DOCSLIB.ORG

Peter Gwozdz

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Peter Gwozdz Peter Gwozdz comparison to the historical record is beyond the scope of this article. The first article in this two-part series developed a set of tools for the analysis of Y-STR data from groups of I use the conventional notation “Haplogroup R1a1” for related people (Gwozdz, 2009). The present article generally accepted SNP haplogroup clades, and the no- applies these tools to Polish Y-STR data. A number of tation “P type” for types that are introduced here, and specially defined terms are used in this article and they “Pc type” for subtypes. A “type” is as defined in Part I are defined in the companion article (Part I). of this two-part series of articles. Most of the types are presented as hypothetical subdivisions of Haplogroup Pawlowski (2002) identified a Y-STR haplotype that is R1a1 (R-M17 or R-M198), so the stem haplogroup is 15 times more common in Poland than in the rest of R1a1 if not specified. In this article I retain the R1a1 Europe. That haplotype, determined at nine STR mark- designation for Haplogroup R-M17 in order to be com- ers, represents 4.6% of Pawlowski’s Polish data. This patible with the reference data. It is the same haplo- haplotype, called “P type” here, is evidence of a domi- group currently designated as R1a1a (ISOGG, 2009). nant Y-DNA clade in a relatively recent Polish popula- The conventional asterisk (*) as used in the construction tion expansion. One purpose of this article is to add “R1a*” indicates those downstream subsets of R1a that evidence, and to estimate the size and age of the hypoth- are not in any presently defined sub-haplogroups of R1a. esized P type clade. “R1a” without an asterisk means all of R1a. For exam- ple, R1a includes R1a1; R1a* does not include R1a1. Roewer (2005) analyzed European Y-STR data, show- ing it can supplement single nucleotide polymorphism About half of Polish Y-DNA is in Haplogroup R1a (SNP) markers in the study of population structure (Wiik, 2008; McDonald, 2005). within historical times. Pawlowski’s data source is a subset of Roewer’s source, Yhrd, a European forensic “Polish” is difficult to define exactly. Biskupski (2006) compilation. Another purpose of this article is to identi- published a delightful essay regarding the ambiguity of fy common Polish STR haplotypes, as modal haplotype the word “Polish.” In this article “Polish” simply refers candidates for hypothetical clades, with estimated size to people either born in historical Poland or who have and age. Other than brief comments in discussion, patrilineal lines that go back to historical Poland. ____________________________________________________________ The on page 156 of the companion article Address for correspondence: Peter Gwozdz, [email protected] provides a concise two-page statement of the method of this article, with terms defined in boldface. Received: June 5, 2009; accepted: September 13, 2009 159 160 FTDNA projects include family samples. These are edited, as explained in the companion article. Family The Y-STR data for this article is available from three sets were identified by noting identical family names Internet sources: Ysearch, Yhrd (Willuweit, 2007), and with identical 67-marker haplotypes, or similar haplo- Family Tree DNA (FTDNA). FTDNA has a number of types with sequential ID codes (or nearly sequential). “projects” that focus on surnames, haplogroups, and All but one of each family set were removed, leaving a geographic areas. The primary source for this article is representative with the most markers. For the Polish the Polish Project. See Web Resources at the end of this Project, where family sets are uncommon, only 13 of article for URLs. There is incidental use of data from 913 (1.4%) data entries were removed. Only two of the other projects, which data is available by substitution of R1a1 haplotypes were removed. Those 13 removals are the quoted project name for /polish/ in the public ad- from eight family pairs and one family set of six samples, dress for the Polish Project. of which five were removed. That set of six, which had identical haplotypes at 12 markers (four were identical Polish Project data follows the FTDNA standards and at 25 markers), is an example of how large unedited marker order, with progressive STR marker sets avail- family sets can distort haplotype frequency data. Addi- able, accumulating 12, 25, 37, and 67 markers, plus a few tional sets of very similar (zero genetic distance steps at additional rare compound markers, and minus rare miss- 25 markers, or less than two steps at 37, or less than ing markers. Data from all available STR markers are four steps at 67) haplotypes without identical names, 61 used here. The Polish Project has at least the standard 12 samples (6.8%), were not removed. Insofar as this markers for all samples, so those 12 markers provide the editing may not remove some family sets without family best statistics, although at lowest resolution. names, the data are biased slightly toward larger clus- ters. Insofar as this editing may remove men who The Ysearch database consists primarily of Y-STR haplo- actually submitted data independently, data is biased type data from individual men (herein, “samples”), but slightly, toward smaller clusters. also includes some modal haplotypes, fictitious entries for research purposes. The latter records were removed from Ysearch also has family sets, but Ysearch ID codes are the data before analysis. not assigned in sequence, so editing was restricted to identical family names with 67-marker haplotypes at Gwozdz: Y-STR mountains in haplospace, Part II: Application to common Polish clades 161 zero or one step separation. Also, Ysearch results were dler (2006) mutation rates to calculate age from ASD. As sorted by family name and visually scanned for suspi- explained in the companion article, I distinguish two cious sets of samples, for which the detailed data were kinds of age: TMRCA vs. time of hypothetical population checked by ID code for “contact person," where the expansion. same contact person is assumed to be the collector of a family set; only one such set was identified. Statistical methods are described in the companion article. See the companion article, “Y-STR Mountains in Hap- lospace, Part I: Methods,” for the “mountain” method. The word “type” means “mountain” in these articles. The FTDNA Polish Project data were downloaded 15 Briefly, a “type” is defined using an STR cluster for May 2009. An archive copy of the data is available as which a step frequency graph looks like a mountain. “PolishProject15May2009.xls” in the is an example. A “signature” is the modal . The total of 913 samples was edited to 900 as ex- haplotype using markers that best distinguish from plained above in . Editing and other types in the parent haplogroup. A “definition” matching notes are in “Evaluator15May2009.xls” and includes the modal haplotype and “cutoff” that produc- again in “Results15May2009.xls." All Polish Project es the best mountain. The cutoff is the next step, just samples have values for at least the first 12 markers. beyond the mountain. The “background” of samples gives the ten most common 12-marker haplo- that may not belong to the type for statistical reasons is types, which are all the haplotypes with more than six estimated based on the samples in the “gap” of steps samples. Also in are four of the eleven haplotypes with low sample frequency just beyond the mountain. with six or five samples (discussed below). The file The statistical background percent (SBP), a recommend- “Polish12.xls” has all 614 haplotypes at 12 markers in a ed measure of type quality, is the percent of samples in format similar to . a mountain that may not belong to the type for statisti- cal reasons, at 70% confidence maximum, including P type is the most common haplotype at 12 markers in objective adjustment for systematic statistical errors. A Poland. The 12-marker haplotypes in are an summary of the mountain method is at the end of the introduction; P, K, N, Y, etc. types are defined using the companion article. best ranked of all 67 markers with more discussion below. A small SBP means an isolated type, taken as evidence, My “Code Type” labels of are assigned albeit not proof, that the type represents a clade. with hypothetical foresight, anticipating the 67-marker results presented later in this article. A common haplo- Concentration of a type in Poland is taken as evidence, type, even at only 12 markers, provides a candidate modal albeit not proof, that the type represents a clade. haplotype for a type, as explained in the companion article and as demonstrated below. (“Type” means: The Polish Project is used as representative of Poland. hypothetical clade / modal haplotype / set of possible Yhrd is used to verify and update Pawlowski’s most haplotypes / associated cluster of data). Most of the common haplotype, here called P type. The Ysearch P haplotypes in are such candidates, but the statisti- type fraction of entries with “Poland” as origin is used cal evidence at 12 markers is insufficient by itself to as a calibration of the Polish fraction on Ysearch; confidently conclude that any of the entries is a other types with similar Polish fraction in Ysearch are modal haplotype for a type. Even at 67 markers some of taken to be similarly Polish. them are highly hypothetical, as discussed below. The fourth most common haplotype in , eleven sam- Age is estimated using Averaged Squared Distance ples, which I call PbKa, could also be a candidate type, but (ASD) in STR data, as explained in the companion I have found no evidence for it.
Load more

Recommended publications
  • R1b-M343 (Xp312 Xu106) Y-STR Report
    R1b-M343 (xP312 xU106) Y-STR Report Dirk Struve May 21, 2017 Contents 1 Introduction1 2 About Y-STR markers2 3 Time estimates3 3.1 A word of caution.........................3 3.2 Method..............................4 3.3 Results...............................6 3.3.1 111 marker TMRCA estimates..............6 3.3.2 500 marker TMRCA estimates..............9 3.3.3 Towards genealogical time frames............ 13 3.3.4 Using only YFull results................. 16 4 Marker statistics 17 References 19 1 Introduction This document contains time estimates about the formation of clades and their TMRCAs (Time to Most Recent Common Ancestor) based upon Y- STR marker results reported by YFull and Family Tree DNA. You might ask yourself, why use STRs when YFull has already published a phylogenetic tree [15] with time estimates solely based on the stable SNP mutations. There are a variety of good reasons for this: 1 1. Different scientific methods can yield different results. It is good to calculate time estimates using independent methods. If different meth- ods yield the same results, we know that we can trust the methods. Otherwise we should be cautious and search for improvements. 2. Mutations happen by coincidence. There is always a statistical uncer- tainty. Using different methods can help to identify statistical outliers and improve the results. 3. Not all SNPs are suited for genealogical purposes. This could result in wrong time estimates. Even if YFull has carefully crafted it's method to exclude wrong SNPs [1], it is good to have a second method to verify their results. 4. STRs provide a higher time resolution than SNPs.
    [Show full text]
  • The Phylogenealogy of R-L21: Four and a Half Millennia of Expansion and Redistribution
    The phylogenealogy of R-L21: four and a half millennia of expansion and redistribution Joe Flood* * Dr Flood is a mathematician, economist and data analyst. He was a Principal Research Scientist at CSIRO and has been a Fellow at a number of universities including Macquarie University, University of Canberra, Flinders University, University of Glasgow, University of Uppsala and the Royal Melbourne Institute of Technology. He was a foundation Associate Director of the Australian Housing and Urban Research Institute. He has been administrator of the Cornwall Y-DNA Geographic Project and several surname projects at FTDNA since 2007. He would like to give credit to the many ‘citizen scientists’ who made this paper possible by constructing the detailed R1b haplotree over the past few years, especially Alex Williamson. 1 ABSTRACT: Phylogenealogy is the study of lines of descent of groups of men using the procedures of genetic genealogy, which include genetics, surname studies, history and social analysis. This paper uses spatial and temporal variation in the subclade distribution of the dominant Irish/British haplogroup R1b-L21 to describe population changes in Britain and Ireland over a period of 4500 years from the early Bronze Age until the present. The main focus is on the initial spread of L21-bearing populations from south-west Britain as part of the Beaker Atlantic culture, and on a major redistribution of the haplogroup that took place in Ireland and Scotland from about 100 BC. The distributional evidence for a British origin for L21 around 2500 BC is compelling. Most likely the mutation originated in the large Beaker colony in south-west Britain, where many old lineages still survive.
    [Show full text]
  • Reconstruction of the Lineage Y Chromosome Haplotype Of
    1Institute of Molecular Anthropology, 75005 Paris, France Abstract: As part of the Napoléon I Genome (NIG) project we have reconstructed, based on more than one hundred Y-STRs (Y-short tandem repeats), the complete Y-haplotype of the non-recombinant part of the Y-chromosome (NRY) of French Emperor Napoléon I (1769-1821). We already knew the allelic values at Y-markers of the Y- chromosome of Napoléon I, but only for the palindromic STR YCAIIa and b and for the non-palindromic Y-STR DYS19. The present reconstruction aims to compare the allelic values at Y-STRs of the DNA of Charles Napoléon (C.N.), the living 4th generation descendant of Jérôme Bonaparte (Napoléon I’s youngest brother), with those of Alexandre Colonna Walewski (A.C.W.), the living 4th generation descendant of Count Alexandre Walewski (the son born of the union between Napoléon I and Countess Maria Walewska). We have previously established that Napoléon I, C.N. and A.C.W. are of the same Y-haplogroup E1b1b1b2a1. The allelic values for C.N. and A.C.W. are the same for ninety-three other non-palindromic markers (belonging to ninety different STRs) and for thirty- eight other palindromic markers (belonging to fifteen different STRs); these values then constitute those deduced in the reconstruction of the allelic values of the STR markers of the Napoléon I’s Y-haplotype. Four non-palindromic STRs and two palindromic STRs have different allelic values in C.N. and A.C.W.; we have deduced the allelic value of Napoléon I for one (DYS454), and the probable allelic values for two (Y-GATA-C4 and DYS712) of these non- palindromic variable STRs.
    [Show full text]
  • R1b-M343 (Xp312 Xu106) Y-STR Report
    R1b-M343 (xP312 xU106) Y-STR Report Dirk Struve Dec 4, 2017 Contents 1 Introduction1 2 About Y-STR markers2 3 FTDNA and YFull results3 3.1 Differences between FTDNA and YFull.............3 3.2 How to merge...........................4 4 Time estimates5 4.1 A word of caution.........................5 4.2 Method..............................6 4.3 Results...............................8 4.3.1 111 marker TMRCA estimates..............8 4.3.2 500 marker TMRCA estimates.............. 13 4.3.3 Towards genealogical time frames............ 17 4.3.4 Using only YFull results................. 20 5 Marker statistics 22 References 24 1 Introduction This document contains time estimates about the formation of clades and their TMRCAs (Time to Most Recent Common Ancestor) based upon Y- STR marker results reported by YFull and Family Tree DNA. 1 You might ask yourself, why use STRs when YFull has already published a phylogenetic tree [16] with time estimates solely based on the stable SNP mutations. There are a variety of good reasons for this: 1. Different scientific methods can yield different results. It is good to calculate time estimates using independent methods. If different meth- ods yield the same results, we know that we can trust the methods. Otherwise we should be cautious and search for improvements. 2. Mutations happen by coincidence. There is always a statistical uncer- tainty. Using different methods can help to identify statistical outliers and improve the results. 3. Not all SNPs are suited for genealogical purposes. This could result in wrong time estimates. Even if YFull has carefully crafted it's method to exclude wrong SNPs [1], it is good to have a second method to verify their results.
    [Show full text]
  • Uniting the Time Scales of Genealogy and Genetics Using Correlation Techniques to Explore Y-DNA
    Uniting the Time Scales of Genealogy and Genetics Using Correlation Techniques to Explore Y-DNA -- William E. Howard III -- Version 24: 25 February 2014 Abstract: We have investigated the errors and uncertainties involved in the RCC correlation approach to the analysis of Y-DNA haplotypes using extensive mutation models with weighted DYS values. We conclude that: (1) there is no evidence that the observed RCC time scale, properly calibrated, cannot be used over time periods of at least 100,000 years; (2) that the ratio of the standard deviation to the RCC value at each mutation averages about 43 percent (SD = 4%) over times of genetic interest; (3) a correction (F>1) needs to be applied to observed values of RCC over genetic time intervals to account for backward mutations that are known to occur but cannot be observed; (4) the distribution of marker values as well as the Chandler average mutation rate over 37 markers is consistent with Poisson statistics, confirming that the distribution of mutations take place randomly; and (5) using an extrapolation of junction points on a Y-DNA STR phylogenetic tree, we are able to estimate the date of the progenitor of Haplotype A to about 100,000 years ago (est. SD ~ 30%) as well as the dates for other haplotypes and SNPs. We suggest error assignments that should be applied to pairs and groups of haplotypes and we present methods to estimate the time when the progenitor of a group lived. We investigate the error assignments to be made in the analysis of groups of haplotypes (e.g., in surname clusters and junction points on a dated Y-STR phylogenetic tree).
    [Show full text]
  • DYF399X Report
    David N. Ewing, M.D. January 29, 2009 DYF399X Report Note This page concerns only DYF399X in the Ewing Project and presupposes a working knowledge of the project and how its groups are organized. Links to our other Results Pages are available in the Results Directory, which can be reached through the link at the top of this page. If you are not acquainted with the Ewing Project, please start with the Help and Introduction links. Background DYF399X usually consists of three alleles of a very rapidly mutating marker in a palindromic region of the Y-chromosome, which makes it subject to recLOH events and much complicates interpretation. If you don’t understand this first sentence of the report, don’t feel like the Lone Ranger—me neither, really. At the end of this page under References, I have quoted an email from Thomas Krahn, a scientist with FtDNA, which gives a number of references for the more technically minded among you. For our purposes, it is sufficient to start with the understanding that DYF399X provides rapidly mutating markers that may help us differentiate branches within the large closely related group of Ewings. DYF399X will only be helpful to men who have already identified a group of genetically closely related men for which they are trying to get better genetic branch resolution. For the Ewing Project, this means that it could be helpful for members of any of the subgroups of Groups 1, and 2 to have this test. It would not be much help for members of Groups 3, 4 and 5—at least not until some larger clusters have been identified within these groups.
    [Show full text]
  • HIS NAME IS MY NAME TOO a Y‐DNA STUDY of the OWSTON SURNAME and ITS VARIANTS James M
    HIS NAME IS MY NAME TOO A Y‐DNA STUDY OF THE OWSTON SURNAME AND ITS VARIANTS James M. Owston, EdD Draft Version 6.2 5 February 2012 The Owston One‐Name Study is registered with the The author is a member of the ABSTRACT In 1990, three family researchers had the fortune of discovering each other nearly simultaneously and began sharing information that became the basis of this study. While nearly all discovered Owstons and Oustons could be traced to one of three families having their origins in the original East Riding of Yorkshire, there was no evidence proving that familial connections existed among the three groups. These families originated in Ganton, Sherburn, and Thornholme in the parish of Burton Agnes. By utilizing Y-DNA testing at 43 markers, this study sought to discover if the three families could be linked genealogically, although traditional records signifying such did not exist. If connected, it would likely to have been prior to the adoption of English parish registers in 1538. Although the study is ongoing, preliminary reports link members of all three families to a common ancestor in the past. Seven of the 10 original participants share common markers of the I1 haplogroup. Of the remaining three participants, two Thornholme subjects did not match anyone else. Since genealogical data has a confirmed paper trail to the earliest known ancestor of the Thornholme family, it has been determined that non-paternity events occurred in these two lines. In addition, one Sherburn family member did not match any other participant due to an adoption in his ancestral line.
    [Show full text]
  • RJGG of the Genetic Legacy of the Mongols
    The Russian Journal of Genetic Genealogy (Русская версия): Том 4, №2, 2012 год ISSN: 1920-2997 http://ru.rjgg.org © Все права защищены RJGG The Genetic Origin Kherlen Batbayar of the Turko-Mongols and Review Zhaxylyk M. Sabitov of The Genetic Legacy of the Mongols. Part 1: The Y-chromosomal Lineages of Chinggis Khan Abstract Batu-Mungke Dayan Khan, a direct descendant of Chinggis Khan (commonly known as Genghis Khan) proved himself to be one of the most influential and powerful rulers in Mongolian history. After experiencing decades of East and West Mongolian political strife and incessant battling, Dayan Khan became the sole survivor of Chinggis Khan’s lineage in Mongolia Proper. Chinggis Khan raised five sons, all of whom reached adulthood. Besides Dayan Khan’s descendants residing in Mongolia Proper, only two other offspring of Chinggis Khan’s family line prevailed in the Central Asian countries of Kazakhstan and Uzbekistan. These two lineages’ modal haplotypes belong to haplogroup C3 under different subgroups. However, according to a genetic research study, The Genetic Legacy of the Mongols, Chinggis Khan’s descendants number approximately 16 million. One may only hypothes- ize that this calculation is unreasonably inaccurate when studying both the historical and genetic, or genealogical, points-of-view. In this study, we have determined Batu-Mungke Dayan Khan’s haplotype by analyzing 12 Y- chromosomal STR loci of seven surviving elders of the House of Dayan Khan. Our findings differ significantly from those provided in The Genetic Legacy of Mongols. Chinggis Khan’s three surviving lineages’ Y-chromosome DNA test results suggest the near-extinction, not the proliferation, of the direct male descendant line of Chinggis Khan.
    [Show full text]
  • Phasing the Chromosomes of a Family Group When One Parent Is
    Journal of Genetic Genealogy, 6(1), 2010 Towards improvements in y-DNA Surname Project Administration James M. Irvine Abstract This paper surveys a sample of 12 y-DNA surname projects, selected to reflect a variety of features, with the objective of identifying some possible learning points for amateur project administrators. The survey identifies a wide variety of procedures now being used in administering such projects. Many of these variations appear to reflect differing opportunities and constraints for individual projects that are determined by surname size. The paper develops three inter-related issues directly arising from the survey. First, means for relating project size to surname size are explored. It is shown that few projects exceed a “penetration” ratio of more than 0.1% of y-DNA tests per head of population, and that this ratio may be an inverse function of surname size. Measures are also developed to relate old world/new world ratios of surname populations and participants‟ places of residence; from these a crude measure of any geographical bias in individual projects is developed. Second, the survey identifies a diversity of the “rules of thumb” presently used for determining genetic “closeness,” and a case is made for moving on from genetic distance criteria that give equal weight to all markers to a criterion that takes account of differing mutation rates, such as some TiP parameter. Third, the difficulties in identifying and handling the sensitive subject of Non Paternal Events (NPEs) are addressed. A case made for differentiating between introgressive- and egressive-NPEs, and it is shown that most projects probably underestimate this phenomenon.
    [Show full text]
  • The Comments Below Apply to the Currently Available Y Chromosome Marker Results Pertaining to the Low German Mennonite DNA Project
    Mennonite DNA Project Y Chromosome Data Discussion by Tim Janzen: January 2021 [email protected] The Low German Mennonite DNA Project Y chromosome data is available for download as an Excel spreadsheet. The headings are self-explanatory. There is a dark gray row between each surname. Thick black lines separate the various subgroups within surnames if there is more than one progenitor for that surname. In a few cases, it is unclear if a haplotype belongs in a specific subgroup. In such cases there is a question mark after the number in the subgroup column. Y chromosome STR marker values that are different from the modal value are highlighted in yellow. In such situations, a mutation has occurred within the past 500 years or so in one of the lineages from the original progenitor of that surname or subgroup. If the earliest known ancestors were known to be brothers the names of the brothers are highlighted in blue. The FTDNA kit numbers for new participants since the last update a year ago are highlighted in green. In some situations there is additional information for some multi-copy markers such as DYS459, DYS 464, and CDY on the Family Tree DNA website that is not included in the spreadsheet and the cells in the spreadsheet are highlighted in brown where this is the case. The information wasn’t included in the spreadsheet for simplicity, but the data can be found in the project’s website at https://www.familytreedna.com/public/menno/default.aspx?section=yresults after any project member has logged into the FTDNA website.
    [Show full text]
  • Null Alleles in Genetic Genealogy 0
    Null Alleles in Genetic Genealogy 0 Thomas Krahn FTDNA Conference 2009 Definition of Null Allele ● Original meaning: A mutant copy of a gene that completely lacks that gene's normal function. (Wikipedia) DNA Gene Promotor Transcription RNA Polymerase mRNA Not a sharp definition. Splicing Many things can go wrong in the complex gene Translation expression process. Protein Ribosomes Definition of Null Allele ● Concerning DNA markers: A DNA segment of good quality, limited to the two primer pairs of a PCR reaction that doesn't yield a PCR product in some biological samples while all other samples of that kind show a clearly detectable signal with the same PCR reaction. Note: This is my own definition. Other definitions I found in the literature and on the internet usually focus on a very narrow subtype of a DNA segment. E.g. STR markers. Definition of Null Allele ● Concerning DNA markers: A DNA segment of good quality, limited to the two primer pairs of a PCR reaction that doesn't yield a PCR product in some biological samples while all other samples of that kind show a clearly detectable signal with the same PCR reaction. For a PCR reaction we need a solution of intact DNA. Degraded (sheared) DNA cannot be amplified because the TAQ polymerase needs to extend one DNA strand down until the reverse primer. If the TAQ drops off from the DNA segment before it reaches the reverse primer we will not get an exponential amplification. Since degraded DNA doesn't represent a species who can have descendants, we exclude degraded DNA from being a Null Allele for genealogical purpose.
    [Show full text]
  • Y Chromosome)
    Advances in Anthropology 2011. Vol.1, No.2, 26-34 Copyright © 2011 SciRes. DOI:10.4236/aa.2011.12005 Mutation Rate Constants in DNA Genealogy (Y Chromosome) Igor L. Rozhanskii, Anatole A. Klyosov* The Academy of DNA Genealogy, Newton, USA. Email: *[email protected] Received September 14th, 2011; revised November 10th, 2011; accepted November 21st, 2011. The basic principles of DNA genealogy and the mutation rate constants for haplotypes of Y chromosome are considered. They are exemplified with 3160 haplotypes, 2489 of those in the 67 marker format, with 55 DNA lineages, 11 of them having documented confirmed common ancestors. In total, they cover 8 haplogroups and the time range from 225 to ca. 8000 years before present. A series (including 67 marker, 37 marker, 25 marker, 16 marker mostly of the Y filer haplotype panel, 12 marker, as well as the “slowest” 22 marker and its subset of 6 marker haplotypes) were calibrated using documented genealogies (with a number of lineages which allegedly descended from some legendary and/or mythical historical figures that were examined and verified employing the calibration plots). The study principally confirms a number of previously made or assumed theoretical foun- dations of DNA genealogy, such as a postulated stochastic character of mutations in non-recombining parts of DNA, the first-order kinetics of mutations in the DNA, the same values of the mutation rate constants for dif- ferent haplogroups and lineages, and the principles of calculating timespans to the most recent common ances- tors taking into account corrections for back (reverse) mutations. Keywords: Y Chromosome, Mutations, Haplotypes, Haplogroups, TMRCA, STR, SNP Introduction particularly wide-spread in Western Europe.
    [Show full text]