RESUMO
Advancements in long-read transcriptome sequencing (long-RNA-seq) technology have revolutionized the study of isoform diversity. These full-length transcripts enhance the detection of various transcriptome structural variations, including novel isoforms, alternative splicing events, and fusion transcripts. By shifting the open reading frame or altering gene expressions, studies have proved that these transcript alterations can serve as crucial biomarkers for disease diagnosis and therapeutic targets. In this project, we proposed IFDlong, a bioinformatics and biostatistics tool to detect isoform and fusion transcripts using bulk or single-cell long-RNA-seq data. Specifically, the software performed gene and isoform annotation for each long-read, defined novel isoforms, quantified isoform expression by a novel expectation-maximization algorithm, and profiled the fusion transcripts. For evaluation, IFDlong pipeline achieved overall the best performance when compared with several existing tools in large-scale simulation studies. In both isoform and fusion transcript quantification, IFDlong is able to reach more than 0.8 Spearman's correlation with the truth, and more than 0.9 cosine similarity when distinguishing multiple alternative splicing events. In novel isoform simulation, IFDlong can successfully balance the sensitivity (higher than 90%) and specificity (higher than 90%). Furthermore, IFDlong has proved its accuracy and robustness in diverse in-house and public datasets on healthy tissues, cell lines and multiple types of diseases. Besides bulk long-RNA-seq, IFDlong pipeline has proved its compatibility to single-cell long-RNA-seq data. This new software may hold promise for significant impact on long-read transcriptome analysis. The IFDlong software is available at https://github.com/wenjiaking/IFDlong.
RESUMO
Receptor tyrosine kinases MET and epidermal growth factor receptor (EGFR) are critically involved in initiation of liver regeneration. Other cytokines and signaling molecules also participate in the early part of the process. Regeneration employs effective redundancy schemes to compensate for the missing signals. Elimination of any single extracellular signaling pathway only delays but does not abolish the process. Our present study, however, shows that combined systemic elimination of MET and EGFR signaling (MET knockout + EGFR-inhibited mice) abolishes liver regeneration, prevents restoration of liver mass, and leads to liver decompensation. MET knockout or simply EGFR-inhibited mice had distinct and signaling-specific alterations in Ser/Thr phosphorylation of mammalian target of rapamycin, AKT, extracellular signal-regulated kinases 1/2, phosphatase and tensin homolog, adenosine monophosphate-activated protein kinase α, etc. In the combined MET and EGFR signaling elimination of MET knockout + EGFR-inhibited mice, however, alterations dependent on either MET or EGFR combined to create shutdown of many programs vital to hepatocytes. These included decrease in expression of enzymes related to fatty acid metabolism, urea cycle, cell replication, and mitochondrial functions and increase in expression of glycolysis enzymes. There was, however, increased expression of genes of plasma proteins. Hepatocyte average volume decreased to 35% of control, with a proportional decrease in the dimensions of the hepatic lobules. Mice died at 15-18 days after hepatectomy with ascites, increased plasma ammonia, and very small livers. CONCLUSION: MET and EGFR separately control many nonoverlapping signaling endpoints, allowing for compensation when only one of the signals is blocked, though the combined elimination of the signals is not tolerated; the results provide critical new information on interactive MET and EGFR signaling and the contribution of their combined absence to regeneration arrest and liver decompensation. (Hepatology 2016;64:1711-1724).