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

Area of Science:

• Genomics
• Population Genetics
• Systems Biology

Background:

• Few studies explore genetic architecture of gene expression in natural, outbreeding populations.
• Biological networks are often scale-free, offering resilience to mutations.
• The interplay between selection, gene expression variation, and network structure is understudied.

Purpose of the Study:

• Investigate the genetic architecture of natural gene expression variation in Populus tremula.
• Examine the relationship between gene expression, co-expression network topology, and selection.
• Determine the role of selection in shaping gene expression variation in natural populations.

Main Methods:

• RNA-Sequencing to profile gene expression in Populus tremula winter buds.
• Expression Quantitative Trait Locus (eQTL) mapping to identify genetic associations.
• Co-expression network inference and analysis of network topology and selection signatures.

Main Results:

• Identified 164,290 significant eQTLs linking 6,241 genes (eGenes) to 147,419 SNPs (eSNPs).
• Local eQTLs were more frequent and had larger effect sizes than distant eQTLs, primarily in regulatory regions.
• eGenes were underrepresented in network hubs and enriched in the periphery; higher connectivity correlated with stronger purifying selection.

Conclusions:

• Purifying selection is a key driver of the genetic architecture of natural gene expression variation in Populus tremula.
• Network connectivity is associated with the strength of purifying selection, influencing gene expression regulation.
• Integrated genetic and genomic analyses provide insights into the evolution of gene expression in natural populations.