Addressing missing context in regulatory variation across primate evolution

Abstract

In primates, loci associated with adaptive trait variation often fall in non-coding regions. Understanding the mechanisms linking these regulatory variants to fitness-relevant phenotypes remains challenging, but can be addressed using functional genomic data. However, such data are rarely generated at scale in non-human primates. When they are, only select tissues, cell types, developmental stages, and cellular environments are typically considered, despite appreciation that adaptive variants often exhibit context-dependent effects. In this review, we 1) discuss why context-dependent regulatory loci might be especially evolutionarily relevant in primates, 2) explore challenges and emerging solutions for mapping such context-dependent variation, and 3) discuss the scientific questions these data could address. We argue that filling this gap will provide critical insights into evolutionary processes, human disease, and regulatory adaptation.

Keywords: context-dependent gene regulation; evolution; functional genomics; genetics of adaptation; primates.

Figure 1.. Dimensions of context-dependent regulatory variation to be characterized across primates.

Depiction of the various functional genomic datasets that could be collected across tissues, cell types, developmental stages, and cellular environments for diverse primate species to identify context-dependent regulatory loci. Heatmaps represent the possibility of measuring molecular phenotypes (e.g., gene expression) from different contexts across different individuals, subspecies, and species within the primate order (note the heatmap values themselves are not biologically based nor do they represent biological hypotheses). In the stacked heatmaps, each level represents variation across developmental stages, ranging from undifferentiated, pluripotent cells (bottom), to differentiating and maturing cells (middle), and lastly fully differentiated cells (top) across a variety of different tissues. In the right panel with the 2-dimensional heatmap, each row represents variation across different cellular environments for a given cell type, in a given tissue, for a given set of primate individuals. The primate phylogenetic tree was generated using data from the 10kTrees website Version 3 [96], and portions of this figure were created with BioRender.com.

Figure 2.. Existing expression QTL studies conducted in NHPs.

Summary of findings from a literature review of existing expression QTL studies in NHPs (see Supplemental Text). (A) Histogram displaying the number of studies that include samples from a given genus, with colors denoting the tissue or cell type examined in each study. Some studies include more than one species and/or more than one tissue or cell type. In the figure legend, the numbers listed next to each tissue or cell type represent the number of studies that include such samples. (B) Pie chart depicting the number of studies that contained multi-tissue or multi-cell type analyses (‘Yes’) or were conducted in only one tissue or cell type (‘No’). (C) Pie chart depicting the number of studies that contained imposed, experimental environments (‘Yes’) or were conducted at baseline (‘No’). Silhouette images were created with BioRender.com.