Sex differences in interindividual gene expression variability across human tissues

Abstract

Understanding phenotypic sex differences has long been a goal of biology from both a medical and evolutionary perspective. Although much attention has been paid to mean differences in phenotype between the sexes, little is known about sex differences in phenotypic variability. To gain insight into sex differences in interindividual variability at the molecular level, we analyzed RNA-seq data from 43 tissues from the Genotype-Tissue Expression project (GTEx). Within each tissue, we identified genes that show sex differences in gene expression variability. We found that these sex-differentially variable (SDV) genes are associated with various important biological functions, including sex hormone response, immune response, and other signaling pathways. By analyzing single-cell RNA sequencing data collected from breast epithelial cells, we found that genes with sex differences in gene expression variability in breast tissue tend to be expressed in a cell-type-specific manner. We looked for an association between SDV expression and Graves' disease, a well-known heavily female-biased disease, and found a significant enrichment of Graves' associated genes among genes with higher variability in females in thyroid tissue. This suggests a possible role for SDV expression in sex-biased disease. We then examined the evolutionary constraints acting on genes with sex differences in variability and found that they exhibit evidence of increased selective constraint. Through analysis of sex-biased eQTL data, we found evidence that SDV expression may have a genetic basis. Finally, we propose a simple evolutionary model for the emergence of SDV expression from sex-specific constraints.

Fig. 1.

The identification of genes with SDV gene expression. (A) Outline of pipeline to identify SDV genes. (B) The number of genes with SDV expression identified in each tissue. The x-axis has a pseudo-log scale. (C) A total of two examples of SDV genes with higher variation in females (WNT4 in the pituitary gland) and in males (CLEC7A in breast tissue), respectively.

Fig. 2.

Biological properties of SDV genes. (A) Following meta-analysis SDV genes with higher variation in males and females are enriched for terms related to various signaling pathways, immune response, and sex-hormone response. (B) Genes with higher variability in males are enriched for terms related to estrogen and immune response in breast tissue. (C) Following meta-analysis, genes with higher variability in females are enriched for targets of two transcription factors. (D) SDV genes identified in breast tissue show highly cell-type specific expression in breast epithelial tissue (P-value calculated using the Mann–Whitney U test). Higher τ indicates greater cell-type specificity. (E) Genes with higher variability in females in the thyroid are significantly enriched for genes associated with Graves’ disease (P-value calculated using a hypergeometric test).

Fig. 3.

SDV genes are associated with increased constraint. (A) A total of 14 out of 20 tested tissues with at least 20 SDV genes show a depletion in eGenes among SDV genes. Significance was tested using Fisher’s exact test at FDR < 0.05. (B) Across the 20 tested tissues, the median fold enrichment of eGenes is significantly lower than expected by chance. The red line shows the observed median fold-enrichment, while the blue distribution shows the empirical null distribution. (C) Genes with SDV expression in at least one tissue show significantly elevated mean phastCons scores in proximal promoters (100 bp upstream of TSS) indicating increased conservation. (D) Genes with SDV expression in at least one tissue show significantly increased LINSIGHT scores, indicating greater functional importance. (E) Genes with SDV expression in at least one tissue show significantly reduced LOEUF scores, indicating more intolerance to loss of function mutations. For (C)–(E), SDV genes were considered to be SDV if they showed SDV expression in at least one tissue out of the 20 tested tissues. Only genes expressed in all 20 tested tissues were considered to remove bias. For (C)–(E), P-values were calculated using the Mann–Whitney U test.

Fig. 4.

Simulations show that SDV expression can arise through sex-specific constraint. Simulation results showing the output from 30 simulations in both the equal selection and sex-specific selection conditions. (A) Equal constraint in both sexes results in a similar phenotypic variance in both sexes. (B) Increased sex-specific constraint acting in females reduces the phenotypic (expression) variation across individuals. (C) Increased constraint in females results in reduced genetic variance, consistent with our observations of reduced cis-regulatory variation in SDV genes.