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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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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The Ratio of X Chromosome to Autosomes02:45

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In most organisms, sex is determined by the ratio of X and Y chromosomes. However, in some organisms, such as Drosophila and C.elegans, sex is determined by the ratio of the number of X chromosomes to the number of sets of autosomes. The Y chromosome in Drosophila is active but does not determine sex. It contains genes responsible for the production of sperms in adult flies.  
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Related Experiment Video

Updated: Jun 1, 2025

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A Novel Statistical Method for Unmasking Sex-Specific Genomics Signatures in Complex Traits.

Samaneh Mansouri1,2,3, Mélissa Rochette3, Benoit Labonté2,4

  • 1Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Québec City, Québec, Canada.

Genetic Epidemiology
|January 17, 2025
PubMed
Summary

This study introduces SubsetRV, a novel method to identify sex-specific genetic signals in complex traits and diseases. It accurately detects genetic associations in males, females, or both, advancing our understanding of sex-dimorphic influences.

Keywords:
SKAT statisticsSubsetRVrare variantssex‐specific genetic factorssubset‐based analysis

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Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Genotype-phenotype association studies often miss sex-specific genetic signals influencing complex traits and diseases.
  • Rare genetic variants have significant per-allele effects in disease development.
  • Existing methods for rare variant analysis cannot distinguish the sex-specific origins of detected genetic signals.

Purpose of the Study:

  • To develop a novel statistical methodology, SubsetRV, for identifying genes associated with traits or diseases in specific sex subsets (males, females, or both).
  • To address the limitation of current methods in pinpointing the sex-specific origin of genetic signals.
  • To enable broader applications in multiple traits analysis.

Main Methods:

  • Proposed SubsetRV, a new methodology for gene-based analysis of rare variants.
  • Applied SubsetRV to sex-dimorphic analysis, treating traits as sex-specific subsets.
  • Validated the method through simulation studies and real data analysis.

Main Results:

  • SubsetRV reliably identifies genes associated with specific traits or diseases in males, females, or both.
  • Simulation studies confirmed the accuracy and reliability of SubsetRV.
  • Real data analysis on bipolar disorder and schizophrenia revealed potential sex-specific genetic signals.

Conclusions:

  • SubsetRV is a valuable tool for uncovering sex-specific genetic candidates in complex traits and diseases.
  • The methodology aids in a deeper understanding of disease mechanisms by dissecting sex-dimorphic genetic influences.
  • An R package for SubsetRV is publicly available on GitHub for broader research application.