Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

2024 Abstracts

Develop Software Tools to Discover Genotype-Specific RNA-Splicing Variants and Microexon Alternative Splicing in Plant Populations

Authors:

Chi Zhang* ([email protected], PI), Yu Shi

Institutions:

University of Nebraska–Lincoln

References

Pre-mRNA splicing is an essential step in the regulation of gene expression. Although extensive research has been conducted, there remain open questions, significant knowledge gaps, and requirements for bioinformatic tools in plants, especially at the population level and for microexon (exons ≤ 15 nucleotides) splicing. What is lacking are efficient and accurate methods to analyze population transcriptome datasets to define and identify the full spectrum of RNA- splicing variants and link these RNA-splicing variants to phenotype in plant populations. This project’s goals are to create broadly applicable software tools to quantify genotype-specific RNA-splicing (GSS) variants based on multiomics data in a population to facilitate gene function discovery and develop frameworks to associate RNA-splicing variants to identify candidate genes that influence plant adaptability to the environment.

Once a bioinformatics framework capable of analyzing multiomics data to identify high-quality RNA-splicing variations in plant populations is established, it will reveal the link from genotype-specific RNA splicing, to protein functions, and finally to the phenotypic response. This will enable the researchers to comprehend how RNA-splicing regulation translate into organismal phenotypes and underlying molecular mechanisms that determine phenotypic outcomes in response to perturbations of complex biological systems. To achieve these goals and construct integrative computational tools, the team is currently (1) developing an online database of microexons for 132 plant genomes; (2) developing the second version of microexon modeling software tools (ME modeler version 2) to model microexons in plants more efficiently and more accurately; and (3) developing VaSP2 for alternative splicing analysis in plant populations.