Submitted by John Vogel on
Successful reproduction between different species is very rare in mammals, but it is quite common in plants, and is often a key process in their evolution. When such a hybridization is accompanied by genome duplication, the offspring is called an allopolyploid. Allopolyploids such as wheat, cotton, canola, strawberry and peanut must balance the activities of multiple complete and distinct genomes in a single nucleus. RNA sequencing (RNA-seq) is a very widely used technology for studying gene expression. The purpose of our project is to develop a large and diverse RNA-seq dataset for the allopolyploid grass Brachypodium hybridum, and its diploid parents, with the goal of using these data to study how allopolyploidy affects global trends in gene expression. Brachypodium is a popular model organism for studying grasses—it is a close relative of wheat, but it is easier to grow and its genome is 30 times smaller. Thus our results should be highly relevant to many important crops, particularly cereals.
The modern view of gene expression sees the transcriptome as a highly interconnected network, where each gene represents a node. By performing RNA-seq on tissues harvested from plants under diverse conditions, we will build a gene expression network for B. hybridum and for its diploid parents. We will explore whether this framework--merging of two networks into a single network--is truly an apt way of representing gene expression in allopolyploids. In addition to this fundamental question, we expect that certain biological pathways will be differently regulated in the allopolyploid. Examples are nitrogen and phosphorous usage, which are so critical for the maintenance of large amounts of DNA, or photosynthesis, which may need to adjust to increased metabolic demands. This project will scrutinize the mathematical frameworks we use to represent complex biological systems, and explore how hybridization affects agronomically important biological pathways in a crop-like plant.
The student will collect tissue from various organs of diploid and polyploid Brachypodium, subjected to various stresses such as drought or hormone treatment. The student will have some freedom in choosing stress treatments they are interested in, provided that the treatments are not cost-prohibitive. They will then extract and process RNA from these tissue samples for RNA-seq. A single semester will not be sufficient time for the student to receive and analyze their own RNA-seq data, but nonetheless the student will have the opportunity to analyze RNA-seq data for a similar Brachypodium project. Through this effort the student will develop bench skills and become familiar with RNA-seq, an extremely useful skillset in many fields of biology. They will also learn best practices of bioinformatic data analysis, and receive a gentle introduction to the R programming language if desired.
No particular qualifications necessary. Introductory biology coursework is a plus.