Long Noncoding RNA EGOT Responds to Stress Signals to Regulate Cell Inflammation and Growth.

The cell has several mechanisms to sense and neutralize stress. Stress-related stimuli activate pathways that counteract danger, support cell survival, and activate the inflammatory response. We use human cells to show that these processes are modulated by EGOT, a long noncoding RNA highly induced by viral infection, whose inhibition results in increased levels of antiviral IFN-stimulated genes (ISGs) and decreased viral replication. We now show that EGOT is induced in response to cell stress, viral replication, or the presence of pathogen-associated molecular patterns via the PI3K/AKT, MAPKs, and NF-κB pathways, which lead to cell survival and inflammation. Transcriptome analysis and validation experiments show that EGOT modulates PI3K/AKT and NF-κB responses. On the one hand, EGOT inhibition decreases expression of PI3K/AKT-induced cellular receptors and cell proliferation. In fact, EGOT levels are increased in several tumors. On the other hand, EGOT inhibition results in decreased levels of key NF-κB target genes, including those required for inflammation and ISGs in those cells that build an antiviral response. Mechanistically, EGOT depletion decreases the levels of the key coactivator TBLR1, essential for transcription by NF-κB. In summary, EGOT is induced in response to stress and may function as a switch that represses ISG transcription until a proper antiviral or stress response is initiated. EGOT then helps PI3K/AKT, MAPKs, and NF-κB pathways to activate the antiviral response, cell inflammation, and growth. We believe that modulation of EGOT levels could be used as a therapy for the treatment of certain viral infections, immune diseases, and cancer.

DeepMSPeptide: peptide detectability prediction using deep learning.

SUMMARY: The protein detection and quantification using high-throughput proteomic technologies is still challenging due to the stochastic nature of the peptide selection in the mass spectrometer, the difficulties in the statistical analysis of the results and the presence of degenerated peptides. However, considering in the analysis only those peptides that could be detected by mass spectrometry, also called proteotypic peptides, increases the accuracy of the results. Several approaches have been applied to predict peptide detectability based on the physicochemical properties of the peptides. In this manuscript, we present DeepMSPeptide, a bioinformatic tool that uses a deep learning method to predict proteotypic peptides exclusively based on the peptide amino acid sequences. AVAILABILITY AND IMPLEMENTATION: DeepMSPeptide is available at https://github.com/vsegurar/DeepMSPeptide. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MiTPeptideDB: a proteogenomic resource for the discovery of novel peptides.

MOTIVATION: The principal lines of research in MS/MS based Proteomics have been directed toward the molecular characterization of the proteins including their biological functions and their implications in human diseases. Recent advances in this field have also allowed the first attempts to apply these techniques to the clinical practice. Nowadays, the main progress in Computational Proteomics is based on the integration of genomic, transcriptomic and proteomic experimental data, what is known as Proteogenomics. This methodology is being especially useful for the discovery of new clinical biomarkers, small open reading frames and microproteins, although their validation is still challenging. RESULTS: We detected novel peptides following a proteogenomic workflow based on the MiTranscriptome human assembly and shotgun experiments. The annotation approach generated three custom databases with the corresponding peptides of known and novel transcripts of both protein coding genes and non-coding genes. In addition, we used a peptide detectability filter to improve the computational performance of the proteomic searches, the statistical analysis and the robustness of the results. These innovative additional filters are specially relevant when noisy next generation sequencing experiments are used to generate the databases. This resource, MiTPeptideDB, was validated using 43 cell lines for which RNA-Seq experiments and shotgun experiments were available. AVAILABILITY AND IMPLEMENTATION: MiTPeptideDB is available at http://bit.ly/MiTPeptideDB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm.

The Human Proteome Project (HPP) is leading the international effort to characterize the human proteome. Although the main goal of this project was first focused on the detection of missing proteins, a new challenge arose from the need to assign biological functions to the uncharacterized human proteins and describe their implications in human diseases. Not only the proteins with experimental evidence (uPE1 proteins) but also the uncharacterized missing proteins (uMPs) were the objects of study in this challenge, neXt-CP50. In this work, we developed a new bioinformatic approach to infer biological annotations for the uPE1 proteins and uMPs based on a "guilt-by-association" analysis using public RNA-Seq data sets. We used the correlation of these proteins with the well-characterized PE1 proteins to construct a network. In this way, we applied the PageRank algorithm to this network to identify the most relevant nodes, which were the biological annotations of the uncharacterized proteins. All of the generated information was stored in a database. In addition, we implemented the web application UPEFinder (https://upefinder.proteored.org) to facilitate the access to this new resource. This information is especially relevant for the researchers of the HPP who are interested in the generation and validation of new hypotheses about the functions of these proteins. Both the database and the web application are publicly available (https://github.com/ubioinformat/UPEfinder).

The regulon of the RNA chaperone CspA and its auto-regulation in Staphylococcus aureus.

RNA-binding proteins (RBPs) are essential to fine-tune gene expression. RBPs containing the cold-shock domain are RNA chaperones that have been extensively studied. However, the RNA targets and specific functions for many of them remain elusive. Here, combining comparative proteomics and RBP-immunoprecipitation-microarray profiling, we have determined the regulon of the RNA chaperone CspA of Staphylococcus aureus. Functional analysis revealed that proteins involved in carbohydrate and ribonucleotide metabolism, stress response and virulence gene expression were affected by cspA deletion. Stress-associated phenotypes such as increased bacterial aggregation and diminished resistance to oxidative-stress stood out. Integration of the proteome and targetome showed that CspA post-transcriptionally modulates both positively and negatively the expression of its targets, denoting additional functions to the previously proposed translation enhancement. One of these repressed targets was its own mRNA, indicating the presence of a negative post-transcriptional feedback loop. CspA bound the 5'UTR of its own mRNA disrupting a hairpin, which was previously described as an RNase III target. Thus, deletion of the cspA 5'UTR abrogated mRNA processing and auto-regulation. We propose that CspA interacts through a U-rich motif, which is located at the RNase III cleavage site, portraying CspA as a putative RNase III-antagonist.

Identification of mutations associated with acquired resistance to sunitinib in renal cell cancer.

Sunitinib is one of the most widely used targeted therapeutics for renal cell carcinoma (RCC), but acquired resistance against targeted therapies remains a major clinical challenge. To dissect mechanisms of acquired resistance and unravel reliable predictive biomarkers for sunitinib in RCC, we sequenced the exons of 409 tumor-suppressor genes and oncogenes in paired tumor samples from an RCC patient, obtained at baseline and after development of acquired resistance to sunitinib. From newly arising mutations, we selected, using in silico prediction models, six predicted to be deleterious, located in G6PD, LRP1B, SETD2, TET2, SYNE1, and DCC. Consistently, immunoblotting analysis of lysates derived from sunitinib-desensitized RCC cells and their parental counterparts showed marked differences in the levels and expression pattern of the proteins encoded by these genes. Our further analysis demonstrates essential roles for these proteins in mediating sunitinib cytotoxicity and shows that their loss of function renders tumor cells resistant to sunitinib in vitro and in vivo. Finally, sunitinib resistance induced by continuous exposure or by inhibition of the six proteins was overcome by treatment with cabozantinib or a low-dose combination of lenvatinib and everolimus. Collectively, our results unravel novel markers of acquired resistance to sunitinib and clinically relevant approaches for overcoming this resistance in RCC.

Proteogenomics in the context of the Human Proteome Project (HPP).

INTRODUCTION: The technological and scientific progress performed in the Human Proteome Project (HPP) has provided to the scientific community a new set of experimental and bioinformatic methods in the challenging field of shotgun and SRM/MRM-based Proteomics. The requirements for a protein to be considered experimentally validated are now well-established, and the information about the human proteome is available in the neXtProt database, while targeted proteomic assays are stored in SRMAtlas. However, the study of the missing proteins continues being an outstanding issue. Areas covered: This review is focused on the implementation of proteogenomic methods designed to improve the detection and validation of the missing proteins. The evolution of the methodological strategies based on the combination of different omic technologies and the use of huge publicly available datasets is shown taking the Chromosome 16 Consortium as reference. Expert commentary: Proteogenomics and other strategies of data analysis implemented within the C-HPP initiative could be used as guidance to complete in a near future the catalog of the human proteins. Besides, in the next years, we will probably witness their use in the B/D-HPP initiative to go a step forward on the implications of the proteins in the human biology and disease.

Epigenomic profiling of myelofibrosis reveals widespread DNA methylation changes in enhancer elements and ZFP36L1 as a potential tumor suppressor gene that is epigenetically regulated.

In this study we interrogated the DNA methylome of myelofibrosis patients using high-density DNA methylation arrays. We detected 35,215 differentially methylated CpG, corresponding to 10,253 genes, between myelofibrosis patients and healthy controls. These changes were present both in primary and secondary myelofibrosis, which showed no differences between them. Remarkably, most differentially methylated CpG were located outside gene promoter regions and showed significant association with enhancer regions. This aberrant enhancer hypermethylation was negatively correlated with the expression of 27 genes in the myelofibrosis cohort. Of these, we focused on the ZFP36L1 gene and validated its decreased expression and enhancer DNA hypermethylation in an independent cohort of patients and myeloid cell-lines. In vitro reporter assay and 5'-azacitidine treatment confirmed the functional relevance of hyper-methylation of ZFP36L1 enhancer. Furthermore, in vitro rescue of ZFP36L1 expression had an impact on cell proliferation and induced apoptosis in SET-2 cell line indicating a possible role of ZFP36L1 as a tumor suppressor gene in myelofibrosis. Collectively, we describe the DNA methylation profile of myelofibrosis, identifying extensive changes in enhancer elements and revealing ZFP36L1 as a novel candidate tumor suppressor gene.

Richter transformation driven by Epstein-Barr virus reactivation during therapy-related immunosuppression in chronic lymphocytic leukaemia.

The increased risk of Richter transformation (RT) in patients with chronic lymphocytic leukaemia (CLL) due to Epstein-Barr virus (EBV) reactivation during immunosuppressive therapy with fludarabine other targeted agents remains controversial. Among 31 RT cases classified as diffuse large B-cell lymphoma (DLBCL), seven (23%) showed EBV expression. In contrast to EBV- tumours, EBV+ DLBCLs derived predominantly from IGVH-hypermutated CLL, and they also showed CLL-unrelated IGVH sequences more frequently. Intriguingly, despite having different cellular origins, clonally related and unrelated EBV+ DLBCLs shared a previous history of immunosuppressive chemo-immunotherapy, a non-germinal centre DLBCL phenotype, EBV latency programme type II or III, and very short survival. These data suggested that EBV reactivation during therapy-related immunosuppression can transform either CLL cells or non-tumoural B lymphocytes into EBV+ DLBCL. To investigate this hypothesis, xenogeneic transplantation of blood cells from 31 patients with CLL and monoclonal B-cell lymphocytosis (MBL) was performed in Rag2-/- IL2γc-/- mice. Remarkably, the recipients' impaired immunosurveillance favoured the spontaneous outgrowth of EBV+ B-cell clones from 95% of CLL and 64% of MBL patients samples, but not from healthy donors. Eventually, these cells generated monoclonal tumours (mostly CLL-unrelated but also CLL-related), recapitulating the principal features of EBV+ DLBCL in patients. Accordingly, clonally related and unrelated EBV+ DLBCL xenografts showed indistinguishable cellular, virological and molecular features, and synergistically responded to combined inhibition of EBV replication with ganciclovir and B-cell receptor signalling with ibrutinib in vivo. Our study underscores the risk of RT driven by EBV in CLL patients receiving immunosuppressive therapies, and provides the scientific rationale for testing ganciclovir and ibrutinib in EBV+ DLBCL. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

X-box Binding Protein 1 Regulates Unfolded Protein, Acute-Phase, and DNA Damage Responses During Regeneration of Mouse Liver.

BACKGROUND & AIMS: Liver regeneration after partial hepatectomy (PH) increases the protein folding burden at the endoplasmic reticulum of remnant hepatocytes, resulting in induction of the unfolded protein response. We investigated the role of the core unfolded protein response transcription factor X-box binding protein 1 (XBP1) in liver regeneration using genome-wide chromatin immunoprecipitation analysis. METHODS: We performed studies with C57Bl6-J (control) and interleukin 6-knockout mice. Mice underwent PH or sham surgeries. In some mice, hepatic expression of XBP1 was knocked down by injection of adenoviral vectors encoding small hairpin RNAs against Xbp1 messenger RNA. Liver tissues were collected before surgery and at 6 and 48 hours after surgery and analyzed by chromatin immunoprecipitation followed by sequencing. We also performed functional analyses of HepG2 cells. RESULTS: Expression of XBP1 by hepatocytes increased immediately after PH (priming phase of liver regeneration) in control mice, but this effect was delayed in interleukin 6-deficient mice. In mice with knockdown of XBP1, we observed of liver tissue persistent endoplasmic reticulum stress, defects in acute-phase response, and increased hepatocellular damage, compared with control mice. Chromatin immunoprecipitation analyses of liver tissue showed that at 6 hours after PH, liver XBP1 became bound to a large set of genes implicated in proteostasis, the acute-phase response, metabolism, and the DNA damage response (DDR). At this time point, XBP1 bound the promoter of the signal transducer and activator of transcription 3 gene (Stat3). Livers of XBP1-knockdown mice showed reduced expression of STAT3 and had lower levels of STAT3 phosphorylation at Ser727, a modification that promotes cell proliferation and the DDR. Regenerating livers from XBP1-knockdown mice expressed high levels of a marker of DNA double-strand breaks, phosphorylated histone 2A, member X (H2AX), compared with control mice. The inhibition of XBP1 expression caused a reduced up-regulation of DDR messenger RNAs in regenerating hepatocytes. CONCLUSION: In livers of mice, we found that PH induces expression of XBP1, and that this activity requires interleukin 6. XBP1 expression regulates the unfolded protein response, acute-phase response, and DDR in hepatocytes. In regenerating livers, XBP1 deficiency leads to endoplasmic reticulum stress and DNA damage.

Whole-epigenome analysis in multiple myeloma reveals DNA hypermethylation of B cell-specific enhancers.

While analyzing the DNA methylome of multiple myeloma (MM), a plasma cell neoplasm, by whole-genome bisulfite sequencing and high-density arrays, we observed a highly heterogeneous pattern globally characterized by regional DNA hypermethylation embedded in extensive hypomethylation. In contrast to the widely reported DNA hypermethylation of promoter-associated CpG islands (CGIs) in cancer, hypermethylated sites in MM, as opposed to normal plasma cells, were located outside CpG islands and were unexpectedly associated with intronic enhancer regions defined in normal B cells and plasma cells. Both RNA-seq and in vitro reporter assays indicated that enhancer hypermethylation is globally associated with down-regulation of its host genes. ChIP-seq and DNase-seq further revealed that DNA hypermethylation in these regions is related to enhancer decommissioning. Hypermethylated enhancer regions overlapped with binding sites of B cell-specific transcription factors (TFs) and the degree of enhancer methylation inversely correlated with expression levels of these TFs in MM. Furthermore, hypermethylated regions in MM were methylated in stem cells and gradually became demethylated during normal B-cell differentiation, suggesting that MM cells either reacquire epigenetic features of undifferentiated cells or maintain an epigenetic signature of a putative myeloma stem cell progenitor. Overall, we have identified DNA hypermethylation of developmentally regulated enhancers as a new type of epigenetic modification associated with the pathogenesis of MM.

Long noncoding RNA EGOT negatively affects the antiviral response and favors HCV replication.

The role of long noncoding RNAs (lncRNAs) in viral infection is poorly studied. We have identified hepatitis C virus (HCV)-Stimulated lncRNAs (CSRs) by transcriptome analysis. Interestingly, two of these CSRs (PVT1 and UCA1) play relevant roles in tumorigenesis, providing a novel link between HCV infection and development of liver tumors. Expression of some CSRs seems induced directly by HCV, while others are upregulated by the antiviral response against the virus. In fact, activation of pathogen sensors induces the expression of CSR32/EGOT RIG-I and the RNA-activated kinase PKR sense HCV RNA, activate NF-κB and upregulate EGOT EGOT is increased in the liver of patients infected with HCV and after infection with influenza or Semliki Forest virus (SFV). Genome-wide guilt-by-association studies predict that EGOT may function as a negative regulator of the antiviral pathway. Accordingly, EGOT depletion increases the expression of several interferon-stimulated genes and leads to decreased replication of HCV and SFV Our results suggest that EGOT is a lncRNA induced after infection that increases viral replication by antagonizing the antiviral response.

Enhanced Missing Proteins Detection in NCI60 Cell Lines Using an Integrative Search Engine Approach.

The Human Proteome Project (HPP) aims deciphering the complete map of the human proteome. In the past few years, significant efforts of the HPP teams have been dedicated to the experimental detection of the missing proteins, which lack reliable mass spectrometry evidence of their existence. In this endeavor, an in depth analysis of shotgun experiments might represent a valuable resource to select a biological matrix in design validation experiments. In this work, we used all the proteomic experiments from the NCI60 cell lines and applied an integrative approach based on the results obtained from Comet, Mascot, OMSSA, and X!Tandem. This workflow benefits from the complementarity of these search engines to increase the proteome coverage. Five missing proteins C-HPP guidelines compliant were identified, although further validation is needed. Moreover, 165 missing proteins were detected with only one unique peptide, and their functional analysis supported their participation in cellular pathways as was also proposed in other studies. Finally, we performed a combined analysis of the gene expression levels and the proteomic identifications from the common cell lines between the NCI60 and the CCLE project to suggest alternatives for further validation of missing protein observations.

A new HDV mouse model identifies mitochondrial antiviral signaling protein (MAVS) as a key player in IFN-ß induction.

BACKGROUND & AIMS: Studying hepatitis delta virus (HDV) and developing new treatments is hampered by the limited availability of small animal models. Herein, a description of a robust mouse model of HDV infection that mimics several important characteristics of the human disease is presented. METHODS: HDV and hepatitis B virus (HBV) replication competent genomes were delivered to the mouse liver using adeno-associated viruses (AAV; AAV-HDV and AAV-HBV). Viral load, antigen expression and genomes were quantified at different time points after AAV injection. Furthermore, liver pathology, genome editing, and the activation of the innate immune response were evaluated. RESULTS: AAV-HDV infection initiated HDV replication in mouse hepatocytes. Genome editing was confirmed by the presence of small and large HDV antigens and sequencing. Viral replication was detected for 45days, even after the AAV-HDV vector had almost disappeared. In the presence of HBV, HDV infectious particles were detected in serum. Furthermore, as observed in patients, co-infection was associated with the reduction of HBV antigen expression and the onset of liver damage that included the alteration of genes involved in the development of liver pathologies. HDV replication induced a sustained type I interferon response, which was significantly reduced in immunodeficient mice and almost absent in mitochondrial antiviral signaling protein (MAVS)-deficient mice. CONCLUSION: The animal model described here reproduces important characteristics of human HDV infection and provides a valuable tool for characterizing the viral infection and for developing new treatments. Furthermore, MAVS was identified as a main player in HDV detection and adaptive immunity was found to be involved in the amplification of the innate immune response. Lay summary: Co-infection with hepatitis B and D virus (HBV and HDV, respectively) often causes a more severe disease condition than HBV alone. Gaining more insight into HDV and developing new treatments is hampered by limited availability of adequate immune competent small animal models and new ones are needed. Here, a mouse model of HDV infection is described, which mimics several important characteristics of the human disease, such as the initiation and maintenance of replication in murine hepatocytes, genome editing and, in the presence of HBV, generation of infectious particles. Lastly, the involvement of an adaptive immunity and the intracellular signaling molecule MAVS in mounting a strong and lasting innate response was shown. Thus, our model serves as a useful tool for the investigation of HDV biology and new treatments.

Progress and pitfalls in finding the 'missing proteins' from the human proteome map.

INTRODUCTION: The Human Proteome Project was launched with two main goals: the comprehensive and systematic definition of the human proteome map and the development of ready to use analytical tools to measure relevant proteins in their biological context in health and disease. Despite the great progress in this endeavour, there is still a group of reluctant proteins with no, or scarce, experimental evidence supporting their existence. These are called the 'missing proteins' and represent one of the biggest challenges to complete the human proteome map. Areas covered: This review focuses on the description of the missing proteome based on the HUPO standards, the analysis of the reasons explaining the difficulty of detecting missing proteins and the strategies currently used in the search for missing proteins. The present and future of the quest for the missing proteins is critically revised hereafter. Expert commentary: An overarching multidisciplinary effort is currently being done under the HUPO umbrella to allow completion of the human proteome map. It is expected that the detection of missing proteins will grow in the coming years since the methods and the best tissue/cell type sample for their search are already on the table.

Detection of Missing Proteins Using the PRIDE Database as a Source of Mass Spectrometry Evidence.

The current catalogue of the human proteome is not yet complete, as experimental proteomics evidence is still elusive for a group of proteins known as the missing proteins. The Human Proteome Project (HPP) has been successfully using technology and bioinformatic resources to improve the characterization of such challenging proteins. In this manuscript, we propose a pipeline starting with the mining of the PRIDE database to select a group of data sets potentially enriched in missing proteins that are subsequently analyzed for protein identification with a method based on the statistical analysis of proteotypic peptides. Spermatozoa and the HEK293 cell line were found to be a promising source of missing proteins and clearly merit further attention in future studies. After the analysis of the selected samples, we found 342 PSMs, suggesting the presence of 97 missing proteins in human spermatozoa or the HEK293 cell line, while only 36 missing proteins were potentially detected in the retina, frontal cortex, aorta thoracica, or placenta. The functional analysis of the missing proteins detected confirmed their tissue specificity, and the validation of a selected set of peptides using targeted proteomics (SRM/MRM assays) further supports the utility of the proposed pipeline. As illustrative examples, DNAH3 and TEPP in spermatozoa, and UNCX and ATAD3C in HEK293 cells were some of the more robust and remarkable identifications in this study. We provide evidence indicating the relevance to carefully analyze the ever-increasing MS/MS data available from PRIDE and other repositories as sources for missing proteins detection in specific biological matrices as revealed for HEK293 cells.

Proteogenomic Analysis of Single Amino Acid Polymorphisms in Cancer Research.

The integration of genomics and proteomics has led to the emergence of proteogenomics, a field of research successfully applied to the characterization of cancer samples. The diagnosis, prognosis and response to therapy of cancer patients will largely benefit from the identification of mutations present in their genome. The current state of the art of high throughput experiments for genome-wide detection of somatic mutations in cancer samples has allowed the development of projects such as the TCGA, in which hundreds of cancer genomes have been sequenced. This huge amount of data can be used to generate protein sequence databases in which each entry corresponds to a mutated peptide associated with certain cancer types. In this chapter, we describe a bioinformatics workflow for creating these databases and detecting mutated peptides in cancer samples from proteomic shotgun experiments. The performance of the proposed method has been evaluated using publicly available datasets from four cancer cell lines.

Base pairing interaction between 5'- and 3'-UTRs controls icaR mRNA translation in Staphylococcus aureus.

The presence of regulatory sequences in the 3' untranslated region (3'-UTR) of eukaryotic mRNAs controlling RNA stability and translation efficiency is widely recognized. In contrast, the relevance of 3'-UTRs in bacterial mRNA functionality has been disregarded. Here, we report evidences showing that around one-third of the mapped mRNAs of the major human pathogen Staphylococcus aureus carry 3'-UTRs longer than 100-nt and thus, potential regulatory functions. We selected the long 3'-UTR of icaR, which codes for the repressor of the main exopolysaccharidic compound of the S. aureus biofilm matrix, to evaluate the role that 3'-UTRs may play in controlling mRNA expression. We showed that base pairing between the 3'-UTR and the Shine-Dalgarno (SD) region of icaR mRNA interferes with the translation initiation complex and generates a double-stranded substrate for RNase III. Deletion or substitution of the motif (UCCCCUG) within icaR 3'-UTR was sufficient to abolish this interaction and resulted in the accumulation of IcaR repressor and inhibition of biofilm development. Our findings provide a singular example of a new potential post-transcriptional regulatory mechanism to modulate bacterial gene expression through the interaction of a 3'-UTR with the 5'-UTR of the same mRNA.

Prediction of a missing protein expression map in the context of the human proteome project.

Experimental evidence for the entire human proteome has been defined in the Human Proteome Project, and it is publicly available in the neXtProt database. However, there are still human proteins for which reliable experimental evidence does not exist, and the identification of such information has become one of the overriding objectives in the chromosome-centric study of the human proteome. With this aim and considering the complexity of protein detection using shotgun and targeted proteomics, the research community has addressed the integration of transcriptomics and proteomics landscapes. Here, we describe an analytical pipeline that predicts the probability of a missing protein being expressed in a biological sample based on (1) gene sequence characteristics, (2) the probability of an expressed gene being a coding gene of a missing protein in a certain sample, and (3) the probability of a gene being expressed in a transcriptomic experiment. More than 3400 microarray experiments were analyzed corresponding to three biological sources: cell lines, normal tissues, and cancer samples. A gene classification based on gene expression profiles distinguished among ubiquitous, nonubiquitous, nonexpressed, and coding genes of missing proteins. In addition, a different tissue-specific expression pattern for the coding genes of missing proteins is reported. Our results underline the relevance of selecting an appropriate sample for the detection of missing proteins and provide a comprehensive method to score their expression probability. Testis, brain, and skeletal muscle are the most promising normal tissues.

Proteogenomics Dashboard for the Human Proteome Project.

dasHPPboard is a novel proteomics-based dashboard that collects and reports the experiments produced by the Spanish Human Proteome Project consortium (SpHPP) and aims to help HPP to map the entire human proteome. We have followed the strategy of analog genomics projects like the Encyclopedia of DNA Elements (ENCODE), which provides a vast amount of data on human cell lines experiments. The dashboard includes results of shotgun and selected reaction monitoring proteomics experiments, post-translational modifications information, as well as proteogenomics studies. We have also processed the transcriptomics data from the ENCODE and Human Body Map (HBM) projects for the identification of specific gene expression patterns in different cell lines and tissues, taking special interest in those genes having little proteomic evidence available (missing proteins). Peptide databases have been built using single nucleotide variants and novel junctions derived from RNA-Seq data that can be used in search engines for sample-specific protein identifications on the same cell lines or tissues. The dasHPPboard has been designed as a tool that can be used to share and visualize a combination of proteomic and transcriptomic data, providing at the same time easy access to resources for proteogenomics analyses. The dasHPPboard can be freely accessed at: http://sphppdashboard.cnb.csic.es.