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

Approximate Bayesian computational methods to estimate the strength of divergent selection in population genomics models

Statistical estimation of parameters in large models of evolutionary processes is often too computationally inefficient to pursue using exact model likelihoods, even with single-nucleotide polymorphism (SNP) data, which offers a way to reduce the size of genetic data while retaining relevant information. Approximate Bayesian Computation (ABC) to perform statistical inference about parameters of large models takes the advantage of simulations to bypass direct evaluation of model likelihoods. We develop a mechanistic model to simulate forward-in-time divergent selection with variable migration rates, modes of reproduction (sexual, asexual), length and number of migration-selection cycles. We investigate the computational feasibility of ABC to perform statistical inference and study the quality of estimates on the position of loci under selection and the strength of selection. To expand the parameter space of positions under selection, we enhance the model by implementing an outlier scan on summarized observed data. We evaluate the usefulness of summary statistics well-known to capture the strength of selection, and assess their informativeness under divergent selection. We also evaluate the effect of genetic drift with respect to an idealized deterministic model with single-locus selection. We discuss the role of the recombination rate as a confounding factor in estimating the strength of divergent selection, and emphasize its importance in break down of linkage disequilibrium (LD). We answer the question for which part of the parameter space of the model we recover strong signal for estimating the selection, and determine whether population differentiation-based summary statistics or LD-based summary statistics perform well in estimating selection.

Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits

Recombination is a main source of genetic variability. However, the potential role of the variation generated by recombination in phenotypic traits, including diseases, remains unexplored because there is currently no method to infer chromosomal subpopulations based on recombination pattern differences. We developed recombClust, a method that uses SNP-phased data to detect differences in historic recombination in a chromosome population. We validated our method by performing simulations and by using real data to accurately predict the alleles of well-known recombination modifiers, including common inversions in Drosophila melanogaster and human, and the chromosomes under selective pressure at the lactase locus in humans. We then applied recombClust to the complex human 1q21.1 region, where nonallelic homologous recombination produces deleterious phenotypes. We discovered and validated the presence of two different recombination histories in these regions that significantly associated with the differential expression of ANKRD35 in whole blood and that were in high linkage with variants previously associated with hypertension. By detecting differences in historic recombination, our method opens a way to assess the influence of recombination variation in phenotypic traits.

Mapping Recombination Rate on the Autosomal Chromosomes Based on the Persistency of Linkage Disequilibrium Phase Among Autochthonous Beef Cattle Populations in Spain

In organisms with sexual reproduction, genetic diversity, and genome evolution are governed by meiotic recombination caused by crossing-over, which is known to vary within the genome. In this study, we propose a simple method to estimate the recombination rate that makes use of the persistency of linkage disequilibrium (LD) phase among closely related populations. The biological material comprised 171 triplets (sire/dam/offspring) from seven populations of autochthonous beef cattle in Spain (Asturiana de los Valles, Avileña-Negra Ibérica, Bruna dels Pirineus, Morucha, Pirenaica, Retinta, and Rubia Gallega), which were genotyped for 777,962 SNPs with the BovineHD BeadChip. After standard quality filtering, we reconstructed the haplotype phases in the parental individuals and calculated the LD by the correlation -r- between each pair of markers that had a genetic distance < 1 Mb. Subsequently, these correlations were used to calculate the persistency of LD phase between each pair of populations along the autosomal genome. Therefore, the distribution of the recombination rate along the genome can be inferred since the effect of the number of generations of divergence should be equivalent throughout the genome. In our study, the recombination rate was highest in the largest chromosomes and at the distal portion of the chromosomes. In addition, the persistency of LD phase was highly heterogeneous throughout the genome, with a ratio of 25.4 times between the estimates of the recombination rates from the genomic regions that had the highest (BTA18-7.1 Mb) and the lowest (BTA12-42.4 Mb) estimates. Finally, an overrepresentation enrichment analysis (ORA) showed differences in the enriched gene ontology (GO) terms between the genes located in the genomic regions with estimates of the recombination rate over (or below) the 95^th (or 5^th) percentile throughout the autosomal genome.

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 F _ST 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.

The Time Scale of Recombination Rate Evolution in Great Apes

We present three linkage-disequilibrium (LD)-based recombination maps generated using whole-genome sequence data from 10 Nigerian chimpanzees, 13 bonobos, and 15 western gorillas, collected as part of the Great Ape Genome Project (Prado-Martinez J, et al. 2013. Great ape genetic diversity and population history. Nature 499:471-475). We also identified species-specific recombination hotspots in each group using a modified LDhot framework, which greatly improves statistical power to detect hotspots at varying strengths. We show that fewer hotspots are shared among chimpanzee subspecies than within human populations, further narrowing the time scale of complete hotspot turnover. Further, using species-specific PRDM9 sequences to predict potential binding sites (PBS), we show higher predicted PRDM9 binding in recombination hotspots as compared to matched cold spot regions in multiple great ape species, including at least one chimpanzee subspecies. We found that correlations between broad-scale recombination rates decline more rapidly than nucleotide divergence between species. We also compared the skew of recombination rates at centromeres and telomeres between species and show a skew from chromosome means extending as far as 10-15 Mb from chromosome ends. Further, we examined broad-scale recombination rate changes near a translocation in gorillas and found minimal differences as compared to other great ape species perhaps because the coordinates relative to the chromosome ends were unaffected. Finally, on the basis of multiple linear regression analysis, we found that various correlates of recombination rate persist throughout the African great apes including repeats, diversity, and divergence. Our study is the first to analyze within- and between-species genome-wide recombination rate variation in several close relatives.

The 8p23 inversion polymorphism determines local recombination heterogeneity across human populations

For decades, chromosomal inversions have been regarded as fascinating evolutionary elements as they are expected to suppress recombination between chromosomes with opposite orientations, leading to the accumulation of genetic differences between the two configurations over time. Here, making use of publicly available population genotype data for the largest polymorphic inversion in the human genome (8p23-inv), we assessed whether this inhibitory effect of inversion rearrangements led to significant differences in the recombination landscape of two homologous DNA segments, with opposite orientation. Our analysis revealed that the accumulation of genetic differentiation is positively correlated with the variation in recombination profiles. The observed recombination dissimilarity between inversion types is consistent across all populations analyzed and surpasses the effects of geographic structure, suggesting that both structures (orientations) have been evolving independently over an extended period of time, despite being subjected to the very same demographic history. Aside this mainly independent evolution, we also identified a short segment (350 kb, <10% of the whole inversion) in the central region of the inversion where the genetic divergence between the two structural haplotypes is diminished. Although it is difficult to demonstrate it, this could be due to gene flow (possibly via double-crossing over events), which is consistent with the higher recombination rates surrounding this segment. This study demonstrates for the first time that chromosomal inversions influence the recombination landscape at a fine-scale and highlights the role of these rearrangements as drivers of genome evolution.

Population-specific common SNPs reflect demographic histories and highlight regions of genomic plasticity with functional relevance

BACKGROUND

Population differentiation is the result of demographic and evolutionary forces. Whole genome datasets from the 1000 Genomes Project (October 2012) provide an unbiased view of genetic variation across populations from Europe, Asia, Africa and the Americas. Common population-specific SNPs (MAF > 0.05) reflect a deep history and may have important consequences for health and wellbeing. Their interpretation is contextualised by currently available genome data.

RESULTS

The identification of common population-specific (CPS) variants (SNPs and SSV) is influenced by admixture and the sample size under investigation. Nine of the populations in the 1000 Genomes Project (2 African, 2 Asian (including a merged Chinese group) and 5 European) revealed that the African populations (LWK and YRI), followed by the Japanese (JPT) have the highest number of CPS SNPs, in concordance with their histories and given the populations studied. Using two methods, sliding 50-SNP and 5-kb windows, the CPS SNPs showed distinct clustering across large genome segments and little overlap of clusters between populations. iHS enrichment score and the population branch statistic (PBS) analyses suggest that selective sweeps are unlikely to account for the clustering and population specificity. Of interest is the association of clusters close to recombination hotspots. Functional analysis of genes associated with the CPS SNPs revealed over-representation of genes in pathways associated with neuronal development, including axonal guidance signalling and CREB signalling in neurones.

CONCLUSIONS

Common population-specific SNPs are non-randomly distributed throughout the genome and are significantly associated with recombination hotspots. Since the variant alleles of most CPS SNPs are the derived allele, they likely arose in the specific population after a split from a common ancestor. Their proximity to genes involved in specific pathways, including neuronal development, suggests evolutionary plasticity of selected genomic regions. Contrary to expectation, selective sweeps did not play a large role in the persistence of population-specific variation. This suggests a stochastic process towards population-specific variation which reflects demographic histories and may have some interesting implications for health and susceptibility to disease.

Similarity in recombination rate and linkage disequilibrium at CYP2C and CYP2D cytochrome P450 gene regions among Europeans indicates signs of selection and no advantage of using tagSNPs in population isolates

OBJECTIVE

Linkage disequilibrium (LD) and recombination rate variations are known to vary considerably between human genome regions and populations mostly because of the combined effects of mutation, recombination, and demographic history. Thus, the pattern of LD is a key issue to disentangle variants associated with complex traits. Here, we aim to describe the haplotype structure and LD variation at the pharmacogenetically relevant cytochrome P450 CYP2C and CYP2D gene regions among European populations.

METHODS

To assess the haplotype structure, LD pattern, and recombination rate variations in the clinically significant CYP2C and CYP2D regions, we genotyped 143 single-nucleotide polymorphisms (SNPs) across these two genome regions in a diverse set of 11 European population samples and one sub-Saharan African sample.

RESULTS

Our results showed extended patterns of LD and in general a low rate of recombination at these loci, and a low degree of allele differentiation for the two cytochrome P450 regions among Europeans, with the exception of the Sami and the Finns as European outliers. The Sami sample showed reduced haplotype diversity and higher LD for the two cytochrome P450 regions than the other Europeans, a feature that is proposed to enhance the LD mapping of underlying common complex traits. However, recombination hotspots and LD blocks at these two regions showed highly consistent structures across Europeans including Finns and Sami. Moreover, we showed that the CEPH sample has significantly higher tag transferability among Europeans and a more efficient tagging of both the rare CYP2C9 and the common CYP2C19 functional variants than the Sami. Our data set included CYP2C9*3 (rs1057910) and CYP2C19*2 (rs4244285) enzyme activity-altering variants associated in a recent genome-wide study with acenocoumarol-induced and warfarin-induced anticoagulation or to the antiplatelet effect of clopidogrel, respectively. Including these known activity-altering variants, we showed the haplotype variation and high derived allele frequencies of novel recently identified acenocoumarol genome-wide associated SNPs at CYP2C9 (rs4086116) and CYP2C18 (rs12772169, rs1998591, rs2104543, rs1042194) loci in a comprehensive set of 11 European populations. Furthermore, a significant frequency difference of a CYP2C19*2 gene mutation causing variable drug reactions was observed among Europeans.

CONCLUSION

The CEPH sample representing the general European population as such in the HapMap project seems to be the optimal population sample for the LD mapping of common complex traits among Europeans. Nevertheless, it is still argued that the unique pattern of LD in the Sami may offer an advantage for further association mapping, especially if multiple rare variants play a role in disease etiology. However, besides the activity-altering CYP2C9*3 (rs1057910) and CYP2C19*2 (rs4244285) variants, the high derived allele frequencies of novel recently identified acenocoumarol genome-wide associated SNPs at CYP2C9 (rs4086116) and CYP2C18 (rs12772169, rs1998591, rs2104543, rs1042194) loci variants indicated that the CYP2C region may have been influenced by selection. Thus, this fine-scale haplotype map of the CYP2C and CYP2D regions may help to choose markers for further association mapping of complex pharmacogenetic traits at these loci.

Reconstructing past changes in locus-specific recombination rates

BACKGROUND

Recombination rates vary at the level of the species, population and individual. Now recognized as a transient feature of the genome, recombination rates at a given locus can change markedly over time. Existing inferential methods, predominantly based on linkage disequilibrium patterns, return a long-term average estimate of past recombination rates. Such estimates can be misleading, but no analytical framework to infer recombination rates that have changed over time is currently available.

RESULTS

We apply coalescent modeling in conjunction with a suite of summary statistics to show that the recombination history of a locus can be reconstructed from a time series of genetic samples. More usefully, we describe a new method, based on n-tuple dataset subsampling, to infer past changes in recombination rate from DNA sequences taken at a single time point. This subsampling strategy can correctly assign simulated loci to constant, increasing and decreasing recombination models with an accuracy of 84%.

CONCLUSIONS

While providing an important stepping-stone to determining past recombination rates, n-tuple subsampling still exhibits a moderate error rate. Theoretical limitations indicated by coalescent theory suggest that highly accurate inference of past recombination rates will remain challenging. Nevertheless, we show for the first time that reconstructing historic recombination rates is possible in principle.

Population demographic history can cause the appearance of recombination hotspots

Although the prevailing view among geneticists suggests that recombination hotspots exist ubiquitously across the human genome, there is only limited experimental evidence from a few genomic regions to support the generality of this claim. A small number of true recombination hotspots are well supported experimentally, but the vast majority of hotspots have been identified on the basis of population genetic inferences from the patterns of linkage disequilibrium (LD) seen in the human population. These inferences are made assuming a particular model of human history, and one of the assumptions of that model is that the effective population size of humans has remained constant throughout our history. Our results show that relaxation of the constant population size assumption can create LD and variation patterns that are qualitatively and quantitatively similar to human populations without any need to invoke localized hotspots of recombination. In other words, apparent recombination hotspots could be an artifact of variable population size over time. Several lines of evidence suggest that the vast majority of hotspots identified on the basis of LD information are unlikely to have elevated recombination rates.