2021 Oct;44(5):548-559. doi: 10.1016/j.bj.2021.02.003. Epub 2021 Feb 13. PMID: 34649833; PMCID: PMC8640565 https://pmc.ncbi.nlm.nih.gov/articles/PMC8640565/

Eichler, E. E. Copy Number Variation and Human Disease. Nature Education 1(3):1, 2008,  https://www.nature.com/scitable/topicpage/copy-number-variation-and-human-disease-741737/

What are copy number variants?, 12 Aug 2020, Genomics Education Programme, https://www.genomicseducation.hee.nhs.uk/blog/what-are-copy-number-variants/

Clancy, S. Copy number variation. Nature Education 1(1):95, 2008, https://www.nature.com/scitable/topicpage/copy-number-variation-445/

Copy number variant, National Cancer Institute, https://www.cancer.gov/publications/dictionaries/genetics-dictionary/def/copy-number-variant

Copy Number Variation (CNV), 3 Nov 2024, National Human Genome Research Institute, https://www.genome.gov/genetics-glossary/Copy-Number-Variation

[29] Several approaches are used to determine if an SNV meets the one percent population frequency threshold:

  • Large-Scale Population Studies: Projects like the 1000 Genomes Project have sequenced thousands of individuals across multiple populations to identify and validate SNPs
  • A number of detection technologies are used such as real-time PCR, the use of microarrays, and Next-generation sequencing (NGS).

See for example:

The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature 526, 68–74 (2015). https://doi.org/10.1038/nature15393 

Patricia M Schnepp, Mengjie Chen, Evan T Keller, Xiang Zhou, SNV identification from single-cell RNA sequencing data, Human Molecular Genetics, Volume 28, Issue 21, 1 November 2019, Pages 3569–3583, https://doi.org/10.1093/hmg/ddz207

Telenti A, Pierce LC, Biggs WH, di Iulio J, Wong EH, Fabani MM, Kirkness EF, Moustafa A, Shah N, Xie C, Brewerton SC, Bulsara N, Garner C, Metzker G, Sandoval E, Perkins BA, Och FJ, Turpaz Y, Venter JC. Deep sequencing of 10,000 human genomes. Proc Natl Acad Sci U S A. 2016 Oct 18;113(42):11901-11906. doi: 10.1073/pnas.1613365113. Epub 2016 Oct 4. PMID: 27702888; PMCID: PMC5081584. https://pmc.ncbi.nlm.nih.gov/articles/PMC5081584/

SNVs vs. SNPs, CD Genomics, https://www.cd-genomics.com/resource-snvs-vs-snps.html

Efficiently detect single nucleotide polymorphisms and variants, Illumina, https://www.illumina.com/techniques/popular-applications/genotyping/snp-snv-genotyping.html

[30] What are single nucleotide polymorphisms (SNPs)?, MedlinePlus, https://medlineplus.gov/genetics/understanding/genomicresearch/snp/

SNP, IMS Riken Center for Integrative Medical Sciences, https://www.ims.riken.jp/english/glossary/genome.php

The 1000 Genomes Project Consortium. A global reference for human genetic variation.Nature 526, 68–74 (2015). https://doi.org/10.1038/nature15393

[31] Ancestry Information Markers, National Human Genome Research Institute, https://www.genome.gov/genetics-glossary/Ancestry-informative-Markers

Joon-Ho You, Janelle S. Taylor, Karen L. Edwards, Stephanie M. Fullerton, What are our AIMs? Interdisciplinary Perspectives on the Use of Ancestry Estimation in Disease Research, National Library of Medicine, 2012 Nov 5. doi: 10.1080/21507716.2012.717339

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

[32] What are single nucleotide polymorphisms (SNPs)?, MedlinePlus, https://medlineplus.gov/genetics/understanding/genomicresearch/snp/

[33] AIMs are single-nucleotide polymorphisms (SNPs) that show substantially different frequencies between populations from different geographical regions15. These genetic variations can be used to estimate the geographical origins of a person’s ancestors, typically by continent of origin.

AIMs are found within the approximately 15 million SNP sites in human DNA (about 0.4% of total base pairs). They are often traced to the Y chromosome, Mitochondrial DNA, and Autosomal regions.

AIMs can distinguish between major continental populations (Africa, Asia, Europe). They require multiple markers working together (typically 20-30 or more) for accurate ancestry determination. They can identify fine population structure within continents using larger marker sets. 

The effectiveness of AIMs depends on the number of markers used:

  • 40-80 markers can identify five broad continental clusters;
  • 128 markers can characterize samples into 8 broad continental groups; and
  • Larger sets (>46,000 markers) can identify detailed subpopulation structure

Hinkley, Ellen, DNA Testing Choice, 16 Dec 2016, https://dnatestingchoice.com/en-us/news/what-is-an-autosomal-dna-test

Lamiaa Mekhfi, Bouchra El Khalfi, Rachid Saile, Hakima Yahia, and Abdelaziz Soukri, The interest of informative ancestry markers (AIM) and their fields of application, , BIO Web of Conferences 115, 07003 (2024),https://doi.org/10.1051/bioconf/202411507003 

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

Ancestry Information Markers, National Human Genome Research Institute, https://www.genome.gov/genetics-glossary/Ancestry-informative-Markers

Ancestry-informative marker, Wikipedia, This page was last edited on 14 August 2024, https://en.wikipedia.org/wiki/Ancestry-informative_marker

[34] Autosomal DNA Statistics, International Society of Genetic Genealogy Wiki, This page was last edited on 17 October 2022, https://isogg.org/wiki/Autosomal_DNA_statistics

Autosomal SNP comparison chart, International Society of Genetic Genealogy Wiki, This page was last edited on 29 January 2024, https://isogg.org/wiki/Autosomal_SNP_comparison_chart

DNA Structure and the Testing Process, FamilyTreeDNA Help Center, https://help.familytreedna.com/hc/en-us/articles/6189190247311-DNA-Structure-and-the-Testing-Process

Catherine A. Ball, Mathew J Barber, Jake Byrnes, Peter Carbonetto, Kenneth G. Chahine, Ross E. Curtis, Julie M. Granka, Eunjung Han, Eurie L. Hong, Amir R. Kermany, Natalie M. Myres, Keith Noto, Jianlong Qi, Kristin Rand, Yong Wang and Lindsay Willmore, AncestryDNA Matching White Paper, 31 Mar 2016, AncestryDNA, https://www.ancestry.com/cs/dna-help/matches/whitepaper; PDF: https://www.ancestry.com/dna/resource/whitePaper/AncestryDNA-Matching-White-Paper.pdf

Autosomal DNA match thresholds, International Society of Genetic Genealogy Wiki, This page was last edited on 31 August 2024, https://isogg.org/wiki/Autosomal_DNA_match_thresholds

Daniel Kling, Christopher Phillips, Debbie Kennett, Andreas Tillmar,

Investigative genetic genealogy: Current methods, knowledge and practice, Forensic Science International: Genetics, Volume 52, 2021, https://doi.org/10.1016/j.fsigen.2021.102474

Davis DJ, Challis JH. Automatic segment filtering procedure for processing non-stationary signals. J Biomech. 2020 Mar 5;101:109619. doi: 10.1016/j.jbiomech.2020.109619. Epub 2020 Jan 9. PMID: 31952818.

The Order of Nucleotides in a Gene Is Revealed by DNA Sequencing, Scitable, Nature Education, https://www.nature.com/scitable/topicpage/the-order-of-nucleotides-in-a-gene-6525806/

[35] The Illumina Global Screening Array (GSA) is a customizable genotyping microarray platform.  Its base configuration

  • Contains approximately 654,000 fixed markers spanning the human genome;
  • Supports 24 samples per array in standard format;
  • Requires 200 ng DNA input;
  • Achieves call rates greater than 99% and reproducibility greater than 99.9%; and
  • Allows addition of up to 100,000 custom markers

Illumina microarray solutions, Illumina, https://www.illumina.com/techniques/microarrays.html

Efficiently detect single nucleotide polymorphisms and variants, Illumina, https://www.illumina.com/techniques/popular-applications/genotyping/snp-snv-genotyping.html

Custom design tools for genotyping any variant, in any species, Illumina, https://www.illumina.com/techniques/popular-applications/genotyping/custom-genotyping.html

Infinium™ Global Screening Array-24 v3.0 BeadChip, Illumina , https://www.illumina.com/content/dam/illumina-marketing/documents/products/datasheets/infinium-global-screening-array-data-sheet-370-2016-016.pdf

Infinium Global Screening Array-24 Kit, Illumina, https://www.illumina.com/products/by-type/microarray-kits/infinium-global-screening.html

Efficiently detect single nucleotide polymorphisms and variants, Illumina, https://www.illumina.com/techniques/popular-applications/genotyping/snp-snv-genotyping.html

Custom design tools for genotyping any variant, in any species, Illumina, https://www.illumina.com/techniques/popular-applications/genotyping/custom-genotyping.html

[36] Estes, Roberta, Comparing DNA Results – Different Tests at the Same Testing Company, 5 Sep 2017, DNAeXplained – Genetic Genealogy, https://dna-explained.com/2023/05/18/comparing-dna-results-different-tests-at-the-same-testing-company/

[37]  Estes, Roberta, Concepts -Imputation, 5 Sep 2017, DNAeXplained – Genetic Genealogy, https://dna-explained.com/2017/09/05/concepts-imputation/

Illumina microarray solutions, Illumina, https://www.illumina.com/techniques/microarrays.html

Efficiently detect single nucleotide polymorphisms and variants, Illumina, https://www.illumina.com/techniques/popular-applications/genotyping/snp-snv-genotyping.html

[38] See for example: Our Autosomal DNA Test (Family Finder™), FamilyTreeDNA HelpCenter, https://help.familytreedna.com/hc/en-us/articles/4411203169679-Our-Autosomal-DNA-Test-Family-Finder

[39] Different DNA testing companies use centimorgans (cM) in slightly different ways when reporting matches and relationships:

  1. Matching thresholds: Companies set different minimum thresholds for reporting matches. For example: AncestryDNA currently uses a threshold of 8 cM; 23andMe uses 7 cM and at least 700 SNPs for the first matching segment; and MyHeritage uses 8 cM.
  2. Algorithms and filtering: Companies use proprietary algorithms to filter and process the raw DNA data. AncestryDNA uses algorithms called Timber and Underdog to phase data and filter out high-frequency segments. Other companies may use different methods, leading to variations in reported shared cM.
  3. Total cM calculations: The total amount of cM a person has can vary between companies. 23andMe reports about 7,440 cM total and AncestryDNA seems to use around 6,800-7,000 cM total.
  4. Reporting of segments: Some companies like 23andMe and FamilyTreeDNA provide detailed segment data. AncestryDNA does not show specific segment information.
  5. Confidence levels: Companies may assign different confidence levels or relationship probabilities based on shared cM. For example, AncestryDNA previously used confidence scores like “Extremely High” for cMs greater than 60.
  6. Handling of small segments: Companies differ in how they handle very small matching segments, with some including segments as small as one cM and others excluding anything below their threshold.

These differences in methodologies can result in variations in reported shared cM and relationship estimates between companies for the same pair of individuals. This is why matches and relationship predictions may not be identical across different testing companies.

Centimorgan, Wikipedia, This page was last edited on 1 May 2024, https://en.wikipedia.org/wiki/Centimorgan

What’s the difference between shared centimorgans and shared segments?, 11 Nov 2019, The Tech Initiative, https://www.thetech.org/ask-a-geneticist/articles/2019/centimorgans-vs-shared-segments/

centiMorgan, Internatioal Society of Genetic Genealogy, This page was last edited on 15 August 2024, https://isogg.org/wiki/CentiMorgan

[40] Hansen, Annelie, Untangling the Centimorgans on Your DNA Test, FamilySearch Blog, https://www.familysearch.org/en/blog/centimorgan-chart-understanding-dna

Green Dragon Genealogy, Yes, but what EXACTLY is a centiMorgan?, 19 Sep 2021, Green Dragon Genealogy,https://greendragongenealogy.co.uk/dna/yes-but-what-exactly-is-a-centimorgan/

[41] Autosomal DNA match thresholds, International Society of Genetic Genealogy Wiki, This page was last edited on 31 August 2024, https://isogg.org/wiki/Autosomal_DNA_match_thresholds

[42] Autosomal DNA Statistics, International Society of Genetic Genealogy Wiki, This page was last edited on 17 October 2022, https://isogg.org/wiki/Autosomal_DNA_statistics

Autosomal DNA match thresholds, International Society of Genetic Genealogy Wiki, This page was last edited on 31 August 2024, https://isogg.org/wiki/Autosomal_DNA_match_thresholds

Estes, Roberta , Comparing DNA Results – Different Tests at the Same Testing Company, DNAeXplained – Genetic Genealogy Blog, 18 May 2023, https://dna-explained.com/2023/05/18/comparing-dna-results-different-tests-at-the-same-testing-company/

Autosomal DNA testing comparison chart, International Society of Genetic Genealogy Wiki, This page was last edited on 8 October 2024, https://isogg.org/wiki/Autosomal_DNA_testing_comparison_chart

[43] Phasing, International Society of Genetic Genealogy Wiki, This page was last edited on 24 May 2024, https://isogg.org/wiki/Phasing

A Guide to Phasing from Illumina: https://youtu.be/15NPZCGP_e4

Autosomal DNA match thresholds, International Society of Genetic Genealogy Wiki, This page was last edited on 31 August 2024, https://isogg.org/wiki/Autosomal_DNA_match_thresholds

Davis DJ, Challis JH. Automatic segment filtering procedure for processing non-stationary signals. J Biomech. 2020 Mar 5;101:109619. doi: 10.1016/j.jbiomech.2020.109619. Epub 2020 Jan 9. PMID: 31952818.