Interestingly, our preliminary data indicated that there was no correlation between expression levels and chromosomal positions of expressed genes.
It can also help us to study the relationship between expression levels and codon usage bias since highly-expressed genes need abundant ribosomes and matching tRNAs for efficient translation.
To identify those sequences associated with differences in sensitivity to camptothecin, we assessed whether each one of the 34 genes differentially expressed in resistant LoVo and sensitive L2/L3 cells showed a significant correlation between expression levels and camptothecin-induced apoptosis in the 30 cell lines in our panel.
A number of copies contain large deletions however no obvious relationship between expression levels and sequence conservation could be identified.
Analyses done on animal models however have reported a more diverse pattern when investigating relationships between expression levels and intron size and density.
We found no association between expression levels and the length of mature mRNA, the size of the protein and GC content in distant spacers, introns, and primary transcripts.
However, if a direct growth-rate dependent feedback significantly contributes to the regulation of gene expression, it would lead to an apparent correlation between expression levels and growth rates when a large number of unrelated mutants are examined.
We find a positive correlation between expression levels and both intron number (R = +0.0893, p = <0.0005) and intron density (number of introns/kb of CDS; R = +0.0753, p = <0.005).
However, the most interesting finding from the gene expression studies was on ERBB3 which showed a highly significant (p<10−10) association between expression levels and genotypes at multiple SNPs (Figure 2a).
TGFA and EGFR gene expression data of 51 PTCs, harboring known genetic mutations, and 5 normal thyroid tissues from pathologies other than thyroid cancer, reported in another publicly available dataset obtained on Affimetrix platform [9], were analyzed for possible correlations between expression levels and genetic mutations.
