Chromosome-scale genomes of wild and cultivated Morinda officinalis.

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-03-17 DOI:10.1038/s41597-025-04776-5
Ruirui Li, Xiaodie Geng, Min Liu, Guangming Liu, Tong Wei, Huan Liu, Yanqun Li, Sunil Kumar Sahu, Hong Wu
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Abstract

Morinda officinalis is a renowned medicinal and edible plant native to southern China and northern Vietnam. Its dried roots, known as bajitian are extensively used in traditional Chinese medicine to treat various ailments. Driven by the increasing market demand, the wild populations of M. officinalis have been threatened, leading to the surge of cultivated varieties. Here, we present the chromosome-scale genome assemblies of both wild and cultivated M. officinalis, achieved through a combination of nanopore long-read sequencing and Hi-C technology, resulting in high-quality genomes for the wild (423 Mb) and cultivated (425 Mb) M. officinalis, boasting scaffold N50 values of 5.91 Mb and 10.99 Mb, respectively. Additionally, we predicted 31,308 and 29,528 protein-coding genes in wild and cultivated M. officinalis, respectively. Approximately 96.3% and 97.8% of the assembled sequences were anchored to 11 pseudo-chromosomes for the wild and cultivated genomes. The high-quality chromosome-scale genomes of M. officinalis could serve as a valuable resource for understanding the genetic basis of medicinal trait variations, improving cultivation practices, and conserving this ecologically and economically important species.

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野生和栽培马桑的染色体尺度基因组。
巴戟天是一种著名的药用和食用植物,原产于中国南部和越南北部。它的干根,被称为八鸡天,在中医中广泛用于治疗各种疾病。在市场需求增长的驱动下,马尾松野生种群受到威胁,导致栽培品种激增。通过纳米孔长读测序和Hi-C技术的结合,我们展示了野生和栽培的山茱萸染色体尺度的基因组组装,得到了野生山茱萸(423 Mb)和栽培山茱萸(425 Mb)的高质量基因组,支架N50值分别为5.91 Mb和10.99 Mb。此外,我们在野生和栽培的马蹄草中分别预测了31,308和29,528个蛋白质编码基因。在野生和栽培基因组中,分别有96.3%和97.8%的序列被锚定在11条伪染色体上。高质量的铁皮石斛染色体尺度基因组可为了解药用性状变异的遗传基础、改进栽培方法和保护这一生态和经济上重要的物种提供宝贵的资源。
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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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