Abstract

Changes in gene regulation have been proposed as critical in the evolution of phenotypic diversity of mammals, especially primates. However, the lack of high-quality reference genomes for most species and the limited number of independently derived transcripts for non-human primates has made it difficult to study gene regulation across multiple primates. To overcome these problems, I will describe how we used massively-parallel sequencing to interrogate mRNA samples extracted from the livers of 16 species (12 primates including human, and 4 non-primate out groups; 4 samples per species). Of the 12 primate species, 8 do not have currently available reference genome sequences, which means that we had to assemble their transcriptomes de novo. This study design results in the generation of nucleotide sequence, quantitative expression, and gene structure data from thousands of genes, enabling insights into gene regulation and sequence evolution across a broad spectrum of primate species. I will discuss how our analysis reveals sets of genes whose expression levels are consistent with the action of natural selection along individual or ancestral primate lineages. Further, I will give examples of specific genes whose function and expression pattern we hypothesize may underlie particular adaptive processes.

Understanding the sets of genes that are differentially expressed between species and associating these changes with known phenotypic information is important. However, it is also vital to understand the mechanisms by which gene expression levels are regulated. To address this, in the second part of my presentation, I will describe initial results from a study where we have assayed gene expression levels in F0 and F1-crosses of three closely-related mouse strains (BL6, AJ, and CAST ) using RNA -sequencing. Our analysis (using a Bayesian statistical framework) enables a comparison of gene expression levels in the F1 crosses to the corresponding parental expression levels, allowing the identification of genes whose expression levels are consistent with:

1. Imprinting
2. A pattern of cis regulation
3. A pattern of trans regulation

Finally, I will describe how we can use this classification to obtain insights into the regulation of gene expression levels.