Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.4K
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...
12.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Dimensionality reduction of genetic data using contrastive learning.

Genetics·2025
Same author

Genotyping of SNPs in bread wheat at reduced cost from pooled experiments and imputation.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2024
Same author

Observation of a single protein by ultrafast X-ray diffraction.

Light, science & applications·2024
Same author

Achieving improved accuracy for imputation of ancient DNA.

Bioinformatics (Oxford, England)·2022
Same author

An empirical evaluation of genotype imputation of ancient DNA.

G3 (Bethesda, Md.)·2022
Same author

A deep learning framework for characterization of genotype data.

G3 (Bethesda, Md.)·2022

Related Experiment Video

Updated: May 31, 2025

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

38.9K

Using feedback in pooled experiments augmented with imputation for high genotyping accuracy at reduced cost.

Camille Clouard1, Carl Nettelblad1,2

  • 1Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala SE-751 05, Sweden.

G3 (Bethesda, Md.)
|January 23, 2025
PubMed
Summary

Genomic selection (GS) in plant breeding accelerates variety development. A new method combining pooled genotyping and iterative imputation significantly improves genotype accuracy for rare and common variants cost-effectively.

Keywords:
SNP arrayimputationiterative refinementpooling

More Related Videos

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.1K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.2K

Related Experiment Videos

Last Updated: May 31, 2025

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

38.9K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.1K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.2K

Area of Science:

  • Plant breeding
  • Genetics
  • Bioinformatics

Background:

  • Genomic selection (GS) accelerates plant breeding but is limited by high genotyping costs.
  • Dense marker data, especially rare variants, are crucial for reliable GS insights.
  • Existing imputation methods struggle with rare variants, while pooling can miss them.

Purpose of the Study:

  • To develop a cost-effective computational strategy for genotyping single nucleotide polymorphisms (SNPs) using pooled genotyping and population-based imputation.
  • To investigate the addition of iterative coupling to a joint model of pooling and imputation.
  • To enhance genotype accuracy for both low- and high-frequency variants.

Main Methods:

  • Combining pooled genotyping with population-based imputation.
  • Implementing iterative coupling where imputed genotype probabilities feedback to adjust prior probabilities.
  • Utilizing a joint model of pooling and imputation with reference haplotypes.

Main Results:

  • The iterative feedback mechanism improves genotype prediction accuracy significantly.
  • Average concordance increased from 94.5% to 98.4%.
  • High genotype accuracy was achieved for both low- and high-frequency variants at limited computational cost.

Conclusions:

  • Iterative coupling in a joint pooling and imputation model is a powerful strategy for accurate SNP genotyping.
  • This approach offers a cost-effective solution for implementing GS in plant breeding.
  • The method effectively leverages the strengths of both pooling and imputation for improved genomic insights.