These data suggest that for some of the alternatively spliced genes the expression levels and the ratio between transcripts change during vegetative growth.
In contrast, we had expected the highest overlap of transcript changes between dcl1 and hyl1 because miRNA targets accumulate less in hyl1 than dcl1 [12], and HYL1 interacts with DCL1 to promote the precise processing and efficient generation of miRNAs [4].
In order to identify specific transcript changes between partial resistance and susceptibility responses, the transcript profiles of Bur-0 plants inoculated with either the eH isolate (leading to partial resistance) or with the e2 isolate (leading to complete susceptibility) were compared.
On the contrary, its duplicated gene MdHsfB1b did not show any remarkable transcript changes between the different flower and fruit stages.
Interestingly, transcript changes in hyl1 and hst mutants greatly overlapped, suggesting a novel functional connection between HST and HYL.
With the exception of L1L sense, which showed expression at day 45 based on qPCR, but not RNA-Seq results, all tested transcripts showed a good agreement in transcript changes between these two methods.
As randomly fragmented mRNA molecules will generate less short-read tags for a short transcript than for a longer transcript, changes in expression between two (relatively) poorly sampled transcripts are less discernible from sampling noise.
In agreement with previous studies, investigation of the association between transcript and copy number changes in humans [8] and in mice [34] revealed greater functional impact from variants residing outside the protein coding gene locus.
In general our transcriptomics and proteomics data agree well, as we detected for both proteomic comparisons a correlation of >0.5 between transcript and protein fold changes, while correlations from 0.4 - 0.7 [ 1] to 0.21 [ 75] have been reported earlier.
This resulted in improved correlations between CEF changes and transcript levels.
