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

• Published in: PloS one 2016-06, Vol.11 (6), p.e0157236-e0157236
• Main Authors: Chen, Jiafa, Zavala, Cristian, Ortega, Noemi, Petroli, Cesar, Franco, Jorge, Burgueño, Juan, Costich, Denise E, Hearne, Sarah J
• Format: Article
• Language: English
• Subjects: Analysis; Biology and Life Sciences; Breeding; Case reports; Case studies; Conservation; Contamination; Corn; Data processing; Gene frequency; Genetic aspects; Genetic Markers; Genomes; Genomics; Genotyping; Genotyping Techniques - methods; Germplasm; Heterogeneity; Inbreeding; Low cost; Markers; Optimization; Physiological aspects; Plant breeding; Polymorphism, Single Nucleotide; Public sector; Quality Control; Quality management; Regeneration; Research and Analysis Methods; Resource conservation; Sampling; Single nucleotide polymorphisms; Single-nucleotide polymorphism; Studies; Wheat; Zea mays; Zea mays - genetics
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0157236

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.