Chromosome-level genome assembly of American sweetgum (Liquidambar styraciflua, Altingiaceae).

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Yazhen Ma, Shixiong Ding, Yingxiong Qiu
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引用次数: 0

Abstract

The deciduous American sweetgum (Liquidambar styraciflua, Altingiaceae) is a popular ornamental and economically valuable tree renowned for its sweet-smelling bark resin, abundant volatile substances, and spectacular fall leaf color. However, the absence of a reference genome hinders thorough investigations into the mechanisms underlying phenotypic variation, secondary metabolite synthesis and adaptation, both in this species and other Liquidambar members. In this study, we sequenced and constructed a chromosome-level assembly of the L. styraciflua genome, covering 662.48 Mb with a scaffold N50 of 39.54 Mb, by integrating PacBio, Illumina and chromosome conformation capture data. We identified 58.83% of the genome sequences as repetitive elements and 25,713 protein-coding genes, 97.28% of which were functionally annotated. The genome sequencing reads, assembly and annotation data have been deposited in publicly available repositories. This high-quality genome assembly provides valuable resources for further evolutionary and functional genomic studies in American sweetgum and other Liquidambar species.

美国小叶桉(Liquidambar styraciflua, Altingiaceae)染色体组水平的基因组组装。
落叶美洲鹅掌楸(Liquidambar styraciflua,Altingiaceae)是一种广受欢迎的观赏树种,也是一种具有经济价值的树种,因其树皮树脂气味甜美、挥发性物质丰富以及秋季叶色壮观而闻名。然而,参考基因组的缺失阻碍了对该树种和其他枫香树成员的表型变异、次生代谢物合成和适应机制的深入研究。在本研究中,我们通过整合 PacBio、Illumina 和染色体构象捕获数据,测序并构建了一个染色体组水平的 L. styraciflua 基因组,覆盖 662.48 Mb,支架 N50 为 39.54 Mb。我们确定了 58.83% 的基因组序列为重复元件,25,713 个蛋白编码基因,其中 97.28% 的基因有功能注释。基因组测序读数、组装和注释数据已存入公开资料库。这一高质量的基因组组装为进一步研究美国甘李和其他枫香树物种的进化和功能基因组提供了宝贵的资源。
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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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