相关实验视频

Updated: Jun 9, 2026

Non-Laser Capture Microscopy Approach for the Microdissection of Discrete Mouse Brain Regions for Total RNA Isolation and Downstream Next-Generation Sequencing and Gene Expression Profiling |

Non-Laser Capture Microscopy Approach for the Microdissection of Discrete Mouse Brain Regions for Total RNA Isolation and Downstream Next-Generation Sequencing and Gene Expression Profiling |

Published on: November 13, 2011

全长RNA转录序列测序追踪了室内老鼠自然种群中的大脑异形多样性

Wenyu Zhang^1,2,3, Anja Guenther^3,4, Yuanxiao Gao⁵

¹Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an 710129, China; wyzhang@nwpu.edu.cn tautz@evolbio.mpg.de.

Genome research

|September 17, 2024

概括

研究人员在小鼠群体中探索了RNA转录异型多样性,确定了超过117,000种独特的异型. 这种广泛的目录揭示了特定种群的模式,并突出了家政基因作为同型变异的关键驱动因素.

科学领域:

基因组学就是基因组学.
分子生物学分子生物学
进化生物学进化生物学

背景情况:

替代拼接产生不同的RNA转录异型从单个基因在真核生物.
自然种群中同型多样性的全部程度及其进化影响尚未得到充分理解.

研究的目的:

在人口层面创建一个完整长度RNA转录异型的广泛目录.
为了研究异形体在不同老鼠种群和物种中的多样性和分布模式.
确定驱动同型多样性的主要来源和机制.

主要方法:

采用了一种新的全长转录丰富协议,具有5'CAP选择.
从48个 *Mus musculus* 种群, *Mus spretus* 和 *Mus spicilegus* 种群的个体中测序了全长RNA转录.
在人口层面开发了高质量的异形目录.

主要成果:

确定了117,728种不同的异型,其中49%是新发现.
异形分布模式在遗传学上具有信息性,并且与单核酸多态 (SNP) 多样性相关.
古代的家政基因和替代的第一个外体是对异构体多样性的重要贡献者.

结论:

生成的异形目录是迄今为止在人口层面上最广泛的.
异形多样性提供了对人口结构和进化历史的见解.
将小鼠基因组注释改进为 ~ 40,000 个保存的异型,可以帮助比较功能基因组学.

更多相关视频

Quantitative Analysis of Alternative Pre-mRNA Splicing in Mouse Brain Sections Using RNA In Situ Hybridization Assay

Quantitative Analysis of Alternative Pre-mRNA Splicing in Mouse Brain Sections Using RNA In Situ Hybridization Assay

Published on: August 26, 2018

Isolation of Region-specific Microglia from One Adult Mouse Brain Hemisphere for Deep Single-cell RNA Sequencing

Isolation of Region-specific Microglia from One Adult Mouse Brain Hemisphere for Deep Single-cell RNA Sequencing

Published on: December 3, 2019

相关概念视频

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...