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Related Concept Videos

General Transcription Factors01:30

General Transcription Factors

5.9K
Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
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Transcription Factors02:16

Transcription Factors

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Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
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Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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Structure of a Gene01:30

Structure of a Gene

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A gene is the fundamental unit of heredity. Every individual has two copies of each gene, one inherited from each parent. Although most people contain the same genes, there is a small fraction that is slightly different amongst people. A gene with a small difference in its sequence of DNA bases forms different alleles, contributing to different phenotypes.
However, only 1% of the DNA is composed of genes that encode proteins; the rest, 99% is non-coding DNA. This non-coding DNA performs...
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Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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Tissue Homogenization and Cell Lysis01:32

Tissue Homogenization and Cell Lysis

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Tissue homogenization involves disintegrating tissue architecture and lysing cells, and is an early step in isolating and analyzing cellular components. The method used for homogenization depends on the sample type, the amount of sample available, the analyte to be obtained, and the sensitivity of the method. These methods are broadly classified as mechanical and non-mechanical methods.
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Related Experiment Video

Updated: Oct 20, 2025

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
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Tissue heterogeneity is prevalent in gene expression studies.

Gregor Sturm1, Markus List2, Jitao David Zhang3

  • 1Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, 6020 Innsbruck, Austria.

NAR Genomics and Bioinformatics
|September 13, 2021
PubMed
Summary

Tissue heterogeneity, the unintended profiling of other cells, is a common issue in gene expression data, affecting up to 40% of samples. This variance source, identified using BioQC, impacts reproducibility in biomedical research.

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Area of Science:

  • Biomedical research
  • Genomics
  • Bioinformatics

Background:

  • Reproducibility is a major challenge in gene expression studies.
  • Established factors like batch effects and annotation errors contribute to irreproducibility.
  • Tissue heterogeneity, unintended profiling of non-target cells, is a newly identified source of variance.

Purpose of the Study:

  • To systematically analyze the prevalence of tissue heterogeneity in publicly available gene expression datasets.
  • To quantify the impact of tissue heterogeneity across different tissue types.
  • To highlight tissue heterogeneity as a significant factor affecting data reproducibility.

Main Methods:

  • Systematic analysis of 2,667 gene expression datasets (76,576 samples).
  • Utilized two independent data compendia.
  • Employed a reproducible, open-source software pipeline, including BioQC for quality control.

Main Results:

  • Tissue heterogeneity affects between 1% and 40% of samples, varying by tissue type.
  • Identified severe heterogeneity linked to annotation errors or sample handling.
  • Detected moderate heterogeneity likely due to tissue infiltration or contamination.

Conclusions:

  • Tissue heterogeneity is a widespread phenomenon in public gene expression data.
  • It represents a significant, often overlooked, source of variance impacting reproducibility.
  • Advocates for implementing quality control methods like BioQC to detect and mitigate tissue heterogeneity before data analysis.