Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice.

Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice. Research Abstract Details 

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Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice. Abstract Text:

Thomas A Drake,Eric E Schadt,Aldons J Lusis,

The millions of common DNA variations that occur in the human population, or among inbred strains of mice and rats, perturb the expression (transcript levels) of a large fraction of the genes expressed in a particular tissue. The hundreds or thousands of common cis-acting variations that occur in the population may in turn affect the expression of thousands of other genes by affecting transcription factors, signaling molecules, RNA processing, and other processes that act in trans. The levels of transcripts are conveniently quantitated using expression arrays, and the cis- and trans-acting loci can be mapped using quantitative trait locus (QTL) analysis, in the same manner as loci for physiologic or clinical traits. Thousands of such expression QTL (eQTL) have been mapped in various crosses in mice, as well as other experimental organisms, and less detailed maps have been produced in studies of cells from human pedigrees. Such an integrative genetics approach (sometimes referred to as "genetical genomics") is proving useful for identifying genes and pathways that contribute to complex clinical traits. The coincidence of clinical trait QTL and eQTL can help in the prioritization of positional candidate genes. More importantly, mathematical modeling of correlations between levels of transcripts and clinical traits in genetic crosses can allow prediction of causal interactions and the identification of "key driver" genes. An important objective of such studies will be to model biological networks in physiologic processes. When combined with high-density single nucleotide polymorphism (SNP) mapping, it should be feasible to identify genes that contribute to transcript levels using association analysis in outbred populations. In this review we discuss the basic concepts and applications of this integrative genomic approach to cardiovascular and metabolic diseases.

Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice. Publishing Authors By Initials

TA Drake,EE Schadt,AJ Lusis,

For similar animals: chordata: vertebrates: mammals: rodentia: muridae: murinae: mice research abstracts see: animals: chordata: vertebrates: mammals: rodentia: muridae: murinae: mice research

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Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice. Journal Published:

PUBLICATION TYPE: Review

Journal: Mammalian genome : official journal of the Interna

VOLUME: 17

Page Numbers: 466-79

Journal Abbreviation: Mamm. Genome

ISSN: 0938-8990

DAY: 12

MONTH: 06

YEAR: 2006

Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice. Information

Number of References: 37

LANGUAGE: eng

NlmUniqueID: 9100916

Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice. Keywords Mesh Terms:

KEYWORDS: Mice

MESH TERMS: genetics

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Grant and Affiliation Information for Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice.

AFFILIATION: Department of Pathology and Laboratory Medicine, University of California-Los Angeles, Los Angeles, CA 90095-1732, USA.

Country: United States

AGENCY: United States NHLBI

GRANT: HL 70526

ACRONYM: HL

MEDLINETA: Mamm Genome

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