Mining transcript features related to translation in Arabidopsis using LASSO and random forest

Translation is an important process for all living organisms. During translation, messenger RNA is rewritten into protein. Multiple control mechanisms determine how much protein is generated during translation. In particular, several regulatory elements located on mRNA transcripts are known to affect translation. In this study, a genome-wide analysis was performed to mine features related to translation in the genome of Arabidopsis thaliana. We used ribosome footprinting data to measure translation and constructed a predictive model using LASSO and random forest to select features that likely affect translation. We identified multiple transcript features and measured their influence on translation in different transcript regions. We found that features related to different translation stages may have a different impact on translation; often, features relevant to the elongation step were playing a stronger role. Interestingly, we found that the contribution of features may be different for transcripts belonging to different functional groups, suggesting that transcripts might employ different mechanisms for the regulation of translation.