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A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms

Soil salinity is one of the most serious environmental challenges, posing a growing threat to agriculture across the world. Soil salinity has a significant impact on rice growth, development, and production. Hence, improving rice varieties’ resistance to salt stress is a viable solution for meeting...

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Autores principales: Ullah, Mohammad Asad, Abdullah-Zawawi, Muhammad-Redha, Zainal-Abidin, Rabiatul-Adawiah, Sukiran, Noor Liyana, Uddin, Md Imtiaz, Zainal, Zamri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182744/
https://www.ncbi.nlm.nih.gov/pubmed/35684203
http://dx.doi.org/10.3390/plants11111430
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author Ullah, Mohammad Asad
Abdullah-Zawawi, Muhammad-Redha
Zainal-Abidin, Rabiatul-Adawiah
Sukiran, Noor Liyana
Uddin, Md Imtiaz
Zainal, Zamri
author_facet Ullah, Mohammad Asad
Abdullah-Zawawi, Muhammad-Redha
Zainal-Abidin, Rabiatul-Adawiah
Sukiran, Noor Liyana
Uddin, Md Imtiaz
Zainal, Zamri
author_sort Ullah, Mohammad Asad
collection PubMed
description Soil salinity is one of the most serious environmental challenges, posing a growing threat to agriculture across the world. Soil salinity has a significant impact on rice growth, development, and production. Hence, improving rice varieties’ resistance to salt stress is a viable solution for meeting global food demand. Adaptation to salt stress is a multifaceted process that involves interacting physiological traits, biochemical or metabolic pathways, and molecular mechanisms. The integration of multi-omics approaches contributes to a better understanding of molecular mechanisms as well as the improvement of salt-resistant and tolerant rice varieties. Firstly, we present a thorough review of current knowledge about salt stress effects on rice and mechanisms behind rice salt tolerance and salt stress signalling. This review focuses on the use of multi-omics approaches to improve next-generation rice breeding for salinity resistance and tolerance, including genomics, transcriptomics, proteomics, metabolomics and phenomics. Integrating multi-omics data effectively is critical to gaining a more comprehensive and in-depth understanding of the molecular pathways, enzyme activity and interacting networks of genes controlling salinity tolerance in rice. The key data mining strategies within the artificial intelligence to analyse big and complex data sets that will allow more accurate prediction of outcomes and modernise traditional breeding programmes and also expedite precision rice breeding such as genetic engineering and genome editing.
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spelling pubmed-91827442022-06-10 A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms Ullah, Mohammad Asad Abdullah-Zawawi, Muhammad-Redha Zainal-Abidin, Rabiatul-Adawiah Sukiran, Noor Liyana Uddin, Md Imtiaz Zainal, Zamri Plants (Basel) Review Soil salinity is one of the most serious environmental challenges, posing a growing threat to agriculture across the world. Soil salinity has a significant impact on rice growth, development, and production. Hence, improving rice varieties’ resistance to salt stress is a viable solution for meeting global food demand. Adaptation to salt stress is a multifaceted process that involves interacting physiological traits, biochemical or metabolic pathways, and molecular mechanisms. The integration of multi-omics approaches contributes to a better understanding of molecular mechanisms as well as the improvement of salt-resistant and tolerant rice varieties. Firstly, we present a thorough review of current knowledge about salt stress effects on rice and mechanisms behind rice salt tolerance and salt stress signalling. This review focuses on the use of multi-omics approaches to improve next-generation rice breeding for salinity resistance and tolerance, including genomics, transcriptomics, proteomics, metabolomics and phenomics. Integrating multi-omics data effectively is critical to gaining a more comprehensive and in-depth understanding of the molecular pathways, enzyme activity and interacting networks of genes controlling salinity tolerance in rice. The key data mining strategies within the artificial intelligence to analyse big and complex data sets that will allow more accurate prediction of outcomes and modernise traditional breeding programmes and also expedite precision rice breeding such as genetic engineering and genome editing. MDPI 2022-05-27 /pmc/articles/PMC9182744/ /pubmed/35684203 http://dx.doi.org/10.3390/plants11111430 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Ullah, Mohammad Asad
Abdullah-Zawawi, Muhammad-Redha
Zainal-Abidin, Rabiatul-Adawiah
Sukiran, Noor Liyana
Uddin, Md Imtiaz
Zainal, Zamri
A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms
title A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms
title_full A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms
title_fullStr A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms
title_full_unstemmed A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms
title_short A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms
title_sort review of integrative omic approaches for understanding rice salt response mechanisms
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182744/
https://www.ncbi.nlm.nih.gov/pubmed/35684203
http://dx.doi.org/10.3390/plants11111430
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