Revolution and advances in gene editing and genomics technology for developing climate-resilient legume crops: developments and prospects.

IF 3.8 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Gayatri Mishra
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引用次数: 0

Abstract

Legumes are essential for agriculture and food security. Biotic and abiotic stresses pose significant challenges to legume production, lowering productivity levels. Most legumes must be genetically improved by introducing alleles that give pest and disease resistance, abiotic stress adaptability, and high yield potential. The quickest way to develop high-yielding elite legume varieties with long-lasting resistance is to tap into potential resistance alleles present in landraces and wild relatives and exploit them in legume resistance breeding programs using next-generation molecular breeding methods. Most of the reviews focus on the advancements made by genome editing technologies in generating climate-tolerant legumes for breeding. This review discusses the challenges of genome-based editing tools and how the integration of other popular breeding methodologies, such as QTLs and GWAS, as well as computational techniques, can aid in the development of climate-tolerant legume crops. This review highlights genomics-based methodologies and recent advances that make it easier to assess genetic diversity and uncover adaptive genes in legumes. Computational approaches, such as machine learning, are important in mining the breeding-related genes identified by CRISPR and other genomic tools, as well as detecting the key elements and factors that regulate the expression of these genes, which addresses the challenge of developing climate-resilient legume crops.

用于培育气候适应型豆科作物的基因编辑和基因组技术的革命与进展:发展与展望。
豆类对农业和粮食安全至关重要。生物和非生物胁迫对豆类生产构成重大挑战,降低了生产力水平。大多数豆科植物必须通过引入具有抗病虫害、非生物胁迫适应性和高产潜力的等位基因来进行遗传改良。培育具有持久抗性的高产优质豆科植物品种的最快方法是利用存在于地方品种和野生近缘品种中的潜在抗性等位基因,并利用下一代分子育种方法在豆科植物抗性育种计划中加以利用。大多数评论集中在基因组编辑技术在培育耐候性豆类育种方面取得的进展。这篇综述讨论了基于基因组的编辑工具的挑战,以及如何整合其他流行的育种方法,如qtl和GWAS,以及计算技术,可以帮助开发耐气候的豆科作物。这篇综述强调了基于基因组学的方法和最近的进展,使评估遗传多样性和发现豆类的适应性基因变得更容易。计算方法,如机器学习,在挖掘由CRISPR和其他基因组工具鉴定的育种相关基因,以及检测调节这些基因表达的关键元素和因素方面非常重要,这解决了开发气候适应型豆科作物的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Plant Molecular Biology
Plant Molecular Biology 生物-生化与分子生物学
自引率
2.00%
发文量
95
审稿时长
1.4 months
期刊介绍: Plant Molecular Biology is an international journal dedicated to rapid publication of original research articles in all areas of plant biology.The Editorial Board welcomes full-length manuscripts that address important biological problems of broad interest, including research in comparative genomics, functional genomics, proteomics, bioinformatics, computational biology, biochemical and regulatory networks, and biotechnology. Because space in the journal is limited, however, preference is given to publication of results that provide significant new insights into biological problems and that advance the understanding of structure, function, mechanisms, or regulation. Authors must ensure that results are of high quality and that manuscripts are written for a broad plant science audience.
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