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Somatic to iPS Cell Reprogramming01:29

Somatic to iPS Cell Reprogramming

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Reprogramming alters the gene expression in somatic cells, transforming them into induced pluripotent stem (iPS) cells over several generations. Scientists can reprogram cells by introducing genes for four transcription factors—Oct4, Sox2, Klf4, and c-Myc (OSKM) by viral or non-viral methods. These factors are also known as Yamanaka factors after Shinya Yamanaka, who first generated iPS cells using mouse skin cells. Yamanaka was awarded the Nobel Prize in Physiology or Medicine in 2012...
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Maintenance of the ES Cell State01:14

Maintenance of the ES Cell State

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The cells of the blastocyst inner cell mass only remain pluripotent for a short time. This state of pluripotency and self-renewal can be maintained in embryonic stem (ES) cell culture by adding specific chemicals or growth factors to ensure the cells can continue dividing and later differentiate into different cell types. In some cases, the cells are grown on a feeder layer of differentiated cells, which provides the growth factors and extracellular matrix components necessary for stem cell...
1.9K
Methods of Nuclear Reprogramming01:24

Methods of Nuclear Reprogramming

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Nuclear reprogramming is a process of transforming one cell type into an unrelated cell type by epigenetic changes that alter the cell’s original gene expression pattern. Such epigenetic changes force cells to express a different set of genes, which play a significant role in inducing transformation into other cell types. Nuclear reprogramming offers applications in reproductive cloning for livestock propagation and regenerative medicine — developing patient-specific cells for...
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Combinatorial Gene Control02:33

Combinatorial Gene Control

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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.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
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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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Transcription Factors02:16

Transcription Factors

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Updated: Apr 28, 2026

A Simple Method to Identify Kinases That Regulate Embryonic Stem Cell Pluripotency by High-throughput Inhibitor Screening
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原始的な多能性のための必須の転写因子プログラムを定義する.

S-J Dunn1, G Martello2, B Yordanov1

  • 1Computational Science Laboratory, Microsoft Research, Cambridge, CB1 2FB, UK.

Science (New York, N.Y.)
|June 7, 2014
PubMed
まとめ
この要約は機械生成です。

科学者たちは,胚性幹細胞 (ES) の自己再生と分化を説明する単純な分子計算モデルを発見しました. この最小限の遺伝子調節ネットワークは,複雑な細胞の行動を簡素化し,将来の幹細胞研究を支援します.

さらに関連する動画

Oct4GiP Reporter Assay to Study Genes that Regulate Mouse Embryonic Stem Cell Maintenance and Self-renewal
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Author Spotlight: Reprogramming Cancer Cells to iPSCs to Study Disease Progression and Treatment Targets
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関連する実験動画

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A Simple Method to Identify Kinases That Regulate Embryonic Stem Cell Pluripotency by High-throughput Inhibitor Screening
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Oct4GiP Reporter Assay to Study Genes that Regulate Mouse Embryonic Stem Cell Maintenance and Self-renewal
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Author Spotlight: Reprogramming Cancer Cells to iPSCs to Study Disease Progression and Treatment Targets
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科学分野:

  • * 発達生物学について
  • * コンピュータ生物学
  • * システム生物学

背景:

  • * 多能胚性幹細胞 (ES) は,自己再生と分化を制御する複雑な遺伝子調節ネットワークを有しています.
  • * これらの細胞の運命を制御する正確な分子回路と実行プログラムについては,まだ完全に理解されていません.

研究 の 目的:

  • * ES細胞の遺伝子調節回路を簡素化し,理解するために,データに制限された計算アプローチを開発する.
  • * ES細胞の行動を説明するのに十分な最小限の構成要素と相互作用のセットを特定する.

主な方法:

  • * 遺伝子規制ネットワークをモデル化するために,データに制限された計算戦略を採用しました.
  • * ネットワークの複雑性を削減して,重要なコンポーネントと相互作用を特定します.
  • * 既知のES細胞の自己更新仕様と,遺伝的混乱に対する予測された応答に対してモデルを検証しました.

主要な成果:

  • *16の相互作用と12の構成要素からなる,ES細胞行動のための最小限の遺伝子調節ネットワークモデルを派生した.
  • *このモデルは,確立されたES細胞の自己再生特性をうまく説明しています.
  • * 70%の精度で遺伝的混乱に対する新しい,直感に反する反応を予測した.

結論:

  • * ES細胞のアイデンティティの伝播は,広範囲のインタラクトームではなく,比較的単純な分子計算によって制御されます.
  • * この簡素化されたモデルは,幹細胞の運命決定を理解し予測するための強力な枠組みを提供します.