First of all, it is inconceivable to me how scientists can continue to use the 3x slower "evolutionary mutation rate" for their analyses of Y-chromosome ages on the basis of Y-STR markers. I have done my small part in my Y-STR series to show that this mutation rate is applicable only for a rather specific demographic history, and completely unsuitable to real growing human populations where Y-STR variance accumulates at close to the genealogical rate. And, my observations merely elaborated quantitatively what was already present in Zhivotovsky et al. (2006) but has been completely ignored since:
In simulations of a neutral process with average rate of increase m = 1, the number of surviving haplogroups rapidly decreased with time and corresponded well with the theory of mutant survival (Li 1955, p. 242), and the average size of the surviving haplogroups increased each generation by a value rapidly approaching 0.5 (data not shown), which agrees with asymptotic fraction of 2/t of haplotypes that survive at generation t (Athreya and Ney 1972, p. 19). The accumulated variance increased almost linearly (fig. 1), at a rate of increase about 0.00028 per generation; that is, the actual rate of accumulation microsatellite variation was about 3.6 times less than that predicted from the germ line mutation rate. This corresponds perfectly to the 3- to 4-fold difference observed between germ line and evolutionarily effective mutation rate.The issue is all but resolved in the amateur "genetic genealogy" community, but even professional geneticists often use either genealogical or evolutionary rate, or take an agnostic stance by reporting results based on both rates. To arrive at strong conclusions about a topic on the basis of a mutation rate that is, to say the least, controversial, without even acknowledging the existence of a controversy is unsatisfactory. Y-chromosome researchers ought to copy the attitude of those working with autosomal DNA, where a corresponding mutation rate controversy was not swept under the carpet, but acknowledged (e.g., in the recent Meyer et al. high-coverage Denisova paper), with the implications of the uncertainty during the present "transitional" period quantified in the form of wider confidence intervals.
This "mutation rate" issue notwithstanding, it was also recently shown that by Busby et al. that Y-STR based estimates have a dependence on the set of Y-STRs used, with markers exhibiting linear behavior across different time spans. This does not invalidate their use as molecular clocks, but highlights the need to not only select a bunch of Y-STRs, but also either (i) demonstrate that the selected set exhibits linear behavior for the time span of interest, or (ii) correct for deviations from linearity. Again, this type of modelling of microsatellite behavior was recently achieved for autosomal STRs by Sun et al. Note that such deviations result in a slower rate than the genealogical one, but the mechanism whereby this is produced is completely different than the one proposed by Zhivotovsky et al.: it is not drift in a non-growing (m=1) population that reduces the effective rate, but rather "saturation" of the mutation process, whereby the variance at fast-mutating markers grows sub-linearly with time, because of physical constraints on their possible range of values.
I don't hope that Y-STR based age estimation will have much to offer in the coming years. But the third set of the 1000 Genomes Project is on its way, and this will include a variety of South Asian samples. Very soon we will be in a good position to study the time depth of common ancestry between e.g., European and South Asian Y-chromosomes within various haplogroups using point mutations, and these are not plagued by many of the problems associated with Y-STR variation and its interpretation.
Finally, I can't help but notice that this paper has not acknowledged the tremendous progress in resolving the Y chromosome phylogeny done by non-academic researchers. With the current state of our knowledge, the claim that haplogroup R1a1 is "autochthonous" in India is not tenable. Even if one discounts all the evidence made by SNP discoveries in the commercial testing world (and why should they?), finer-scale structure within this haplogroup has now been officially published and appears to be inconsistent with a South Asian origin of this haplogroup.
Certainly, not all is resolved; for example, the representation of tribal populations in commercial DNA testing is almost non-existent, and a sampling of their Y-SNP diversity is urgently needed. A very useful paradigm of research is that of recent work on the most basal clade of the Y-chromosome phylogeny (A00) in which the identification of very unique Y-chromosomes by genetic genealogists was combined with academic samples of "indigenous" peoples to produce new knowledge.
Much of population genetic research will benefit from such consilience between academics and amateurs. This is not an idle hope, but a recognition that this field is one in which the public not only has a substantial interest but can also do something about it. Many might be interested in Mars exploration, but without Elon Musk's bank account, most are consigned to being consumers of information about the Red Planet. Hopefully, better ways of combining the efforts of research scientists and the educated public can be identified and used in the near future.
PLoS ONE 7(11): e50269. doi:10.1371/journal.pone.0050269
Population Differentiation of Southern Indian Male Lineages Correlates with Agricultural Expansions Predating the Caste System
GaneshPrasad ArunKumar et al.
Previous studies that pooled Indian populations from a wide variety of geographical locations, have obtained contradictory conclusions about the processes of the establishment of the Varna caste system and its genetic impact on the origins and demographic histories of Indian populations. To further investigate these questions we took advantage that both Y chromosome and caste designation are paternally inherited, and genotyped 1,680 Y chromosomes representing 12 tribal and 19 non-tribal (caste) endogamous populations from the predominantly Dravidian-speaking Tamil Nadu state in the southernmost part of India. Tribes and castes were both characterized by an overwhelming proportion of putatively Indian autochthonous Y-chromosomal haplogroups (H-M69, F-M89, R1a1-M17, L1-M27, R2-M124, and C5-M356; 81% combined) with a shared genetic heritage dating back to the late Pleistocene (10–30 Kya), suggesting that more recent Holocene migrations from western Eurasia contributed less than 20% of the male lineages. We found strong evidence for genetic structure, associated primarily with the current mode of subsistence. Coalescence analysis suggested that the social stratification was established 4–6 Kya and there was little admixture during the last 3 Kya, implying a minimal genetic impact of the Varna (caste) system from the historically-documented Brahmin migrations into the area. In contrast, the overall Y-chromosomal patterns, the time depth of population diversifications and the period of differentiation were best explained by the emergence of agricultural technology in South Asia. These results highlight the utility of detailed local genetic studies within India, without prior assumptions about the importance of Varna rank status for population grouping, to obtain new insights into the relative influences of past demographic events for the population structure of the whole of modern India.