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指纹查找器:鉴定棉花群体中的基因组指纹位点,用于遗传分析和育种进展。

Fingerprint Finder: Identifying Genomic Fingerprint Sites in Cotton Cohorts for Genetic Analysis and Breeding Advancement.

机构信息

National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.

National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.

出版信息

Genes (Basel). 2024 Mar 19;15(3):378. doi: 10.3390/genes15030378.

Abstract

Genomic data in Gossypium provide numerous data resources for the cotton genomics community. However, to fill the gap between genomic analysis and breeding field work, detecting the featured genomic items of a subset cohort is essential for geneticists. We developed FPFinder v1.0 software to identify a subset of the cohort's fingerprint genomic sites. The FPFinder was developed based on the term frequency-inverse document frequency algorithm. With the short-read sequencing of an elite cotton pedigree, we identified 453 pedigree fingerprint genomic sites and found that these pedigree-featured sites had a role in cotton development. In addition, we applied FPFinder to evaluate the geographical bias of fiber-length-related genomic sites from a modern cotton cohort consisting of 410 accessions. Enriching elite sites in cultivars from the Yangtze River region resulted in the longer fiber length of Yangze River-sourced accessions. Apart from characterizing functional sites, we also identified 12,536 region-specific genomic sites. Combining the transcriptome data of multiple tissues and samples under various abiotic stresses, we found that several region-specific sites contributed to environmental adaptation. In this research, FPFinder revealed the role of the cotton pedigree fingerprint and region-specific sites in cotton development and environmental adaptation, respectively. The FPFinder can be applied broadly in other crops and contribute to genetic breeding in the future.

摘要

棉花基因组中的基因组数据为棉花基因组学领域提供了大量的数据资源。然而,为了弥合基因组分析与田间工作之间的差距,检测亚群的特征基因组项目对于遗传学家来说至关重要。我们开发了 FPFinder v1.0 软件,用于识别亚群的指纹基因组位点。FPFinder 是基于术语频率-逆文档频率算法开发的。通过对一个优秀棉花品系的短读测序,我们鉴定出 453 个品系指纹基因组位点,并发现这些与品系相关的位点在棉花发育中起作用。此外,我们还应用 FPFinder 评估了由 410 个品系组成的现代棉花群体中与纤维长度相关的基因组位点的地理偏倚。在品种中富集优良位点导致了长江源品种的纤维长度变长。除了表征功能位点外,我们还鉴定了 12536 个特定区域的基因组位点。结合多个组织和不同非生物胁迫下样本的转录组数据,我们发现一些特定区域的位点有助于环境适应。在这项研究中,FPFinder 分别揭示了棉花品系指纹和特定区域位点在棉花发育和环境适应中的作用。FPFinder 可以广泛应用于其他作物,并为未来的遗传育种做出贡献。

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