Age-dependent recombination rates in human pedigrees

In humans, chromosome-number abnormalities have been associated with altered recombination and increased maternal age. Therefore, age-related effects on recombination are of major importance, especially in relation to the mechanisms involved in human trisomies. Here, we examine the relationship between maternal age and recombination rate in humans. We localized crossovers at high resolution by using over 600,000 markers genotyped in a panel of 69 French-Canadian pedigrees, revealing recombination events in 195 maternal meioses. Overall, we observed the general patterns of variation in fine-scale recombination rates previously reported in humans. However, we make the first observation of a significant decrease in recombination rates with advancing maternal age in humans, likely driven by chromosome-specific effects. The effect appears to be localized in the middle section of chromosomal arms and near subtelomeric regions. We postulate that, for some chromosomes, protection against non-disjunction provided by recombination becomes less efficient with advancing maternal age, which can be partly responsible for the higher rates of aneuploidy in older women. We propose a model that reconciles our findings with reported associations between maternal age and recombination in cases of trisomies.     

A neutral explanation for the correlation of diversity with recombination rates in humans

One of the most striking findings to emerge from the study of genomic patterns of variation is that regions with lower recombination rates tend to have lower levels of intraspecific diversity but not of interspecies divergence. This uncoupling of variation within and between species has been widely interpreted as evidence that natural selection shapes patterns of genetic variability genomewide. We revisited the relationship between diversity, divergence, and recombination in humans, using data from closely related species and better estimates of recombination rates than previously available. We show that regions that experience less recombination have reduced divergence to chimpanzee and to baboon, as well as lower levels of diversity. This observation suggests that mutation and recombination are associated processes in humans, so that the positive correlation between diversity and recombination may have a purely neutral explanation. Consistent with this hypothesis, diversity levels no longer increase significantly with recombination rates after correction for divergence to chimpanzee.     

Similarity in recombination rate estimates highly correlates with genetic differentiation in humans

Recombination varies greatly among species, as illustrated by the poor conservation of the recombination landscape between humans and chimpanzees. Thus, shorter evolutionary time frames are needed to understand the evolution of recombination. Here, we analyze its recent evolution in humans. We calculated the recombination rates between adjacent pairs of 636,933 common single-nucleotide polymorphism loci in 28 worldwide human populations and analyzed them in relation to genetic distances between populations. We found a strong and highly significant correlation between similarity in the recombination rates corrected for effective population size and genetic differentiation between populations. This correlation is observed at the genome-wide level, but also for each chromosome and when genetic distances and recombination similarities are calculated independently from different parts of the genome. Moreover, and more relevant, this relationship is robustly maintained when considering presence/absence of recombination hotspots. Simulations show that this correlation cannot be explained by biases in the inference of recombination rates caused by haplotype sharing among similar populations. This result indicates a rapid pace of evolution of recombination, within the time span of differentiation of modern humans.     

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.     

Hitchhiking and recombination in birds: evidence from Mhc-linked and unlinked loci in Red-winged Blackbirds (Agelaius phoeniceus)

Hitchhiking phenomena and genetic recombination have important consequences for a variety of fields for which birds are model species, yet we know virtually nothing about naturally occurring rates of recombination or the extent of linkage disequilibrium in birds. We took advantage of a previously sequenced cosmid clone from Red-winged Blackbirds (Agelaius phoeniceus) bearing a highly polymorphic Mhc class II gene, Agph-DABI, to measure the extent of linkage disequilibrium across approximately 40 kb of genomic DNA and to determine whether non-coding nucleotide diversity was elevated as a result of physical proximity to a target of balancing selection. Application of coalescent theory predicts that the hitchhiking effect is enhanced by the larger effective population size of blackbirds compared with humans, despite the presumably higher rates of recombination in birds. We surveyed sequence polymorphism at three Mhc-linked loci occurring 1.5-40 kb away from Agph-DAB1 and found that nucleotide diversity was indistinguishable from that found at three presumably unlinked, non-coding introns (beta-actin intron 2, beta-fibrinogen intron 7 and rhodopsin intron 2). Linkage disequilibrium as measured by Lewontin's D' was found only across a few hundred base pairs within any given locus, and was not detectable among any Mhc-linked loci. Estimated rates of the per site recombination rate p derived from three different analytical methods suggest that the amounts of recombination in blackbirds are up to two orders of magnitude higher than in humans, a discrepancy that cannot be explained entirely by the higher effective population size of blackbirds relative to humans. In addition, the ratio of the number of estimated recombination events per mutation frequently exceeds 1, as in Drosophila, again much higher than estimates in humans. Although the confidence limits of the blackbird estimates themselves span an order of magnitude, these data suggest that in blackbirds the hitchhiking effect for this region is negligible and may imply that the per site per individual recombination rate is high, resembling those of Drosophila more than those of humans.     

Recombination rate variation in closely related species

Despite their importance to successful meiosis and various evolutionary processes, meiotic recombination rates sometimes vary within species or between closely related species. For example, humans and chimpanzees share virtually no recombination hotspot locations in the surveyed portion of the genomes. However, conservation of recombination rates between closely related species has also been documented, raising an apparent contradiction. Here, we evaluate how and why conflicting patterns of recombination rate conservation and divergence may be observed, with particular emphasis on features that affect recombination, and the scale and method with which recombination is surveyed. Additionally, we review recent studies identifying features influencing fine-scale and broad-scale recombination patterns and informing how quickly recombination rates evolve, how changes in recombination impact selection and evolution in natural populations, and more broadly, which forces influence genome evolution.     

Can a genome change its (hot)spots?

A new study by Jeffreys et al. shows that the rate of recombination in recombination hotspots in humans is not constant through time. This observation adds weight to the idea that hotspots are transient on evolutionary timescales. However, questions remain as to what controls their evolution and how these rapid changes influence broad-scale rates of recombination.     

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.     

Absence of the TAP2 human recombination hotspot in chimpanzees

Recent experiments using sperm typing have demonstrated that, in several regions of the human genome, recombination does not occur uniformly but instead is concentrated in “hotspots” of 1–2 kb. Moreover, the crossover asymmetry observed in a subset of these has led to the suggestion that hotspots may be short-lived on an evolutionary time scale. To test this possibility, we focused on a region known to contain a recombination hotspot in humans, TAP2, and asked whether chimpanzees, the closest living evolutionary relatives of humans, harbor a hotspot in a similar location. Specifically, we used a new statistical approach to estimate recombination rate variation from patterns of linkage disequilibrium in a sample of 24 western chimpanzees (Pan troglodytes verus). This method has been shown to produce reliable results on simulated data and on human data from the TAP2 region. Strikingly, however, it finds very little support for recombination rate variation at TAP2 in the western chimpanzee data. Moreover, simulations suggest that there should be stronger support if there were a hotspot similar to the one characterized in humans. Thus, it appears that the human TAP2 recombination hotspot is not shared by western chimpanzees. These findings demonstrate that fine-scale recombination rates can change between very closely related species and raise the possibility that rates differ among human populations, with important implications for linkage-disequilibrium based association studies.     

Microsatellite variation and recombination rate in the human genome

Background (purifying) selection on deleterious mutations is expected to remove linked neutral mutations from a population, resulting in a positive correlation between recombination rate and levels of neutral genetic variation, even for markers with high mutation rates. We tested this prediction of the background selection model by comparing recombination rate and levels of microsatellite polymorphism in humans. Published data for 28 unrelated Europeans were used to estimate microsatellite polymorphism (number of alleles, heterozygosity, and variance in allele size) for loci throughout the genome. Recombination rates were estimated from comparisons of genetic and physical maps. First, we analyzed 61 loci from chromosome 22, using the complete sequence of this chromosome to provide exact physical locations. These 61 microsatellites showed no correlation between levels of variation and recombination rate. We then used radiation-hybrid and cytogenetic maps to calculate recombination rates throughout the genome. Recombination rates varied by more than one order of magnitude, and most chromosomes showed significant suppression of recombination near the centromere. Genome-wide analyses provided no evidence for a strong positive correlation between recombination rate and polymorphism, although analyses of loci with at least 20 repeats suggested a weak positive correlation. Comparisons of microsatellites in lowest-recombination and highest-recombination regions also revealed no difference in levels of polymorphism. Together, these results indicate that background selection is not a major determinant of microsatellite variation in humans.     

Application of coalescent methods to reveal fine-scale rate variation and recombination hotspots

There has been considerable recent interest in understanding the way in which recombination rates vary over small physical distances, and the extent of recombination hotspots, in various genomes. Here we adapt, apply, and assess the power of recently developed coalescent-based approaches to estimating recombination rates from sequence polymorphism data. We apply full-likelihood estimation to study rate variation in and around a well-characterized recombination hotspot in humans, in the beta-globin gene cluster, and show that it provides similar estimates, consistent with those from sperm studies, from two populations deliberately chosen to have different demographic and selectional histories. We also demonstrate how approximate-likelihood methods can be used to detect local recombination hotspots from genomic-scale SNP data. In a simulation study based on 80 100-kb regions, these methods detect 43 out of 60 hotspots (ranging from 1 to 2 kb in size), with only two false positives out of 2000 subregions that were tested for the presence of a hotspot. Our study suggests that new computational tools for sophisticated analysis of population diversity data are valuable for hotspot detection and fine-scale mapping of local recombination rates.     

Estimating recombination rates from population-genetic data

Obtaining an accurate measure of how recombination rates vary across the genome has implications for understanding the molecular basis of recombination, its evolutionary significance and the distribution of linkage disequilibrium in natural populations. Although measuring the recombination rate is experimentally challenging, good estimates can be obtained by applying population-genetic methods to DNA sequences taken from natural populations. Statistical methods are now providing insights into the nature and scale of variation in the recombination rate, particularly in humans. Such knowledge will become increasingly important owing to the growing use of population-genetic methods in biomedical research.     

Insights into recombination from patterns of linkage disequilibrium in humans

An ability to predict levels of linkage disequilibrium (LD) between linked markers would facilitate the design of association studies and help to distinguish between evolutionary models. Unfortunately, levels of LD depend crucially on the rate of recombination, a parameter that is difficult to measure. In humans, rates of genetic exchange between markers megabases apart can be estimated from a comparison of genetic and physical maps; these large-scale estimates can then be interpolated to predict LD at smaller ("local") scales. However, if there is extensive small-scale heterogeneity, as has been recently proposed, local rates of recombination could differ substantially from those averaged over much larger distances. We test this hypothesis by estimating local recombination rates indirectly from patterns of LD in 84 genomic regions surveyed by the SeattleSNPs project in a sample of individuals of European descent and of African-Americans. We find that LD-based estimates are significantly positively correlated with map-based estimates. This implies that large-scale, average rates are informative about local rates of recombination. Conversely, although LD-based estimates are based on a number of simplifying assumptions, it appears that they capture considerable information about the underlying recombination rate or at least about the ordering of regions by recombination rate. Using LD-based estimators, we also find evidence for homologous gene conversion in patterns of polymorphism. However, as we demonstrate by simulation, inferences about gene conversion are unreliable, even with extensive data from homogeneous regions of the genome, and are confounded by genotyping error.     

Variation in recombination rate across the genome: evidence and implications

Recent data from humans and other species provide convincing evidence of variation in recombination rate in different genomic regions. Comparison of physical and genetic maps reveals variation on a scale of megabases, with substantial differences between sexes. Recombination is often suppressed near centromeres and elevated near telomeres, but neither of these observations is true for all chromosomes. In humans, patterns of linkage disequilibrium and experimental measures of recombination from sperm-typing reveal dramatic hotspots of recombination on a scale of kilobases. Genome-wide variation in the amount of crossing-over may be due to variation in the density of hotspots, the intensity of hotspots, or both. Theoretical models of selection and linkage predict that genetic variation will be reduced in regions of low recombination, and this prediction is supported by data from several species. Heterogeneity in rates of crossing-over provides both an opportunity and a challenge for identifying disease genes: as associations occur in blocks, genomic regions containing disease loci may be identified with relatively few markers, yet identifying the causal mutations is unlikely to be achieved through associations alone.     

Cytological Studies of Human Meiosis: Sex-Specific Differences in Recombination Originate at,or Prior to,Establishment of Double-Strand Breaks

Meiotic recombination is sexually dimorphic in most mammalian species, including humans, but the basis for the male:female differences remains unclear. In the present study, we used cytological methodology to directly compare recombination levels between human males and females, and to examine possible sex-specific differences in upstream events of double-strand break (DSB) formation and synaptic initiation. Specifically, we utilized the DNA mismatch repair protein MLH1 as a marker of recombination events, the RecA homologue RAD51 as a surrogate for DSBs, and the synaptonemal complex proteins SYCP3 and/or SYCP1 to examine synapsis between homologs. Consistent with linkage studies, genome-wide recombination levels were higher in females than in males, and the placement of exchanges varied between the sexes. Subsequent analyses of DSBs and synaptic initiation sites indicated similar male:female differences, providing strong evidence that sex-specific differences in recombination rates are established at or before the formation of meiotic DSBs. We then asked whether these differences might be linked to variation in the organization of the meiotic axis and/or axis-associated DNA and, indeed, we observed striking male:female differences in synaptonemal complex (SC) length and DNA loop size. Taken together, our observations suggest that sex specific differences in recombination in humans may derive from chromatin differences established prior to the onset of the recombination pathway.     

Multiple loci contribute to genome-wide recombination levels in male mice

Recent linkage-based studies in humans suggest the presence of loci that affect either genome-wide recombination rates, utilization of recombination hotspots, or both. We have been interested in utilizing cytological methodology to directly assess recombination in mammalian meiocytes and to identify recombination-associated loci. In the present report we summarize studies in which we combined a cytological assay of recombination in mouse pachytene spermatocytes with QTL analyses to identify loci that contribute to genome-wide levels of recombination in male meiosis. Specifically, we analyzed MLH1 foci, a marker of crossovers, in 194 F2 male mice derived from a subspecific cross between CAST/EiJ and C57BL/6J parental strains. We then used these data to uncover loci associated with individual variation in mean MLH1 values. We identified seven recombination-associated loci across the genome (on chromosomes 2, 3, 4, 14, 15, 17, and X), indicating that there are multiple recombination “setting” loci in mammalian male meiosis.     

Effects of recombination rate on human endogenous retrovirus fixation and persistence

Endogenous retroviruses (ERVs) result from germ line infections by exogenous retroviruses. They can proliferate within the genome of their host species until they are either inactivated by mutation or removed by recombinational deletion. ERVs belong to a diverse group of mobile genetic elements collectively termed transposable elements (TEs). Numerous studies have attempted to elucidate the factors determining the genomic distribution and persistence of TEs. Here we show that, within humans, gene density and not recombination rate correlates with fixation of endogenous retroviruses, whereas the local recombination rate determines their persistence in a full-length state. Recombination does not appear to influence fixation either via the ectopic exchange model or by indirect models based on the efficacy of selection. We propose a model linking rates of meiotic recombination to the probability of recombinational deletion to explain the effect of recombination rate on persistence. Chromosomes 19 and Y are exceptions, possessing more elements than other regions, and we suggest this is due to low gene density and elevated rates of human ERV integration in males for chromosome Y and segmental duplication for chromosome 19.     

The influence of recombination on human genetic diversity

In humans, the rate of recombination, as measured on the megabase scale, is positively associated with the level of genetic variation, as measured at the genic scale. Despite considerable debate, it is not clear whether these factors are causally linked or, if they are, whether this is driven by the repeated action of adaptive evolution or molecular processes such as double-strand break formation and mismatch repair. We introduce three innovations to the analysis of recombination and diversity: fine-scale genetic maps estimated from genotype experiments that identify recombination hotspots at the kilobase scale, analysis of an entire human chromosome, and the use of wavelet techniques to identify correlations acting at different scales. We show that recombination influences genetic diversity only at the level of recombination hotspots. Hotspots are also associated with local increases in GC content and the relative frequency of GC-increasing mutations but have no effect on substitution rates. Broad-scale association between recombination and diversity is explained through covariance of both factors with base composition. To our knowledge, these results are the first evidence of a direct and local influence of recombination hotspots on genetic variation and the fate of individual mutations. However, that hotspots have no influence on substitution rates suggests that they are too ephemeral on an evolutionary time scale to have a strong influence on broader scale patterns of base composition and long-term molecular evolution.     

Genome-wide variation in the human and fruitfly: a comparison

Average levels of nucleotide diversity are ten-fold lower in humans than in the fruitfly, Drosophila melanogaster. Despite this difference, apparently as a result of a lower population size, patterns of genomic diversity are strikingly similar in being correlated with local rates of recombination, and influenced by similar interactions between positive natural selection and recombination. Both species also show lower levels of variation on average in non-African compared to African populations, reflecting a similar evolutionary history and perhaps both natural selection and founder effects in new environments.     

Estimating ancestral population sizes and divergence times

This article presents a new method for jointly estimating species divergence times and ancestral population sizes. The method improves on previous ones by explicitly incorporating intragenic recombination, by utilizing orthologous sequence data from closely related species, and by using a maximum-likelihood framework. The latter allows for efficient use of the available information and provides a way of assessing how much confidence we should place in the estimates. I apply the method to recently collected intergenic sequence data from humans and the great apes. The results suggest that the human-chimpanzee ancestral population size was four to seven times larger than the current human effective population size and that the current human effective population size is slightly >10,000. These estimates are similar to previous ones, and they appear relatively insensitive to assumptions about the recombination rates or mutation rates across loci.