Tagging large CNV blocks in wheat boosts digitalization of germplasm resources by ultra-low-coverage sequencing.

IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences
Jianxia Niu, Wenxi Wang, Zihao Wang, Zhe Chen, Xiaoyu Zhang, Zhen Qin, Lingfeng Miao, Zhengzhao Yang, Chaojie Xie, Mingming Xin, Huiru Peng, Yingyin Yao, Jie Liu, Zhongfu Ni, Qixin Sun, Weilong Guo
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引用次数: 0

Abstract

Background: The massive structural variations and frequent introgression highly contribute to the genetic diversity of wheat, while the huge and complex genome of polyploid wheat hinders efficient genotyping of abundant varieties towards accurate identification, management, and exploitation of germplasm resources.

Results: We develop a novel workflow that identifies 1240 high-quality large copy number variation blocks (CNVb) in wheat at the pan-genome level, demonstrating that CNVb can serve as an ideal DNA fingerprinting marker for discriminating massive varieties, with the accuracy validated by PCR assay. We then construct a digitalized genotyping CNVb map across 1599 global wheat accessions. Key CNVb markers are linked with trait-associated introgressions, such as the 1RS·1BL translocation and 2NvS translocation, and the beneficial alleles, such as the end-use quality allele Glu-D1d (Dx5 + Dy10) and the semi-dwarf r-e-z allele. Furthermore, we demonstrate that these tagged CNVb markers promote a stable and cost-effective strategy for evaluating wheat germplasm resources with ultra-low-coverage sequencing data, competing with SNP array for applications such as evaluating new varieties, efficient management of collections in gene banks, and describing wheat germplasm resources in a digitalized manner. We also develop a user-friendly interactive platform, WheatCNVb ( http://wheat.cau.edu.cn/WheatCNVb/ ), for exploring the CNVb profiles over ever-increasing wheat accessions, and also propose a QR-code-like representation of individual digital CNVb fingerprint. This platform also allows uploading new CNVb profiles for comparison with stored varieties.

Conclusions: The CNVb-based approach provides a low-cost and high-throughput genotyping strategy for enabling digitalized wheat germplasm management and modern breeding with precise and practical decision-making.

通过超低覆盖率测序技术标记小麦中的大型 CNV 块,促进种质资源的数字化。
背景:小麦的大量结构变异和频繁的外源引入极大地促进了小麦的遗传多样性,而多倍体小麦庞大而复杂的基因组则阻碍了对丰富品种进行高效基因分型以实现种质资源的准确鉴定、管理和开发利用:我们开发了一种新的工作流程,在泛基因组水平上鉴定出小麦中的 1240 个高质量大拷贝数变异块(CNVb),证明 CNVb 可作为鉴别大量品种的理想 DNA 指纹标记,其准确性已通过 PCR 检测得到验证。然后,我们构建了一个涵盖全球 1599 个小麦品种的数字化 CNVb 基因分型图谱。关键的 CNVb 标记与性状相关的引种(如 1RS-1BL 易位和 2NvS 易位)以及有益等位基因(如最终使用品质等位基因 Glu-D1d (Dx5 + Dy10) 和半矮小 r-e-z 等位基因)相关联。此外,我们还证明了这些标记的 CNVb 标记可促进使用超低覆盖率测序数据评估小麦种质资源的稳定且经济高效的策略,可与 SNP 阵列竞争,应用于新品种评估、基因库藏品的高效管理以及小麦种质资源的数字化描述等。我们还开发了一个用户友好型交互平台--WheatCNVb ( http://wheat.cau.edu.cn/WheatCNVb/ ),用于探索不断增加的小麦种质资源的 CNVb 图谱,并提出了一种类似 QR 码的单个数字 CNVb 指纹表示法。该平台还允许上传新的 CNVb 图谱,以便与储存的品种进行比较:结论:基于 CNVb 的方法提供了一种低成本、高通量的基因分型策略,可实现数字化的小麦种质管理和现代育种,做出精确而实用的决策。
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
Genome Biology
Genome Biology BIOTECHNOLOGY & APPLIED MICROBIOLOGY-GENETICS & HEREDITY
CiteScore
25.50
自引率
3.30%
发文量
0
审稿时长
14 weeks
期刊介绍: Genome Biology is a leading research journal that focuses on the study of biology and biomedicine from a genomic and post-genomic standpoint. The journal consistently publishes outstanding research across various areas within these fields. With an impressive impact factor of 12.3 (2022), Genome Biology has earned its place as the 3rd highest-ranked research journal in the Genetics and Heredity category, according to Thomson Reuters. Additionally, it is ranked 2nd among research journals in the Biotechnology and Applied Microbiology category. It is important to note that Genome Biology is the top-ranking open access journal in this category. In summary, Genome Biology sets a high standard for scientific publications in the field, showcasing cutting-edge research and earning recognition among its peers.
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