观赏植物紫花苜蓿染色体水平基因组组装。

IF 6.9 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2025-07-04 DOI:10.1038/s41597-025-05473-z

Xi Chen, Xiu Li, Shengwen Tang, Jiao Ma, Zhangshun Zhu, Fangwen Li, Xiaoqing Shi

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引用次数: 0

摘要

玫瑰Alcea rosea是锦葵科的一员，以其丰富的花色和全球园艺意义而闻名。在这里，我们提出了一个高质量的玫瑰花参考基因组，实现了基因组组装大小为1.01 Gbp， Contig N50长度为36.61 Mbp。基因组序列成功定位到21条染色体，支架N50长度达到52.57 Mbp，支架基因组完整性为99.6%。共鉴定出565.84 Mbp（占整个基因组的56%）的重复序列，以转座元件为主，特别是长末端重复（LTR）元件，占整个基因组的48.44%。51436个基因被注释。预测基因的平均基因长度为2739.92 bp，平均编码序列长度为1242.54 bp。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Chromosome-level genome assembly of the ornamental plant Alcea rosea.

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Chromosome-level genome assembly of the ornamental plant Alcea rosea.

Alcea rosea, a member of the Malvaceae family, is celebrated for its rich floral palette and global horticultural significance. Here, we present a high-quality reference genome for A. rosea, achieving a genome assembly size of 1.01 Gbp, with a Contig N50 length of 36.61 Mbp. The genome sequence was successfully mapped to 21 chromosomes, and the scaffold N50 length reached 52.57 Mbp, with a scaffold genome completeness of 99.6%. A total of 565.84 Mbp (comprising 56% of the genome) of repetitive sequences were identified, with transposable elements being predominant, particularly long terminal repeat (LTR) elements, which accounted for 48.44% of the genome. 51,436 genes were annotated. Among these predicted genes, the average gene length and coding sequence (CDS) length were 2739.92 bp and 1242.54 bp, respectively.

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来源期刊

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.