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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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Related Experiment Video

Updated: Oct 11, 2025

Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis
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A high-resolution consensus linkage map for barley based on GBS-derived genotypes.

Amina Abed1, Ana Badea2, Aaron Beattie3

  • 1Département de Phytologie, Université Laval, Pavillon Charles-Eugène Marchand 1030, Avenue de la Médecine, Quebec City, QC G1V 0A6, Canada.

Genome
|December 6, 2021
PubMed
Summary
This summary is machine-generated.

Researchers developed a high-resolution barley linkage map using genotyping-by-sequencing (GBS) single nucleotide polymorphisms (SNPs). This map offers dense marker coverage, aiding genomic research and marker development.

Keywords:
barleybi-parental populationcarte consensuscarte de liaison génétiqueconsensus mapgenetic positiongenotyping-by-sequencinggénotypage par séquençagelinkage maporgepolymorphisme mononucléotidiquepopulation biparentaleposition génétiquerecombination eventsingle-nucleotide polymorphismévènement de recombinaison

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Area of Science:

  • Plant genetics
  • Genomics
  • Molecular biology

Background:

  • Genotyping-by-sequencing (GBS) is a prevalent method in barley genetic studies.
  • Accurate translation of physical SNP positions to genetic positions is crucial for genetic mapping.

Purpose of the Study:

  • To construct a high-resolution consensus linkage map for barley using GBS-derived single nucleotide polymorphisms (SNPs).

Main Methods:

  • Integrated data from 11 bi-parental populations (3743 progenies).
  • Applied uniform SNP-calling and filtering to identify 50,875 segregating SNPs.
  • Grouped SNPs into 18,580 non-redundant bins.

Main Results:

  • Developed a consensus linkage map spanning 1050.1 cM.
  • Achieved high marker density with an average of 17.7 bins and 48.4 SNPs per cM.
  • Map exhibits minimal gaps, with the largest interval between bins at 3.7 cM and a mean distance of 0.06 cM.

Conclusions:

  • The high-resolution map provides a valuable resource for barley genomic research.
  • Facilitates understanding of recombination landscapes for quantitative trait loci (QTLs) and genome-wide association studies (GWAS).
  • Supports the development of uniform SNP distributions for cost-effective genotyping tools.