SEASTAR: systematic evaluation of alternative transcription start sites in RNA

Abstract

Alternative first exons diversify the transcriptomes of eukaryotes by producing variants of the 5′ Untranslated Regions (5′UTRs) and N-terminal coding sequences. Accurate transcriptome-wide detection of alternative first exons typically requires specialized experimental approaches that are designed to identify the 5′ ends of transcripts. We developed a computational pipeline SEASTAR that identifies first exons from RNA-seq data alone then quantifies and compares alternative first exon usage across multiple biological conditions. The exons inferred by SEASTAR coincide with transcription start sites identified directly by CAGE experiments and bear epigenetic hallmarks of active promoters. To determine if differential usage of alternative first exons can yield insights into the mechanism controlling gene expression, we applied SEASTAR to an RNA-seq dataset that tracked the reprogramming of mouse fibroblasts into induced pluripotent stem cells. We observed dynamic temporal changes in the usage of alternative first exons, along with correlated changes in transcription factor expression. Using a combined sequence motif and gene set enrichment analysis we identified N-Myc as a regulator of alternative first exon usage in the pluripotent state. Our results demonstrate that SEASTAR can leverage the available RNA-seq data to gain insights into the control of gene expression and alternative transcript variation in eukaryotic transcriptomes.

An integrated multi-omics approach identifies the landscape of interferon-α-mediated responses of human pancreatic beta cells

“…The usage of alternative transcription start (TSS) sites is another mechanism that generates different transcripts from the same gene 41 . We used the SEASTAR pipeline 42 for the computational identification and quantitative analysis of first exon usage. This approach recognized >250 events of alternative first exon (AFE) usage occurring in 166 different genes at 8 h, and >130 events of AFE usage in 88 genes at 24 h (Fig.…”

“…Changes in the alternative transcription start site (TSS) initiation increase the repertoire of IFNα-regulated transcripts. a The tool SEASTAR42 was used to estimate the frequency of differential alternative first exon (AFE) usage induced by IFNα in human beta cells. The total number of IFNαdependent AFEs events (left) and number of genes with AFEs (right) in the indicated time point are shown (n = 5, ΔPSI > |0.2|, FDR < 0.05).…”

Gene Regulatory Network Perturbation by Genetic and Epigenetic Variation

“…Alternative transcription start site is a major mechanism for diversity of human transcriptome. Qin et al have developed a computational pipeline SEASTAR to identify first exons from RNA-seq data alone [110]. Alternative first exon usage is then quantified and compared across multiple samples.…”

Single-cell RNA cap and tail sequencing (scRCAT-seq) reveals subtype-specific isoforms differing in transcript demarcation

“…The accuracy of TES and TSS peaks called by scRCAT-seq is substantially improved when coupled to a machine learning algorithm that filters out the noisy false-positive peaks. Previously, machine learning has been successfully used to predict differential alternative splicing 32,33 , but none of them have been developed for the purpose of identifying authentic demarcations of RNA isoforms to elucidate the transcriptomic complexity of single cells. Furthermore, the model trained in this study also improves the accuracy of other methods to over 90%, as evidenced by the ERCC data from C1 CAGE 19,26 and C1 STRT 26 , indicating that our model can be applied to other datasets that contain previously unrecognized high false-positive signals.…”