Friday, September 13, 2013

Our new pre-print: An integrative genomic approach illuminates the causes and consequences of genetic background effects

This is a guest post by Dr. Chris Chandler. Cross posted from Haldane's Sieve.

Biologists have long recognized that a mutation can have variable effects on an organism's phenotype; even introductory genetics classes often make this observation by introducing the concepts of penetrance and expressivity. More mysterious, however, are the factors that influence the phenotypic expression of a mutation or allele. We know, for instance, that introducing the same mutation into two different but otherwise wild-type genetic backgrounds can result in vastly different phenotypes. But what specific differences between these two genetic backgrounds interact with the mutation, and how? And how does gene expression fit into this puzzle? Answering these questions has not been an easy task, which is not too surprising when you realize that penetrance and expressivity are, in reality, complex quantitative traits. We therefore adopted a multi-pronged genetic and genomic approach to tease apart the mechanisms mediating background dependence in a mutation affecting wing development in the fly Drosophila melanogaster.

The phenotypic patterns seen in our model trait have already been characterized: the scalloped[E3] (sd[E3]) mutation has strong effects in the Oregon-R (ORE) background, resulting in a tiny, underdeveloped wing, while its effects in the Samarkand (SAM) background are still obvious but much less extreme, resulting in a blade-like wing.

To try to find out what causes these differences, we generated and combined a variety of datasets: whole-genome re-sequencing of the parental strains and a panel of introgression lines to map the background modifiers of the sd[E3] phenotype; transcription profiling (using two microarray datasets and one RNA-seq-like dataset), including analyses of allele-specific expression in flies carrying a "hybrid" genetic background; predictions of binding sites for the SD protein, which is a transcription factor; and a screen for deletion alleles that enhance or suppress the sd[E3] phenotype in a background-dependent fashion.

Our results point to a complex genetic basis for this background dependence. We found evidence for a number of loci that are likely to modulate the effects of the sd[E3] allele. However, some unexpected inconsistencies provide a cautionary tale for those intending to take a similar mapping-by-introgression approach for their trait of interest: do multiple replicates, and introgress in both directions, or you may inadvertently end up mapping some other trait! Although the number of candidate genes we identified were generally large, by combining those results with data from our other datasets, we were able to narrow our focus to those showing a consistent signal, yielding a robust set of candidate genes for further study. Without getting into too much detail, we also used a novel approach to show that background-dependent modifier deletions of the sd[E3] phenotype (of which there are many) involve higher-order epistatic interactions between the sd[E3] mutation, the deletion, and the genetic background, rather than quantitative non-complementation (so more than two genes were involved).

Overall, we think that an integrative approach like this could be useful for others trying to understand complex traits, including genetic background-dependence of mutations. In addition, if you're a Drosophila researcher working with the commonly used Samarkand or Oregon-R strains, our genome re-sequencing data (raw and assembled), including SNPs, will soon be available in public repositories for genetic data.

No comments:

Post a Comment