McKhann et al. reported that CBF and COR (Cold Regulated) genes respond differently to cold stress in eight accessions, though they could not find clear correlation between gene expression, sequence polymorphism and cold tolerance [ 17].
Taken together, our analyses of expression data and phylogenetic relationship of Arabidopsis and soybean TCS members indicate a correlation between gene expression, sequence conservation and gene function, which is consistent with the results reported previously.
Another possible reason is that, there may not exist simple linear relationships between gene expression pattern and sequence length.
This phenomenon, which has been underestimated due to the low correlations between gene expression and gene sequence characteristics reported in other studies, may have played a relevant role on the evolution of the human gene sequences.
Furthermore, several studies found a strong correlation between gene expression divergence and coding sequence divergence [3], [8], [9], [10], [11], while other studies [2], [5], [12], [13], [14], [15] suggested little correlation between them.
The neutral model was previously supported by a lack of correlation between gene expression profiles and gene sequence divergence [ 52], a general observation that is in line with our own results.
We use genome-wide estimates of gene expression (>50,000 expressed genes) to study the relationship between gene expression, codon bias, rates of sequence divergence, protein length, and gene duplication.
We use genome-wide estimates of gene expression to investigate the relationship between gene expression, codon bias, rates of sequence divergence, and protein length.
This work advances our current understanding of plant science by showing the complex relationships between gene expression, codon bias, rates of sequence divergence, and gene duplication in gymnosperms.
Computational methods that define relationships between gene expression levels and putative regulatory sequences in the promoter regions of differentially expressed genes based on large-scale microarray data and genome sequence screening are increasingly being used to establish a signal transduction network [ 18, 24, 25].
If selection is acting on gene sequences to maximize expression efficiency, we might expect to find a relationship between gene expression profiles and some descriptions of sequence parameters.
