Improving Plant Breeding in Polyploid Crops Using Models for Demography and Selection

Blischak Paul D, Columbus OH

Investigators

Abstract

This action funds an NSF National Plant Genome Initiative Postdoctoral Research Fellowship in Biology for FY 2018. The fellowship supports a research and training plan in a host laboratory for the Fellow who also presents a plan to broaden participation in biology. The title of the research and training plan for this fellowship to Dr. Paul Blischak is "Improving Plant Breeding in Polyploid Crops Using Models for Demography and Selection." The host institution for the fellowship is the University of Arizona and the sponsoring scientists are Drs. Michael Barker and Ryan Gutenkunst. The process of domestication impacts levels of genetic diversity through the selection of individuals with desirable characteristics. Discovering what genes are associated with these agriculturally important traits can therefore be difficult as a result of this initial population bottleneck. Many agricultural species also have additional sets of chromosomes as a result of whole genome duplication (polyploidy), further complicating genetic analyses. This project focuses on the development of computational tools to identify domestication-related genes for crop improvement in polyploid species. These methods will be applied to canola (Brassica napus), an economically important polyploid crop responsible for the production of vegetable and synthetic oils, livestock feed, and biofuels. Training objectives include the development of statistical and computational methods and their application to the improvement of plant breeding efforts in polyploid crops. Broader impacts include the development of open-source software, tutorials, and teaching materials that can be used by plant breeders and educators. Tools for the analysis of genome-wide DNA sequence data that aim to understand the process of domestication in polyploid crops are generally lacking. The main goals of this research are (1) to develop statistical models for the analysis of historical demography in polyploid crops, (2) to use these methods to infer the demographic history of B. napus, and (3) to leverage this demographic information to better identify domestication-related genes. This will be achieved through the implementation of new models in the Python package DaDi (Diffusion Approximation for Demographic Inference), applying these models to B. napus, and using the results to perform genome-scale simulations for the identification of genes under positive selection. All data, scripts, and protocols for this project will be made available in public repositories, and all software will be freely available and open source. Keywords: Brassica, canola, demography, domestication, polyploidy, selection This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.