(A) R-based heat map of 10 selected DEGs for RT-qPCR. (B) Relative expression levels of selected ten genes and 18S as an internal reference detected by RT-qPCR in control and symptomatic leaves. Error bars symbolized standard error of three biological replicates and * shows significance determined by Student’s t-test.</p
Quantifying gene expression levels is an important research tool to understand biological systems. R...
Quantifying gene expression levels is an important research tool to understand biological systems. R...
<p>A total of 30 genes, including (A) 10 downregulated, (B) 10 upregulated, and (C) 10 unigenes with...
Relative expression levels of selected ten genes and 18S as an internal reference detected by RT-qPC...
<p>Twenty genes were chosen for RT-qPCR validation. The white and black bars represent the relative ...
<p>Expression levels of 26 randomly selected genes in the four samples used in this study were detec...
The grey-scale bars represent relative gene expression in control (dark grey) and treated plants (li...
<p>Data were normalized against a reference of wintersweet actin and tubulin genes. All quantitative...
<p>Gene expression data from the immune gene microarray shown as mean log<sub>2</sub> values of rati...
<p>The graph depicts the values obtained in microarrays and relative mRNA levels obtained using RT-q...
<p>(A) Leaf 10. (B) Leaf 20. Relative transcript level for each candidate gene at different sampled ...
<p>Relative gene expression (RGE) (in grey) in the four samples assayed: the resistant ‘Rojo Pasión’...
<p>The miRNA levels were normalized to an internal control (actin) and expressed relative to the val...
<p>(A) Validation of the selected up-regulated genes. (B) Validation of the selected down-regulated ...
Quantifying gene expression levels is an important research tool to understand biological systems. R...
Quantifying gene expression levels is an important research tool to understand biological systems. R...
Quantifying gene expression levels is an important research tool to understand biological systems. R...
<p>A total of 30 genes, including (A) 10 downregulated, (B) 10 upregulated, and (C) 10 unigenes with...
Relative expression levels of selected ten genes and 18S as an internal reference detected by RT-qPC...
<p>Twenty genes were chosen for RT-qPCR validation. The white and black bars represent the relative ...
<p>Expression levels of 26 randomly selected genes in the four samples used in this study were detec...
The grey-scale bars represent relative gene expression in control (dark grey) and treated plants (li...
<p>Data were normalized against a reference of wintersweet actin and tubulin genes. All quantitative...
<p>Gene expression data from the immune gene microarray shown as mean log<sub>2</sub> values of rati...
<p>The graph depicts the values obtained in microarrays and relative mRNA levels obtained using RT-q...
<p>(A) Leaf 10. (B) Leaf 20. Relative transcript level for each candidate gene at different sampled ...
<p>Relative gene expression (RGE) (in grey) in the four samples assayed: the resistant ‘Rojo Pasión’...
<p>The miRNA levels were normalized to an internal control (actin) and expressed relative to the val...
<p>(A) Validation of the selected up-regulated genes. (B) Validation of the selected down-regulated ...
Quantifying gene expression levels is an important research tool to understand biological systems. R...
Quantifying gene expression levels is an important research tool to understand biological systems. R...
Quantifying gene expression levels is an important research tool to understand biological systems. R...
<p>A total of 30 genes, including (A) 10 downregulated, (B) 10 upregulated, and (C) 10 unigenes with...