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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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A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
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Among all the organelles in an animal cell, only mitochondria have their own independent genomes. Animal mitochondrial DNA is a double-stranded, closed-circular molecule with around 20,000 base pairs. Mitochondrial DNA is unique in that one of its two strands, the heavy, or H, -strand is guanine rich, whereas the complementary strand is cytosine rich and called the light, or L, -strand. Compared to nuclear DNA, mitochondrial DNA has a very low percentage of non-coding regions and is marked by...
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Genetic transfer occurs when genetic information is passed from one organism to another. It occurs via two mechanisms: vertical gene transfer and horizontal gene transfer. Vertical gene transfer occurs when genetic information is transferred from one generation to the next, which happens much more frequently than horizontal gene transfer. Both sexual and asexual reproduction are forms of vertical gene transfer, where one or more organisms pass some or all of their genome onto their progeny.
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Beyond heritability: improving discoverability in imaging genetics.

Chun Chieh Fan1, Olav B Smeland2, Andrew J Schork3

  • 1Center for Multimodal Imaging and Genetics, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA.

Human Molecular Genetics
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Summary
This summary is machine-generated.

Discovering genetic variants for brain structure is challenging. New methods improve genetic discovery in imaging genetics by redefining measures and leveraging genomic data, accelerating identification of brain structure

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Area of Science:

  • Neuroimaging Genetics
  • Genomics
  • Brain Structure

Background:

  • Structural neuroimaging measures are key in imaging genetics, with large projects accumulating nearly 50,000 samples for genome-wide association studies (GWAS).
  • Despite high heritability of brain structure, GWAS have identified limited novel genetic variants.
  • Heritability alone is insufficient for assessing GWAS statistical power; discoverability, dependent on genomic architecture and sample size, is crucial.

Purpose of the Study:

  • To discuss limitations of heritability in guiding GWAS power for neuroimaging traits.
  • To highlight the importance of discoverability for identifying genetic variants.
  • To present novel methods for boosting genetic discovery in imaging genetics.

Main Methods:

  • Redefining imaging measures independent of traditional anatomical conventions to enhance discoverability.
  • Leveraging enrichment priors from genomic annotations.
  • Utilizing independent GWAS of pleiotropic traits to characterize effect size distributions.

Main Results:

  • Novel methods improve discoverability, enabling identification of more genetic effects on brain structure.
  • Enhanced characterization of effect size distributions leads to identification of reliable and replicable genetic loci.
  • Statistical tools incorporating insights into genetic discoverability accelerate the identification of genetic underpinnings of brain structural variation.

Conclusions:

  • Discoverability is a critical factor for genetic discovery in neuroimaging.
  • Innovative approaches in defining imaging measures and integrating genomic data enhance the identification of genetic variants.
  • These advancements promise to accelerate our understanding of the genetic basis of human brain structural variation.