High-quality, genome-wide SNP genotypic data for pedigreed germplasm of the diploid outbreeding species apple, peach, and sweet cherry through a common workflow

Publication Overview
TitleHigh-quality, genome-wide SNP genotypic data for pedigreed germplasm of the diploid outbreeding species apple, peach, and sweet cherry through a common workflow
AuthorsVanderzande S, Howard NP, Cai L, Da Silva Linge C, Antanaviciute L, Bink MCAM, Kruisselbrink JW, Bassil N, Gasic K, Iezzoni A, Van de Weg E, Peace C
TypeJournal Article
Journal NamePloS one
Volume14
Issue6
Year2019
Page(s)e0210928
CitationVanderzande S, Howard NP, Cai L, Da Silva Linge C, Antanaviciute L, Bink MCAM, Kruisselbrink JW, Bassil N, Gasic K, Iezzoni A, Van de Weg E, Peace C. High-quality, genome-wide SNP genotypic data for pedigreed germplasm of the diploid outbreeding species apple, peach, and sweet cherry through a common workflow. PloS one. 2019; 14(6):e0210928.

Abstract

High-quality genotypic data is a requirement for many genetic analyses. For any crop, errors in genotype calls, phasing of markers, linkage maps, pedigree records, and unnoticed variation in ploidy levels can lead to spurious marker-locus-trait associations and incorrect origin assignment of alleles to individuals. High-throughput genotyping requires automated scoring, as manual inspection of thousands of scored loci is too time-consuming. However, automated SNP scoring can result in errors that should be corrected to ensure recorded genotypic data are accurate and thereby ensure confidence in downstream genetic analyses. To enable quick identification of errors in a large genotypic data set, we have developed a comprehensive workflow. This multiple-step workflow is based on inheritance principles and on removal of markers and individuals that do not follow these principles, as demonstrated here for apple, peach, and sweet cherry. Genotypic data was obtained on pedigreed germplasm using 6-9K SNP arrays for each crop and a subset of well-performing SNPs was created using ASSIsT. Use of correct (and corrected) pedigree records readily identified violations of simple inheritance principles in the genotypic data, streamlined with FlexQTL software. Retained SNPs were grouped into haploblocks to increase the information content of single alleles and reduce computational power needed in downstream genetic analyses. Haploblock borders were defined by recombination locations detected in ancestral generations of cultivars and selections. Another round of inheritance-checking was conducted, for haploblock alleles (i.e., haplotypes). High-quality genotypic data sets were created using this workflow for pedigreed collections representing the U.S. breeding germplasm of apple, peach, and sweet cherry evaluated within the RosBREED project. These data sets contain 3855, 4005, and 1617 SNPs spread over 932, 103, and 196 haploblocks in apple, peach, and sweet cherry, respectively. The highly curated phased SNP and haplotype data sets, as well as the raw iScan data, of germplasm in the apple, peach, and sweet cherry Crop Reference Sets is available through the Genome Database for Rosaceae.

Projects
This publication contains information about 6 projects:
Project NameDescription
RosBREED_Peach_CRS_Haplotype_2020
RosBREED_Apple_CRS_Haplotype_2020
RosBREED_Sweet_Cherry_CRS_Haplotype_2020
RosBREED_Sweet_Cherry_CRS_SNP_Genotype_2020RosBREED_Sweet_Cherry_CRS_SNP_Genotype_2020
RosBREED_Apple_CRS_SNP_Genotype_2020RosBREED Apple CRS SNP Genotype 2020
RosBREED_Peach_CRS_SNP_Genotype_2020RosBREED_Peach_CRS_SNP_Genotype_2020
Features
This publication contains information about 1,295 features:
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Pages

Featuremaps
This publication contains information about 3 maps:
Map Name
Sweet Cherry-RosBREED-1.6K-2019
Peach-RosBREED-4K-2019
Apple-RosBREED-3.9K-2019
Cross References
This publication is also available in the following databases:
DatabaseAccession
PMID: PubMedPMID:31246947