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SNPViz 分析 72 个测序大豆基因组揭示的主要大豆成熟基因单倍型。

Major soybean maturity gene haplotypes revealed by SNPViz analysis of 72 sequenced soybean genomes.

机构信息

Plant Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, University of Missouri, Columbia, Missouri, United States of America.

Department of Computer Science, University of Missouri, Columbia, Missouri, United States of America.

出版信息

PLoS One. 2014 Apr 11;9(4):e94150. doi: 10.1371/journal.pone.0094150. eCollection 2014.

DOI:10.1371/journal.pone.0094150
PMID:24727730
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3984090/
Abstract

In this Genomics Era, vast amounts of next-generation sequencing data have become publicly available for multiple genomes across hundreds of species. Analyses of these large-scale datasets can become cumbersome, especially when comparing nucleotide polymorphisms across many samples within a dataset and among different datasets or organisms. To facilitate the exploration of allelic variation and diversity, we have developed and deployed an in-house computer software to categorize and visualize these haplotypes. The SNPViz software enables users to analyze region-specific haplotypes from single nucleotide polymorphism (SNP) datasets for different sequenced genomes. The examination of allelic variation and diversity of important soybean [Glycine max (L.) Merr.] flowering time and maturity genes may provide additional insight into flowering time regulation and enhance researchers' ability to target soybean breeding for particular environments. For this study, we utilized two available soybean genomic datasets for a total of 72 soybean genotypes encompassing cultivars, landraces, and the wild species Glycine soja. The major soybean maturity genes E1, E2, E3, and E4 along with the Dt1 gene for plant growth architecture were analyzed in an effort to determine the number of major haplotypes for each gene, to evaluate the consistency of the haplotypes with characterized variant alleles, and to identify evidence of artificial selection. The results indicated classification of a small number of predominant haplogroups for each gene and important insights into possible allelic diversity for each gene within the context of known causative mutations. The software has both a stand-alone and web-based version and can be used to analyze other genes, examine additional soybean datasets, and view similar genome sequence and SNP datasets from other species.

摘要

在这个基因组学时代,大量的下一代测序数据已经在数百个物种的多个基因组中公开可用。分析这些大规模数据集可能会变得很繁琐,特别是当比较数据集内和不同数据集或生物体之间的多个样本中的核苷酸多态性时。为了方便等位基因变异和多样性的探索,我们开发并部署了一个内部计算机软件来对这些单倍型进行分类和可视化。SNPViz 软件使用户能够分析来自不同测序基因组的单核苷酸多态性 (SNP) 数据集的特定区域的单倍型。对大豆 [Glycine max (L.) Merr.]开花时间和成熟基因的重要等位基因变异和多样性的研究,可能会为开花时间调控提供更多的见解,并增强研究人员针对特定环境进行大豆育种的能力。在这项研究中,我们利用了两个可用的大豆基因组数据集,总共包含 72 个大豆基因型,包括品种、地方品种和野生种 Glycine soja。分析了主要的大豆成熟基因 E1、E2、E3 和 E4 以及用于植物生长结构的 Dt1 基因,以确定每个基因的主要单倍型数量,评估单倍型与已鉴定的变异等位基因的一致性,并确定人工选择的证据。结果表明,每个基因的少数主要单倍型群被分类,并深入了解了每个基因在已知致病突变背景下的可能等位基因多样性。该软件具有独立和基于网络的版本,可用于分析其他基因,检查其他大豆数据集,并查看来自其他物种的类似基因组序列和 SNP 数据集。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcd9/3984090/5afdb44df1ed/pone.0094150.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcd9/3984090/d7ecb1e5c222/pone.0094150.g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcd9/3984090/5afdb44df1ed/pone.0094150.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcd9/3984090/d7ecb1e5c222/pone.0094150.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcd9/3984090/b062d889a541/pone.0094150.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcd9/3984090/401a5e1a3574/pone.0094150.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcd9/3984090/369b1de58d95/pone.0094150.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcd9/3984090/aa2b47086be5/pone.0094150.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcd9/3984090/5afdb44df1ed/pone.0094150.g006.jpg

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