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.     

Hotspots and richness pattern of grasshopper species in cultural landscapes

The success of the hotspot approach for biodiversity conservation depends on the spatial scale and the indicator species used. In this study, we investigated grasshopper species richness in Switzerland at a 1 ha resolution including a total of 111 species. We compared the representativeness of common and of endangered grasshopper species for the overall grasshopper species richness and we assessed the efficiency of the hotspot approach for grasshopper conservation. The pattern of overall grasshopper species richness was well represented by both the number of common and the number of endangered grasshopper species. For evaluating the efficiency of different hotspot approaches for conservation, we compared hotspots of common species, hotspots of endangered species (rarity hotspots), and hotspots of all grasshopper species (richness hotspots). Among these hotspot types, richness hotspots not only featured most common grasshopper species, but they even contained more endangered species than the rarity hotspots. The combination of rarity hotspots and hotspots of common species featured more species than the other combinations of hotspot types. However, the gain of combining two hotspot types compared to the single-hotspot approach was low (max. 3 species). About 24% of the species were not contained in any of the hotspots. These grasshopper species require species-specific action plans. As rarity hotspots were located in areas that are rather strongly affected by landscape change, species richness in rarity hotspots may decrease in the future. We conclude that, for grasshoppers, the hotspot approach on the 1 ha scale can be an effective way to conserve a high proportion of species richness.     

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.     

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.     

Do biodiversity hotspots match with rodent conservation hotspots?

Biodiversity hotspots are used widely to designate priority regions for conservation efforts. It is unknown, however, whether the current network of hotspots adequately represents globally threatened taxonomic diversity for whole plant and animal groups. We used a mammalian group traditionally neglected in terms of conservation efforts, the rodents, in order to test whether biodiversity hotspots match the current distribution of threatened taxa (genera and species). Significantly higher numbers of threatened rodent genera and species fell within biodiversity hotspots; nonetheless over 25% of the total threatened genera and species did not occur in any biodiversity hotspot. This was particularly true for the Australian region, where 100% of the threatened genera and species fell outside biodiversity hotspots, with many threatened taxa found in Papua-New Guinea. We suggest to officially including Papua New Guinea among biodiversity hotspots for rodents, and also the steppic/semidesert areas of central Asia.     

Differential Association of the Conserved SUMO Ligase Zip3 with Meiotic Double-Strand Break Sites Reveals Regional Variations in the Outcome of Meiotic Recombination

During the first meiotic prophase, programmed DNA double-strand breaks (DSBs) are distributed non randomly at hotspots along chromosomes, to initiate recombination. In all organisms, more DSBs are formed than crossovers (CO), the repair product that creates a physical link between homologs and allows their correct segregation. It is not known whether all DSB hotspots are also CO hotspots or if the CO/DSB ratio varies with the chromosomal location. Here, we investigated the variations in the CO/DSB ratio by mapping genome-wide the binding sites of the Zip3 protein during budding yeast meiosis. We show that Zip3 associates with DSB sites that are engaged in repair by CO, and Zip3 enrichment at DSBs reflects the DSB tendency to be repaired by CO. Moreover, the relative amount of Zip3 per DSB varies with the chromosomal location, and specific chromosomal features are associated with high or low Zip3 per DSB. This work shows that DSB hotspots are not necessarily CO hotspots and suggests that different categories of DSB sites may fulfill different functions.     

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.     

Detecting sequence polymorphisms associated with meiotic recombination hotspots in the human genome

Background  

Meiotic recombination events tend to cluster into narrow spans of a few kilobases long, called recombination hotspots. Such hotspots are not conserved between human and chimpanzee and vary between different human ethnic groups. At the same time, recombination hotspots are heritable. Previous studies showed instances where differences in recombination rate could be associated with sequence polymorphisms.     

The Red Queen theory of recombination hotspots

Recombination hotspots are small chromosomal regions, where meiotic crossover events happen with high frequency. Recombination is initiated by a double‐strand break (DSB) that requires the intervention of the molecular repair mechanism. The DSB repair mechanism may result in the exchange of homologous chromosomes (crossover) and the conversion of the allelic sequence that breaks into the one that does not break (biased gene conversion). Biased gene conversion results in a transmission advantage for the allele that does not break, thus preventing recombination and rendering recombination hotspots transient. How is it possible that recombination hotspots persist over evolutionary time (maintaining the average chromosomal crossover rate) when they are self‐destructive? This fundamental question is known as the recombination hotspot paradox and has attracted much attention in recent years. Yet, that attention has not translated into a fully satisfactory answer. No existing model adequately explains all aspects of the recombination hotspot paradox. Here, we formulate an intragenomic conflict model resulting in Red Queen dynamics that fully accounts for all empirical observations regarding the molecular mechanisms of recombination hotspots, the nonrandom targeting of the recombination machinery to hotspots and the evolutionary dynamics of hotspot turnover.     

Will hotspots conserve extra primate and carnivore evolutionary history?

Setting aside biodiversity hotspots would be especially compelling if they contained not just enormous numbers of species but also excessive evolutionary history. A recent study seemed to provide evidence for this incentive for hotspot conservation. Sechrest et al . (2002 ) reported that hotspots contain more endemic phylogenetic diversity (PD) than expected based on the numbers of primate and carnivore species they contain. We extend their analysis and revise some of their claims. For primates and threatened carnivores, we show that the original analysis was driven by a single hotspot (Madagascar) that contains an ancient endemic clade. The remaining hotspots harbour less rather than significantly more endemic PD than expected. Thus, while one hotspot contains an enormous excess of evolutionary history, the remaining hotspots do not. Our analysis reveals that the overriding influence of a single hotspot can create the misleading impression that hotspots generally contain excessive evolutionary history. Justification for the hotspot initiative should be based on robust evidence. We join others in endorsing an increased role for detailed phylogenetic analysis in conservation planning.     

Mutation hotspots in the p53 gene in tumors of different origin: correlation with evolutionary conservation and signs of positive selection

We present a classification analysis of the mutation spectra of the p53 gene and construct maps of hotspots for the germline (Li-Fraumein syndrome), different types of tumors and their derived cell lines. While spectra from solid tumors share common hotspots with the germline spectrum, they also contain unique sets of somatic hotspots that are not observed in the germline. All these hotspots correspond to amino acid replacements in the DNA-binding interface of p53. The mutation spectra of lymphomas and cell lines derived from lymphomas and lung cancers contained few hotspots compared to solid tumors. Thus, the distribution of hotspots in the p53 gene appears to depend on the tumor type and cell growth conditions; this specificity is missed by the bulk hotspot analysis. A negative correlation was detected between the amino acid replacement propensity in tumors and evolutionary variability: the hotspots are located in the positions that are highly conserved in p53 and its paralogs, p63 and p73. In all the mutation spectra, substitutions leading to amino acid replacements strongly dominate over silent substitutions, indicating that functional sites evolving under strong purifying selection are subject to intensive positive selection in p53-dependent tumors. These results are compatible with the gain-of-function concept of the role of p53 in tumorigenesis.     

Multimer Formation Explains Allelic Suppression of PRDM9 Recombination Hotspots

Genetic recombination during meiosis functions to increase genetic diversity, promotes elimination of deleterious alleles, and helps assure proper segregation of chromatids. Mammalian recombination events are concentrated at specialized sites, termed hotspots, whose locations are determined by PRDM9, a zinc finger DNA-binding histone methyltransferase. Prdm9 is highly polymorphic with most alleles activating their own set of hotspots. In populations exhibiting high frequencies of heterozygosity, questions remain about the influences different alleles have in heterozygous individuals where the two variant forms of PRDM9 typically do not activate equivalent populations of hotspots. We now find that, in addition to activating its own hotspots, the presence of one Prdm9 allele can modify the activity of hotspots activated by the other allele. PRDM9 function is also dosage sensitive; Prdm9 ^+/- heterozygous null mice have reduced numbers and less active hotspots and increased numbers of aberrant germ cells. In mice carrying two Prdm9 alleles, there is allelic competition; the stronger Prdm9 allele can partially or entirely suppress chromatin modification and recombination at hotspots of the weaker allele. In cell cultures, PRDM9 protein variants form functional heteromeric complexes which can bind hotspots sequences. When a heteromeric complex binds at a hotspot of one PRDM9 variant, the other PRDM9 variant, which would otherwise not bind, can still methylate hotspot nucleosomes. We propose that in heterozygous individuals the underlying molecular mechanism of allelic suppression results from formation of PRDM9 heteromers, where the DNA binding activity of one protein variant dominantly directs recombination initiation towards its own hotspots, effectively titrating down recombination by the other protein variant. In natural populations with many heterozygous individuals, allelic competition will influence the recombination landscape.     

The spatial regulation of meiotic recombination hotspots: Are all DSB hotspots crossover hotspots?

A key step for the success of meiosis is programmed homologous recombination, during which crossovers, or exchange of chromosome arms, take place. Crossovers increase genetic diversity but their main function is to ensure accurate chromosome segregation. Defects in crossover number and position produce aneuploidies that represent the main cause of miscarriages and chromosomal abnormalities such as Down's syndrome. Recombination is initiated by the formation of programmed double strand breaks (DSBs), which occur preferentially at places called DSB hotspots. Among all DSBs generated, only a small fraction is repaired by crossover, the other being repaired by other homologous recombination pathways. Crossover maps have been generated in a number of organisms, defining crossover hotspots. With the availability of genome-wide maps of DSBs as well as the ability to measure genetically the repair outcome at several hotspots, it is becoming more and more clear that not all DSB hotspots behave the same for crossover formation, suggesting that chromosomal features distinguish different types of hotspots.     

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

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

Transmission of infectious diseases en route to habitat hotspots

Background

The spread of infectious diseases in wildlife populations is influenced by patterns of between-host contacts. Habitat “hotspots” - places attracting a large numbers of individuals or social groups - can significantly alter contact patterns and, hence, disease propagation. Research on the importance of habitat hotspots in wildlife epidemiology has primarily focused on how inter-individual contacts occurring at the hotspot itself increase disease transmission. However, in territorial animals, epidemiologically important contacts may primarily occur as animals cross through territories of conspecifics en route to habitat hotspots. So far, the phenomenon has received little attention. Here, we investigate the importance of these contacts in the case where infectious individuals keep visiting the hotspots and in the case where these individuals are not able to travel to the hotspot any more.

Methodology and Principal Findings

We developed a simulation epidemiological model to investigate both cases in a scenario when transmission at the hotspot does not occur. We find that (i) hotspots still exacerbate epidemics, (ii) when infectious individuals do not travel to the hotspot, the most vulnerable individuals are those residing at intermediate distances from the hotspot rather than nearby, and (iii) the epidemiological vulnerability of a population is the highest when the number of hotspots is intermediate.

Conclusions and Significance

By altering animal movements in their vicinity, habitat hotspots can thus strongly increase the spread of infectious diseases, even when disease transmission does not occur at the hotspot itself. Interestingly, when animals only visit the nearest hotspot, creating additional artificial hotspots, rather than reducing their number, may be an efficient disease control measure.     

HIV-1 Vaccine-Induced T-Cell Reponses Cluster in Epitope Hotspots that Differ from Those Induced in Natural Infection with HIV-1

Several recent large clinical trials evaluated HIV vaccine candidates that were based on recombinant adenovirus serotype 5 (rAd-5) vectors expressing HIV-derived antigens. These vaccines primarily elicited T-cell responses, which are known to be critical for controlling HIV infection. In the current study, we present a meta-analysis of epitope mapping data from 177 participants in three clinical trials that tested two different HIV vaccines: MRKAd-5 HIV and VRC-HIVAD014-00VP. We characterized the population-level epitope responses in these trials by generating population-based epitope maps, and also designed such maps using a large cohort of 372 naturally infected individuals. We used these maps to address several questions: (1) Are vaccine-induced responses randomly distributed across vaccine inserts, or do they cluster into immunodominant epitope hotspots? (2) Are the immunodominance patterns observed for these two vaccines in three vaccine trials different from one another? (3) Do vaccine-induced hotspots overlap with epitope hotspots induced by chronic natural infection with HIV-1? (4) Do immunodominant hotspots target evolutionarily conserved regions of the HIV genome? (5) Can epitope prediction methods be used to identify these hotspots? We found that vaccine responses clustered into epitope hotspots in all three vaccine trials and some of these hotspots were not observed in chronic natural infection. We also found significant differences between the immunodominance patterns generated in each trial, even comparing two trials that tested the same vaccine in different populations. Some of the vaccine-induced immunodominant hotspots were located in highly variable regions of the HIV genome, and this was more evident for the MRKAd-5 HIV vaccine. Finally, we found that epitope prediction methods can partially predict the location of vaccine-induced epitope hotspots. Our findings have implications for vaccine design and suggest a framework by which different vaccine candidates can be compared in early phases of evaluation.     

Geographic discrepancies between global and local rarity richness patterns and the implications for conservation

The emerging interest in the biological and conservation significance of locally rare species prompts a number of questions about their correspondence with other categories of biodiversity, especially global rarity. Here we present an analysis of the correspondence between the distributions of globally and locally rare plants. Using biological hotspots of rarity as our framework, we evaluate the extent to which conservation of globally rare plants will act as a surrogate for conservation of locally rare taxa. Subsequently, we aim to identify gaps between rarity hotspots and protected land to guide conservation planning. We compiled distribution data for globally and locally rare plants from botanically diverse Napa County, California into a geographic information system. We then generated richness maps highlighting hotspots of global and local rarity. Following this, we overlaid the distribution of these hotspots with the distribution of protected lands to identify conservation gaps. Based on occupancy of 1 km² grid cells, we found that over half of Napa County is occupied by at least one globally or locally rare plant. Hotspots of global and local rarity occurred in a substantially smaller portion of the county. Of these hotspots, less than 5% were classified as multi-scale hotspots, i.e. they were hotspots of global and local rarity. Although, several hotspots corresponded with the 483 km² of protected lands in Napa County, some of the richest areas did not. Thus, our results show that there are important conservation gaps in Napa County. Furthermore, if only hotspots of global rarity are preserved, only a subset of locally rare plants will be protected. Therefore, conservation of global, local, and multi-scale hotspots needs serious consideration if the goals are to protect a larger variety of biological attributes, prevent extinction, and limit extirpation in Napa County.