CircAST: Fulllength Assembly and Quantification of Alternatively Spliced Isoforms in Circular RNAs. Abstract   Circular RNAs (circRNAs), covalently closed continuous RNA loops, are generated from cognate linear RNAs through back splicing events, and alternative splicing events may generate different circRNA isoforms at the same locus. However, the challenges of reconstruction and quantification of alternatively spliced fulllength circRNAs remain unresolved. On the basis of the internal structural characteristics of circRNAs, we developed CircAST, a tool to assemble alternatively spliced circRNA transcripts and estimate their expression by using multiple splice graphs. Simulation studies showed that CircAST correctly assembled the full sequences of circRNAs with a sensitivity of 85.63%xe2x80x9394.32% and a precision of 81.96%xe2x80x9387.55%. By assigning reads to specific isoforms, CircAST quantified the expression of circRNA isoforms with correlation coefficients of 0.85xe2x80x930.99 between theoretical and estimated values. We evaluated CircAST on an inhouse mouse testis RNAseq dataset with RNase R treatment for enriching circRNAs and identified 380 circRNAs with fulllength sequences different from those of their corresponding cognate linear RNAs. RTPCR and Sanger sequencing validated 32 out of 37 randomly selected isoforms, thus further indicating the good performance of CircAST, especially for isoforms with low abundance. We also applied CircAST to published experimental data and observed substantial diversity in circular transcripts across samples, thus suggesting that circRNA expression is highly regulated. CircAST can be accessed freely at  https:github.comxiaofengsongCircAST .

Differential splicing analysis based on isoforms expression with NBSplice Abstract   Alternative splicing alterations have been widely related to several human diseases revealing the importance of their study for the success of translational medicine. Differential splicing (DS) occurrence has been mainly analyzed through exonbased approaches over RNAseq data. Although these strategies allow identifying differentially spliced genes, they ignore the identity of the affected gene isoforms which is crucial to understand the underlying pathological processes behind alternative splicing changes. Moreover, despite several isoform quantification tools for RNAseq data have been recently developed, DS tools have not taken advantage of them.  Here, the NBSplice R package for differential splicing analysis by means of isoform expression data is presented. It estimates differences on relative expressions of gene transcripts between experimental conditions to infer changes in gene alternative splicing patterns. The developed tool was evaluated using a synthetic RNAseq dataset with controlled differential splicing. NBSplice accurately predicted DS occurrence, outperforming current methods in terms of accuracy, sensitivity, Fscore, and false discovery rate control. The usefulness of our development was demonstrated by the analysis of a real cancer dataset, revealing new differentially spliced genes that could be studied pursuing new colorectal cancer biomarkers discovery.