Natural variation in genome architecture among 205 Drosophila melanogaster Genetic Reference Panel lines

The Drosophila melanogaster Genetic Reference Panel (DGRP) is a community resource of 205 sequenced inbred lines, derived to improve our understanding of the effects of naturally occurring genetic variation on molecular and organismal phenotypes. We used an integrated genotyping strategy to identify 4,853,802 single nucleotide polymorphisms (SNPs) and 1,296,080 non-SNP variants. Our molecular population genomic analyses show higher deletion than insertion mutation rates and stronger purifying selection on deletions. Weaker selection on insertions than deletions is consistent with our observed distribution of genome size determined by flow cytometry, which is skewed toward larger genomes. Insertion/deletion and single nucleotide polymorphisms are positively correlated with each other and with local recombination, suggesting that their nonrandom distributions are due to hitchhiking and background selection. Our cytogenetic analysis identified 16 polymorphic inversions in the DGRP. Common inverted and standard karyotypes are genetically divergent and account for most of the variation in relatedness among the DGRP lines. Intriguingly, variation in genome size and many quantitative traits are significantly associated with inversions. Approximately 50% of the DGRP lines are infected with Wolbachia, and four lines have germline insertions of Wolbachia sequences, but effects of Wolbachia infection on quantitative traits are rarely significant. The DGRP complements ongoing efforts to functionally annotate the Drosophila genome. Indeed, 15% of all D. melanogaster genes segregate for potentially damaged proteins in the DGRP, and genome-wide analyses of quantitative traits identify novel candidate genes. The DGRP lines, sequence data, genotypes, quality scores, phenotypes, and analysis and visualization tools are publicly available.

The phenotypic impact of naturally occurring genetic and molecular mitochondrial variation in a Drosophila Genetic Reference Population

Roel Paulus Josephus Bevers

Genome-wide association (GWA) studies aim to dissect the relationship between genotype and phenotype. So far, the focus has been on nuclear genetic determinants as variation in the mitochondrial genome is often low in the study cohorts. Despite this observation, mitochondrial genomic variants are increasingly linked to metabolic and neurological disorders. Thus, there is much to gain from studying how mitochondrial variation interacts with nuclear variation and/or environment, and how this subsequently affects phenotypes. In my thesis I address these topics using Drosophila melanogaster as a model system, and specifically the Drosophila Genetic Reference Panel (DGRP). The DGRP consists of 200 sequenced and genetically diverse Drosophila populations and has been extensively used to study a wide-range of quantitative traits. However, in all of these studies, researchers have focussed on the influence of nuclear genetic variants in the absence of a high-resolution map of mitochondrial variants. To address this problem, we have developed a high-throughput method to specifically sequence mitochondrial DNA that enabled us to characterize mitochondrial genomic variation to an unprecedented depth. On average, each DGRP line had 25 mitochondrial variants (1 in 600 bp) and that most of the variants detected were unique for each line. However, we also found that some variants are more prevalent and show they can be used to construct mitochondrial haplotypes. We then used these haplotypes to test whether mitochondrial variation affected previously published phenotypes. We detected significant associations with 12 out of 259 publicly accessible phenotypes and found that these were mostly related to metabolism and responses to environmental cues. We selected one of the significant phenotypes, food intake in males, to verify our findings. We demonstrated the effect of mitochondrial haplotypes on the phenotype by swapping mitochondria from ¿high food intake¿ lines with mitochondria from ¿low food intake¿ lines and vice versa. We observed that, largely independent of the nuclear background, DGRP lines with a ¿high food intake mitochondria¿ consumed more food and concomitantly, DGRP lines with the ¿low food intake mitochondria¿ consumed less food. Furthermore, we investigated the influence of natural genetic variation was on the response to a high-fat diet. We designed a control and a high-fat diet and fed this to >100 DGRP lines and measured the lifespan on each diet. On average, lifespan was decreased by 48% on a high-fat diet, however this ranged from an increase of 2% to a decrease of 60% accentuating the complexity of the underlying genetic architecture. Our dataset was relatively small and limited our genome-wide and mitochondrial haplotype association analyses. Nonetheless, our GWA analysis detected variants related to genes involved in lipid metabolism and mitochondria but we did not detect significant associations with mitochondrial haplotypes. This suggests that while mitochondrial function may be important for the response to a high-fat diet, it is not dependent on the mitochondrial haplotype. Taken together, the work described in my thesis demonstrates the significance of accounting for mitochondrial haplotypes in phenotype association analyses. By doing so, it can open up new insights into genotype-to-phenotype relationships and gene regulation.

EPFL2018

Genomic Variation and Its Impact on Gene Expression in Drosophila melanogaster

Monica Albarca Aguilera, Bart Deplancke, Jeffrey David Jensen, Andreas Massouras, Sebastian Martin Waszak

Understanding 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.

Public Library of Science2012

Elucidating regulatory mechanisms shaping the transcriptome and proteome of the gut immune response in Drosophila melanogaster

Michael Vincent Frochaux

Work on Drosophila melanogaster paved the way to our current understanding of modern genetics. Since then, this model organism has contributed greatly to various fields such as neurobiology, development, and immunology. The discovery and analysis of the various pathways of the Drosophila immune response led the way to the in-depth characterization of the gut immune response. Furthermore, a genome-wide association study on a population of Drosophila identified resistance to infection by the entomopathogenic bacteria Pseudomonas entomophila (P.e.) as a complex phenotype, with highly resistant and susceptible lines, and highlighted genes and pathways mediating inter-individual differences. However, the molecular mechanisms mediating the resistance to enteric infection remain largely uncharacterized. This study uses the same Drosophila population to analyze what are the molecular mechanisms mediating the resistance to enteric infection. We analyzed the genetic determinants of gene expression variation among the most resistant and susceptible lines in response to infection using expression quantitative trait loci (eQTL) analysis. We also characterized the mode of action of these eQTLs into cis- and trans-acting. Furthermore, we identified the gene nutcracker (ntc) as the only differentially-expressed gene between resistance classes. We then demonstrate that loss of function ntc mutants are significantly more susceptible to infection and then identify a single nucleotide polymorphism (SNP) located in a transcription factor binding site (TFBS) which affects the binding affinity of the transcription factor Broad leading to allele-specific expression variation of the gene ntc. If the transcriptomic response to infection has been thoroughly characterized, it is not the case for the proteomic response. We thus sought to characterize for the first time the proteomic response of the Drosophila to enteric infection. We performed mass spectrometry and RNA sequencing on dissected guts from flies infected by two Gram-negative bacteria, Erwinia carotovora carotovora 15 (Ecc15) or Pseudomonas entomophila, 4h and 16h after infection. We found that a large portion of the measurable proteome (12%) varies after infection and that protein changes are strongly time- and infection-dependent. We showed the relatively poor correlation between gene expression and protein abundance in the Drosophila enteric immune response. Finally, we performed a screen of several proteins that were identified in our proteomics work but had previously not been found when assessing the gene expression response to infection using loss-of-function mutants and identifying 7 genes that modulate overall susceptibility to P.e. infection. In summary, this work analyze the genetic determinants of gene expression variation in the DGRP population upon infection and characterize them according to their mode of action. Furthermore, we describe how a non-coding variant lowers resistance to infection by modulating ntc gene expression through altered Broad repressor binding. Finally, it provides the first comprehensive characterization of the Drosophila gut proteome upon infection by Gram-negative bacteria which can be the basis of future proteomic analysis of the enteric immune response