Person: Ayroles, Julien
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Ayroles
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Julien
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Ayroles, Julien
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Publication Genetic incompatibilities are widespread within species(Nature Publishing Group, 2013) Corbett-Detig, Russell B.; Zhou, Jun; Clark, Andrew G.; Hartl, Daniel; Ayroles, JulienThe importance of epistasis—non-additive interactions between alleles—in shaping population fitness has long been a controversial topic, hampered in part by lack of empirical evidence1, 2, 3, 4. Traditionally, epistasis is inferred on the basis of non-independence of genotypic values between loci for a given trait. However, epistasis for fitness should also have a genomic footprint5, 6, 7. To capture this signal, we have developed a simple approach that relies on detecting genotype ratio distortion as a sign of epistasis, and we apply this method to a large panel of Drosophila melanogaster recombinant inbred lines8, 9. Here we confirm experimentally that instances of genotype ratio distortion represent loci with epistatic fitness effects; we conservatively estimate that any two haploid genomes in this study are expected to harbour 1.15 pairs of epistatically interacting alleles. This observation has important implications for speciation genetics, as it indicates that the raw material to drive reproductive isolation is segregating contemporaneously within species and does not necessarily require, as proposed by the Dobzhansky–Muller model, the emergence of incompatible mutations independently derived and fixed in allopatry. The relevance of our result extends beyond speciation, as it demonstrates that epistasis is widespread but that it may often go undetected owing to lack of statistical power or lack of genome-wide scope of the experiments.Publication Genomic Variation and Its Impact on Gene Expression in Drosophila Melanogaster(Public Library of Science, 2012) Massouras, Andreas; Waszak, Sebastian M.; Albarca-Aguilera, Monica; Hens, Korneel; Holcombe, Wiebke; Ayroles, Julien; Dermitzakis, Emmanouil T.; Stone, Eric A.; Jensen, Jeffrey D.; Mackay, Trudy F. C.; Deplancke, BartUnderstanding the relationship between genetic and phenotypic variation is one of the great outstanding challenges in biology. To meet this challenge, comprehensive genomic variation maps of human as well as of model organism populations are required. Here, we present a nucleotide resolution catalog of single-nucleotide, multi-nucleotide, and structural variants in 39 Drosophila melanogaster Genetic Reference Panel inbred lines. Using an integrative, local assembly-based approach for variant discovery, we identify more than 3.6 million distinct variants, among which were more than 800,000 unique insertions, deletions (indels), and complex variants (1 to 6,000 bp). While the SNP density is higher near other variants, we find that variants themselves are not mutagenic, nor are regions with high variant density particularly mutation-prone. Rather, our data suggest that the elevated SNP density around variants is mainly due to population-level processes. We also provide insights into the regulatory architecture of gene expression variation in adult flies by mapping cis-expression quantitative trait loci (cis-eQTLs) for more than 2,000 genes. Indels comprise around 10% of all cis-eQTLs and show larger effects than SNP cis-eQTLs. In addition, we identified two-fold more gene associations in males as compared to females and found that most cis-eQTLs are sex-specific, revealing a partial decoupling of the genomic architecture between the sexes as well as the importance of genetic factors in mediating sex-biased gene expression. Finally, we performed RNA-seq-based allelic expression imbalance analyses in the offspring of crosses between sequenced lines, which revealed that the majority of strong cis-eQTLs can be validated in heterozygous individuals.Publication Using Whole-Genome Sequence Data to Predict Quantitative Trait Phenotypes in Drosophila melanogaster(Public Library of Science, 2012) Ober, Ulrike; Stone, Eric A.; Richards, Stephen; Zhu, Dianhui; Gibbs, Richard A.; Stricker, Christian; Gianola, Daniel; Schlather, Martin; Mackay, Trudy F. C.; Simianer, Henner; Ayroles, JulienPredicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP) genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ∼2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP) model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012) for starvation resistance (startle response). The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP–based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms.