Fine-scale Recombination Rates Research Articles

The fine-scale recombination rate variation and associations with genomic features in a butterfly.

Recombination is a key molecular mechanism that has profound implications on both micro- and macroevolutionary processes. However, the determinants of recombination rate variation in holocentric organisms are poorly understood, in particular in Lepidoptera (moths and butterflies). The wood white butterfly (Leptidea sinapis) shows considerable intraspecific variation in chromosome numbers and is a suitable system for studying regional recombination rate variation and its potential molecular underpinnings. Here, we developed a large whole-genome resequencing data set from a population of wood whites to obtain high-resolution recombination maps using linkage disequilibrium information. The analyses revealed that larger chromosomes had a bimodal recombination landscape, potentially caused by interference between simultaneous chiasmata. The recombination rate was significantly lower in subtelomeric regions, with exceptions associated with segregating chromosome rearrangements, showing that fissions and fusions can have considerable effects on the recombination landscape. There was no association between the inferred recombination rate and base composition, supporting a limited influence of GC-biased gene conversion in butterflies. We found significant but variable associations between the recombination rate and the density of different classes of transposable elements, most notably a significant enrichment of short interspersed nucleotide elements in genomic regions with higher recombination rate. Finally, the analyses unveiled significant enrichment of genes involved in farnesyltranstransferase activity in recombination coldspots, potentially indicating that expression of transferases can inhibit formation of chiasmata during meiotic division. Our results provide novel information about recombination rate variation in holocentric organisms and have particular implications for forthcoming research in population genetics, molecular/genome evolution, and speciation.

Variation in fine-scale recombination rate in temperature-evolved Drosophila melanogaster populations in response to selection.

Meiotic recombination plays a critical evolutionary role in maintaining fitness in response to selective pressures due to changing environments. Variation in recombination rate has been observed amongst and between species and populations and within genomes across numerous taxa. Studies have demonstrated a link between changes in recombination rate and selection, but the extent to which fine-scale recombination rate varies between evolved populations during the evolutionary period in response to selection is under active research. Here, we utilize a set of 3 temperature-evolved Drosophila melanogaster populations that were shown to have diverged in several phenotypes, including recombination rate, based on the temperature regime in which they evolved. Using whole-genome sequencing data from these populations, we generated linkage disequilibrium-based fine-scale recombination maps for each population. With these maps, we compare recombination rates and patterns among the 3 populations and show that they have diverged at fine scales but are conserved at broader scales. We further demonstrate a correlation between recombination rates and genomic variation in the 3 populations. Lastly, we show variation in localized regions of enhanced recombination rates, termed warm spots, between the populations with these warm spots and associated genes overlapping areas previously shown to have diverged in the 3 populations due to selection. These data support the existence of recombination modifiers in these populations which are subject to selection during evolutionary change.

Recombination Rate Variation and Infrequent Sex Influence Genetic Diversity in Chlamydomonas reinhardtii.

Recombination confers a major evolutionary advantage by breaking up linkage disequilibrium between harmful and beneficial mutations, thereby facilitating selection. However, in species that are only periodically sexual, such as many microbial eukaryotes, the realized rate of recombination is also affected by the frequency of sex, meaning that infrequent sex can increase the effects of selection at linked sites despite high recombination rates. Despite this, the rate of sex of most facultatively sexual species is unknown. Here, we use genomewide patterns of linkage disequilibrium to infer fine-scale recombination rate variation in the genome of the facultatively sexual green alga Chlamydomonas reinhardtii. We observe recombination rate variation of up to two orders of magnitude and find evidence of recombination hotspots across the genome. Recombination rate is highest flanking genes, consistent with trends observed in other nonmammalian organisms, though intergenic recombination rates vary by intergenic tract length. We also find a positive relationship between nucleotide diversity and physical recombination rate, suggesting a widespread influence of selection at linked sites in the genome. Finally, we use estimates of the effective rate of recombination to calculate the rate of sex that occurs in natural populations, estimating a sexual cycle roughly every 840 generations. We argue that the relatively infrequent rate of sex and large effective population size creates a population genetic environment that increases the influence of selection on linked sites across the genome.

Inference and analysis of population-specific fine-scale recombination maps across 26 diverse human populations.

Fine-scale rates of meiotic recombination vary by orders of magnitude across the genome and differ between species and even populations. Studying cross-population differences has been stymied by the confounding effects of demographic history. To address this problem, we developed a demography-aware method to infer fine-scale recombination rates and applied it to 26 diverse human populations, inferring population-specific recombination maps. These maps recapitulate many aspects of the history of these populations including signatures of the trans-Atlantic slave trade and the Iberian colonization of the Americas. We also investigated modulators of the local recombination rate, finding further evidence that Polycomb group proteins and the trimethylation of H3K27 elevate recombination rates. Further differences in the recombination landscape across the genome and between populations are driven by variation in the gene that encodes the DNA binding protein PRDM9, and we quantify the weak effect of meiotic drive acting to remove its binding sites.

Exploration of fine-scale recombination rate variation in the domestic horse.

Total genetic map length and local recombination landscapes typically vary within and across populations. As a first step to understanding the recombination landscape in the domestic horse, we calculated population recombination rates and identified likely recombination hotspots using approximately 1.8 million SNP genotypes for 485 horses from 32 distinct breeds. The resulting breed-averaged recombination map spans 2.36 Gb and accounts for 2939.07 cM. Recombination hotspots occur once per 23.8 Mb on average and account for ∼9% of the physical map length. Regions with elevated recombination rates in the entire cohort were enriched for genes in pathways involving interaction with the environment: immune system processes (specifically, MHC class I and class II genes), responses to stimuli, and serotonin receptor pathways. We found significant correlations between differences in local recombination rates and population differentiation quantified by FST. Analysis of breed-specific maps revealed thousands of hotspot regions unique to particular breeds, as well as unique “coldspots,” regions where a particular breed showed below-average recombination, whereas all other breeds had evidence of a hotspot. Finally, we identified relative enrichment (P = 5.88 × 10−27) for the in silico–predicted recognition motif for equine PR/SET domain 9 (PRDM9) in recombination hotspots. These results indicate that selective pressures and PRDM9 function contribute to variation in recombination rates across the domestic horse genome.

Divergent Fine-Scale Recombination Landscapes between a Freshwater and Marine Population of Threespine Stickleback Fish.

Meiotic recombination is a highly conserved process that has profound effects on genome evolution. At a fine-scale, recombination rates can vary drastically across genomes, often localized into small recombination “hotspots” with highly elevated rates, surrounded by regions with little recombination. In most species studied, the location of hotspots within genomes is highly conserved across broad evolutionary timescales. The main exception to this pattern is in mammals, where hotspot location can evolve rapidly among closely related species and even among populations within a species. Hotspot position in mammals is controlled by the gene, Prdm9, whereas in species with conserved hotspots, a functional Prdm9 is typically absent. Due to a limited number of species where recombination rates have been estimated at a fine-scale, it remains unclear whether hotspot conservation is always associated with the absence of a functional Prdm9. Threespine stickleback fish (Gasterosteus aculeatus) are an excellent model to examine the evolution of recombination over short evolutionary timescales. Using a linkage disequilibrium-based approach, we found recombination rates indeed varied at a fine-scale across the genome, with many regions organized into narrow hotspots. Hotspots had highly divergent landscapes between stickleback populations, where only ∼15% of these hotspots were shared. Our results indicate that fine-scale recombination rates may be diverging between closely related populations of threespine stickleback fish. Interestingly, we found only a weak association of a PRDM9 binding motif within hotspots, which suggests that threespine stickleback fish may possess a novel mechanism for targeting recombination hotspots at a fine-scale.

The Recombination Landscape in Wild House Mice Inferred Using Population Genomic Data.

Characterizing variation in the rate of recombination across the genome is important for understanding several evolutionary processes. Previous analysis of the recombination landscape in laboratory mice has revealed that the different subspecies have different suites of recombination hotspots. It is unknown, however, whether hotspots identified in laboratory strains reflect the hotspot diversity of natural populations or whether broad-scale variation in the rate of recombination is conserved between subspecies. In this study, we constructed fine-scale recombination rate maps for a natural population of the Eastern house mouse, Mus musculus castaneus. We performed simulations to assess the accuracy of recombination rate inference in the presence of phase errors, and we used a novel approach to quantify phase error. The spatial distribution of recombination events is strongly positively correlated between our castaneus map, and a map constructed using inbred lines derived predominantly from M. m. domesticus. Recombination hotspots in wild castaneus show little overlap, however, with the locations of double-strand breaks in wild-derived house mouse strains. Finally, we also find that genetic diversity in M. m. castaneus is positively correlated with the rate of recombination, consistent with pervasive natural selection operating in the genome. Our study suggests that recombination rate variation is conserved at broad scales between house mouse subspecies, but it is not strongly conserved at fine scales.

Whole-genome patterns of linkage disequilibrium across flycatcher populations clarify the causes and consequences of fine-scale recombination rate variation in birds.

Recombination rate is heterogeneous across the genome of various species and so are genetic diversity and differentiation as a consequence of linked selection. However, we still lack a clear picture of the underlying mechanisms for regulating recombination. Here we estimated fine-scale population recombination rate based on the patterns of linkage disequilibrium across the genomes of multiple populations of two closely related flycatcher species (Ficedula albicollis and F. hypoleuca). This revealed an overall conservation of the recombination landscape between these species at the scale of 200kb, but we also identified differences in the local rate of recombination despite their recent divergence (<1 million years). Genetic diversity and differentiation were associated with recombination rate in a lineage-specific manner, indicating differences in the extent of linked selection between species. We detected 400-3,085 recombination hotspots per population. Location of hotspots was conserved between species, but the intensity of hotspot activity varied between species. Recombination hotspots were primarily associated with CpG islands (CGIs), regardless of whether CGIs were at promoter regions or away from genes. Recombination hotspots were also associated with specific transposable elements (TEs), but this association appears indirect due to shared preferences of the transposition machinery and the recombination machinery for accessible open chromatin regions. Our results suggest that CGIs are a major determinant of the localization of recombination hotspots, and we propose that both the distribution of TEs and fine-scale variation in recombination rate may be associated with the evolution of the epigenetic landscape.

Two-Locus Likelihoods Under Variable Population Size and Fine-Scale Recombination Rate Estimation.

Two-locus sampling probabilities have played a central role in devising an efficient composite-likelihood method for estimating fine-scale recombination rates. Due to mathematical and computational challenges, these sampling probabilities are typically computed under the unrealistic assumption of a constant population size, and simulation studies have shown that resulting recombination rate estimates can be severely biased in certain cases of historical population size changes. To alleviate this problem, we develop here new methods to compute the sampling probability for variable population size functions that are piecewise constant. Our main theoretical result, implemented in a new software package called LDpop, is a novel formula for the sampling probability that can be evaluated by numerically exponentiating a large but sparse matrix. This formula can handle moderate sample sizes ([Formula: see text]) and demographic size histories with a large number of epochs ([Formula: see text]). In addition, LDpop implements an approximate formula for the sampling probability that is reasonably accurate and scales to hundreds in sample size ([Formula: see text]). Finally, LDpop includes an importance sampler for the posterior distribution of two-locus genealogies, based on a new result for the optimal proposal distribution in the variable-size setting. Using our methods, we study how a sharp population bottleneck followed by rapid growth affects the correlation between partially linked sites. Then, through an extensive simulation study, we show that accounting for population size changes under such a demographic model leads to substantial improvements in fine-scale recombination rate estimation.

Trans-ancestral studies fine map the SLE-susceptibility locus TNFSF4.

We previously established an 80 kb haplotype upstream of TNFSF4 as a susceptibility locus in the autoimmune disease SLE. SLE-associated alleles at this locus are associated with inflammatory disorders, including atherosclerosis and ischaemic stroke. In Europeans, the TNFSF4 causal variants have remained elusive due to strong linkage disequilibrium exhibited by alleles spanning the region. Using a trans-ancestral approach to fine-map the locus, utilising 17,900 SLE and control subjects including Amerindian/Hispanics (1348 cases, 717 controls), African-Americans (AA) (1529, 2048) and better powered cohorts of Europeans and East Asians, we find strong association of risk alleles in all ethnicities; the AA association replicates in African-American Gullah (152,122). The best evidence of association comes from two adjacent markers: rs2205960-T (P = 1.71×10−34, OR = 1.43[1.26–1.60]) and rs1234317-T (P = 1.16×10−28, OR = 1.38[1.24–1.54]). Inference of fine-scale recombination rates for all populations tested finds the 80 kb risk and non-risk haplotypes in all except African-Americans. In this population the decay of recombination equates to an 11 kb risk haplotype, anchored in the 5′ region proximal to TNFSF4 and tagged by rs2205960-T after 1000 Genomes phase 1 (v3) imputation. Conditional regression analyses delineate the 5′ risk signal to rs2205960-T and the independent non-risk signal to rs1234314-C. Our case-only and SLE-control cohorts demonstrate robust association of rs2205960-T with autoantibody production. The rs2205960-T is predicted to form part of a decameric motif which binds NF-κBp65 with increased affinity compared to rs2205960-G. ChIP-seq data also indicate NF-κB interaction with the DNA sequence at this position in LCL cells. Our research suggests association of rs2205960-T with SLE across multiple groups and an independent non-risk signal at rs1234314-C. rs2205960-T is associated with autoantibody production and lymphopenia. Our data confirm a global signal at TNFSF4 and a role for the expressed product at multiple stages of lymphocyte dysregulation during SLE pathogenesis. We confirm the validity of trans-ancestral mapping in a complex trait.

Genome-Wide Fine-Scale Recombination Rate Variation in Drosophila melanogaster

Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features—including recombination rates, diversity, divergence, GC content, gene content, and sequence quality—is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and diversity.

Classical Genetics Meets Next-Generation Sequencing: Uncovering a Genome-Wide Recombination Map in Drosophila melanogaster

Classical Genetics Meets Next-Generation Sequencing: Uncovering a Genome-Wide Recombination Map in Drosophila melanogaster

Fine-Scale Population Recombination Rates, Hotspots, and Correlates of Recombination in the Medicago truncatula Genome

Recombination rates vary across the genome and in many species show significant relationships with several genomic features, including distance to the centromere, gene density, and GC content. Studies of fine-scale recombination rates have also revealed that in several species, there are recombination hotspots, that is, short regions with recombination rates 10–100 greater than those in surrounding regions. In this study, we analyzed whole-genome resequence data from 26 accessions of the model legume Medicago truncatula to gain insight into the genomic features that are related to high- and low-recombination rates and recombination hotspots at 1 kb scales. We found that high-recombination regions (1-kb windows among those in the highest 5% of the distribution) on all three chromosomes were significantly closer to the centromere, had higher gene density, and lower GC content than low-recombination windows. High-recombination windows are also significantly overrepresented among some gene functional categories—most strongly NB–ARC and LRR genes, both of which are important in plant defense against pathogens. Similar to high-recombination windows, recombination hotspots (1-kb windows with significantly higher recombination than the surrounding region) are significantly nearer to the centromere than nonhotspot windows. By contrast, we detected no difference in gene density or GC content between hotspot and nonhotspot windows. Using linear model wavelet analysis to examine the relationship between recombination and genomic features across multiple spatial scales, we find a significant negative correlation with distance to the centromere across scales up to 512 kb, whereas gene density and GC content show significantly positive and negative correlations, respectively, only up to 64 kb. Correlations between recombination and genomic features, particularly gene density and polymorphism, suggest that they are scale dependent and need to be assessed at scales relevant to the evolution of those features.

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.

The recombination landscape around forensic STRs: Accurate measurement of genetic distances between syntenic STR pairs using HapMap high density SNP data

Family studies can be used to measure the genetic distance between same-chromosome (syntenic) STRs in order to detect physical linkage or linkage disequilibrium. However, family studies are expensive and time consuming, in many cases uninformative, and lack a reliable means to infer the phase of the diplotypes obtained. HapMap provides a more comprehensive and fine-scale estimation of recombination rates using high density multi-point SNP data (average inter-SNP distance: 900 nucleotides). Data at this fine scale detects sub-kilobase genetic distances across the whole recombining human genome. We have used the most recent HapMap SNP data release 22 to measure and compare genetic distances, and by inference fine-scale recombination rates, between 29 syntenic STR pairs identified from 39 validated STRs currently available for forensic use. The 39 STRs comprise 23 core loci: SE33, Penta D & E, 13 CODIS and 7 non-CODIS European Standard Set STRs, plus supplementary STRs in the recently released Promega CS-7™ and Qiagen Investigator HDplex™ kits. Also included were D9S1120, a marker we developed for forensic use unique to chromosome 9, and the novel D6S1043 component STR of SinoFiler™ (Applied Biosystems). The data collated provides reliable estimates of recombination rates between each STR pair, that can then be placed into haplotype frequency calculators for short pedigrees with multiple meiotic inputs and which just requires the addition of allele frequencies. This allows all current STR sets or their combinations to be used in supplemented paternity analyses without the need for further adjustment for physical linkage. The detailed analysis of recombination rates made for autosomal forensic STRs was extended to the more than 50 X chromosome STRs established or in development for complex kinship analyses.

Genetic and Evolutionary Correlates of Fine-Scale Recombination Rate Variation in Drosophila persimilis

Recombination is fundamental to meiosis in many species and generates variation on which natural selection can act, yet fine-scale linkage maps are cumbersome to construct. We generated a fine-scale map of recombination rates across two major chromosomes in Drosophila persimilis using 181 SNP markers spanning two of five major chromosome arms. Using this map, we report significant fine-scale heterogeneity of local recombination rates. However, we also observed "recombinational neighborhoods," where adjacent intervals had similar recombination rates after excluding regions near the centromere and telomere. We further found significant positive associations of fine-scale recombination rate with repetitive element abundance and a 13-bp sequence motif known to associate with human recombination rates. We noted strong crossover interference extending 5-7Mb from the initial crossover event. Further, we observed that fine-scale recombination rates in D.persimilis are strongly correlated with those obtained from a comparable study of its sister species, D.pseudoobscura. We documented a significant relationship between recombination rates and intron nucleotide sequence diversity within species, but no relationship between recombination rate and intron divergence between species. These results are consistent with selection models (hitchhiking and background selection) rather than mutagenic recombination models for explaining the relationship of recombination with nucleotide diversity within species. Finally, we found significant correlations between recombination rate and GC content, supporting both GC-biased gene conversion (BGC) models and selection-driven codon bias models. Overall, this genome-enabled map of fine-scale recombination rates allowed us to confirm findings of broader-scale studies and identify multiple novel features that merit further investigation.

Fine-scale recombination rate differences between sexes, populations and individuals

Meiotic recombinations contribute to genetic diversity by yielding new combinations of alleles. Recently, high-resolution recombination maps were inferred from high-density single-nucleotide polymorphism (SNP) data using linkage disequilibrium (LD) patterns that capture historical recombination events. The use of these maps has been demonstrated by the identification of recombination hotspots and associated motifs, and the discovery that the PRDM9 gene affects the proportion of recombinations occurring at hotspots. However, these maps provide no information about individual or sex differences. Moreover, locus-specific demographic factors like natural selection can bias LD-based estimates of recombination rate. Existing genetic maps based on family data avoid these shortcomings, but their resolution is limited by relatively few meioses and a low density of markers. Here we used genome-wide SNP data from 15,257 parent-offspring pairs to construct the first recombination maps based on directly observed recombinations with a resolution that is effective down to 10 kilobases (kb). Comparing male and female maps reveals that about 15% of hotspots in one sex are specific to that sex. Although male recombinations result in more shuffling of exons within genes, female recombinations generate more new combinations of nearby genes. We discover novel associations between recombination characteristics of individuals and variants in the PRDM9 gene and we identify new recombination hotspots. Comparisons of our maps with two LD-based maps inferred from data of HapMap populations of Utah residents with ancestry from northern and western Europe (CEU) and Yoruba in Ibadan, Nigeria (YRI) reveal population differences previously masked by noise and map differences at regions previously described as targets of natural selection.

Genetic and evolutionary correlates of fine-scale recombination rate variation in Drosophila persimilis

Recombination is fundamental to meiosis in many species and generates variation on which natural selection can act, yet fine-scale linkage maps are cumbersome to construct. We generated a fine-scale map of recombination rates across two major chromosomes in Drosophila persimilis using 181 SNP markers spanning two of five major chromosome arms. Using this map, we report significant fine-scale heterogeneity of local recombination rates. However, we also observed “recombinational neighborhoods,” where adjacent intervals had similar recombination rates after excluding regions near the centromere and telomere. We further found significant positive associations of fine-scale recombination rate with repetitive element abundance and a 13-bp sequence motif known to associate with human recombination rates. We noted strong crossover interference extending 5–7 Mb from the initial crossover event. Further, we observed that fine-scale recombination rates in D. persimilis are strongly correlated with those obtained from a comparable study of its sister species, D. pseudoobscura. We documented a significant relationship between recombination rates and intron nucleotide sequence diversity within species, but no relationship between recombination rate and intron divergence between species. These results are consistent with selection models (hitchhiking and background selection) rather than mutagenic recombination models for explaining the relationship of recombination with nucleotide diversity within species. Finally, we found significant correlations between recombination rate and GC content, supporting both GC-biased gene conversion (BGC) models and selection-driven codon bias models. Overall, this genome-enabled map of fine-scale recombination rates allowed us to confirm findings of broader-scale studies and identify multiple novel features that merit further investigation.

Population genomic inference of recombination rates and hotspots

As more human genomic data become available, fine-scale recombination rate variation can be inferred on a genome-wide scale. Current statistical methods to infer recombination rates that can be applied to moderate, or large, genomic regions are limited to approximated likelihoods. Here, we develop a Bayesian full-likelihood method using Markov Chain Monte Carlo (MCMC) to estimate background recombination rates and hotspots. The probability model is inspired by the observed patterns of recombination at several genomic regions analyzed in sperm-typing studies. Posterior probabilities and Bayes factors of recombination hotspots along chromosomes are inferred. For moderate-size genomic regions (e.g., with <100 SNPs), the full-likelihood method is used. Larger regions are split into subintervals (typically each having between 20 and 50 markers). The likelihood is approximated based on the genealogies for each subinterval. The background recombination rates, hotspots, and parameters are evaluated by using a parallel computing approach and assuming shared parameters across the subintervals. Simulation analyses show that our method can accurately estimate the variation in recombination rates across genomic regions. In particular, clusters of hotspots can be distinguished even though weaker hotspots are present. The method is applied to SNP data from the HLA region, the MS32, and chromosome 19.

Bayesian inference of fine-scale recombination rates using population genomic data

Recently, several statistical methods for estimating fine-scale recombination rates using population samples have been developed. However, currently available methods that can be applied to large-scale data are limited to approximated likelihoods. Here, we developed a full-likelihood Markov chain Monte Carlo method for estimating recombination rate under a Bayesian framework. Genealogies underlying a sampling of chromosomes are effectively modelled by using marginal individual single nucleotide polymorphism genealogies related through an ancestral recombination graph. The method is compared with two existing composite-likelihood methods using simulated data.Simulation studies show that our method performs well for different simulation scenarios. The method is applied to two human population genetic variation datasets that have been studied by sperm typing. Our results are consistent with the estimates from sperm crossover analysis.