细胞类型演化中有关基因表达的建模研究
结题报告
批准号:
12001401
项目类别:
青年科学基金项目
资助金额:
24.0 万元
负责人:
梁聪
依托单位:
学科分类:
生物与生命科学中的数学
结题年份:
2023
批准年份:
2020
项目状态:
已结题
项目参与者:
梁聪
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中文摘要
生物个体的复杂程度与构成其的细胞种类数有密切的关系。细胞类型的演化以细胞作为演化单位,研究新的细胞类型及其功能的产生与演化机制,其研究对理解细胞功能和生物多样性有着重要作用。伴随着功能基因组测序技术的发展,多物种多细胞类型的基因表达谱数据大量涌现。然而基于此类数据的演化推断仍存在很大困难,与之相关的数学模型与统计分析方法亟待发展以适应细胞类型演化研究的需要。因此,本项目拟深入研究细胞基因表达演化的数学模型及其在细胞类型演化研究中的应用。具体的本项目拟:(1)构建全基因组基因表达演化的随机过程模型,估计单基因层面的细胞间基因表达关联演化强度;(2)构建不同演化分支上细胞间基因表达关联演化强度差异的检验方法;(3)针对现有模型的不足,改进细胞基因表达演化的随机过程模型及其分析方法。本项目的研究将为细胞类型演化的相关假说提供关键定量分析工具,并为解析细胞功能演化的分子机制提供重要的参考信息。
英文摘要
Body plan complexity is correlated with the number of cell types it consists. In the study of cell type evolution, cell types are taken as “evolutionary units”. The study of novel cell type origination and their functional evolution will significantly enhance our understanding of cellular functions and biodiversity at the organismal level. With the development of next generation sequencing techniques, immense cross-species and cross-celltype gene expression data have been generated in cell type evolutionary studies. However, methods for evolutionary inferences based on such comparative transcriptomic datasets are still limited. Mathematical models and statistical methods are desired to make inferences about cell type evolution strengths and to test evolutionary hypotheses. In this proposal, we plan to investigate the stochastic models of gene expression evolution and their applications to understand questions that emerge in cell type evolutionary studies. This project consists three specific aims: (1) Study the stochastic model of genome-wide gene expression evolution, and estimate the per-gene level of correlated evolution in gene expression; (2) Develop the hypothesis test methods to evaluate the differences in the level of overall correlated evolution in gene expression among evolutionary branches; (3) Improve the current models of cell type specific gene expression evolution such that they could fit the biological phenomena more accurately. The results of this project will provide quantitative methods to answer questions that emerge in cell type evolutionary studies, and provide significant insights into the study of the molecular mechanisms of cell type evolution.
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DOI:10.1109/tetc.2022.3225570
发表时间:2023-07-01
期刊:IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING
影响因子:5.9
作者:Yan, Zihui;Liang, Cong;Wu, Huaming
通讯作者:Wu, Huaming
DOI:10.1109/lcomm.2022.3202961
发表时间:2022
期刊:IEEE Communications Letters
影响因子:--
作者:Zihui Yan;Cong Liang;Huaming Wu
通讯作者:Huaming Wu
国内基金
海外基金