NSF Postdoctoral Fellowship in Biology: Interplay of Ploidy and the Distribution of Fitness Effects in Brassica

Conover, Justin L, Ames IA

Investigators

Abstract

This action funds an NSF Plant Genome Postdoctoral Research Fellowship in Biology for FY 2022. 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. Justin Conover is “Interplay of Ploidy and the Distribution of Fitness Effects in Brassica”. The host institution for the fellowship is the University of Arizona and the sponsoring scientists are Drs. Michael Barker and Ryan Gutenkunst. The domestication of wild plants to create agricultural crops resulted in many changes in their genomes. Understanding those changes can deepen our understanding of agricultural history and potentially guide future crop improvements. DNA mutations can affect an individual’s evolutionary fitness (ability to survive and reproduce), with consequences ranging from lethality, to having no effect, to being highly beneficial. However, our understanding of mutation fitness effects in crops is incomplete, largely because many crops have more than two complete sets of chromosomes, which complicates genomic analyses and may affect how mutations change fitness. This project will develop new approaches to understand the fitness effects of mutations in plants and apply them to multiple economically important Brassica crops, including canola, broccoli, cauliflower, and turnips. The tools developed and insights gained will be applicable to many other crops including cotton, wheat, peanuts, and quinoa. Broader impacts from this project will increase the participation of students from historically underrepresented groups in STEM, including Alaskan Natives and Native Americans, as well as members of the LGBTQ+ community, through paid research opportunities and free public workshops to prepare application materials for graduate schools and external fellowships. Training objectives include obtaining expertise in the application of computational and statistical methods to population-level genomic data and the analysis of gene expression data. The distribution of fitness effects (DFE) of new mutations is a fundamental concept in population genetics that is important for understanding and predicting how natural selection operates in populations. Considerable attention has been given to understand how properties of the DFE can differ between populations in animal model systems, but DFE research has been relatively neglected in plants. Although many crop systems have undergone recent and recurrent whole genome duplication (polyploidy) events, often accompanied by interspecific hybridization, the ways in which shifts in ploidy levels affect the DFE in plants are poorly understood. This project uses allopolyploid Brassica napus, and its diploid progenitors B. rapa and B. oleracea to characterize how ancient and recent polyploidy events influences the DFE of a population and to model correlations in the DFE between the subgenomes of a single allopolyploid population. The work will be achieved primarily through the use and development of the Python package dadi (Diffusion Approximation for Demographic Inference) and publicly available transcriptomic and whole-genome resequencing data. All data, scripts, and methodological advances will be made available in public repositories, and all software will be open-source and freely available. 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.