一种单倍型解析的关节草染色体水平基因组组装。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Wenjie Yang, Changci Jiang, Changwei Bi, Zhuang Zhao, Chenlong Fu, Fangping Li, Zhuangwei Hou, Quanjun Hu, Zefu Wang
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引用次数: 0

摘要

草叶草(Oxalis articulata)是一种广泛分布的多年生草本植物,以其对多种环境条件的适应性而闻名。在这里,我们报告了第一个单倍型解析的,染色体尺度的O. articulata (Oxalidaceae)基因组组装,通过PacBio HiFi长读取和Hi-C技术生成。该组合包含两个单倍型,大小分别为377.04 Mb (contig N50 = 31.13 Mb)和342.70 Mb (contig N50 = 47.46 Mb)。我们在这两种单倍型中分别预测了36,063个蛋白质编码基因(94.33%的功能注释)和38,292个蛋白质编码基因(93.80%的功能注释)。这一高质量的基因组组装为今后的生态和生化研究奠定了坚实的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A haplotype-resolved chromosomal-level genome assembly of Oxalis articulata.

A haplotype-resolved chromosomal-level genome assembly of Oxalis articulata.

A haplotype-resolved chromosomal-level genome assembly of Oxalis articulata.

A haplotype-resolved chromosomal-level genome assembly of Oxalis articulata.

Oxalis articulata is a widely distributed perennial herb known for its adaptability to diverse environmental conditions. Here, we report the first haplotype-resolved, chromosome-scale genome assembly for O. articulata (Oxalidaceae), generated through PacBio HiFi long reads and Hi-C technology. The resulting assembly comprises two haplotypes with sizes of 377.04 Mb (contig N50 = 31.13 Mb) and 342.70 Mb (contig N50 = 47.46 Mb), respectively. We predicted 36,063 protein-coding genes (94.33% functionally annotated) and 38,292 protein-coding genes (93.80% functionally annotated) in the two haplotypes, respectively. This high-quality genome assembly lays a solid groundwork for future initiatives in ecological and biochemical research for O. articulata.

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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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