13 research outputs found

    Curated genome annotation of Oryza sativa ssp. japonica and comparative genome analysis with Arabidopsis thaliana

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    We present here the annotation of the complete genome of rice Oryza sativa L. ssp. japonica cultivar Nipponbare. All functional annotations for proteins and non-protein-coding RNA (npRNA) candidates were manually curated. Functions were identified or inferred in 19,969 (70%) of the proteins, and 131 possible npRNAs (including 58 antisense transcripts) were found. Almost 5000 annotated protein-coding genes were found to be disrupted in insertional mutant lines, which will accelerate future experimental validation of the annotations. The rice loci were determined by using cDNA sequences obtained from rice and other representative cereals. Our conservative estimate based on these loci and an extrapolation suggested that the gene number of rice is ~32,000, which is smaller than previous estimates. We conducted comparative analyses between rice and Arabidopsis thaliana and found that both genomes possessed several lineage-specific genes, which might account for the observed differences between these species, while they had similar sets of predicted functional domains among the protein sequences. A system to control translational efficiency seems to be conserved across large evolutionary distances. Moreover, the evolutionary process of protein-coding genes was examined. Our results suggest that natural selection may have played a role for duplicated genes in both species, so that duplication was suppressed or favored in a manner that depended on the function of a gene

    A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma

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    The mass spectrometry-based peptidomics approaches have proven its usefulness in several areas such as the discovery of physiologically active peptides or biomarker candidates derived from various biological fluids including blood and cerebrospinal fluid. However, to identify biomarkers that are reproducible and clinically applicable, development of a novel technology, which enables rapid, sensitive, and quantitative analysis using hundreds of clinical specimens, has been eagerly awaited. Here we report an integrative peptidomic approach for identification of lung cancer-specific serum peptide biomarkers. It is based on the one-step effective enrichment of peptidome fractions (molecular weight of 1,000–5,000) with size exclusion chromatography in combination with the precise label-free quantification analysis of nano-LC/MS/MS data set using Expressionist proteome server platform. We applied this method to 92 serum samples well-managed with our SOP (standard operating procedure) (30 healthy controls and 62 lung adenocarcinoma patients), and quantitatively assessed the detected 3,537 peptide signals. Among them, 118 peptides showed significantly altered serum levels between the control and lung cancer groups (p<0.01 and fold change >5.0). Subsequently we identified peptide sequences by MS/MS analysis and further assessed the reproducibility of Expressionist-based quantification results and their diagnostic powers by MRM-based relative-quantification analysis for 96 independently prepared serum samples and found that APOA4 273–283, FIBA 5–16, and LBN 306–313 should be clinically useful biomarkers for both early detection and tumor staging of lung cancer. Our peptidome profiling technology can provide simple, high-throughput, and reliable quantification of a large number of clinical samples, which is applicable for diverse peptidome-targeting biomarker discoveries using any types of biological specimens

    Citrullination of RGG Motifs in FET Proteins by PAD4 Regulates Protein Aggregation and ALS Susceptibility

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    Summary: Recent proteome analyses have provided a comprehensive overview of various posttranslational modifications (PTMs); however, PTMs involving protein citrullination remain unclear. We performed a proteomic analysis of citrullinated proteins, and we identified more than 100 PAD4 (peptidyl arginine deiminase 4) substrates. Approximately one-fifth of the PAD4 substrates contained an RG/RGG motif, and PAD4 competitively inhibited the methylation of the RGG motif in FET proteins (FUS, EWS, and TAF15) and hnRNPA1, which are causative genes for ALS (amyotrophic lateral sclerosis). PAD4-mediated citrullination significantly inhibited the aggregation of FET proteins, a frequently observed feature in neurodegenerative diseases. FUS protein levels in arsenic-induced stress granules were significantly increased in Padi4−/− mouse embryonic fibroblasts (MEFs). Moreover, rs2240335 was associated with low expression of PADI4 in the brain and a high risk of ALS (p = 0.0381 and odds ratio of 1.072). Our findings suggest that PAD4-mediated RGG citrullination plays a key role in protein solubility and ALS pathogenesis

    Plasma Low-Molecular-Weight Proteome Profiling Identified Neuropeptide‑Y as a Prostate Cancer Biomarker Polypeptide

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    In prostate cancer diagnosis, PSA test has greatly contributed to the early detection of prostate cancer; however, expanding overdiagnosis and unnecessary biopsies have emerged as serious issues. To explore plasma biomarkers complementing the specificity of PSA test, we developed a unique proteomic technology QUEST-MS (Quick Enrichment of Small Targets for Mass Spectrometry). The QUEST-MS method based on 96-well formatted sequential reversed-phase chromatography allowing efficient enrichment of <20 kDa proteins quickly and reproducibly. Plasma from 24 healthy controls, 19 benign prostate hypertrophy patients, and 73 prostate cancer patients were purified with QUEST-MS and analyzed by LC/MS/MS. Among 153 057 nonredundant peptides, 189 peptides showed prostate cancer specific detection pattern, which included a neurotransmitter polypeptide neuropeptide-Y (NPY). We further validated the screening results by targeted multiple reaction monitoring technology using independent sample set (<i>n</i> = 110). The ROC curve analysis revealed that logistic regression-based combination of NPY, and PSA showed 81.5% sensitivity and 82.2% specificity for prostate cancer diagnosis. Thus QUEST-MS technology allowed comprehensive and high-throughput profiling of plasma polypeptides and had potential to effectively uncover very low abundant tumor-derived small molecules, such as neurotransmitters, peptide hormones, or cytokines

    Plasma Low-Molecular-Weight Proteome Profiling Identified Neuropeptide‑Y as a Prostate Cancer Biomarker Polypeptide

    No full text
    In prostate cancer diagnosis, PSA test has greatly contributed to the early detection of prostate cancer; however, expanding overdiagnosis and unnecessary biopsies have emerged as serious issues. To explore plasma biomarkers complementing the specificity of PSA test, we developed a unique proteomic technology QUEST-MS (Quick Enrichment of Small Targets for Mass Spectrometry). The QUEST-MS method based on 96-well formatted sequential reversed-phase chromatography allowing efficient enrichment of <20 kDa proteins quickly and reproducibly. Plasma from 24 healthy controls, 19 benign prostate hypertrophy patients, and 73 prostate cancer patients were purified with QUEST-MS and analyzed by LC/MS/MS. Among 153 057 nonredundant peptides, 189 peptides showed prostate cancer specific detection pattern, which included a neurotransmitter polypeptide neuropeptide-Y (NPY). We further validated the screening results by targeted multiple reaction monitoring technology using independent sample set (<i>n</i> = 110). The ROC curve analysis revealed that logistic regression-based combination of NPY, and PSA showed 81.5% sensitivity and 82.2% specificity for prostate cancer diagnosis. Thus QUEST-MS technology allowed comprehensive and high-throughput profiling of plasma polypeptides and had potential to effectively uncover very low abundant tumor-derived small molecules, such as neurotransmitters, peptide hormones, or cytokines

    The Rice Annotation Project Database (RAP-DB): 2008 update

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    The Rice Annotation Project Database (RAP-DB) was created to provide the genome sequence assembly of the International Rice Genome Sequencing Project (IRGSP), manually curated annotation of the sequence, and other genomics information that could be useful for comprehensive understanding of the rice biology. Since the last publication of the RAP-DB, the IRGSP genome has been revised and reassembled. In addition, a large number of rice-expressed sequence tags have been released, and functional genomics resources have been produced worldwide. Thus, we have thoroughly updated our genome annotation by manual curation of all the functional descriptions of rice genes. The latest version of the RAP-DB contains a variety of annotation data as follows: clone positions, structures and functions of 31 439 genes validated by cDNAs, RNA genes detected by massively parallel signature sequencing (MPSS) technology and sequence similarity, flanking sequences of mutant lines, transposable elements, etc. Other annotation data such as Gnomon can be displayed along with those of RAP for comparison. We have also developed a new keyword search system to allow the user to access useful information. The RAP-DB is available at: http://www.w3.org/1999/ http://rapdb.dna.affrc.go.jp/ and http://rapdb.lab.nig.ac.jp/
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