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相关概念视频

Epistasis Analysis01:09

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Evolution of New Traits in Microbes01:24

Evolution of New Traits in Microbes

Microorganisms evolve rapidly due to their large population sizes and short generation times, often exhibiting measurable changes within days under laboratory conditions. Natural selection acts on standing genetic variation, enabling the retention and amplification of beneficial traits that confer fitness advantages in changing environments.Adaptive Pigment Regulation in RhodobacterIn Rhodobacter, a genus of purple non-sulfur bacteria, light-harvesting pigments such as bacteriochlorophyll and...
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

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).
Genetic Drift03:33

Genetic Drift

Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.

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相关实验视频

Updated: May 11, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

根据基于发展的基因型-表型地图的适应动态.

Isaac Salazar-Ciudad1, Miquel Marín-Riera

  • 1Evolutionary phenomics group. Developmental Biology Program, Institute of Biotechnology, University of Helsinki, PO Box 56, FIN-00014 Helsinki, Finland. isaac.salazar@uab.cat

Nature
|May 3, 2013
PubMed
概括
此摘要是机器生成的。

发育复杂性限制了自然选择.

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Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
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Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

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Last Updated: May 11, 2026

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Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

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科学领域:

  • 进化生物学是进化生物学.
  • 发育生物学是发展生物学.
  • 遗传学 是一个遗传学.

背景情况:

  • 自然选择可以在多大程度上优化表型仍在争论中.
  • 发育过程可能会影响适应的极限.
  • 了解基因型适应性图对于进化研究至关重要.

研究的目的:

  • 研究发展过程如何影响适应.
  • 将基因型-适应性地图分解为基因型-表型和表型-适应性组件.
  • 确定哪些复杂的表型适应性地图允许持续适应.

主要方法:

  • 器官发育的计算模型被用来创建一个基因型-表型图.
  • 采用了三种不同的表型适应性地图:"许多特征"",少数特征"和"粗性".
  • 通过突变,漂移和组合地图来模拟进化.

主要成果:

  • 基因型-表型图的复杂性显著限制了适应.
  • 只有在"粗性"和"少数特征"的表型-适应性地图上才观察到持续的适应性.
  • "多特征"地图显示,由于发育复杂性,适应潜力有限.

结论:

  • 发展过程在塑造适应性景观方面发挥着至关重要的作用.
  • 自然选择优化表型的能力取决于表型-适应性图的结构.
  • 这项研究提供了对进化优化局限性的发展见解.