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

Metadata Updated: November 10, 2020

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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Public: This dataset is intended for public access and use. License: Creative Commons CCZero

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Metadata Created Date November 10, 2020
Metadata Updated Date November 10, 2020

Metadata Source

Harvested from USDA JSON

Additional Metadata

Resource Type Dataset
Metadata Created Date November 10, 2020
Metadata Updated Date November 10, 2020
Publisher Agricultural Research Service
Unique Identifier Unknown
Identifier f10719ac-d5a3-4f8b-8115-54cad7a5ba89
Data Last Modified 2019-08-05
Public Access Level public
Bureau Code 005:18
Metadata Context
Schema Version
Catalog Describedby
Program Code 005:040
Source Datajson Identifier True
Source Hash 90fe1eccc02608cf70d40fa8bee965e3c60c8ae0
Source Schema Version 1.1

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