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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.
GWAS does not require the identification of the target gene involved in...
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Single Nucleotide Polymorphisms-SNPs01:05

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Comparing Copy Number Variations and SNPs02:26

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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Updated: Jan 11, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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Increased genomic predictive ability in mango using GWAS-preselected variants and fixed-effect SNPs.

Norman Munyengwa1, Melanie J Wilkinson1,2,3,4, Daniel Ortiz-Barrientos2,3

  • 1Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD, Australia.

Frontiers in Plant Science
|November 14, 2025
PubMed
Summary
This summary is machine-generated.

Genomic selection in mangoes shows improved accuracy by incorporating preselected variants from genome-wide association studies (GWAS) and fixed-effect markers. This strategy enhances predictive ability for key fruit traits, boosting breeding efficiency.

Keywords:
GWAS-preselected variantsgenome-wide association studiesgenomic predictionmangopopulation structureprediction accuracywhole-genome sequencing

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Area of Science:

  • Plant Breeding
  • Genomics
  • Quantitative Genetics

Background:

  • Genomic selection (GS) using whole-genome sequencing (WGS) data offers potential for improving breeding value accuracy in fruit trees.
  • Previous studies indicate limited gains with WGS data compared to high-density marker sets, necessitating strategies to enhance predictive power.
  • Incorporating preselected variants from genome-wide association studies (GWAS) is a promising approach to refine GS models.

Purpose of the Study:

  • To investigate the impact of incorporating GWAS-preselected variants and fixed-effect markers into genomic best linear unbiased prediction (GBLUP) models.
  • To assess the improvement in predictive ability for fruit blush color (FBC), average fruit weight (AFW), fruit firmness (FF), and trunk circumference (TC) in mango (Mangifera indica L.).

Main Methods:

  • Utilized WGS data from 225 mango accessions with phenotypic data spanning 1999-2024.
  • Assessed predictive ability using GBLUP models, comparing approaches that ignored or accounted for population structure via fixed principal components.
  • Evaluated the effect of including GWAS-preselected variants and fixed-effect single nucleotide polymorphisms (SNPs) on predictive ability.

Main Results:

  • Accounting for population structure significantly reduced predictive ability, suggesting subpopulations influenced initial estimates.
  • GWAS-preselected variants improved predictive abilities compared to using all WGS data, especially when population structure was considered.
  • Fixed-effect SNPs notably enhanced predictive ability for FBC, and the combination of GWAS-preselected variants and fixed-effect markers yielded the highest improvements for FBC and TC.

Conclusions:

  • Leveraging GWAS-preselected variants and fixed-effect SNPs effectively enhances predictive ability in genomic selection for mangoes.
  • This refined approach holds potential for significantly improving breeding efficiency in fruit trees by increasing accuracy.
  • GWAS identified specific trait-associated SNPs for FBC, AFW, and TC, providing valuable targets for marker-assisted selection.