NSF Postdoctoral Fellowship in Biology FY 2019: The Genomic Basis for Dysregulation of Protein Abundance in Maize

Gage, Joseph Lee, Ithaca NY

Investigators

Abstract

This action funds an NSF National Plant Genome Initiative Postdoctoral Research Fellowship in Biology for FY 2019. 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 Joseph Gage is "The Genomic Basis for Dysregulation of Protein Abundance in Maize" The host institutions for the fellowship are Cornell University and Washington University and the sponsoring scientists are Drs. Edward S. Buckler and Richard Vierstra. DNA sequences get translated into proteins, which are important components in determining an organism's size, shape, and health. Small differences in DNA sequence can cause large changes in how much of the resulting protein is made, but little is known about how those changes in DNA sequence affect protein quantity. To learn more about the relationship between DNA sequence and protein quantity, this research will measure the abundance of thousands of different proteins produced by twenty-seven diverse varieties of maize (corn). Genome sequences as well as gene expression levels will be used to learn how differences in DNA sequence result in differing amounts of protein. The data generated will be used to build machine learning models that can predict protein abundance from DNA sequence alone. The findings from this study will provide new insights into how complex traits (like an organism's size, shape, or health) are controlled by differences in DNA sequence spread throughout the genome. Broader impacts include mentoring and training undergraduate and graduate students as well as participating in the Skype-A-Scientist program (https://skypeascientist.com) which pairs scientists in various STEM disciplines with classrooms of children for question and answer sessions. Training objectives include obtaining expertise in bioinformatics, molecular genetics, proteomics, transcriptomics, application of machine learning, and functional genomics. Proteins are a crucial determinant of phenotype. As the ultimate step in the central dogma of molecular biology, their presence and abundance determine phenotypic state. To date, there are no published studies of proteomic variability between genetically diverse members of an economic important crop plant species. This project seeks to develop a model of how rare and deleterious alleles cause dysregulation of protein abundance by affecting translation, transport, and degradation via changes to protein structure and function in maize. This research will break new ground in maize functional genomics and proteomics by integrating pre-existing genomic data with newly generated time-series transcriptomic data and proteomic characterization of twenty-seven diverse maize inbred lines to generate a multi-omic dataset that captures all three levels of the central dogma of molecular biology: DNA, RNA, and protein. Since genomic variants can affect protein abundance by dysregulation of either transcription, translation, or both, transcript and protein abundance will be used together to assess specifically how genetic variants impact translation on a genome-wide scale. Genetic variants with influential effects on translation will be identified and characterized for their effects on protein secondary structure, solvent accessibility, contact between residues, and intrinsic disorder. These features will be used to formulate an overarching model to describe the influence of rare and deleterious variants on protein abundance. All proteomic and transcriptomic data generated for the twenty-seven diverse maize inbred lines will be useful for other projects and researchers, and for that reason, it is important that all data be as accessible and organized as possible. Raw reads from 3? RNA sequencing will be deposited on the NCBI-SRA (https://www.ncbi.nlm.nih.gov/sra), and the raw mass spectra from proteomic assays will be made available on the ProteomeXchange database (http://www.proteomexchange.org/). Transcript and protein abundance data will be made available through a DOI and hosted by CyVerse (https://www.cyverse.org/data-store). Keywords: gene expression, dysregulation of protein accumulation, sequencing, proteomics, modeling, maize 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.