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Ankit Malhotra

Bio: Ankit Malhotra is an academic researcher from University of Virginia. The author has contributed to research in topics: Structural variation & Genomics. The author has an hindex of 17, co-authored 27 publications receiving 20446 citations.

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
14 Jun 2007-Nature
TL;DR: Functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project are reported, providing convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts.
Abstract: We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.

5,091 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

Journal ArticleDOI
Peter H. Sudmant1, Tobias Rausch, Eugene J. Gardner2, Robert E. Handsaker3, Robert E. Handsaker4, Alexej Abyzov5, John Huddleston1, Yan Zhang6, Kai Ye7, Goo Jun8, Goo Jun9, Markus His Yang Fritz, Miriam K. Konkel10, Ankit Malhotra, Adrian M. Stütz, Xinghua Shi11, Francesco Paolo Casale12, Jieming Chen6, Fereydoun Hormozdiari1, Gargi Dayama9, Ken Chen13, Maika Malig1, Mark Chaisson1, Klaudia Walter12, Sascha Meiers, Seva Kashin3, Seva Kashin4, Erik Garrison14, Adam Auton15, Hugo Y. K. Lam, Xinmeng Jasmine Mu6, Xinmeng Jasmine Mu3, Can Alkan16, Danny Antaki17, Taejeong Bae5, Eliza Cerveira, Peter S. Chines18, Zechen Chong13, Laura Clarke12, Elif Dal16, Li Ding7, S. Emery9, Xian Fan13, Madhusudan Gujral17, Fatma Kahveci16, Jeffrey M. Kidd9, Yu Kong15, Eric-Wubbo Lameijer19, Shane A. McCarthy12, Paul Flicek12, Richard A. Gibbs20, Gabor T. Marth14, Christopher E. Mason21, Androniki Menelaou22, Androniki Menelaou23, Donna M. Muzny24, Bradley J. Nelson1, Amina Noor17, Nicholas F. Parrish25, Matthew Pendleton24, Andrew Quitadamo11, Benjamin Raeder, Eric E. Schadt24, Mallory Romanovitch, Andreas Schlattl, Robert Sebra24, Andrey A. Shabalin26, Andreas Untergasser27, Jerilyn A. Walker10, Min Wang20, Fuli Yu20, Chengsheng Zhang, Jing Zhang6, Xiangqun Zheng-Bradley12, Wanding Zhou13, Thomas Zichner, Jonathan Sebat17, Mark A. Batzer10, Steven A. McCarroll3, Steven A. McCarroll4, Ryan E. Mills9, Mark Gerstein6, Ali Bashir24, Oliver Stegle12, Scott E. Devine2, Charles Lee28, Evan E. Eichler1, Jan O. Korbel12 
01 Oct 2015-Nature
TL;DR: In this paper, the authors describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which are constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations.
Abstract: Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

1,971 citations

Journal ArticleDOI
TL;DR: The data suggest that tRFs are not random by-products of tRNA degradation or biogenesis, but an abundant and novel class of short RNAs with precise sequence structure that have specific expression patterns and specific biological roles.
Abstract: New types of small RNAs distinct from microRNAs (miRNAs) are progressively being discovered in various organisms. In order to discover such novel small RNAs, a library of 17- to 26-base-long RNAs was created from prostate cancer cell lines and sequenced by ultra-high-throughput sequencing. A significant number of the sequences are derived from precise processing at the 5' or 3' end of mature or precursor tRNAs to form three series of tRFs (tRNA-derived RNA fragments): the tRF-5, tRF-3, and tRF-1 series. These sequences constitute a class of short RNAs that are second most abundant to miRNAs. Northern hybridization, quantitative RT-PCR, and splinted ligation assays independently measured the levels of at least 17 tRFs. To demonstrate the biological importance of tRFs, we further investigated tRF-1001, derived from the 3' end of a Ser-TGA tRNA precursor transcript that is not retained in the mature tRNA. tRF-1001 is expressed highly in a wide range of cancer cell lines but much less in tissues, and its expression in cell lines was tightly correlated with cell proliferation. siRNA-mediated knockdown of tRF-1001 impaired cell proliferation with the specific accumulation of cells in G2, phenotypes that were reversed specifically by cointroducing a synthetic 2'-O-methyl tRF-1001 oligoribonucleotide resistant to the siRNA. tRF-1001 is generated in the cytoplasm by tRNA 3'-endonuclease ELAC2, a prostate cancer susceptibility gene. Our data suggest that tRFs are not random by-products of tRNA degradation or biogenesis, but an abundant and novel class of short RNAs with precise sequence structure that have specific expression patterns and specific biological roles.

923 citations


Cited by
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Journal ArticleDOI
06 Sep 2012-Nature
TL;DR: The Encyclopedia of DNA Elements project provides new insights into the organization and regulation of the authors' genes and genome, and is an expansive resource of functional annotations for biomedical research.
Abstract: The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.

13,548 citations

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
21 Dec 2007-Science
TL;DR: This article showed that OCT4, SOX2, NANOG, and LIN28 factors are sufficient to reprogram human somatic cells to pluripotent stem cells that exhibit the essential characteristics of embryonic stem (ES) cells.
Abstract: Somatic cell nuclear transfer allows trans-acting factors present in the mammalian oocyte to reprogram somatic cell nuclei to an undifferentiated state. We show that four factors (OCT4, SOX2, NANOG, and LIN28) are sufficient to reprogram human somatic cells to pluripotent stem cells that exhibit the essential characteristics of embryonic stem (ES) cells. These induced pluripotent human stem cells have normal karyotypes, express telomerase activity, express cell surface markers and genes that characterize human ES cells, and maintain the developmental potential to differentiate into advanced derivatives of all three primary germ layers. Such induced pluripotent human cell lines should be useful in the production of new disease models and in drug development, as well as for applications in transplantation medicine, once technical limitations (for example, mutation through viral integration) are eliminated.

9,836 citations

Journal ArticleDOI
23 Jan 2015-Science
TL;DR: In this paper, a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level.
Abstract: Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

9,745 citations

Journal ArticleDOI
Monkol Lek, Konrad J. Karczewski1, Konrad J. Karczewski2, Eric Vallabh Minikel1, Eric Vallabh Minikel2, Kaitlin E. Samocha, Eric Banks2, Timothy Fennell2, Anne H. O’Donnell-Luria1, Anne H. O’Donnell-Luria2, Anne H. O’Donnell-Luria3, James S. Ware, Andrew J. Hill4, Andrew J. Hill1, Andrew J. Hill2, Beryl B. Cummings2, Beryl B. Cummings1, Taru Tukiainen2, Taru Tukiainen1, Daniel P. Birnbaum2, Jack A. Kosmicki, Laramie E. Duncan2, Laramie E. Duncan1, Karol Estrada2, Karol Estrada1, Fengmei Zhao2, Fengmei Zhao1, James Zou2, Emma Pierce-Hoffman1, Emma Pierce-Hoffman2, Joanne Berghout5, David Neil Cooper6, Nicole A. Deflaux7, Mark A. DePristo2, Ron Do, Jason Flannick1, Jason Flannick2, Menachem Fromer, Laura D. Gauthier2, Jackie Goldstein1, Jackie Goldstein2, Namrata Gupta2, Daniel P. Howrigan2, Daniel P. Howrigan1, Adam Kiezun2, Mitja I. Kurki1, Mitja I. Kurki2, Ami Levy Moonshine2, Pradeep Natarajan, Lorena Orozco, Gina M. Peloso1, Gina M. Peloso2, Ryan Poplin2, Manuel A. Rivas2, Valentin Ruano-Rubio2, Samuel A. Rose2, Douglas M. Ruderfer8, Khalid Shakir2, Peter D. Stenson6, Christine Stevens2, Brett Thomas1, Brett Thomas2, Grace Tiao2, María Teresa Tusié-Luna, Ben Weisburd2, Hong-Hee Won9, Dongmei Yu, David Altshuler2, David Altshuler10, Diego Ardissino, Michael Boehnke11, John Danesh12, Stacey Donnelly2, Roberto Elosua, Jose C. Florez1, Jose C. Florez2, Stacey Gabriel2, Gad Getz1, Gad Getz2, Stephen J. Glatt13, Christina M. Hultman14, Sekar Kathiresan, Markku Laakso15, Steven A. McCarroll2, Steven A. McCarroll1, 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. Daly2, Mark J. Daly1, Daniel G. MacArthur2, Daniel G. MacArthur1 
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