山茶科山茶基因组调查及SSR分析。

IF 1.4 4区生物学 Q4 GENETICS & HEREDITY

Genetics research Pub Date : 2022-01-01 DOI:10.1155/2022/5417970

Yu Bai, Lin Ye, Kang Yang, Hui Wang

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引用次数: 1

摘要

山茶花(Camellia nitidissima Chi, CNC)是一种金色的山茶花，被誉为“山茶花女王”。它是一种生长在中国的观赏、药用和食用植物。在本研究中，我们利用Illumina测序平台对CNC进行了基因组调查、测序分析和SSR鉴定。21-mer分析预测其基因组大小为2778.82 Mb，杂合度和重复率分别为1.42%和65.27%。CNC基因组序列被组装成9,399,197个支架，覆盖约2,910 Mb, N50为869个碱基对。发现其基因组特征与油茶相似。此外，从基因组数据中鉴定出1,940,616个SSRs，包括单核苷酸(61.85%)、二核苷酸(28.71%)、三核苷酸(6.51%)、四核苷酸(1.85%)、五核苷酸(0.57%)和六核苷酸(0.51%)。我们相信这些数据将为开发新的CNC分子标记以及进一步的CNC全基因组测序提供有用的基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Genome Survey and SSR Analysis of Camellia nitidissima Chi (Theaceae).

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Genome Survey and SSR Analysis of Camellia nitidissima Chi (Theaceae).

Camellia nitidissima Chi (CNC), a species of golden Camellia, is well known as "the queen of camellias." It is an ornamental, medicinal, and edible plant grown in China. In this study, we conducted a genome survey sequencing analysis and simple sequence repeat (SSR) identification of CNC using the Illumina sequencing platform. The 21-mer analysis predicted its genome size to be 2,778.82 Mb, with heterozygosity and repetition rates of 1.42% and 65.27%, respectively. The CNC genome sequences were assembled into 9,399,197 scaffolds, covering ∼2,910 Mb and an N50 of 869 base pair. Its genomic characteristics were found to be similar to those of Camellia oleifera. In addition, 1,940,616 SSRs were identified from the genome data, including mono-(61.85%), di-(28.71%), tri-(6.51%), tetra-(1.85%), penta-(0.57%), and hexanucleotide motifs (0.51%). We believe these data will provide a useful foundation for the development of novel molecular markers for CNC as well as for further whole-genome sequencing of CNC.

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来源期刊

Genetics research 生物-遗传学

自引率

6.70%

发文量

审稿时长

>12 weeks

期刊介绍： Genetics Research is a key forum for original research on all aspects of human and animal genetics, reporting key findings on genomes, genes, mutations and molecular interactions, extending out to developmental, evolutionary, and population genetics as well as ethical, legal and social aspects. Our aim is to lead to a better understanding of genetic processes in health and disease. The journal focuses on the use of new technologies, such as next generation sequencing together with bioinformatics analysis, to produce increasingly detailed views of how genes function in tissues and how these genes perform, individually or collectively, in normal development and disease aetiology. The journal publishes original work, review articles, short papers, computational studies, and novel methods and techniques in research covering humans and well-established genetic organisms. Key subject areas include medical genetics, genomics, human evolutionary and population genetics, bioinformatics, genetics of complex traits, molecular and developmental genetics, Evo-Devo, quantitative and statistical genetics, behavioural genetics and environmental genetics. The breadth and quality of research make the journal an invaluable resource for medical geneticists, molecular biologists, bioinformaticians and researchers involved in genetic basis of diseases, evolutionary and developmental studies.