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Resolution: standard / high Figure 2.
Transcriptomic reprogramming in different climatic seasons. (a) Cluster dendrogram of the first developmental stage dataset using the average expression
value of the three biological replicates. Pearson's correlation values were converted
into distance coefficients to define the height of the dendrogram. Sample names are
composed by vineyard abbreviation followed by the indication of the harvesting year
(06, 07, or 08) and by the indication of the developmental stage (1). Blue, green,
and red indicate samples harvested in 2006, in 2008, and in 2007, respectively. Data
are the average of the three biological replicates. (b) Hierarchical clustering analysis of transcripts that were differentially modulated
among different seasons in first-stage samples. Kruskal-Wallis analysis of variance
(P <0.01, three groups) was used to define transcripts whose expression is modulated
in at least one growing season. Pearson's correlation distance was used as the metric
to create the transcriptional profile dendrogram. Sample names are composed by vineyard
abbreviation followed by the indication of the harvesting year (06, 07, or 08) and
by the indication of the developmental stage (1). Data are the average of the three
biological replicates. (c) Cluster dendrogram of the second and the third developmental stage datasets using
the average expression value of the three biological replicates. Pearson's correlation
values were converted into distance coefficients to define the height of the dendrogram.
Sample names are composed by vineyard abbreviation followed by the indication of the
harvesting year (06, 07, or 08) and by the indication of the developmental stages
(2 or 3). Blue, green, and red indicate samples harvested in 2006, in 2008, and in
2007, respectively. Data are the average of the three biological replicates. MapMan
software (v. 3.5) was used to visualize ripe berry genes specifically expressed in
the 2006/2008 (white) and 2007 (red) growing seasons in an overview of metabolism
(d) and focusing on the phenylpropanoid pathway (e).
Dal Santo et al. Genome Biology 2013 14:r54 doi:10.1186/gb-2013-14-6-r54 |