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引用次数: 0
摘要
在过去十年中,全基因组关联研究发现了数千个与复杂性状有显著关联的变异。对于每个基因位点,都需要基因表达水平来进一步探索其生物学功能。为此,PrediXcan 算法利用大规模参考数据,从单核苷酸多态性推算基因表达水平,从而测试基因与性状的关联,找出候选因果基因。然而,由于大多数参考数据都来自欧洲血统的受试者,而东亚血统受试者的预测基因表达的准确性和稳健性仍不清楚,这就带来了挑战。在此,我们首先模拟了多种情况,以探索人群多样性水平对基因表达的影响。我们利用基因组聚合数据库(The Genome Aggregation Database)中的等位基因频率信息估算了种群差异变异。我们发现,变体的权重是影响基因表达预测的主要因素,根据比例测试,约 70% 的变体具有显著的种群差异。为了深入了解人口对基因表达水平的影响,我们利用等位基因频率信息为 EAS 祖先开发了一个基因表达参考面板,即 Predict Asian-Population (PredictAP)。在使用 EAS 受试者的基因型数据时,PredictAP 可被视为 PrediXcan 的辅助工具。
Cross-population enhancement of PrediXcan predictions with a gnomAD-based east Asian reference framework.
Over the past decade, genome-wide association studies have identified thousands of variants significantly associated with complex traits. For each locus, gene expression levels are needed to further explore its biological functions. To address this, the PrediXcan algorithm leverages large-scale reference data to impute the gene expression level from single nucleotide polymorphisms, and thus the gene-trait associations can be tested to identify the candidate causal genes. However, a challenge arises due to the fact that most reference data are from subjects of European ancestry, and the accuracy and robustness of predicted gene expression in subjects of East Asian (EAS) ancestry remains unclear. Here, we first simulated a variety of scenarios to explore the impact of the level of population diversity on gene expression. Population differentiated variants were estimated by using the allele frequency information from The Genome Aggregation Database. We found that the weights of a variants was the main factor that affected the gene expression predictions, and that ~70% of variants were significantly population differentiated based on proportion tests. To provide insights into this population effect on gene expression levels, we utilized the allele frequency information to develop a gene expression reference panel, Predict Asian-Population (PredictAP), for EAS ancestry. PredictAP can be viewed as an auxiliary tool for PrediXcan when using genotype data from EAS subjects.
期刊介绍:
Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data.
The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.