对感染仙草的 Pyricularia penniseti 进行了近乎完整的组装,确定了其八条核心染色体。

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2024-10-31 DOI:10.1038/s41597-024-04035-z
Yuyong Li, Xianjun Wang, Jianqiang Huang, Zhenyu Fang, Xiwen Lian, Guodong Lu, Guifang Lin, Zonghua Wang, Baohua Wang, Xiuxiu Li, Huakun Zheng
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引用次数: 0

摘要

Pyricularia 属真菌会导致许多具有重要经济价值的作物和禾本科植物(如小麦、水稻和岑氏禾本科植物 JUJUNCAO)发生稻瘟病。与效应器的增减有关的结构变异在很大程度上促成了这种真菌对不同寄主植物的适应性进化。端粒到端粒的基因组组装将有助于通过比较基因组学鉴定全基因组的结构变异。在这里,我们报告了从端粒到端粒的、近乎完整的、感染 JUJUNCAO 的 Pyricularia penniseti 分离物 JC-1 的基因组组装。该基因组包括八条核心染色体和两条编外染色体(命名为 mini1 和 mini2),跨度为 42.1 Mb。我们注释了 12,156 个蛋白编码基因,并确定了基因组中 4.54% 的重复序列。与核心染色体相比,两条编外染色体包含的基因更少,重复序列更多。我们的基因组和研究结果为今后研究Pyricularia真菌的基因组进化、结构变异和宿主适应性提供了宝贵的资源。
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Near complete assembly of Pyricularia penniseti infecting Cenchrus grass identified its eight core chromosomes.

Fungi from the Pyricularia genus cause blast disease in many economically important crops and grasses, such as wheat, rice, and Cenchrus grass JUJUNCAO. Structure variation associated with the gain and loss of effectors contributes largely to the adaptive evolution of this fungus towards diverse host plants. A telomere-to-telomere genome assembly would facilitate the identification of genome-wide structural variations through comparative genomics. Here, we report a telomere-to-telomere, near-complete genome assembly of a Pyricularia penniseti isolate JC-1 infecting JUJUNCAO. The assembly consists of eight core chromosomes and two supernumerary chromosomes, named mini1 and mini2, spanning 42.1 Mb. We annotated 12,156 protein-coding genes and identified 4.54% of the genome as repetitive sequences. The two supernumerary chromosomes contained fewer genes and more repetitive sequences than the core chromosomes. Our genome and results provide valuable resources for the future study in genome evolution, structure variation and host adaptation of the Pyricularia fungus.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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