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Human Molecular Genetics
Article . 2005 . Peer-reviewed
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Genetical genomics: combining genetics with gene expression analysis

Authors: Jun, Li; Margit, Burmeister;

Genetical genomics: combining genetics with gene expression analysis

Abstract

The biological mechanisms that link genetic variation and its phenotypic outcome stand as a central puzzle in biology. Geneticists have usually approached this problem by trying to identify genetic variants that underlie the trait in question. Ten years ago, microarray technology opened a second front by making it possible to compare expression levels for most active genes under a variety of genetic and environmental conditions. A typical study reveals up- or down-regulation of genes or pathways associated with a phenotype (case/control) or condition (treated/untreated). In the past few years, a number of groups have started to combine gene expression studies with genetic linkage analysis, leading to a new synergy between these approaches. In this strategy, expression levels are treated as quantitative phenotypes and genetic variants that influence gene expression are sought. Several studies have shown that mRNA levels for many genes are heritable, thus amenable to genetic analysis. Quantitative trait loci mapping efforts have led to the initial characterization of genetic regulation in 'cis' probably because of variants in the gene's own regulatory regions, as well as in 'trans', i.e. by loci elsewhere in the genome. The existence of some 'master regulators' that each affects expression levels of hundreds of genes is an important finding that will surely enrich our understanding of regulatory networks. Although this novel field is still developing, understanding the genetic basis of molecular phenotypes such as gene expression is expected to shed light on the intermediate processes that connect genotype to cellular and organismal traits and represents a critical step towards true systems biology.

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Keywords

Genotype, Gene Expression Profiling, Genetic Variation, Genomics, Models, Biological, Phenotype, Quantitative Trait, Heritable, Gene Expression Regulation, Animals, Humans, RNA, Messenger

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
89
Top 10%
Top 10%
Top 1%
bronze