Computational protocol: Development of DArT-based PCR markers for selecting drought-tolerant spring barley

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Protocol publication

[…] Two genetic linkage maps for malting and fodder genotypes of Polish spring barley were created using the DArT marker system. QTL regions for physiological parameters associated with the drought response were described in detail in a previous publication (Wójcik-Jagła et al. ) and were used to select DArT markers for conversion. Among the 33 QTLs reported, 11 QTLs with the highest percentage of explained variation (>10 %), high additive effects, and the greatest physiological importance were chosen. Additionally, seven regions significant in the preliminary simple marker regression analysis were selected. Thirty non-redundant clone sequences out of 53 DArT markers selected by these criteria were obtained from the Diversity Arrays network ( 30 DArT clone sequences obtained in the previous step were tested by MISA software to find microsatellite repeats (Thiel et al. ). To identify as many potentially polymorphic regions as possible, the microsatellite defining criteria were restricted to the following (size of motifs/minimal number of repeats): (1/8), (2/5), (3/4), (4/4), (5/3), and (6/2). The maximum distance between imperfect microsatellites was set to 100 bp. Sequences lacking microsatellite motifs were used to identify STS markers by PCR reactions with specially designed primers (Table ). Additionally, for some chromosome regions, 31 SSR markers selected from barley genetic maps constructed with DArT and SSR markers in the GrainGenes database were tested (Table ). The sequences of SSR markers were obtained from the GrainGenes and HarvEST:Barley databases ( and The PCR primers were designed using Primer3 software (v. 0.4.0).To discern original DArTs, a “T” prefix was added to the name of the DArT marker adapted into the PCR system. The markers were assigned to bin locations based on the barley maps (Wenzl et al. ; Aghnoum et al. ; Wójcik-Jagła et al. ; König et al. ) and the data from The physical locations of DArT clones were established with respect to “Morex” (an assembly of whole-genome shotgun sequence from barley) using the IPK Barley BLAST Server ( Polymorphism information content (PIC) values were calculated as in Tyrka et al. (). The functional annotation of sequences was performed using the Blast2GO software (Conesa et al. ). [...] A detailed description of the phenotyping process and its results has been published previously (Rapacz et al. ). In general, the results of phenotyping comprised the stress indices [SI = (d/w) × 100 %, w : parameter value in a well-watered plant, d: parameter value after drought treatment] calculated for the physiological parameters. Drought induced changes in the following parameters: electrolyte leakage from leaf tissues (EL), leaf water content (WC), CO2 net assimilation rate (Pn), transpiration rate (Tr), as well as different parameters of chlorophyll fluorescence describing: (1) the quantum yield of electron transport at PSII (φPSII); (2) the quantum efficiency of energy transfer between PSII antennas and reaction centers (Fv/Fm); (3) the overall performance index of PSII calculated for equal absorption (PI); (4) the flux of the energy absorbed in PSII antennas per leaf cross-section (CS): ABS/CS; (5) the flux of the energy trapped in PSII reaction centers (TRo/CS); (6) the flux of the energy used for electron transport (ETo/CS); (7) the energy dissipated from PSII (DIo/CS); and (8) the maximum number of active PSII reaction centers (RC/CSm). The rate of PSII quantum efficiency related to the quantum efficiency of CO2 assimilation, φPSII/φCO2, was also calculated.The results of genotyping were compared with those of phenotyping using Spearman’s correlation coefficient calculated between the presence of a marker and the SI value for the physiological trait of the linked QTL, after converting the results from allelic into the 0–1 format. Additionally, statistical significance of the difference between drought susceptibility index (DSI) mean values in the plants containing different allelic variants of the marker was tested using the Mann–Whitney U test. In the case of markers characterized by the presence of different sized products, each pairwise comparison was performed. All the statistical analyses were done using STATISTICA 10.0 software (StatSoft, Tulsa, OK, USA). […]

Pipeline specifications

Software tools MISA, Primer3, Blast2GO, Statistica
Databases BB
Applications Miscellaneous, WGS analysis, qPCR
Organisms Hordeum vulgare