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Related Concept Videos

Frequency-dependent Selection01:21

Frequency-dependent Selection

22.6K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
22.6K
Types of Selection01:46

Types of Selection

43.1K
Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
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Dose-Response Relationship: Selectivity and Specificity01:25

Dose-Response Relationship: Selectivity and Specificity

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Drugs exert their therapeutic effects by interacting with receptors, enzymes, or ion channels that are present throughout the human body. The strength and duration of the interaction between a drug and its target receptor are characterized by the selectivity and specificity of the drug. Selectivity refers to a drug's strong preference for its intended target over other targets. For instance, isoprenaline, a non-selective β-adrenergic agonist, interacts with both β1- and...
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Conservation of Small Populations02:04

Conservation of Small Populations

16.1K
Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
16.1K
Limits to Natural Selection01:38

Limits to Natural Selection

33.4K
Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.
33.4K
Genetic Drift03:33

Genetic Drift

42.0K
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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Related Experiment Video

Updated: Nov 17, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

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Population-specific causal disease effect sizes in functionally important regions impacted by selection.

Huwenbo Shi1,2, Steven Gazal3,4, Masahiro Kanai4,5,6,7,8

  • 1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. hshi@hsph.harvard.edu.

Nature Communications
|February 18, 2021
PubMed
Summary
This summary is machine-generated.

Genetic architecture varies across populations, impacting disease risk prediction. New methods reveal that functionally important genomic regions show more population-specific genetic effects, especially in conserved and regulatory areas.

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

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Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

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Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
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Area of Science:

  • Human genetics
  • Population genetics
  • Genomic annotation

Background:

  • Trans-ethnic genetic correlations are often below 1, indicating population-specific genetic effects for many diseases.
  • This limits the accuracy of trans-ethnic polygenic risk prediction models.
  • Understanding genetic correlation differences across populations is crucial for improving genomic medicine.

Purpose of the Study:

  • To develop a novel method (S-LDXR) for analyzing genetic correlation across genomic annotations.
  • To investigate the extent and location of population-specific genetic effects in human diseases and complex traits.
  • To identify genomic features associated with varying levels of trans-ethnic genetic correlation.

Main Methods:

  • Developed S-LDXR (Stratified Linkage Disequilibrium Score Regression) to partition squared trans-ethnic genetic correlation.
  • Applied S-LDXR to genome-wide summary statistics from East Asian and European cohorts for 31 diseases/traits.
  • Analyzed correlations across genomic annotations, including background selection and gene expression data.

Main Results:

  • The average trans-ethnic genetic correlation was 0.85.
  • Squared trans-ethnic genetic correlation was significantly depleted (0.82) in regions under strong background selection.
  • Population-specific causal effects were enriched in conserved, regulatory regions, and near specifically expressed genes (e.g., immune, skin).

Conclusions:

  • Genomic regions under selection exhibit more population-specific genetic effects.
  • Functional importance, conserved regions, and gene expression patterns correlate with genetic specificity.
  • Gene-environment interactions, particularly with positive selection, may explain these observed patterns.