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Related Concept Videos

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Ribosome Profiling

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Related Experiment Video

Updated: Oct 16, 2025

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
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Comparability of reference-based and reference-free transcriptome analysis approaches at the gene expression level.

Sung-Gwon Lee1, Dokyun Na2, Chungoo Park3

  • 1School of Biological Sciences and Technology, Chonnam National University, Gwangju, 61186, Republic of Korea.

BMC Bioinformatics
|October 22, 2021
PubMed
Summary

Reference-free transcriptome analysis can be replaced by reference-based approaches for gene expression quantification. However, careful validation is needed for low-expression genes, long coding sequences, or large gene families when using the reference-free method.

Keywords:
Quantification of gene expressionRNA-seqReference-based assemblyReference-free assemblyTranscriptome analysis

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Area of Science:

  • Bioinformatics
  • Genomics
  • Transcriptomics

Background:

  • High-throughput RNA sequencing is crucial for understanding cell type dynamics.
  • Reference-free (RF) de novo transcriptome analysis is vital for non-model organisms lacking complete genomes.
  • Previous studies assessed transcriptome assembly but not expression level consistency between RF and RB methods.

Purpose of the Study:

  • To evaluate differences in gene expression profiles between RF and RB transcriptome analyses.
  • To determine the reliability of RF methods compared to RB approaches for gene expression quantification.

Main Methods:

  • Comparative analysis of gene expression profiles.
  • Evaluation of transcriptome repertoires and quantification accuracy.
  • Assessment of potential biases in RF analysis for specific gene types.

Main Results:

  • Reference-based approaches can effectively replace reference-free methods for transcriptome repertoires and gene expression quantification.
  • Reference-free methods may require cautious interpretation for certain gene categories.
  • Lowly expressed genes, long coding sequences, and large gene families necessitate careful validation when using RF analysis.

Conclusions:

  • Empirical results provide valuable insights for transcriptome analysis in non-model organisms.
  • Reference-based methods offer a reliable alternative for gene expression studies.
  • Understanding the limitations of RF analysis is crucial for accurate biological interpretation.