Browsing by Subject "MHC"

Genome-wide association studies have identified thousands of DNA variants associated with specific phenotypes, yet it remains unknown which variants are causal. Additionally, more than 90 percent of common variants occur in noncoding genomic regions, further complicating efforts to predict their function. Large consortia efforts have leveraged functional genomics assays to characterize the genome-wide and epigenome-wide features of noncoding regions and common candidate cis-regulatory elements. However, these predictions are largely based on DNA sequence or correlation of epigenome marks alone, and do not provide information for which genes and broader regulatory networks are controlled by these candidate cis-regulatory elements. Advancements in CRISPR/Cas9-based genome and epigenome editing tools and multiplexed screening assays have enabled systematic perturbation of candidate cis-regulatory elements. We first sought to establish principles for performing noncoding CRISPR screens. We next applied these principles to investigate a subclass of cis-regulatory elements that respond to mechanical stimuli. Finally, we combined noncoding CRISPR screening approaches with single cell transcriptome profiling to clarify the regulatory landscape in diverse cell types in the Major Histocompatibility (MHC) Locus, one of the most complex regions of the human genome. Through these efforts, we establish guidelines for noncoding CRISPR screen design, execution, and analysis, identify mechanosensitive cis-regulatory elements and their role in complex cellular processes, and reveal cell-type specific and shared regulatory mechanisms governing gene expression in the MHC locus. Collectively, these studies provide experimental and computational frameworks for future investigation of cis-regulatory element function and will enable further dissection of variant-gene-phenotype relationships.

The threats of human encroachment and climate change are increasing and understanding the interplay between genetic diversity, fitness, and ecological variation has become critical for predicting adaptive responses and species extinction risk. Decreasing genetic diversity, owing to population decline or inbreeding, can be detrimental at the level of the individual, population, or species. One of the major challenges for evolutionary and conservation biologists is identifying the specific genetic components that influence inter-individual variation in fitness remains. As a direct link between genetic-make up and individual fitness, the Major Histocompatibility Complex (MHC) is critical to the activation of the adaptive immune system. Biologist have suggested that in addition to influencing an individual's health, variation at the MHC may be related to an individual's survival and reproductive success. Here, I test this hypothesis using two populations of ring-tailed lemurs (Lemur catta) at long-term study sites to achieve individual and population-level comparisons of MHC diversity and to integrate new genetic technology with behavioral, ecological, and environmental data. First, I address the difficulty of genotyping large populations at hypervariable genes by using next generation sequencing and suggest improvements to current methods. Second, I describe patterns of variation at the MHC-DRB 2nd exon, including diversity between alleles, individuals, and populations. Next, I examine the relationship between MHC-DRB diversity and measures of immunocompetence, parasitism, and survival within a broader framework of ecological variability across captive and wild conditions. Because the MHC is also thought to be important in mate choice and reproduction, I use an experimental approach in captive individuals to investigate possible mechanisms of MHC-based signaling through olfactory communication. Lastly, I link a female's MHC genotype to her reproductive success in the wild and explore if this relationship is altered by environmental stressors. The results of this dissertation emphasize the increasing feasibility of using genetic approaches to investigate the fitness correlates of genetic diversity non-model systems. These advances are critical for future studies and the integration of behavioral, ecological, and genetic perspectives in semi-natural and wild environments.