ABSTRACT
There is a continuing interest in the analysis of gene architecture and gene expression to determine the relationship that may exist. Advances in high-quality sequencing technologies and large-scale resource datasets have increased the understanding of relationships and cross-referencing of expression data to the large genome data. Although a negative correlation between expression level and gene (especially transcript) length has been generally accepted, there have been some conflicting results arising from the literature concerning the impacts of different regions of genes, and the underlying reason is not well understood. The research aims to apply quantile regression techniques for statistical analysis of coding and noncoding sequence length and gene expression data in the plant, Arabidopsis thaliana, and fruit fly, Drosophila melanogaster, to determine if a relationship exists and if there is any variation or similarities between these species. The quantile regression analysis found that the coding sequence length and gene expression correlations varied, and similarities emerged for the noncoding sequence length (5' and 3' UTRs) between animal and plant species. In conclusion, the information described in this study provides the basis for further exploration into gene regulation with regard to coding and noncoding sequence length.
ABSTRACT
The availability of genomic DNA and cDNA sequence data has escalated the data mining and genomics era. We aim to investigate the length distributions of the non-coding and coding regions of protein genes of two model organisms, Arabidopsis thaliana and Drosophila melanogaster. A non-linear functional relationship model was applied and strong correlation was found between the Coding Sequence (CDS) and non-coding sequence regions, conditional on the 5' UTR data. Significant differences were found between the protein functional classes and each gene region. Examination of the non-coding and coding regions of these organisms has revealed possible correlations.
