Chromosome-level genome assembly of Paracoccus marginatus based on PacBio and Hi-C technologies.

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Jiufeng Wei, Jinying Xue, Xuejie Shen, Gaoxiang Zhang, Qing Zhao, Yunyun Lu, Minmin Niu, Wei Ji
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Abstract

Invasive species pose a serious threat to ecosystems and biodiversity, leading to considerable economic losses for countries. The papaya mealybug (Paracoccus marginatus), is a prominent invasive pest that affects over 200 plant species and has been recorded in more than 60 countries and regions.Here, the chromosome-level genome of P. marginatus was assembled using PacBio and Hi-C technologies. The resulting genome, with a total size of 213.81 Mb, was organized into four chromosomes. The contig and scaffold N50 values were 20.2 Mb and 48.01 Mb, respectively. The genome assembly attained a BUSCO completeness score of 95.5%, and CEGMA analysis showed that 99.56% of the genome was thoroughly annotated. It includes 13,367 predicted protein-coding genes, with 49.26% of the assembly identified as repetitive sequences. This high-quality genome serves as a valuable resource for a range of research fields, such as population genetics, evolutionary studies, invasive species management, and comparative genomics within Hemiptera and other insect groups.

基于PacBio和Hi-C技术的边缘副球菌染色体水平基因组组装。
入侵物种对生态系统和生物多样性构成严重威胁,给各国造成巨大的经济损失。番木瓜粉蚧(Paracoccus marginatus)是一种影响200多种植物的重要入侵害虫,已在60多个国家和地区被记录。本研究利用PacBio和Hi-C技术,对边角扁豆的染色体水平基因组进行了组装。得到的基因组总大小为213.81 Mb,由四条染色体组成。contig和scaffold N50值分别为20.2 Mb和48.01 Mb。基因组组装的BUSCO完整性评分为95.5%,CEGMA分析显示99.56%的基因组被完全注释。它包括13367个预测的蛋白质编码基因,其中49.26%的组装被确定为重复序列。这种高质量的基因组为种群遗传学、进化研究、入侵物种管理、半翅目昆虫和其他昆虫类群的比较基因组学等研究领域提供了宝贵的资源。
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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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