肺炎克雷伯菌亚群基因组序列数据草图。肺炎菌B36336,一种从人类血液感染中分离出来的多重耐药菌株

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Nur Husna Shahimi , Zakuan Zaini Deris , Zeti Norfidiyati Salmuna , Shuhaila Mat-Sharani , Nik Yusnoraini Yusof
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引用次数: 0

摘要

从人血中分离出肺炎克雷伯菌B36336株,采用PacBioscience和Illumina测序技术相结合的杂交组装方法获得其基因组草图序列。使用TRIM GALORE、SPAdes、PILON、QUAST等软件分别对引物序列进行去除、组装、抛光和评估组装基因组的质量。共获得6个contigs,共5,750,896个reads, N50为5,423,907,GC含量为57.13%。根据COG注释,主要功能类别为碳水化合物运输和代谢(G: 561),氨基酸运输和代谢(E: 461)和转录(K: 414)。目前的数据可用于鉴定可能特异性存在于耐多药肺炎克雷伯菌(MDR-Kp)物种中的抗菌素耐药基因和毒力因子。原始基因组数据存储在NCBI SRA数据库中,PacBioscience数据存储在SRR32374857, Illumina数据存储在SRR32374856, BioProject登录号为PRJNA1215784。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Draft genome sequence data of Klebsiella pneumoniae subsp. pneumoniae B36336, a multidrug-resistant strain isolated from a human bloodstream infection
Klebsiella pneumoniae B36336 strain was isolated from human blood and its draft genome sequence was obtained using a hybrid assembly approach that combined PacBioscience and Illumina sequencing technologies. Software such as TRIM GALORE, SPAdes, PILON and QUAST, were used to remove primer sequences, assemble, polish and evaluate the quality of the assembled genome respectively. The assembly resulted in 6 contigs with a total 5,750,896 reads, an N50 of 5,423,907, and a GC content of 57.13 %. According to COG annotation, the predominant functional categories were Carbohydrate Transport and Metabolism (Category G: 561), Amino Acid Transport and Metabolism (Category E: 461) and Transcription (Category K: 414). The present data can be used in identification of antimicrobial resistance genes and virulence factors that may be specifically present in multidrug-resistant Klebsiella pneumoniae (MDR-Kp) species. The raw genomic data was deposited in NCBI SRA database SRR32374857 for PacBioscience data and SRR32374856 for Illumina data under BioProject accession number PRJNA1215784.
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来源期刊
Data in Brief
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.
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