Torgeir Hvidsten - Gene co-expression network connectivity is an important determinant of selective constraint

Systems biology has established that biological networks are buffered against large effect mutations, but there remains little data resolving this with natural variation of gene expression. We utilised RNA-Sequencing to assay gene expression in a natural population of aspens and performed expression Quantitative Trait Locus (eQTL) mapping. We found approximately four times as many local as distant eQTLs, with local eQTLs having significantly higher effect sizes. eQTLs were primarily located in regulatory regions of genes. We used the gene expression data to infer a co-expression network and investigated the relationship between network characteristics, gene expression genetic architecture and population genetics parameters: eGenes were underrepresented in network module cores (hubs) and overrepresented in the periphery of the network, with a negative correlation between eQTL effect size and network connectivity. Module core genes have experienced stronger selective constraint on coding and non-coding sequence, with connectivity being more strongly associated with selection signatures than expression level. Our integrated genetics and genomics results suggest that purifying selection is the primary mechanism underlying the genetic architecture of natural variation in gene expression assayed in aspen and that connectivity within the co-expression network is linked to the strength of purifying selection.