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Omics and CRISPR-Cas9 Approaches for Molecular Insight, Functional Gene Analysis, and Stress Tolerance Development in Crops

Plants are regularly exposed to biotic and abiotic stresses that adversely affect agricultural production. Omics has gained momentum in the last two decades, fueled by statistical methodologies, computational capabilities, mass spectrometry, nucleic-acid sequencing, and peptide-sequencing platforms....

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Autores principales: Razzaq, Muhammad Khuram, Aleem, Muqadas, Mansoor, Shahid, Khan, Mueen Alam, Rauf, Saeed, Iqbal, Shahid, Siddique, Kadambot H. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7866018/
https://www.ncbi.nlm.nih.gov/pubmed/33525517
http://dx.doi.org/10.3390/ijms22031292
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author Razzaq, Muhammad Khuram
Aleem, Muqadas
Mansoor, Shahid
Khan, Mueen Alam
Rauf, Saeed
Iqbal, Shahid
Siddique, Kadambot H. M.
author_facet Razzaq, Muhammad Khuram
Aleem, Muqadas
Mansoor, Shahid
Khan, Mueen Alam
Rauf, Saeed
Iqbal, Shahid
Siddique, Kadambot H. M.
author_sort Razzaq, Muhammad Khuram
collection PubMed
description Plants are regularly exposed to biotic and abiotic stresses that adversely affect agricultural production. Omics has gained momentum in the last two decades, fueled by statistical methodologies, computational capabilities, mass spectrometry, nucleic-acid sequencing, and peptide-sequencing platforms. Functional genomics—especially metabolomics, transcriptomics, and proteomics—have contributed substantially to plant molecular responses to stress. Recent progress in reverse and forward genetics approaches have mediated high-throughput techniques for identifying stress-related genes. Furthermore, web-based genetic databases have mediated bioinformatics techniques for detecting families of stress-tolerant genes. Gene ontology (GO) databases provide information on the gene product’s functional features and help with the computational estimation of gene function. Functional omics data from multiple platforms are useful for positional cloning. Stress-tolerant plants have been engineered using stress response genes, regulatory networks, and pathways. The genome-editing tool, CRISPR-Cas9, reveals the functional features of several parts of the plant genome. Current developments in CRISPR, such as de novo meristem induction genome-engineering in dicots and temperature-tolerant LbCas12a/CRISPR, enable greater DNA insertion precision. This review discusses functional omics for molecular insight and CRISPR-Cas9-based validation of gene function in crop plants. Omics and CRISPR-Cas9 are expected to garner knowledge on molecular systems and gene function and stress-tolerant crop production.
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spelling pubmed-78660182021-02-07 Omics and CRISPR-Cas9 Approaches for Molecular Insight, Functional Gene Analysis, and Stress Tolerance Development in Crops Razzaq, Muhammad Khuram Aleem, Muqadas Mansoor, Shahid Khan, Mueen Alam Rauf, Saeed Iqbal, Shahid Siddique, Kadambot H. M. Int J Mol Sci Review Plants are regularly exposed to biotic and abiotic stresses that adversely affect agricultural production. Omics has gained momentum in the last two decades, fueled by statistical methodologies, computational capabilities, mass spectrometry, nucleic-acid sequencing, and peptide-sequencing platforms. Functional genomics—especially metabolomics, transcriptomics, and proteomics—have contributed substantially to plant molecular responses to stress. Recent progress in reverse and forward genetics approaches have mediated high-throughput techniques for identifying stress-related genes. Furthermore, web-based genetic databases have mediated bioinformatics techniques for detecting families of stress-tolerant genes. Gene ontology (GO) databases provide information on the gene product’s functional features and help with the computational estimation of gene function. Functional omics data from multiple platforms are useful for positional cloning. Stress-tolerant plants have been engineered using stress response genes, regulatory networks, and pathways. The genome-editing tool, CRISPR-Cas9, reveals the functional features of several parts of the plant genome. Current developments in CRISPR, such as de novo meristem induction genome-engineering in dicots and temperature-tolerant LbCas12a/CRISPR, enable greater DNA insertion precision. This review discusses functional omics for molecular insight and CRISPR-Cas9-based validation of gene function in crop plants. Omics and CRISPR-Cas9 are expected to garner knowledge on molecular systems and gene function and stress-tolerant crop production. MDPI 2021-01-28 /pmc/articles/PMC7866018/ /pubmed/33525517 http://dx.doi.org/10.3390/ijms22031292 Text en © 2021 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Razzaq, Muhammad Khuram
Aleem, Muqadas
Mansoor, Shahid
Khan, Mueen Alam
Rauf, Saeed
Iqbal, Shahid
Siddique, Kadambot H. M.
Omics and CRISPR-Cas9 Approaches for Molecular Insight, Functional Gene Analysis, and Stress Tolerance Development in Crops
title Omics and CRISPR-Cas9 Approaches for Molecular Insight, Functional Gene Analysis, and Stress Tolerance Development in Crops
title_full Omics and CRISPR-Cas9 Approaches for Molecular Insight, Functional Gene Analysis, and Stress Tolerance Development in Crops
title_fullStr Omics and CRISPR-Cas9 Approaches for Molecular Insight, Functional Gene Analysis, and Stress Tolerance Development in Crops
title_full_unstemmed Omics and CRISPR-Cas9 Approaches for Molecular Insight, Functional Gene Analysis, and Stress Tolerance Development in Crops
title_short Omics and CRISPR-Cas9 Approaches for Molecular Insight, Functional Gene Analysis, and Stress Tolerance Development in Crops
title_sort omics and crispr-cas9 approaches for molecular insight, functional gene analysis, and stress tolerance development in crops
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7866018/
https://www.ncbi.nlm.nih.gov/pubmed/33525517
http://dx.doi.org/10.3390/ijms22031292
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