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At least 19 recordsLinked to original sources
PubMed2003

deCODE genetics, Inc.

deCODE genetics, Inc. has compiled the world's most comprehensive collection of population data on genealogy, genotypes and phenotypes. This combination of resources provides an effective system for identifying key genes linked to common diseases and to the regulation of drug response. deCODE has successfully mapped genes in over 25 common complex diseases and isolated genes in eight of these. The methodology used to map these genes is based upon the company's genealogical database of the Icelandic population, which enables deCODE scientists to efficiently conduct population- and genome-wide linkage studies to identify key genetic factors involved in phenotypes ranging from diseases to drug response. In its growing pharmacogenomics program, deCODE has combined this linkage approach with high-throughput expression profiling to develop accurate tests that can predict individual responsiveness to virtually any drug of interest. deCODE is applying its unrivaled discovery capabilities to bring to market new drugs, DNA-based diagnostic products and pharmacogenomic tests. The company believes that such tests will play a crucial role in delivering personalized medicine - contributing to the development of more effective means of diagnosing and treating disease by matching each patient with the most suitable drug.

Chromosome Mapping↗
PubMed2006

Scientific rationality, uncertainty and the governance of human genetics: an interview study with researchers at deCODE genetics.

Technology development in human genetics is fraught with uncertainty, controversy and unresolved moral issues, and industry scientists are sometimes accused of neglecting the implications of their work. The present study was carried out to elicit industry scientists' reflections on the relationship between commercial, scientific and ethical dimensions of present day genetics and the resources needed for robust governance of new technologies. Interviewing scientists of the company deCODE genetics in Iceland, we found that in spite of optimism, the informants revealed ambiguity and uncertainty concerning the use of human genetic technologies for the prevention of common diseases. They concurred that uncritical marketing of scientific success might cause exaggerated public expectations of health benefits from genetics, with the risk of backfiring and causing resistance to genetics in the population. On the other hand, the scientists did not address dilemmas arising from the commercial nature of their own employer. Although the scientists tended to describe public fear as irrational, they identified issues where scepticism might be well founded and explored examples where they, despite expert knowledge, held ambiguous or tentative personal views on the use of predictive genetic technologies. The rationality of science was not seen as sufficient to ensure beneficial governance of new technologies. The reflexivity and suspension of judgement demonstrated in the interviews exemplify productive features of moral deliberation in complex situations. Scientists should take part in dialogues concerning the governance of genetic technologies, acknowledge any vested interests, and use their expertise to highlight, not conceal the technical and moral complexity involved.

Fear↗
PubMed2004

Reprogrammed genetic decoding in cellular gene expression.

Reprogrammed genetic decoding signals in mRNAs productively overwrite the normal decoding rules of translation. These "recoding" signals are associated with sites of programmed ribosomal frameshifting, hopping, termination codon suppression, and the incorporation of the unusual amino acids selenocysteine and pyrrolysine. This review summarizes current knowledge of the structure and function of recoding signals in cellular genes, the biological importance of recoding in gene regulation, and ways to identify new recoded genes.

Animals↗
PubMed2026

Advances in genomics-driven genetic decoding and genomic design breeding in tomato.

Tomatoes are highly nutritious and represent one of the important vegetable fruits worldwide. Both historically and moving forward, genetic decoding and precision breeding remain fundamental to tomato improvement. Here, we summarize pivotal advances in decoding tomato genomes across domestication, improvement and evolution processes and provide a perspective on future breeding through precision design. In-depth population genetic studies have revealed how artificial selection systematically prioritized yield-related alleles at the cost of narrowing genetic diversity, especially at flavor-related loci-highlighting the urgent need to reconcile these trade-offs. Comparative genomics across species, viewed through an evolutionary lens, has uncovered critical insights into functional genes, deepening our understanding of the genetic architecture and regulatory mechanisms underlying key traits. Collectively, these advances have enabled precise identification and functional characterization of key genetic elements, paving the way for systematic redomestication of tomato through precision genomic design. Looking ahead, more efficient and precise breeding strategies will be required to accelerate genetic gains in tomato in the coming decades. The integration of recent genomic advances, coupled with genomic selection and artificial intelligence, into genomic design breeding offers a transformative framework, unlocking unprecedented opportunities for developing highly flavorful and consumer-customized tomato varieties.

Journal Article↗
PubMed2000

Nonlinearity in genetic decoding: homologous DNA replicase genes use alternatives of transcriptional slippage or translational frameshifting.

The tau and gamma subunits of DNA polymerase III are both encoded by a single gene in Escherichia coli and Thermus thermophilus. gamma is two-thirds the size of tau and shares virtually all its amino acid sequence with tau. E. coli and T. thermophilus have evolved very different mechanisms for setting the approximate 1:1 ratio between tau and gamma. Both mechanisms put ribosomes into alternate reading frames so that stop codons in the new frame serve to make the smaller gamma protein. In E. coli, approximately 50% of initiating ribosomes translate the dnaX mRNA conventionally to give tau, but the other 50% shift into the -1 reading frame at a specific site (A AAA AAG) in the mRNA to produce gamma. In T. thermophilus ribosomal frameshifting is not required: the dnaX mRNA is a heterogeneous population of molecules with different numbers of A residues arising from transcriptional slippage on a run of nine T residues in the DNA template. Translation of the subpopulation containing nine As (or +/- multiples of three As) yields tau. The rest of the population of mRNAs (containing nine +/- nonmultiples of three As) puts ribosomes into the alternate reading frames to produce the gamma protein(s). It is surprising that two rather similar dnaX sequences in E. coli and T. thermophilus lead to very different mechanisms of expression.

Bacterial Proteins↗
PubMed2001

Yin-yang genetics, or the HSD deCODE controversy.

Iceland has attracted world-wide attention because of a controversy surrounding the Icelandic Health Sector Database Act of 1998 and the genomics company deCODE Genetics. The controversy concerns limits to state power, bioethics and regulation of research, and civil liberties. Understanding it necessitates paying attention to the yin-yang-like character of deCODE; it is international or Icelandic, what is the relation between the HSD and deCODE, will the HSD engulf the Icelandic nation as a whole?

Databases, Genetic↗
PubMed2001

Biosamples, genomics, and human rights: context and content of Iceland's Biobanks Act.

In recent years, human DNA sampling and collection has accelerated without the development of enforceable rules protecting the human rights of donors. The need for regulation of biobanking is especially acute in Iceland, whose parliament has granted a for-profit corporation, deCODE Genetics, an exclusive license to create a centralized database of health records for studies on human genetic variation. Until recently, how deCODE Genetics would get genetic material for its genotypic-phenotypic database remained unclear. However, in May 2000, the Icelandic Parliament passed the Icelandic Biobanks Act, the world's earliest attempt to construct binding rules for the use of biobanks in scientific research. Unfortunately, Iceland has lost an opportunity for bringing clear and ethically sound standards to the use of human biological samples in deCODE's database and in other projects: the Biobanks Act has extended a notion of "presumed consent" from the use of medical records to the use of patients' biological samples; worse, the act has made it possible--perhaps likely--that a donor's wish to withdraw his/her sample will be ignored. Inadequacies in the Act's legislative process help account for these deficiencies in the protection of donor autonomy.

Blood Specimen Collection↗
PubMed1998

An rRNA fragment and its antisense can alter decoding of genetic information.

rRNA plays a central role in protein synthesis and is intimately involved in the initiation, elongation, and termination stages of translation. However, the mode of its participation in these reactions, particularly as to the decoding of genetic information, remains elusive. In this paper, we describe a new approach that allowed us to identify an rRNA segment whose function is likely to be related to translation termination. By screening an expression library of random rRNA fragments, we identified a fragment of the Escherichia coli 23S rRNA (nucleotides 74 to 136) whose expression caused readthrough of UGA nonsense mutations in certain codon contexts in vivo. The antisense RNA fragment produced a similar effect, but in neither case was readthrough of UAA or UAG observed. Since termination at UGA in E. coli specifically requires release factor 2 (RF2), our data suggest that the fragments interfere with RF2-dependent termination.

Codon, Terminator↗
PubMed1999

The assent of a nation: genethics and Iceland.

The Icelandic parliament passed legislation authorizing the establishment of a national health sector database which will be sponsored financially by private enterprises through DeCode Genetics Inc. Health related data will be gathered from patients, without their informed consent, from all points of contact with Icelandic public and private health care providers. A centralized data curator will 'non-personalize' the identity of the subjects in a one-way coding system which the government and DeCode Genetics argue overrides the need for informed consent. This legislation is in conflict with the European Data Protection Act, which requires informed consent for the collection of personal data. The law raises many ethical questions regarding the central tenets of informed consent, the power of government, the rights of the human subject, and finally, the responsibility of the clinician balancing commitments of the patient and research.

Bioethics↗
PubMed2004

Coding and consent: moral challenges of the database project in Iceland.

A major moral problem in relation to the deCODE genetics database project in Iceland is that the heavy emphasis placed on technical security of healthcare information has precluded discussion about the issue of consent for participation in the database. On the other hand, critics who have emphasised the issue of consent have most often demanded that informed consent for participation in research be obtained. While I think that individual consent is of major significance, I argue that this demand for informed consent is neither suitable nor desirable in this case. I distinguish between three aspects of the database and show that different types of consent are appropriate for each. In particular, I describe the idea of a written authorisation based on general information about the database as an alternative to informed consent and presumed consent in database research.

Databases, Factual↗
PubMed2004

Property rights in genetic information.

The primary theme of this paper is the normative case against ownership of one's genetic information along with the source of that information (usually human tissues samples). The argument presented here against such "upstream" property rights is based primarily on utilitarian grounds. This issue has new salience thanks to the Human Genome Project and "bio-prospecting" initiatives based on the aggregation of genetic information, such as the one being managed by deCODE Genetics in Iceland. The rationale for ownership is twofold: ownership will protect the basic human rights of privacy and autonomy and it will enable the data subjects to share in the tangible benefits of the genetic research. Proponents of this viewpoint often cite the principle of genetic exceptionalism, which asserts that genetic information needs a higher level of protection than other kinds of personal information such as financial data. We argue, however, that the recognition of such ownership rights would lead to inefficiency along with the disutility of genetic discoveries. Biomedical research will be hampered if property rights in genes and genetic material are too extensive. We contend that other mechanisms such as informed consent and strict confidentiality rules can accomplish the same result as a property right without the liabilities of an exclusive entitlement.

Access to Information↗
PubMed2024

Decoding the genetic landscape of allergic rhinitis: a comprehensive network analysis revealing key genes and potential therapeutic targets.

BACKGROUND: Allergic Rhinitis (AR), an inflammatory affliction impacting the upper respiratory tract, has been registering a substantial surge in incidence across the globe. METHODS: We embarked on examination of differentially expressed genes (DEGs) and the Weighted Gene Co-Expression Network Analysis (WGCNA). With this armory of genes identified, we engaged the tools of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Our study continued with the establishment of a protein-protein interaction (PPI) network and the application of LASSO regression. Finally, we leveraged a docking model to elucidate potential drug-gene interactions involving these key genes. RESULTS: Through WGCNA and different express genes screening, PPI network was performed, identifying top 20 key genes, including CD44, CD69, CD274. LASSO regression identified three independent factors, STARD5, CST1, and CHAC1, that were significantly associated with AR. A predictive model was developed with an AUC value over 0.75. Also, 105 potential therapeutic agents were discovered, including Fluorouracil, Cyclophosphamide, Doxorubicin, and Hydrocortisone, offering promising therapeutic strategies for AR. CONCLUSION: By fuzing DEGs with key genes derived from WGCNA, this study has illuminated a comprehensive network of gene interactions involved in the pathogenesis of AR, paving the way for future biomarker and therapeutic target discovery in AR.

Humans↗