Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice

The millions of common DNA variations that occur in the human population, or among inbred strains of mice and rats, perturb the expression (transcript levels) of a large fraction of the genes expressed in a particular tissue. The hundreds or thousands of common cis-acting variations that occur in the population may in turn affect the expression of thousands of other genes by affecting transcription factors, signaling molecules, RNA processing, and other processes that act in trans. The levels of transcripts are conveniently quantitated using expression arrays, and the cis- and trans-acting loci can be mapped using quantitative trait locus (QTL) analysis, in the same manner as loci for physiologic or clinical traits. Thousands of such expression QTL (eQTL) have been mapped in various crosses in mice, as well as other experimental organisms, and less detailed maps have been produced in studies of cells from human pedigrees. Such an integrative genetics approach (sometimes referred to as “genetical genomics”) is proving useful for identifying genes and pathways that contribute to complex clinical traits. The coincidence of clinical trait QTL and eQTL can help in the prioritization of positional candidate genes. More importantly, mathematical modeling of correlations between levels of transcripts and clinical traits in genetic crosses can allow prediction of causal interactions and the identification of “key driver” genes. An important objective of such studies will be to model biological networks in physiologic processes. When combined with high-density single nucleotide polymorphism (SNP) mapping, it should be feasible to identify genes that contribute to transcript levels using association analysis in outbred populations. In this review we discuss the basic concepts and applications of this integrative genomic approach to cardiovascular and metabolic diseases

Identification of a Genetic Locus on Chromosome 11 That Regulates Leukocyte Infiltration in Mouse Carotid Artery

exterior, long view of the rear building, August 199

On the origin of the chemical barrier and tunneling in enzymes

This paper presents both a review of some recent results from our group and experimental groups, and some new theoretical results all of which are helping to form a more physically rigorous picture of the process of enzymatic catalysis. A common classical picture of enzymatic catalysis is the transition state tight binding model. Schwartz and Schramm (Nat. Chem. Biol. 2009, 5, 551-558.) have recently argued from both theoretical and experimental results that this picture is incorrect. We now investigate what the nature of barriers might be in enzymatic reactions, and what this viewpoint might imply for tunneling in a hydrogen transfer enzyme. For lactate dehydrogenase we conclude that the enzymes role in catalysis is at least partially to hunt through configuration space for those configurations that minimize chemical free energy barriers. Those configurations do not seem to be stable basins on the free energy surface, and in fact the overall free energy barrier to reaction may well largely be due to this stochastic hunt-both probabilistically and energetically. We suggest further computations to test this hypothesis