Genetical genomics: combining genetics with gene expression analysis

The biological mechanisms that link genetic variation and its phenotypic outcome stand as a central puzzle inbiology. Geneticists have usually approached this problem by trying to identify genetic variants that underliethe trait in question. Ten years ago, microarray technology opened a second front by making it possible tocompare expression levels for most active genes under a variety of genetic and environmental conditions. Atypical 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 combinegene 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 inﬂuencegene expression are sought. Several studies have shown that mRNA levels for many genes are heritable, thusamenable to genetic analysis. Quantitative trait loci mapping efforts have led to the initial characterization ofgenetic 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 affectsexpression levels of hundreds of genes is an important ﬁnding that will surely enrich our understandingof regulatory networks. Although this novel ﬁeld is still developing, understanding the genetic basis ofmolecular phenotypes such as gene expression is expected to shed light on the intermediate processesthat connect genotype to cellular and organismal traits and represents a critical step towards true systemsbiology.INTRODUCTIONMost common human diseases, including cancer, heart diseaseand schizophrenia, have complex etiologies, involving theaction of many genes, as well as dynamic gene–environmentinteractions. To elucidate the mechanisms underlying diseasesusceptibility and progression and to improve diagnosis andtreatment, an important strategy is to use genetic methods toidentify the causative DNA variants and use this knowledgeas the ﬁrst step towards the eventual unraveling of thecomplex interplay between genes and environment. Asecond, more recent approach, made possible by the emer-gence of microarray technology since the early 1990s, is toanalyze gene expression patterns globally in tissues fromhealthy and diseased individuals and use the steady-statemRNA levels to infer the maladaptive regulatory changesaccompanying the disease. Until recently, genetic and geneexpression studies were largely separate endeavors, involvingdifferent study designs, biological materials and analysis tools.Occasionally, a study searching for the overlap between genesexpressed in a relevant pathway and the chromosomal regionidentiﬁed by linkage could pinpoint a clear candidate thatturned out to be the correct gene (1). A systematic integrationof genetic association and linkage results with gene expressionresults remains, however, a signiﬁcant challenge.In the past few years, genetic and gene expressionapproaches have been brought together, in what has beencoined ‘genetical genomics’ (2), to study the genetic basisof gene expression (Fig. 1). The importance of understandingthe genetic basis of gene expression, and by extension ofbiological regulation, is predicated on the widely held viewthat genetic contribution to phenotypic diversity is just as