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Association mapping of agronomic and quality traits in USDA pea single-plant collection

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Abstract

Association mapping is an efficient approach for the identification of the molecular basis of agronomic traits in crop plants. For this purpose in pea (Pisum sativum L.), we genotyped and phenotyped individual lines of the single-plant-derived core collection of the USDA pea collection including accessions from 330 landraces and cultivars of Pisum sativum subsp. sativum var. sativum, 28 P. sativum subsp. elatius var. elatius, 16 P. sativum subsp. sativum var. arvense, four P. sativum subsp. elatius var. pumilio, three P. abyssinicum, two P. fulvum, and one P. sativum subsp. transcaucasicum. These 384 accessions were collected or donated from a total of 64 countries. The accessions were genotyped with 256 informative SNPs using a primer extension chemistry and matrix-assisted laser desorption/ionization (MALDI–TOF) mass spectrometry assay. Genetic structure analysis showed that the collection was structured into two main groups, corresponding roughly to the cultivated types/landraces and the more primitive form species and subspecies, with some intermediates. Linkage disequilibrium of pairwise loci and population structure of the collection were analyzed, and an association analysis between SNP genotypes and 25 valuable traits such as disease resistance, seed type/color, flower color, seed low molecular weight carbohydrate concentration, and seed mineral nutrient concentration was performed using a mixed linear model. A total of 71 marker–trait associations were detected as significant with 1–34 markers per trait based on the false discovery rate (FDR < 0.05). This study demonstrates the potential of using association mapping to identify markers for pea breeding.

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Acknowledgments

This project was supported by the USA Dry Pea and Lentil Council. We thank Mr. Hun Huang Ooi for assistance with DNA plate organization and Ms. Sheri McGrew for taking care of the plants in the greenhouse. The Sequenom iPLEX assay was done in the USDA Wheat Genetics, Quality, Physiology, and Disease Research Unit. We thank Dr. Derick Jiwan and Dr. Deven See for their technical support on SNP calling and validation. The contents of this publication do not necessarily reflect the views or policies of the US Department of Agriculture, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government.

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Authors and Affiliations

  1. Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99164, USA

    Peng Cheng

  2. Department of Horticulture, Washington State University, Pullman, WA, 99164, USA

    Yu Ma

  3. Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY, 14850, USA

    William Holdsworth & Michael Mazourek

  4. Department of Pediatrics, USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, 1100 Bates Street, Houston, TX, 77030, USA

    Michael A. Grusak

  5. US Department of Agriculture, Agricultural Research Service, Western Regional Plant Introduction Station, Pullman, WA, 99164, USA

    Clarice J. Coyne & Sam Fuchs

  6. US Department of Agriculture, Agricultural Research Service, Grain Legume Genetics and Physiology Research Unit, Pullman, WA, 99164, USA

    Rebecca J. McGee

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Correspondence to Rebecca J. McGee.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Phenotypic data for each trait of PSP collection (XLSX 83 kb)

Primers used in Sequenom MassArray for SNPs (XLSX 46 kb)

11032_2015_277_MOESM3_ESM.pptx

Plot of mean likelihood L(K) and variance per K value from STRUCTURE (upper left); Evanno plots determine the number of K subgroups (Earl and vonHoldt 2011) (PPTX 69 kb)

11032_2015_277_MOESM4_ESM.pptx

Descriptive statistics for the seed concentration data for mineral nutrients and low molecular weight carbohydrates (PPTX 827 kb)

11032_2015_277_MOESM5_ESM.pptx

Linkage disequilibrium (LD) plot of 203 SNPs with the genetic distance (cM) information. Lower left are linkage disequilibrium P values and upper right are r 2 values (PPTX 81 kb)

11032_2015_277_MOESM6_ESM.pptx

Intra-chromosomal LD (r 2) decay of marker pairs over all chromosomes as a function of genetic distance (cM). The horizontal line indicates the 95th percentile distribution of unlinked r 2 (PPTX 214 kb)

The linkage disequilibrium (LD) overview for the PSP collection calculated using 203 SNPs (DOCX 20 kb)

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Cheng, P., Holdsworth, W., Ma, Y. et al. Association mapping of agronomic and quality traits in USDA pea single-plant collection. Mol Breeding 35, 75 (2015). https://doi.org/10.1007/s11032-015-0277-6

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