Gene expression and adaptive noncoding changes during human evolution

Abstract

Background: Despite evidence for adaptive changes in both gene expression and non-protein-coding, putatively regulatory regions of the genome during human evolution, the relationship between gene expression and adaptive changes in cis-regulatory regions remains unclear.

Results: Here we present new measurements of gene expression in five tissues of humans and chimpanzees, and use them to assess this relationship. We then compare our results with previous studies of adaptive noncoding changes, analyzing correlations at the level of gene ontology groups, in order to gain statistical power to detect correlations.

Conclusions: Consistent with previous studies, we find little correlation between gene expression and adaptive noncoding changes at the level of individual genes; however, we do find significant correlations at the level of biological function ontology groups. The types of function include processes regulated by specific transcription factors, responses to genetic or chemical perturbations, and differentiation of cell types within the immune system. Among functional categories co-enriched with both differential expression and noncoding adaptation, prominent themes include cancer, particularly epithelial cancers, and neural development and function.

Keywords: Adaptation; Gene expression; Gene function; Gene regulation; Human evolution.

Fig. 1

Boxplot of the –log10(qvalue) distributions from the GLM examining the Tissue (left, orange) and Species (right, green) effects

Fig. 2

Correlation between tissue specificity and gene expression divergence between humans and chimpanzees. There is a significant correlation between higher specificity to a tissue and expression divergence (adipose tissue as an example here)

Fig. 3

Bubble plot of GO Biological Process enrichments for gene expression differences across five tissues between human and chimpanzee. To display these traits visually, we calculated an optimal 2-dimensional arrangement using non-metric multidimensional scaling on the between-category sematic similarity scores, a measure of a priori relatedness of traits. Traits whose SimREL distance is less than 0.5 are considered similar within the GO Biological Process ontology tree (code available on request). The significantly differentially expressed categories are displayed on the same axes, but separated into two plots for clarity. In each plot, the intensity of the colors of the circles and text indicate the evidence for differential expression of each trait. The area of the circle is proportional to the log of the number of genes counted in each trait

Fig. 4

Ideogram of clustering of significant differentially expressed genes in humans compared to chimpanzees across tissues (red bars highlight the chromosomal enrichment regions in Table 1)