The Pattern of Polymorphism on Human Chromosome 21

Abstract

Polymorphism data from 20 partially resequenced copies of human chromosome 21-more than 20,000 polymorphic sites-were analyzed. The allele-frequency distribution shows no deviation from the simplest population genetic model with a constant population size (although we show that our analysis has no power to detect population growth). The average rate of recombination per site is estimated to be roughly one-half of the rate of mutation per site, again in agreement with simple model predictions. However, sliding-window analyses of the amount of polymorphism and the extent of linkage disequilibrium (LD) show significant deviations from standard models. This could be due to the history of selection or demographic change, but it is impossible to draw strong conclusions without much better knowledge of variation in the relationship between genetic and physical distance along the chromosome.[Supplemental material is available online at www.genome.org.]There are essentially two reasons for studying the pattern of genetic polymorphism in population samples. The first is to identify polymorphisms that have important phenotypic effects. The pattern of polymorphism is important when searching for alleles that are statistically associated with phenotypic differences, either because they are directly causative, or because they are in linkage disequilibrium (LD) with variants (at other sites) that are directly causative.The second reason, which is also the focus of this paper, is interest in the evolutionary process that gave rise to the pattern of polymorphism. One may be interested in forces that influence all loci, such as migration, mutation, and recombination, or one may be interested in the history of selection on a particular locus. Many years of research in population genetics (empirical as well as theoretical) have led to a sophisticated mathematical theory for this type of analysis (for review, see Li 1997;Kreitman 2000;Nordborg 2001;Stephens 2001). Arguably the most fundamental insight that has emerged from this work is that in order to overcome the enormous variance that is due to random history and estimate evolutionary parameters accurately, data from surprisingly large numbers of loci are needed. Indeed, it can be said (with only slight exaggeration), that theory has typically told us that in order to answer the questions of interest, more data are required than is feasible to collect.This situation is about to change. As a result of rapid advances in genotyping technology (primarily due to the enormous efforts devoted to finding polymorphisms associated with human diseases), polymorphism data on a genomic scale will soon become common. The most spectacular example to date is provided by Patil et al. (2001), who partially resequenced 20 copies of human chromosome 21. Although their data are in many ways unsuitable for evolutionary genetics (see below), this is to a significant extent compensated for by quantity: over 21,000 polymorphic sites, with enough recombination to ensure that most sites are effectively ind...

Pattern of polymorphism after strong artificial selection in a domestication event

“…Therefore, such selection does not necessarily reduce neutral variation in the region surrounding the selected site. As a consequence, artificial selection is not as easy to detect as a recent selective sweep due to natural selection, which creates a clear reduction in the level of polymorphism (15,30,31). For selection during domestication, the initial frequencies of alleles that ancient breeders favored have greatly affected the likelihood that evidence for selection can be detected from patterns of polymorphism.…”

Estimating Recombination Rates From Single-Nucleotide Polymorphisms Using Summary Statistics

“…However, this assumption is not realistic. For example, there is considerable evidence that crossing-over rates vary across the human genome at all scales (e.g., Fullerton et al 1994;Dunham et al 1999;Jeffreys et al 2001;Innan et al 2003). To examine the effects of nonuniform crossing over, we simulated data under a model where crossing over is nonuniform and gene conversion is uniform along the sequence.…”

“…To compare estimation methods, we tested them on 50-kb DNA sequences simulated with u set to 0.8/kb (estimates for human data from Innan et al 2003) and sample size of n ¼ 18 for haplotype data and 2n ¼ 36 for genotype data. It is usually difficult to estimate both gene-conversion rates and tract lengths from SNPs (Padhukasahasram et al 2004).…”

A two-locus gene conversion model with selection and its application to the human RHCE and RHD genes

“…Therefore, and C are estimated from w and b , assuming free recombination (R ϭ ϱ). This assumption is not unreasonable, because the distance between the two genes is Ϸ80 kb, so that R may not be small when the recombination rate is on the same order as the mutation rate (45,46). The effect of recombination on w and b is very small unless R is low (27).…”