Evolutionary and Biomedical Insights from the Rhesus Macaque Genome

doi:10.1126/science.1139247

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Science 13 April 2007:
Vol. 316. no. 5822, pp. 222 - 234
DOI: 10.1126/science.1139247

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Research Articles

Evolutionary and Biomedical Insights from the Rhesus Macaque Genome

Rhesus Macaque Genome Sequencing and Analysis Consortium^*, Richard A. Gibbs¹^,2, Jeffrey Rogers³, Michael G. Katze⁴, Roger Bumgarner⁴, George M. Weinstock¹^,2, Elaine R. Mardis⁵, Karin A. Remington⁶, Robert L. Strausberg⁶, J. Craig Venter⁶, Richard K. Wilson⁵, Mark A. Batzer⁷, Carlos D. Bustamante⁸, Evan E. Eichler⁹, Matthew W. Hahn¹⁰, Ross C. Hardison¹¹, Kateryna D. Makova¹¹, Webb Miller¹¹, Aleksandar Milosavljevic¹^,2, Robert E. Palermo⁴, Adam Siepel⁸, James M. Sikela¹², Tony Attaway¹^,2, Stephanie Bell¹^,2, Kelly E. Bernard⁵, Christian J. Buhay¹^,2, Mimi N. Chandrabose¹^,2, Marvin Dao¹^,2, Clay Davis¹^,2, Kimberly D. Delehaunty⁵, Yan Ding¹^,2, Huyen H. Dinh¹^,2, Shannon Dugan-Rocha¹^,2, Lucinda A. Fulton⁵, Ramatu Ayiesha Gabisi¹^,2, Toni T. Garner¹^,2, Jennifer Godfrey⁵, Alicia C. Hawes¹^,2, Judith Hernandez¹^,2, Sandra Hines¹^,2, Michael Holder¹^,2, Jennifer Hume¹^,2, Shalini N. Jhangiani¹^,2, Vandita Joshi¹^,2, Ziad Mohid Khan¹^,2, Ewen F. Kirkness⁶, Andrew Cree¹^,2, R. Gerald Fowler¹^,2, Sandra Lee¹^,2, Lora R. Lewis¹^,2, Zhangwan Li¹^,2, Yih-shin Liu¹^,2, Stephanie M. Moore¹^,2, Donna Muzny¹^,2, Lynne V. Nazareth¹^,2, Dinh Ngoc Ngo¹^,2, Geoffrey O. Okwuonu¹^,2, Grace Pai⁶, David Parker¹^,2, Heidie A. Paul¹^,2, Cynthia Pfannkoch⁶, Craig S. Pohl⁵, Yu-Hui Rogers⁶, San Juana Ruiz¹^,2, Aniko Sabo¹^,2, Jireh Santibanez¹^,2, Brian W. Schneider¹^,2, Scott M. Smith⁵, Erica Sodergren¹^,2, Amanda F. Svatek¹^,2, Teresa R. Utterback¹^,2, Selina Vattathil¹^,2, Wesley Warren⁵, Courtney Sherell White¹^,2, Asif T. Chinwalla⁵, Yucheng Feng⁵, Aaron L. Halpern⁶, LaDeana W. Hillier⁵, Xiaoqiu Huang¹³, Pat Minx⁵, Joanne O. Nelson⁵, Kymberlie H. Pepin⁵, Xiang Qin¹^,2, Granger G. Sutton⁶, Eli Venter⁶, Brian P. Walenz⁶, John W. Wallis⁵, Kim C. Worley¹^,2, Shiaw-Pyng Yang⁵, Steven M. Jones¹⁴, Marco A. Marra¹⁴, Mariano Rocchi¹⁵, Jacqueline E. Schein¹⁴, Robert Baertsch¹⁶, Laura Clarke¹⁷, Miklós Csürös¹⁸, Jarret Glasscock⁵, R. Alan Harris¹^,2, Paul Havlak¹^,2, Andrew R. Jackson¹^,2, Huaiyang Jiang¹^,2, Yue Liu¹^,2, David N. Messina⁵, Yufeng Shen¹^,2, Henry Xing-Zhi Song¹^,2, Todd Wylie⁵, Lan Zhang¹^,2, Ewan Birney¹⁷, Kyudong Han⁷, Miriam K. Konkel⁷, Jungnam Lee⁷, Arian F. A. Smit¹⁹, Brygg Ullmer²⁰, Hui Wang⁷, Jinchuan Xing⁷^,21, Richard Burhans¹¹, Ze Cheng⁹, John E. Karro¹¹, Jian Ma²², Brian Raney²², Xinwei She⁹, Michael J. Cox¹², Jeffery P. Demuth¹⁰, Laura J. Dumas¹², Sang-Gook Han¹⁰, Janet Hopkins¹², Anis Karimpour-Fard²³, Young H. Kim²⁴, Jonathan R. Pollack²⁴, Tomas Vinar⁸, Charles Addo-Quaye¹¹, Jeremiah Degenhardt⁸, Alexandra Denby⁸, Melissa J. Hubisz²⁵, Amit Indap⁸, Carolin Kosiol⁸, Bruce T. Lahn²⁵^,26, Heather A. Lawson¹¹, Alison Marklein⁸, Rasmus Nielsen²⁷, Eric J. Vallender²⁵^,26, Andrew G. Clark²⁸, Betsy Ferguson²⁹, Ryan D. Hernandez⁸, Kashif Hirani¹^,2, Hildegard Kehrer-Sawatzki³⁰, Jessica Kolb³⁰, Shobha Patil¹^,2, Ling-Ling Pu¹^,2, Yanru Ren¹^,2, David Glenn Smith³, David A. Wheeler¹^,2, Ian Schenck¹¹, Edward V. Ball³¹, Rui Chen¹^,2, David N. Cooper³¹, Belinda Giardine¹¹, Fan Hsu²², W. James Kent²², Arthur Lesk¹¹, David L. Nelson², William E. O'Brien², Kay Prüfer³², Peter D. Stenson³¹, James C. Wallace⁴, Hui Ke³³, Xiao-Ming Liu³⁴, Peng Wang³³, Andy Peng Xiang³³, Fan Yang³³, Galt P. Barber²², David Haussler³⁵^,16, Donna Karolchik²², Andy D. Kern²², Robert M. Kuhn²², Kayla E. Smith²², Ann S. Zwieg²²

¹ Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA.
² Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
³ Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, TX 78227, USA.
⁴ Department of Microbiology, University of Washington, Seattle, WA 98195, USA.
⁵ Genome Sequencing Center, Washington University, St. Louis, MO 63108, USA.
⁶ J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, USA.
⁷ Department of Biological Sciences, Biological Computation and Visualization Center, Center for BioModular Multi-scale Systems, Louisiana State University, Baton Rouge, LA 70803, USA.
⁸ Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA.
⁹ Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
¹⁰ Department of Biology and School of Informatics, Indiana University, Bloomington, IN 47405, USA.
¹¹ Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, University Park, PA 16802, USA.
¹² Human Medical Genetics and Neuroscience Programs, Department of Pharmacology, University of Colorado at Denver and Health Sciences Center, Aurora, CO 80045, USA.
¹³ Department of Computer Science, Iowa State University, Ames, IA 50011, USA.
¹⁴ Genome Sciences Centre, British Columbia Cancer Agency, 570 West 7th Avenue, Vancouver, BC, Canada.
¹⁵ Department of Genetics and Microbiology, University of Bari, Bari, Italy.
¹⁶ Department of Bioinformatics, University of California Santa Cruz, Santa Cruz, CA 95060, USA.
¹⁷ The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK.
¹⁸ Département d'Informatique et de Recherche Opérationnelle, Université de Montréal, Montréal, QC H3C 3J7, Canada.
¹⁹ Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103–8904, USA.
²⁰ Center for Computation and Technology, Department of Computer Sciences, Louisiana State University, Baton Rouge, LA 70803, USA.
²¹ Eccles Institute of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA.
²² Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.
²³ Department of Preventative Medicine and Biometrics, University of Colorado at Denver and Health Sciences Center, Aurora, CO 80045, USA.
²⁴ Department of Pathology, Stanford University, Stanford, CA 94305, USA.
²⁵ Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.
²⁶ Howard Hughes Medical Institute, Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.
²⁷ Institute of Biology, University of Copenhagen, Copenhagen DK-1017, Denmark.
²⁸ Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA.
²⁹ Genetics Research and Informatics Program, Oregon National Primate Research Center, Beaverton, OR 97006, USA.
³⁰ Institute of Human Genetics, University of Ulm, Ulm, 89081, Germany.
³¹ Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff, CF14 4XN, UK.
³² Department Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, 04103, Germany.
³³ Centre for Stem Cell Biology and Tissue Engineering, Sun Yat-sen University, Guangzhou 510080, China.
³⁴ South-China Primate Research and Development Center, Guangzhou 510080, China.
³⁵ Howard Hughes Medical Institute, Santa Cruz, CA 95060, USA.

Fig. 1. Evolutionary triangulation in the human, chimpanzee and rhesus macaque lineages (lineage-specific breaks), showing a summary of chromosomal breakpoints on a microscopic scale (Fig. 3) (7). Circled numbers indicate numbers of lineage-specific breaks. [View Larger Version of this Image (47K GIF file)]

Fig. 2. Assembly by three methods of the rhesus macaque genome. WGS, whole-genome shotgun. BCM-HGSC, Baylor College of Medicine Human Genome Sequencing Center; WashU-GSC, Washington University Genome Sequencing Center; JCVI, J. Craig Venter Institute. QA/QC, quality assurance and quality control. [View Larger Version of this Image (27K GIF file)]

Fig. 3. Chromosomal breakpoints between rhesus macaque and the human-chimpanzee ancestor. Each chromosome is represented by a white bar (left) and a colored bar (right). A total of 820 thin horizontal lines in the white bars represent submicroscopic breakpoints (10-kbp to 4-Mbp range) detected by genomic triangulation (19), and 43 thick black lines in the colored bars represent breakpoints on a microscopic scale (>4 Mbp) (7). Numbers above each bar show the total lines within the bar. [View Larger Version of this Image (27K GIF file)]

Fig. 4. Global pattern of macaque segmental duplications. The statistics are based on all WGAC duplications (> 90%, >1 kb in length), whereas the figure displays only those between 90 and 95% sequence identity and >10 kb in length for simplicity. Red lines indicate interchromosomal (Inter) duplications, blue ticks show intrachromosomal (Intra) events, and purple bars show centromeric, acrocentric, and/or large-gap regions. WGAC, whole-genome assembly comparison. nr, nonredundant. [View Larger Version of this Image (56K GIF file)]

Fig. 5. Organization of the PRAME gene cluster in the HCR lineages. (A) Maximum-likelihood phylogeny for PRAME-like genes in the human (H), chimpanzee (P), and rhesus macaque (M) genomes. Colored circles indicate inferred duplication events, partial genes are shown in italics, and branches showing significant evidence of positive selection are colored orange (P values are shown above orange lines). Scale bar, 0.05 substitutions per site. (B) Another view of the same phylogeny, showing the duplication history in the context of the species tree (7). [View Larger Version of this Image (23K GIF file)]

Fig. 6. Numbers of human genes passing successive filters in the orthology analysis pipeline. Genes are required to fall in regions of large-scale synteny between genomes, to have completely aligned coding regions, not to have frame-shift indels or altered gene structures, and not to show signs of recent duplication. [View Larger Version of this Image (21K GIF file)]

Fig. 7. Distributions of ${omega}$ in primates versus rodents. Histogram of estimates of ${omega}$ = dN/dS for human, chimpanzee, and macaque versus estimates for mouse and rat in 5641 orthologous quintets, showing a pronounced shift toward larger values in primates (P = 2.2 x 10^–16, Mann Whitney test). Genes with dN = 0 or dS = 0 are counted in the relative frequencies but not shown. [View Larger Version of this Image (25K GIF file)]

Fig. 8. SNP within rhesus macaques. (A) SNP densities per kilobase for eight Chinese (blue) and eight Indian (red) individuals in autosomes and the X chromosome. Error bars indicate standard error with variance calculated across individual-chromosome replicates. (B) Distribution of Tajima's D statistic across 166 amplicons for each population (n = 38 for Indian and n = 9 for Chinese individuals). (C) The distribution of the number of haplotypes per haplotype block (determined using the four-gamete test) across five regions. [View Larger Version of this Image (12K GIF file)]

Fig. 9. Ancestral disease mutations. Examples of human mutations that match the sequences of chimp and/or macaque are shown. (A) Genes in which the ancestral allele is now the disease-associated allele in humans. (B) An instance in which the mutant allele in humans is the normal allele in macaque. The amino acid sequences predicted for the boreoeutherian ancestor (65) are given on the top row of each alignment block. Identities are shown as dots and differences are given as letters (73). The position of the mutation in humans is boxed in orange, and the box extends through the relevant comparisons. [View Larger Version of this Image (26K GIF file)]

Fig. 10. Application of rhesus-specific microarrays. A microarray based on the rhesus macaque draft genome was used to analyze gene expression in a macaque model of human influenza infection. Gray bars measure an overall response for indicated functional categories, based on corresponding heat maps, and reveal a significant rebound in expression at day 7 for genes associated with the inflammatory response, when compared to interferon induction. Red, increased expression; green, reduced expression. Details are given in (7, 70). [View Larger Version of this Image (49K GIF file)]