RESUMEN
Alternative splicing (AS) events modulate certain pathways and phenotypic plasticity in cancer. Although previous studies have computationally analyzed splicing events, it is still a challenge to uncover biological functions induced by reliable AS events from tremendous candidates. To provide essential splicing event signatures to assess pathway regulation, we developed a database by collecting two datasets: (i) reported literature and (ii) cancer transcriptome profile. The former includes knowledge-based splicing signatures collected from 63,229 PubMed abstracts using natural language processing, extracted for 202 pathways. The latter is the machine learning-based splicing signatures identified from pan-cancer transcriptome for 16 cancer types and 42 pathways. We established six different learning models to classify pathway activities from splicing profiles as a learning dataset. Top-ranked AS events by learning model feature importance became the signature for each pathway. To validate our learning results, we performed evaluations by (i) performance metrics, (ii) differential AS sets acquired from external datasets, and (iii) our knowledge-based signatures. The area under the receiver operating characteristic values of the learning models did not exhibit any drastic difference. However, random-forest distinctly presented the best performance to compare with the AS sets identified from external datasets and our knowledge-based signatures. Therefore, we used the signatures obtained from the random-forest model. Our database provided the clinical characteristics of the AS signatures, including survival test, molecular subtype, and tumor microenvironment. The regulation by splicing factors was additionally investigated. Our database for developed signatures supported retrieval and visualization system.
RESUMEN
The emergence and progression of cancers is accompanied by a dysregulation of transcriptional programs. The three-dimensional (3D) organization of the human genome has emerged as an important multi-level mediator of gene transcription and regulation. In cancer cells, this organization can be restructured, providing a framework for the deregulation of gene activity. The CTCF protein, initially identified as the product from a tumor suppressor gene, is a jack-of-all-trades for the formation of 3D genome organization in normal cells. Here, we summarize how CTCF is involved in the multi-level organization of the human genome and we discuss emerging insights into how perturbed CTCF function and DNA binding causes the activation of oncogenes in cancer cells, mostly through a process of enhancer hijacking. Moreover, we highlight non-canonical functions of CTCF that can be relevant for the emergence of cancers as well. Finally, we provide guidelines for the computational identification of perturbed CTCF binding and reorganized 3D genome structure in cancer cells.
RESUMEN
Intron retention (IR) occurs when an intron is transcribed into pre-mRNA and remains in the final mRNA. An increasing body of literature has demonstrated a major role for IR in numerous biological functions and in disease. Here we give an overview of the different computational approaches for detecting IR events from sequencing data. We show that these are based on different biological and computational assumptions that may lead to dramatically different results. We describe the various approaches for mitigating errors in detecting intron retention and for discovering IR signatures between different conditions.
RESUMEN
Alternative pre-mRNA processing greatly increases the coding capacity of the human genome and regulatory factors involved in RNA processing play critical roles in tissue development and maintenance. Indeed, abnormal functions of RNA processing factors have been associated with a wide range of human diseases from cancer to neurodegenerative disorders. While many studies have emphasized the importance of alternative splicing (AS), recent high-throughput sequencing efforts have also allowed global surveys of alternative polyadenylation (APA). For the majority of pre-mRNAs, as well as some non-coding transcripts such as lncRNAs, APA selects different 3'-ends and thus modulates the availability of regulatory sites recognized by trans-acting regulatory effectors, including miRs and RNA binding proteins (RBPs). Here, we compare the available technologies for assessing global polyadenylation patterns, summarize the roles of auxiliary factors on APA, and discuss the impact of differential polyA site (pA) selection in the determination of cell fate, transformation and disease.
Asunto(s)
Poliadenilación , ARN Mensajero/metabolismo , Regiones no Traducidas 3' , Animales , Enfermedad/genética , Regulación de la Expresión Génica , Humanos , Proteínas de Unión al ARN/metabolismoRESUMEN
Tandem alternative splice sites (TASS) form a defined class of alternative splicing and give rise to mRNA insertion/deletion variants with only small size differences. Previous work has confirmed evolutionary conservation of TASS elements while many cases show only low tissue specificity of isoform ratios. We pinpoint stochasticity and noise as important methodological issues for the dissection of TASS isoform patterns. Resolving such uncertainties, a recent report showed regulation in a cell culture system, with shifts of alternative splicing isoform ratios dependent on cell density. This novel type of regulation affects not only multiple TASS isoforms, but also other alternative splicing classes, in a concerted manner. Here, we discuss how specific regulatory network architectures may be realized through the novel regulation type and highlight the role of differential isoform functions as a key step in order to better understand the functional role of TASS.