Variation in estimated recombination rates across human populations

Recently it has been reported that recombination hotspots appear to be highly variable between humans and chimpanzees, and there is evidence for between-person variability in hotspots, and evolutionary transience. To understand the nature of variation in human recombination rates, it is important to describe patterns of variability across populations. Direct measurement of recombination rates remains infeasible on a large scale, and population-genetic approaches can be imprecise, and are affected by demographic history. Reports to date have suggested broad similarity in recombination rates at large genomic scales and across human populations. Here, we examine recombination rate estimates at a finer population and genomic scale: 28 worldwide populations and 107 SNPs in a 1 Mb stretch of chromosome 22q. We employ analysis of variance of recombination rate estimates, corrected for differences in effective population size using genome-wide microsatellite mutation rate estimates. We find substantial variation in fine-scale rates between populations, but reduced variation within continental groups. All effects examined (SNP-pair, region, population and interactions) were highly significant. Adjustment for effective population size made little difference to the conclusions. Observed hotspots tended to be conserved across populations, albeit at varying intensities. This holds particularly for populations from the same region, and also to a considerable degree across geographical regions. However, some hotspots appear to be population-specific. Several results from studies on the population history of humans are in accordance with our analysis. Our results suggest that between-population variation in DNA sequences may underly recombination rate variation.     

Apparent mutational hotspots and long distance linkage disequilibrium resulting from a bottleneck

Genome wide patterns of nucleotide diversity and recombination reveal considerable variation including hotspots. Some studies suggest that these patterns are primarily dictated by individual locus history related at a broader scale to the population demographic history. Because bottlenecks have occurred in the history of numerous species, we undertook a simulation approach to investigate their impact on the patterns of aggregation of polymorphic sites and linkage disequilibrium (LD). We developed a new index (Polymorphism Aggregation Index) to characterize this aggregation and showed that variation in the density of polymorphic sites results from an interplay between the bottleneck scenario and the recombination rate. Under particular conditions, aggregation is maximized and apparent mutation hotspots resulting in a 50-fold increase in polymorphic sites density can occur. In similar conditions, long distance LD can be detected.     

Population-genetic basis of haplotype blocks in the 5q31 region

We investigated patterns of nucleotide variation in the 5q31 region identified by Daly et al. as containing haplotype blocks, to determine whether the blocklike pattern requires the assumption of hotspots in recombination. Using extensive simulations that generate data matched to the Daly et al. data set in (a) the method of ascertainment of single-nucleotide polymorphisms, (b) the heterozygosity of ascertained markers, (c) the number of block boundaries, and (d) the diversity of haplotypes within blocks, we show that the patterns found in the Daly et al. data are not consistent with the assumption of uniform recombination in a population of constant size but are consistent either with the presence of hotspots in a population of constant size or with the absence of hotspots if there was a period of rapid population growth. We further show that estimates of local recombination rate can distinguish between population growth and hotspots as the primary cause of a blocklike pattern. Estimates of local recombination rates for the Daly et al. data do not indicate the presence of recombination hotspots.     

Bayesian Inference of Shared Recombination Hotspots Between Humans and Chimpanzees

Recombination generates variation and facilitates evolution. Recombination (or lack thereof) also contributes to human genetic disease. Methods for mapping genes influencing complex genetic diseases via association rely on linkage disequilibrium (LD) in human populations, which is influenced by rates of recombination across the genome. Comparative population genomic analyses of recombination using related primate species can identify factors influencing rates of recombination in humans. Such studies can indicate how variable hotspots for recombination may be both among individuals (or populations) and over evolutionary timescales. Previous studies have suggested that locations of recombination hotspots are not conserved between humans and chimpanzees. We made use of the data sets from recent resequencing projects and applied a Bayesian method for identifying hotspots and estimating recombination rates. We also reanalyzed SNP data sets for regions with known hotspots in humans using samples from the human and chimpanzee. The Bayes factors (BF) of shared recombination hotspots between human and chimpanzee across regions were obtained. Based on the analysis of the aligned regions of human chromosome 21, locations where the two species show evidence of shared recombination hotspots (with high BFs) were identified. Interestingly, previous comparative studies of human and chimpanzee that focused on the known human recombination hotspots within the β-globin and HLA regions did not find overlapping of hotspots. Our results show high BFs of shared hotspots at locations within both regions, and the estimated locations of shared hotspots overlap with the locations of human recombination hotspots obtained from sperm-typing studies.     

Demography,recombination hotspot intensity,and the block structure of linkage disequilibrium

BACKGROUND: Effective gene mapping based on genetic association data will require detailed knowledge of patterns of linkage disequilibrium (LD) in human populations. It has been recently suggested that linkage disequilibrium in humans may be organized in a block-like structure, with islands of high LD separated by regions of rapid breakdown of LD due to recombination hotspots. The experimental data to date, however, are limited, and fundamental questions remain about the implications of recombination rate heterogeneity. Here, we use computer simulations to evaluate how such heterogeneity influences patterns of LD, and we develop formal criteria to assess whether the patterns are functionally block like in the context of association mapping.RESULTS: Our analyses suggest that, even in models of extreme recombination rate heterogeneity, some human populations will have a functionally block-like structure to the pattern of LD, but others will not, depending on their precise demographic histories. In fact, for many models, we find that, following an LD-generating event, populations may move through discrete phases that can be functionally described as pre-block, block, and post-block. An analysis of observed and expected patterns of LD surrounding hotspots within the MHC Class II region confirms these theoretical expectations.CONCLUSIONS: Even if highly punctuated patterns of recombination are the rule, patterns of LD are still likely to show differences among populations and among genomic regions that are of practical importance in the design of genetic association studies. The notion that the average extent of LD is a useful concept for the design of association studies must be abandoned in light of the experimental and theoretical evidence.     

Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data

We introduce a new statistical model for patterns of linkage disequilibrium (LD) among multiple SNPs in a population sample. The model overcomes limitations of existing approaches to understanding, summarizing, and interpreting LD by (i) relating patterns of LD directly to the underlying recombination process; (ii) considering all loci simultaneously, rather than pairwise; (iii) avoiding the assumption that LD necessarily has a "block-like" structure; and (iv) being computationally tractable for huge genomic regions (up to complete chromosomes). We examine in detail one natural application of the model: estimation of underlying recombination rates from population data. Using simulation, we show that in the case where recombination is assumed constant across the region of interest, recombination rate estimates based on our model are competitive with the very best of current available methods. More importantly, we demonstrate, on real and simulated data, the potential of the model to help identify and quantify fine-scale variation in recombination rate from population data. We also outline how the model could be useful in other contexts, such as in the development of more efficient haplotype-based methods for LD mapping.     

Lower-than-expected linkage disequilibrium between tightly linked markers in humans suggests a role for gene conversion

Understanding the pattern of linkage disequilibrium (LD) in the human genome is important both for successful implementation of disease-gene mapping approaches and for inferences about human demographic histories. Previous studies have examined LD between loci within single genes or confined genomic regions, which may not be representative of the genome; between loci separated by large distances, where little LD is seen; or in population groups that differ from one study to the next. We measured LD in a large set of locus pairs distributed throughout the genome, with loci within each pair separated by short distances (average 124 bp). Given current models of the history of the human population, nearly all pairs of loci at such short distances would be expected to show complete LD as a consequence of lack of recombination in the short interval. Contrary to this expectation, a significant fraction of pairs showed incomplete LD. A standard model of recombination applied to these data leads to an estimate of effective human population size of 110,000. This estimate is an order of magnitude higher than most estimates based on nucleotide diversity. The most likely explanation of this discrepancy is that gene conversion increases the apparent rate of recombination between nearby loci.     

Mapping genes for common diseases: the case for genetic (LD) maps

We examine the current effort to develop a haplotype map of the human genome and suggest an alternative approach which represents linkage disequilibrium patterns in the form of a metric LD map. LD maps have some of the useful properties of genetic linkage maps but have a much higher resolution which is optimal for SNP-based association mapping of common diseases. The studies that have been undertaken to date suggest that LD and recombination maps show some close similarities because of abundant, narrow, recombination hot spots. These hot spots are co-localised in all populations but, unlike linkage maps, LD maps differ in scale for different populations because of differences in population history. The prospects for developing optimized panels of SNPs and the use of linkage disequilibrium maps in disease gene localisation are assessed in the light of recent evidence.     

Linkage Disequilibrium Decay and Past Population History in the Human Genome

The fluctuation of population size has not been well studied in the previous studies of theoretical linkage disequilibrium (LD) expectation. In this study, an improved theoretical prediction of LD decay was derived to account for the effects of changes in effective population sizes. The equation was used to estimate effective population size (N_e) assuming a constant N_e and LD at equilibrium, and these N_e estimates implied the past changes of N_e for a certain number of generations until equilibrium, which differed based on recombination rate. As the influence of recent population history on the N_e estimates is larger than old population history, recent changes in population size can be inferred more accurately than old changes. The theoretical predictions based on this improved expression showed accurate agreement with the simulated values. When applied to human genome data, the detailed recent history of human populations was obtained. The inferred past population history of each population showed good correspondence with historical studies. Specifically, four populations (three African ancestries and one Mexican ancestry) showed population growth that was significantly less than that of other populations, and two populations originated from China showed prominent exponential growth. During the examination of overall LD decay in the human genome, a selection pressure on chromosome 14, the gephyrin gene, was observed in all populations.     

Patterns of linkage disequilibrium in mitochondrial DNA of 16 ruminant populations

Mitochondrial DNA (mtDNA) is a widely employed molecular tool in phylogeography, in the inference of human evolutionary history, in dating the domestication of livestock and in forensic science. In humans and other vertebrates the popularity of mtDNA can be partially attributed to an assumption of strict maternal inheritance, such that there is no recombination between mitochondrial lineages. The recent demonstration that linkage disequilibrium (LD) declines as a function of distance between polymorphic sites in hominid mitochondrial genomes has been interpreted as evidence of recombination between mtDNA haplotypes, and hence nonclonal inheritance. However, critics of mtDNA recombination have suggested that this association is an artefact of an inappropriate measure of LD or of sequencing error, and subsequent studies of other populations have failed to replicate the initial finding. Here we report the analysis of 16 ruminant populations and present evidence that LD significantly declines with distance in five of them. A meta-analysis of the data indicates a nonsignificant trend of LD declining with distance. Most of the earlier criticisms of patterns between LD and distance in hominid mtDNA are not applicable to this data set. Our results suggest that either ruminant mtDNA is not strictly clonal or that compensatory selection has influenced patterns of variation at closely linked sites within the mitochondrial control region. The potential impact of these processes should be considered when using mtDNA as a tool in vertebrate population genetic, phylogenetic and forensic studies.     

A combination of cis and trans control can solve the hotspot conversion paradox

There is growing evidence that in a variety of organisms the majority of meiotic recombination events occur at a relatively small fraction of loci, known as recombination hotspots. If hotspot activity results from the DNA sequence at or near the hotspot itself (in cis), these hotspots are expected to be rapidly lost due to biased gene conversion, unless there is strong selection in favor of the hotspot itself. This phenomenon makes it very difficult to maintain existing hotspots and even more difficult for new hotspots to evolve; it has therefore come to be known as the "hotspot conversion paradox." I develop an analytical framework for exploring the evolution of recombination hotspots under the forces of selection, mutation, and conversion. I derive the general conditions under which cis- and trans-controlled hotspots can be maintained, as well as those under which new hotspots controlled by both a cis and a trans locus can invade a population. I show that the conditions for maintenance of and invasion by trans- or cis-plus-trans-controlled hotspots are broader than for those controlled entirely in cis. Finally, I show that a combination of cis and trans control may allow for long-lived polymorphisms in hotspot activity, the patterns of which may explain some recently observed features of recombination hotspots.     

Equilibrium processes cannot explain high levels of short- and medium-range linkage disequilibrium in the domesticated grass Sorghum bicolor

Patterns of linkage disequilibrium (LD) are of interest because they provide evidence of both equilibrium (e.g., mating system or long-term population structure) and nonequilibrium (e.g., demographic or selective) processes, as well as because of their importance in strategies for identifying the genetic basis of complex phenotypes. We report patterns of short and medium range (up to 100 kb) LD in six unlinked genomic regions in the partially selfing domesticated grass, Sorghum bicolor. The extent of allelic associations in S. bicolor, as assessed by pairwise measures of LD, is higher than in maize but lower than in Arabidopsis, in qualitative agreement with expectations based on mating system. Quantitative analyses of the population recombination parameter, rho, however, based on empirical estimates of rates of recombination, mutation, and self-pollination, show that LD is more extensive than expected under a neutral equilibrium model. The disparity between rho and the population mutation parameter, , is similar to that observed in other species whose population history appears to be complex. From a practical standpoint, these results suggest that S. bicolor is well suited for association studies using reasonable numbers of markers, since LD typically extends at least several kilobases but has largely decayed by 15 kb.     

Linkage disequilibrium and inference of ancestral recombination in 538 single-nucleotide polymorphism clusters across the human genome

The prospect of using linkage disequilibrium (LD) for fine-scale mapping in humans has attracted considerable attention, and, during the validation of a set of single-nucleotide polymorphisms (SNPs) for linkage analysis, a set of data for 4,833 SNPs in 538 clusters was produced that provides a rich picture of local attributes of LD across the genome. LD estimates may be biased depending on the means by which SNPs are first identified, and a particular problem of ascertainment bias arises when SNPs identified in small heterogeneous panels are subsequently typed in larger population samples. Understanding and correcting ascertainment bias is essential for a useful quantitative assessment of the landscape of LD across the human genome. Heterogeneity in the population recombination rate, rho=4Nr, along the genome reflects how variable the density of markers will have to be for optimal coverage. We find that ascertainment-corrected rho varies along the genome by more than two orders of magnitude, implying great differences in the recombinational history of different portions of our genome. The distribution of rho is unimodal, and we show that this is compatible with a wide range of mixtures of hotspots in a background of variable recombination rate. Although rho is significantly correlated across the three population samples, some regions of the genome exhibit population-specific spikes or troughs in rho that are too large to be explained by sampling. This result is consistent with differences in the genealogical depth of local genomic regions, a finding that has direct bearing on the design and utility of LD mapping and on the National Institutes of Health HapMap project.     

Live hot, die young: transmission distortion in recombination hotspots

There is strong evidence that hotspots of meiotic recombination in humans are transient features of the genome. For example, hotspot locations are not shared between human and chimpanzee. Biased gene conversion in favor of alleles that locally disrupt hotspots is a possible explanation of the short lifespan of hotspots. We investigate the implications of such a bias on human hotspots and their evolution. Our results demonstrate that gene conversion bias is a sufficiently strong force to produce the observed lack of sharing of intense hotspots between species, although sharing may be much more common for weaker hotspots. We investigate models of how hotspots arise, and find that only models in which hotspot alleles do not initially experience drive are consistent with observations of rather hot hotspots in the human genome. Mutations acting against drive cannot successfully introduce such hotspots into the population, even if there is direct selection for higher recombination rates, such as to ensure correct segregation during meiosis. We explore the impact of hotspot alleles on patterns of haplotype variation, and show that such alleles mask their presence in population genetic data, making them difficult to detect.     

Linkage disequilibrium patterns across a recombination gradient in African Drosophila melanogaster

Previous multilocus surveys of nucleotide polymorphism have documented a genome-wide excess of intralocus linkage disequilibrium (LD) in Drosophila melanogaster and D. simulans relative to expectations based on estimated mutation and recombination rates and observed levels of diversity. These studies examined patterns of variation from predominantly non-African populations that are thought to have recently expanded their ranges from central Africa. Here, we analyze polymorphism data from a Zimbabwean population of D. melanogaster, which is likely to be closer to the standard population model assumptions of a large population with constant size. Unlike previous studies, we find that levels of LD are roughly compatible with expectations based on estimated rates of crossing over. Further, a detailed examination of genes in different recombination environments suggests that markers near the telomere of the X chromosome show considerably less linkage disequilibrium than predicted by rates of crossing over, suggesting appreciable levels of exchange due to gene conversion. Assuming that these populations are near mutation-drift equilibrium, our results are most consistent with a model that posits heterogeneity in levels of exchange due to gene conversion across the X chromosome, with gene conversion being a minor determinant of LD levels in regions of high crossing over. Alternatively, if levels of exchange due to gene conversion are not negligible in regions of high crossing over, our results suggest a marked departure from mutation-drift equilibrium (i.e., toward an excess of LD) in this Zimbabwean population. Our results also have implications for the dynamics of weakly selected mutations in regions of reduced crossing over.     

Recombination hotspots as a point process

The variation of the recombination rate along chromosomal DNA is one of the important determinants of the patterns of linkage disequilibrium. A number of inferential methods have been developed which estimate the recombination rate and its variation from population genetic data. The majority of these methods are based on modelling the genealogical process underlying a sample of DNA sequences and thus explicitly include a model of the demographic process. Here we propose a different inferential procedure based on a previously introduced framework where recombination is modelled as a point process along a DNA sequence. The approach infers regions containing putative hotspots based on the inferred minimum number of recombination events; it thus depends only indirectly on the underlying population demography. A Poisson point process model with local rates is then used to infer patterns of recombination rate estimation in a fully Bayesian framework. We illustrate this new approach by applying it to several population genetic datasets, including a region with an experimentally confirmed recombination hotspot.     

Assessing the performance of the haplotype block model of linkage disequilibrium

Several recent studies have suggested that linkage disequilibrium (LD) in the human genome has a fundamentally "blocklike" structure. However, thus far there has been little formal assessment of how well the haplotype block model captures the underlying structure of LD. Here we propose quantitative criteria for assessing how blocklike LD is and apply these criteria to both real and simulated data. Analyses of several large data sets indicate that real data show a partial fit to the haplotype block model; some regions conform quite well, whereas others do not. Some improvement could be obtained by genotyping higher marker densities but not by increasing the number of samples. Nonetheless, although the real data are only moderately blocklike, our simulations indicate that, under a model of uniform recombination, the structure of LD would actually fit the block model much less well. Simulations of a model in which much of the recombination occurs in narrow hotspots provide a much better fit to the observed patterns of LD, suggesting that there is extensive fine-scale variation in recombination rates across the human genome.     

SNP microarray analysis for genome-wide detection of crossover regions

There is a great deal of interest in understanding the non-random distribution of recombination events over the human genome, because it has important implications for using linkage disequilibrium (LD) to identify human disease genes. So far, only a few recombination hotspots in the human genome have been characterised and the identification of new crossover hotspots will contribute to a better understanding of the mechanisms that govern their formation and distribution. This study shows that high-density single nucleotide polymorphism (SNP) arrays, together with the presented analysis method, are an appropriate tool for generating a whole-genome recombination pattern and for detecting new crossover regions with enhanced recombination frequency. Based on the genotype data of 16 members of a Caucasian three-generation family, we identified 825 crossover regions. The average recombination frequency of females and males was 0.77 and 0.56 cM/Mb, respectively. We detected 24 crossover regions showing elevated recombination activity, which comprised known hotspots, like the MHC II region, confirming the non-random distribution of recombination events along the genome. Interestingly, 29.2% of the identified crossover hotspot regions overlapped with regions flanked by segmental duplications published by Bailey et al. (Science 297:1003–1007, 2002) suggesting that segmental duplications and crossover hotspot regions are mechanistically linked. By extrapolating the results of the present study, we conclude that it might be feasible, at least in part, to estimate to what extent the block-like pattern of LD exactly relies on the genome-wide crossover pattern using the next generation high-density SNP microarrays.Electronic Supplementary Material Supplementary material is available for this article at     

A fine-scale linkage-disequilibrium measure based on length of haplotype sharing

High-throughput genotyping technologies for SNPs have enabled the recent completion of the International HapMap Project (phase I), which has stimulated much interest in studying genomewide linkage-disequilibrium (LD) patterns. Conventional LD measures, such as D' and r(2), are two-point measurements, and their relationship with physical distance is highly noisy. We propose a new LD measure, Delta , defined in terms of the correlation coefficient for shared haplotype lengths around two loci, thereby borrowing information from multiple loci. A U-statistic-based estimator of Delta , which takes into consideration the dependence structure of the observed data, is developed and compared with an estimator based on the usual empirical correlation coefficient. Furthermore, we propose methods for inferring LD-decay rates and recombination hotspots on the basis of Delta . The results from coalescent-simulation studies and analysis of HapMap SNP data demonstrate that the proposed estimators of Delta are superior to the two most popular conventional LD measures, in terms of their close relationship with physical distance and recombination rate, their small variability, and their strong robustness to marker-allele frequencies. These merits may offer new opportunities for mapping complex disease genes and for investigating recombination mechanisms on the basis of better-quantified LD.     

Disentangling linkage disequilibrium and linkage from dense single-nucleotide polymorphism trio data

Parent-offspring trios are widely collected for disease gene-mapping studies and are being extensively genotyped as part of the International HapMap Project. With dense maps of markers on trios, the effects of LD and linkage can be separated, allowing estimation of recombination rates in a model-free setting. Here we define a model-free multipoint method on the basis of dense sequence polymorphism data from parent-offspring trios to estimate intermarker recombination rates. We use simulations to show that this method has up to 92% power to detect recombination hotspots of intensity 25 times background over a region of size 10 kb typed at density 1 marker per 2.5 kb and almost 100% power to detect large hotspots of intensity >125 times background over regions of size 10 kb typed with just 1 marker per 5 kb (alpha = 0.05). We found strong agreement at megabase scales between estimates from our method applied to HapMap trio data and estimates from the genetic map. At finer scales, using Centre d'Etude du Polymorphisme Humain (CEPH) pedigree data across a 10-Mb region of chromosome 20, a comparison of population recombination rate estimates obtained from our method with estimates obtained using a coalescent-based approximate-likelihood method implemented in PHASE 2.0 shows detection of the same coldspots and most hotspots: The Spearman rank correlation between the estimates from our method and those from PHASE is 0.58 (p < 2.2(-16)).