SNP Genotyping Data for the Barley Population in "Registration of the S2MET Barley Mapping Population for Multi-Environment Genomewide Selection"
2019-07-25
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2014-09-01
2015-09-01
2015-09-01
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2017-10-01
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Title
SNP Genotyping Data for the Barley Population in "Registration of the S2MET Barley Mapping Population for Multi-Environment Genomewide Selection"
Published Date
2019-07-25
Authors
Author Contact
Smith, Kevin, P
smith376@umn.edu
smith376@umn.edu
Type
Dataset
Abstract
Two barley populations were genotyped for use in studies of genomewide selection: a training population of 183 individuals and a selection candidate population of 1200 individuals.
Description
1383 (1200 + 183) barley individuals were genotyped using genotyping-by-sequencing (GBS). 100 - 150 bp single-end reads were generated from the USDA-ARS Small Grains Genotyping Lab in Fargo, ND. SNPs were called using a custom pipeline (https://github.com/neyhartj/GBarleyS) and were filtered for mapping quality, genotype quality, and read depth (see README). Markers and entries were further processed and filtered on minor allele frequency and missingness using the relevant R script (see README). Missing marker genotypes were imputed using 3 different methods using the relevant R script (see README). Both the unimputed ("discrete") and imputed ("imputed") marker genotypes are available in this repository.
Referenced by
Neyhart, J. L., and K. P. Smith. 2019. Validating Genomewide Predictions of Genetic Variance in a Contemporary Breeding Program. Crop Sci. 59:1062-1072.
https://doi.org/10.2135/cropsci2018.11.0716
Multi-trait Improvement by Predicting Genetic Correlations in Breeding Crosses. (2019). Jeffrey L. Neyhart, Aaron J. Lorenz and Kevin P. Smith G3: GENES, GENOMES, GENETICS.
https://doi.org/10.1534/g3.119.400406
Neyhart, J. L., D. Sweeney, M. Sorrells, C. Kapp, K. D. Kephart, J. Sherman, E. J. Stockinger, S. Fisk, P. Hayes, S. Daba, M. Mohammadi, N. Hughes, L. Lukens, P. G. Barrios, L. Gutiérrez, and K. P. Smith. 2019. Registration of the S2MET Barley Mapping Population for Multi-Environment Genomewide Selection. J. Plant. Reg. 13:270-280.
https://doi.org/10.3198/jpr2018.06.0037crmp
https://doi.org/10.2135/cropsci2018.11.0716
Multi-trait Improvement by Predicting Genetic Correlations in Breeding Crosses. (2019). Jeffrey L. Neyhart, Aaron J. Lorenz and Kevin P. Smith G3: GENES, GENOMES, GENETICS.
https://doi.org/10.1534/g3.119.400406
Neyhart, J. L., D. Sweeney, M. Sorrells, C. Kapp, K. D. Kephart, J. Sherman, E. J. Stockinger, S. Fisk, P. Hayes, S. Daba, M. Mohammadi, N. Hughes, L. Lukens, P. G. Barrios, L. Gutiérrez, and K. P. Smith. 2019. Registration of the S2MET Barley Mapping Population for Multi-Environment Genomewide Selection. J. Plant. Reg. 13:270-280.
https://doi.org/10.3198/jpr2018.06.0037crmp
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Funding information
U.S. Wheat and Barley Scab Initiative
Minnesota Department of Agriculture
Rahr Malting Company
the Brewers Association
American Malting Barley Association
USDA-NIFA Grant #2018-67011-28075
Minnesota Department of Agriculture
Rahr Malting Company
the Brewers Association
American Malting Barley Association
USDA-NIFA Grant #2018-67011-28075
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Suggested citation
Neyhart, Jeffrey L; Smith, Kevin P. (2019). SNP Genotyping Data for the Barley Population in "Registration of the S2MET Barley Mapping Population for Multi-Environment Genomewide Selection". Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/cp4r-0v95.
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Description
Size
README.txt
Description of data
(8.88 KB)
S2_final_imputed_genos_hmp.txt
Imputed marker genotypes
(37.22 MB)
S2_final_discrete_genos_hmp.txt
Unimputed marker genotypes
(19.36 MB)
2row_GBS_final_snps_newpos_renamed.vcf.gz
VCF file for processing and imputation
(313.8 MB)
UMN_S2_pedigree.csv
Data used in R scripts
(279.97 KB)
GBS_marker_info.csv
File used in R scripts
(10.36 MB)
s2_marker_data_imputation_use.R
R script for imputing marker data
(21.61 KB)
s2_marker_data_processing_use.R
R script to filter and process marker data
(20.94 KB)
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