The telomere-to-telomere chromosome-scale genome assembly of Acremonium chrysogenum.

IF 6.9 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2025-08-07 DOI:10.1038/s41597-025-05645-x

Chao Han, Yiping Zhang, Hengyu Liang, Minliang Chen, Jiahuang Li, Zichun Hua

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Abstract

Acremonium chrysogenum is a notable filamentous fungus recognized for its essential contribution to the pharmaceutical sector through the biosynthesis of cephalosporin C (CPC). CPC functions as a key intermediate in the biosynthesis of β-lactam antibiotics, which are employed to combat bacterial infections. This study successfully generated a telomere-to-telomere (T2T) chromosome-scale genome sequence for A. chrysogenum, combining BGI short reads, PacBio HiFi long reads, and Hi-C technology. This genome sequence contained eight complete chromosomes (29.00 Mb) and a circular mitochondrial genome (27.27 kb), featuring an N50 length of 3.87 Mb. Repetitive elements accounted for 9.65% of genomic content, and a total of 7,745 genes involved in protein coding were annotated. This well-assembled reference genome of A. chrysogenum serves as an important foundation for elucidating the biosynthetic pathway of cephalosporin C and for molecular breeding. Furthermore, it offers valuable insights into chromosome organization, genome evolution, and regulatory mechanisms, facilitating future advancements in antibiotic research and fungal biotechnology.

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黄顶孢的端粒到端粒染色体的基因组组装。

Acremonium chrysogenum是一种著名的丝状真菌，因其通过生物合成头孢菌素C （CPC）对制药部门的重要贡献而得到认可。CPC作为β-内酰胺类抗生素生物合成的关键中间体，用于对抗细菌感染。本研究结合BGI短序列、PacBio HiFi长序列和Hi-C技术，成功生成了a . chrysogenum的端粒到端粒（T2T）染色体尺度的基因组序列。该基因组序列包含8条完整的染色体（29.00 Mb）和一个圆形线粒体基因组（27.27 kb）， N50长度为3.87 Mb。重复元件占基因组内容的9.65%，共注释了7745个参与蛋白质编码的基因。这一完整的参考基因组为阐明头孢菌素C的生物合成途径和分子育种奠定了重要基础。此外，它为染色体组织、基因组进化和调控机制提供了有价值的见解，促进了抗生素研究和真菌生物技术的未来发展。

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来源期刊

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.