第一个大叶紫檀(Rubroshorea macrophylla)基因组调查数据。

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Hung Hui Chung , Asmeralda Ai Leen Soh , Melinda Mei Lin Lau , Han Ming Gan , Siong Fong Sim , Leonard Whye Kit Lim
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引用次数: 0

摘要

大叶红杉成活率高,生长速度快,是造林中不可缺少的树种之一。由于该树种的遗传兴趣相对较低,其基因组景观一直面临稀缺,阻碍了我们对表达其上述优越特性的基因的进一步阐明。在本研究中,我们对恩卡邦简通进行了基因组调查和微卫星分析。结果表明,该物种基因组大小为312,071,515 bp,重复序列占18.43%,杂合率为1.16%。BUSCO分析发现83.5%的contigs是单拷贝基因,而12.7%的contigs是重复基因。碎片化和缺失率分别为2.8%和1%。在这项研究中,从Illumina平台获得的短读测序结果将在不久的将来补充纳米孔长读测序结果,用于杂交基因组组装。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The first engkabang jantong (Rubroshorea macrophylla) genome survey data
The engkabang jantong (Rubroshorea macrophylla) is one of the most indispensable tree species for reforestation due to its high survival rate and rapid growth rate. Due to relatively low genetic interest of this tree species, its genomic landscape has since faced scarcity, impeding our further elucidation on genes that are involved in expressing its aforementioned superior properties. In this study, we performed genome survey and microsatellite analysis of engkabang jantong. Based on the results, the estimated genome size of this species is 312,071,515 bp with 18.43 % repeated sequences and 1.16 % heterozygosity. BUSCO analysis unearthed that 83.5 % of the contigs are single-copy genes whereas 12.7 % of them are duplicated. Only 2.8 % and 1 % of them are fragmented and missing respectively. The short-read sequencing results obtained from the Illumina platform in this study will be essential to complement the Nanopore long-read sequencing results in hybrid genome assembly endeavors in the near future.
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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