Poly(A) code analyses reveal key determinants for tissue-specific mRNA alternative polyadenylation.
mRNA alternative polyadenylation (APA) is a critical mechanism for post-transcriptional gene regulation and is often regulated in a tissue- and/or developmental stage-specific manner. An ultimate goal for the APA field has been to be able to computationally predict APA profiles under different physiological or pathological conditions. As a first step toward this goal, we have assembled a poly(A) code for predicting tissue-specific poly(A) sites (PASs). Based on a compendium of over 600 features that have known or potential roles in PAS selection, we have generated and refined a machine-learning algorithm using multiple high-throughput sequencing-based data sets of tissue-specific and constitutive PASs. This code can predict tissue-specific PASs with >85% accuracy. Importantly, by analyzing the prediction performance based on different RNA features, we found that PAS context, including the distance between alternative PASs and the relative position of a PAS within the gene, is a key feature for determining the susceptibility of a PAS to tissue-specific regulation. Our poly(A) code provides a useful tool for not only predicting tissue-specific APA regulation, but also for studying its underlying molecular mechanisms.
Department of Microbiology and Molecular Genetics, School of Medicine, University of California, Irvine, Irvine, California 92697, USA Institute for Genomics and Bioinformatics, University of California, Irvine, Irvine, California 92697, USA Department of Computer Science, University of California, Irvine, Irvine, California 92697, USA.
Lingjie
L
Weng
Institute for Genomics and Bioinformatics, University of California, Irvine, Irvine, California 92697, USA Department of Computer Science, University of California, Irvine, Irvine, California 92697, USA.
Yi
Y
Li
Institute for Genomics and Bioinformatics, University of California, Irvine, Irvine, California 92697, USA Department of Computer Science, University of California, Irvine, Irvine, California 92697, USA.
Xiaohui
X
Xie
Department of Microbiology and Molecular Genetics, School of Medicine, University of California, Irvine, Irvine, California 92697, USA.
Yongsheng
Y
Shi
D000465:Algorithms; D006801:Humans; D011061:Poly A / Q000235:genetics*; D026723:Polyadenylation; D012333:RNA, Messenger / Q000235:genetics
D012333:RNA, Messenger; D011061:Poly A
mRNA 3′ processing; machine learning; post-transcriptional gene regulation; tissue specificity