四倍体油茶树单倍型解析基因组组装。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Rui Wang, Weiguo Li, Zhilong He, Haomin Lyu, Xiangnan Wang, Changrong Ye, Chengfeng Xun, Gaohong Xiao, Ying Zhang, Zhen Zhang, Yushen Ma, Longsheng Chen, Bolin Chen, Gaofeng Jia, Bingchuan Tian, Yongzhong Chen
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引用次数: 0

摘要

油茶属油茶属油茶属植物,是重要的木本食用油茶植物,具有很高的生态价值和经济价值。该四倍体物种的单倍型分解基因组组装有助于揭示基因组进化以及亚基因组和单倍型之间的功能分化。在这项研究中,我们使用PacBio HiFi, Hi-C和Illumina测序实现了第一个染色体水平的单倍型解决基因组组装。这些支架的N50分别为44.46 Mb和41.40 Mb,被定位到60条染色体和4个不同的单倍型,每个单倍型都具有独特的转座子特征。单倍型长度在2967.25 ~ 3041.66 Mb之间,包含51336 ~ 52631个蛋白编码基因,其中99.4%被注释。在单倍型中鉴定出非编码rna和重复元件。这一全面的基因组资源将加强对油茶的分子和遗传学研究,有助于油茶的保护和利用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Haplotype-resolved genome assembly of the tetraploid Youcha tree Camellia meiocarpa Hu.

Haplotype-resolved genome assembly of the tetraploid Youcha tree Camellia meiocarpa Hu.

Haplotype-resolved genome assembly of the tetraploid Youcha tree Camellia meiocarpa Hu.

Haplotype-resolved genome assembly of the tetraploid Youcha tree Camellia meiocarpa Hu.

Camellia meiocarpa Hu, a member of Youcha species in the genus Camellia, is an important woody edible Youcha plant with high ecological and economic value. The haplotype-resolved genome assembly of this tetraploid species can shed light on genomic evolution and the functional divergence among subgenomes and haplotypes. In this study, we achieved the first chromosome-level haplotype-resolved genome assembly using PacBio HiFi, Hi-C, and Illumina sequencing. The scaffolds, with an N50 of 44.46 Mb and 41.40 Mb, were mapped to 60 chromosomes and four distinct haplotypes, each with unique transposon features. The haplotypes varied in length (2967.25 Mb to 3041.66 Mb) and contained 51,336 to 52,631 protein-coding genes, 99.4% of which were annotated. Non-coding RNAs and repetitive elements were identified across haplotypes. This comprehensive genomic resource will enhance molecular and genetic studies, aiding in the conservation and utilization of Youcha.

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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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