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Related Concept Videos

General Transcription Factors01:30

General Transcription Factors

7.4K
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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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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Master Transcription Regulators02:23

Master Transcription Regulators

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Transcription Factors02:16

Transcription Factors

83.2K
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...
83.2K
Transcription01:10

Transcription

157.9K
Overview
Transcription is the process of synthesizing RNA from a DNA sequence by RNA polymerase. It is the first step in producing a protein from a gene sequence. Additionally, many other proteins and regulatory sequences are involved in the proper synthesis of messenger RNA (mRNA). Regulation of transcription is responsible for the differentiation of all the different types of cells and often for the proper cellular response to environmental signals.
Transcription Can Produce Different Kinds...
157.9K
Transcription01:17

Transcription

34.4K
Transcription is the synthesis of RNA from a DNA sequence by RNA polymerase. It is the first step in producing a protein from a gene sequence. Additionally, many other proteins and regulatory sequences are involved in correctly synthesizing messenger RNA (mRNA). Transcriptional regulation is responsible for the differentiation of different types of cells and often for the proper cellular response to environmental signals.
Transcription Can Produce Different Kinds of RNA Molecules
In eukaryotes,...
34.4K

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Related Experiment Video

Updated: Mar 6, 2026

Author Spotlight: An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations
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Discovering sparse transcription factor codes for cell states and state transitions during development.

Leon A Furchtgott1,2, Samuel Melton1,3, Vilas Menon4,5

  • 1FAS Center for Systems Biology, Harvard University, Cambridge, United States.

Elife
|March 16, 2017
PubMed
Summary

Researchers developed a new computational method to analyze gene expression patterns, revealing key genes that guide cell development and lineage decisions in various tissues.

Keywords:
Transcriptomicscomputational biologydevelopmental biologyhumanmousestem cellssystems biology

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Area of Science:

  • Computational biology
  • Developmental biology
  • Genomics

Background:

  • Determining cell lineage pathways and identifying influential genes from gene expression data is computationally complex.
  • Multipotent cell differentiation involves intricate lineage choices and gene regulation.

Purpose of the Study:

  • To develop a statistical framework for simultaneously inferring cell lineage transitions and identifying key regulatory genes.
  • To apply this framework to reconstruct developmental trees and analyze single-cell RNA sequencing data.

Main Methods:

  • Discovered a gene expression pattern correlating with developmental topologies in B- and T-cell lineages.
  • Developed a statistical model to infer lineage relationships and gene determinants from expression data.
  • Applied the framework to hematopoietic, intestinal, and human cortical development datasets.

Main Results:

  • Successfully reconstructed early hematopoietic and intestinal developmental trees.
  • Inferred a neocortical-hindbrain split in early human cortical progenitor cells.
  • Identified key genes potentially controlling lineage decisions in cortical development.

Conclusions:

  • The developed framework enables simultaneous inference of cell identity, lineage, and key regulatory genes.
  • This approach offers a powerful tool for understanding complex developmental processes from gene expression data.