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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9182744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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