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Related Concept Videos

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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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
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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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Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
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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.
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In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
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Discovery of rare variants for complex phenotypes.

Jack A Kosmicki1,2,3,4, Claire L Churchhouse1,2,3, Manuel A Rivas1,2

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Rare variants contribute to complex traits, but detecting them requires larger sample sizes than common variants. Advances in sequencing and large-scale projects are improving our understanding of rare genetic variations.

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Area of Science:

  • Genetics
  • Genomics
  • Complex Trait Genetics

Background:

  • Sequencing technologies enable rare variant analysis in complex traits.
  • Previous studies show rare variants contribute to phenotypic variability.
  • Exome sequencing has had limited success for complex trait gene discovery.

Purpose of the Study:

  • To review considerations for rare variant analysis in complex traits.
  • To introduce topics including power, study design, and statistical approaches.
  • To discuss the role of rare mutations in complex trait etiology.

Main Methods:

  • Review of current literature and large-scale sequencing efforts.
  • Discussion of challenges in rare variant association studies.
  • Exploration of statistical testing approaches for rare variants.

Main Results:

  • Rare variants are significant contributors to complex trait variation.
  • Larger sample sizes are needed for rare variant detection compared to common variants.
  • Large-scale sequencing projects are advancing the study of rare variation.

Conclusions:

  • Rare variant association studies require substantial sample sizes.
  • Ongoing advancements in sequencing and data aggregation are crucial.
  • Future large-scale studies will clarify the role of rare mutations in complex diseases.