Computational protocol: Genome-Wide Association Study Reveals a New QTL for Salinity Tolerance in Barley (Hordeum vulgare L.)

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Protocol publication

[…] A total of 408 DArT markers distributed over the whole genome were used for population structure analysis using STRUCTURE software (v2.3.3) (). The number of clusters (K) was set from 2 to 12 and 20 iterations were conducted in an admixture model with a 10,000 burning period and 10,000 MCMC (Markov Chain Monte Carlo). K value was the number of clusters when ΔK achieved maximum value (). Principle component analysis (PCA) was performed using GAPIT R package to visualize the dispersion of the association panel in a graph (). A kinship analysis was conducted using SPAGeDi software (). The kinship matrix measured the genetic similarity between individuals. [...] A GWAS among phenotypic trait (mean value of 2013 and 2014), DArT markers (genotype), population structure and kinship were conducted using TASSEL software (v3.0) (). The Q, K and Q + K methods were used for GWAS. For Q model: y = Xβ + Qν + e; for K model: y = Xβ + Zμ + e; for Q + K model: y = Xβ + Qν + Zμ + e. X is DArT marker matrix, Q and Z represent sub-population membership matrix and kinship matrix, respectively, β and ν are coefficient vectors for DArT marker and sub-population membership, respectively, μ is a vector of random genetic effects μ ~ N (0, 2 K) and e is the random error vector. P < 0.01 (-log10 (P) > 2) was set as the significant threshold in the association study. Manhattan plots were displayed using R software (v2.14.2). For evaluating the fitness and efficiency of different models, quantile–quantile (Q–Q) plots were shown using TASSEL (v3.0). [...] A genetic linkage map for this natural population has been constructed using Diversity Array Technology (DArT) markers. The DArT markers consensus genetic map was provided at The software package MapQTL 6.0 () was also used to detect QTL and confirm the relationship between different markers around each QTL, since the GWAS resulted in several marker-trait associations with many markers locating at close positions to each other. QTL were first analyzed by interval mapping (IM). The marker with highest LOD values at each putative QTL identified using IM was selected as a cofactor and the selected markers were used as genetic background controls in the approximate multiple QTL model (MQM). The population structure (Q-matrix) was used as covariates. A logarithm of the odds (LOD) threshold value of 3.0 was applied to declare the presence of a QTL at 95% significance level. […]

Pipeline specifications

Software tools GAPIT, SPAGeDi, TASSEL, MapQTL
Applications Phylogenetics, WGS analysis, GWAS
Organisms Hordeum vulgare