基于转录组数据分析小鼠心肌细胞直接重编程的分子机制

Lili Ye,Fuhai Song,Xing Peng,Guangchun Han,Ting Wei,Fengmin Ji,Hongxing Lei

Genomics and Applied Biology（2016）

Cited 0|Views11

Abstract

本研究旨在从分子水平揭示小鼠成纤维细胞直接重编程为心肌细胞的机制,为诱导心肌细胞再生提供新思路.在公共基因芯片数据库(GEO)中下载小鼠(Mus musculus)心肌细胞直接重编程相关的基因芯片数据,其中成纤维细胞样本数24例,诱导性心肌细胞样本数43例.利用统计软件R3.1.1采用Rankprod算法(p＜0.05,|lgFC|＞1)获得心肌细胞直接重编程过程中的差异表达基因,利用DAVID、ToppGene和STRING等在线工具对差异表达基因进行生物信息学分析.最终分析筛选出210个心肌细胞直接重编程过程的差异表达基因,包括115个表达上调,95个表达下调.生物信息学分析发现Cybb、Clqa和Fabp4等基因以及横纹肌收缩等信号通路在心肌细胞直接重编程过程中起着重要作用.

Key words

Cardiomyocyte,Differentially expressed gene,Bioinformatics,Direct reprogramming,Microarray

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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