Cargando…

The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines

Quality control (QC) of germplasm identity and purity is a critical component of breeding and conservation activities. SNP genotyping technologies and increased availability of markers provide the opportunity to employ genotyping as a low-cost and robust component of this QC. In the public sector av...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Jiafa, Zavala, Cristian, Ortega, Noemi, Petroli, Cesar, Franco, Jorge, Burgueño, Juan, Costich, Denise E., Hearne, Sarah J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4900658/
https://www.ncbi.nlm.nih.gov/pubmed/27280295
http://dx.doi.org/10.1371/journal.pone.0157236
_version_ 1782436680564736000
author Chen, Jiafa
Zavala, Cristian
Ortega, Noemi
Petroli, Cesar
Franco, Jorge
Burgueño, Juan
Costich, Denise E.
Hearne, Sarah J.
author_facet Chen, Jiafa
Zavala, Cristian
Ortega, Noemi
Petroli, Cesar
Franco, Jorge
Burgueño, Juan
Costich, Denise E.
Hearne, Sarah J.
author_sort Chen, Jiafa
collection PubMed
description Quality control (QC) of germplasm identity and purity is a critical component of breeding and conservation activities. SNP genotyping technologies and increased availability of markers provide the opportunity to employ genotyping as a low-cost and robust component of this QC. In the public sector available low-cost SNP QC genotyping methods have been developed from a very limited panel of markers of 1,000 to 1,500 markers without broad selection of the most informative SNPs. Selection of optimal SNPs and definition of appropriate germplasm sampling in addition to platform section impact on logistical and resource-use considerations for breeding and conservation applications when mainstreaming QC. In order to address these issues, we evaluated the selection and use of SNPs for QC applications from large DArTSeq data sets generated from CIMMYT maize inbred lines (CMLs). Two QC genotyping strategies were developed, the first is a “rapid QC”, employing a small number of SNPs to identify potential mislabeling of seed packages or plots, the second is a “broad QC”, employing a larger number of SNP, used to identify each germplasm entry and to measure heterogeneity. The optimal marker selection strategies combined the selection of markers with high minor allele frequency, sampling of clustered SNP in proportion to marker cluster distance and selecting markers that maintain a uniform genomic distribution. The rapid and broad QC SNP panels selected using this approach were further validated using blind test assessments of related re-generation samples. The influence of sampling within each line was evaluated. Sampling 192 individuals would result in close to 100% possibility of detecting a 5% contamination in the entry, and approximately a 98% probability to detect a 2% contamination of the line. These results provide a framework for the establishment of QC genotyping. A comparison of financial and time costs for use of these approaches across different platforms is discussed providing a framework for institutions involved in maize conservation and breeding to assess the resource use effectiveness of QC genotyping. Application of these research findings, in combination with existing QC approaches, will ensure the regeneration, distribution and use in breeding of true to type inbred germplasm. These findings also provide an effective approach to optimize SNP selection for QC genotyping in other species.
format Online
Article
Text
id pubmed-4900658
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-49006582016-06-24 The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines Chen, Jiafa Zavala, Cristian Ortega, Noemi Petroli, Cesar Franco, Jorge Burgueño, Juan Costich, Denise E. Hearne, Sarah J. PLoS One Research Article Quality control (QC) of germplasm identity and purity is a critical component of breeding and conservation activities. SNP genotyping technologies and increased availability of markers provide the opportunity to employ genotyping as a low-cost and robust component of this QC. In the public sector available low-cost SNP QC genotyping methods have been developed from a very limited panel of markers of 1,000 to 1,500 markers without broad selection of the most informative SNPs. Selection of optimal SNPs and definition of appropriate germplasm sampling in addition to platform section impact on logistical and resource-use considerations for breeding and conservation applications when mainstreaming QC. In order to address these issues, we evaluated the selection and use of SNPs for QC applications from large DArTSeq data sets generated from CIMMYT maize inbred lines (CMLs). Two QC genotyping strategies were developed, the first is a “rapid QC”, employing a small number of SNPs to identify potential mislabeling of seed packages or plots, the second is a “broad QC”, employing a larger number of SNP, used to identify each germplasm entry and to measure heterogeneity. The optimal marker selection strategies combined the selection of markers with high minor allele frequency, sampling of clustered SNP in proportion to marker cluster distance and selecting markers that maintain a uniform genomic distribution. The rapid and broad QC SNP panels selected using this approach were further validated using blind test assessments of related re-generation samples. The influence of sampling within each line was evaluated. Sampling 192 individuals would result in close to 100% possibility of detecting a 5% contamination in the entry, and approximately a 98% probability to detect a 2% contamination of the line. These results provide a framework for the establishment of QC genotyping. A comparison of financial and time costs for use of these approaches across different platforms is discussed providing a framework for institutions involved in maize conservation and breeding to assess the resource use effectiveness of QC genotyping. Application of these research findings, in combination with existing QC approaches, will ensure the regeneration, distribution and use in breeding of true to type inbred germplasm. These findings also provide an effective approach to optimize SNP selection for QC genotyping in other species. Public Library of Science 2016-06-09 /pmc/articles/PMC4900658/ /pubmed/27280295 http://dx.doi.org/10.1371/journal.pone.0157236 Text en © 2016 Chen et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Chen, Jiafa
Zavala, Cristian
Ortega, Noemi
Petroli, Cesar
Franco, Jorge
Burgueño, Juan
Costich, Denise E.
Hearne, Sarah J.
The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines
title The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines
title_full The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines
title_fullStr The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines
title_full_unstemmed The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines
title_short The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines
title_sort development of quality control genotyping approaches: a case study using elite maize lines
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4900658/
https://www.ncbi.nlm.nih.gov/pubmed/27280295
http://dx.doi.org/10.1371/journal.pone.0157236
work_keys_str_mv AT chenjiafa thedevelopmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT zavalacristian thedevelopmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT orteganoemi thedevelopmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT petrolicesar thedevelopmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT francojorge thedevelopmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT burguenojuan thedevelopmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT costichdenisee thedevelopmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT hearnesarahj thedevelopmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT chenjiafa developmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT zavalacristian developmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT orteganoemi developmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT petrolicesar developmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT francojorge developmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT burguenojuan developmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT costichdenisee developmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines
AT hearnesarahj developmentofqualitycontrolgenotypingapproachesacasestudyusingelitemaizelines