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利用多组学策略和生物信息学创新推动大豆改良:综述

Harnessing Multi-Omics Strategies and Bioinformatics Innovations for Advancing Soybean Improvement: A Comprehensive Review.

作者信息

Haidar Siwar, Hooker Julia, Lackey Simon, Elian Mohamad, Puchacz Nathalie, Szczyglowski Krzysztof, Marsolais Frédéric, Golshani Ashkan, Cober Elroy R, Samanfar Bahram

机构信息

Agriculture and Agri-Food Canada, Ottawa Research and Development Centre, Ottawa, ON K1A 0C6, Canada.

Department of Biology, Ottawa Institute of Systems Biology, Carleton University, Ottawa, ON K1S 5B6, Canada.

出版信息

Plants (Basel). 2024 Sep 28;13(19):2714. doi: 10.3390/plants13192714.

Abstract

Soybean improvement has entered a new era with the advent of multi-omics strategies and bioinformatics innovations, enabling more precise and efficient breeding practices. This comprehensive review examines the application of multi-omics approaches in soybean-encompassing genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics. We first explore pre-breeding and genomic selection as tools that have laid the groundwork for advanced trait improvement. Subsequently, we dig into the specific contributions of each -omics field, highlighting how bioinformatics tools and resources have facilitated the generation and integration of multifaceted data. The review emphasizes the power of integrating multi-omics datasets to elucidate complex traits and drive the development of superior soybean cultivars. Emerging trends, including novel computational techniques and high-throughput technologies, are discussed in the context of their potential to revolutionize soybean breeding. Finally, we address the challenges associated with multi-omics integration and propose future directions to overcome these hurdles, aiming to accelerate the pace of soybean improvement. This review serves as a crucial resource for researchers and breeders seeking to leverage multi-omics strategies for enhanced soybean productivity and resilience.

摘要

随着多组学策略和生物信息学创新的出现,大豆改良进入了一个新时代,使育种实践更加精确和高效。这篇综述全面考察了多组学方法在大豆中的应用,涵盖基因组学、转录组学、蛋白质组学、代谢组学、表观基因组学和表型组学。我们首先探讨了预育种和基因组选择作为为先进性状改良奠定基础的工具。随后,我们深入研究了每个组学领域的具体贡献,强调了生物信息学工具和资源如何促进多方面数据的生成和整合。该综述强调了整合多组学数据集以阐明复杂性状和推动优良大豆品种开发的作用。在其有可能彻底改变大豆育种的背景下,讨论了包括新型计算技术和高通量技术在内的新兴趋势。最后,我们阐述了与多组学整合相关的挑战,并提出了克服这些障碍的未来方向,旨在加快大豆改良的步伐。这篇综述为寻求利用多组学策略提高大豆生产力和抗逆性的研究人员和育种者提供了重要资源。

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