Mining salt stress-related genes in Spartina alterniflora via analyzing co-evolution signal across 365 plant species using phylogenetic profiling

Journal article

Gao, Shang, Chen, Shoukun, Yang, Maogeng, Wu, Jinran, Chen, Shihua and Li, Huihui. (2023). Mining salt stress-related genes in Spartina alterniflora via analyzing co-evolution signal across 365 plant species using phylogenetic profiling. aBIOTECH. 4(4), pp. 1-12. https://doi.org/10.1007/s42994-023-00125-5
AuthorsGao, Shang, Chen, Shoukun, Yang, Maogeng, Wu, Jinran, Chen, Shihua and Li, Huihui
Abstract

With the increasing number of sequenced species, phylogenetic profiling (PP) has become a powerful method to predict functional genes based on co-evolutionary information. However, its potential in plant genomics has not yet been fully explored. In this context, we combined the power of machine learning and PP to identify salt stress-related genes in a halophytic grass, Spartina alterniflora, using evolutionary information generated from 365 plant species. Our results showed that the genes highly co-evolved with known salt stress-related genes are enriched in biological processes of ion transport, detoxification and metabolic pathways. For ion transport, five identified genes coding two sodium and three potassium transporters were validated to be able to uptake Na+. In addition, we identified two orthologs of trichome-related AtR3-MYB genes, SaCPC1 and SaCPC2, which may be involved in salinity responses. Genes co-evolved with SaCPCs were enriched in functions related to the circadian rhythm and abiotic stress responses. Overall, this work demonstrates the feasibility of mining salt stress-related
genes using evolutionary information, highlighting the potential of PP as a valuable tool for plant functional genomics.

KeywordsPhylogenetic profiling; Spartina alterniflora; Salt stress-related gene; Machine learning, ; Evolutionary information
Year01 Jan 2023
JournalaBIOTECH
Journal citation4 (4), pp. 1-12
PublisherSpringer
ISSN2662-1738
Digital Object Identifier (DOI)https://doi.org/10.1007/s42994-023-00125-5
Web address (URL)https://link.springer.com/article/10.1007/s42994-023-00125-5
Open accessOpen access
Research or scholarlyResearch
Page range1-12
Publisher's version
License
File Access Level
Open
Output statusPublished
Publication dates
Online07 Dec 2023
Publication process dates
Accepted23 Oct 2023
Deposited30 May 2024
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© The Author(s) 2023

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Place of publicationSingapore
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