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相关概念视频

Mutation, Gene Flow, and Genetic Drift01:09

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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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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.
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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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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.
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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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相关实验视频

Updated: Sep 8, 2025

Measuring Microbial Mutation Rates with the Fluctuation Assay
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波动结构预测全基因组扰动结果

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
概括

我们开发了CIPHER, 一种用于分析单细胞扰动屏幕中的基因表达数据的新框架. CIPHER使用基因协同波动来预测细胞如何应对干扰,从而提高生物洞察力.

关键词:
贝叶斯统计波动情况全基因组反应线性响应理论单细胞扰动

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科学领域:

  • 功能性基因组学
  • 系统生物学
  • 统计物理

背景情况:

  • 解释聚合单细胞扰动屏幕是一个挑战.
  • 目前的方法要么是不透明的深度学习模型,要么是过于简单的框架.
  • 不被扰乱的细胞中的基因共波动可以为扰乱反应建模提供信息.

研究的目的:

  • 介绍CIPHER (扰动和高维表达响应的共变推理),这是预测全转录组扰动结果的新框架.
  • 利用线性响应理论和基因共波动来增强扰动屏幕的生物解释.

主要方法:

  • 开发了CIPHER,一个使用线性响应理论和基因共波动的框架.
  • 在合成网络和11个大规模单细胞扰动数据集 (4,234个扰动,>1.36M个细胞) 上验证.
  • 使用贝叶斯推断来估计不确定性意识效应的大小.

主要成果:

  • 通过利用基因共变性,CIPHER准确地对单个和双重扰动进行了全基因组应答.
  • 消除基因对基因的共异性使模型的性能降低了11倍,突出显示了波动结构的重要性.
  • 基因与基因的相关性可以在独立的研究中转移,这表明基因的波动模式得到保留.
  • CIPHER在识别扰动方面表现优于差异表达量,并提供了不确定性意识的估计.
  • 整个基因组的反应通过共变矩阵沿着~3个全球基因模块传播.

结论:

  • 在理解复杂的生物反应方面, CIPHER 展示了理论模型的力量.
  • 细胞波动模式为预测扰动结果提供了关键的基本设计原理.
  • 利用基因协同波动为功能基因组学分析提供了更强大的方法.