Zia Khan, Ph.D.
University of Maryland, College Park
Center for Bioinformatics and Computational Biology (CBCB)
Understanding how genetic differences affect phenotypic variation within and between species is a central goal
of evolutionary and medical genetics. In this talk, I present two stories related to this important goal. The
first is a study of mRNA expression and protein abundance divergence between human, chimpanzee, and rhesus
macaque lymphoblastoid cell lines using RNA-seq and high-resolution, quantitative mass spectrometry data. Our
results show that protein abundance levels between primates evolve under much stronger evolutionary constraint
than mRNA expression levels. We use data from all three species to computationally identify genes whose
regulation might have evolved under natural selection, and considered jointly, our data allowed us to identify
genes where human-specific changes might specifically affect post-transcriptional regulation. The second story
focuses on a data set where we collected genome-wide quantitative mass spectrometry along with ribosomal
profiling data for 62 human lymphoblastoid cell lines, for which RNA-sequencing and genotype information is
also available. From our analysis, we find substantial sharing of genetic effects on gene regulation from RNA
to protein, presumably through effects on transcriptional regulation. However, a large fraction of these
variants have attenuated effects on protein levels, suggesting that their downstream effects are often
buffered. We find scarce evidence of variants that effect ribosome occupancy, independent of mRNA levels.
Therefore, variants that effect protein levels independent of mRNA levels are likely due to changes in
post-translational regulation. Overall, these two stories highlight the importance of studying multiple
regulatory layers to better understand phenotypic variation within and between species.
Hosted by Olivier Elemento, Ph.D.