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。受精后，每个个体分别从母亲那里得到一条单倍体染色体（n=23条染色体，约30亿个DNA碱基），从父亲那里得到一条单倍体染色体，形成二倍体基因组。在临床基因组注释和复杂疾病研究等基因组亚学科中，更有效的二倍体基因组解释方法有助于阐明基因组功能和缺失的基因组遗传能力。该研究项目将与新加坡国立大学的计算基因组学专家宋永健博士合作，开发计算方法来揭示依赖于人类基因组二倍体特性的特征。人类基因组测序技术近年来发展迅速。然而，需要精确的统计和计算方法来为个体突变分配母体或父亲的特定（相位）功能。序列分析通过利用家族三重奏，考虑到每个变体的特定阶段背景，可能会发现突变组合的功能影响，否则这些影响将无法被发现。该项目的目标是提供一个模块化的阶段计算管道，可以适用于测序三重奏的数据集，因此核三重奏和扩展谱系的数据集将被纳入本研究。目前，一个初步的“功能阶段”管道已经在编程语言Python和r中实现，用于分析样本。这个早期阶段的软件已经发现了关于阶段特定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。该奖项由美国国家科学基金会与新加坡国家研究基金会共同资助。

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.