Transcriptome‐wide genotype–phenotype associations in Daphnia in a predation risk environment

Abstract

Phenotypic variation plays an important role in how species cope with environmental challenges. Pinpointing which genes and genomic regions are underlying phenotypic variability thus helps to understand the processes of acclimation and adaptation. We used Daphnia as a system to identify candidates playing a role in phenotypic variation related to a predation risk environment with a genome‐wide association approach. Furthermore, a gene co‐expression network analysis allowed identifying clusters of co‐expressed genes which correlated to life history traits. To enhance the understanding of the functional roles of the transcripts, we identified orthologs and paralogs from related species and used ontologies to annotate the candidates of interest. Our study revealed that only one life history trait and two morphometric traits have a genetic association in the presence of predation risk (fish kairomones), whereas most genotype–phenotype associations were detected in a genotype–environment interaction analysis for reproduction‐related phenotypic traits. The gene co‐expression network analysis identified a total of 44 modules, of which one module correlated to another life history trait namely the ‘total number of broods’. The combined use of gene co‐expression network and transcriptome‐wide association analysis allowed the identification of 131 candidate transcripts associated with life history traits in Daphnia galeata. These results lay the ground for targeted studies to further understand phenotypic variability in this species.

Capturing the rapidly evolving study of adaptation

“…This method – which exploits the fact that genetic variation is scored at high resolution throughout the genome and focuses on patterns of covariation among neighbouring loci – is clearly conceptually distinct from an approach where genetic variation is scored separately at each locus or averaged across loci . Similar reasoning applies to approaches (and their empirical applications) that make use of recombination rate variation for improved parameter inference, or which describe covariation in gene expression among transcripts by using networks (Fruciano et al., 2019; Langfelder & Horvath, 2007; Ravindran et al., 2021; Zhang & Horvath, 2005). Conceptually, all these tools make use of covariation within a certain data type.…”

“…For instance, Ravindran et al. (2021) sought to uncover the genetic basis of phenotypic variation in Daphnia for traits of adaptive value under high predation risk. By using genotypic and phenotypic data in genome‐wide association in combination with weighted gene co‐expression network analyses, these authors identified several candidate transcripts associated with relevant life‐history traits.…”

Trehalose mediates salinity-stress tolerance in a crustacean

“…As a keystone species in standing freshwater bodies, Daphnia magna is a widespread crustacean across the Holarctic 21 . It has become a primary model to understand genetics in an environmental context 22,23 , by linking important ecological traits, such as resistance to environmental stressors [24][25][26][27] , to genomic regions. A powerful aspect of the Daphnia system is the possibility to breed animals both sexually and asexually (clonal), enabling researchers to separate genetic and non-genetic effects in common garden experiments.…”