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Related Concept Videos

Heritability01:06

Heritability

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Heritability is a statistical concept that measures the degree to which genetic differences among individuals contribute to trait variations within a population. It is a fundamental idea in genetics, often prone to misinterpretation. Heritability is expressed as a percentage, reflecting the proportion of variation in a specific trait across a population that can be linked to genetic differences. However, it's important to understand that heritability does not determine how "genetic"...
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Pharmacogenetics and Pharmacogenomics: Overview01:29

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Pharmacogenetics and pharmacogenomics examine how genetic factors influence an individual's response to drugs. While pharmacogenetics focuses on the impact of specific genetic variants on drug effects, pharmacogenomics takes a broader approach, studying how genetic variation across populations contributes to differences in drug responses. These fields aim to explain why individuals may experience varying levels of efficacy or adverse reactions to the same medication.Variability in drug...
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Genetic Variation01:25

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Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
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Behavioral Genetics and Its Designs01:23

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Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Principles of Pharmacogenetics: Types of Genetic Variants01:27

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The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
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Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis
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Genomic heritability: what is it?

Gustavo de Los Campos1, Daniel Sorensen2, Daniel Gianola3

  • 1Departments of Epidemiology & Biostatistics, and Statistics, Michigan State University, United States of America.

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|May 6, 2015
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Summary
This summary is machine-generated.

Whole-genome regression models are valuable for predicting complex traits. However, genomic heritability estimates may be biased when not all causal variants are typed, requiring caution for population parameter inferences.

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Area of Science:

  • Human genetics
  • Quantitative genetics
  • Statistical genetics

Background:

  • Whole-genome regression methods are widely used for analyzing complex traits and diseases in human genetics.
  • These methods estimate genetic parameters like genetic variance and heritability.
  • Current assumptions in data analysis may conflict with quantitative genetic concepts.

Purpose of the Study:

  • To develop theory for precise definitions of parameters in high-dimensional genomic regressions.
  • To precisely define and analyze genomic heritability within classical quantitative genetics theory.
  • To investigate the relationship between genomic and trait heritability.

Main Methods:

  • Developing theoretical frameworks for genomic regression parameters.
  • Proposing a definition of genomic heritability grounded in quantitative genetics.
  • Utilizing simulations to assess inferential problems and biases.

Main Results:

  • Genomic heritability equals trait heritability only when all causal variants are typed.
  • A large proportion of markers in linkage disequilibrium with quantitative trait loci (QTL) can lead to misspecified likelihood functions.
  • This misspecification can cause finite-sample bias and inconsistency in estimates.

Conclusions:

  • Caution is advised when using marker-based regressions for population parameter inferences, such as genomic heritability.
  • Genomic heritability and trait heritability are not always equivalent.
  • While biases exist, whole-genome regression models remain effective predictive tools.