Large scale comparison of global gene expression patterns in human and mouse
TLDR
The results indicate that the global patterns of tissue-specific expression of orthologous genes are conserved in human and mouse.Abstract:
It is widely accepted that orthologous genes between species are conserved at the sequence level and perform similar functions in different organisms. However, the level of conservation of gene expression patterns of the orthologous genes in different species has been unclear. To address the issue, we compared gene expression of orthologous genes based on 2,557 human and 1,267 mouse samples with high quality gene expression data, selected from experiments stored in the public microarray repository ArrayExpress. In a principal component analysis (PCA) of combined data from human and mouse samples merged on orthologous probesets, samples largely form distinctive clusters based on their tissue sources when projected onto the top principal components. The most prominent groups are the nervous system, muscle/heart tissues, liver and cell lines. Despite the great differences in sample characteristics and experiment conditions, the overall patterns of these prominent clusters are strikingly similar for human and mouse. We further analyzed data for each tissue separately and found that the most variable genes in each tissue are highly enriched with human-mouse tissue-specific orthologs and the least variable genes in each tissue are enriched with human-mouse housekeeping orthologs. The results indicate that the global patterns of tissue-specific expression of orthologous genes are conserved in human and mouse. The expression of groups of orthologous genes co-varies in the two species, both for the most variable genes and the most ubiquitously expressed genes.read more
Citations
More filters
Singular Value Decomposition for Genome-Wide Expression Data Processing and Modeling
TL;DR: Using singular value decomposition in transforming genome-wide expression data from genes x arrays space to reduced diagonalized "eigengenes" x "eigenarrays" space gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype.
Journal ArticleDOI
Reuse of public genome-wide gene expression data
Johan Rung,Alvis Brazma +1 more
TL;DR: The utility of the gene expression data that are in the public domain and how researchers are making use of these data are discussed and recommendations are provided that can improve the utility of such data.
Journal ArticleDOI
PhenomeNET: a whole-phenome approach to disease gene discovery
TL;DR: It is demonstrated that PhenomeNET can identify orthologous genes, genes involved in the same pathway and gene–disease associations through the comparison of mutant phenotypes, and is applied to prioritize genes for rare and orphan diseases for which the molecular basis is unknown.
Journal ArticleDOI
Gene Expression Atlas update—a value-added database of microarray and sequencing-based functional genomics experiments
Misha Kapushesky,Tomasz Adamusiak,Tony Burdett,Aedín C. Culhane,Anna Farne,Alexey Filippov,Ele Holloway,Andrey Klebanov,Nataliya Kryvych,Natalja Kurbatova,Pavel Kurnosov,James Malone,Olga Melnichuk,Robert Petryszak,Nikolay Pultsin,Gabriella Rustici,Andrew Tikhonov,Ravensara S. Travillian,Eleanor Williams,Andrey Zorin,Helen Parkinson,Alvis Brazma +21 more
TL;DR: The Gene Expression Atlas is an added-value database providing information about gene expression in different cell types, organism parts, developmental stages, disease states, sample treatments and other biological/experimental conditions.
Journal ArticleDOI
Comparative transcriptomics in human and mouse
TL;DR: Cross-species comparisons of genomes, transcriptomes and gene regulation are now feasible at unprecedented resolution and throughput, enabling the comparison of human and mouse biology at the molecular level.
References
More filters
Journal ArticleDOI
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
Aravind Subramanian,Pablo Tamayo,Vamsi K. Mootha,Sayan Mukherjee,Benjamin L. Ebert,Michael A. Gillette,Amanda G. Paulovich,Scott L. Pomeroy,Todd R. Golub,Eric S. Lander,Jill P. Mesirov +10 more
TL;DR: The Gene Set Enrichment Analysis (GSEA) method as discussed by the authors focuses on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation.
Journal ArticleDOI
Exploration, normalization, and summaries of high density oligonucleotide array probe level data
Rafael A. Irizarry,Bridget G. Hobbs,Francois Collin,Yasmin Beazer-Barclay,Kristen J. Antonellis,Uwe Scherf,Terence P. Speed +6 more
TL;DR: There is no obvious downside to using RMA and attaching a standard error (SE) to this quantity using a linear model which removes probe-specific affinities, and the exploratory data analyses of the probe level data motivate a new summary measure that is a robust multi-array average (RMA) of background-adjusted, normalized, and log-transformed PM values.
Journal ArticleDOI
A gene atlas of the mouse and human protein-encoding transcriptomes
Andrew I. Su,Tim Wiltshire,Serge Batalov,Hilmar Lapp,Keith A. Ching,David Block,Jie Zhang,Richard Soden,Mimi Hayakawa,Gabriel Kreiman,Gabriel Kreiman,Michael P. Cooke,John R. Walker,John B. Hogenesch,John B. Hogenesch +14 more
TL;DR: In this paper, high-density oligonucleotide arrays offer the opportunity to examine patterns of gene expression on a genome scale, and the authors have designed custom arrays that interrogate the expression of the vast majority of proteinencoding human and mouse genes and have used them to profile a panel of 79 human and 61 mouse tissues.
Journal ArticleDOI
Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks
Javed Khan,Jun S. Wei,Markus Ringnér,Markus Ringnér,Lao H. Saal,Marc Ladanyi,Frank Westermann,Frank Berthold,Manfred Schwab,Cristina R. Antonescu,Carsten Peterson,Paul S. Meltzer +11 more
TL;DR: The ability of the trained ANN models to recognize SRBCTs is demonstrated, and the potential applications of these methods for tumor diagnosis and the identification of candidate targets for therapy are demonstrated.
Book
Bioinformatics and Computational Biology Solutions Using R and Bioconductor
TL;DR: In this article, the authors present a detailed case study of R algorithms with publicly available data, and a major section of the book is devoted to fully worked case studies, with a companion website where readers can reproduce every number, figure and table on their own computers.
Related Papers (5)
Genomic responses in mouse models poorly mimic human inflammatory diseases
Seok Junhee Seok,Shaw Warren,G. Cuenca Alex,N. Mindrinos Michael,V. Baker Henry,Weihong Xu,Daniel R. Richards,Grace P. McDonald-Smith,Hong Gao,Laura Hennessy,Celeste C. Finnerty,Cecilia M Lopez,Shari Honari,Ernest E. Moore,Joseph P. Minei,Joseph Cuschieri,Paul E. Bankey,Jeffrey L. Johnson,Jason L. Sperry,Avery B. Nathens,Timothy R. Billiar,Michael West,Marc G. Jeschke,Matthew B. Klein,Richard L. Gamelli,Nicole S. Gibran,Bernard H. Brownstein,Carol L. Miller-Graziano,Steve E. Calvano,Philip H. Mason,J. Perren Cobb,Laurence G. Rahme,Stephen F. Lowry,Ronald V. Maier,Lyle L. Moldawer,David N. Herndon,Ronald W. Davis,Wenzhong Xiao,Wenzhong Xiao,Ronald G. Tompkins +39 more
Initial sequencing and comparative analysis of the mouse genome.
Robert H. Waterston,Kerstin Lindblad-Toh,Ewan Birney,Jane Rogers,Josep F. Abril,Pankaj K. Agarwal,Richa Agarwala,Rachel Ainscough,Marina Alexandersson,Peter An,Stylianos E. Antonarakis,John Attwood,Robert Baertsch,J Bailey,K F Barlow,Stephan Beck,Eric Berry,Bruce W. Birren,Toby Bloom,Peer Bork,Marc Botcherby,Nicolas Bray,Michael R. Brent,Daniel G. Brown,Daniel G. Brown,Stephen D. Brown,Carol J. Bult,John Burton,Jonathan Butler,R. D. Campbell,Piero Carninci,Simon Cawley,Francesca Chiaromonte,Asif T. Chinwalla,Deanna M. Church,Michele Clamp,C M Clee,Francis S. Collins,Lisa Cook,Richard R. Copley,Alan Coulson,Olivier Couronne,James Cuff,Val Curwen,Tim Cutts,Mark J. Daly,Robert David,Joy Davies,Kimberly D. Delehaunty,Justin Deri,Emmanouil T. Dermitzakis,Colin N. Dewey,Nicholas J. Dickens,Mark Diekhans,Sheila Dodge,Inna Dubchak,Diane M. Dunn,Sean R. Eddy,Laura Elnitski,Richard D. Emes,Pallavi Eswara,Eduardo Eyras,Adam Felsenfeld,Ginger A. Fewell,Paul Flicek,Karen Foley,Wayne N. Frankel,Lucinda Fulton,Robert S. Fulton,Terrence S. Furey,Diane Gage,Richard A. Gibbs,Gustavo Glusman,Sante Gnerre,Nick Goldman,Leo Goodstadt,Darren Grafham,Tina Graves,Eric D. Green,Simon G. Gregory,Roderic Guigó,Mark S. Guyer,Ross C. Hardison,David Haussler,Yoshihide Hayashizaki,Deana W. LaHillier,Angela S. Hinrichs,Wratko Hlavina,Timothy Holzer,Fan Hsu,Axin Hua,Tim Hubbard,Adrienne Hunt,Ian J. Jackson,David B. Jaffe,L. Steven Johnson,Matthew Jones,Thomas A. Jones,A Joy,Michael Kamal,Elinor K. Karlsson,Donna Karolchik,Arkadiusz Kasprzyk,Jun Kawai,Evan Keibler,Cristyn Kells,W. James Kent,Andrew Kirby,Diana L. Kolbe,Ian F Korf,Raju Kucherlapati,Edward J. Kulbokas,David Kulp,Tom Landers,J. P. Leger,Steven Leonard,Ivica Letunic,Rosie Levine,Jia Li,Ming Li,Christine Lloyd,Susan Lucas,Bin Ma,Donna Maglott,Elaine R. Mardis,Lucy Matthews,Evan Mauceli,John Mayer,Megan McCarthy,W. Richard McCombie,Stuart McLaren,Kirsten McLay,John Douglas Mcpherson,James Meldrim,Beverley Meredith,Jill P. Mesirov,Webb Miller,Tracie L. Miner,Emmanuel Mongin,Kate Montgomery,Michael J. Morgan,Richard Mott,James C. Mullikin,Donna M. Muzny,William E. Nash,Joanne O. Nelson,Michael N. Nhan,Robert Nicol,Zemin Ning,Chad Nusbaum,Michael J. O’Connor,Yasushi Okazaki,Karen Oliver,Emma Overton-Larty,Lior Pachter,Genís Parra,Kymberlie H. Pepin,Jane Peterson,Pavel A. Pevzner,Robert W. Plumb,Craig Pohl,Alex Poliakov,Tracy C. Ponce,Chris P. Ponting,Simon C. Potter,Michael A. Quail,Alexandre Reymond,Bruce A. Roe,Krishna M. Roskin,Edward M. Rubin,Alistair G. Rust,Ralph Santos,Victor Sapojnikov,Brian Schultz,Jörg Schultz,Matthias S. Schwartz,Scott Schwartz,Carol Scott,Steven Seaman,Steve Searle,Ted Sharpe,Andrew Sheridan,Ratna Shownkeen,Sarah Sims,Jonathan Singer,Guy Slater,Arian F.A. Smit,Douglas Smith,Brian Spencer,Arne Stabenau,Nicole Stange-Thomann,Charles W. Sugnet,Mikita Suyama,Glenn Tesler,Johanna Thompson,David Torrents,Evanne Trevaskis,John Tromp,Catherine Ucla,Abel Ureta-Vidal,Jade P. Vinson,Andrew von Niederhausern,Claire M. Wade,Melanie M. Wall,R. J. Weber,Robert B. Weiss,Michael C. Wendl,Anthony P. West,Kris A. Wetterstrand,Raymond Wheeler,Simon Whelan,Jamey Wierzbowski,David Willey,Sophie Williams,Richard K. Wilson,Eitan E. Winter,Kim C. Worley,Dudley Wyman,Shan Yang,Shiaw Pyng Yang,Evgeny M. Zdobnov,Michael C. Zody,Eric S. Lander +222 more
Gene Ontology: tool for the unification of biology
M Ashburner,Catherine A. Ball,Judith A. Blake,David Botstein,Heather Butler,J. M. Cherry,Allan Peter Davis,Kara Dolinski,Selina S. Dwight,J.T. Eppig,Midori A. Harris,David P. Hill,Laurie Issel-Tarver,Andrew Kasarskis,Suzanna E. Lewis,John C. Matese,Joel E. Richardson,M. Ringwald,Gerald M. Rubin,Gavin Sherlock +19 more
The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease
Justin Lamb,Emily D. Crawford,David Peck,Joshua W. Modell,Irene C. Blat,Matthew J. Wrobel,Jim Lerner,Jean Philippe Brunet,Aravind Subramanian,Kenneth N. Ross,Michael Reich,Haley Hieronymus,Haley Hieronymus,Guo Wei,Guo Wei,Scott A. Armstrong,Scott A. Armstrong,Stephen J. Haggarty,Stephen J. Haggarty,Paul A. Clemons,Ru Wei,Steven A. Carr,Eric S. Lander,Eric S. Lander,Todd R. Golub +24 more