This study revealed a strong correlation (Spearman ρ of 0.83, p < 0.0001) between northern and microarray gene expression estimates.
However, agreement between transcript abundance and qPCR gene expression estimates were relatively poor, both in terms of direction and magnitude, and in only 6 out of 14 assays were expression estimates similar.
While agreement between sequencing and qPCR based gene expression estimates was relatively poor; qPCR expression data tentatively identified candidate genes for further study of salinity tolerance in this taxon.
To ensure consistency between the different methodologies used to generate nuclear and cellular data, gene expression estimates were based on all genomic reads, including reads mapping to introns which have been found to accurately predict gene expression levels10, 19.
Many methods now exist that estimate individual isoform estimates, which can then be combined to give accurate gene expression estimates.
Strikingly, the highest negative correlation between methylation and gene expression (estimated by Affymetrix U133plus2, [ 26]) was observed for the same two probes (Spearman correlation coefficients −0.543 and −0.571, respectively).
In further agreement with previous observations [ 13, 16], we find reasonably good positive correlation between gene expression levels estimated by the two methods.
We acquired embryonic transcriptome data from the work of Grishkevich et al. (2012) and tested for a correlation between gene expression level and our estimates of embryonic lethality.
When examining the correlation between gene expression and CUB, we estimated correlation coefficients in HK and TS genes, respectively.
No changes were observed in the expression of genes encoding proteins involved in fatty acid oxidation, what brings the only inconsistency between gene expression profile and substrate oxidation estimated by indirect calorimetry in our experiment.
