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1.
BMC Bioinformatics ; 15: 179, 2014 Jun 10.
Article in English | MEDLINE | ID: mdl-24917541

ABSTRACT

BACKGROUND: Understanding the molecular mechanisms involved in disease is critical for the development of more effective and individualized strategies for prevention and treatment. The amount of disease-related literature, including new genetic information on the molecular mechanisms of disease, is rapidly increasing. Extracting beneficial information from literature can be facilitated by computational methods such as the knowledge-discovery approach. Several methods for mining gene-disease relationships using computational methods have been developed, however, there has been a lack of research evaluating specific disease candidate genes. RESULTS: We present a novel method for gathering and prioritizing specific disease candidate genes. Our approach involved the construction of a set of Medical Subject Headings (MeSH) terms for the effective retrieval of publications related to a disease candidate gene. Information regarding the relationships between genes and publications was obtained from the gene2pubmed database. The set of genes was prioritized using a "weighted literature score" based on the number of publications and weighted by the number of genes occurring in a publication. Using our method for the disease states of pain and Alzheimer's disease, a total of 1101 pain candidate genes and 2810 Alzheimer's disease candidate genes were gathered and prioritized. The precision was 0.30 and the recall was 0.89 in the case study of pain. The precision was 0.04 and the recall was 0.6 in the case study of Alzheimer's disease. The precision-recall curve indicated that the performance of our method was superior to that of other publicly available tools. CONCLUSIONS: Our method, which involved the use of a set of MeSH terms related to disease candidate genes and a novel weighted literature score, improved the accuracy of gathering and prioritizing candidate genes by focusing on a specific disease.


Subject(s)
Computational Biology/methods , Databases, Factual , Gene Expression Regulation , Medical Subject Headings , Alzheimer Disease/genetics , Animals , Humans , Pain/genetics
2.
Biol Pharm Bull ; 32(3): 354-8, 2009 Mar.
Article in English | MEDLINE | ID: mdl-19252277

ABSTRACT

A comprehensive gene-expression analysis during platelet (PLT) production from megakaryocytes may give important information on genes involved in the PLT production process. However, the low abundance of primary megakaryocytes makes the gene expression analysis difficult. Therefore, we employed MEG-01 cells, a human megakaryocytic cell line, and confirmed that the cell line produces PLT-like particles by treatment with phorbol myristate acetate (PMA). After treatment of MEG-01 cells with PMA for 8 or 24 h, comprehensive gene expression analysis was carried out using a microarray and Reverse Transcription-Polymerase Chain Reaction (RT-PCR). From the microarray analysis, 141 genes were up-regulated (>2-fold) and 164 genes were down-regulated (<1/2-fold). However, known PLT-related genes were not included in the up- or down-regulated genes. On the other hand, RT-PCR analysis detected increased expression of beta1-tubulin, CD62P, gpIbalpha and gpIII, which are related to PLT function and megakaryocyte differentiation, following PMA treatment for 24 h. These results indicate that the MEG-01 cell may be an alternative model system to study the process of human PLT production from megakaryocytes. The gene-expression analysis might be a powerful tool for identifying genes related to PLT production, if the experimental conditions are optimized.


Subject(s)
Blood Platelets/cytology , Gene Expression Profiling , Megakaryocytes/drug effects , Tetradecanoylphorbol Acetate/pharmacology , Cell Line , Humans , Megakaryocytes/cytology , Megakaryocytes/metabolism , Oligonucleotide Array Sequence Analysis , Reverse Transcriptase Polymerase Chain Reaction
3.
Stem Cells ; 25(4): 862-70, 2007 Apr.
Article in English | MEDLINE | ID: mdl-17420226

ABSTRACT

Murine megakaryocytes (MKs) are defined by CD41/CD61 expression and acetylcholinesterase (AChE) activity; however, their stages of differentiation in bone marrow (BM) have not been fully elucidated. In murine lineage-negative (Lin(-))/CD45(+) BM cells, we found CD41(+) MKs without AChE activity (AChE(-)) except for CD41(++) MKs with AChE activity (AChE(+)), in which CD61 expression was similar to their CD41 level. Lin(-)/CD41(+)/CD45(+)/AChE(-) MKs could differentiate into AChE(+), with an accompanying increase in CD41/CD61 during in vitro culture. Both proplatelet formation (PPF) and platelet (PLT) production for Lin(-)/CD41(+)/CD45(+)/AChE(-) MKs were observed later than for Lin(-)/CD41(++)/CD45(+)/AChE(+) MKs, whereas MK progenitors were scarcely detected in both subpopulations. GeneChip and semiquantitative polymerase chain reaction analyses revealed that the Lin(-)/CD41(+)/CD45(+)/AChE(-) MKs are assigned at the stage between the progenitor and PPF preparation phases in respect to the many MK/PLT-specific gene expressions, including beta1-tubulin. In normal mice, the number of Lin(-)/CD41(+)/CD45(+)/AChE(-) MKs was 100 times higher than that of AChE(+) MKs in BM. When MK destruction and consequent thrombocytopenia were caused by an antitumor agent, mitomycin-C, Lin(-)/CD41(+)/CD45(+)/AChE(-) MKs led to an increase in AChE(+) MKs and subsequent PLT recovery with interleukin-11 administration. It was concluded that MKs in murine BM at least in part consist of immature Lin(-)/CD41(+)/CD45(+)/AChE(-) MKs and more differentiated Lin(-)/CD41(++)/CD45(+)/AChE(+) MKs. Immature Lin(-)/CD41(+)/CD45(+)/AChE(-) MKs are a major MK population compared with AChE(+) MKs in BM and play an important role in rapid PLT recovery in vivo.


Subject(s)
Acetylcholinesterase/analysis , Leukocyte Common Antigens/genetics , Megakaryocytes/cytology , Megakaryocytes/immunology , Platelet Membrane Glycoprotein IIb/genetics , Animals , Biomarkers/analysis , Bone Marrow Cells/cytology , Bone Marrow Cells/immunology , Cell Culture Techniques , Colony-Forming Units Assay , Gene Expression Profiling , Male , Mice , Mice, Inbred BALB C , Polymerase Chain Reaction
4.
Genomics Proteomics Bioinformatics ; 4(4): 238-44, 2006 Nov.
Article in English | MEDLINE | ID: mdl-17531799

ABSTRACT

Understanding the coupling specificity between G protein-coupled receptors (GPCRs) and specific classes of G proteins is important for further elucidation of receptor functions within a cell. Increasing information on GPCR sequences and the G protein family would facilitate prediction of the coupling properties of GPCRs. In this study, we describe a novel approach for predicting the coupling specificity between GPCRs and G proteins. This method uses not only GPCR sequences but also the functional knowledge generated by natural language processing, and can achieve 92.2% prediction accuracy by using the C4.5 algorithm. Furthermore, rules related to GPCR-G protein coupling are generated. The combination of sequence analysis and text mining improves the prediction accuracy for GPCR-G protein coupling specificity, and also provides clues for understanding GPCR signaling.


Subject(s)
GTP-Binding Proteins/metabolism , Models, Theoretical , Receptors, G-Protein-Coupled/metabolism , Protein Binding , Sequence Analysis, Protein
5.
Clin Exp Pharmacol Physiol ; 32(5-6): 355-66, 2005.
Article in English | MEDLINE | ID: mdl-15854142

ABSTRACT

1. We have confirmed the Diabetes Mellitus OLETF type I (Dmo1) effect on hyperphagia, dyslipidaemia and obesity in the Otsuka Long-Evans Tokushima Fatty (OLETF) strain. The critical interval was narrowed down to 570 kb between D1Got258 to p162CA1 by segregation analyses using congenic lines. 2. Within the critical 570 kb region of the Dmo1 locus, we identified the G-protein-coupled receptor gene GPR10 as the causative gene mutated in the OLETF strain. The ATG translation initiation codon of GPR10 is changed into ATA in this strain and, so, is unavailable for the initiation of translation. 3. The GPR10 protein has a cognate ligand, namely prolactin-releasing peptide (PrRP). Centrally administered PrRP suppressed the food intake of congenic rats that have a Brown Norway derived Dmo1 region (i.e. with wild-type GPR10), but did not suppress that of the OLETF strain, indicating that GPR10 is without function and could explain hyperphagia in the OLETF strain. 4. Moreover, when restricted in food volume to the same level consumed by the congenic strain, OLETF rats showed few differences in the parameters of dyslipidaemia and obesity compared with congenic strains. 5. Taken together, these results demonstrate that the mutated GPR10 receptor is responsible for the hyperphagia leading to obesity and dyslipidaemia in the obese diabetic strain rat.


Subject(s)
Dyslipidemias/genetics , Hyperphagia/genetics , Mutation/genetics , Obesity/genetics , Quantitative Trait Loci/genetics , Receptors, G-Protein-Coupled/genetics , Animals , Base Sequence/genetics , Genotype , Male , Rats , Rats, Inbred BN , Rats, Inbred OLETF , Species Specificity
6.
Clin Exp Pharmacol Physiol ; 31(1-2): 110-2, 2004.
Article in English | MEDLINE | ID: mdl-14756694

ABSTRACT

1. Dmo1 (Diabetes Mellitus OLETF type I) is a major quantitative trait locus for dyslipidaemia, obesity and diabetes phenotypes of male Otsuka Long Evans Tokushima Fatty (OLETF) rats. 2. Our congenic lines, produced by transferring Dmo1 chromosomal segments from the non-diabetic Brown Norway (BN) rat into the OLETF strain, have confirmed the strong, wide-range therapeutic effects of Dmo1 on dyslipidaemia, obesity and diabetes in the fourth (BC4) and fifth (BC5) generations of congenic animals. Analysis of a relatively small number of BC5 rats (n = 71) suggested that the critical Dmo1 interval lies within a < 4.9 cM region between D1Rat461 and D1Rat459. 3. To confirm the assignment of the Dmo1 critical interval, we intercrossed BC5 animals to produce a larger study population (BC5:F1 males; n = 406). For the present study, we used bodyweight at 18 weeks of age as an index of obesity; this phenotype is representative of the closely associated dyslipidaemia and hyperglycaemia phenotypes. 4. Interval mapping assigned logarithm of odds (LOD) peaks at the D1Rat90 marker (LOD = 9.11). One LOD support interval lies within the < 1.7 cM region between D1Rat461 and D1Rat459. 5. This large intercross study confirms that Dmo1 is likely localized within the interval.


Subject(s)
Diabetes Mellitus/genetics , Obesity , Animals , Animals, Congenic , Body Weight/genetics , Crosses, Genetic , Female , Hyperglycemia/genetics , Hyperlipidemias/blood , Hyperlipidemias/genetics , Male , Phenotype , Rats , Rats, Inbred BN , Rats, Inbred OLETF
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