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PubMed2006

bioNMF: a versatile tool for non-negative matrix factorization in biology.

BACKGROUND: In the Bioinformatics field, a great deal of interest has been given to Non-negative matrix factorization technique (NMF), due to its capability of providing new insights and relevant information about the complex latent relationships in experimental data sets. This method, and some of its variants, has been successfully applied to gene expression, sequence analysis, functional characterization of genes and text mining. Even if the interest on this technique by the bioinformatics community has been increased during the last few years, there are not many available simple standalone tools to specifically perform these types of data analysis in an integrated environment. RESULTS: In this work we propose a versatile and user-friendly tool that implements the NMF methodology in different analysis contexts to support some of the most important reported applications of this new methodology. This includes clustering and biclustering gene expression data, protein sequence analysis, text mining of biomedical literature and sample classification using gene expression. The tool, which is named bioNMF, also contains a user-friendly graphical interface to explore results in an interactive manner and facilitate in this way the exploratory data analysis process. CONCLUSION: bioNMF is a standalone versatile application which does not require any special installation or libraries. It can be used for most of the multiple applications proposed in the bioinformatics field or to support new research using this method. This tool is publicly available at http://www.dacya.ucm.es/apascual/bioNMF.

Algorithms↗

PubMed2006

MultiSeq: unifying sequence and structure data for evolutionary analysis.

BACKGROUND: Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. RESULTS: Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. CONCLUSION: MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural visualization program for analyzing molecular dynamics simulations. Both are freely distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics and MultiSeq is included with VMD starting with version 1.8.5. The MultiSeq website has details on how to download and use the software: http://www.scs.uiuc.edu/~schulten/multiseq/

Algorithms↗

PubMed2006

Verification of predicted alternatively spliced Wnt genes reveals two new splice variants (CTNNB1 and LRP5) and altered Axin-1 expression during tumour progression.

BACKGROUND: Splicing processes might play a major role in carcinogenesis and tumour progression. The Wnt pathway is of crucial relevance for cancer progression. Therefore we focussed on the Wnt/beta-catenin signalling pathway in order to validate the expression of sequences predicted as alternatively spliced by bioinformatic methods. Splice variants of its key molecules were selected, which may be critical components for the understanding of colorectal tumour progression and may have the potential to act as biological markers. For some of the Wnt pathway genes the existence of splice variants was either proposed (e.g. beta-Catenin and CTNNB1) or described only in non-colon tissues (e.g. GSK3beta) or hitherto not published (e.g. LRP5). RESULTS: Both splice variants--normal and alternative form--of all selected Wnt pathway components were found to be expressed in cell lines as well as in samples derived from tumour, normal and healthy tissues. All splice positions corresponded totally with the bioinformatical prediction as shown by sequencing. Two hitherto not described alternative splice forms (CTNNB1 and LRP5) were detected. Although the underlying EST data used for the bioinformatic analysis suggested a tumour-specific expression neither a qualitative nor a significant quantitative difference between the expression in tumour and healthy tissues was detected. Axin-1 expression was reduced in later stages and in samples from carcinomas forming distant metastases. CONCLUSION: We were first to describe that splice forms of crucial genes of the Wnt-pathway are expressed in human colorectal tissue. Newly described splicefoms were found for beta-Catenin, LRP5, GSK3beta, Axin-1 and CtBP1. However, the predicted cancer specificity suggested by the origin of the underlying ESTs was neither qualitatively nor significant quantitatively confirmed. That let us to conclude that EST sequence data can give adequate hints for the existence of alternative splicing in tumour tissues. That no difference in the expression of these splice forms between cancerous tissues and normal mucosa was found, may indicate that the existence of different splice forms is of less significance for cancer formation as suggested by the available EST data. The currently available EST source is still insufficient to clearly deduce colon cancer specificity. More EST data from colon (tumour and healthy) is required to make reliable predictions.

Aged↗

PubMed2006

Genome Annotation Transfer Utility (GATU): rapid annotation of viral genomes using a closely related reference genome.

BACKGROUND: Since DNA sequencing has become easier and cheaper, an increasing number of closely related viral genomes have been sequenced. However, many of these have been deposited in GenBank without annotations, severely limiting their value to researchers. While maintaining comprehensive genomic databases for a set of virus families at the Viral Bioinformatics Resource Center http://www.biovirus.org and Viral Bioinformatics - Canada http://www.virology.ca, we found that researchers were unnecessarily spending time annotating viral genomes that were close relatives of already annotated viruses. We have therefore designed and implemented a novel tool, Genome Annotation Transfer Utility (GATU), to transfer annotations from a previously annotated reference genome to a new target genome, thereby greatly reducing this laborious task. RESULTS: GATU transfers annotations from a reference genome to a closely related target genome, while still giving the user final control over which annotations should be included. GATU also detects open reading frames present in the target but not the reference genome and provides the user with a variety of bioinformatics tools to quickly determine if these ORFs should also be included in the annotation. After this process is complete, GATU saves the newly annotated genome as a GenBank, EMBL or XML-format file. The software is coded in Java and runs on a variety of computer platforms. Its user-friendly Graphical User Interface is specifically designed for users trained in the biological sciences. CONCLUSION: GATU greatly simplifies the initial stages of genome annotation by using a closely related genome as a reference. It is not intended to be a gene prediction tool or a "complete" annotation system, but we have found that it significantly reduces the time required for annotation of genes and mature peptides as well as helping to standardize gene names between related organisms by transferring reference genome annotations to the target genome. The program is freely available under the General Public License and can be accessed along with documentation and tutorial from http://www.virology.ca/gatu.

Amino Acid Sequence↗

PubMed2006

The DtxR protein acting as dual transcriptional regulator directs a global regulatory network involved in iron metabolism of Corynebacterium glutamicum.

BACKGROUND: The knowledge about complete bacterial genome sequences opens the way to reconstruct the qualitative topology and global connectivity of transcriptional regulatory networks. Since iron is essential for a variety of cellular processes but also poses problems in biological systems due to its high toxicity, bacteria have evolved complex transcriptional regulatory networks to achieve an effective iron homeostasis. Here, we apply a combination of transcriptomics, bioinformatics, in vitro assays, and comparative genomics to decipher the regulatory network of the iron-dependent transcriptional regulator DtxR of Corynebacterium glutamicum. RESULTS: A deletion of the dtxR gene of C. glutamicum ATCC 13032 led to the mutant strain C. glutamicum IB2103 that was able to grow in minimal medium only under low-iron conditions. By performing genome-wide DNA microarray hybridizations, differentially expressed genes involved in iron metabolism of C. glutamicum were detected in the dtxR mutant. Bioinformatics analysis of the genome sequence identified a common 19-bp motif within the upstream region of 31 genes, whose differential expression in C. glutamicum IB2103 was verified by real-time reverse transcription PCR. Binding of a His-tagged DtxR protein to oligonucleotides containing the 19-bp motifs was demonstrated in vitro by DNA band shift assays. At least 64 genes encoding a variety of physiological functions in iron transport and utilization, in central carbohydrate metabolism and in transcriptional regulation are controlled directly by the DtxR protein. A comparison with the bioinformatically predicted networks of C. efficiens, C. diphtheriae and C. jeikeium identified evolutionary conserved elements of the DtxR network. CONCLUSION: This work adds considerably to our currrent understanding of the transcriptional regulatory network of C. glutamicum genes that are controlled by DtxR. The DtxR protein has a major role in controlling the expression of genes involved in iron metabolism and exerts a dual regulatory function as repressor of genes participating in iron uptake and utilization and as activator of genes responsible for iron storage and DNA protection. The data suggest that the DtxR protein acts as global regulator by controlling the expression of other regulatory proteins that might take care of an iron-dependent regulation of a broader transcriptional network of C. glutamicum genes.

Bacterial Proteins↗

PubMed2006

Gbrowse Moby: a Web-based browser for BioMoby Services.

BACKGROUND: The BioMoby project aims to identify and deploy standards and conventions that aid in the discovery, execution, and pipelining of distributed bioinformatics Web Services. As of August, 2006, approximately 680 bioinformatics resources were available through the BioMoby interoperability platform. There are a variety of clients that can interact with BioMoby-style services. Here we describe a Web-based browser-style client--Gbrowse Moby--that allows users to discover and "surf" from one bioinformatics service to the next using a semantically-aided browsing interface. RESULTS: Gbrowse Moby is a low-throughput, exploratory tool specifically aimed at non-informaticians. It provides a straightforward, minimal interface that enables a researcher to query the BioMoby Central web service registry for data retrieval or analytical tools of interest, and then select and execute their chosen tool with a single mouse-click. The data is preserved at each step, thus allowing the researcher to manually "click" the data from one service to the next, with the Gbrowse Moby application managing all data formatting and interface interpretation on their behalf. The path of manual exploration is preserved and can be downloaded for import into automated, high-throughput tools such as Taverna. Gbrowse Moby also includes a robust data rendering system to ensure that all new data-types that appear in the BioMoby registry can be properly displayed in the Web interface. CONCLUSION: Gbrowse Moby is a robust, yet facile entry point for both newcomers to the BioMoby interoperability project who wish to manually explore what is known about their data of interest, as well as experienced users who wish to observe the functionality of their analytical workflows prior to running them in a high-throughput environment.

Journal Article↗

PubMed2026

Molecular residual disease assessment in colorectal and bladder cancer by somatic structural variant analysis of cell-free DNA whole-genome sequencing data.

BACKGROUND: Whole-genome sequencing (WGS)-based methods for circulating tumor DNA (ctDNA) detection typically rely on tumor-informed identification of somatic single nucleotide variants (SNVs). Somatic structural variants (SVs) are another type of cancer-specific genomic alteration, which owing to their larger genomic footprint and unique breakpoint junctions, are easier to distinguish from sequencing noise than SNVs. They are, however, rarely used for ctDNA detection because of (1) artifacts from WGS procedures that SV callers may falsely interpret as genuine SVs. This makes it difficult to establish high-confidence SV catalogos from short-read tumor WGS and can cause false-positive ctDNA detections. (2) Lack of robust strategies to quantify SV-supporting reads in plasma WGS. To address these barriers and enable integration of SV biomarkers into WGS-based ctDNA detection, we present a bioinformatic framework for algorithmic curation of somatic SV calls from fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tumors, coupled with a novel approach for sensitive, accurate mapping and quantification of SV breakpoint-supporting reads in plasma WGS. METHODS: Tumor, normal and plasma WGS data from 144 patients with stage III colorectal cancer was used to establish the bioinformatic framework. This included ~30x WGS data from 1564 serially collected plasma samples. The framework was validated using tumor/normal/plasma WGS data from 32 patients with muscle-invasive bladder cancer. SV-based ctDNA detection was benchmarked against previously published SNV-based ctDNA results for the same samples. RESULTS: After curation of SV calls and quantification in plasma WGS, our SV-based approach enabled robust ctDNA detection with overall specificity exceeding 99% in plasma samples. Furthermore, we observed strong concordance (Pearson’s r > 0.93, p < 2.2 × 10− 16) between ctDNA-positive samples identified by our SV-based method and previous SNV-based analyses, validating the reliability of our approach. Finally, we demonstrated application of the method in an independent bladder cancer cohort, highlighting its generalizability and potential clinical use. CONCLUSIONS: We provide a bioinformatic framework that establishes somatic SVs as ultra-specific biomarkers for WGS-based, tumor-informed ctDNA detection. The approach delivers specific detection even when the SV catalogos are established from FFPE samples. The SV framework can stand alone or enhance SNV-based analysis pipelines.

Humans↗

PubMed2001

EBI databases and services.

The EMBL Outstation-European Bioinformatics Institute (EBI) is a center for research and services in bioinformatics. It serves researchers in molecular biology, genetics, medicine, and agriculture from academia, and the agricultural, biotechnology, chemical, and pharmaceutical industries. The Institute manages and makes available databases of biological data including nucleic acid, protein sequences, and macromolecular structures. It provides to this community bioinformatics services relevant to molecular biology free of charge over the Internet. Some of these databases and services are described in this review.

Computational Biology↗

PubMed2006

The role of transglutaminase-2 and its substrates in human diseases.

The most characteristic enzymatic function of the class of enzymes known as transglutaminases (TG, EC 2.3.2.13) is the formation of covalent bonds between epsilon-amino groups of primary amines (from lysines or others) and the gamma-carboxamine group of glutamine residues of proteins. In the last years, a growing body of evidence indicate that the most interesting member of the TG family, namely the tissue TG (tTG, also called transglutaminase type 2, TG2), possesses more than one catalytic function. In fact, TG2 is able to catalyze a crosslinking reaction, a deamidation reaction and also shows GTP-binding/hydrolyzing and isopeptidase activities. Therefore, it can act on several classes of substrates, ranging from proteins to peptides, small reactive molecules like mono- and polyamines, and nucleotides. Given the broad spectrum of potentially different activities, elucidating the role of TG2 and its substrates in cellular functions and human diseases is a difficult task. In this study we focus our attention on substrates of TG2 and report a number of interesting considerations about their possible interplay in biological processes and involvement in human diseases, including genetic disorders. A significant improvement in understanding this complex scenario may come from a "multi-interfaced" approach, by exploiting different bioinformatic tools. Starting from a database of known TG2 substrates and using bioinformatic cross-search among other databases, we generated relational tables from which an involvement of TG2 in several genetic disorders can be hypothesized. Developing new bioinformatic tools and strategies to investigate the role of TG2 in molecular mechanisms underlying human diseases will add new light to this fascinating field of research.

Autoimmune Diseases↗

PubMed2005

Transactivating effect of complete S protein of hepatitis B virus and cloning of genes transactivated by complete S protein using suppression subtractive hybridization technique.

AIM: To investigate the transactivating effect of complete S protein of hepatitis B virus (HBV) and to construct a subtractive cDNA library of genes transactivated by complete S protein of HBV by suppression subtractive hybridization (SSH) technique and to clone genes associated with its transactivation activity, and to pave the way for elucidating the pathogenesis of hepatitis B virus infection. METHODS: pcDNA3.1(-)-complete S containing full-length HBV S gene was constructed by insertion of HBV complete S gene into BamH I/Kpn I sites. HepG2 cells were cotransfected with pcDNA3.1(-)-complete S and pSV-lacZ. After 48 h, cells were collected and detected for the expression of beta-galactosidase (beta-gal). Suppression subtractive hybridization and bioinformatics techniques were used. The mRNA of HepG2 cells transfected with pcDNA3.1(-)-complete S and pcDNA3.1(-) empty vector was isolated, and detected for the expression of complete S protein by reverse transcription polymerase chain reaction (RT-PCR) method, and cDNA was synthesized. After digestion with restriction enzyme RsaI, cDNA fragments were obtained. Tester cDNA was then divided into two groups and ligated to the specific adaptors 1 and 2, respectively. After tester cDNA had been hybridized with driver cDNA twice and underwent nested PCR twice, amplified cDNA fragments were subcloned into pGEM-Teasy vectors to set up the subtractive library. Amplification of the library was carried out within E. coli strain DH5alpha. The cDNA was sequenced and analyzed in GenBank with BLAST search after polymerase chain reaction (PCR) amplification. RESULTS: The complete S mRNA could be detected by RT-PCR in HepG2 cells transfected with the pcDNA3.1(-)-complete S. The activity of beta-gal in HepG2 cells transfected with the pcDNA3.1(-)-complete S was 6.9 times higher than that of control plasmid. The subtractive library of genes transactivated by HBV complete S protein was constructed successfully. The amplified library contains 86 positive clones. Colony PCR showed that 86 clones contained DNA inserts of 200-1 000 bp, respectively. Sequence analysis was performed in 35 clones randomly, and the full length sequences were obtained with bioinformatics method and searched for homologous DNA sequence from GenBank, altogether 33 coding sequences were obtained. These cDNA sequences might be target genes transactivated by complete S protein of HBV. Moreover, two unknown genes were discovered, full length coding sequences were obtained by bioinformatics techniques, one of them was named complete S transactivated protein 1 (CSTP1) and registered in GenBank (AY553877). CONCLUSION: The complete S gene of HBV has a transactivating effect on SV40 early promoter. A subtractive cDNA library of genes transactivated by HBV complete S protein using SSH technique has been constructed successfully. The obtained sequences may be target genes transactivated by HBV complete S protein among which some genes coding proteins are involved in cell cycle regulation, metabolism, immunity, signal transduction, cell apoptosis and formation mechanism of hepatic carcinoma.

Cell Line, Tumor↗

PubMed2002

Proteomic approaches to tumor marker discovery.

CONTEXT: Current tumor markers for ovarian cancer still lack adequate sensitivity and specificity to be applicable in large populations. High-throughput proteomic profiling and bioinformatics tools allow for the rapid screening of a large number of potential biomarkers in serum, plasma, or other body fluids. OBJECTIVE: To determine whether protein profiles of plasma can be used to identify potential biomarkers that improve the detection of ovarian cancer. DESIGN: We analyzed plasma samples that had been collected between 1998 and 2001 from patients with sporadic ovarian serous neoplasms before tumor resection at various International Federation of Gynecology and Obstetrics stages (stage I [n = 11], stage II [n = 3], and stage III [n = 29]) and from women without known neoplastic disease (n = 38) using proteomic profiling and bioinformatics. We compared results between the patients with and without cancer and evaluated their discriminatory performance against that of the cancer antigen 125 (CA125) tumor marker. RESULTS: We selected 7 biomarkers based on their collective contribution to the separation of the 2 patient groups. Among them, we further purified and subsequently identified 3 biomarkers. Individually, the biomarkers did not perform better than CA125. However, a combination of 4 of the biomarkers significantly improved performance (P < or =.001). The new biomarkers were complementary to CA125. At a fixed specificity of 94%, an index combining 2 of the biomarkers and CA125 achieves a sensitivity of 94% (95% confidence interval, 85%-100.0%) in contrast to a sensitivity of 81% (95% confidence interval, 68%-95%) for CA125 alone. CONCLUSIONS: The combined use of bioinformatics tools and proteomic profiling provides an effective approach to screen for potential tumor markers. Comparison of plasma profiles from patients with and without known ovarian cancer uncovered a panel of potential biomarkers for detection of ovarian cancer with discriminatory power complementary to that of CA125. Additional studies are required to further validate these biomarkers.

Adult↗

PubMed2001

A new network-based biologic database system.

Bioinformatics is playing an increasingly important role in the processing and analysis of biomedical data. The collection, storage and analysis of biologic information are key components of bioinformatics. In the genome era, with the explosion of sequence and structural information available to researchers, the structure of biologic databases is becoming more complicated, the contents is becoming larger, and the management and development is also becoming more difficult. A network-based biologic database has been developed. This database system integrates administration, development and analysis of bioinformatics with common and friendly interface. For the life scientists without much computer programming expertise, the system is easy to master.

Computational Biology↗

PubMed2000

Rice at the forefront of plant genome informatics.

As rice genomicsdata continue to accumulate at a rapid rate, are becoming more valuable to warehouse and access large and rigorous data sets. This article gives an overview of available resources on rice bioinformatics and their role in elucidating and propagating biological and genomic information in rice. Of particular focus here is the informatics infrastructure developed at the Rice Genome Research Program (RGP) following an extensive rice genome analysis. The database named INE (Integrated Rice Genome Explorer) integrates the genetic and physical mapping information with the genome sequence being generated in collaboration with the International Rice Genome Sequencing Project (IRGSP). Database links are initially evaluated using an interoperable query tool to explore and compare data across the rice and maize genome databases and potential application to multiple crop database querying. A proposed logistics for interlinking these resources is presented to integrate, manipulate and analyze information on the rice genome. One of the biggest challenges of rice bioinformatics lies in the emerging role of rice as a model system among grass crop species. In view of the importance of comparative genetics in the formulation of new knowledge on plant genomes and genes, comparative bioinformatics remains an essential strategy to gain new insights on the needs and expectations on rice genomics.

Chromosome Mapping↗

PubMed2002

[Molecular cloning, characterization, chromosomal assignment, genomic organization and verification of SFRS12(SRrp508), a novel member of human SR protein superfamily and a human homolog of rat SRrp86].

We have identified and characterized a novel human serine-arginine-rich (SR) splicing regulatory protein 508 (SRrp508) gene that is related to other members of the growing SR superfamily, but only homologous to rat (Rattus norvegicus) serine-arginine-rich splicing regulatory protein 86 (SRrp86) gene. The full-length cDNA of 3811 bp for human SRrp508 was cloned through a blast search of public databases following the identification of a cDNA contig of 658 bp obtained by EST assembly with full robotization in supercomputer in large-scale. Structurally, human SRrp508 encodes a polypeptide of 508 amino acids, which contains a single amino-terminal RNA recognition motif (RRM) and two carboxy-terminal domains rich in serine-arginine dipeptides that are highly conserved among other members of the SR superfamily. The conserved SR and RRM domains emphasize the biological importance of this gene. The SRrp508 gene, which contains 12 exons ranging from 0.096 to 2.093 kb and 11 introns ranging from 0.14 to 5.153 kb, is mapped to the human cytogenetic region 5q11.2-q12.1 using the bioinformatic analysis, and it does not link to any other genes. Furthermore, we have experimentally cloned and sequenced a cDNA fragment of 1680 bp containing the full-length ORF of 1527 bp in this novel human gene by RT-PCR from the single-stranded human pancreas cDNA library (Clontech), which is fully identical with that of the in silico cloning determined by the nucleotide sequencing. Thus, we in silico cloned his gene with GenBank accession number of AF459094 identified solely by bioinformatic analysis of the nucleotide and protein. This novel gene has promotors, TATA-box, several stop codons in the upstream of ORF, and PolyA signal in the downstream of ORF. Based on the above results, it can be concluded that we have obtained a complete novel human gene. The gene sequence exhibits good overall homology to that of rat SRrp86 gene, with 84% and 86% identity over the full-length nucleotide and protein, respectively, and with 96% and 86% identity over the serine-rich domain (RS) or arginine-rich domain (RA), respectively. The full-length sequence exhibits little overall homology to any other known protein at either the nucleotide or the amino acid level. The other two most closely related proteins, with 34% and 35% identity over the full-length protein, respectively, or with 51% and 54% identity over the full-length nucleotide of ORF, respectively, are drosophila serine-arginine-rich protein 54 (SRp54) and human arginine-rich nuclear protein 54 (p54). When comparisons are restricted to the RS or RA domains, the percent identity increased for both SRp54 and p54 are 44% and 54% or 38% and 43%, respectively. These results well demonstrate that only the novel human protein of 508 amino acids cloned is the human homolog of rat SRrp86, thus correcting the standpoint made by Barnard and Patton (Barnard DC, Patton JG. Identification and Characterization of a Novel Serine-Arginine-Rich Splicing Regulatory Protein. Molecular and Cellular Biology, 2000, 20(9): 3049-3057) that human arginine-rich nuclear protein 54 (p54) is the human homolog of the rat SRrp86, and suggesting that human SRrp508 is a new member of this growing superfamily of SR proteins. SRrp508 has an extensive expression profile, and may be a transcriptional factor. On the basis of its sequence and functional properties, we have named this protein SRrp508 for SR-related splicing regulatory protein of 508 amino acids. In summary, by combining bioinformatic analysis with experimental verification, we have successfully cloned the human cDNA homolog of rat SRrp86, which is verified by a series of theoretical and experimental evidence. The HGNC has just given SRrp508 gene entry the nomenclature information containing APPROVED SYMBOL: SFRS12; NAME: splicing factor, arginine/serine-rich 12; and ALIAS: DKFZp564B176, SRrp86. We have cloned this gene for near one year with no person landing the GenBank for registering the same gene. Our newly-established technique line will be helpful in discovering much more novel human genes.

Amino Acid Sequence↗

PubMed2003

Probabilistic graphical models for computational biomedicine.

BACKGROUND: As genomics becomes increasingly relevant to medicine, medical informatics and bioinformatics are gradually converging into a larger field that we call computational biomedicine. OBJECTIVES: Developing a computational framework that is common to the different disciplines that compose computational biomedicine will be a major enabler of the further development and integration of this research domain. METHODS: Probabilistic graphical models such as Hidden Markov Models, belief networks, and missing-data models together with computational methods such as dynamic programming, Expectation-Maximization, data-augmentation Gibbs sampling, and the Metropolis-Hastings algorithm provide the tools for an integrated probabilistic approach to computational biomedicine. RESULTS AND CONCLUSIONS: We show how graphical models have already found a broad application in different fields composing computational biomedicine. We also indicate several challenges that lie at the interface between medical informatics, statistical genomics, and bioinformatics. We also argue that graphical models offer a unified framework making it possible to integrate in a statistically meaningful way multiple models ranging from the molecular level to cellular and to clinical levels. Because of their versatility and firm statistical underpinning, we assert that probabilistic graphical models can serve as the lingua franca for many computationally intensive approaches to biology and medicine. As such, graphical models should be a foundation of the curriculum of students in these fields. From such a foundation, students could then build towards specific computational methods in medical informatics, medical image analysis, statistical genetics, or bioinformatics while keeping the communication open between these areas.

Computational Biology↗

PubMed2003

[Study on the gene mutation of TIGR in primary open angle glaucoma, their relatives and normal controls in Chongqing].

OBJECTIVE: To study trabecular meshwork induced glucocorticoid response protein (TIGR) gene mutation in primary open angle glaucoma (POAG), their relatives and normal controls in Chongqing. METHODS: (1) The coding sequence of TIGR was screened for sequence alterations using polymerase chain reaction (PCR) followed by single-strand conformation polymorphism (SSCP). (2) Samples corresponding to bands of altered mobility were sequenced. (3) The sequence alterations were analyzed by bioinformatics. RESULTS: (1) In 15 POAG, TIGR gene mutation was found in 5 cases. In 10 POAG relatives, 2 TIGR gene mutations were found. No TIGR gene mutation was found in 20 normal persons in Chongqing. (2) The mutation sites Ser55Thr, Asp247Stop and in 49021 c-t alteration discovered in the present study have not been reported previously. The 63155 c-t alternation has been reported as a polymorphism site previously. (3) Bioinformatics analysis indicated that the mutations in structural domain could lead to the changes in the amino acid sequence coded, second structure of protein, isoelectric point and antigen binding site. CONCLUSIONS: We found that the TIGR gene mutations is closely related to the occurrence of JOAG in Chongqing. The relatives of POAG patients may have a higher incidence of TIGR gene mutation as compared with the controls. Furthermore, after analyzed by bioinformatics, we found that the alteration of structure and biological activity of TIGR protein resulted from gene mutation may be one of the important changes that leading to the occurrence of POAG.

Adolescent↗

PubMed2004

[Development of IgHV family specific nucleic acid vaccine against lymphoma by construction of fusion gene of immunoglobulin heavy chain variable region and cytokine].

OBJECTIVE: To construct the gene co-expression vector of immunoglobulin heavy chain variable region (IgHV) gene and GM-CSF or IL-2 as IgHV family specific nucleic acid vaccine to lymphoma, and study the immune response of the immunized mice against lymphoma. METHODS: Six clones with significantly different length in gene fragments were selected from a gene bank constructed from normal fetal umbilical cord blood. These gene fragments in the clones were sequenced. The sequences were translated into IgHV peptides. T cell epitopes in the IgHV were predicted by bioinformatics. Meanwhile 6 clones of IgHV1 constructed before were analyzed. The most typical clone of IgHV1 and IgHV3 containing most of the T cell epitopes were selected. The IgHV gene fragments whose complementary determining region 3 (CDR3) was cut out and composed mainly of framework region were cloned into eukaryotic expression vector. The gene fragments of framework region of IgHV linking with gene of GM-CSF or IL-2 were cloned into pcDNA3.0 to form fusion genes of IgHV (FR)-GM-CSF/IL-2. Then they were transected into COS cells, African green monkey renal cells, by Lipofectin and their transient expression product was detected by ELISA. Twenty male Balb/c mice were randomly divided into 5 groups of 4 mice to be injected with different vectors at the weeks 0, 2, and 4: with IgHV3 (FR)/pcDNA3.0, with IgHV3 (FR)-IL-2/pcDNA 3.0, with blank vector pcDNA3.0 as control, with IgHV1 (FR)/pcDNA3.0, and with IgHV1 (FR)-IL-2/pcDNA3.0. At the weeks 0, 2, 4, 6, and 8 serum was collected from the mice to undergo indirect immunofluorescence examination to detect the antibodies against Namalwa cells, lymphoma cells from Africa green monkey, and normal lymphocytes. ELISA was used to examine the serum interferon (IFN)-gamma. RESULTS: About 30 of T cell epitopes existed in each IgHV peptides predicted by bioinformatics. Among the bioinformatics prediction, about 90% of the T cell epitopes were in the framework region (FR) of IgHV, and the first 10% with higher prediction score were in FR. The CDR3 of two typical IgHV sequences were cut down and the remaining sequences, mainly composed of FR, were used to construct the IgHV (FR)/pcDNA3.0 expression vectors. The 3' end of IgHV1 (FR) and IgHV3 (FR) were linked to GM-CSF or IL-2 gene successfully. The expression of GM-CSF in the group transfected with IgHV (FR)-GM-CSF/pcDNA3.0 were 200 times higher than in the group transfected with control pcDNA3.0. The expression of IL-2 in the group transfected with IgHV (FR)-IL-2/pcDNA3.0 were 60 times higher than in the group transfected with control pcDNA3.0. The antibody against IgHV1 family lymphoma cell line Namalwa could be detected since the second week in the mice immunized with IgHV1 (FR)-IL-2/pcDNA3.0. The antibody could be detected since the fourth week in the mice immunized with IgHV1 (FR). The antibody against lymphocyte line of IgHV3 family could be detected since the second week in the mice immunized with IgHV3 (FR)-IL-2/pcDNA3.0. The antibody could be detected since the fourth week in the mice immunized with IgHV3 (FR)/pcDNA3.0. The contents of serum IFN-gamma the mice immunized with IgHV1 (FR)-IL-2/pcDNA3.0 and with IgHV3 (FR)-IL-2/pcDNA3.0 was significantly higher than those of the mice immunized with IgHV (FR)/pcDNA3.0 or pcDNA3.0 (all P < 0.01). CONCLUSION: The gene fragments of IgHV (FR) can be used to construct IgHV family specific nucleic acid vaccine that induces anti-lymphoma immune response in mice by muscle injection. The expressing vectors of IgHV (FR)-GM-CSF/IL-2 induces stronger immunoreaction.

Animals↗

PubMed2005

Systematic search for natural antisense transcripts in eukaryotes (review).

The availability of several complete genome sequences and large numbers of expressed sequences, has led to the development of bioinformatic strategies for large-scale predictions of natural antisense transcripts. In the past two years, this has given at least 1,600 human pairs and 2,500 murine pairs of natural antisense transcripts. However, due to limitations in bioinformatic search tools, experimental validation of the predicted antisense transcripts is crucial. This has been performed only for a small fraction of the large number of predicted natural antisense transcripts. Additionally, bioinformatic approaches will not allow systematic identification of natural antisense transcripts in specific cell or tissue types. More recently, an experimental approach for identification of sense-antisense transcript pairs has been developed. The principle of the strategy is based upon the selection of double-stranded cDNAs as a result of hybridization between first-strand cDNAs that should be generated in the presence of actinomycin D. This experimental strategy allows systematic analysis of sense and antisense partners in any cell or tissue type.

Animals↗