Prediction and feature analysis of intron retention events in plant genome |
| |
| Affiliation: | 1. School of Mechano-Electronic Engineering, Xidian University, Xi''an 710071, China;2. School of Economics and Management, Xidian University, Xi''an 710071, China;3. Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA;1. MOAC Doctoral Training Centre, University of Warwick, Coventry, CV4 7AL, UK;2. Warwick Centre for Analytical Science, University of Warwick, Coventry, CV4 7AL, UK;3. School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK;4. Department of Chemistry, University of Warwick, Coventry, CV4 7AL, UK;1. ANID – Millennium Science Initiative Program – Millennium Institute for Integrative Biology (iBio), Avda. Libertador Bernardo O’Higgins 340, Santiago, Chile;2. Centro de Biotecnologia Vegetal, Universidad Andres Bello, Republica 330, Santiago, Chile;3. Centro de Genomica y Bioinformatica, Facultad de Ciencias, Universidad Mayor, Camino la Pirámide 5750, Huechuraba, Santiago, Chile;4. Escuela de Biotecnologia, Facultad de Ciencias, Universidad Mayor, Camino la Pirámide 5750, Huechuraba, Santiago, Chile;5. Departamento de Genetica Molecular y Microbiologia, Facultad de Ciencias Biologicas, Pontificia Universidad Catolica de Chile, Avda. Libertador Bernardo O’Higgins 340, Santiago, Chile |
| |
| Abstract: | Alternative splicing (AS) is a major contributor to increase the potential informational content of eukaryotic genomes by creating multiple mRNA species and proteins from a single gene. In plants, up to 60% genes are alternatively spliced and the most common type of AS is intron retention (IR). Genomic analyses of IR have illuminated its crucial role in shaping the evolution of genomes, in the control of developmental processes, and in the dynamic regulation of the transcriptome to influence phenotype. To explore the relationship between the sequence feature and the formation mechanism of IR, we statistically analyzed the retained introns and proposed an improved random forest-based hybrid method to predict intron retention events in plant genome. The results indicate that IR has significant relationship with individual introns which have weaker 5’ splice sites, lower GC content and less termination codon occurrence. By the method we proposed, 93.48% retained introns can be correctly distinguished from constitutive introns. Strikingly, our study will facilitate a better understanding of underlying mechanisms involved in intron retention. |
| |
| Keywords: | Alternative splicing Intron retention Feature selection Random forest Plant |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
