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Fengtang Yang

Bio: Fengtang Yang is an academic researcher from Wellcome Trust Sanger Institute. The author has contributed to research in topics: Karyotype & Genome. The author has an hindex of 59, co-authored 256 publications receiving 31481 citations. Previous affiliations of Fengtang Yang include Wellcome Trust & University of Cambridge.


Papers
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Journal ArticleDOI
Adam Auton1, Gonçalo R. Abecasis2, David Altshuler3, Richard Durbin4  +514 moreInstitutions (90)
01 Oct 2015-Nature
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

Journal ArticleDOI
23 Nov 2006-Nature
TL;DR: A first-generation CNV map of the human genome is constructed through the study of 270 individuals from four populations with ancestry in Europe, Africa or Asia, underscoring the importance of CNV in genetic diversity and evolution and the utility of this resource for genetic disease studies.
Abstract: Copy number variation (CNV) of DNA sequences is functionally significant but has yet to be fully ascertained. We have constructed a first-generation CNV map of the human genome through the study of 270 individuals from four populations with ancestry in Europe, Africa or Asia (the HapMap collection). DNA from these individuals was screened for CNV using two complementary technologies: single-nucleotide polymorphism (SNP) genotyping arrays, and clone-based comparative genomic hybridization. A total of 1,447 copy number variable regions (CNVRs), which can encompass overlapping or adjacent gains or losses, covering 360 megabases (12% of the genome) were identified in these populations. These CNVRs contained hundreds of genes, disease loci, functional elements and segmental duplications. Notably, the CNVRs encompassed more nucleotide content per genome than SNPs, underscoring the importance of CNV in genetic diversity and evolution. The data obtained delineate linkage disequilibrium patterns for many CNVs, and reveal marked variation in copy number among populations. We also demonstrate the utility of this resource for genetic disease studies.

4,275 citations

Journal ArticleDOI
Kerstin Howe, Matthew D. Clark, Carlos Torroja1, Carlos Torroja2  +171 moreInstitutions (11)
25 Apr 2013-Nature
TL;DR: A high-quality sequence assembly of the zebrafish genome is generated, made up of an overlapping set of completely sequenced large-insert clones that were ordered and oriented using a high-resolution high-density meiotic map, providing a clearer understanding of key genomic features such as a unique repeat content, a scarcity of pseudogenes, an enrichment of zebra fish-specific genes on chromosome 4 and chromosomal regions that influence sex determination.
Abstract: Zebrafish have become a popular organism for the study of vertebrate gene function. The virtually transparent embryos of this species, and the ability to accelerate genetic studies by gene knockdown or overexpression, have led to the widespread use of zebrafish in the detailed investigation of vertebrate gene function and increasingly, the study of human genetic disease. However, for effective modelling of human genetic disease it is important to understand the extent to which zebrafish genes and gene structures are related to orthologous human genes. To examine this, we generated a high-quality sequence assembly of the zebrafish genome, made up of an overlapping set of completely sequenced large-insert clones that were ordered and oriented using a high-resolution high-density meiotic map. Detailed automatic and manual annotation provides evidence of more than 26,000 protein-coding genes, the largest gene set of any vertebrate so far sequenced. Comparison to the human reference genome shows that approximately 70% of human genes have at least one obvious zebrafish orthologue. In addition, the high quality of this genome assembly provides a clearer understanding of key genomic features such as a unique repeat content, a scarcity of pseudogenes, an enrichment of zebrafish-specific genes on chromosome 4 and chromosomal regions that influence sex determination.

3,573 citations

01 Oct 2015
TL;DR: The 1000 Genomes Project as mentioned in this paper provided a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and reported the 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.
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.

3,247 citations


Cited by
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28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
TL;DR: This work presents Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer, and uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions.
Abstract: We present Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer. MACS empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, and is freely available.

13,008 citations

Journal Article
Fumio Tajima1
30 Oct 1989-Genomics
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

01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

10,124 citations

Journal ArticleDOI
Monkol Lek, Konrad J. Karczewski1, Konrad J. Karczewski2, Eric Vallabh Minikel1, Eric Vallabh Minikel2, Kaitlin E. Samocha, Eric Banks1, Timothy Fennell1, Anne H. O’Donnell-Luria3, Anne H. O’Donnell-Luria1, Anne H. O’Donnell-Luria2, James S. Ware, Andrew J. Hill2, Andrew J. Hill4, Andrew J. Hill1, Beryl B. Cummings1, Beryl B. Cummings2, Taru Tukiainen2, Taru Tukiainen1, Daniel P. Birnbaum1, Jack A. Kosmicki, Laramie E. Duncan1, Laramie E. Duncan2, Karol Estrada1, Karol Estrada2, Fengmei Zhao1, Fengmei Zhao2, James Zou1, Emma Pierce-Hoffman2, Emma Pierce-Hoffman1, Joanne Berghout5, David Neil Cooper6, Nicole A. Deflaux7, Mark A. DePristo1, Ron Do, Jason Flannick1, Jason Flannick2, Menachem Fromer, Laura D. Gauthier1, Jackie Goldstein2, Jackie Goldstein1, Namrata Gupta1, Daniel P. Howrigan2, Daniel P. Howrigan1, Adam Kiezun1, Mitja I. Kurki2, Mitja I. Kurki1, Ami Levy Moonshine1, Pradeep Natarajan, Lorena Orozco, Gina M. Peloso1, Gina M. Peloso2, Ryan Poplin1, Manuel A. Rivas1, Valentin Ruano-Rubio1, Samuel A. Rose1, Douglas M. Ruderfer8, Khalid Shakir1, Peter D. Stenson6, Christine Stevens1, Brett Thomas1, Brett Thomas2, Grace Tiao1, María Teresa Tusié-Luna, Ben Weisburd1, Hong-Hee Won9, Dongmei Yu, David Altshuler1, David Altshuler10, Diego Ardissino, Michael Boehnke11, John Danesh12, Stacey Donnelly1, Roberto Elosua, Jose C. Florez2, Jose C. Florez1, Stacey Gabriel1, Gad Getz1, Gad Getz2, Stephen J. Glatt13, Christina M. Hultman14, Sekar Kathiresan, Markku Laakso15, Steven A. McCarroll1, Steven A. McCarroll2, Mark I. McCarthy16, Mark I. McCarthy17, Dermot P.B. McGovern18, Ruth McPherson19, Benjamin M. Neale1, Benjamin M. Neale2, Aarno Palotie, Shaun Purcell8, Danish Saleheen20, Jeremiah M. Scharf, Pamela Sklar, Patrick F. Sullivan14, Patrick F. Sullivan21, Jaakko Tuomilehto22, Ming T. Tsuang23, Hugh Watkins16, Hugh Watkins17, James G. Wilson24, Mark J. Daly1, Mark J. Daly2, Daniel G. MacArthur1, Daniel G. MacArthur2 
18 Aug 2016-Nature
TL;DR: The aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC) provides direct evidence for the presence of widespread mutational recurrence.
Abstract: Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

8,758 citations