Conserved Domains in Promoters of Differentially Expressed Genes Under High Night Temperature Stress in Rice: How to Find Them and What Can They Tell Us?

Authors

Emalynn Tobias, Nova Southeastern UniversityFollow
Jenna M. Handal, Nova Southeastern UniversityFollow
Paul Lup, Nova Southeastern UniversityFollow
Michael Egozi, Nova Southeastern UniversityFollow
Braham Dhillon, University of Florida IFAS, Ft. Lauderdale Research & Education Center
Andy Pereira, University of Arkansas, Fayetteville
Navdeep Gill, Nova Southeastern UniversityFollow

Publication Date

Winter 4-10-2024

Keywords

differently expressed genes, promoters, conserved domains, Cypress, LaGrue, high night temperatures

Abstract

Crop plant response to stress involves changes in gene expression patterns. This complex process of gene regulation depends on the presence of cis- and trans-acting components. One of the key steps in understanding changes in gene expression associated with a plant’s response to stress begins with the identification of “conserved domains” in the promoters of differentially expressed genes (DEGs). The conserved domains can play a crucial role in gene regulation by providing binding sites for transcription factors. In this study, we aim to identify the cis-regulatory elements (CREs) in the promoters of 149 DEGs that were identified in the transcriptomic analysis of two rice varieties- Cypress and LaGrue. These two rice varieties are known to perform well and poorly, respectively, under high night temperatures (HNT) based on their ability to withstand heat stress. It is expected that the DEGs that are up- or down-regulated by HNT stress, either exhibit a shared set of CREs in their promoters or harbor polymorphic patterns that are common to specific DEG patterns, identification of which can help understand the plant’s varied response to stress. A variety of computational methods will be used to find cis-acting elements / transcriptional activation motifs involved in HNT stress in rice. This information will be leveraged in machine learning algorithms to develop predictive models for manipulating genes for breeding purposes such as to improve grain quality and yield, enhancing rice plants' resilience to high night temperatures and contributing to the overall adaptability of rice crops to heat stress conditions.

This Research has been presented

Undergraduate Student Symposium 2024

Recommended Citation

Tobias, Emalynn; Handal, Jenna M.; Lup, Paul; Egozi, Michael; Dhillon, Braham; Pereira, Andy; and Gill, Navdeep, "Conserved Domains in Promoters of Differentially Expressed Genes Under High Night Temperature Stress in Rice: How to Find Them and What Can They Tell Us?" (2024). Bioinformatics. 3.
https://nsuworks.nova.edu/bioinformatics/3