Coding and long non-coding RNAs provide evidence of distinct transcriptional reprogramming for two ecotypes of the extremophile plant Eutrema salsugineum undergoing water deficit stress.

Background: The severity and frequency of drought has increased around the globe, creating challenges in ensuring food security for a growing world population. As a consequence, improving water use efficiency by crops has become an important objective for crop improvement. Some wild crop relatives have adapted to extreme osmotic stresses and can provide valuable insights into traits and genetic signatures that can guide efforts to improve crop tolerance to water deficits.

Evidence that tolerance of Eutrema salsugineum to low phosphate conditions is hard-wired by constitutive metabolic and root-associated adaptations.

The extremophyte Eutrema salsugineum (Yukon ecotype) has adapted to an environment low in available phosphate through metabolic and root-associated traits that enables it to efficiently retrieve, use, and recycle phosphorus. Efficient phosphate (Pi) use by plants would increase crop productivity under Pi-limiting conditions and reduce our reliance on Pi applied as fertilizer. An ecotype of Eutrema salsugineum originating from the Yukon, Canada, shows no evidence of decreased relative growth rate or biomass under low Pi conditions and, as such, offers a promising model for identifying mechanisms to improve Pi use by crops.

Molecular Traits of Long Non-protein Coding RNAs from Diverse Plant Species Show Little Evidence of Phylogenetic Relationships.

Long non-coding RNAs (lncRNAs) represent a diverse class of regulatory loci with roles in development and stress responses throughout all kingdoms of life. LncRNAs, however, remain under-studied in plants compared to animal systems. To address this deficiency, we applied a machine learning prediction tool, Classifying RNA by Ensemble Machine learning Algorithm (CREMA), to analyze RNAseq data from 11 plant species chosen to represent a wide range of evolutionary histories.

Demographic expansion and genetic load of the halophyte model plant Eutrema salsugineum.

The halophyte model plant Eutrema salsugineum (Brassicaceae) disjunctly occurs in temperate to subarctic Asia and North America. This vast, yet extremely discontinuous distribution constitutes an ideal system to examine long-distance dispersal and the ensuing accumulation of deleterious mutations as expected in expanding populations of selfing plants. In this study, we resequenced individuals from 23 populations across the range of E.

Prediction of plant lncRNA by ensemble machine learning classifiers.

Background: In plants, long non-protein coding RNAs are believed to have essential roles in development and stress responses. However, relative to advances on discerning biological roles for long non-protein coding RNAs in animal systems, this RNA class in plants is largely understudied. With comparatively few validated plant long non-coding RNAs, research on this potentially critical class of RNA is hindered by a lack of appropriate prediction tools and databases.