Author
John W. Belmont
Other affiliations: Boston Children's Hospital, University of Texas MD Anderson Cancer Center, United States Department of Veterans Affairs ...read more
Bio: John W. Belmont is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Population & Exome sequencing. The author has an hindex of 76, co-authored 273 publications receiving 39393 citations. Previous affiliations of John W. Belmont include Boston Children's Hospital & University of Texas MD Anderson Cancer Center.
Papers published on a yearly basis
Papers
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Baylor College of Medicine1, Chinese Academy of Sciences2, Chinese National Human Genome Center3, University of Hong Kong4, The Chinese University of Hong Kong5, Hong Kong University of Science and Technology6, Illumina7, McGill University8, Washington University in St. Louis9, University of California, San Francisco10, Wellcome Trust Sanger Institute11, Beijing Normal University12, Health Sciences University of Hokkaido13, Shinshu University14, University of Tsukuba15, Howard University16, University of Ibadan17, Case Western Reserve University18, University of Utah19, Cold Spring Harbor Laboratory20, Johns Hopkins University21, University of Oxford22, North Carolina State University23, National Institutes of Health24, Massachusetts Institute of Technology25, Chinese Academy of Social Sciences26, Kyoto University27, Nagasaki University28, Wellcome Trust29, Genome Canada30, Foundation for the National Institutes of Health31, University of Maryland, Baltimore32, Vanderbilt University33, Stanford University34, New York University35, University of California, Berkeley36, University of Oklahoma37, University of New Mexico38, Université de Montréal39, University of California, Los Angeles40, University of Michigan41, University of Wisconsin-Madison42, London School of Economics and Political Science43, Genetic Alliance44, GlaxoSmithKline45, University of Washington46, Harvard University47, University of Chicago48, Fred Hutchinson Cancer Research Center49, University of Tokyo50
TL;DR: The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance the ability to choose targets for therapeutic intervention.
Abstract: The goal of the International HapMap Project is to determine the common patterns of DNA sequence variation in the human genome and to make this information freely available in the public domain. An international consortium is developing a map of these patterns across the genome by determining the genotypes of one million or more sequence variants, their frequencies and the degree of association between them, in DNA samples from populations with ancestry from parts of Africa, Asia and Europe. The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance our ability to choose targets for therapeutic intervention.
5,926 citations
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27 Oct 2005
TL;DR: A public database of common variation in the human genome: more than one million single nucleotide polymorphisms for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations, including ten 500-kilobase regions in which essentially all information about common DNA variation has been extracted.
Abstract: Inherited genetic variation has a critical but as yet largely uncharacterized role in human disease. Here we report a public database of common variation in the human genome: more than one million single nucleotide polymorphisms (SNPs) for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations, including ten 500-kilobase regions in which essentially all information about common DNA variation has been extracted. These data document the generality of recombination hotspots, a block-like structure of linkage disequilibrium and low haplotype diversity, leading to substantial correlations of SNPs with many of their neighbours. We show how the HapMap resource can guide the design and analysis of genetic association studies, shed light on structural variation and recombination, and identify loci that may have been subject to natural selection during human evolution.
5,479 citations
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TL;DR: The Phase II HapMap is described, which characterizes over 3.1 million human single nucleotide polymorphisms genotyped in 270 individuals from four geographically diverse populations and includes 25–35% of common SNP variation in the populations surveyed, and increased differentiation at non-synonymous, compared to synonymous, SNPs is demonstrated.
Abstract: We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.
4,565 citations
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Pardis C. Sabeti1, Pardis C. Sabeti2, Patrick Varilly1, Patrick Varilly2 +255 more•Institutions (50)
TL;DR: ‘Long-range haplotype’ methods, which were developed to identify alleles segregating in a population that have undergone recent selection, and new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population are developed.
Abstract: With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2). We used 'long-range haplotype' methods, which were developed to identify alleles segregating in a population that have undergone recent selection, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population:LARGE and DMD, both related to infection by the Lassa virus, in West Africa;SLC24A5 and SLC45A2, both involved in skin pigmentation, in Europe; and EDAR and EDA2R, both involved in development of hair follicles, in Asia.
1,778 citations
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TL;DR: The human androgen-receptor gene (HUMARA) contains a highly polymorphic trinucleotide repeat in the first exon that correlates with X inactivation, and the development of a PCR assay that distinguishes between the maternal and paternal alleles and identifies their methylation status is developed.
Abstract: The human androgen-receptor gene (HUMARA; GenBank) contains a highly polymorphic trinucleotide repeat in the first exon. We have found that the methylation of HpaII and HhaI sites less than 100 bp away from this polymorphic short tandem repeat (STR) correlates with X inactivation. The close proximity of the restriction-enzyme sites to the STR allows the development of a PCR assay that distinguishes between the maternal and paternal alleles and identifies their methylation status. The accuracy of this assay was tested on (a) DNA from hamster/human hybrid cell lines containing either an active or inactive human X chromosome; (b) DNA from normal males and females; and (c) DNA from females showing nonrandom patterns of X inactivation. Data obtained using this assay correlated substantially with those obtained using the PGK, HPRT, and M27 beta probes, which detect X inactivation patterns by Southern blot analysis. In order to demonstrate one application of this assay, we examined X inactivation patterns in the B lymphocytes of potential and obligate carriers of X-linked agammaglobulinemia.
1,659 citations
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TL;DR: The GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
Abstract: Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS—the 1000 Genome pilot alone includes nearly five terabases—make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
20,557 citations
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TL;DR: Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface.
Abstract: Summary: Research over the last few years has revealed significant haplotype structure in the human genome. The characterization of these patterns, particularly in the context of medical genetic association studies, is becoming a routine research activity. Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface.
Availability: http://www.broad.mit.edu/mpg/haploview/
Contact: jcbarret@broad.mit.edu
13,862 citations
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TL;DR: Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets, including visualizing sliding window results integrated with available genome annotations in the UCSC browser.
Abstract: Motivation: DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser.
Availability: Freely available to academic users from: http://www.ub.edu/dnasp
Contact: [email protected]
13,511 citations
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TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
12,661 citations
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TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.
11,521 citations