Quantitative and function analysis platform for repetitive genes and gene isoforms in pluripotency regulation and differentiations

多能性调控和分化中重复基因和基因亚型的定量和功能分析平台

• 批准号: 10451490
• 负责人: Kin Fai Au
• 金额: $ 60万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10451490
• 关键词: Address; Adopted; Alternative Splicing; Anterior; Bioinformatics; Biological; Biology; Biomedical Research; Complex; Computer software; Data; Development; Developmental Biology; Differentiated Gene; Embryonic Development; Endoderm; Event; Exons; Foundations; Genes; Genetic; Human; Laboratory Research; Lead; Methodology; Methods; Modeling; Names; Nature; Pathway Analysis; Pattern; Pilot Projects; Prevalence; Primitive foregut structure; Problem Solving; Protein Isoforms; Publications; Publishing; Regulation; Repetitive Sequence; Research; Retrotransposon; Role; Sampling; Series; Solid; Spliced Genes; Statistical Models; Structure; Structure of primordial sex cell; Techniques; Technology; The Jackson Laboratory; Time; Transcript; Zebrafish; base; cost; dark matter; data integration; differential expression; experimental study; gene network; human embryonic stem cell; human stem cells; improved; indexing; innovation; next generation sequencing; novel; pluripotency; pluripotency factor; precision medicine; public health relevance; rapid technique; statistics; stem cell biology; stem cell differentiation; stem cells; tool; transcriptome; transcriptome sequencing; transcriptomics

PROJECT SUMMARY / ABSTRACT Many researches have indicated the prevalence and important functions of repetitive genes and gene isoforms, especially on stem cell biology and developmental biology. While the development of the existing techniques to characterize transcriptome based on Next Generation Sequencing (NGS), has dramatically accelerated the research of different transcriptomic events and has led to many important biological findings, the abundance estimation of repetitive genes and genes isoforms remain a challenging problem. Hence, many downstream quantitative analyses, such as differential expression analysis and network construction are hindered by this limit. As the new long-read techniques have been optimized to convey robust sequencing data of transcriptome with more unambiguous alignment, it brings in new discernible information that is useful for addressing certain challenging but important transcriptomic problems. Our objective is to develop a series of bioinformatics methods to perform more reliable quantitative and function analyses of repetitive genes and gene isoforms, including abundance estimation, network construction and function prediction. Aim 1 is to identify quantification errors and the incorrectly quantified genes and gene isoforms. Aim 2 is to solve the problem of quantification by data integration. Aim 3 is to construct gene isoform network and find the possible isoform-specific functions by network analysis. The methods will be applied to study the expression and function of repetitive genes and gene isoforms in human stem cells and differentiations in Aim 4. These studies are anticipated to provide the first bioinformatics platform for improve our understanding of repetitive genes and gene isoforms with complex biomedical context in a comprehensive manner.

项目摘要/摘要