http://hpgl.stanford.edu/publication...4_p487-494.pdf


CONCLUSIONS

The haploid Y chromosome is unusual in that it is depauperate in genes relative to other nuclear chromosomes. However, the other unusual innate properties of being largely nonrecombining as well as having a low effective population size relative to other loci, combine both to preserve haplotypes over evolutionary time scales and to record numerous episodes of population divergence, even on micro-geographic scales, making it perhaps the single most insightful haplotype system known to characterize population affinity, substructure, and history. Some Y-chromosome polymorphisms could become part of a genome-wide inventory of genomic control markers useful in assessing the influences of population stratification. Both the Y chromosome and autosomes can be evaluated as SNPSTR systems with the empirical determination of phase providing an index of haplotype deterioration (Mountain et al. 2002). The Y chromosome provides a comparative model for evaluating haplotypes from other regions of the genome. The recovery of complex scenarios can be best advanced via an integrative approach, since the totality of the evidence should be reflective of an overall history and some correlation should be expected. When the story lines from multiple genes reinforce one another, overall population histories are revealed. Conversely, when different genes yield different haplotype patterns, locus-specific forces are in play. The recent and ongoing progress in deciphering the Y-chromosome structure in contemporary populations provides new opportunities to formulate specific testable hypotheses involving human evolutionary population genetics. Although the genetic legacy of Homo sapiens remains incomplete, the recent ability to unearth new levels of shared Y-chromosome haplotypic heritage and subsequent diversification provide not only an index of contemporary population structure, but also a preamble to human prehistory and substantial foundation for comparisons with other genomic regions.