Adaptation via natural selection is the process by which the incredible fit between every species and its environment has evolved. Despite its importance, we still have little understanding of which genetic variants have been adaptive in any species, and how these variants act at the molecular level. One classic question is whether most adaptations involve changes in protein sequences, or in cis- regulatory elements; another fundamental question is whether adaptations typically involve single mutations of large effect, or many mutations of small effect. Historically, most studies pinpointing the genetic basis of polymorphic traits have focused on protein sequence changes of large effect, because these have been the simplest to identify. However recent work has suggested that polygenic cis-regulatory adaptations may actually be far more common. Unfortunately these have traditionally been almost impossible to identify, due to the very small individual effect of each variant on the selected trait. Over the past five years, we have developed a method to find these polygenic adaptations from genome-wide data, based on the idea of a ?sign test?. The goal is to identify cases where selection has led to up- or down-regulation of multiple genes via independent mutations. Using this test in yeast, we have identified gene expression adaptations involving toxin resistance, ergosterol biosynthesis, and pathogenicity. Overall, our applications of the sign test have identified several hundred genes involved in cis-regulatory adaptations, including the first examples of gene expression adaptation occurring at the level of pathways and protein complexes; the first known cases of regulatory adaptations affecting behavior and pathogenicity; and the first examples of polygenic gene expression adaptations of any kind in house mice and humans. In this project we have two major goals. First, we will develop computational and experimental tools based on CRISPR/Cas9 technology that will make characterizing cis-regulatory variants far more practical in a wide range of species. Second, we will develop methods for high-throughput mapping of genes contributing to divergence in fitness, the key phenotype for natural selection. This project will also lay the groundwork for future investigations into facets of gene expression evolution important to human health, such as how gene expression evolves in both humans and their pathogens.
The subject of this project?the evolution of gene expression?is of great importance to biomedicine, as illustrated with two examples from our recent work. First, we found that a gene expression adaptation led to the emergence of pathogenicity in a strain of yeast that was isolated from a human AIDS patient; investigating how and why this has occurred may inform our understanding of emerging infectious diseases. Second, the pathway we have studied most intensively, ergosterol biosynthesis, is also the target of most antifungal drugs; we have found an adaptive mutation that increases resistance to a commonly used antifungal drug, Amphotericin B, revealing a mechanism by which drug resistance may evolve.
| Combs, Peter A; Krupp, Joshua J; Khosla, Neil M et al. (2018) Tissue-Specific cis-Regulatory Divergence Implicates eloF in Inhibiting Interspecies Mating in Drosophila. Curr Biol 28:3969-3975.e3 |
| Martin, Trevor; Fraser, Hunter B (2018) Comparative expression profiling reveals widespread coordinated evolution of gene expression across eukaryotes. Nat Commun 9:4963 |
| Artieri, Carlo G; Naor, Adit; Turgeman-Grott, Israela et al. (2017) Cis-regulatory evolution in prokaryotes revealed by interspecific archaeal hybrids. Sci Rep 7:3986 |
| Carja, Oana; MacIsaac, Julia L; Mah, Sarah M et al. (2017) Worldwide patterns of human epigenetic variation. Nat Ecol Evol 1:1577-1583 |
| Kita, Ryosuke; Venkataram, Sandeep; Zhou, Yiqi et al. (2017) High-resolution mapping of cis-regulatory variation in budding yeast. Proc Natl Acad Sci U S A 114:E10736-E10744 |
| Sharon, Eilon; Sibener, Leah V; Battle, Alexis et al. (2016) Genetic variation in MHC proteins is associated with T cell receptor expression biases. Nat Genet 48:995-1002 |
| Agoglia, Rachel M; Fraser, Hunter B (2016) Disentangling Sources of Selection on Exonic Transcriptional Enhancers. Mol Biol Evol 33:585-90 |
| Babak, Tomas; DeVeale, Brian; Tsang, Emily K et al. (2015) Genetic conflict reflected in tissue-specific maps of genomic imprinting in human and mouse. Nat Genet 47:544-9 |
| Naranjo, Santiago; Smith, Justin D; Artieri, Carlo G et al. (2015) Dissecting the Genetic Basis of a Complex cis-Regulatory Adaptation. PLoS Genet 11:e1005751 |
| Artieri, Carlo G; Fraser, Hunter B (2014) Evolution at two levels of gene expression in yeast. Genome Res 24:411-21 |
Showing the most recent 10 out of 18 publications
