EAPSI: Deciphering functionality of mutations across the human genome with respect to parental DNA contribution

EAPSI：破译人类基因组突变与亲代 DNA 贡献相关的功能

• 批准号: 1415114
• 负责人: Danjuma Quarless
• 金额: $ 0.51万
• 依托单位: Quarless Danjuma X
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1415114&HistoricalAwards=false
• 关键词: EAPSI; Deciphering; functionality; mutations; across

Every human genome consists of approximately 6.5 billion deoxyribose nucleic acid (DNA) bases organized into two sets of 23 chromosomes. Each individual receives one haploid set of chromosomes (n=23 chromosomes, ~3 billion DNA bases) from their mother and one set from their father upon fertilization, making a diploid genome. More effective methods accounting for diploid genome could help elucidate genome function and missing genome heritability in a number of genomic sub-disciplines including clinical genome annotation and complex disease studies. In collaboration with Dr. Ken Wing-Kin Sung at the National University of Singapore who has expertise in computational genomics, this research project will develop computational methods to uncover features dependent on the diploid nature of the human genome.Human genome sequencing technologies have rapidly advanced in recent years. However, accurate statistical and computational methods are needed to assign maternal or paternal specific (phase) function to individual mutations. Sequence analyses that take into account the phase-specific context of each variant by leveraging familial trios may uncover the functional effects of mutation combinations that would otherwise go undetected. The goal of this project is to provide a modular phase computational pipeline that can be adapted for datasets of sequenced trios, thus datasets where nuclear trios and extended pedigrees have been sequenced will be incorporated into this study. Currently, a preliminary 'functional phase' pipeline to analyze samples has been implemented in the programming languages Python and R. This early stage software has already uncovered novel insights regarding the frequency of phase-specific functional coding pairs and statistical determination of functional variants alleles in the available dataset. This NSF EAPSI award is funded in collaboration with the National Research Foundation of Singapore.

每个人类基因组由大约65亿个脱氧核糖核酸（DNA）碱基组成，组成两组23条染色体。受精后，每个个体从母亲那里获得一组单倍体染色体（n=23条染色体，约30亿个DNA碱基），从父亲那里获得一组染色体，形成二倍体基因组。解释二倍体基因组的更有效方法可以帮助阐明许多基因组子学科（包括临床基因组注释和复杂疾病研究）中的基因组功能和缺失的基因组遗传性。这项研究计划将与新加坡国立大学的Ken Wing-Kin Sung博士合作，他在计算基因组学方面具有专长，该研究计划将开发计算方法，以揭示依赖于人类基因组二倍体性质的特征。然而，需要精确的统计和计算方法来分配母体或父体特异性（相位）功能到个体突变。通过利用家族性三联体来考虑每个变体的阶段特异性背景的序列分析可以揭示突变组合的功能效应，否则这些功能效应将无法检测到。本项目的目标是提供一个模块化的阶段计算管道，可以适用于测序的三人组数据集，因此将核三人组和扩展谱系测序的数据集纳入本研究。目前，已经在编程语言Python和R中实现了分析样本的初步“功能阶段”管道。这个早期阶段的软件已经揭示了关于可用数据集中阶段特异性功能编码对的频率和功能变体等位基因的统计测定的新见解。这个NSF EAPSI奖是与新加坡国家研究基金会合作资助的。