Transcriptome Analysis of Bronchoalveolar Lavage Fluid From Children With Mycoplasma pneumoniae Pneumonia Reveals Natural Killer and T Cell-Proliferation Responses

High-throughput RNA sequencing (RNA-seq) promises a comprehensive picture of the transcriptome, allowing for the complete annotation and quantification of all genes and their isoforms across samples. Realizing this promise requires increasingly complex computational methods. These computational challenges fall into three main categories: (i) read mapping, (ii) transcriptome reconstruction and (iii) expression quantification. Here we explain the major conceptual and practical challenges, and the general classes of solutions for each category. Finally, we highlight the interdependence between these categories and discuss the benefits for different biological applications.

Natural killer (NK) cells are innate effector lymphocytes necessary for defence against stressed, microbe-infected, or malignant cells. NK cells kill target cells by either of two major mechanisms that require direct contact between NK cells and target cells. In the first pathway, cytoplasmic granule toxins, predominantly a membrane-disrupting protein known as perforin, and a family of structurally related serine proteases (granzymes) with various substrate specificities, are secreted by exocytosis and together induce apoptosis of the target cell. The granule-exocytosis pathway potently activates cell-death mechanisms that operate through the activation of apoptotic cysteine proteases (caspases), but can also cause cell death in the absence of activated caspases. The second pathway involves the engagement of death receptors (e.g. Fas/CD95) on target cells by their cognate ligands (e.g. FasL) on NK cells, resulting in classical caspase-dependent apoptosis. The comparative role of these pathways in the pathophysiology of many diseases is being dissected by analyses of gene-targeted mice that lack these molecules, and humans who have genetic mutations affecting these pathways. We are also now learning that the effector function of NK cells is controlled by interactions involving specific NK cell receptors and their cognate ligands, either on target cells, or other cells of the immune system. This review will discuss the functional importance of NK cell cytotoxicity and the receptor/ligand interactions that control these processes.

Ultra-deep RNA sequencing has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We develop MATS (multivariate analysis of transcript splicing), a Bayesian statistical framework for flexible hypothesis testing of differential alternative splicing patterns on RNA-Seq data. MATS uses a multivariate uniform prior to model the between-sample correlation in exon splicing patterns, and a Markov chain Monte Carlo (MCMC) method coupled with a simulation-based adaptive sampling procedure to calculate the P-value and false discovery rate (FDR) of differential alternative splicing. Importantly, the MATS approach is applicable to almost any type of null hypotheses of interest, providing the flexibility to identify differential alternative splicing events that match a given user-defined pattern. We evaluated the performance of MATS using simulated and real RNA-Seq data sets. In the RNA-Seq analysis of alternative splicing events regulated by the epithelial-specific splicing factor ESRP1, we obtained a high RT–PCR validation rate of 86% for differential exon skipping events with a MATS FDR of <10%. Additionally, over the full list of RT–PCR tested exons, the MATS FDR estimates matched well with the experimental validation rate. Our results demonstrate that MATS is an effective and flexible approach for detecting differential alternative splicing from RNA-Seq data.