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Comparison of array‐ and sequencing‐based markers for genome‐wide association mapping and genomic prediction in spring wheat
Author(s) -
Liu Caiyun,
Sukumaran Sivakumar,
Jarquin Diego,
Crossa Jose,
Dreisigacker Susanne,
Sansaloni Carolina,
Reynolds Matthew
Publication year - 2020
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.1002/csc2.20098
Subject(s) - biology , genome wide association study , single nucleotide polymorphism , genetics , minor allele frequency , genotyping , pedigree chart , genetic association , genetic diversity , population , association mapping , allele frequency , computational biology , allele , genotype , gene , medicine , environmental health
Notwithstanding the rapid development of high‐throughput genotyping platforms in recent years, several plant research programs find themselves in a dilemma of which marker system to use while conducting genome‐wide association studies (GWAS) and genomic selection. To gain insight into this, we genotyped an elite spring wheat ( Triticum aestivum L.) association mapping initiative (WAMI, 287 lines) panel with various array‐based platforms—(i) Diversity Arrays Technology (DArT), (ii) Illumina Infinium BeadChip wheat 9K iSelect (I9K), and (iii) wheat 90K iSelect (I90K)—and sequencing‐based platform DArTseq. The raw markers refined using a common set of protocols after the bioinformatics analysis were compared by performing a series of genetic analyses: estimates of genetic diversity through nucleotide diversity (π), population structure and familial relatedness, marker‐trait associations (MTAs), and genomic prediction. Results indicated that genetic data from DArTseq consisted of a high proportion of rare allele markers (1% < minor allele frequency < 5%). The nucleotide diversity statistic (π) was higher for the array‐based single nucleotide polymorphisms (SNPs) than sequencing‐based SNPs. The I9K detected population structure caused by the variety ‘Kauz’ and grouped the population into two subgroups, whereas I90K, DArT, and DArTseq detected five subgroups driven by key pedigrees. The I90K with the highest marker density identified a high number of significant MTAs. Genomic prediction accuracy varied among traits; DArTseq and I90K produced similar prediction accuracies. Among the marker platforms compared, I90K was the best genotyping platform for GWAS, and DArTseq—given the low cost per SNP—was the best platform for genomic prediction in spring wheat.