Literature DB >> 35669703

Genome-wide association study and genomic prediction of white rust resistance in USDA GRIN spinach germplasm.

Ainong Shi1, Gehendra Bhattarai1, Haizheng Xiong1, Carlos A Avila2, Chunda Feng3, Bo Liu3, Vijay Joshi4, Larry Stein4, Beiquan Mou5, Lindsey J du Toit6, James C Correll3.   

Abstract

White rust, caused by Albugo occidentalis, is one of the major yield-limiting diseases of spinach (Spinacia oleracea) in some major commercial production areas, particularly in southern Texas in the United States. The use of host resistance is the most economical and environment-friendly approach to managing white rust in spinach production. The objectives of this study were to conduct a genome-wide associating study (GWAS), to identify single nucleotide polymorphism (SNP) markers associated with white rust resistance in spinach, and to perform genomic prediction (GP) to estimate the prediction accuracy (PA). A GWAS panel of 346 USDA (US Dept. of Agriculture) germplasm accessions was phenotyped for white rust resistance under field conditions and GWAS was performed using 13 235 whole-genome resequencing (WGR) generated SNPs. Nine SNPs, chr2_53 049 132, chr3_58 479 501, chr3_95 114 909, chr4_9 176 069, chr4_17 807 168, chr4_83 938 338, chr4_87 601 768, chr6_1 877 096, and chr6_31 287 118, located on chromosomes 2, 3, 4, and 6 were associated with white rust resistance in this GWAS panel. Four scenarios were tested for PA using Pearson's correlation coefficient (r) between the genomic estimation breeding value (GEBV) and the observed values: (1) different ratios between the training set and testing set (fold), (2) different GP models, (3) different SNP numbers in three different SNP sets, and (4) the use of GWAS-derived significant SNP markers. The results indicated that a 2- to 10-fold difference in the various GP models had similar, although not identical, averaged r values in each SNP set; using GWAS-derived significant SNP markers would increase PA with a high r-value up to 0.84. The SNP markers and the high PA can provide valuable information for breeders to improve spinach by marker-assisted selection (MAS) and genomic selection (GS).
© The Author(s) 2022. Published by Oxford University Press on behalf of Nanjing Agricultural University.

Entities:  

Year:  2022        PMID: 35669703      PMCID: PMC9157682          DOI: 10.1093/hr/uhac069

Source DB:  PubMed          Journal:  Hortic Res        ISSN: 2052-7276            Impact factor:   7.291


  44 in total

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4.  Mixed linear model approach adapted for genome-wide association studies.

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Journal:  Nat Genet       Date:  2010-03-07       Impact factor: 38.330

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Authors:  Hari P Poudel; Millicent D Sanciangco; Shawn M Kaeppler; C Robin Buell; Michael D Casler
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8.  High resolution mapping and candidate gene identification of downy mildew race 16 resistance in spinach.

Authors:  Gehendra Bhattarai; Wei Yang; Ainong Shi; Chunda Feng; Braham Dhillon; James C Correll; Beiquan Mou
Journal:  BMC Genomics       Date:  2021-06-26       Impact factor: 3.969

9.  Genomic Prediction and Selection for Fruit Traits in Winter Squash.

Authors:  Christopher O Hernandez; Lindsay E Wyatt; Michael R Mazourek
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  1 in total

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