Academic journal article Genetics

The Effects of Weak Genetic Perturbations on the Transcriptome of the Wing Imaginal Disc and Its Association with Wing Shape in Drosophila Melanogaster

Academic journal article Genetics

The Effects of Weak Genetic Perturbations on the Transcriptome of the Wing Imaginal Disc and Its Association with Wing Shape in Drosophila Melanogaster

Article excerpt

ABSTRACT

A major objective of genomics is to elucidate the mapping between genotypic and phenotypic space as a step toward understanding how small changes in gene function can lead to elaborate phenotypic changes. One approach that has been utilized is to examine overall patterns of covariation between phenotypic variables of interest, such as morphology, physiology, and behavior, and underlying aspects of gene activity, in particular transcript abundance on a genome-wide scale. Numerous studies have demonstrated that such patterns of covariation occur, although these are often between samples with large numbers of unknown genetic differences (different strains or even species) or perturbations of large effect (sexual dimorphism or strong loss-of-function mutations) that may represent physiological changes outside of the normal experiences of the organism. We used weak mutational perturbations in genes affecting wing development in Drosophila melanogaster that influence wing shape relative to a co-isogenic wild type. We profiled transcription of 1150 genes expressed during wing development in 27 heterozygous mutants, as well as their co-isogenic wild type and one additional wild-type strain. Despite finding clear evidence of expression differences between mutants and wild type, transcriptional profiles did not covary strongly with shape, suggesting that information from transcriptional profiling may not generally be predictive of final phenotype. We discuss these results in the light of possible attractor states of gene expression and how this would affect interpretation of covariation between transcriptional profiles and other phenotypes.

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FUNCTIONAL genomic research is dominated by two paradigms that derive their conceptual foundations from computer science and statistical genetics, respectively. Network biologists are interested in the patterns of connectivity between genes and gene products and in the consequences that these patterns impose on properties of biological systems, such as metabolic flux or phenotypic robustness (Reeves et al. 2006; Yakoby et al. 2008; Yan et al. 2009; Zartman et al. 2009). Quantitative geneticists tend to be more linear in their search for association between genotypes and phenotypes (including gene expression), and their models generally assume a preponderance of additive effects of individual variants (Passador-Gurgel et al. 2007; Ayroles et al. 2009; Edwards et al. 2009). A major challenge for systems biologists is to unify these two frameworks through their studies of the genomic consequences of genetic perturbation.

An additional obstacle is that there are also two conceptually different approaches to perturbation analysis used to address questions relating to genotype-phenotype mappings. One is to introduce large mutational or pharmacological changes to relatively homogeneous systems such as cell lines or clones of organisms in a highly controlled manner. While experimentally appealing, the perturbations are often well beyond the range of physiological or functional relevance, so the results may be difficult to generalize to actual biological circumstances. The alternative is to harness natural genetic or ecological variation, either in cross-sectional studies or in pedigrees and crosses (Passador-Gurgel et al. 2007; Rockman 2008; Ayroles et al. 2009; Edwards et al. 2009; Harbison et al. 2009). An advantage is that perturbation effects are averaged, and potentially replicated, over different genetic backgrounds, but the genomic effects of individual loci are generally subtle and detected only by statistical methods. They then require functional validation in more controlled experimental systems. Neither genome-wide association studies nor whole-genome expression profiling have yet proven capable of consistently describing more than a fraction of the underlying genetic basis of phenotypic variation. Nevertheless, it is of interest to bridge these conceptual gaps by studying how local perturbations of gene function ramify throughout the complex of genetic pathways operating in cells, tissues, and organisms. …

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