Biology subjects

Macdonald, S. J.

Publications and source records attributed to Macdonald, S. J..

3 recordsLinked to original sources

bioRxiv2018

Structural variants exhibit allelic heterogeneity and shape variation in complex traits

Despite extensive effort to reveal the genetic basis of complex phenotypic variation, studies typically explain only a fraction of trait heritability. It has been hypothesized that individually rare hidden structural variants (SVs) could account for a significant fraction of variation in complex traits. To investigate this hypothesis, we assembled 14 Drosophila melanogaster genomes and systematically identified more than 20,000 euchromatic SVs, of which [~]40% are invisible to high specificity short read genotyping approaches. SVs are common in Drosophila genes, with almost one third of diploid individuals harboring an SV in genes larger than 5kb, and nearly a quarter harboring multiple SVs in genes larger than 10kb. We show that SV alleles are rarer than amino acid polymorphisms, implying that they are more strongly deleterious. A number of functionally important genes harbor previously hidden structural variants that likely affect complex phenotypes (e.g., Cyp6g1, Drsl5, Cyp28d1&2, InR, and Gss1&2).Furthermore, SVs are overrepresented in quantitative trait locus candidate genes from eight Drosophila Synthetic Population Resource (DSPR) mapping experiments. We conclude that SVs are pervasive in genomes, are frequently present as heterogeneous allelic series, and can act as rare alleles of large effect.

genomics↗

bioRxiv2018

Dissection of complex, fitness-related traits in multiple Drosophila mapping populations offers insight into the genetic control of stress resistance

We leverage two complementary Drosophila melanogaster mapping panels to genetically dissect starvation resistance, an important fitness trait. Using >1600 genotypes of the multiparental Drosophila Synthetic Population Resource (DSPR) we map numerous starvation stress QTL that collectively explain a substantial fraction of trait heritability. QTL effects further allowed us to estimate DSPR founder phenotypes, predictions that were correlated with the actual founder phenotypes. Starvation resistance has been linked to triglyceride level, and while we observe a modest phenotypic correlation between the traits in the DSPR, overlap among the QTL identified for each trait is low. Since we show that DSPR strains with extreme starvation phenotypes also differ in desiccation resistance and activity level, our data imply that multiple physiological mechanisms contribute to starvation variability. We also exploit the Drosophila Genetic Reference Panel (DGRP), identifying a number of sequence variants associated with starvation resistance. Consistent with prior work these sites rarely fall within QTL intervals mapped in the DSPR. Two other groups previously measured starvation resistance in the DGRP, offering a unique opportunity to directly compare mapping results across labs. We found strong phenotypic correlations among studies, but extremely low overlap in the sets of genomewide significant sites. Despite this, our analyses revealed that the most highly-associated variants from each study typically showed the same additive effect sign in independent studies, in contrast to otherwise equivalent sets of random variants. This consistency provides evidence for reproducible trait-associated sites in a widely-used mapping panel, and highlights the polygenic nature of starvation resistance.

genetics↗

bioRxiv2017

Naturally-segregating Variation at Ugt86Dd Contributes to Nicotine Resistance in Drosophila melanogaster

Identifying the causative sequence polymorphisms underlying complex trait variation is a key goal of evolutionary and biomedical genetics. By knowing the precise molecular events that confer phenotypic changes we can gain insight into the pathways underlying complex traits and the evolutionary forces acting on variation. Genetic analysis of complex traits in model systems regularly starts by constructing QTL maps, but generally fails to identify causative nucleotide-level polymorphisms. Previously we mapped a series of QTL contributing to resistance to nicotine in a Drosophila melanogaster multiparental mapping resource, and here use a battery of functional tests to resolve QTL to the molecular level. One large-effect QTL resided over a cluster of UDP-glucuronosyltransferases, and quantitative complementation tests using deficiencies eliminating subsets of these detoxification genes revealed allelic variation impacting resistance. RNAseq showed that Ugt86Dd had significantly higher expression in genotypes that are more resistant to nicotine, and anterior midgut-specific RNAi of this gene reduced resistance. We discovered a naturally-segregating 22-bp frameshift deletion in Ugt86Dd, and overexpression of the insertion-containing allele in a range of tissues enhanced resistance. Accounting for the InDel event during mapping largely eliminates the QTL, implying the InDel explains the bulk of the effect associated with the mapped locus. Finally, we edited a relatively resistant genetic background to generate lesions in Ugt86Dd that recapitulate the naturally-occurring putative loss-of-function allele, and succeeded in radically reducing resistance. The putatively causative coding InDel in Ugt86Dd can be a launchpad for future mechanistic exploration of xenobiotic detoxification.\n\nARTICLE SUMMARYResolving the mutations that contribute to among-individual trait variation is a major goal of biomedical and evolutionary genetics. In general however, genetic mapping experiments do not allow immediate resolution of the underlying causative variants. Previous mapping work revealed several loci contributing to nicotine resistance in Drosophila melanogaster. We employed a battery of functional tests to demonstrate that the detoxification gene Ugt86Dd has a major phenotypic effect, and that a segregating frameshift mutation is likely causative. Editing the gene to introduce a premature stop codon led to a significant reduction in resistance, validating its role in xenobiotic detoxification.

genetics↗