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Related Concept Videos

RNA-seq03:21

RNA-seq

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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. 
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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.
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Related Experiment Video

Updated: May 15, 2025

T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing
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T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing

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RNA-seq based T cell repertoire extraction compared with TCR-seq.

Linoy Menda Dabran1, Alona Zilberberg1, Sol Efroni1

  • 1The Mina & Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel.

Oxford Open Immunology
|April 7, 2025
PubMed
Summary
This summary is machine-generated.

RNA sequencing struggles to accurately extract T cell receptor (TCR) sequences, particularly Complementarity-Determining Region 3 (CDR3) variants. TCR sequencing remains the gold standard for reliable repertoire analysis.

Keywords:
AIRR-seqRNA-seqT cell repertoire extractionTCR-seq

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Area of Science:

  • Immunology
  • Bioinformatics
  • Genomics

Background:

  • Vast amounts of RNA sequencing data exist, offering potential for T cell receptor (TCR) repertoire analysis.
  • Current methods for extracting TCR sequences from RNA sequencing data lack validation against established gold standards.
  • Understanding TCR repertoires is crucial for immunology and disease research.

Purpose of the Study:

  • To assess the feasibility and accuracy of extracting T cell receptor (TCR) sequences from RNA sequencing data.
  • To benchmark RNA sequencing-derived TCR data against gold-standard TCR sequencing.
  • To evaluate the impact of sequencing read length and T cell abundance on data extraction.

Main Methods:

  • Comparative analysis of TCR sequences extracted from RNA sequencing versus TCR sequencing (gold standard).
  • Evaluation using both 75 base pair single-end and 150 base pair paired-end sequencing.
  • Calculation of T cell abundance to assess correlation with extracted TCR reads.

Main Results:

  • Significant discrepancies were observed between TCR sequences derived from RNA sequencing and gold-standard TCR sequencing.
  • Longer sequencing read lengths did not substantially improve the accuracy of Complementarity-Determining Region 3 (CDR3) extraction.
  • No significant correlation was found between T cell abundance and the number of TCR reads obtained from RNA sequencing.

Conclusions:

  • RNA sequencing is currently insufficient for accurate and reliable T cell receptor (TCR) sequence extraction.
  • TCR sequencing methodologies are essential for precise repertoire analysis.
  • Researchers should prioritize TCR sequencing for studies requiring accurate TCR repertoire data.