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Christian J. Buhay

Other affiliations: Human Genome Sequencing Center
Bio: Christian J. Buhay is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Genome & Exome sequencing. The author has an hindex of 29, co-authored 33 publications receiving 27910 citations. Previous affiliations of Christian J. Buhay include Human Genome Sequencing Center.

Papers
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Journal ArticleDOI
Curtis Huttenhower1, Curtis Huttenhower2, Dirk Gevers1, Rob Knight3  +250 moreInstitutions (42)
14 Jun 2012-Nature
TL;DR: The Human Microbiome Project Consortium reported the first results of their analysis of microbial communities from distinct, clinically relevant body habitats in a human cohort; the insights into the microbial communities of a healthy population lay foundations for future exploration of the epidemiology, ecology and translational applications of the human microbiome as discussed by the authors.
Abstract: The Human Microbiome Project Consortium reports the first results of their analysis of microbial communities from distinct, clinically relevant body habitats in a human cohort; the insights into the microbial communities of a healthy population lay foundations for future exploration of the epidemiology, ecology and translational applications of the human microbiome.

8,410 citations

Journal Article
TL;DR: The Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far, finding the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals.
Abstract: Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.

6,350 citations

Journal ArticleDOI
Barbara A. Methé1, Karen E. Nelson1, Mihai Pop2, Heather Huot Creasy3  +250 moreInstitutions (42)
14 Jun 2012-Nature
TL;DR: The Human Microbiome Project (HMP) Consortium has established a population-scale framework which catalyzed significant development of metagenomic protocols resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomics data available to the scientific community as mentioned in this paper.
Abstract: A variety of microbial communities and their genes (microbiome) exist throughout the human body, playing fundamental roles in human health and disease. The NIH funded Human Microbiome Project (HMP) Consortium has established a population-scale framework which catalyzed significant development of metagenomic protocols resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 to 18 body sites up to three times, which to date, have generated 5,177 microbial taxonomic profiles from 16S rRNA genes and over 3.5 Tb of metagenomic sequence. In parallel, approximately 800 human-associated reference genomes have been sequenced. Collectively, these data represent the largest resource to date describing the abundance and variety of the human microbiome, while providing a platform for current and future studies.

2,172 citations

Journal ArticleDOI
Andrew V. Biankin1, Andrew V. Biankin2, Andrew V. Biankin3, Nicola Waddell4, Karin S. Kassahn4, Marie-Claude Gingras5, Lakshmi Muthuswamy6, Amber L. Johns2, David Miller4, Peter Wilson4, Ann-Marie Patch4, Jianmin Wu2, David K. Chang2, David K. Chang1, David K. Chang3, Mark J. Cowley2, Brooke Gardiner4, Sarah Song4, Ivon Harliwong4, Senel Idrisoglu4, Craig Nourse4, Ehsan Nourbakhsh4, Suzanne Manning4, Shivangi Wani4, Milena Gongora4, Marina Pajic2, Christopher J. Scarlett2, Christopher J. Scarlett7, Anthony J. Gill8, Anthony J. Gill2, Anthony J. Gill9, Andreia V. Pinho2, Ilse Rooman2, Matthew J. Anderson4, Oliver Holmes4, Conrad Leonard4, Darrin Taylor4, Scott Wood4, Qinying Xu4, Katia Nones4, J. Lynn Fink4, Angelika N. Christ4, Timothy J. C. Bruxner4, Nicole Cloonan4, Gabriel Kolle10, Felicity Newell4, Mark Pinese2, R. Scott Mead2, R. Scott Mead11, Jeremy L. Humphris2, Warren Kaplan2, Marc D. Jones2, Emily K. Colvin2, Adnan Nagrial2, Emily S. Humphrey2, Angela Chou11, Angela Chou2, Venessa T. Chin2, Lorraine A. Chantrill2, Amanda Mawson2, Jaswinder S. Samra9, James G. Kench12, James G. Kench2, James G. Kench8, Jessica A. Lovell2, Roger J. Daly2, Neil D. Merrett8, Neil D. Merrett3, Christopher W. Toon2, Krishna Epari13, Nam Q. Nguyen14, Andrew Barbour4, Nikolajs Zeps15, Nipun Kakkar5, Fengmei Zhao5, Yuan Qing Wu5, Min Wang5, Donna M. Muzny5, William E. Fisher5, F. Charles Brunicardi16, Sally E. Hodges5, Jeffrey G. Reid5, Jennifer Drummond5, Kyle Chang5, Yi Han5, Lora Lewis5, Huyen Dinh5, Christian J. Buhay5, Timothy Beck6, Lee Timms6, Michelle Sam6, Kimberly Begley6, Andrew M.K. Brown6, Deepa Pai6, Ami Panchal6, Nicholas Buchner6, Richard de Borja6, Robert E. Denroche6, Christina K. Yung6, Stefano Serra17, Nicole Onetto6, Debabrata Mukhopadhyay18, Ming-Sound Tsao17, Patricia Shaw17, Gloria M. Petersen18, Steven Gallinger19, Steven Gallinger17, Ralph H. Hruban20, Anirban Maitra20, Christine A. Iacobuzio-Donahue20, Richard D. Schulick20, Christopher L. Wolfgang20, Richard A. Morgan20, Rita T. Lawlor, Paola Capelli21, Vincenzo Corbo, Maria Scardoni21, Giampaolo Tortora, Margaret A. Tempero22, Karen M. Mann23, Nancy A. Jenkins23, Pedro A. Perez-Mancera24, David J. Adams25, David A. Largaespada26, Lodewyk F. A. Wessels27, Alistair G. Rust25, Lincoln Stein6, David A. Tuveson24, Neal G. Copeland23, Elizabeth A. Musgrove2, Elizabeth A. Musgrove1, Aldo Scarpa21, James R. Eshleman20, Thomas J. Hudson6, Robert L. Sutherland1, Robert L. Sutherland2, David A. Wheeler5, John V. Pearson4, John Douglas Mcpherson6, Richard A. Gibbs5, Sean M. Grimmond4 
15 Nov 2012-Nature
TL;DR: It is found that frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, are also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement ofAxon guidance genes in pancreatic carcinogenesis.
Abstract: Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.

1,752 citations

Journal ArticleDOI
13 Apr 2007-Science
TL;DR: The genome sequence of an Indian-origin Macaca mulatta female is determined and compared with chimpanzees and humans to reveal the structure of ancestral primate genomes and to identify evidence for positive selection and lineage-specific expansions and contractions of gene families.
Abstract: The rhesus macaque (Macaca mulatta) is an abundant primate species that diverged from the ancestors of Homo sapiens about 25 million years ago. Because they are genetically and physiologically similar to humans, rhesus monkeys are the most widely used nonhuman primate in basic and applied biomedical research. We determined the genome sequence of an Indian-origin Macaca mulatta female and compared the data with chimpanzees and humans to reveal the structure of ancestral primate genomes and to identify evidence for positive selection and lineage-specific expansions and contractions of gene families. A comparison of sequences from individual animals was used to investigate their underlying genetic diversity. The complete description of the macaque genome blueprint enhances the utility of this animal model for biomedical research and improves our understanding of the basic biology of the species.

1,297 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: The open-source software package DADA2 for modeling and correcting Illumina-sequenced amplicon errors is presented, revealing a diversity of previously undetected Lactobacillus crispatus variants.
Abstract: We present the open-source software package DADA2 for modeling and correcting Illumina-sequenced amplicon errors (https://github.com/benjjneb/dada2). DADA2 infers sample sequences exactly and resolves differences of as little as 1 nucleotide. In several mock communities, DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.

14,505 citations

Journal ArticleDOI
TL;DR: The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% correct bases commonly reported by other methods.
Abstract: Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.

11,329 citations

Journal ArticleDOI
22 Apr 2013-PLOS ONE
TL;DR: The phyloseq project for R is a new open-source software package dedicated to the object-oriented representation and analysis of microbiome census data in R, which supports importing data from a variety of common formats, as well as many analysis techniques.
Abstract: Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.

11,272 citations

Journal ArticleDOI
Curtis Huttenhower1, Curtis Huttenhower2, Dirk Gevers2, Rob Knight3  +250 moreInstitutions (42)
14 Jun 2012-Nature
TL;DR: The Human Microbiome Project Consortium reported the first results of their analysis of microbial communities from distinct, clinically relevant body habitats in a human cohort; the insights into the microbial communities of a healthy population lay foundations for future exploration of the epidemiology, ecology and translational applications of the human microbiome as discussed by the authors.
Abstract: The Human Microbiome Project Consortium reports the first results of their analysis of microbial communities from distinct, clinically relevant body habitats in a human cohort; the insights into the microbial communities of a healthy population lay foundations for future exploration of the epidemiology, ecology and translational applications of the human microbiome.

8,410 citations