Chromosome as a chronicler: Genetic dating, historical events, and DNA-genealogic temptation

Chromosome as a chronicler: Genetic dating, historical events, and DNA-genealogic temptation Nonrecombinant portions of the genome, Y chromosome and mitochondrial DNA, are widely used for research on human population gene pools and reconstruction of their history. These systems allow the genetic dating of clusters of emerging haplotypes. The main method for age estimations is ρ statistics, which is an average number of mutations from founder haplotype to all modern-day haplotypes. A researcher can estimate the age of the cluster by multiplying this number by the mutation rate. The second method of estimation, ASD, is used for STR haplotypes of the Y chromosome and is based on the squared difference in the number of repeats. In addition to the methods of calculation, methods of Bayesian modeling assume a new significance. They have greater computational cost and complexity, but they allow obtaining an a posteriori distribution of the value of interest that is the most consistent with experimental data. The mutation rate must be known for both calculation methods and modeling methods. It can be determined either during the analysis of lineages or by providing calibration points based on populations with known formation time. These two approaches resulted in rate estimations for Y-chromosomal STR haplotypes with threefold difference. This contradiction was only recently refuted through the use of sequence data for the complete Y chromosome; “whole-genomic” rates of single nucleotide mutations obtained by both methods are mutually consistent and mark the area of application for different rates of STR markers. An issue even more crucial than that of the rates is correlation of the reconstructed history of the haplogroup (a cluster of haplotypes) and the history of the population. Although the need for distinguishing “lineage history” and “population history” arose in the earliest days of phylogeographic research, reconstructing the population history using genetic dating requires a number of methods and conditions. It is known that population history events leave distinct traces in the history of haplogroups only under certain demographic conditions. Direct identification of national history with the history of its occurring haplogroups is inappropriate and is avoided in population genetic studies, although because of its simplicity and attractiveness it is a constant temptation for researchers. An example of DNA genealogy, an amateur field that went beyond the borders of even citizen science and is consistently using the principle of equating haplogroup with lineage and population, which leads to absurd results (e.g., Eurasia as an origin of humankind), can serve as a warning against a simplified approach for interpretation of genetic dating results. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Russian Journal of Genetics Springer Journals

Chromosome as a chronicler: Genetic dating, historical events, and DNA-genealogic temptation

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Publisher
Springer Journals
Copyright
Copyright © 2016 by Pleiades Publishing, Inc.
Subject
Biomedicine; Human Genetics; Animal Genetics and Genomics; Microbial Genetics and Genomics
ISSN
1022-7954
eISSN
1608-3369
D.O.I.
10.1134/S1022795416070048
Publisher site
See Article on Publisher Site

Abstract

Nonrecombinant portions of the genome, Y chromosome and mitochondrial DNA, are widely used for research on human population gene pools and reconstruction of their history. These systems allow the genetic dating of clusters of emerging haplotypes. The main method for age estimations is ρ statistics, which is an average number of mutations from founder haplotype to all modern-day haplotypes. A researcher can estimate the age of the cluster by multiplying this number by the mutation rate. The second method of estimation, ASD, is used for STR haplotypes of the Y chromosome and is based on the squared difference in the number of repeats. In addition to the methods of calculation, methods of Bayesian modeling assume a new significance. They have greater computational cost and complexity, but they allow obtaining an a posteriori distribution of the value of interest that is the most consistent with experimental data. The mutation rate must be known for both calculation methods and modeling methods. It can be determined either during the analysis of lineages or by providing calibration points based on populations with known formation time. These two approaches resulted in rate estimations for Y-chromosomal STR haplotypes with threefold difference. This contradiction was only recently refuted through the use of sequence data for the complete Y chromosome; “whole-genomic” rates of single nucleotide mutations obtained by both methods are mutually consistent and mark the area of application for different rates of STR markers. An issue even more crucial than that of the rates is correlation of the reconstructed history of the haplogroup (a cluster of haplotypes) and the history of the population. Although the need for distinguishing “lineage history” and “population history” arose in the earliest days of phylogeographic research, reconstructing the population history using genetic dating requires a number of methods and conditions. It is known that population history events leave distinct traces in the history of haplogroups only under certain demographic conditions. Direct identification of national history with the history of its occurring haplogroups is inappropriate and is avoided in population genetic studies, although because of its simplicity and attractiveness it is a constant temptation for researchers. An example of DNA genealogy, an amateur field that went beyond the borders of even citizen science and is consistently using the principle of equating haplogroup with lineage and population, which leads to absurd results (e.g., Eurasia as an origin of humankind), can serve as a warning against a simplified approach for interpretation of genetic dating results.

Journal

Russian Journal of GeneticsSpringer Journals

Published: Jul 30, 2016

References

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