Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes.

Complementing genome sequence with deep transcriptome and proteome data could enable more accurate assembly and annotation of newly sequenced genomes. Here, we provide a proof-of-concept of an integrated approach for analysis of the genome and proteome of Anopheles stephensi, which is one of the most important vectors of the malaria parasite. To achieve broad coverage of genes, we carried out transcriptome sequencing and deep proteome profiling of multiple anatomically distinct sites. Based on transcriptomic data alone, we identified and corrected 535 events of incomplete genome assembly involving 1196 scaffolds and 868 protein-coding gene models. This proteogenomic approach enabled us to add 365 genes that were missed during genome annotation and identify 917 gene correction events through discovery of 151 novel exons, 297 protein extensions, 231 exon extensions, 192 novel protein start sites, 19 novel translational frames, 28 events of joining of exons, and 76 events of joining of adjacent genes as a single gene. Incorporation of proteomic evidence allowed us to change the designation of more than 87 predicted "noncoding RNAs" to conventional mRNAs coded by protein-coding genes. Importantly, extension of the newly corrected genome assemblies and gene models to 15 other newly assembled Anopheline genomes led to the discovery of a large number of apparent discrepancies in assembly and annotation of these genomes. Our data provide a framework for how future genome sequencing efforts should incorporate transcriptomic and proteomic analysis in combination with simultaneous manual curation to achieve near complete assembly and accurate annotation of genomes.

A draft map of the human proteome.

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

Transcriptomic and Proteomic Data Integration and Two-Dimensional Molecular Maps with Regulatory and Functional Linkages: Application to Cell Proliferation and Invasion Networks in Glioblastoma.

Glioblastoma multiforme (GBM), the most aggressive primary brain tumor, is characterized by high rates of cell proliferation, migration, and invasion. New therapeutic strategies and targets are being continuously explored with the hope for better outcome. By overlaying transcriptomic and proteomic data from GBM clinical tissues, we identified 317 differentially expressed proteins to be concordant with the messenger RNAs (mRNAs). We used these entities to generate integrated regulatory information at the level of microRNAs (miRNAs) and their mRNA and protein targets using prediction programs or experimentally verified miRNA target mode in the miRWalk database. We observed 60% or even more of the miRNA-target pairs to be consistent with experimentally observed inverse expression of these molecules in GBM. The integrated view of these regulatory cascades in the contexts of cell proliferation and invasion networks revealed two-dimensional molecular interactions with regulatory and functional linkages (miRNAs and their mRNA-protein targets in one dimension; multiple miRNAs associated in a functional network in the second dimension). A total of 28 of the 35 differentially expressed concordant mRNA-protein entities represented in the proliferation network, and 51 of the 59 such entities represented in the invasion network, mapped to altered miRNAs from GBM and conformed to an inverse relationship in their expression. We believe the two-dimensional maps of gene expression changes enhance the strength of the discovery datasets derived from omics-based studies for their applications in GBM as well as tumors in general.

Insights from Chromosome-Centric Mapping of Disease-Associated Genes: Chromosome 12 Perspective.

In line with the aims of the Chromosome-based Human Proteome Project and the Biology/Disease-based Human Proteome Project, we have been studying differentially expressed transcripts and proteins in gliomas­the most prevalent primary brain tumors. Here, we present a perspective on important insights from this analysis in terms of their co-expression, co-regulation/de-regulation, and co-localization on chromosome 12 (Chr. 12). We observe the following: (1) Over-expression of genes mapping onto amplicon regions of chromosomes may be considered as a biological validation of mass spectrometry data. (2) Their co-localization further suggests common determinants of co-expression and co-regulation of these clusters. (3) Co-localization of "missing" protein genes of Chr. 12 in close proximity to functionally related genes may help in predicting their functions. (4) Further, integrating differentially expressed gene-protein sets and their ontologies with medical terms associated with clinical phenotypes in a chromosome-centric manner reveals a network of genes, diseases, and pathways­a diseasome network. Thus, chromosomal mapping of disease data sets can help uncover important regulatory and functional links that may offer new insights for biomarker development.

Chromosome-centric human proteome project: deciphering proteins associated with glioma and neurodegenerative disorders on chromosome 12.

In line with the aims of the Chromosome-centric Human Proteome Project (C-HPP) to completely annotate proteins of each chromosome and biology/disease driven HPP (B/D-HPP) to decipher their relation to diseases, we have generated a nonredundant catalogue of protein-coding genes for Chromosome 12 (Chr. 12) and further annotated proteins associated with major neurological disorders. Integrating high level proteomic evidence from four major databases (neXtProt, Global Proteome Machine (GPMdb), PeptideAtlas, and Human Protein Atlas (HPA)) along with Ensembl data resource resulted in the identification of 1066 protein coding genes, of which 171 were defined as "missing proteins" based on the weak or complete absence of experimental evidence. With functional annotations using DAVID and GAD, about 40% of the proteins could be grouped as brain related with implications in cancer or neurological disorders. We used published and unpublished high confidence mass spectrometry data from our group and other literature consisting of more than 5000 proteins derived from clinical specimens from patients with human gliomas, Alzheimer's disease, and Parkinson's disease and mapped it onto Chr. 12. We observed a total of 202 proteins mapping to human Chr. 12, 136 of which were differentially expressed in these disease conditions as compared to the normal. Functional grouping indicated their association with cell cycle, cell-to-cell signaling, and other important processes and networks, whereas their disease association analysis confirmed neurological diseases and cancer as the major group along with psycological disorders, with several overexpressed genes/proteins mapping to 12q13-15 amplicon region. Using multiple strategies and bioinformatics tools, we identified 103 differentially expressed proteins to have secretory potential, 17 of which have already been reported in direct analysis of the plasma or cerebrospinal fluid (CSF) from the patients and 21 of them mapped to cancer associated protein (CAPs) database that are amenable to selective reaction monitoring (SRM) assays for targeted proteomic analysis. Our analysis also reveals, for the first time, mass spectrometric evidence for two "missing proteins" from Chr. 12, namely, synaptic vesicle 2-related protein (SVOP) and IQ motif containing D (IQCD). The analysis provides a snapshot of Chr. 12 encoded proteins associated with gliomas and major neurological conditions and their secretability which can be used to drive efforts for clinical applications.

Towards developing biomarkers for glioblastoma multiforme: a proteomics view.

Glioblastoma multiforme (GBM) is one of the most aggressive and lethal forms of the primary brain tumors. With predominance of tumor heterogeneity and emergence of new subtypes, new approaches are needed to develop tissue-based markers for tumor typing or circulatory markers to serve as blood-based assays. Multi-omics data integration for GBM tissues would offer new insights on the molecular view of GBM pathogenesis useful to identify biomarker panels. On the other hand, mapping differentially expressed tissue proteins for their secretory potential through bioinformatics analysis or analysis of the tumor cell secretome or tumor exosomes would enhance our understanding of the tumor microenvironment and prospects for targeting circulatory biomarkers. In this review, the authors first present potential biomarker candidates for GBM that have been reported and then focus on plausible pipelines for multi-omic data integration to identify additional, high-confidence molecular panels for clinical applications in GBM.

Acute Lymphoblastic Leukemia with Myeloid Mutations Is a High-Risk Disease Associated with Clonal Hematopoiesis.

Myeloid neoplasms arise from preexisting clonal hematopoiesis (CH); however, the role of CH in the pathogenesis of acute lymphoblastic leukemia (ALL) is unknown. We found that 18% of adult ALL cases harbored TP53, and 16% had myeloid CH-associated gene mutations. ALL with myeloid mutations (MyM) had distinct genetic and clinical characteristics, associated with inferior survival. By using single-cell proteogenomic analysis, we demonstrated that myeloid mutations were present years before the diagnosis of ALL, and a subset of these clones expanded over time to manifest as dominant clones in ALL. Single-cell RNA sequencing revealed upregulation of genes associated with cell survival and resistance to apoptosis in B-ALL with MyM, which responds better to newer immunotherapeutic approaches. These findings define ALL with MyM as a high-risk disease that can arise from antecedent CH and offer new mechanistic insights to develop better therapeutic and preventative strategies. SIGNIFICANCE: CH is a precursor lesion for lymphoblastic leukemogenesis. ALL with MyM has distinct genetic and clinical characteristics, associated with adverse survival outcomes after chemotherapy. CH can precede ALL years before diagnosis, and ALL with MyM is enriched with activated T cells that respond to immunotherapies such as blinatumomab. See related commentary by Iacobucci, p. 142.

A proteomics sample metadata representation for multiomics integration and big data analysis.

The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.

Identification of a Novel Splice Variant of Neural Cell Adhesion Molecule in Glioblastoma Through Proteogenomics Analysis.

Splice variants are known to be important in the pathophysiology of tumors, including the brain cancers. We applied a proteogenomics pipeline to identify splice variants in glioblastoma (GBM, grade IV glioma), a highly malignant brain tumor, using in-house generated mass spectrometric proteomic data and public domain RNASeq dataset. Our analysis led to the identification of a novel exon that maps to the long isoform of Neural cell adhesion molecule 1 (NCAM1), expressed on the surface of glial cells and neurons, important for cell adhesion and cell signaling. The presence of the novel exon is supported with the identification of five peptides spanning it. Additional peptides were also detected in sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gel separated proteins from GBM patient tissue, underscoring the presence of the novel peptides in the intact brain protein. The novel exon was detected in the RNASeq dataset in 18 of 25 GBM samples and separately validated in additional 10 GBM tumor tissues using quantitative real-time-polymerase chain reaction (qRT-PCR). Both transcriptomic and proteomic data indicate downregulation of NCAM1, including the novel variant, in GBM. Domain analysis of the novel NCAM1 sequence indicates that the insertion of the novel exon contributes extra low-complexity region in the protein that may be important for protein-protein interactions and hence for cell signaling associated with tumor development. Taken together, the novel NCAM1 variant reported in this study exemplifies the importance of future multiomics research and systems biology applications in GBM.

Multi-Omics Data Integration and Mapping of Altered Kinases to Pathways Reveal Gonadotropin Hormone Signaling in Glioblastoma.

Glioblastoma multiforme (GBM) is one of the most lethal brain tumors with an inadequately understood pathophysiology. Biomarkers that guide accurate diagnosis and treatment decisions would greatly support precision medicine for GBM. Previous studies of GBM have focused on signaling pathways such as epidermal growth factor receptor (EGFR), platelet-derived growth factor receptors (PDGFRs), notch, wnt, and others, identified with single omics technology platforms (genomics, transcriptomics, or proteomics), but not with their integrated use. In this context, we report here a multi-omics pathway view, expanded through integration of the expression data at transcriptomic and proteomic levels, followed by selection of a functionally related group of proteins such as kinases deregulated in GBM. By using this strategy, we observed a highly significant enrichment of the gonadotropin-releasing hormone (GnRH) signaling pathway that was not deciphered with single omics datasets. The curation of the GnRH pathway with extensive literature analysis brought about a comprehensive annotation of the pathway, which included several additional pathway members that were not previously annotated. A targeted search resulted in identification of additional nonkinase members of the pathway in the GBM multi-omics datasets. We found evidence of GnRH receptor expression in GBM and other cancers. We offer here an updated generic pathway map of GnRH signaling, show its enrichment in the context of GBM, and discuss its plausible cross-connectivity with EGFR, wnt, calcium, and focal adhesion kinase signaling pathways that were earlier shown to be the top deregulated pathways in GBM. In conclusion, this study demonstrates the promise of multi-omics research and analyses to better understand complex cancers and suggests continued efforts and research in this direction in the field of integrative biology.

A pathway map of glutamate metabolism.

Glutamate metabolism plays a vital role in biosynthesis of nucleic acids and proteins. It is also associated with a number of different stress responses. Deficiency of enzymes involved in glutamate metabolism is associated with various disorders including gyrate atrophy, hyperammonemia, hemolytic anemia, γ-hydoxybutyric aciduria and 5-oxoprolinuria. Here, we present a pathway map of glutamate metabolism representing metabolic intermediates in the pathway, 107 regulator molecules, 9 interactors and 3 types of post-translational modifications. This pathway map provides detailed information about enzyme regulation, protein-enzyme interactions, post-translational modifications of enzymes and disorders due to enzyme deficiency. The information included in the map was based on published experimental evidence reported from mammalian systems.