Genetical genomics: combining genetics with gene expression analysis

被引:68
作者
Li, J
Burmeister, M [1 ]
机构
[1] Univ Michigan, Dept Psychiat, Ann Arbor, MI 48109 USA
[2] Stanford Univ, Stanford Human Genome Ctr, Palo Alto, CA 94304 USA
[3] Univ Michigan, Dept Human Genet, Mol & Behav Neurosci Inst, Ann Arbor, MI 48109 USA
关键词
D O I
10.1093/hmg/ddi267
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:R163 / R169
页数:7
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