Whole genome sequence data of Comamonas sediminis FS4_11, a fumonisin B1-transforming bacterium, using hybrid nanopore-illumina sequencing

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-06-24 DOI:10.1016/j.dib.2025.111829

Yang Wang , Mengru Zhao , Zhe Wang , Xiaohong Luo , Chengfei Wang , Baoyuan Guo

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引用次数: 0

Abstract

The genome of Comamonas sediminis FS4_11, a bacterial strain with mycotoxin fumonisin B1 (FB1) transformation capability, was sequenced using Oxford Nanopore Technologies (ONT) and Illumina platforms. The final assembly generated a circular chromosome of 5,148,490 bp with a mean G+C content of 63.74%, representing a contiguous genomic structure. Genome annotation predicted 4565 protein-coding sequences (CDSs), 82 transfer RNAs (tRNAs), 18 ribosomal RNAs (rRNAs; 6 each of 5S, 16S, and 23S rRNA), 1 transfer-messenger RNA (tmRNA), and 8 pseudogenes and other non-coding RNAs. Functional annotation identified 939 potential virulence factors, two putative AdeF-related antibiotic resistance genes, 1486 potential pathogen-host interaction proteins, and a candidate carboxylesterase for FB1 transformation. This dataset primarily aids in identifying potential FB1 detoxification enzyme genes and assessing strain biosafety. It also offers significant reuse potential for comparative genomics and understanding bacterial evolution.

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利用杂交纳米孔illumina测序技术获得富马菌素b1转化菌沉积Comamonas sediminis FS4_11全基因组序列数据

利用Oxford Nanopore Technologies （ONT）和Illumina平台对具有真菌毒素伏马菌素B1 （FB1）转化能力的Comamonas sediminis FS4_11进行了基因组测序。最终组装得到一条5148490 bp的圆形染色体，平均G+C含量为63.74%，具有连续的基因组结构。基因组注释预测了4565个蛋白质编码序列（CDSs）、82个转移rna （tRNAs）、18个核糖体rna (RNAs)；5S、16S和23S rRNA各6个)，传递信使RNA (tmRNA) 1个，假基因和其他非编码RNA 8个。功能注释鉴定出939个潜在的毒力因子，两个假定的aef相关抗生素耐药基因，1486个潜在的病原体-宿主相互作用蛋白，以及一个FB1转化的候选羧酸酯酶。该数据集主要有助于鉴定潜在的FB1解毒酶基因和评估菌株的生物安全性。它还为比较基因组学和理解细菌进化提供了重要的重用潜力。

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

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.