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LDSplitDB: a database for studies of meiotic recombination hotspots in MHC using human genomic data.

ABSTRACT: BACKGROUND:Meiotic recombination happens during the process of meiosis when chromosomes inherited from two parents exchange genetic materials to generate chromosomes in the gamete cells. The recombination events tend to occur in narrow genomic regions called recombination hotspots. Its dysregulation could lead to serious human diseases such as birth defects. Although the regulatory mechanism of recombination events is still unclear, DNA sequence polymorphisms have been found to play crucial roles in the regulation of recombination hotspots. METHOD:To facilitate the studies of the underlying mechanism, we developed a database named LDSplitDB which provides an integrative and interactive data mining and visualization platform for the genome-wide association studies of recombination hotspots. It contains the pre-computed association maps of the major histocompatibility complex (MHC) region in the 1000 Genomes Project and the HapMap Phase III datasets, and a genome-scale study of the European population from the HapMap Phase II dataset. Besides the recombination profiles, related data of genes, SNPs and different types of epigenetic modifications, which could be associated with meiotic recombination, are provided for comprehensive analysis. To meet the computational requirement of the rapidly increasing population genomics data, we prepared a lookup table of 400 haplotypes for recombination rate estimation using the well-known LDhat algorithm which includes all possible two-locus haplotype configurations. CONCLUSION:To the best of our knowledge, LDSplitDB is the first large-scale database for the association analysis of human recombination hotspots with DNA sequence polymorphisms. It provides valuable resources for the discovery of the mechanism of meiotic recombination hotspots. The information about MHC in this database could help understand the roles of recombination in human immune system. DATABASE URL: http://histone.scse.ntu.edu.sg/LDSplitDB.

SUBMITTER: Guo J

PROVIDER: S-EPMC5918432 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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LDSplitDB: a database for studies of meiotic recombination hotspots in MHC using human genomic data.

Guo Jing J Chen Hao H Yang Peng P Lee Yew Ti YT Wu Min M Przytycka Teresa M TM Kwoh Chee Keong CK Zheng Jie J

BMC medical genomics 20180420 Suppl 2

<h4>Background</h4>Meiotic recombination happens during the process of meiosis when chromosomes inherited from two parents exchange genetic materials to generate chromosomes in the gamete cells. The recombination events tend to occur in narrow genomic regions called recombination hotspots. Its dysregulation could lead to serious human diseases such as birth defects. Although the regulatory mechanism of recombination events is still unclear, DNA sequence polymorphisms have been found to play cruc ...[more]

PMID: 29697370

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Project description:Meiotic recombination is required for the orderly segregation of chromosomes during meiosis and for providing genetic diversity among offspring. Among mammals, as well as yeast and higher plants, recombination preferentially occurs at highly delimited chromosomal sites 1-2 kb long known as hotspots. Although considerable progress has been made in understanding the roles various proteins play in carrying out the molecular events of the recombination process, relatively little is understood about the factors controlling the location and relative activity of mammalian recombination hotspots. To search for trans-acting factors controlling the positioning of recombination events, we compared the locations of crossovers arising in an 8-Mb segment of a 100-Mb region of mouse Chromosome 1 (Chr 1) when the longer region was heterozygous C57BL/6J (B6) x CAST/EiJ (CAST) and the remainder of the genome was either similarly heterozygous or entirely homozygous B6. The lack of CAST alleles in the remainder of the genome resulted in profound changes in hotspot activity in both females and males. Recombination activity was lost at several hotspots; new, previously undetected hotspots appeared; and still other hotspots remained unaffected, indicating the presence of distant trans-acting gene(s) whose CAST allele(s) activate or suppress the activity of specific hotspots. Testing the activity of three activated hotspots in sperm samples from individual male progeny of two genetic crosses, we identified a single trans-acting regulator of hotspot activity, designated Rcr1, that is located in a 5.30-Mb interval (11.74-17.04 Mb) on Chr 17. Using an Escherichia coli cloning assay to characterize the molecular products of recombination at two of these hotspots, we found that Rcr1 controls the appearance of both crossover and noncrossover gene conversion events, indicating that it likely controls the sites of the double-strand DNA breaks that initiate the recombination process.

Project description:BackgroundMicrosatellites are highly abundant in eukaryotic genomes but their function and evolution are not yet well understood. Their elevated mutation rate makes them ideal markers of genetic difference, but high levels of unexplained heterogeneity in mutation rates among microsatellites at different genomic locations need to be elucidated in order to improve the power and accuracy of the many types of study that use them as genetic markers. Recombination could contribute to this heterogeneity, since while replication errors are thought to be the predominant mechanism for microsatellite mutation, meiotic recombination is involved in some mutation events. There is also evidence suggesting that microsatellites could function as recombination signals. The yeast S. cerevisiae is a useful model organism with which to further explore the link between microsatellites and recombination, since it is very amenable to genetic study, and meiotic recombination hotspots have been mapped throughout its entire genome.ResultsWe examined in detail the relationship between microsatellites and hotspots of meiotic double-strand breaks, the precursors of meiotic recombination, throughout the S. cerevisiae genome. We included all tandem repeats with motif length (repeat period) between one and six base pairs. Long, short and two-copy arrays were considered separately. We found that long, mono-, di- and trinucleotide microsatellites are around twice as frequent in hot than non-hot intergenic regions. The associations are weak or absent for repeats with less than six copies, and also for microsatellites with 4-6 base pair motifs, but high-copy arrays with motif length greater than three are relatively very rare throughout the genome. We present evidence that the association between high-copy, short-motif microsatellites and recombination hotspots is not driven by effects on microsatellite distribution of other factors previously linked to both recombination and microsatellites, including transcription, GC-content and transposable elements.ConclusionOur findings suggest that a mutation bias relating to recombination hotspots causing repeats to form and grow, and/or regulation of a subset of hotspots by simple sequences, may be significant processes in yeast. Some previous evidence has cast doubt on both of these possibilities, and as a result they have not been explored on a large scale, but the strength of the association we report suggests that they deserve further experimental testing.

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:In many mammals, including humans and mice, the zinc finger histone methyltransferase PRDM9 performs the first step in meiotic recombination by specifying the locations of hotspots, the sites of genetic recombination. PRDM9 binds to DNA at hotspots through its zinc finger domain and activates recombination by trimethylating histone H3K4 on adjacent nucleosomes through its PR/SET domain. Recently, the isolated PR/SET domain of PRDM9 was shown capable of also trimethylating H3K36 in vitro, raising the question of whether this reaction occurs in vivo during meiosis, and if so, what its function might be. Here, we show that full-length PRDM9 does trimethylate H3K36 in vivo in mouse spermatocytes. Levels of H3K4me3 and H3K36me3 are highly correlated at hotspots, but mutually exclusive elsewhere. In vitro, we find that although PRDM9 trimethylates H3K36 much more slowly than it does H3K4, PRDM9 is capable of placing both marks on the same histone molecules. In accord with these results, we also show that PRDM9 can trimethylate both K4 and K36 on the same nucleosomes in vivo, but the ratio of K4me3/K36me3 is much higher for the pair of nucleosomes adjacent to the PRDM9 binding site compared to the next pair further away. Importantly, H3K4me3/H3K36me3-double-positive nucleosomes occur only in regions of recombination: hotspots and the pseudoautosomal (PAR) region of the sex chromosomes. These double-positive nucleosomes are dramatically reduced when PRDM9 is absent, showing that this signature is PRDM9-dependent at hotspots; the residual double-positive nucleosomes most likely come from the PRDM9-independent PAR. These results, together with the fact that PRDM9 is the only known mammalian histone methyltransferase with both H3K4 and H3K36 trimethylation activity, suggest that trimethylation of H3K36 plays an important role in the recombination process. Given the known requirement of H3K36me3 for double strand break repair by homologous recombination in somatic cells, we suggest that it may play the same role in meiosis.

Project description:BackgroundA fundamental goal of single nucleotide polymorphism (SNP) genotyping is to determine the sharing of alleles between individuals across genomic loci. Such analyses have diverse applications in defining the relatedness of individuals (including unexpected relationships in nominally unrelated individuals, or consanguinity within pedigrees), analyzing meiotic crossovers, and identifying a broad range of chromosomal anomalies such as hemizygous deletions and uniparental disomy, and analyzing population structure.Principal findingsWe present SNPduo, a command-line and web accessible tool for analyzing and visualizing the relatedness of any two individuals using identity by state. Using identity by state does not require prior knowledge of allele frequencies or pedigree information, and is more computationally tractable and is less affected by population stratification than calculating identity by descent probabilities. The web implementation visualizes shared genomic regions, and generates UCSC viewable tracks. The command-line version requires pedigree information for compatibility with existing software and determining specified relationships even though pedigrees are not required for IBS calculation, generates no visual output, is written in portable C++, and is well-suited to analyzing large datasets. We demonstrate how the SNPduo web tool identifies meiotic crossover positions in siblings, and confirm our findings by visualizing meiotic recombination in synthetic three-generation pedigrees. We applied SNPduo to 210 nominally unrelated Phase I / II HapMap samples and, consistent with previous findings, identified six undeclared pairs of related individuals. We further analyzed identity by state in 2,883 individuals from multiplex families with autism and identified a series of anomalies including related parents, an individual with mosaic loss of chromosome 18, an individual with maternal heterodisomy of chromosome 16, and unexplained replicate samples.ConclusionsSNPduo provides the ability to explore and visualize SNP data to characterize the relatedness between individuals. It is compatible with, but distinct from, other established analysis software such as PLINK, and performs favorably in benchmarking studies for the analyses of genetic relatedness.

Dataset Information

LDSplitDB: a database for studies of meiotic recombination hotspots in MHC using human genomic data.

Publications

LDSplitDB: a database for studies of meiotic recombination hotspots in MHC using human genomic data.

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