Moreover, the GGE biplot provides greater insight, as it illustrates the relationship between the genotype and its GE interaction [8]. However, the GGE biplot results need to be validated with the original data. According to the original data, genotypes G4 and G6 had respectively the highest and lowest mean yield performances across environments, an inference supported graphically by fitting the GGE model to the original data (Fig. 4 and Table 1), suggesting that the GGE biplot results are in agreement with the original yield data. These results are in accord Trichostatin A in vivo with those of other studies [16] and [17] that found agreement between GGE biplot results and the

original yield data. Phenotypic yield stability is a trait of special interest for plant breeders and farmers. This trait can be quantified if genotypes are evaluated in different environments [30]. No correlation was found between yield ranks and stability ranks that were based on measuring GE interaction, including AMMI distance in the AMMI model; stability index in the GGE biplot; S2di Staurosporine in the JRA; and σ2 in the YSi statistic, indicating that these stability indices describe static stability and accordingly could be used if selection is to be based primarily on stability. This conclusion is in agreement with other reports on cereal crops for which stability indices based on measuring GE effects are not correlated with mean yield in bread

wheat, durum wheat and barley [31]. It is also supported by other reports

[32], [33], [34], [35] and [36]. Helms [32] found that the correlations of oat yield with σ2 and S2di were poor. Jalaluddin and Harrison [33] reported no correlation of wheat grain yield with σ2 or S2di. Sneller et al. [35] also found no relationship of soybean yield with the statistics AMMI, σ2, and S2di. Many statistical methods have been developed to analyze data from MET to gain a better understanding and interpretation of observed GE interaction patterns, with the aim of identifying outstanding new cultivars with high stability in crop breeding programs. A worthwhile discussion of many of these methods and their efficiency in identifying superior click here genotypes in MET data can be found in reviews [10], [11], [12], [13], [16], [17] and [18]. Fan et al. [14] and Mohammadi et al. [15] reported high rank correlations between GGE and YSi and concluded that YSi should be useful in selecting superior genotypes in the absence of GGE biplot software. Baxevanos et al. [37] also reported a high correlation between YSi and GGE distance. Goyal et al. [17] reported some agreement between JRA and GGE biplot methods in identifying stable genotypes with high yield performance. According to Goyal et al. [17], S2di and GGE biplot models were not in general agreement in identifying high-yielding and stable genotypes, a conclusion differing from that of Alwala et al. [16].

‘Permeability’ offers a way to conceptualise the impact of these barriers [17]. Highly permeable services require less work and fewer resources from patients who access them – for example, EDs in the UK which are open at all times. A service that seems accessible may in fact be impermeable to particular patient groups [19]. For example, despite general practices being locally available, with designated systems for urgent access, patients in our study described that they were, in fact, impermeable because of

factors such as receptionists’ gate-keeping, and travel cost or mobility problems. In our study, the combination of high permeability and technological expertise led INCB024360 most patients to choose the hospital ED in times of perceived urgent need. In seeking to reduce EC use, healthcare policy this website defines patients as in need of education to use services effectively, or suggests the need for reorganisation of healthcare systems to reduce use of costly emergency care services, especially the ED [2], [7] and [23]. This ‘deficit’ model also dominates previous research investigating EC use, with research focusing on characteristics of

the patient [3], [24], [25] and [26] or the healthcare system [11], [27] and [28] that increase EC use. In contrast, this qualitative study demonstrates that patients understood the array of EC services available and were discriminating in their use of them, influenced primarily by previous experiences of services which recursively shaped their future healthcare choices. It contributes to a growing body of research which emphasises the social processes of help-seeking, and the expertise

patients bring to decision-making around healthcare use [19], [21], [29] and [30]. Our participant sample was large and heterogeneous with respect to age, gender, level of healthcare use (routine care Amino acid and EC) and types of LTCs. We also probed in-depth about instances when they used EC and instances when they did not use EC, and prompted participants to reflect on their decision-making processes about what healthcare options to use and when to use them. This study has several limitations. First, it is possible that patients recounted previous use of EC in what they believed to be publicly defensible ways [31]. The use of serial qualitative interviews [32] examining patients’ healthcare use over time, might enable access to more private accounts, whereby patient’s decision-making can be discussed more openly with a familiar researcher. This approach would enable further insights into the establishment of patterns of healthcare use and how these patterns might be changed. Second, the study was limited to one geographical region, which may limit the transferability of the specific findings to other settings.

Genes associated with the FAK signaling pathway (involved in cell cycle, proliferation and migration) were mostly down-regulated or unaltered at various concentrations (including Fak/Ptk2; data not shown). Functional enrichment analysis of rat specific expression was compromised by the small number of differentially expressed orthologs (249) but did identify intrinsic prothrombin activation (mostly down-regulated) as enriched. Overall, Enzalutamide SDD elicited more dose-dependent differential expression in mice (± 2-fold at 520 mg/L SDD and P1(t) > 0.999) than rats ( Table 3).

Although median EC50s were comparable, comparing EC50 distributions of overlapping orthologous genes identified species-specific differences

for some over-represented pathways (Supplementary  Fig. S7). For example, rat duodenal orthologs had a lower median (~ 10-fold) and EC50 range for Translation/Protein Biosynthesis, Cell Cycle and Oxidoreductase, while Inflammatory Response showed comparable median EC50s between the species at day 8 (Supplementary  Fig. S7A). Differences in median EC50s were also identified for over-represented functions associated with Ribosome (mouse 23.0 vs. rat 52.6 mg/L), Translation (mouse 26.8 vs. rat 46.0 mg/L), Cell cycle (mouse 36.8 vs. rat 4.5 mg/L SDD) and Nucleoside binding (mouse 52.5 vs. rat 6.1 mg/L SDD). However, other over-represented MK-8776 manufacturer functions such as Oxidoreductase, Immune response, Carbohydrate binding, Apoptosis, and Proteolysis exhibited comparable median EC50s between the species at day 91 (Supplementary  Fig. S7B). EC50 distributions also exhibited different ranges (12–361 mg/L for Oxidoreductase in mouse duodenum at day 8 compared to 33–54 mg/L range for Proteolysis in rat duodenum at 91 days). Therefore, assessing the effect of SDD on a pathway based on a median ADP ribosylation factor EC50 is limited by a lack of information regarding the critical regulatory reactions that dictate

sensitivity since regulation can also be post-translational, and may not be directly reflected by differential gene expression. Total chromium concentrations, including the most abundant trivalent and hexavalent chromium species, were measured in rodent small intestine at 91 days (Thompson et al., 2011b and Thompson et al., 2012). Full length duodenum was measured for total Cr tissue determination, whereas full length duodenal epithelial scrapings (mucosa only) were used for gene expression analyses in this and the previous study (Kopec et al., 2012).1 At similar duodenal tissue concentrations, a comparable number of genes were differentially expressed in both species. However, at ≥ 170 mg/L SDD mouse Cr levels were almost double rat levels (42–61 μg/g compared to 26–32 μg/g), consistent with the ~ 2-fold increase in the number of differentially expressed genes (Fig. 10A).

Toxin

encoding DNA was amplified in the first PCR step (E-PCR1) using gene-specific primers listed in Table 1 (PCR-conditions: 10× Fermentas PCR-buffer, dNTPs 0.2 mM PD-1/PD-L1 inhibitor cancer each, forward and reverse primer 0.5 μM each, 0.05 U/μl Taq DNA polymerase, 2 ng DNA, ad MilliQ H2O to a final volume of 50 μl. Initial denaturation at 95 °C for 10 min, denaturation at 94 °C for 30 s, primer annealing at 54 °C for 30 s, primer extension at 72 °C for 45 s, final extension at 72 °C for 5 min; number of cycles: 30) ( Table 2). 100 ng PCR product from the first PCR step was directly applied to the second PCR amplification (E-PCR2) procedure. In E-PCR2 adapter primers were used to add tag-encoding sequences and regulatory sequences at the 5′- and 3′-end of the final PCR-product for cell-free expression (Suppl. Table S1). Amplification was performed according to the manufacturers recommendations (EasyXpress Linear Template Kit PLUS, Qiagen, Hilden, Germany). E-PCR2 was performed in a final volume of 25 μl (PCR-conditions: 5 μl 5× High Fidelity PCR Selleckchem S3I201 buffer, 2.5 μl adapter primer each, High Fidelity DNA Polymerase 0.05 U/μl, initial denaturation at 95 °C for 5 min, denaturation at 94 °C for 60 s, primer annealing at 50 °C for 60 s, primer extension at 72 °C for

45 s, final extension at 72 °C for 10 min; number of cycles: 30). All E-PCR2 products were analyzed by agarose (1%) gel electrophoresis to determine quality and concentration by comparison with a known DNA marker. A 9 μl aliquot of the individual linear E-PCR2 products was directly used in the cell-free prokaryotic system without any further purification. Genomic DNA extraction from V. parahaemolyticus Mephenoxalone O3:K6 strain was performed with the RTP Bacteria DNA Kit from Stratec Molecular, Berlin, Germany. Primers used for the amplification

of the tdh2 gene for the construction of an E. coli recombinant plasmid were VparaF (5′-CAA AGC CTC ATA GAG TTG TAA G-3′) and VparaR (5′-GAA GCG AAT AAA TAG CGT G-3′) amplifying an 972 bp fragment of the genomic DNA of the O3:K6 strain PMA1.6 containing the complete coding sequence of the tdh2 gene ( Suppl. Fig. S3). PCR reaction was performed with DreamTaqTM DNA Polymerase (Fermentas, St. Leon-Rot, Germany) according to the manufacturers recommendations. The PCR product was inserted into the multiple cloning site of the vector pJET2 (Fermentas, St. Leon-Rot, Germany). Finally, the plasmid pJET2-TDH2 was introduced into E. coli DH5α. Sequencing of plasmids and PCR products was carried out by QIAGEN sequencing services (Hilden, Germany). The obtained sequences were analyzed using the Lasergene program “SeqMan” (DNASTAR, Inc., Madison, USA). Sequence translations were performed using the program Accelrys (DS-) gene (Accelrys Inc., San Diego, USA).

Synthetic peptides containing the sequence RKKH of jararhagin catalytic domain have been shown to bind to the I domain of the α2 subunit (Ivaska et al., 1999) inducing conformational changes

(Nymalm et al., 2004) or competing (Lambert et al., Selleck SB431542 2008) to the binding of the integrin to collagen. In spite of that, most of the described adhesive motifs are present in disintegrin-like and cysteine-rich domains, called adhesive domains (Baldo et al., 2010; Kamiguti et al., 2003, 1996a; Serrano et al., 2006). Jararhagin-C, comprised only of jararhagin disintegrin-like and cysteine-rich domains, inhibits collagen-induced platelet aggregation (Moura-da-Silva et al., 1999; Usami et al., 1994), induces leukocyte rolling and release of cytokines (Clissa et al., 2006) and binds to basement membrane collagens in venules and capillary vessels within hemorrhagic lesion (Baldo et al., 2010). Binding motifs have been characterized within disintegrin-like and cysteine-rich domains of jararhagin-C. Peptides based on the disintegrin-like region (De-Luca et al., 1995; Kamiguti et al., 1997b) or cysteine-rich domains (Kamiguti et al., 2003) have been shown

to inhibit collagen-induced platelet aggregation. The mechanism involved in inhibition of platelet aggregation probably includes jararhagin binding to α2β1 integrin collagen receptor since it has been already shown the toxin binding to A1 domain of vWF through a motif enclosed in jararhagin cysteine-rich domain (Serrano et al., 2006). Moreover, SVMPs also obstruct the interaction between platelets and collagen by binding mTOR target to collagen fibers (Tanjoni et al., 2003a; Zhou et al., 1996) using a conformational motif located in the disintegrin-like domain (Moura-da-Silva et al., 2008) resulting in the inhibition of collagen-induced platelet functions. Taken together, these observations

indicate that jararhagin, as other SVMPs, displays multiple mechanisms, related to different structural motifs to reach its effect on platelet inhibition. Although the structure/function Verteporfin research buy relationships are essential to enlighten the molecular mechanisms resulting in the action of a toxin, the complexity of the 3D structure of jararhagin may be a limiting factor and bring about some concerns on the experiments described above. Jararhagin-C contains 28 cysteines that may be arranged randomly in disulfide bridges in recombinant proteins or fragments when folding occurs in heterologous systems. Moreover, synthetic peptides used in most experiments described above were designed according to the primary structure, assuming that residues flanked by cysteines are in independent loops. The importance of conformation-dependent motifs was confirmed when the first crystal structure of P-III SVMPs was published (Takeda et al., 2006).

The LAP ELISA measured Latent TGF-β1 without preceding acidification of human samples and did not cross-react with LAP2 or − 3. No cross-reactivity of the LAP ELISA with Latent TGF-β in bovine serum was found making the ELISA suitable also for human cell supernatants containing bovine serum. BALB/c mice were immunized subcutaneously with 10 μg recombinant human (rh) Latent TGF-β1 (R&D Systems, Abingdon, UK) in 50 μl phosphate-buffered saline (PBS) and 50 μl Freund’s complete

adjuvant (Sigma-Aldrich, St. Louis, MO, USA). Mice were boosted using Freund’s incomplete adjuvant week 4 and 7 (Sigma). At week 27, 10 μg antigen in PBS was given intraperitoneally and 3 days later spleen cells were fused with Sp2/0 cells as described (elGhazali et al., 1993). Positive hybridomas selleck identified by indirect ELISA were subcloned Torin 1 cell line and cultured. MAbs were purified and biotinylated as described (Zuber et al., 2005). Mice were housed and handled at the Karolinska Institute, Solna, Sweden, according to the guidelines of the Swedish Ethical Committee for Animal Protection. Maxisorp 96-well plates (Nunc, Roskilde, Denmark) were

coated for 16 h at 4 °C with 2 μg/ml of rh LAP1, Latent TGF-β1 or TGF-β1 (R&D Systems) in 100 μl PBS. Other assay steps were at room temperature (RT), using 100 μl/well. Five washes using PBS with 0.1% Tween 20 were made between assay steps. After coating, wells were blocked for 1 h with incubation aminophylline buffer (PBS with 0.05% Tween 20 and 0.1% bovine serum albumin). Hybridoma supernatants were diluted in incubation buffer and incubated 2 h. Next, goat-anti-mouse IgG alkaline phosphatase conjugate (Mabtech, Nacka Strand, Sweden) was added and incubated for 1 h, followed by development with para-nitrophenyl phosphate (Sigma) and absorbance measurement (405 nm) by an ELISA reader (Labsystems, Helsinki, Finland). In the LAP ELISA, mAb MT593 (IgG1) was coated at 2 μg/ml and wells were blocked as above. Volumes and temperature for all assay steps and washes in between

were as above. Human plasma was diluted in an ELISA diluent (Mabtech) preventing potential interference by heterophilic antibodies in the samples (Bolstad et al., 2011). Also rh LAP1, Latent TGF-β1 and TGF-β1 and other samples were diluted in ELISA diluent. ELISA diluent was added to acidified samples after the acid treatment. After sample incubation for 2 h, mAb MT517-biotin (IgG1) at 1 μg/ml in ELISA diluent was incubated 1 h followed by streptavidin-horse radish peroxidase conjugate (SA-HRP; Mabtech) in incubation buffer for 1 h. The assay was developed with 3,3′,5,5′-tetramethylbenzidine substrate (Mabtech) and stopped with 1 M H2SO4 followed by absorbance measurement (450 nm). The same protocol was used for TGF-β1 ELISA (Human TGF-β1 DuoSet kit specific for TGF-β1; R&D Systems). Sample levels were determined against standards using rhLAP1 in the LAP ELISA and rhTGF-β1 in the TGF-β1 ELISA.

Nevertheless, most particle doses were outright cytotoxic after 24 h exposure of the cells (Fig. 4B). The PM2.5 material VERP, and the EHC-93sol fraction, were not cytotoxic by XTT reduction assay at any dose tested after 2, 3, and 7 h exposure, and remained marginally

cytotoxic CH5424802 solubility dmso after 24 h exposure (i.e. >80% viability). Respiratory burst effects (induction or inhibition) of particles as well as their effects on cytotoxicity were summarized as relative potencies (β, Table 2). The potency of the particles for respiratory burst (βi) was not correlated (r = 0.101, p = 0.756, Pearson correlation) to cytotoxic potency at 2 h after particle exposure (βv2). Nevertheless, it is conceivable that for particles with high cytotoxicity (e.g. SRM-1648, copper II oxide), the measurements of respiratory bursts would be biased by the low cell viability. Therefore, an unbiased potency estimate (βi-v2 = βi − βv2) was calculated. Most of the inhibitory effect of copper II oxide on the measured selleck inhibitor respiratory burst appeared to be explained by the low cell viability (βi-v2 ≈ 0). In contrast, the inhibitory effects of iron III oxide and iron II/III oxide were not explained by a decrease of cell viability (βi-v2 ≈ −0.16 and ≈−0.06, respectively).

The viability of the cells at 2, 3, 7 and 24 h was highly correlated across

the different particle preparations (r > 0.9, p < 0.0002, Pearson) (data not shown). While the stimulants by themselves caused an induction of respiratory burst that was several fold higher CYTH4 than that resulting from the macrophage response to particles (Fig. 2), exposure of the cells to particles prior to stimulation effectively abrogated the stimulant-induced respiratory burst (Fig. 5). The inhibition of the stimulant-induced respiratory burst was seen across all the stimulants tested for most particle doses. This was particularly evident in cells induced by Zymosan (Fig. 5B). Exceptions to this general inhibition response included PMA stimulation in cells exposed to EHC-93sol, TiO2, or SiO2 ( Fig 5A) and a number of particles where the lowest dose did not produce reductions in respiratory burst, such as EHC-93tot, EHC-93insol in PMA-treated cells ( Fig 5A) and EHC-93tot and TiO2 in LPS/IFN-γ-treated cells ( Fig. 5C). In fact, SiO2 was particularly potent in enhancing PMA- ( Fig 5A) and LPS/IFN-γ- ( Fig 5C) induced effects at all doses tested (dose within particle, p < 0.05) while TiO2 and EHC-93sol showed increases at some doses (dose within particle, p < 0.05), but the effects were marginal once adjusted for cell viability ( Table 3) (TiO2, βi-v2 = −0.007 and EHC-93sol, βi-v2 = 0.024).

Moreover, in this study flow assessments were performed at rest and not during deep inspiration [17]. The documentation of a condition near to the “blocked” flow of the criterion 4 is provided in another pathological conditions, transient global amnesia, as a segmental IJV Selleckchem BMN673 absence of flow with a reversed flow direction in IJV branches [12] and [13]. In Fig. 4, an

example of this condition is shown in a patient with transient global amnesia. It is notable that the majority of so-called blocks are strictly positional conditions, often reversed by the ipsi- or contralateral tilting of the neck. For this reason in the present protocol, special attention was paid for avoiding to define a “blocked” flow in IJV if this condition was reversed by a minimal neck rotation. It is also interesting to note that the situation described in Fig. 2 may gain two points, if the absence of flow is present in supine and upright positions, 1 for the criterion 3 and 1 for the criterion 4. A global hemodynamics of the venous system rather than single segment evaluation is the aim; therefore a useful and validated

tool is the calculation of the arterial blood flow and venous blood flow, as used in literature for distinguishing the cerebral drainage pattern in single subjects, because of ABT-199 price the wide variability of the contribution of jugular, vertebral routes of both sides and extrajugular–extravertebral routes. For this protocol the blood flow is calculated in both supine and standing position for IJV and VV for the outflow and for ICA and VA for the inflow (only in the supine position), by applying the formula BF = CSA × TAV [4], [16] and [17]. The definition of this criterion is that CSA of IJV in upright position is larger than the one in supine position, being the normal condition the

opposite one. Some authors questioned about a mistake for this criterion [4] and [7] and anyway a difference between right and left IJV in supine and upright position has been described in patients with transient global amnesia, because Carnitine palmitoyltransferase II of the compression of the left brachiocephalic vein in the thoracic outlet [11]. This criterion has been proposed by Zamboni et al. [1] and [2] as a marker of the loss of venous compliance. In this protocol, considering the doubts expressed from other authors [4] and [7] also the deviation from the normal response to breath, with an increasing CSA during the inspirium phase and a decreasing CSA during the expirium phase, will be signaled, in order to better understand the global hemodynamic response.

The two compounds are freely soluble in cell media to a concentration of 500 μM, if they are first dissolved in DMSO. Thus, when determining the GARD input concentration, 500 μM will be selleck the high end of the titration range. Cell stimulations were performed as described, and harvested cells were stained with PI (Fig. 2A). The relative viability of cells stimulated with 2-nitro-1,4-phenylendiamine decreases with increasing stimuli concentration. The Rv90 value for this compound is identified at a concentration of 300 μM. In contrast, methyl salicylate does not have any cytotoxic effect on MUTZ-3, as the relative viability

remains unchanged with increasing stimuli concentration. Thus, the GARD input concentrations for 2-nitro-1,4-phenylendiamine and methyl salicylate are 300 and 500 μM, respectively. Once the GARD input concentration for all samples to be assayed are established, cell stimulations for 24 h are repeated. Cells are harvested, RNA is isolated, cDNA is prepared and arrays are hybridized as described. Both stimulations are performed in triplicate, independent experiments. Thereafter, the array data from the triplicate stimulations are normalized,

together with available training data, with the RMA algorithm, In this case, the training data refer to the remaining 36 stimulations and vehicle controls used for the establishment of the GARD Prediction Signature (Johansson et al., 2011), a total ERK inhibitor libraries of 131 arrays. At this point, the training data is used for training an SVM model. The model is then used to classify the test data, i.e. 2-nitro-1,4-phenylindiamine and methyl salicylate, as either sensitizer or non-sensitizer (Fig. 2B). The

obtained decision values for this experiment DCLK1 are presented in Table 1. The reproducibility of GARD was determined by assessing the correlation between the triplicate samples of each of the 38 reference chemicals used for assay development. RNA from these triplicate samples were collected at different days and on different batches of cells. Thus, biological variations in terms of cell cycle and growth rate are integrated in the assessment of reproducibility, as well as technical variation during RNA isolation, array hybridization and variation between array batches. The variation in raw signal was assessed by studying Pearson’s correlation coefficient (Table 2). The correlation coefficient is calculated by comparing data for the 200 genes in the GARD Prediction Signature, or for data derived from the complete array. For the GARD Prediction Signature, the correlation coefficient is 0.99 or above in 86% of all comparisons made. The lowest correlation between replicates is observed for penicillin G and p-phenylendiamine, with a coefficient of 0.97. When comparing replicates based on the full array, only Penicillin G has a coefficient below 0.99. Thus, the data is highly reproducible, with stable expression levels of the measured transcripts in technical and biological replicates.

We further analyzed the function of TaWAK5 in wheat defense responses to R. cerealis using virus-induced gene silencing (VIGS) technique. Six wheat (T. aestivum L.) lines/cultivars exhibiting different levels of resistance buy BKM120 and susceptibility to R. cerealis

were used in this study. They included CI12633 and Shanhongmai (resistant to R. cerealis); Navit 14, and Shannong 0431 (moderately resistant to R. cerealis); Wenmai 6 (susceptible to R. cerealis); and Yangmai 158 (moderately susceptible to R. cerealis) [28]. A major Jiangsu virulent isolate strain of pathogen fungus R. cerealis causing the sharp eyespot disease, R0301, was provided by Profs. Huaigu Chen and Shibin Cai from Jiangsu Academy of Agricultural Sciences, China. Wheat plants were grown in a 14 h light/10 h dark (22 °C/10 °C) regime. At the tillering stage, the 2nd base sheath of each wheat plant was inoculated with small toothpick fragments harboring well-developed learn more mycelia of the pathogen R. cerealis following Chen [27]. Mock treatment (control) plants were inoculated with small toothpick fragments soaked in liquid potato dextrose agar (PDA). Inoculated plants were grown at 90% relative humidity for 4 days. The inoculated stems were sampled at 0, 4, 7, 10, 14, and 21 days post inoculation,

quickly frozen in liquid nitrogen, and stored at − 80 °C prior to total RNA extraction. At 4 dpi, the roots, sheaths, stems, and leaves of the inoculated CI12633 plants were collected, respectively. At 45 dpi, the

roots, stems, leaves, and young either spikes of the inoculated CI12633 plants were separately sampled and used for RNA extraction and the tissue expression profiles of TaWAK5. In additional experiments, the seedlings at the three-leaf stage of the resistant line CI12633 were treated with phyto-hormones, including 1.0 mmol L− 1 SA, 0.1 mmol L− 1 MeJA (JA analog), ethylene released from 0.2 mmol L− 1 ethephon, and 0.2 mmol L− 1ABA, following Zhang et al. [29]. Leaves were collected for RNA extraction at 0, 1, 3, 6, 12, and 24 h after treatment with these hormones. Total RNA was extracted using TRIzol reagent (Qiagen, China) according to the manufacturer’s instructions. DNase I treatment was used to remove genomic DNA. First-strand cDNA was synthesized using 2 μg purified RNA, AMV reverse transcriptase, and oligo (dT15) primers (TaKaRa Inc., Tokyo, Japan) according to the manufacturer’s instructions for the cDNA synthesis kit. Based on microarray analysis results, a partial cDNA fragment (GenBank accession number CA642360), which was differentially expressed between the resistant wheat genotype CI12633 and the susceptible wheat Wenmai 6, was identified. Based on the sequence of CA642360 and using a 3′-Full RACE Core Set kit v.2.0 from TaKaRa Inc., the sequence of the 3′ untranslated region (UTR) was amplified from cDNA of CI12633 stems that had been challenged with the pathogen R. cerealis for 21 days.