中国高粱654的端粒-端粒基因组组装。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Fulin Wang, Jiandong Bao, Heng Zhang, Guowei Zhai, Tao Song, Zhijian Liu, Yu Han, Fan Yu, Guihua Zou, Ying Zhu
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引用次数: 0

摘要

高粱654自交系是中国许多商业杂交系和重组自交系的亲本,在许多重要农艺性状的克隆中发挥了关键作用。在这项研究中,我们利用PacBio HiFi、超长牛津纳米孔技术和Hi-C测序数据,展示了近交系654 (728.81 Mb)的端粒到端粒(T2T)基因组组装。T2T基因组组装体具有高完整性(包含所有10个着丝粒和20个端粒,无间隙)、高连续性(连续N90: 52.02 Mb)、高完备性(BUSCO完备性98.33%,k-mer完备性98.88%,LAI 24.38)和极低碱基误差(3.37 × 10-7, QV: 64.72)。62.34%的序列被鉴定为重复序列,其余区域包含44,399个蛋白质编码基因,其中30,245个被功能注释。无间隙T2T基因组组装使潜在的翻译基因组学得以全面展现,为今后高粱育种中基因组进化、结构变异和农艺性状遗传控制的研究提供了最高分辨率的遗传图谱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A telomere-to-telomere genome assembly of Chinese grain sorghum 654.

The grain sorghum inbred line 654 serves as a parent for numerous Chinese commercial hybrids and recombinant inbred lines (RILs), which have played a pivotal role in the cloning of several agronomically important traits. In this study, we present a telomere-to-telomere (T2T) genome assembly of the inbred line 654 (728.81 Mb) using PacBio HiFi, ultra-long Oxford Nanopore Technology, and Hi-C sequencing data. The T2T genome assembly has high integrity (contains all of 10 centromeres and 20 telomeres without any gaps), high contiguity (contig N90: 52.02 Mb), high completeness (98.33% BUSCO completeness, 98.88% k-mer completeness, and LAI 24.38), and extremely low base error (3.37 × 10-7, QV: 64.72). A total of 62.34% sequences were identified as repetitive, and rest region contained 44,399 protein-coding genes, of which 30,245 were functionally annotated. The gap-free T2T genome assembly enables the full picture of the potential translational genomics, and provides the highest resolution genetic map for future studies on genome evolution, structure variation, and the genetic control of agronomic traits in sorghum breeding.

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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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