Chromosome-level genome assembly of banaba (Lagerstroemia speciosa L.).

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Zhiting Wan, Tangchun Zheng, Ming Cai, Jia Wang, Huitang Pan, Tangren Cheng, Qixiang Zhang
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Abstract

Lagerstroemia speciosa is a famous medicinal and ornamental plant of the Lagerstroemia genus, with large and gorgeous flowers and a flowering period of 3 to 5 months. L. speciosa extracts have been used for many years in folk medicine to treat diabetes. Here, we used PacBio and Hi-C sequencing technologies to obtain a high-quality whole genome map of L. speciosa at chromosome level. The assembled genome is 306.76 Mb, with a scaffold N50 of 13.03 Mb. 98.75% of contigs were anchored to 24 pseudochromosomes, and 38.58% of the contigs (118.11 Mb) were identified as repeats. 93.54% of the 29,351 protein-coding genes were annotated. In addition, 146 miRNAs, 511 tRNAs, 2,733 rRNAs and 679 snRNAs were annotated. This high-quality genome assembly provides a valuable resource for understanding the species evolution in the Lythraceae family and promoting the study of important traits of L. speciosa.

巴纳巴(Lagerstroemia speciosa L.)染色体级基因组组装。
Lagerstroemia speciosa 是一种著名的药用和观赏植物,属于 Lagerstroemia 属,花朵硕大艳丽,花期为 3 至 5 个月。多年来,L. speciosa 提取物一直被用于治疗糖尿病的民间药物中。在此,我们利用 PacBio 和 Hi-C 测序技术,在染色体水平上获得了高质量的 L. speciosa 全基因组图谱。组装的基因组为 306.76 Mb,支架 N50 为 13.03 Mb。98.75%的等位基因锚定在 24 个假染色体上,38.58%的等位基因(118.11 Mb)被鉴定为重复序列。在 29 351 个蛋白质编码基因中,有 93.54% 的基因得到了注释。此外,还注释了 146 个 miRNA、511 个 tRNA、2,733 个 rRNA 和 679 个 snRNA。这一高质量的基因组组装为了解枸杞科植物的物种进化和促进对枸杞重要性状的研究提供了宝贵的资源。
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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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