Understanding multicellular function and disease with human tissue-specific networks

被引：627

作者：

Greene, Casey S. ^{[1
,2
,3
]}

Krishnan, Arjun ^{[4
]}

Wong, Aaron K. ^{[5
]}

Ricciotti, Emanuela ^{[6
,7
]}

Zelaya, Rene A. ^{[1
]}

Himmelstein, Daniel S. ^{[8
]}

Zhang, Ran ^{[9
]}

Hartmann, Boris M. ^{[10
]}

Zaslavsky, Elena ^{[10
]}

Sealfon, Stuart C. ^{[10
]}

Chasman, Daniel I. ^{[11
,12
]}

FitzGerald, Garret A. ^{[6
,7
]}

Dolinski, Kara ^{[4
]}

Grosser, Tilo ^{[6
,7
]}

Troyanskaya, Olga G. ^{[4
,5
,13
]}

机构：

[1] Geisel Sch Med Dartmouth, Dept Genet, Hanover, NH USA

[2] Dartmouth Hitchcock Norris Cotton Canc Ctr, Lebanon, NH USA

[3] Dartmouth Coll, Inst Quantitat Biomed Sci, Hanover, NH 03755 USA

[4] Princeton Univ, Lewis Sigler Inst Integrat Genom, Princeton, NJ 08544 USA

[5] Princeton Univ, Dept Comp Sci, Princeton, NJ 08544 USA

[6] Univ Penn, Perelman Sch Med, Dept Syst Pharmacol & Translat Therapeut, Philadelphia, PA 19104 USA

[7] Univ Penn, Perelman Sch Med, Inst Translat Med & Therapeut, Philadelphia, PA 19104 USA

[8] Univ Calif San Francisco, Biol & Med Informat, San Francisco, CA 94143 USA

[9] Princeton Univ, Dept Mol Biol, Princeton, NJ 08544 USA

[10] Icahn Sch Med Mt Sinai, Dept Neurol, New York, NY 10029 USA

[11] Brigham & Womens Hosp, Div Prevent Med, Boston, MA 02115 USA

[12] Harvard Univ, Sch Med, Boston, MA USA

[13] Simons Fdn, Simons Ctr Data Anal, New York, NY USA

来源：

NATURE GENETICS | 2015年 / 47卷 / 06期

基金：

美国国家卫生研究院;

关键词：

CHRONIC LYMPHOCYTIC-LEUKEMIA; ENHANCER-BINDING; GENE-FUNCTION; EXPRESSION; LEF-1; GENOME; CELLS; PREDICTION; RESOURCE; AIRWAY;

D O I：

10.1038/ng.3259

中图分类号：

Q3 [遗传学];

学科分类号：

071007 [遗传学];

摘要：

Tissue and cell-type identity lie at the core of human physiology and disease. Understanding the genetic underpinnings of complex tissues and individual cell lineages is crucial for developing improved diagnostics and therapeutics. We present genome-wide functional interaction networks for 144 human tissues and cell types developed using a data-driven Bayesian methodology that integrates thousands of diverse experiments spanning tissue and disease states. Tissue-specific networks predict lineage-specific responses to perturbation, identify the changing functional roles of genes across tissues and illuminate relationships among diseases. We introduce NetWAS, which combines genes with nominally significant genome-wide association study (GWAS) P values and tissue-specific networks to identify disease-gene associations more accurately than GWAS alone. Our webserver, GIANT, provides an interface to human tissue networks through multi-gene queries, network visualization, analysis tools including NetWAS and downloadable networks. GIANT enables systematic exploration of the landscape of interacting genes that shape specialized cellular functions across more than a hundred human tissues and cell types.

引用

页码：569 / 576

页数：8

共 64 条

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