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相关概念视频

RNA-seq03:21

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...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...

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相关实验视频

Updated: May 9, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

使用tRFUniverse功能分析分析小RNA-seq数据分析tRNA衍生的ncRNA的协议.

Alessandro La Ferlita1, Giovanni Nigita2, Alfredo Ferro3

  • 1Department of Internal Medicine, Division of Medical Oncology, Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA.

STAR protocols
|June 12, 2025
PubMed
概括

本研究介绍了一种分析tRNA衍生碎片 (tRFs) 的协议,使用小RNA测序 (smRNA-seq). 该方法有助于在肺癌等疾病中识别失调的tRF.

关键词:
生物信息学是一种生物信息学.癌症 癌症 癌症 癌症基因组学就是基因组学.在RNAseqqq中使用.序列分析是指进行序列分析.

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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

相关实验视频

Last Updated: May 9, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

科学领域:

  • 分子生物学分子生物学
  • 生物信息学是一种生物信息学.
  • 基因组学就是基因组学.

背景情况:

  • 小RNA测序 (smRNA-seq) 对于理解tRNA衍生碎片 (tRFs) 是至关重要的.
  • tRF在人类生理学和疾病中起着重要的作用.
  • 对于准确的tRF表达式分析,需要标准化的协议.

研究的目的:

  • 从smRNA-seq数据中评估tRF表达的综合性协议.
  • 为了能够对tRF表达数据进行可靠的量化和协调.
  • 为了促进在疾病背景下对tRFs的功能分析.

主要方法:

  • smRNA-seq数据预处理的详细步骤,包括质量过和适配器修剪.
  • 阅读映射策略用于准确的tRF识别.
  • 量化tRF表达和协调数据集的程序.
  • 使用tRFUniverse进行功能分析.

主要成果:

  • 该协议有效地从smRNA-seq数据中评估tRF表达.
  • 使用TCGA数据进行的肺癌病例研究显示tRFs显著失调.
  • 确定了与肺癌病原发生相关的特定tRF.

结论:

  • 开发的协议为tRF表达式分析提供了一种可靠的方法.
  • 失调的tRF是肺癌中的潜在生物标志物和治疗点.
  • 这项工作促进了对人类健康和疾病中tRF的进一步研究.