HybridQC: A SNP-Based Quality Control Application for Rapid Hybridity Verification in Diploid Plants

Background/Objectives: Hybridity authentication is an important component of quality assurance and control (QA/QC) in breeding programs. Here, we introduce HybridQC v1.0, a QA/QC software program specially designed for parental purity and hybridity determination. HybridQC rapidly detects molecular m...

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Vydané v:Genes Ročník 15; číslo 10; s. 1252
Hlavní autori: Ongom, Patrick Obia, Ajibade, Yakub Adebare, Mohammed, Saba Baba, Dieng, Ibnou, Fatokun, Christian, Boukar, Ousmane
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Switzerland MDPI AG 01.10.2024
MDPI
Predmet:
Alleles
Breeding
Diploids
Diploidy
Gene polymorphism
Genetic crosses
Genotype
Genotype & phenotype
Germplasm
Heterozygosity
Hybridization, Genetic
Missing data
Plant Breeding - methods
Polymorphism
Polymorphism, Single Nucleotide - genetics
Quality assurance
Quality Control
Single-nucleotide polymorphism
Software
Sorghum
Sorghum - genetics
Sorghum bicolor
Statistical analysis
User interface
Vigna - genetics
Vigna unguiculata
Zea mays
Zea mays - genetics
hybridity determination
marker efficiency
parental purity
software program
quality control
single nucleotide polymorphism
quality assurance
F1 verification
KASP assay
ISSN:2073-4425, 2073-4425
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Abstract Background/Objectives: Hybridity authentication is an important component of quality assurance and control (QA/QC) in breeding programs. Here, we introduce HybridQC v1.0, a QA/QC software program specially designed for parental purity and hybridity determination. HybridQC rapidly detects molecular marker polymorphism between parents of a cross and utilizes only the informative markers for hybridity authentication. Methods: HybridQC is written in Python and designed with a graphical user interface (GUI) compatible with Windows operating systems. We demonstrated the QA/QC analysis workflow and functionality of HybridQC using Kompetitive allele-specific PCR (KASP) SNP genotype data for cowpea (Vigna unguiculata). Its performance was validated in other crop data, including sorghum (Sorghum bicolor) and maize (Zea mays). Results: The application efficiently analyzed low-density SNP data from multiple cowpea bi-parental crosses embedded in a single Microsoft Excel file. HybridQC is optimized for the auto-generation of key summary statistics and visualization patterns for marker polymorphism, parental heterozygosity, non-parental alleles, missing data, and F1 hybridity. An added graphical interface correctly depicted marker efficiency and the proportions of true F1 versus self-fertilized progenies in the data sets used. The output of HybridQC was consistent with the results of manual hybridity discernment in sorghum and maize data sets. Conclusions: This application uses QA/QC SNP markers to rapidly verify true F1 progeny. It eliminates the extensive time often required to manually curate and process QA/QC data. This tool will enhance the optimization efforts in breeding programs, contributing to increased genetic gain.
AbstractList Background/Objectives: Hybridity authentication is an important component of quality assurance and control (QA/QC) in breeding programs. Here, we introduce HybridQC v1.0, a QA/QC software program specially designed for parental purity and hybridity determination. HybridQC rapidly detects molecular marker polymorphism between parents of a cross and utilizes only the informative markers for hybridity authentication. Methods: HybridQC is written in Python and designed with a graphical user interface (GUI) compatible with Windows operating systems. We demonstrated the QA/QC analysis workflow and functionality of HybridQC using Kompetitive allele-specific PCR (KASP) SNP genotype data for cowpea (Vigna unguiculata). Its performance was validated in other crop data, including sorghum (Sorghum bicolor) and maize (Zea mays). Results: The application efficiently analyzed low-density SNP data from multiple cowpea bi-parental crosses embedded in a single Microsoft Excel file. HybridQC is optimized for the auto-generation of key summary statistics and visualization patterns for marker polymorphism, parental heterozygosity, non-parental alleles, missing data, and F1 hybridity. An added graphical interface correctly depicted marker efficiency and the proportions of true F1 versus self-fertilized progenies in the data sets used. The output of HybridQC was consistent with the results of manual hybridity discernment in sorghum and maize data sets. Conclusions: This application uses QA/QC SNP markers to rapidly verify true F1 progeny. It eliminates the extensive time often required to manually curate and process QA/QC data. This tool will enhance the optimization efforts in breeding programs, contributing to increased genetic gain.
: Hybridity authentication is an important component of quality assurance and control (QA/QC) in breeding programs. Here, we introduce HybridQC v1.0, a QA/QC software program specially designed for parental purity and hybridity determination. HybridQC rapidly detects molecular marker polymorphism between parents of a cross and utilizes only the informative markers for hybridity authentication. HybridQC is written in Python and designed with a graphical user interface (GUI) compatible with Windows operating systems. We demonstrated the QA/QC analysis workflow and functionality of HybridQC using Kompetitive allele-specific PCR (KASP) SNP genotype data for cowpea ( ). Its performance was validated in other crop data, including sorghum ( ) and maize ( ). The application efficiently analyzed low-density SNP data from multiple cowpea bi-parental crosses embedded in a single Microsoft Excel file. HybridQC is optimized for the auto-generation of key summary statistics and visualization patterns for marker polymorphism, parental heterozygosity, non-parental alleles, missing data, and F hybridity. An added graphical interface correctly depicted marker efficiency and the proportions of true F versus self-fertilized progenies in the data sets used. The output of HybridQC was consistent with the results of manual hybridity discernment in sorghum and maize data sets. This application uses QA/QC SNP markers to rapidly verify true F progeny. It eliminates the extensive time often required to manually curate and process QA/QC data. This tool will enhance the optimization efforts in breeding programs, contributing to increased genetic gain.
Background/Objectives: Hybridity authentication is an important component of quality assurance and control (QA/QC) in breeding programs. Here, we introduce HybridQC v1.0, a QA/QC software program specially designed for parental purity and hybridity determination. HybridQC rapidly detects molecular marker polymorphism between parents of a cross and utilizes only the informative markers for hybridity authentication. Methods: HybridQC is written in Python and designed with a graphical user interface (GUI) compatible with Windows operating systems. We demonstrated the QA/QC analysis workflow and functionality of HybridQC using Kompetitive allele-specific PCR (KASP) SNP genotype data for cowpea (Vigna unguiculata). Its performance was validated in other crop data, including sorghum (Sorghum bicolor) and maize (Zea mays). Results: The application efficiently analyzed low-density SNP data from multiple cowpea bi-parental crosses embedded in a single Microsoft Excel file. HybridQC is optimized for the auto-generation of key summary statistics and visualization patterns for marker polymorphism, parental heterozygosity, non-parental alleles, missing data, and F[sub.1] hybridity. An added graphical interface correctly depicted marker efficiency and the proportions of true F[sub.1] versus self-fertilized progenies in the data sets used. The output of HybridQC was consistent with the results of manual hybridity discernment in sorghum and maize data sets. Conclusions: This application uses QA/QC SNP markers to rapidly verify true F[sub.1] progeny. It eliminates the extensive time often required to manually curate and process QA/QC data. This tool will enhance the optimization efforts in breeding programs, contributing to increased genetic gain.
Background/Objectives: Hybridity authentication is an important component of quality assurance and control (QA/QC) in breeding programs. Here, we introduce HybridQC v1.0, a QA/QC software program specially designed for parental purity and hybridity determination. HybridQC rapidly detects molecular marker polymorphism between parents of a cross and utilizes only the informative markers for hybridity authentication. Methods: HybridQC is written in Python and designed with a graphical user interface (GUI) compatible with Windows operating systems. We demonstrated the QA/QC analysis workflow and functionality of HybridQC using Kompetitive allele-specific PCR (KASP) SNP genotype data for cowpea (Vigna unguiculata). Its performance was validated in other crop data, including sorghum (Sorghum bicolor) and maize (Zea mays). Results: The application efficiently analyzed low-density SNP data from multiple cowpea bi-parental crosses embedded in a single Microsoft Excel file. HybridQC is optimized for the auto-generation of key summary statistics and visualization patterns for marker polymorphism, parental heterozygosity, non-parental alleles, missing data, and F1 hybridity. An added graphical interface correctly depicted marker efficiency and the proportions of true F1 versus self-fertilized progenies in the data sets used. The output of HybridQC was consistent with the results of manual hybridity discernment in sorghum and maize data sets. Conclusions: This application uses QA/QC SNP markers to rapidly verify true F1 progeny. It eliminates the extensive time often required to manually curate and process QA/QC data. This tool will enhance the optimization efforts in breeding programs, contributing to increased genetic gain.Background/Objectives: Hybridity authentication is an important component of quality assurance and control (QA/QC) in breeding programs. Here, we introduce HybridQC v1.0, a QA/QC software program specially designed for parental purity and hybridity determination. HybridQC rapidly detects molecular marker polymorphism between parents of a cross and utilizes only the informative markers for hybridity authentication. Methods: HybridQC is written in Python and designed with a graphical user interface (GUI) compatible with Windows operating systems. We demonstrated the QA/QC analysis workflow and functionality of HybridQC using Kompetitive allele-specific PCR (KASP) SNP genotype data for cowpea (Vigna unguiculata). Its performance was validated in other crop data, including sorghum (Sorghum bicolor) and maize (Zea mays). Results: The application efficiently analyzed low-density SNP data from multiple cowpea bi-parental crosses embedded in a single Microsoft Excel file. HybridQC is optimized for the auto-generation of key summary statistics and visualization patterns for marker polymorphism, parental heterozygosity, non-parental alleles, missing data, and F1 hybridity. An added graphical interface correctly depicted marker efficiency and the proportions of true F1 versus self-fertilized progenies in the data sets used. The output of HybridQC was consistent with the results of manual hybridity discernment in sorghum and maize data sets. Conclusions: This application uses QA/QC SNP markers to rapidly verify true F1 progeny. It eliminates the extensive time often required to manually curate and process QA/QC data. This tool will enhance the optimization efforts in breeding programs, contributing to increased genetic gain.
Audience Academic
Author Mohammed, Saba Baba
Dieng, Ibnou
Fatokun, Christian
Ajibade, Yakub Adebare
Boukar, Ousmane
Ongom, Patrick Obia
AuthorAffiliation 2 International Institute of Tropical Agriculture (IITA), Ibadan 200001, Nigeria; i.dieng@cgiar.org (I.D.); c.fatokun@cgiar.com (C.F.)
1 International Institute of Tropical Agriculture (IITA), Kano 713103, Nigeria; ajibadeyakubadebare@gmail.com (Y.A.A.); s.mohammed@cgiar.org (S.B.M.); o.boukar@cgiar.org (O.B.)
AuthorAffiliation_xml – name: 1 International Institute of Tropical Agriculture (IITA), Kano 713103, Nigeria; ajibadeyakubadebare@gmail.com (Y.A.A.); s.mohammed@cgiar.org (S.B.M.); o.boukar@cgiar.org (O.B.)
– name: 2 International Institute of Tropical Agriculture (IITA), Ibadan 200001, Nigeria; i.dieng@cgiar.org (I.D.); c.fatokun@cgiar.com (C.F.)
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  givenname: Saba Baba
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  surname: Mohammed
  fullname: Mohammed, Saba Baba
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Issue 10
Keywords hybridity determination
marker efficiency
parental purity
software program
quality control
single nucleotide polymorphism
quality assurance
F1 verification
KASP assay
Language English
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Snippet Background/Objectives: Hybridity authentication is an important component of quality assurance and control (QA/QC) in breeding programs. Here, we introduce...
: Hybridity authentication is an important component of quality assurance and control (QA/QC) in breeding programs. Here, we introduce HybridQC v1.0, a QA/QC...
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SourceType Open Access Repository
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StartPage 1252
SubjectTerms Alleles
Breeding
Diploids
Diploidy
Gene polymorphism
Genetic crosses
Genotype
Genotype & phenotype
Germplasm
Heterozygosity
Hybridization, Genetic
Missing data
Plant Breeding - methods
Polymorphism
Polymorphism, Single Nucleotide - genetics
Quality assurance
Quality Control
Single-nucleotide polymorphism
Software
Sorghum
Sorghum - genetics
Sorghum bicolor
Statistical analysis
User interface
Vigna - genetics
Vigna unguiculata
Zea mays
Zea mays - genetics
Title HybridQC: A SNP-Based Quality Control Application for Rapid Hybridity Verification in Diploid Plants
URI https://www.ncbi.nlm.nih.gov/pubmed/39457376
https://www.proquest.com/docview/3120656585
https://www.proquest.com/docview/3121061421
https://pubmed.ncbi.nlm.nih.gov/PMC11507623
Volume 15
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