Open Access Highly Accessed Research article

Genome-wide association studies for agronomical traits in a world wide spring barley collection

Raj K Pasam1, Rajiv Sharma1, Marcos Malosetti2, Fred A van Eeuwijk2, Grit Haseneyer13, Benjamin Kilian1 and Andreas Graner1*

Author Affiliations

1 Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Gatersleben, Germany

2 Biometris, Wageningen UR, P.O.Box 100, Wageningen, The Netherlands

3 Plant Breeding, Centre of Life and Food Sciences Weihenstephan, Technical University Munich, Freising, Germany

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BMC Plant Biology 2012, 12:16  doi:10.1186/1471-2229-12-16

Published: 27 January 2012

Additional files

Additional file 1:

Table S1 Information of 957 mapped SNP markers from the IPK customized OPA that were successful in our panel.

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Additional file 2:

Table S2 Details of the 212 accessions used for GWAS. Name of the accession, row type, number of successful markers, Structure group, region of origin and country of origin.

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Additional file 3:

Figure S1 STRUCTURE results using DArT markers. Log probability data (LnP(D)) as function of k (number of clusters) from the STRUCTURE run using 1088 DArT markers with the same association panel. The plateau of the graph at K = 6 indicates the minimum number of subgroups possible in the panel.

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Additional file 4:

Figure S2 Phenotypic distribution of 224 spring barley accessions for the traits heading date (HD), plant height (PHT), thousand grain weight (TGW), starch content (SC) and protein content (CPC).

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Additional file 5:

Table S3 Phenotypic variation among two-rowed and six-rowed groups. Estimation of means, standard deviation (SD), variation (VAR), standard error variation (SEVAR) and coefficient of variance (CV%) for each trait among two-rowed and six-rowed groups.

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Additional file 6:

Table S4 Estimation of means, SD, variation (VAR), standard error variation (SEVAR) and coefficient of variance (CV%) among all six subgroups in the panel.

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Additional file 7:

Figure S3 Comparison of BLUPs and BLUEs for starch content. The graph implies that there is not much difference between the BLUPs and BLUEs in our experiment.

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Additional file 8:

Table S5 Marker polymorphism information of the 918 SNP markers used in GWAS in the panel.

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Additional file 9:

Figure S4 Principal Co-ordinate analysis (PCoA) of the panel based on the first two components derived using 918 SNPs. The primary axis tend to separate into subgroups based on their spike morphology character (blue: six-rowed barley; red: two-rowed barley). Further clustering is based on origin of the accessions.

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Additional file 10:

Figure S5 LD plots for each chromosome in barley. The color of squares illustrate the strength of pairwise r2 values on a black and white scale, where black indicates perfect LD (r2 = 1.00) while white indicates perfect equilibrium (r2 = 0). Failed and monomorphic SNPs as well as SNPs with MAF < 0.05 are not considered.

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Additional file 11:

Figure S6 GWAS whole genome scans for row type using different association models (naive, P, Q, QK, PK and K).

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Additional file 12:

Figure S7 GWAS for all traits. Localization of QTL and candidate genes for the traits row type (RT), heading date (HD), plant height (PHT), thousand grain weight (TGW), starch content (SC) and crude protein content (CPC) on the genetic map with 918 SNP markers.

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