Local adaptation in the extremophile Eutrema salsugineum: Exploring the role of putative lncRNAs

Abstract

Eutrema salsugineum is a halophyte that is tolerant to abiotic stresses such as nutritional deficiencies, cold tem- peratures, and drought, and has been used as a model plant for stress tolerance research. Most studies have fo- cused on the Shandong ecotype, a natural accession of E. salsugineum from the temperate region of Shandong, China. However, an E. salsugineum population from Yukon, Canada, has recently emerged as a novel source for insights on the stress response of this species. The Yukon ecotype is naturally found in a subarctic, semiarid environment, and displays different molecular and pheno- typic changes when exposed to stressors compared to the Shandong ecotype. The variation in stress response may indicate local environmental adaptations in each E. salsugineum ecotype. RNASeq libraries of both Shandong and Yukon cabinet grown plants exposed to two sequential drought conditions were obtained, along with RNASeq data of naturally found Yukon plants sam- pled during a year of drought. Using transcriptome infor- mation obtained by RNASeq, assembled transcripts were input into a custom ensemble machine learning algorithm, CREMA, to identify putative long non-coding RNAs (lncRNAs). Using this data, we predict that both Shandong and Yukon ecotypes will express unique lncRNAs that regulate genes required for tolerating local environmental stress. We also predict that Yukon plants found in their natural environment will have elevated expression of these lncRNAs and may express unique “field” Yukon lncRNAs due to constant challenges by multiple stressors. As lncRNAs have been previously as- sociated to abiotic stress in plants, their rapid evolution and gene regulatory functions may also play important roles in how two ecotypes of the same species have potentially adapted to their own natural environments.""

Publication
In Vitro Cellular & Devlopmental Biology-Plant
Caitlin Simopoulos
Caitlin Simopoulos
PhD, Sr. Computational Biologist

I use computational biology and machine learning to understand the world around me!

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