Finding the sources of missing heritability in a yeast cross

For many traits, including susceptibility to common diseases in humans, causal loci uncovered by genetic mapping studies explain only a minority of the heritable contribution to trait variation. Multiple explanations for this "missing heritability" have been proposed. Here we use a large cross between two yeast strains to accurately estimate different sources of heritable variation for 46 quantitative traits and to detect underlying loci with high statistical power. We find that the detected loci explain nearly the entire additive contribution to heritable variation for the traits studied. We also show that the contribution to heritability of gene-gene interactions varies among traits, from near zero to 50%. Detected two-locus interactions explain only a minority of this contribution. These results substantially advance our understanding of the missing heritability problem and have important implications for future studies of complex and quantitative traits

The genetic landscape of protein-protein interaction specificity

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biology, 2020Cataloged from student-submitted PDF of thesis.Includes bibliographical references.Protein-protein interaction specificity is often encoded at the primary sequence level, and by just a few interfacial residues. Collectively, these residues have both positive and negative roles, promoting a desired, cognate interaction and preventing non-cognate interactions, respectively. However, for most protein-protein interactions, the contributions of individual specificity residues are poorly understood and often obscured by robustness and degeneracy of protein interfaces. Using bacterial toxin-antitoxin systems as a model, we use a variant of deep mutational scanning to dissect the positive and negative contributions of antitoxin residues that dictate toxin specificity. By screening a combinatorially complete library of antitoxin variants, we uncover a distribution of fitness effects for individual interface mutations measured across hundreds of genetic backgrounds. We show that positive and negative contributions to specificity are neither inherently coupled nor mutually exclusive. Further, we argue that the wild-type antitoxin may be optimized for specificity, because mutations that further destabilize the non-cognate interaction also weaken the cognate interaction. No mutations strengthen the cognate interaction. By comparing crystal structures of paralogous complexes, we provide a structural rationale for all of these observations. Finally, we use a library approach to identify hundreds of novel systems that are insulated from their parental systems, and that carry only two mutations - a negative specificity element on the toxin, and one on the antitoxin. This result demonstrates that highly similar (and in this case, nearly identical) complexes can be insulated using compensatory mutations of individually large effect. Collectively, this work provides a generalizable approach to understanding the logic of molecular recognition.by Thúy-Lan Võ Lite.Ph. D.Ph.D. Massachusetts Institute of Technology, Department of Biolog

Finding the sources of missing heritability in a yeast cross.

For many traits, including susceptibility to common diseases in humans, causal loci uncovered by genetic-mapping studies explain only a minority of the heritable contribution to trait variation. Multiple explanations for this 'missing heritability' have been proposed. Here we use a large cross between two yeast strains to accurately estimate different sources of heritable variation for 46 quantitative traits, and to detect underlying loci with high statistical power. We find that the detected loci explain nearly the entire additive contribution to heritable variation for the traits studied. We also show that the contribution to heritability of gene-gene interactions varies among traits, from near zero to approximately 50 per cent. Detected two-locus interactions explain only a minority of this contribution. These results substantially advance our understanding of the missing heritability problem and have important implications for future studies of complex and quantitative traits