SequenceLDhot: detecting recombination hotspots

MOTIVATION: There is much local variation in recombination rates across the human genome--with the majority of recombination occurring in recombination hotspots--short regions of around approximately 2 kb in length that have much higher recombination rates than neighbouring regions. Knowledge of this local variation is important, e.g. in the design and analysis of association studies for disease genes. Population genetic data, such as that generated by the HapMap project, can be used to infer the location of these hotspots. We present a new, efficient and powerful method for detecting recombination hotspots from population data. RESULTS: We compare our method with four current methods for detecting hotspots. It is orders of magnitude quicker, and has greater power, than two related approaches. It appears to be more powerful than HotspotFisher, though less accurate at inferring the precise positions of the hotspot. It was also more powerful than LDhot in some situations: particularly for weaker hotspots (10-40 times the background rate) when SNP density is lower (< 1/kb). AVAILABILITY: Program, data sets, and full details of results are available at: http://www.maths.lancs.ac.uk/~fearnhea/Hotspot.     

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.     

Molecular evolution of recombination hotspots and highly recombining pseudoautosomal regions in hominoids

We examined the effects of recombination on the molecular evolution of noncoding regions in pseudoautosomal regions (PARs) and recombination hotspots in hominoids. The PAR-linked regions analyzed had on average longer branch lengths than those of the recombination hotspots. Moreover, contrary to previous observations, we found no correlation between recombination rate and silent site divergence in our data set and little change in the GC content during recent hominoid evolution. This suggests that the current rate of recombination is not a good indicator of the past rates of recombination for these highly recombining regions. Furthermore, human recombination hotspots show increased AT to GC substitutions in the human lineage, while no such pattern is detected for PAR-linked regions. Together, these observations suggest that recombination hotspots in hominoids are transient in the evolutionary time-scale. Interestingly, the 16p13.3 recombination hotspot locus violates a local molecular clock, though the locus appears to be noncoding and should evolve neutrally. We hypothesize that sudden changes in recombination rate have caused the changes in substitution rate at this locus.     

Inference about recombination from haplotype data: lower bounds and recombination hotspots.

Recombination is an important evolutionary mechanism responsible for creating the patterns of haplotype variation observable in human populations. Recently, there has been extensive research on understanding the fine-scale variation in recombination across the human genome using DNA polymorphism data. Historical recombination events leave signature patterns in haplotype data. A nonparametric approach for estimating the number of historical recombination events is to compute the minimum number of recombination events in the history of a set of haplotypes. In this paper, we provide new and improved methods for computing lower bounds on the minimum number of recombination events. These methods are shown to detect a higher number of recombination events for a haplotype dataset from a region in the lipoprotein lipase gene than previous lower bounds. We apply our methods to two datasets for which recombination hotspots have been experimentally determined and demonstrate a high density of detectable recombination events in the regions annotated as recombination hotspots. The programs implementing the methods in this paper are available at www.cs.ucsd.edu/users/vibansal/RecBounds/.     

Genetic Crossovers Are Predicted Accurately by the Computed Human Recombination Map

Hotspots of meiotic recombination can change rapidly over time. This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers. To estimate the accuracy of the computed recombination rate map, we have mapped genetic crossovers to a median resolution of 70 Kb in 10 CEPH pedigrees. We then compared the positions of crossovers with the hotspots computed from HapMap data and performed extensive computer simulations to compare the observed distributions of crossovers with the distributions expected from the calculated recombination rate maps. Here we show that a population-averaged hotspot map computed from linkage disequilibrium data predicts well present-day genetic crossovers. We find that computed hotspot maps accurately estimate both the strength and the position of meiotic hotspots. An in-depth examination of not-predicted crossovers shows that they are preferentially located in regions where hotspots are found in other populations. In summary, we find that by combining several computed population-specific maps we can capture the variation in individual hotspots to generate a hotspot map that can predict almost all present-day genetic crossovers.     

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.     

The recombinational anatomy of a mouse chromosome

Among mammals, genetic recombination occurs at highly delimited sites known as recombination hotspots. They are typically 1-2 kb long and vary as much as a 1,000-fold or more in recombination activity. Although much is known about the molecular details of the recombination process itself, the factors determining the location and relative activity of hotspots are poorly understood. To further our understanding, we have collected and mapped the locations of 5,472 crossover events along mouse Chromosome 1 arising in 6,028 meioses of male and female reciprocal F1 hybrids of C57BL/6J and CAST/EiJ mice. Crossovers were mapped to a minimum resolution of 225 kb, and those in the telomere-proximal 24.7 Mb were further mapped to resolve individual hotspots. Recombination rates were evolutionarily conserved on a regional scale, but not at the local level. There was a clear negative-exponential relationship between the relative activity and abundance of hotspot activity classes, such that a small number of the most active hotspots account for the majority of recombination. Females had 1.2x higher overall recombination than males did, although the sex ratio showed considerable regional variation. Locally, entirely sex-specific hotspots were rare. The initiation of recombination at the most active hotspot was regulated independently on the two parental chromatids, and analysis of reciprocal crosses indicated that parental imprinting has subtle effects on recombination rates. It appears that the regulation of mammalian recombination is a complex, dynamic process involving multiple factors reflecting species, sex, individual variation within species, and the properties of individual hotspots.     

High-resolution sperm typing of meiotic recombination in the mouse MHC Ebeta gene

Meiotic crossovers detected by pedigree analysis in the mouse MHC cluster into hotspots. To explore the properties of hotspots, we subjected the class II E(beta) gene to high-resolution sperm crossover analysis. We confirm the presence of a highly localized hotspot 1.0-1.6 kb wide in the second intron of E(beta) and show that it is flanked by DNA which is almost completely recombinationally inert. Mice heterozygous for haplotype s and another MHC haplotype show major haplotype-dependant variation in crossover rate but always the same hotspot, even in crosses including the highly diverged p haplotype. Crossovers in reciprocal orientations occur at similar rates but show different distributions across the hotspot, with the position of centre points in the two orientations shifted on average by 400 bp. This asymmetry results in crossover products showing biased gene conversion in favour of hotspot markers from the non-initiating haplotype, and supports the double-strand break repair model of recombination, with haplotype s as the most efficient crossover initiator. The detailed behaviour of the E(beta) hotspot, including evidence for highly localized recombination initiation, is strikingly similar to human hotspots.     

A new method for detecting human recombination hotspots and its applications to the HapMap ENCODE data

Computational detection of recombination hotspots from population polymorphism data is important both for understanding the nature of recombination and for applications such as association studies. We propose a new method for this task based on a multiple-hotspot model and an (approximate) log-likelihood ratio test. A truncated, weighted pairwise log-likelihood is introduced and applied to the calculation of the log-likelihood ratio, and a forward-selection procedure is adopted to search for the optimal hotspot predictions. The method shows a relatively high power with a low false-positive rate in detecting multiple hotspots in simulation data and has a performance comparable to the best results of leading computational methods in experimental data for which recombination hotspots have been characterized by sperm-typing experiments. The method can be applied to both phased and unphased data directly, with a very fast computational speed. We applied the method to the 10 500-kb regions of the HapMap ENCODE data and found 172 hotspots among the three populations, with average hotspot width of 2.4 kb. By comparisons with the simulation data, we found some evidence that hotspots are not all identical across populations. The correlations between detected hotspots and several genomic characteristics were examined. In particular, we observed that DNaseI-hypersensitive sites are enriched in hotspots, suggesting the existence of human beta hotspots similar to those found in yeast.     

The Impact of Recombination Hotspots on Genome Evolution of a Fungal Plant Pathogen

Recombination has an impact on genome evolution by maintaining chromosomal integrity, affecting the efficacy of selection, and increasing genetic variability in populations. Recombination rates are a key determinant of the coevolutionary dynamics between hosts and their pathogens. Historic recombination events created devastating new pathogens, but the impact of ongoing recombination in sexual pathogens is poorly understood. Many fungal pathogens of plants undergo regular sexual cycles, and sex is considered to be a major factor contributing to virulence. We generated a recombination map at kilobase-scale resolution for the haploid plant pathogenic fungus Zymoseptoria tritici. To account for intraspecific variation in recombination rates, we constructed genetic maps from two independent crosses. We localized a total of 10,287 crossover events in 441 progeny and found that recombination rates were highly heterogeneous within and among chromosomes. Recombination rates on large chromosomes were inversely correlated with chromosome length. Short accessory chromosomes often lacked evidence for crossovers between parental chromosomes. Recombination was concentrated in narrow hotspots that were preferentially located close to telomeres. Hotspots were only partially conserved between the two crosses, suggesting that hotspots are short-lived and may vary according to genomic background. Genes located in hotspot regions were enriched in genes encoding secreted proteins. Population resequencing showed that chromosomal regions with high recombination rates were strongly correlated with regions of low linkage disequilibrium. Hence, genes in pathogen recombination hotspots are likely to evolve faster in natural populations and may represent a greater threat to the host.     

A novel method with improved power to detect recombination hotspots from polymorphism data reveals multiple hotspots in human genes

We introduce a new method for detection of recombination hotspots from population genetic data. This method is based on (a) defining an (approximate) penalized likelihood for how recombination rate varies with physical position and (b) maximizing this penalized likelihood over possible sets of recombination hotspots. Simulation results suggest that this is a more powerful method for detection of hotspots than are existing methods. We apply the method to data from 89 genes sequenced in African American and European American populations. We find many genes with multiple hotspots, and some hotspots show evidence of being population-specific. Our results suggest that hotspots are randomly positioned within genes and could be as frequent as one per 30 kb.     

A coalescent model of recombination hotspots

Recent experimental findings suggest that the assumption of a homogeneous recombination rate along the human genome is too naive. These findings point to block-structured recombination rates; certain regions (called hotspots) are more prone than other regions to recombination. In this report a coalescent model incorporating hotspot or block-structured recombination is developed and investigated analytically as well as by simulation. Our main results can be summarized as follows: (1) The expected number of recombination events is much lower in a model with pure hotspot recombination than in a model with pure homogeneous recombination, (2) hotspots give rise to large variation in recombination rates along the genome as well as in the number of historical recombination events, and (3) the size of a (nonrecombining) block in the hotspot model is likely to be overestimated grossly when estimated from SNP data. The results are discussed with reference to the current debate about block-structured recombination and, in addition, the results are compared to genome-wide variation in recombination rates. A number of new analytical results about the model are derived.     

Persistence and loss of meiotic recombination hotspots

The contradiction between the long-term persistence of the chromosomal hotspots that initiate meiotic recombination and the self-destructive mechanism by which they act strongly suggests that our understanding of recombination is incomplete. This "hotspot paradox" has been reinforced by the finding that biased gene conversion also removes active hotspots from human sperm. To investigate the requirements for hotspot persistence, we developed a detailed computer simulation model of their activity and its evolutionary consequences. With this model, unopposed hotspot activity could drive strong hotspots from 50% representation to extinction within 70 generations. Although the crossing over that hotspots cause can increase population fitness, this benefit was always too small to slow the loss of hotspots. Hotspots could not be maintained by plausible rates of de novo mutation, nor by crossover interference, which alters the frequency and/or spacing of crossovers. Competition among hotspots for activity-limiting factors also did not prevent their extinction, although the rate of hotspot loss was slowed. Key factors were the probability that the initiating hotspot allele is destroyed and the nonmeiotic contributions hotspots make to fitness. Experimental investigation of these deserves high priority, because until the paradox is resolved all components of the mechanism are open to doubt.     

Molecular mechanisms for environmentally induced and evolutionarily rapid redistribution (plasticity) of meiotic recombination

It has long been known (circa 1917) that environmental conditions, as well as speciation, can affect dramatically the frequency distribution of Spo11/Rec12-dependent meiotic recombination. Here, by analyzing DNA sequence-dependent meiotic recombination hotspots in the fission yeast Schizosaccharomyces pombe, we reveal a molecular basis for these phenomena. The impacts of changing environmental conditions (temperature, nutrients, and osmolarity) on local rates of recombination are mediated directly by DNA site-dependent hotspots (M26, CCAAT, and Oligo-C). This control is exerted through environmental condition-responsive signal transduction networks (involving Atf1, Pcr1, Php2, Php3, Php5, and Rst2). Strikingly, individual hotspots modulate rates of recombination over a very broad dynamic range in response to changing conditions. They can range from being quiescent to being highly proficient at promoting activity of the basal recombination machinery (Spo11/Rec12 complex). Moreover, each different class of hotspot functions as an independently controlled rheostat; a condition that increases the activity of one class can decrease the activity of another class. Together, the independent modulation of recombination rates by each different class of DNA site-dependent hotspots (of which there are many) provides a molecular mechanism for highly dynamic, large-scale changes in the global frequency distribution of meiotic recombination. Because hotspot-activating DNA sites discovered in fission yeast are conserved functionally in other species, this process can also explain the previously enigmatic, Prdm9-independent, evolutionarily rapid changes in hotspot usage between closely related species, subspecies, and isolated populations of the same species.     

Mouse PRDM9 DNA-binding specificity determines sites of histone H3 lysine 4 trimethylation for initiation of meiotic recombination

Meiotic recombination generates reciprocal exchanges between homologous chromosomes (also called crossovers, COs) that are essential for proper chromosome segregation during meiosis and are a major source of genome diversity by generating new allele combinations. COs have two striking properties: they occur at specific sites, called hotspots, and these sites evolve rapidly. In mammals, the Prdm9 gene, which encodes a meiosis-specific histone H3 methyltransferase, has recently been identified as a determinant of CO hotspots. Here, using transgenic mice, we show that the sole modification of PRDM9 zinc fingers leads to changes in hotspot activity, histone H3 lysine 4 trimethylation (H3K4me3) levels, and chromosome-wide distribution of COs. We further demonstrate by an in vitro assay that the PRDM9 variant associated with hotspot activity binds specifically to DNA sequences located at the center of the three hotspots tested. Remarkably, we show that mutations in cis located at hotspot centers and associated with a decrease of hotspot activity affect PRDM9 binding. Taken together, these results provide the direct demonstration that Prdm9 is a master regulator of hotspot localization through the DNA binding specificity of its zinc finger array and that binding of PRDM9 at hotspots promotes local H3K4me3 enrichment.     

Domestication Shapes Recombination Patterns in Tomato

Meiotic recombination is a biological process of key importance in breeding, to generate genetic diversity and develop novel or agronomically relevant haplotypes. In crop tomato, recombination is curtailed as manifested by linkage disequilibrium decay over a longer distance and reduced diversity compared with wild relatives. Here, we compared domesticated and wild populations of tomato and found an overall conserved recombination landscape, with local changes in effective recombination rate in specific genomic regions. We also studied the dynamics of recombination hotspots resulting from domestication and found that loss of such hotspots is associated with selective sweeps, most notably in the pericentromeric heterochromatin. We detected footprints of genetic changes and structural variants, among them associated with transposable elements, linked with hotspot divergence during domestication, likely causing fine-scale alterations to recombination patterns and resulting in linkage drag.     

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.     

Contrasted Patterns of Crossover and Non-crossover at Arabidopsis thaliana Meiotic Recombination Hotspots

The vast majority of meiotic recombination events (crossovers (COs) and non-crossovers (NCOs)) cluster in narrow hotspots surrounded by large regions devoid of recombinational activity. Here, using a new molecular approach in plants, called “pollen-typing”, we detected and characterized hundreds of CO and NCO molecules in two different hotspot regions in Arabidopsis thaliana. This analysis revealed that COs are concentrated in regions of a few kilobases where their rates reach up to 50 times the genome average. The hotspots themselves tend to cluster in regions less than 8 kilobases in size with overlapping CO distribution. Non-crossover (NCO) events also occurred in the two hotspots but at very different levels (local CO/NCO ratios of 1/1 and 30/1) and their track lengths were quite small (a few hundred base pairs). We also showed that the ZMM protein MSH4 plays a role in CO formation and somewhat unexpectedly we also found that it is involved in the generation of NCOs but with a different level of effect. Finally, factors acting in cis and in trans appear to shape the rate and distribution of COs at meiotic recombination hotspots.