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Related Concept Videos

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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Updated: May 27, 2026

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA
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An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

Published on: February 17, 2023

Protein identification using customized protein sequence databases derived from RNA-Seq data.

Xiaojing Wang1, Robbert J C Slebos, Dong Wang

  • 1Department of Biomedical Informatics,Vanderbilt University School of Medicine , Nashville, Tennessee 37232, United States.

Journal of Proteome Research
|November 23, 2011
PubMed
Summary
This summary is machine-generated.

Generating sample-specific protein databases from RNA sequencing (RNA-Seq) data enhances shotgun proteomics. This approach improves peptide identification and protein variant detection for more comprehensive proteomic discovery.

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Area of Science:

  • Proteomics
  • Genomics
  • Bioinformatics

Background:

  • Standard shotgun proteomics uses genome-derived databases, which may not accurately reflect the expressed proteome.
  • RNA sequencing (RNA-Seq) provides a comprehensive view of gene expression, offering potential for improved proteomic analysis.
  • A sample-specific protein database could better represent the actual protein pool, enhancing identification accuracy.

Purpose of the Study:

  • To develop and validate a two-step strategy for constructing sample-specific protein databases from RNA-Seq data.
  • To improve protein identification sensitivity and comprehensiveness in shotgun proteomics.
  • To enable the detection of known and novel peptide variants.

Main Methods:

  • Developed a two-step strategy for building sample-specific protein databases from RNA-Seq data.
  • Step 1: Reduced database size by filtering unexpressed or lowly expressed genes based on transcript quantification.
  • Step 2: Identified high-quality nonsynonymous coding single nucleotide variations (SNVs) from RNA-Seq and incorporated corresponding protein variants.

Main Results:

  • Customized protein sequence databases significantly increased peptide identification sensitivity.
  • Reduced ambiguity in protein assembly and enabled detection of known and novel peptide variants.
  • Demonstrated effectiveness using RNA-Seq and shotgun proteomics data from colorectal cancer cell lines (SW480 and RKO).

Conclusions:

  • Sample-specific databases derived from RNA-Seq data are effective for enhancing shotgun proteomics.
  • This approach leads to more sensitive and comprehensive protein discovery.
  • Enables better characterization of proteomic variations within specific biological samples.