Many types of genomic datasets—including RNA sequencing (RNAseq) and DNA methylation—are influenced by innumerable sources of variability. Frequently, analyses of such variability focus on local effects due to genetics, often overlooking the components of variability related to context-level, individual-level, or environmental effects. Here, we leverage the idea that sources of variability are often conserved across genomic datasets to propose two approaches to partition variability: first into distinct biological and technical components, and second into orthogonal context-specific and context-shared genetic components. Using our methods, we perform more powerful and interpretable genomic association studies (such as transcriptome- or epigenome-wide association studies), and we uncover that heritability is more context-specific at the level of single-cell RNAseq, whereas it is more context-shared at the level of bulk (tissue) RNAseq. Subsequently, we perform an analysis of medical records to elucidate the informativeness and impacts of multiple genomics data types on phenotype imputation tasks. We show that risk scores derived from one’s methylation are more informative than risk scores derived from one’s genotypes in imputation tasks. The work presented here shows lasting impact on the design of multiple classes of genomic association studies as well as studies of the utility of genomic biomarkers in electronic medical records.

It is well-established that proteins are dynamic molecules, endlessly interconverting back and forth between different conformational substates. A primary goal of structural biology is to understand the functional relevance of this conformational polymorphism. The work described here demonstrates the connection between conformational polymorphism and specialized protein functions in the BMC-domain superfamily of symmetric protein oligomers that form the semi-permeable, polyhedral shells of bacterial microcompartment organelles. Three specific structural and biochemical studies of BMC-domain proteins are presented as examples. The first of these studies focuses on a tandem BMC-domain protein, EutL, in which broken oligomeric symmetry allows for a conformational rearrangement that relates to molecular transport functions. The results presented support a model of allosteric regulation of EutL function. The second study presented highlights a case of a difficult structure determination of a BMC-domain protein, CcmK1 (L11K), in which the arrangement of molecules in the crystal lattice suggests the protein oligomers have lower internal symmetry than previously believed, resulting from conformational polymorphism. The third study aims to characterize a BMC-domain shell protein, GrpU, in which an unexpected occurrence of broken symmetry allows the formation of a unique iron-sulfur cluster binding site. These three examples collectively illuminate the role of conformational polymorphism in the BMC-domain family, and provide interesting insight into the complex transport properties of the bacterial microcompartment shell, which remains relatively poorly understood. Finally, a crystallographic analysis is presented that extends the present study beyond the BMC-domain proteins by exploring a novel methodology for detecting and characterizing conformational polymorphism, which can be applied broadly in protein crystallography.