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Kruspe S, Dickey DD, Urak KT, Blanco GN, Miller MJ, Clark KC, Burghardt E, Gutierrez WR, Phadke SD, Kamboj S, Ginader T, Smith BJ, Grimm SK, Schappet J, Ozer H, Thomas A, McNamara JO, Chan CH, Giangrande PH. Rapid and Sensitive Detection of Breast Cancer Cells in Patient Blood with Nuclease-Activated Probe Technology. MOLECULAR THERAPY. NUCLEIC ACIDS 2017; 8:542-557. [PMID: 28918054 PMCID: PMC5577414 DOI: 10.1016/j.omtn.2017.08.004] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Accepted: 08/07/2017] [Indexed: 02/07/2023]
Abstract
A challenge for circulating tumor cell (CTC)-based diagnostics is the development of simple and inexpensive methods that reliably detect the diverse cells that make up CTCs. CTC-derived nucleases are one category of proteins that could be exploited to meet this challenge. Advantages of nucleases as CTC biomarkers include: (1) their elevated expression in many cancer cells, including cells implicated in metastasis that have undergone epithelial-to-mesenchymal transition; and (2) their enzymatic activity, which can be exploited for signal amplification in detection methods. Here, we describe a diagnostic assay based on quenched fluorescent nucleic acid probes that detect breast cancer CTCs via their nuclease activity. This assay exhibited robust performance in distinguishing breast cancer patients from healthy controls, and it is rapid, inexpensive, and easy to implement in most clinical labs. Given its broad applicability, this technology has the potential to have a substantive impact on the diagnosis and treatment of many cancers.
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Affiliation(s)
- Sven Kruspe
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA
| | - David D Dickey
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA
| | - Kevin T Urak
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA; Molecular & Cellular Biology Program, University of Iowa, Iowa City, IA, USA
| | - Giselle N Blanco
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA
| | - Matthew J Miller
- Medical Scientist Training Program, University of Iowa, Iowa City, IA, USA
| | - Karen C Clark
- Interdisciplinary Graduate Program in Genetics, University of Iowa, Iowa City, IA, USA
| | - Elliot Burghardt
- Medical Scientist Training Program, University of Iowa, Iowa City, IA, USA
| | - Wade R Gutierrez
- Medical Scientist Training Program, University of Iowa, Iowa City, IA, USA
| | - Sneha D Phadke
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA
| | - Sukriti Kamboj
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA
| | - Timothy Ginader
- Department of Biostatistics, University of Iowa, Iowa City, IA, USA; Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, USA
| | - Brian J Smith
- Department of Biostatistics, University of Iowa, Iowa City, IA, USA; Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, USA
| | - Sarah K Grimm
- Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, USA
| | - James Schappet
- Institute for Clinical and Translational Science, University of Iowa, Iowa City, IA, USA
| | - Howard Ozer
- Department of Medicine, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Alexandra Thomas
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA; Department of Hematology & Oncology, Wake Forest, Winston Salem, NC, USA
| | - James O McNamara
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA; Molecular & Cellular Biology Program, University of Iowa, Iowa City, IA, USA; Interdisciplinary Graduate Program in Genetics, University of Iowa, Iowa City, IA, USA; Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, USA
| | - Carlos H Chan
- Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, USA; Department of Surgery, University of Iowa, Iowa City, IA, USA.
| | - Paloma H Giangrande
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA; Molecular & Cellular Biology Program, University of Iowa, Iowa City, IA, USA; Interdisciplinary Graduate Program in Genetics, University of Iowa, Iowa City, IA, USA; Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, USA; Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA; Abboud Cardiovascular Research Center, University of Iowa, Iowa City, IA, USA; Environmental Health Sciences Research Center, University of Iowa, Iowa City, IA, USA.
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2
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Mouilleron H, Delcourt V, Roucou X. Death of a dogma: eukaryotic mRNAs can code for more than one protein. Nucleic Acids Res 2016; 44:14-23. [PMID: 26578573 PMCID: PMC4705651 DOI: 10.1093/nar/gkv1218] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2015] [Revised: 10/26/2015] [Accepted: 10/28/2015] [Indexed: 12/13/2022] Open
Abstract
mRNAs carry the genetic information that is translated by ribosomes. The traditional view of a mature eukaryotic mRNA is a molecule with three main regions, the 5' UTR, the protein coding open reading frame (ORF) or coding sequence (CDS), and the 3' UTR. This concept assumes that ribosomes translate one ORF only, generally the longest one, and produce one protein. As a result, in the early days of genomics and bioinformatics, one CDS was associated with each protein-coding gene. This fundamental concept of a single CDS is being challenged by increasing experimental evidence indicating that annotated proteins are not the only proteins translated from mRNAs. In particular, mass spectrometry (MS)-based proteomics and ribosome profiling have detected productive translation of alternative open reading frames. In several cases, the alternative and annotated proteins interact. Thus, the expression of two or more proteins translated from the same mRNA may offer a mechanism to ensure the co-expression of proteins which have functional interactions. Translational mechanisms already described in eukaryotic cells indicate that the cellular machinery is able to translate different CDSs from a single viral or cellular mRNA. In addition to summarizing data showing that the protein coding potential of eukaryotic mRNAs has been underestimated, this review aims to challenge the single translated CDS dogma.
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Affiliation(s)
- Hélène Mouilleron
- Department of biochemistry, Université de Sherbrooke, Sherbrooke, Quebec J1E 4K8, Canada PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec, Canada
| | - Vivian Delcourt
- Department of biochemistry, Université de Sherbrooke, Sherbrooke, Quebec J1E 4K8, Canada PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec, Canada Inserm U-1192, Laboratoire de Protéomique, Réponse Inflammatoire, Spectrométrie de Masse (PRISM), Université de Lille 1, Cité Scientifique, 59655 Villeneuve D'Ascq, France
| | - Xavier Roucou
- Department of biochemistry, Université de Sherbrooke, Sherbrooke, Quebec J1E 4K8, Canada PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec, Canada
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Jackson MA, Lea I, Rashid A, Peddada SD, Dunnick JK. Genetic alterations in cancer knowledge system: analysis of gene mutations in mouse and human liver and lung tumors. Toxicol Sci 2006; 90:400-18. [PMID: 16410370 DOI: 10.1093/toxsci/kfj101] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Mutational incidence and spectra for genes examined in both human and mouse lung and liver tumors were analyzed using the National Institute of Environmental Health Sciences (NIEHS) Genetic Alterations in Cancer (GAC) knowledge system. GAC is a publicly available, web-based system for evaluating data obtained from peer-reviewed studies of genetic changes in tumors associated with exposure to chemical, physical, or biological agents, as well as spontaneous tumors. In mice, mutations in Kras2 and Hras-1 were the most common events reported for lung and liver tumors, respectively, whether chemically induced or spontaneous. There was a significant difference in Kras2 mutation incidence for spontaneous versus induced mouse lung tumors and in Hras-1 mutation incidence and spectrum for spontaneous versus induced mouse liver tumors. The major gene changes reported for human lung and liver tumors were in KRAS2 (lung only) and TP53. The KRAS2 mutation incidence was similar for spontaneous and asbestos-induced human lung tumors, while the TP53 mutation incidence differed significantly. Aflatoxin B1, hepatitis B virus, hepatitis C virus, and vinyl chloride all caused TP53 mutations in human liver tumors, but the mutation spectrum for each agent differed. The incidence of KRAS2 mutations in human compared to mouse lung tumors differed significantly, as did the incidence of Hras and p53 gene mutations in human compared to mouse liver tumors. Differences observed in the mutation spectra for agent-induced compared to spontaneous tumors and similarities in spectra for structurally similar agents support the concept that mutation spectra can serve as a "fingerprint" of exposure based on chemical structure.
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Affiliation(s)
- Marcus A Jackson
- Integrated Laboratory Systems, Inc., Research Triangle Park, North Carolina 27709, USA
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Kalume DE, Peri S, Reddy R, Zhong J, Okulate M, Kumar N, Pandey A. Genome annotation of Anopheles gambiae using mass spectrometry-derived data. BMC Genomics 2005; 6:128. [PMID: 16171517 PMCID: PMC1249570 DOI: 10.1186/1471-2164-6-128] [Citation(s) in RCA: 53] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2005] [Accepted: 09/19/2005] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND A large number of animal and plant genomes have been completely sequenced over the last decade and are now publicly available. Although genomes can be rapidly sequenced, identifying protein-coding genes still remains a problematic task. Availability of protein sequence data allows direct confirmation of protein-coding genes. Mass spectrometry has recently emerged as a powerful tool for proteomic studies. Protein identification using mass spectrometry is usually carried out by searching against databases of known proteins or transcripts. This approach generally does not allow identification of proteins that have not yet been predicted or whose transcripts have not been identified. RESULTS We searched 3,967 mass spectra from 16 LC-MS/MS runs of Anopheles gambiae salivary gland homogenates against the Anopheles gambiae genome database. This allowed us to validate 23 known transcripts and 50 novel transcripts. In addition, a novel gene was identified on the basis of peptides that matched a genomic region where no gene was known and no transcript had been predicted. The amino termini of proteins encoded by two predicted transcripts were confirmed based on N-terminally acetylated peptides sequenced by tandem mass spectrometry. Finally, six sequence polymorphisms could be annotated based on experimentally obtained peptide sequences. CONCLUSION The peptide sequences from this study were mapped onto the genomic sequence using the distributed annotation system available at Ensembl and can be visualized in the context of all other existing annotations. The strategy described in this paper can be used to correct and confirm genome annotations and permit discovery of novel proteins in a high-throughput manner by mass spectrometry.
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Affiliation(s)
- Dário E Kalume
- McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry and Oncology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Suraj Peri
- McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry and Oncology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, DK-5230, Denmark
| | - Raghunath Reddy
- McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry and Oncology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Institute of Bioinformatics, Discoverer Unit 1, 7th Floor International Tech Park Ltd., Whitefield Road, Bangalore – 560 066, India
| | - Jun Zhong
- McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry and Oncology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Mobolaji Okulate
- Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Nirbhay Kumar
- Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Akhilesh Pandey
- McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry and Oncology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
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5
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Integration with the human genome of peptide sequences obtained by high-throughput mass spectrometry. Genome Biol 2004; 6:R9. [PMID: 15642101 PMCID: PMC549070 DOI: 10.1186/gb-2004-6-1-r9] [Citation(s) in RCA: 228] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2004] [Revised: 10/21/2004] [Accepted: 11/17/2004] [Indexed: 11/21/2022] Open
Abstract
Peptides derived from protein tandem mass spectrometry data have been mapped to the human genome sequence forming an expandable resource for the proteomic data. A crucial aim upon the completion of the human genome is the verification and functional annotation of all predicted genes and their protein products. Here we describe the mapping of peptides derived from accurate interpretations of protein tandem mass spectrometry (MS) data to eukaryotic genomes and the generation of an expandable resource for integration of data from many diverse proteomics experiments. Furthermore, we demonstrate that peptide identifications obtained from high-throughput proteomics can be integrated on a large scale with the human genome. This resource could serve as an expandable repository for MS-derived proteome information.
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6
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Abstract
PURPOSE The most common reason for long-term failure of glaucoma filtering surgery (GFS) is scarring of the external filtering "bleb" tissues. The identification of the factors that mediate this process, as well as the development and initial testing of new therapies to limit scarring is enhanced by the use of appropriate animal models. The standard animal model for studying GFS is the rabbit but newer investigative tools that examine changes induced in biologic systems at a genetic level have made development of a rat model desirable. METHODS Glaucoma filtering surgery was performed on 20 Sprague-Dawley rats by introducing a 30-gauge silicone cannula through a penetrating scleral tunnel, under a limbal-based conjunctival flap and suturing the conjunctiva closed. Identical GFS was performed on 3 additional rats, which underwent histologic evaluation at days 2, 5, and 11, following surgery.Fistulizing surgery was also performed on 6 Sprague-Dawley rats, for comparison, by creating a full-thickness needle sclerostomy under a limbal-based conjunctival flap and suturing the conjunctiva closed. RESULTS Following the cannula GFS, well-elevated filtering blebs formed and these gradually failed over the course of 8 to 13 days. Needle tract sclerostomy filtering blebs formed at the site of the fistulizing surgery but rapidly failed over the course of 2 to 3 days. CONCLUSION Cannulated filtering surgery in the rat provides a longer lasting and more predictable model than needle tract sclerostomy for studying wound healing following GFS and may facilitate the study of induced changes at the gene level.
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Affiliation(s)
- M B Sherwood
- Department of Ophthalmology, College of Medicine, University of Florida, Gainesville, Florida 32610-0284, USA.
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Allen JE, Pertea M, Salzberg SL. Computational gene prediction using multiple sources of evidence. Genome Res 2004; 14:142-8. [PMID: 14707176 PMCID: PMC314291 DOI: 10.1101/gr.1562804] [Citation(s) in RCA: 86] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
This article describes a computational method to construct gene models by using evidence generated from a diverse set of sources, including those typical of a genome annotation pipeline. The program, called Combiner, takes as input a genomic sequence and the locations of gene predictions from ab initio gene finders, protein sequence alignments, expressed sequence tag and cDNA alignments, splice site predictions, and other evidence. Three different algorithms for combining evidence in the Combiner were implemented and tested on 1783 confirmed genes in Arabidopsis thaliana. Our results show that combining gene prediction evidence consistently outperforms even the best individual gene finder and, in some cases, can produce dramatic improvements in sensitivity and specificity.
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Affiliation(s)
- Jonathan E Allen
- The Institute for Genomic Research, Rockville, Maryland 20850, USA.
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8
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Birney E, Andrews D, Bevan P, Caccamo M, Cameron G, Chen Y, Clarke L, Coates G, Cox T, Cuff J, Curwen V, Cutts T, Down T, Durbin R, Eyras E, Fernandez-Suarez XM, Gane P, Gibbins B, Gilbert J, Hammond M, Hotz H, Iyer V, Kahari A, Jekosch K, Kasprzyk A, Keefe D, Keenan S, Lehvaslaiho H, McVicker G, Melsopp C, Meidl P, Mongin E, Pettett R, Potter S, Proctor G, Rae M, Searle S, Slater G, Smedley D, Smith J, Spooner W, Stabenau A, Stalker J, Storey R, Ureta-Vidal A, Woodwark C, Clamp M, Hubbard T. Ensembl 2004. Nucleic Acids Res 2004; 32:D468-70. [PMID: 14681459 PMCID: PMC308772 DOI: 10.1093/nar/gkh038] [Citation(s) in RCA: 143] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organize biology around the sequences of large genomes. It is a comprehensive and integrated source of annotation of large genome sequences, available via interactive website, web services or flat files. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. The facilities of the system range from sequence analysis to data storage and visualization and installations exist around the world both in companies and at academic sites. With a total of nine genome sequences available from Ensembl and more genomes to follow, recent developments have focused mainly on closer integration between genomes and external data.
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Affiliation(s)
- E Birney
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
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Peri S, Navarro JD, Amanchy R, Kristiansen TZ, Jonnalagadda CK, Surendranath V, Niranjan V, Muthusamy B, Gandhi TKB, Gronborg M, Ibarrola N, Deshpande N, Shanker K, Shivashankar HN, Rashmi BP, Ramya MA, Zhao Z, Chandrika KN, Padma N, Harsha HC, Yatish AJ, Kavitha MP, Menezes M, Choudhury DR, Suresh S, Ghosh N, Saravana R, Chandran S, Krishna S, Joy M, Anand SK, Madavan V, Joseph A, Wong GW, Schiemann WP, Constantinescu SN, Huang L, Khosravi-Far R, Steen H, Tewari M, Ghaffari S, Blobe GC, Dang CV, Garcia JGN, Pevsner J, Jensen ON, Roepstorff P, Deshpande KS, Chinnaiyan AM, Hamosh A, Chakravarti A, Pandey A. Development of human protein reference database as an initial platform for approaching systems biology in humans. Genome Res 2003; 13:2363-71. [PMID: 14525934 PMCID: PMC403728 DOI: 10.1101/gr.1680803] [Citation(s) in RCA: 747] [Impact Index Per Article: 35.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Human Protein Reference Database (HPRD) is an object database that integrates a wealth of information relevant to the function of human proteins in health and disease. Data pertaining to thousands of protein-protein interactions, posttranslational modifications, enzyme/substrate relationships, disease associations, tissue expression, and subcellular localization were extracted from the literature for a nonredundant set of 2750 human proteins. Almost all the information was obtained manually by biologists who read and interpreted >300,000 published articles during the annotation process. This database, which has an intuitive query interface allowing easy access to all the features of proteins, was built by using open source technologies and will be freely available at http://www.hprd.org to the academic community. This unified bioinformatics platform will be useful in cataloging and mining the large number of proteomic interactions and alterations that will be discovered in the postgenomic era.
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Affiliation(s)
- Suraj Peri
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21287, USA
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Leppert MF, Singh NA. Nonsyndromic seizure disorders: epilepsy and the use of the internet to advance research. Annu Rev Genomics Hum Genet 2003; 4:437-57. [PMID: 14527308 DOI: 10.1146/annurev.genom.4.071902.102155] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The progress in understanding the genetics of nonsyndromic epilepsy is the direct result of dramatic advances made by the Human Genome Project. The development of thousands of precisely mapped genetic markers and the nearly complete sequencing of the entire human genome in 2001 allowed genetic researchers in epilepsy to identify many loci and genes as causal in inherited idiopathic epilepsy. This substantial increase in information has required the development of accurate and online bioinformatic databases. Only the Internet can enable such large amounts of precise DNA sequence information to be transferred to researchers. Along with the construction of these databases has been the development of efficient search algorithms for specific DNA sequences and genetic information. This article summarizes the effect that this burst of new genomic information has had on research aimed at discovering the underlying genetic factors for nonsyndromic epilepsy. Many of the web sites important to epilepsy gene discovery are listed and discussed in this article, including sites with extensive information on genetic markers, genetic analysis, gene sequence, gene expression, gene mutations, and DNA sequence variation. Continued acquisition of information on naturally occurring DNA sequence variants will greatly help research directed towards understanding the genetic susceptibility of the common, nonsyndromic epilepsies and will lead to the promise of personalized medicine.
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Affiliation(s)
- Mark F Leppert
- Department of Human Genetics, University of Utah, Salt Lake City, Utah 84112-5330, USA.
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11
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Abstract
Fifty years after the publication of DNA structure, the whole human genome sequence will be officially finished. This achievement marks the beginning of the task to catalogue every human gene and identify each of their function expression patterns. Currently, researchers estimate that there are about 30,000 human genes and approximately 70% of these can be automatically predicted using a combination of ab initio and similarity-based programs. However, to experimentally investigate every gene's function, the research community requires a high-quality annotation of alternative splicing, pseudogenes, and promoter regions that can only be provided by manual intervention. Manual curation of the human genome will be a long-term project as experimental data are continually produced to confirm or refine the predictions, and new features such as noncoding RNAs and enhancers have not been fully identified. Such a highly curated human gene-set made publicly available will be a great asset for the experimental community and for future comparative genome projects.
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Affiliation(s)
- Jennifer L Ashurst
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, United Kingdom.
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Strausberg RL, Simpson AJG, Wooster R. Sequence-based cancer genomics: progress, lessons and opportunities. Nat Rev Genet 2003; 4:409-18. [PMID: 12776211 DOI: 10.1038/nrg1085] [Citation(s) in RCA: 52] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Technologies that provide a genome-wide view offer an unprecedented opportunity to scrutinize the molecular biology of the cancer cell. The information that is derived from these technologies is well suited to the development of public databases of alterations in the cancer genome and its expression. Here, we describe the synergistic efforts of research programmes in Brazil, the United Kingdom and the United States towards building integrated databases that are widely accessible to the research community, to enable basic and applied applications in cancer research.
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Affiliation(s)
- Robert L Strausberg
- National Cancer Institute, 31 Center Drive, Room 10A07, Bethesda, Maryland 20892, USA.
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Navarro JD, Niranjan V, Peri S, Jonnalagadda CK, Pandey A. From biological databases to platforms for biomedical discovery. Trends Biotechnol 2003; 21:263-8. [PMID: 12788546 DOI: 10.1016/s0167-7799(03)00108-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
The use of high-throughput DNA sequencing and proteomic methods has led to an unprecedented increase in the amount of genomic and proteomic data. Application of computing technologies and development of computational tools to analyze and present these data has not kept pace with the accumulation of information. Here, we discuss the use of different database systems to store biological information and mention some of the key emerging computing technologies that are likely to have a key role in the future of bioinformatics.
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Affiliation(s)
- J Daniel Navarro
- McKusick-Nathans Institute of Genetic Medicine and Dept. of Biological Chemistry, Johns Hopkins University, Baltimore, MD 21287, USA
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14
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Clamp M, Andrews D, Barker D, Bevan P, Cameron G, Chen Y, Clark L, Cox T, Cuff J, Curwen V, Down T, Durbin R, Eyras E, Gilbert J, Hammond M, Hubbard T, Kasprzyk A, Keefe D, Lehvaslaiho H, Iyer V, Melsopp C, Mongin E, Pettett R, Potter S, Rust A, Schmidt E, Searle S, Slater G, Smith J, Spooner W, Stabenau A, Stalker J, Stupka E, Ureta-Vidal A, Vastrik I, Birney E. Ensembl 2002: accommodating comparative genomics. Nucleic Acids Res 2003; 31:38-42. [PMID: 12519943 PMCID: PMC165530 DOI: 10.1093/nar/gkg083] [Citation(s) in RCA: 180] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.
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Affiliation(s)
- M Clamp
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK
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15
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Current Awareness on Comparative and Functional Genomics. Comp Funct Genomics 2003; 4:277-84. [PMID: 18629117 PMCID: PMC2447404 DOI: 10.1002/cfg.227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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