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Understanding how metabolic reactions, cell signaling, and developmental pathways translate the genome of an organism
into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS) statistically connect genotypes
to phenotypes, without any recourse to known molecular interactions, whereas a molecular biology approach directly ties gene
function to phenotype through gene regulatory networks (GRNs). Using natural variation in allele-specific expression, GWAS
and GRN approaches can be merged into a single framework via structural equation modeling (SEM). This approach leverages
the myriad of polymorphisms in natural populations to elucidate and quantitate the molecular pathways that underlie phenotypic
variation. The SEM framework can be used to quantitate a GRN, evaluate its consistency across environments or sexes, identify
the differences in GRNs between species, and annotate GRNs de novo in non-model organisms.
Sergey Nuzhdin combines expertise in Population Biology (Professor in Evolution and Ecology, UC Davis, 1997-2007) and in Molecular and Computational
Biology (USC, 2007-present). He has published more than 100 papers in peer-review journals, including PLoS Biology, Science, Nature Genetics, and
PNAS; has trained over a dozen of independent investigators; and is serving on several editorial boards, and on NIH panels.
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