PennSeq: accurate isoform-specific gene expression quantification in RNA-Seq by modeling non-uniform read distribution

Correctly estimating isoform-specific gene expression is important for understanding complicated biological mechanisms and for mapping disease susceptibility genes. However, estimating isoform-specific gene expression is challenging because various biases present in RNA-Seq (RNA sequencing) data complicate the analysis, and if not appropriately corrected, can affect isoform expression estimation and downstream analysis. In this article, we present PennSeq, a statistical method that allows each isoform to have its own non-uniform read distribution. Instead of making parametric assumptions, we give adequate weight to the underlying data by the use of a non-parametric approach. Our rationale is that regardless what factors lead to non-uniformity, whether it is due to hexamer priming bias, local sequence bias, positional bias, RNA degradation, mapping bias or other unknown reasons, the probability that a fragment is sampled from a particular region will be reflected in the aligned data. This empirical approach thus maximally reflects the true underlying non-uniform read distribution. We evaluate the performance of PennSeq using both simulated data with known ground truth, and using two real Illumina RNA-Seq data sets including one with quantitative real time polymerase chain reaction measurements. Our results indicate superior performance of PennSeq over existing methods, particularly for isoforms demonstrating severe non-uniformity. PennSeq is freely available for download at http://sourceforge.net/projects/pennseq.     

Analysis and design of RNA sequencing experiments for identifying isoform regulation

Through alternative splicing, most human genes express multiple isoforms that often differ in function. To infer isoform regulation from high-throughput sequencing of cDNA fragments (RNA-seq), we developed the mixture-of-isoforms (MISO) model, a statistical model that estimates expression of alternatively spliced exons and isoforms and assesses confidence in these estimates. Incorporation of mRNA fragment length distribution in paired-end RNA-seq greatly improved estimation of alternative-splicing levels. MISO also detects differentially regulated exons or isoforms. Application of MISO implicated the RNA splicing factor hnRNP H1 in the regulation of alternative cleavage and polyadenylation, a role that was supported by UV cross-linking-immunoprecipitation sequencing (CLIP-seq) analysis in human cells. Our results provide a probabilistic framework for RNA-seq analysis, give functional insights into pre-mRNA processing and yield guidelines for the optimal design of RNA-seq experiments for studies of gene and isoform expression.     

(+)Insert smooth muscle myosin heavy chain (SM-B): from single molecule to human

In smooth muscle, alternative mRNA splicing of a single gene produces four myosin heavy chain (SMMHC) isoforms. Two of these isoforms differ by the presence [(+)insert] or absence [(-)insert] of a seven amino acid insert in the motor domain. This insert enhances the kinetic properties of myosin at the molecular level but its exact role at the cell and tissue levels still has to be elucidated. This review focuses on the expression and biological functions of the (+)insert isoform. Current knowledge is summarized regarding its tissue distribution in animals and humans. Studies at the molecular, cellular and tissue levels that aimed at understanding the contribution of this isoform to smooth muscle mechanical function are presented with a particular focus on velocity of shortening. In addition, the altered expression of the (+)insert isoform in diseases and models of diseases and the compensatory mechanisms that occur when the (+)insert is knocked out are discussed. The need for additional studies on the relationship of this isoform to contractile performance and how expression of this isoform is regulated are also considered.     

Quantitative Profiling of Drosophila melanogaster Dscam1 Isoforms Reveals No Changes in Splicing after Bacterial Exposure

The hypervariable Dscam1 (Down syndrome cell adhesion molecule 1) gene can produce thousands of different ectodomain isoforms via mutually exclusive alternative splicing. Dscam1 appears to be involved in the immune response of some insects and crustaceans. It has been proposed that the diverse isoforms may be involved in the recognition of, or the defence against, diverse parasite epitopes, although evidence to support this is sparse. A prediction that can be generated from this hypothesis is that the gene expression of specific exons and/or isoforms is influenced by exposure to an immune elicitor. To test this hypothesis, we for the first time, use a long read RNA sequencing method to directly investigate the Dscam1 splicing pattern after exposing adult Drosophila melanogaster and a S2 cell line to live Escherichia coli. After bacterial exposure both models showed increased expression of immune-related genes, indicating that the immune system had been activated. However there were no changes in total Dscam1 mRNA expression. RNA sequencing further showed that there were no significant changes in individual exon expression and no changes in isoform splicing patterns in response to bacterial exposure. Therefore our studies do not support a change of D. melanogaster Dscam1 isoform diversity in response to live E. coli. Nevertheless, in future this approach could be used to identify potentially immune-related Dscam1 splicing regulation in other host species or in response to other pathogens.     

一个肝癌相关长链非编码RNA的克隆及序列分析

最近我们利用新一代测序(next generation sequencing,NGS)技术对肝细胞癌(hepatocellular carcinoma,HCC)患者活检标本及正常对照肝组织样品进行高通量RNA测序(RNA-sequencing,RNA-Seq),在肝癌样品中染色体11q13.1区域检测到几个相邻的RNA-Seq信号峰,而在正常对照组织中没有检测到,且该染色体区域目前尚无已知基因登录,提示这几个RNA-Seq峰可能代表一个或多个未知的新基因.以此为线索,证实这几个RNA-Seq峰来自同一个新基因,并克隆了该基因全长序列,在克隆该基因全长序列时,发现该基因编码的RNA存在多种剪接形式,最长的转录本为3 562 bp.将该基因编码的12条代表性RNA转录本序列递交到美国国立生物技术信息中心(National Center for Biotechnology Information,NCBI)的GenBank数据库中,GenBank ID号分别为KC136297~KC136308.该基因编码的RNA没有发现明显的开放阅读框(open reading fragment,ORF),提示该基因可能编码长链非编码RNA(long non-coding RNA,lncRNA).为了探讨该lncRNA基因可能的转录调控机制,我们用生物信息学方法预测了该lncRNA基因潜在启动子区域,发现在其转录起始位点上游-719~-469 bp处有一个潜在的启动子,其中包含7个Sp1、1个STAT5和1个EGR1转录因子结合位点.该lncRNA在肝细胞癌发生发展过程中的作用机制值得进一步深入研究.