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

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。每个个体受精后从母亲那里得到一套单倍体染色体(n=23条染色体，约30亿个DNA碱基)，从父亲那里得到一套染色体，形成二倍体基因组。在包括临床基因组注释和复杂疾病研究在内的许多基因组子学科中，更有效的二倍体基因组研究方法可以帮助阐明基因组功能和缺失基因组的遗传性。这项研究项目将与新加坡国立大学在计算基因组学方面拥有专业知识的Ken Wing-Kin Sung博士合作，开发计算方法来揭示依赖于人类基因组二倍体性质的特征。近年来，人类基因组测序技术发展迅速。然而，需要准确的统计和计算方法来将母系或父系特定的(阶段)功能分配给个体突变。通过利用家族三元组考虑到每个变体的特定阶段背景的序列分析可能会揭示突变组合的功能效应，否则这些突变组合将无法被检测到。该项目的目标是提供一个模块化的阶段计算管道，该管道可以适用于已测序的三重序列的数据集，从而将已对核三重序列和扩展家系进行测序的数据集纳入本研究。目前，用编程语言PYTHON和R实现了用于分析样本的初步“功能阶段”流水线。这个早期阶段的软件已经发现了关于特定阶段功能编码对的频率和可用数据集中功能变异等位基因的统计确定的新见解。该NSF EAPSI奖是与新加坡国家研究基金会合作资助的。

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.