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Conservation of recombination hotspots in yeast.

ABSTRACT: Meiotic recombination does not occur randomly along a chromosome, but instead tends to be concentrated in small regions, known as "recombination hotspots." Recombination hotspots are thought to be short-lived in evolutionary time due to their self-destructive nature, as gene conversion favors recombination-suppressing alleles over recombination-promoting alleles during double-strand repair. Consistent with this expectation, hotspots in humans are highly dynamic, with little correspondence in location between humans and chimpanzees. Here, we identify recombination hotspots in two lineages of the yeast Saccharomyces paradoxus, and compare their locations to those found previously in Saccharomyces cerevisiae. Surprisingly, we find considerable overlap between the two species, despite the fact that they are at least 10 times more divergent than humans and chimpanzees. We attribute this unexpected result to the low frequency of sex and outcrossing in these yeasts, acting to reduce the population genetic effect of biased gene conversion. Traces from two other signatures of recombination, namely high mutagenicity and GC-biased gene conversion, are consistent with this interpretation. Thus, recombination hotspots are not inevitably short-lived, but rather their persistence through evolutionary time will be determined by the frequency of outcrossing events in the life cycle.

SUBMITTER: Tsai IJ

PROVIDER: S-EPMC2867876 | biostudies-other | 2010 Apr

REPOSITORIES: biostudies-other

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Conservation of recombination hotspots in yeast.

Tsai Isheng J IJ Burt Austin A Koufopanou Vassiliki V

Proceedings of the National Academy of Sciences of the United States of America 20100412 17

Meiotic recombination does not occur randomly along a chromosome, but instead tends to be concentrated in small regions, known as "recombination hotspots." Recombination hotspots are thought to be short-lived in evolutionary time due to their self-destructive nature, as gene conversion favors recombination-suppressing alleles over recombination-promoting alleles during double-strand repair. Consistent with this expectation, hotspots in humans are highly dynamic, with little correspondence in loc ...[more]

PMID: 20385822

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Project description:BACKGROUND: The regulatory mechanism of recombination is one of the most fundamental problems in genomics, with wide applications in genome wide association studies (GWAS), birth-defect diseases, molecular evolution, cancer research, etc. Recombination events cluster into short genomic regions called "recombination hotspots". Recently, a zinc finger protein PRDM9 was reported to regulate recombination hotspots in human and mouse genomes. In addition, a 13-mer motif contained in the binding sites of PRDM9 is found to be enriched in human hotspots. However, this 13-mer motif only covers a fraction of hotspots, indicating that PRDM9 is not the only regulator of recombination hotspots. Therefore, the challenge of discovering other regulators of recombination hotspots becomes significant. Furthermore, recombination is a complex process. Hence, multiple proteins acting as machinery, rather than individual proteins, are more likely to carry out this process in a precise and stable manner. Therefore, the extension of the prediction of individual trans-regulators to protein complexes is also highly desired. RESULTS: In this paper, we introduce a pipeline to identify genes and protein complexes associated with recombination hotspots. First, we prioritize proteins associated with hotspots based on their preference of binding to hotspots and coldspots. Second, using the above identified genes as seeds, we apply the Random Walk with Restart algorithm (RWR) to propagate their influences to other proteins in protein-protein interaction (PPI) networks. Hence, many proteins without DNA-binding information will also be assigned a score to implicate their roles in recombination hotspots. Third, we construct sub-PPI networks induced by top genes ranked by RWR for various species (e.g., yeast, human and mouse) and detect protein complexes in those sub-PPI networks. CONCLUSIONS: The GO term analysis show that our prioritizing methods and the RWR algorithm are capable of identifying novel genes associated with recombination hotspots. The trans-regulators predicted by our pipeline are enriched with epigenetic functions (e.g., histone modifications), demonstrating the epigenetic regulatory mechanisms of recombination hotspots. The identified protein complexes also provide us with candidates to further investigate the molecular machineries for recombination hotspots. Moreover, the experimental data and results are available on our web site http://www.ntu.edu.sg/home/zhengjie/data/RecombinationHotspot/NetPipe/.

Project description:Deleterious mutations inevitably emerge in any evolutionary process and are speculated to decisively influence the structure of the genome. Meiosis, which is thought to play a major role in handling mutations on the population level, recombines chromosomes via non-randomly distributed hot spots for meiotic recombination. In many genomes, various types of genetic elements are distributed in patterns that are currently not well understood. In particular, important (essential) genes are arranged in clusters, which often cannot be explained by a functional relationship of the involved genes. Here we show by computer simulation that essential gene (EG) clustering provides a fitness benefit in handling deleterious mutations in sexual populations with variable levels of inbreeding and outbreeding. We find that recessive lethal mutations enforce a selective pressure towards clustered genome architectures. Our simulations correctly predict (i) the evolution of non-random distributions of meiotic crossovers, (ii) the genome-wide anti-correlation of meiotic crossovers and EG clustering, (iii) the evolution of EG enrichment in pericentromeric regions and (iv) the associated absence of meiotic crossovers (cold centromeres). Our results furthermore predict optimal crossover rates for yeast chromosomes, which match the experimentally determined rates. Using a Saccharomyces cerevisiae conditional mutator strain, we show that haploid lethal phenotypes result predominantly from mutation of single loci and generally do not impair mating, which leads to an accumulation of mutational load following meiosis and mating. We hypothesize that purging of deleterious mutations in essential genes constitutes an important factor driving meiotic crossover. Therefore, the increased robustness of populations to deleterious mutations, which arises from clustered genome architectures, may provide a significant selective force shaping crossover distribution. Our analysis reveals a new aspect of the evolution of genome architectures that complements insights about molecular constraints, such as the interference of pericentromeric crossovers with chromosome segregation.

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Conservation of recombination hotspots in yeast.

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Conservation of recombination hotspots in yeast.

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