α-amanitin resistance in Drosophila melanogaster: A genome-wide association approach

Efficacy of FimA antibody and clindamycin in silkworm larvae stimulated with Porphyromonas gulae

Objective: Porphyromonas gulae, a major periodontal pathogen in animals, possesses fimbriae that have been classified into three genotypes (A, B, C) based on the diversity of fimA genes encoding fimbrillin protein (FimA). P. gulae strains with type C fimbriae were previously shown to be more virulent than other types. In this study, we further examined the host toxicity mediated by P. gulae fimbriae by constructing recombinant FimA (rFimA) expression vectors for each genotype and raised antibodies to the purified proteins.

Methods and Results: All larvae died within 204 h following infection with P. gulae type C at the low-dose infection, whereas type A and B did not. Among fimA types, the survival rates of the larvae injected with rFimA type C were remarkably decreased, while the survival rates of the larvae injected with rFimA type A and type B were greater than 50%. Clindamycin treatment inhibited the growth of type C strains in a dose-dependent manner, resulting in an increased rate of silkworm survival. Finally, type C rFimA-specific antiserum prolonged the survival of silkworm larvae stimulated by infection with P. gulae type C strain or injection of rFimA type C protein.

Conclusion: These results suggested that type C fimbriae have high potential for enhancement of bacterial pathogenesis, and that both clindamycin and anti-type C rFimA-specific antibodies are potent inhibitors of type C fimbriae-induced toxicity. This is the first report to establish a silkworm infection model using P. gulae for toxicity assessment.

Evolutionary genomics of host plant adaptation: insights from Drosophila

Variation in gene expression in response to the use of alternate host plants can reveal genetic and physiological mechanisms explaining why insect-host relationships vary from host specialism to generalism. Interpreting transcriptome variation relies on well-annotated genomes, making drosophilids valuable model systems, particularly those species with tractable ecological associations. Patterns of whole genome expression and alternate gene splicing in response to growth on different hosts have revealed expression of gene networks of known detoxification genes as well as novel functionally enriched genes of diverse metabolic and structural functions. Integrating trancriptomic responses with fitness differences and levels of phenotypic plasticity in response to alternate hosts will help to reveal the general nature of genotype-phenotype relationships.

Pesticide contamination drives adaptive genetic variation in the endemic mayfly Andesiops torrens within a semi-arid agricultural watershed of Chile

Agrichemical contamination can provoke evolutionary responses in freshwater populations. It is a particularly relevant issue in semi-arid regions due to the sensitivity of endemic species to pollutants and to interactions with temperature stress. This paper investigates the presence of pesticides in rivers within a semi-arid agricultural watershed of Chile, testing for their effects on population genetic characteristics of the endemic mayfly Andesiops torrens (Insecta, Ephemeroptera). Pesticides were detected in sediment samples in ten out of the 30 sites analyzed throughout the upper part of the Limarí watershed. To study the evolutionary impact of such contamination on A. torrens, we used a genome-wide approach and analyzed 2056 single nucleotide polymorphisms (SNPs) loci in 551 individuals from all sites. Genetic differentiation was weak between populations, suggesting high gene flow across the study area. While we did not find evidence of pesticide effects on genetic diversity nor on population differentiation, the allele frequency of three outlier SNP loci correlated significantly with pesticide occurrence. Interrogation of genomic resources indicates that two of these SNPs are located within functional genes that encode for the low-density lipoprotein receptor-related protein 2 and Dumpy, both potentially involved in insect cuticle resistance processes. Such genomic signatures of local adaptation are indicative of past adverse effects of pesticide exposure on the locally adapted populations. Our results reveal that A. torrens is sensitive to pesticide exposure, but that a high gene flow may confer resilience to contamination. This research supports the contention that A. torrens is an ideal model organism to study evolutionary responses induced by pesticides on non-target, endemic species.

Charting the genotype-phenotype map: lessons from the Drosophila melanogaster Genetic Reference Panel

Understanding the genetic architecture (causal molecular variants, their effects, and frequencies) of quantitative traits is important for precision agriculture and medicine and predicting adaptive evolution, but is challenging in most species. The Drosophila melanogaster Genetic Reference Panel (DGRP) is a collection of 205 inbred strains with whole genome sequences derived from a single wild population in Raleigh, NC, USA. The large amount of quantitative genetic variation, lack of population structure, and rapid local decay of linkage disequilibrium in the DGRP and outbred populations derived from DGRP lines present a favorable scenario for performing genome-wide association (GWA) mapping analyses to identify candidate causal genes, polymorphisms, and pathways affecting quantitative traits. The many GWA studies utilizing the DGRP have revealed substantial natural genetic variation for all reported traits, little evidence for variants with large effects but enrichment for variants with low P-values, and a tendency for lower frequency variants to have larger effects than more common variants. The variants detected in the GWA analyses rarely overlap those discovered using mutagenesis, and often are the first functional annotations of computationally predicted genes. Variants implicated in GWA analyses typically have sex-specific and genetic background-specific (epistatic) effects, as well as pleiotropic effects on other quantitative traits. Studies in the DGRP reveal substantial genetic control of environmental variation. Taking account of genetic architecture can greatly improve genomic prediction in the DGRP. These features of the genetic architecture of quantitative traits are likely to apply to other species, including humans. WIREs Dev Biol 2018, 7:e289. doi: 10.1002/wdev.289 This article is categorized under: Invertebrate Organogenesis > Flies.

Charting the genotype-phenotype map: lessons from the Drosophila melanogaster Genetic Reference Panel

Understanding the genetic architecture (causal molecular variants, their effects, and frequencies) of quantitative traits is important for precision agriculture and medicine and predicting adaptive evolution, but is challenging in most species. The Drosophila melanogaster Genetic Reference Panel (DGRP) is a collection of 205 inbred strains with whole genome sequences derived from a single wild population in Raleigh, NC, USA. The large amount of quantitative genetic variation, lack of population structure, and rapid local decay of linkage disequilibrium in the DGRP and outbred populations derived from DGRP lines present a favorable scenario for performing genome-wide association (GWA) mapping analyses to identify candidate causal genes, polymorphisms, and pathways affecting quantitative traits. The many GWA studies utilizing the DGRP have revealed substantial natural genetic variation for all reported traits, little evidence for variants with large effects but enrichment for variants with low P-values, and a tendency for lower frequency variants to have larger effects than more common variants. The variants detected in the GWA analyses rarely overlap those discovered using mutagenesis, and often are the first functional annotations of computationally predicted genes. Variants implicated in GWA analyses typically have sex-specific and genetic background-specific (epistatic) effects, as well as pleiotropic effects on other quantitative traits. Studies in the DGRP reveal substantial genetic control of environmental variation. Taking account of genetic architecture can greatly improve genomic prediction in the DGRP. These features of the genetic architecture of quantitative traits are likely to apply to other species, including humans. WIREs Dev Biol 2018, 7:e289. doi: 10.1002/wdev.289 This article is categorized under: Invertebrate Organogenesis > Flies.

Charting the genotype-phenotype map: lessons from the Drosophila melanogaster Genetic Reference Panel

Understanding the genetic architecture (causal molecular variants, their effects, and frequencies) of quantitative traits is important for precision agriculture and medicine and predicting adaptive evolution, but is challenging in most species. The Drosophila melanogaster Genetic Reference Panel (DGRP) is a collection of 205 inbred strains with whole genome sequences derived from a single wild population in Raleigh, NC, USA. The large amount of quantitative genetic variation, lack of population structure, and rapid local decay of linkage disequilibrium in the DGRP and outbred populations derived from DGRP lines present a favorable scenario for performing genome-wide association (GWA) mapping analyses to identify candidate causal genes, polymorphisms, and pathways affecting quantitative traits. The many GWA studies utilizing the DGRP have revealed substantial natural genetic variation for all reported traits, little evidence for variants with large effects but enrichment for variants with low P-values, and a tendency for lower frequency variants to have larger effects than more common variants. The variants detected in the GWA analyses rarely overlap those discovered using mutagenesis, and often are the first functional annotations of computationally predicted genes. Variants implicated in GWA analyses typically have sex-specific and genetic background-specific (epistatic) effects, as well as pleiotropic effects on other quantitative traits. Studies in the DGRP reveal substantial genetic control of environmental variation. Taking account of genetic architecture can greatly improve genomic prediction in the DGRP. These features of the genetic architecture of quantitative traits are likely to apply to other species, including humans. WIREs Dev Biol 2018, 7:e289. doi: 10.1002/wdev.289 This article is categorized under: Invertebrate Organogenesis > Flies.