TITLE:
Kilin-Klyosov TMRCA Calculator for Time Spans up to Millions of Years
AUTHORS:
Anatole A. Klyosov, Vladimir V. Kilin
KEYWORDS:
Haplogroups, Haplotypes, DNA Genealogy, TMRCA, Mutation Rates
JOURNAL NAME:
Advances in Anthropology,
Vol.6 No.3,
August
24,
2016
ABSTRACT: A TMRCA (Time to the Most Recent Common Ancestor) calculator has been developed, with a capacity to handle up to 10,000 haplotypes simultaneously, for haplotypes being in any format within the 111 markers in the FTDNA (Family Tree DNA, a leading company in systematics of the haplotypes) nomenclature, for haplotypes being in any combination with respect to number of their markers, and for the TMRCA values from a few hundred years to millions of years. The calculator shows the TMRCA data calculated separately and simultaneously in the 6-, 12-, 25-, 37, 67, and 111-marker formats by the linear method, and for haplotypes of any format, such as 7-, 8-, 9-, 10-, 17-, 19-, 23- and any other format by the quadratic method. The calculator also shows a number of mutations (in the whole given dataset of haplotypes), so the TMRCA values can be verified manually, if desired so. The calculator automatically makes corrections for back mutations (in the linear method; there is no need for corrections in the quadratic method), and considers multi-marker mutations and zero alleles, counting them correctly as one mutation. The calculator can be navigated to exclude markers which show an excessive dispersion, which likely is an indication of “admixtures”, which do not belong to the given set of haplotypes. The paper provides a number of examples of TMRCA calculations for datasets of different haplogroups, and shows that the mutation rate constants are the same in different haplogroups. The papers provides a comparison of mutation rate tables by Chandler (2006), Ballantyne et al. (2010), Heinila (2012) and an anonymous investigator (2014) with the mutation rate constants determined and examined in this study. It is shown that the above authors noticeably and significantly overestimated their mutation rates, which often lead to unrealistic TMRCAs.