A compatible exon-exon junction database for the identification of exon skipping events using tandem mass spectrum data

<p>Abstract</p> <p>Background</p> <p>Alternative splicing is an important gene regulation mechanism. It is estimated that about 74% of multi-exon human genes have alternative splicing. High throughput tandem (MS/MS) mass spectrometry provides valuable information for rapidly identifying potentially novel alternatively-spliced protein products from experimental datasets. However, the ability to identify alternative splicing events through tandem mass spectrometry depends on the database against which the spectra are searched.</p> <p>Results</p> <p>We wrote scripts in perl, Bioperl, mysql and Ensembl API and built a theoretical exon-exon junction protein database to account for all possible combinations of exons for a gene while keeping the frame of translation (i.e., keeping only in-phase exon-exon combinations) from the Ensembl Core Database. Using our liver cancer MS/MS dataset, we identified a total of 488 non-redundant peptides that represent putative exon skipping events.</p> <p>Conclusion</p> <p>Our exon-exon junction database provides the scientific community with an efficient means to identify novel alternatively spliced (exon skipping) protein isoforms using mass spectrometry data. This database will be useful in annotating genome structures using rapidly accumulating proteomics data.</p

The utility of mass spectrometry-based proteomic data for validation of novel alternative splice forms reconstructed from RNA-Seq data: a preliminary assessment

Abstract Background Most mass spectrometry (MS) based proteomic studies depend on searching acquired tandem mass (MS/MS) spectra against databases of known protein sequences. In these experiments, however, a large number of high quality spectra remain unassigned. These spectra may correspond to novel peptides not present in the database, especially those corresponding to novel alternative splice (AS) forms. Recently, fast and comprehensive profiling of mammalian genomes using deep sequencing (i.e. RNA-Seq) has become possible. MS-based proteomics can potentially be used as an aid for protein-level validation of novel AS events observed in RNA-Seq data. Results In this work, we have used publicly available mouse tissue proteomic and RNA-Seq datasets and have examined the feasibility of using MS data for the identification of novel AS forms by searching MS/MS spectra against translated mRNA sequences derived from RNA-Seq data. A significant correlation between the likelihood of identifying a peptide from MS/MS data and the number of reads in RNA-Seq data for the same gene was observed. Based on in silico experiments, it was also observed that only a fraction of novel AS forms identified from RNA-Seq had the corresponding junction peptide compatible with MS/MS sequencing. The number of novel peptides that were actually identified from MS/MS spectra was substantially lower than the number expected based on in silico analysis. Conclusions The ability to confirm novel AS forms from MS/MS data in the dataset analyzed was found to be quite limited. This can be explained in part by low abundance of many novel transcripts, with the abundance of their corresponding protein products falling below the limit of detection by MS.http://deepblue.lib.umich.edu/bitstream/2027.42/112811/1/12859_2010_Article_4302.pd

High-Throughput Proteomics Detection of Novel Splice Isoforms in Human Platelets

Alternative splicing (AS) is an intrinsic regulatory mechanism of all metazoans. Recent findings suggest that 100% of multiexonic human genes give rise to splice isoforms. AS can be specific to tissue type, environment or developmentally regulated. Splice variants have also been implicated in various diseases including cancer. Detection of these variants will enhance our understanding of the complexity of the human genome and provide disease-specific and prognostic biomarkers. We adopted a proteomics approach to identify exon skip events - the most common form of AS. We constructed a database harboring the peptide sequences derived from all hypothetical exon skip junctions in the human genome. Searching tandem mass spectrometry (MS/MS) data against the database allows the detection of exon skip events, directly at the protein level. Here we describe the application of this approach to human platelets, including the mRNA-based verification of novel splice isoforms of ITGA2, NPEPPS and FH. This methodology is applicable to all new or existing MS/MS datasets

RNA-Seq Analyses Generate Comprehensive Transcriptomic Landscape and Reveal Complex Transcript Patterns in Hepatocellular Carcinoma

RNA-seq is a powerful tool for comprehensive characterization of whole transcriptome at both gene and exon levels and with a unique ability of identifying novel splicing variants. To date, RNA-seq analysis of HBV-related hepatocellular carcinoma (HCC) has not been reported. In this study, we performed transcriptome analyses for 10 matched pairs of cancer and non-cancerous tissues from HCC patients on Solexa/Illumina GAII platform. On average, about 21.6 million sequencing reads and 10.6 million aligned reads were obtained for samples sequenced on each lane, which was able to identify >50% of all the annotated genes for each sample. Furthermore, we identified 1,378 significantly differently expressed genes (DEGs) and 24, 338 differentially expressed exons (DEEs). Comprehensive function analyses indicated that cell growth-related, metabolism-related and immune-related pathways were most significantly enriched by DEGs, pointing to a complex mechanism for HCC carcinogenesis. Positional gene enrichment analysis showed that DEGs were most significantly enriched at chromosome 8q21.3–24.3. The most interesting findings were from the analysis at exon levels where we characterized three major patterns of expression changes between gene and exon levels, implying a much complex landscape of transcript-specific differential expressions in HCC. Finally, we identified a novel highly up-regulated exon-exon junction in ATAD2 gene in HCC tissues. Overall, to our best knowledge, our study represents the most comprehensive characterization of HBV-related HCC transcriptome including exon level expression changes and novel splicing variants, which illustrated the power of RNA-seq and provided important clues for understanding the molecular mechanisms of HCC pathogenesis at system-wide levels

SAW: A Method to Identify Splicing Events from RNA-Seq Data Based on Splicing Fingerprints

Splicing event identification is one of the most important issues in the comprehensive analysis of transcription profile. Recent development of next-generation sequencing technology has generated an extensive profile of alternative splicing. However, while many of these splicing events are between exons that are relatively close on genome sequences, reads generated by RNA-Seq are not limited to alternative splicing between close exons but occur in virtually all splicing events. In this work, a novel method, SAW, was proposed for the identification of all splicing events based on short reads from RNA-Seq. It was observed that short reads not in known gene models are actually absent words from known gene sequences. An efficient method to filter and cluster these short reads by fingerprint fragments of splicing events without aligning short reads to genome sequences was developed. Additionally, the possible splicing sites were also determined without alignment against genome sequences. A consensus sequence was then generated for each short read cluster, which was then aligned to the genome sequences. Results demonstrated that this method could identify more than 90% of the known splicing events with a very low false discovery rate, as well as accurately identify, a number of novel splicing events between distant exons

OryzaPG-DB: Rice Proteome Database based on Shotgun Proteogenomics

<p>Abstract</p> <p>Background</p> <p>Proteogenomics aims to utilize experimental proteome information for refinement of genome annotation. Since mass spectrometry-based shotgun proteomics approaches provide large-scale peptide sequencing data with high throughput, a data repository for shotgun proteogenomics would represent a valuable source of gene expression evidence at the translational level for genome re-annotation.</p> <p>Description</p> <p>Here, we present OryzaPG-DB, a rice proteome database based on shotgun proteogenomics, which incorporates the genomic features of experimental shotgun proteomics data. This version of the database was created from the results of 27 nanoLC-MS/MS runs on a hybrid ion trap-orbitrap mass spectrometer, which offers high accuracy for analyzing tryptic digests from undifferentiated cultured rice cells. Peptides were identified by searching the product ion spectra against the protein, cDNA, transcript and genome databases from Michigan State University, and were mapped to the rice genome. Approximately 3200 genes were covered by these peptides and 40 of them contained novel genomic features. Users can search, download or navigate the database per chromosome, gene, protein, cDNA or transcript and download the updated annotations in standard GFF3 format, with visualization in PNG format. In addition, the database scheme of OryzaPG was designed to be generic and can be reused to host similar proteogenomic information for other species. OryzaPG is the first proteogenomics-based database of the rice proteome, providing peptide-based expression profiles, together with the corresponding genomic origin, including the annotation of novelty for each peptide.</p> <p>Conclusions</p> <p>The OryzaPG database was constructed and is freely available at <url>http://oryzapg.iab.keio.ac.jp/</url>.</p

Assessing the impact of alternative splicing on the diversity and evolution of the proteome in plants

Splicing is one of the key processing steps during the maturation of a gene’s primary transcript into the mRNA molecule used as a template for protein production. Splicing involves the removal of segments called introns and re-joining of the remaining segments called exons. It is by now well established that not always the same segments are removed from a gene’s primary transcript during the splicing process. The consequence of this splicing variation, termed Alternative Splicing (AS), is that multiple distinct mature mRNA molecules can be produced from a single gene. One of the two biological roles that are ascribed to AS is that of a mechanism which enables an organism to produce multiple functionally distinct proteins from a single gene. Alternatively, AS can serve as a means for controlling gene expression at the post-transcriptional level. Although many clear examples have been reported for both roles, the extent to which AS increases the functional diversity of the proteome, regulates gene expression or simply reflects noise in splicing machinery is not well known. Determining the full functional impact of AS by designing and performing wet-lab experiments for all AS events is unfeasible and bioinformatics approaches have therefore widely been used for studying the impact of AS at a genome-wide scale. In this thesis four bioinformatics studies are presented that were aimed at determining the extent to which AS is used in plants as a mechanism for producing multiple distinct functional proteins from a single gene. Each chapter uses a different method for analyzing specific properties of AS. Under the premise that functional genetic features are more likely to be conserved than non-functional ones, AS events that are present in two or more species are more likely to be biologically relevant than those that are confined to a single species. In chapter 2 we analyzed the conservation of AS by performing a comparative analysis between three divergent plant species. The results of that study indicated that the vast majority of AS events does not persist over long periods of evolution. We concluded, based on this lack of conservation, that AS only has a limited impact on the functional diversity of the proteome in plants. Following this conclusion, it can hypothesized that the variation that AS induces at the transcriptome level is not likely to be manifested at the protein level. In chapter 3 we tested this hypothesis by analyzing two independent proteomics datasets. This type of data can be used to directly identify proteins present in a biological sample. Our results indicated that the variation induced by AS at the transcriptome level is also manifested at the protein level. We concluded that either many AS events have a confined species-specific (not conserved) function or simply produce protein variants that are stable enough to escape rapid turn-over. Another method for determining whether AS increases the functional diversity of the proteome is by determining whether protein sequence variations that are typically induced by AS are common within the plant kingdom. We found (chapter 4) that this is not the case in plants and concluded that novel functions do not frequently arise through AS. We also found that most of the AS-induced variation is lost, similarly as for redundant gene copies, within a very short evolutionary time period. One limitation of genome-wide analyses is that these capture only the more general patterns. However, the functional impact of AS can be very different in different genes or gene-families. In order fully assess the functional impact of AS, it is therefore important to also study the process within the functional context of individual genes or gene families. In chapter 5 we demonstrated this concept by performing a detailed analysis of AS within the MADS-box gene family. We were able to provide clues as to how AS might impact the protein-protein interaction capabilities of individual MADS proteins. Some of our predictions were supported by experimental evidence. We further showed how AS can serve as an evolutionary mechanism for experimenting with novel functions (novel interactions) without the explicit loss of existing functions. The overall conclusion, based on the performed analyses is as follows: AS primarily is a consequence of noise in the splicing machinery and results in an increased diversity of the proteome. However, only a small fraction of the proteins resulting from AS will have beneficial functions and are subsequently selected for during evolution. The large remaining fraction is, similarly as for redundant gene-copies, lost within a very short evolutionary time period after its emergence. </p

Identification and Functional Annotation of Alternatively Spliced Isoforms

Alternative splicing is a key mechanism for increasing the complexity of transcriptome and proteome in eukaryotic cells. A large portion of multi-exon genes in humans undergo alternative splicing, and this can have significant functional consequences as the proteins translated from alternatively spliced mRNA might have different amino acid sequences and structures. The study of alternative splicing events has been accelerated by the next-generation sequencing technology. However, reconstruction of transcripts from short-read RNA sequencing is not sufficiently accurate. Recent progress in single-molecule long-read sequencing has provided researchers alternative ways to help solve this problem. With the help of both short and long RNA sequencing technologies, tens of thousands of splice isoforms have been catalogued in humans and other species, but relatively few of the protein products of splice isoforms have been characterized functionally, structurally and biochemically. The scope of this dissertation includes using short and long RNA sequencing reads together for the purpose of transcript reconstruction, and using high-throughput RNA-sequencing data and gene ontology functional annotations on gene level to predict functions for alternatively spliced isoforms in mouse and human. In the first chapter, I give an introduction of alternative splicing and discuss the existing studies where next generation sequencing is used for transcript identification. Then, I define the isoform function prediction problem, and explain how it differs from better known gene function prediction problem. In the second chapter of this dissertation, I describe our study where the overall transcriptome of kidney is studied using both long reads from PacBio platform and RNA-seq short reads from Illumina platform. We used short reads to validate full-length transcripts found by long PacBio reads, and generated two high quality sets of transcript isoforms that are expressed in glomerular and tubulointerstitial compartments. In the third chapter, I describe our generic framework, where we implemented and evaluated several related algorithms for isoform function prediction for mouse isoforms. We tested these algorithms through both computational evaluation and experimental validation of the predicted ‘responsible’ isoform(s) and the predicted disparate functions of the isoforms of Cdkn2a and of Anxa6. Our algorithm is the first effort to predict and differentiate isoform functions through large-scale genomic data integration. In the fourth chapter, I present the extension of isoform function prediction study to the protein coding isoforms in human. We used a similar multiple instance learning (MIL)-based approach for predicting the function of protein coding splice variants in human. We evaluated our predictions using literature evidence of ADAM15, LMNA/C, and DMXL2 genes. And in the fifth and final chapter, I give a summary of previous chapters and outline the future directions for alternatively spliced isoform reconstruction and function prediction studies.PHDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144017/1/ridvan_1.pd

Duchenne muscular dystrophy : mutation profiling in view of the emerging gene-based therapies

Includes bibliographical references (leaves 97-115).Duchenne Muscular Dystrophy (DMD) is a lethal, X-linked, recessive muscle-wasting disorder affecting 1 in 3 500 live male births worldwide, for which only palliative care is available to date. Large exonic deletions or duplications are found in approximately 70% of DMD patients, for which diagnostic testing is available. The remaining 30% carry point mutations, which go largely undetected, as no testing is currently offered due to the great size of the DMD gene and the logistical challenges involved