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A Bioinformatics Workflow for Genetic Association Studies of Traits in Indonesian Rice

机译:印尼水稻性状遗传关联研究的生物信息学工作流程

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Asian rice is a staple food in Indonesia and worldwide, and its production is essential to food security. Cataloging and linking genetic variation in Asian rice to important traits, such as quality and yield, is needed in developing superior varieties of rice. We develop a bioinformatics workflow for quality control and data analysis of genetic and trait data for a diversity panel of 467 rice varieties found in Indonesia. The bioinformatics workflow operates using a back-end relational database for data storage and retrieval. Quality control and data analysis procedures are implemented and automated using the whole genome data analysis toolset, PLINK, and the [R] statistical computing language. The 467 rice varieties were genotyped using a custom array (717,312 genotypes total) and phenotyped for 12 traits in four locations in Indonesia across multiple seasons. We applied our bioinformatics workflow to these data and present prototype genome-wide association results for a continuous trait - days to flowering. Two genetic variants, located on chromosome 4 and 12 of the rice genome, showed evidence for association in these data. We conclude by outlining extensions to the workflow and plans for more sophisticated statistical analyses.
机译:亚洲大米是印度尼西亚乃至全世界的主食,其生产对粮食安全至关重要。开发优质水稻品种需要将亚洲水稻的遗传变异与重要特性(例如品质和产量)进行分类并将其联系起来。我们开发了一个生物信息学工作流程,以对印度尼西亚发现的467个水稻品种的多样性进行质量控制以及遗传和性状数据的数据分析。生物信息学工作流程使用后端关系数据库进行操作,以进行数据存储和检索。使用整个基因组数据分析工具集,PLINK和[R]统计计算语言来实施和自动化质量控制和数据分析程序。使用自定义阵列对467个水稻品种进行基因分型(共717,312个基因型),并在多个季节中在印度尼西亚四个地方的12个性状进行表型分析。我们将我们的生物信息学工作流程应用于这些数据,并给出了原型基因组范围内的连续性状结果-开花天数。位于水稻基因组4号和12号染色体上的两个遗传变异显示出与这些数据相关的证据。最后,我们概述了工作流程的扩展和计划,以进行更复杂的统计分析。

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