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      Recombination initiation maps of individual human genomes

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          Abstract

          DNA double-strand breaks (DSBs) are introduced in meiosis to initiate recombination and generate crossovers, the reciprocal exchanges of genetic material between parental chromosomes. Here we present high-resolution maps of meiotic DSBs in individual human genomes. Comparing DSB maps between individuals shows that along with DNA binding by PRDM9, additional factors may dictate the efficiency of DSB formation. We find evidence for both GC-biased gene conversion and mutagenesis around meiotic DSB hotspots, while frequent co-localization of DSB hotspots with chromosome rearrangement breakpoints implicates the aberrant repair of meiotic DSBs in genomic disorders. Furthermore, our data indicate that DSB frequency is a major determinant of crossover rate. These maps provide new insights into the regulation of meiotic recombination and the impact of meiotic recombination on genome function.

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          A clustering approach for identification of enriched domains from histone modification ChIP-Seq data.

          Chongzhi Zang, Dustin E. Schones, Chen Zeng … (2009)
          Chromatin states are the key to gene regulation and cell identity. Chromatin immunoprecipitation (ChIP) coupled with high-throughput sequencing (ChIP-Seq) is increasingly being used to map epigenetic states across genomes of diverse species. Chromatin modification profiles are frequently noisy and diffuse, spanning regions ranging from several nucleosomes to large domains of multiple genes. Much of the early work on the identification of ChIP-enriched regions for ChIP-Seq data has focused on identifying localized regions, such as transcription factor binding sites. Bioinformatic tools to identify diffuse domains of ChIP-enriched regions have been lacking. Based on the biological observation that histone modifications tend to cluster to form domains, we present a method that identifies spatial clusters of signals unlikely to appear by chance. This method pools together enrichment information from neighboring nucleosomes to increase sensitivity and specificity. By using genomic-scale analysis, as well as the examination of loci with validated epigenetic states, we demonstrate that this method outperforms existing methods in the identification of ChIP-enriched signals for histone modification profiles. We demonstrate the application of this unbiased method in important issues in ChIP-Seq data analysis, such as data normalization for quantitative comparison of levels of epigenetic modifications across cell types and growth conditions. http://home.gwu.edu/ approximately wpeng/Software.htm. Supplementary data are available at Bioinformatics online.
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            The fine-scale structure of recombination rate variation in the human genome.

            Gilean McVean, Simon Myers, Sarah Hunt … (2004)
            The nature and scale of recombination rate variation are largely unknown for most species. In humans, pedigree analysis has documented variation at the chromosomal level, and sperm studies have identified specific hotspots in which crossing-over events cluster. To address whether this picture is representative of the genome as a whole, we have developed and validated a method for estimating recombination rates from patterns of genetic variation. From extensive single-nucleotide polymorphism surveys in European and African populations, we find evidence for extreme local rate variation spanning four orders in magnitude, in which 50% of all recombination events take place in less than 10% of the sequence. We demonstrate that recombination hotspots are a ubiquitous feature of the human genome, occurring on average every 200 kilobases or less, but recombination occurs preferentially outside genes.
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              Biased gene conversion and the evolution of mammalian genomic landscapes.

              Laurent Duret, Nicolas Galtier (2009)
              Recombination is typically thought of as a symmetrical process resulting in large-scale reciprocal genetic exchanges between homologous chromosomes. Recombination events, however, are also accompanied by short-scale, unidirectional exchanges known as gene conversion in the neighborhood of the initiating double-strand break. A large body of evidence suggests that gene conversion is GC-biased in many eukaryotes, including mammals and human. AT/GC heterozygotes produce more GC- than AT-gametes, thus conferring a population advantage to GC-alleles in high-recombining regions. This apparently unimportant feature of our molecular machinery has major evolutionary consequences. Structurally, GC-biased gene conversion explains the spatial distribution of GC-content in mammalian genomes-the so-called isochore structure. Functionally, GC-biased gene conversion promotes the segregation and fixation of deleterious AT --> GC mutations, thus increasing our genomic mutation load. Here we review the recent evidence for a GC-biased gene conversion process in mammals, and its consequences for genomic landscapes, molecular evolution, and human functional genomics.
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                Author and article information

                Journal
                Journal ID (nlm-journal-id): 0404511
                Journal ID (pubmed-jr-id): 7473
                Journal ID (nlm-ta): Science
                Journal ID (iso-abbrev): Science
                Title: Science (New York, N.Y.)
                ISSN (Print): 0036-8075
                ISSN (Electronic): 1095-9203
                Publication date Nihms-submitted: 11 August 2017
                Publication date (Print): 14 November 2014
                Publication date PMC-release: 07 September 2017
                Volume: 346
                Issue: 6211
                Page: 1256442
                Affiliations
                [1 ]National Institute of Diabetes, Digestive and Kidney Diseases, NIH, Bethesda, MD, USA
                [2 ]Department of Biochemistry and Molecular Biology, Uniformed Services University of Health Sciences, Bethesda, MD, USA
                Author notes
                [3]

                Present address: Inserm UMR1085-Irset, 263 ave du Général Leclerc, 35042, Rennes, France

                [*]

                These authors contributed equally to this work

                Article
                Accession ID: PMC5588152 Pmcid ID: PMC5588152 Pmc-uid ID: 5588152 Manuscript ID: nihpa898614
                DOI: 10.1126/science.1256442
                PMC ID: 5588152
                PubMed ID: 25395542
                SO-VID: f8c08ed6-ffaf-4f8b-bbd8-f3ff55287a33
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