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

Several studies have investigated general properties of the genetic architecture of gene expression variation. Most of these used controlled crosses and it is unclear whether their findings extend to natural populations. Furthermore, 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. Here we utilise RNA-Sequencing to assay gene expression in winter buds undergoing bud flush in a natural population of Populus tremula. We performed expression Quantitative Trait Locus (eQTL) mapping and identified 164,290 significant eQTLs associating 6,241 unique genes (eGenes) with 147,419 unique SNPs (eSNPs). 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 (UTRs or flanking regions), regardless of whether they were local or distant. 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 flushing leaf buds of P. tremula and that connectivity within the co-expression network is linked to the strength of purifying selection. Author summary Numerous studies have shown that many genomic polymorphisms contributing to phenotypic variation are located outside of protein coding regions, suggesting that they act by modulating gene expression. Furthermore, phenotypes are seldom explained by individual genes, but rather emerge from networks of interacting genes. The effect of regulatory variants and the interaction of genes can be described by co-expression networks, which are known to contain a small number of highly connected nodes and many more lowly connected nodes, making them robust to random mutation. While previous studies have examined the genetic architecture of gene expression variation,few were performed in natural populations with fewer still integrating the co-expression network. We undertook a study using a natural population of European aspen (Populus tremula), showing that highly connected genes within the co-expression network are associated with polymorphisms of lower than average effect size, suggesting purifying selection. Furthermore, the most highly connected genes within co-expression network hubs were underrepresented for identified expression quantitative trait loci, suggesting stabilizing selection. In contrast, genes in the periphery of the network displayed signatures of relaxed selective constraint. Highly connected genes are therefore buffered against large expression modulation, providing a mechanistic explanation of how network robustness is established and maintained at the population level.