Identification of TATA and TATA-less promoters in plant genomes by integrating diversity measure, GC-Skew and DNA geometric flexibility.
Accurate identification of core promoters is important for gaining more insight about the understanding of the eukaryotic transcription regulation. In this study, the authors focused on the biologically realistic promoter prediction of plant genomes. By analyzing the correlative conservation, GC-compositional bias and specific structural patterns of TATA and TATA-less promoters in PlantPromDB, a hybrid multi-feature approach based on support vector machine (SVM) for predicting the two types of promoters were developed by integrating local word content, GC-Skew and DNA geometric flexibility. Compared with the TSSP-TCM program on the same test dataset, better prediction results were obtained. Especially for the TATA-less promoter, the accuracy is 10% higher than the result of TSSP-TCM program. The good performance of the hybrid promoters and the experimental data also indicate that our method has the ability to locate the promoter region of the plant genome.
Laboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot, 010021, China.
Yong-Chun
YC
Zuo
Qian-Zhong
QZ
Li
D017360:Arabidopsis / Q000235:genetics*; D001482:Base Composition; D001483:Base Sequence; D019295:Computational Biology; D057225:Data Mining; D018506:Gene Expression Regulation, Plant; D018745:Genome, Plant / Q000235:genetics*; D011401:Promoter Regions, Genetic; D017422:Sequence Analysis, DNA