Back

Cis-regulation of gene expression between sexes and life stages in Rumex hastatulus

Yuan, M.; Sacchi, B. M.; Choudhury, B. I.; Barrett, S. C. H.; Stinchcombe, J. R.; Wright, S. I.

2025-06-20 evolutionary biology
10.1101/2025.06.16.659834 bioRxiv
Show abstract

The potential for conflict between sexes and life stages while sharing predominantly the same genome has important evolutionary consequences. In dioecious angiosperms, genes beneficial for the haploid pollen stage may reduce the fitness of diploid offspring of both males and females. However, we still lack an understanding of the extent of shared genetic architecture for gene expression between the sexes or life stages in plants, a key component for predicting the scope for conflict. We performed expression quantitative trait loci (eQTL) mapping to test if standing variation affects sexes and life stages differently using a population sample of the dioecious outcrossing plant Rumex hastatulus. We compared effect sizes and allele frequencies of cis-eQTLs in male and female leaf tissues and pollen and tested for genotype-by-sex interactions for gene expression. We found stronger shared genetic architecture between sexes than between the life stages. In addition, comparisons of the site frequency spectra for cis-eQTLs to a null distribution found no evidence for a genome-wide pattern consistent with purifying selection. Rare alleles had both up- and down-regulation of gene expression. Our results suggest that any conflict over optimal gene expression between pollen and leaves may be easily resolved due to their distinct genetic architectures, whereas there is more scope for conflict between the sexes in gene expression for leaves, which earlier studies indicate are sexually dimorphic. Our study highlights the use of eQTLs to investigate selection on gene expression and the evolution of conflict between sexes and life stages in dioecious species.

Published in Molecular Biology and Evolution (predicted rank #5) · training set

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.