Title: "Cross-species eQTL mapping for identifying causal relationships between parasites and hosts"
Speaker: Dahlia Nielsen; Department of Biological Sciences, North Carolina State University

Place: Materials and Electrical Engineering (MSEE) B012
Date: March 10, 2014; Tuesday
Time: 4:30pm


Most species of plants and animals, including humans, engage in both beneficial and detrimental symbiotic relationships with other organisms. Of these interactions, parasitic symbioses are especially pernicious. Nematodes alone infect up to half the world's human population, and crop plants and livestock experience substantially reduced yield worldwide from nematode infection. It is apparent from the complexity of parasite life cycles that both host and parasite engage in a well-orchestrated molecular exchange; however, the identity of responsible molecules remains largely unknown. Filling that gap is a prerequisite for the design of new control measures. We have developed an approach that we have demonstrated is highly efficacious at addressing this gap. This approach is an extension of expression QTL (eQTL) mapping, a gene mapping technique in which genetic polymorphisms influencing gene expression regulation are identified. This technique has proven to be a successful tool for identifying genetic pathways and determining how they are disrupted by genetic disorders, disease, or infection. Our extension examines interactions across species - allowing us to detect genetic loci in one organism that modulate expression of the genes of another organism. This technique is ideally suited for identifying pathways involved in the progression of parasitic infections and subsequent host responses. I will illustrate the efficacy of our approach with a proof-of-concept experiment we have performed using a plant-parasite model, and will discuss the application of the method to other biological systems.

Associated reading:
1. Jacek Majewski and Tomi Pastinen. 2011.The study of eQTL variations by RNA-seq: from SNPs to phenotypes. Trends in Genetics. 27(2):72-79.

2. F. Alex Feltus. 2014. Systems genetics: A paradigm to improve discovery of candidate genes and mechanisms underlying complex traits. Plant Science 223:45-48.

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