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Related Concept Videos

Inheritance01:25

Inheritance

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Gregor Mendel's pioneering work on the principles of inheritance fundamentally transformed our understanding of how traits are transmitted from generation to generation. His experiments with pea plants laid the groundwork for the discovery of genes, discrete units within organisms that control heredity.
Each gene exists in pairs, and the combination of these genes from both parents forms an individual's genotype. This genotype is a blueprint of potential traits. Examples of genotype...
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When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
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Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
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An Effective Method to Identify Heritable Components from Multivariate Phenotypes.

Jiangwen Sun1, Henry R Kranzler2, Jinbo Bi1

  • 1Department of Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, United States of America.

Plos One
|December 15, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to identify highly heritable traits for genetic studies by combining multiple indicators. This approach improves the discovery of genetic associations for complex diseases.

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Area of Science:

  • Genetics
  • Biostatistics
  • Quantitative Trait Analysis

Background:

  • Multivariate phenotypes, crucial in genetic association studies, are often analyzed using low-level traits.
  • Current methods for phenotype refinement or heritable component analysis have limitations, including inability to use general pedigrees, inaccurate covariance matrix estimation, and difficulty excluding covariates.
  • Identifying highly heritable components of multivariate phenotypes is key to maximizing the power of genetic association studies.

Purpose of the Study:

  • To develop a novel approach for identifying and maximizing the heritability of combined traits from multivariate phenotypes.
  • To overcome the limitations of existing methods in handling general pedigrees, estimating covariance matrices, and accounting for fixed effects of covariates.
  • To improve the discovery of genetic associations by refining phenotypes for heritability.

Main Methods:

  • Proposed a method to directly search for a combination of low-level traits that maximizes heritability.
  • Formulated a quadratic optimization problem by decomposing the traditional maximum likelihood method for heritability estimation.
  • Developed an approach to generate linearly combined traits corrected for fixed effects of covariates like age, sex, and race.

Main Results:

  • The proposed approach efficiently derived traits with higher heritability compared to existing methods.
  • Demonstrated effectiveness through simulations and a case study on cocaine dependence.
  • Identified genetic markers associated with the derived cocaine-use trait, which were successfully replicated in an independent sample.

Conclusions:

  • The novel method effectively identifies highly heritable combined traits from multivariate phenotypes, enhancing genetic association studies.
  • The approach is computationally efficient and accounts for important covariates, offering advantages over existing techniques.
  • The successful replication of genetic markers underscores the utility and potential of this method in genetic research and disease diagnosis.