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関連する概念動画

Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

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In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
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Position-effect Variegation02:32

Position-effect Variegation

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In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.
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Mismatch Repair01:20

Mismatch Repair

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Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
The Mutator Protein Family Plays a Key Role in DNA Mismatch Repair
The human genome has more than 3 billion base pairs of DNA per cell. Prior to cell division, that vast amount of genetic...
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Point and Frameshift Mutations01:30

Point and Frameshift Mutations

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Point mutations are genetic alterations involving the change of a single nucleotide base pair in DNA. Depending on how the alteration affects protein synthesis, they can lead to various consequences.Point mutations fall into the following types:Silent mutations occur when a nucleotide change does not alter the amino acid sequence due to the redundancy of the genetic code. For instance, changing ACC to ACA still encodes threonine, leaving the protein function unaffected. This occurs because...
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Nucleosome Remodeling02:54

Nucleosome Remodeling

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Nucleosomes are the basic units of chromatin compaction. Each nucleosome consists of the DNA bound tightly around a histone core, which makes the DNA inaccessible to DNA binding proteins such as DNA polymerase and RNA polymerase. Hence, the fundamental problem is to ensure access to DNA when appropriate, despite the compact and protective chromatin structure.
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Updated: Sep 8, 2025

Measuring Microbial Mutation Rates with the Fluctuation Assay
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Measuring Microbial Mutation Rates with the Fluctuation Assay

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変動構造はゲノム全体の混乱結果を予測する.

Benjamin Kuznets-Speck1,2,3,4, Leon Schwartz1,2,3,4,5, Hanxiao Sun1,2,3,4

  • 1Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago IL, USA.

Research square
|August 20, 2025
PubMed
まとめ
この要約は機械生成です。

遺伝子発現データを分析するための 新しい枠組みである CIPHERを開発しました CIPHERは遺伝子共振を用いて 細胞が干渉にどのように反応するか予測し 生物学的洞察を向上させます

キーワード:
ベイズ統計変動するゲノム全体の反応線形応答理論単細胞の乱れ

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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis
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Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

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関連する実験動画

Last Updated: Sep 8, 2025

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07:44

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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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科学分野:

  • 機能的ゲノミクス
  • システム生物学
  • 統計物理学

背景:

  • 単細胞のパルバーブレーションスクリーンの解釈は困難です.
  • 現在の方法は不透明なディープラーニングモデルか 単純化されたフレームワークです
  • 不動の細胞における遺伝子の共変動は,不動の反応モデリングに情報を与えることができます.

研究 の 目的:

  • CIPHER (混乱と高次元表現応答のための共変性推論) を提示します.トランスクリプトーム全体の混乱結果を予測するための新しいフレームワークです.
  • 線形反応理論と遺伝子の共変動を活用して,混乱スクリーンの生物学的な解釈を向上させる.

主な方法:

  • 線形反応理論と遺伝子共変動を用いたフレームワークであるCIPHERを開発した.
  • 合成ネットワークと11の大規模な単細胞の混乱データセット (4,234の混乱, >1.36Mのセル) で検証された.
  • 不確実性認識効果の大きさを推定するためにベイジアン推論を使用した.

主要な成果:

  • CIPHERは,基因共変性を利用して,単一および二重の干渉に対する全ゲノム応答を正確に復元した.
  • 遺伝子コヴァリアンスを除去することで モデルの性能が11倍に低下し 変動構造の重要性を強調しました
  • 遺伝子の相関は,独立した研究で転送可能であり,保存された変動パターンを示している.
  • CIPHERは混乱を特定する際の差分表現メトリックを上回り,不確実性認識の見積もりを提供しました.
  • ~3つのグローバル遺伝子モジュールに沿ってコヴァリアンスマトリックスを通じてゲノム全体の反応が伝播した.

結論:

  • CIPHERは 複雑な生物学的反応を理解する上で 理論的に根拠づけられたモデルの力を示しています
  • 細胞の変動パターンは,混乱の結果を予測するために重要な基本的な設計原理をコードします.
  • 遺伝子の共変動を活用することで 機能的ゲノム解析に より堅固なアプローチが提供されます