Here we present a statistically rigorous approach to quantifying microarray expression data that allows the relative effects of multiple classes of treatment to be compared and incorporates analytical methods that are common to quantitative genetics. From the magnitude of gene effects and contributions of variance components, we find that gene expression in adult flies is affected most strongly by sex, less so by genotype and only weakly by age (for 1- and 6-wk flies); in addition, sex x genotype interactions may be present for as much as 10% of the Drosophila transcriptome. This interpretation is compromised to some extent by statistical issues relating to power and experimental design. Nevertheless, we show that changes in expression as small as 1.2-fold can be highly significant. Genotypic contributions to transcriptional variance may be of a similar magnitude to those relating to some quantitative phenotypes and should be considered when assessing the significance of experimental treatments.
Although most genetic association studies are performed with the intention of detecting nucleotide polymorphisms that are correlated with a complex trait, transcript abundance should also be expected to associate with diseases or phenotypes. We performed a scan for such quantitative trait transcripts in adult female heads of the fruit fly (Drosophila melanogaster) that might explain variation for nicotine resistance. The strongest association was seen for abundance of ornithine aminotransferase transcripts, implicating detoxification and neurotransmitter biosynthesis as mediators of the quantitative response to the drug. Subsequently, genetic analysis and metabolite profiling confirmed a complex role for ornithine and GABA levels in modification of survival time upon chronic nicotine exposure. Differences between populations from North Carolina and California suggest that the resistance mechanism may be an evolved response to environmental exposure.
Expression profiling of Drosophila melanogaster adult female heads for 108 nearly isogenic lines from two different populations, and of CEPH lymphoblastoid lines, shows that differential expression of transcripts among individuals is due to a complex interplay of cis-and trans-acting factors.
Abstract Background: Populations diverge in genotype and phenotype under the influence of such evolutionary processes as genetic drift, mutation accumulation, and natural selection. Because genotype maps onto phenotype by way of transcription, it is of interest to evaluate how these evolutionary factors influence the structure of variation at the level of transcription. Here, we explore the distributions of cis-acting and trans-acting factors and their relative contributions to expression of transcripts that exhibit two or more classes of abundance among individuals within populations.
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