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Related Concept Videos

General Transcription Factors01:30

General 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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Transcription Factors02:16

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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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Combinatorial Gene Control02:33

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Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
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Pleiotropy01:33

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Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...
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Master Transcription Regulators02:23

Master Transcription Regulators

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Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
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Related Experiment Video

Updated: Mar 15, 2026

Author Spotlight: An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations
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Complex Patterns of Association between Pleiotropy and Transcription Factor Evolution.

Kevin N Chesmore1, Jacquelaine Bartlett1, Chao Cheng1

  • 1Department of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, NH.

Genome Biology and Evolution
|September 17, 2016
PubMed
Summary

Pleiotropy constrains human transcription factor evolution, with protein interactions limiting evolution more than DNA targets. Highly pleiotropic genes, often linked to diseases, show distinct evolutionary constraints.

Keywords:
ENCODEevolutionary constraintpleiotropytranscription factors

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Area of Science:

  • Evolutionary biology
  • Genomics
  • Molecular biology

Background:

  • Pleiotropy's role in constraining gene evolution is debated.
  • Human transcription factors (TFs) are well-characterized gene classes.
  • Molecular data enables detailed investigation of pleiotropic effects.

Purpose of the Study:

  • Analyze evolutionary rates of human TFs and their domains.
  • Investigate the impact of pleiotropy (TF-TF interactions, DNA targets) on TF evolution.
  • Determine if pleiotropic constraints differ by functional domain.

Main Methods:

  • Extracted data from ENCODE Chip-Seq, String database, and NHGRI GWAS catalog.
  • Calculated evolutionary rates of full TF proteins and domains using PAML CodeML.
  • Quantified pleiotropy by TF-TF interactions and DNA-binding targets.

Main Results:

  • Both TF-TF interactions and DNA targets correlate with constrained TF evolution.
  • DNA targets constrained only DNA-binding domains; TF-TF interactions constrained full proteins more strongly.
  • Higher protein-protein interaction domain (PID) count correlated with faster evolutionary rates.
  • GWAS-associated TFs are more pleiotropic and linked to disease phenotypes.

Conclusions:

  • Pleiotropy significantly constrains human TF evolution, with domain-specific effects.
  • TF-TF interactions impose stronger evolutionary constraints than DNA-binding targets.
  • Pleiotropy is linked to disease susceptibility, highlighting functional and evolutionary significance.