902 resultados para Human Genome Diversity Project


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This article considers the debate over patent law, informed consent, and benefit-sharing in the context of biomedical research in respect of Indigenous communities. In particular, it focuses upon three key controversies over large-scale biology projects, involving Indigenous populations. These case studies are representative of the tensions between research organisations, Indigenous communities, and funding agencies. Section two considers the aims and origins of the Human Genome Diversity Project, and criticisms levelled against the venture by Indigenous peak bodies and anti-biotechnology groups, such as the Rural Advancement Foundation International. It examines the ways in which the United Nations Educational, Scientific, and Cultural Organization (UNESCO) grappled with questions of patent law, informed consent, and benefit sharing in relation to population genetics. Section three focuses upon the ongoing litigation in Tilousi v. Arizona State University, and the Havasupai Tribe v. Arizona State University. In this matter, the Havasupai tribe from the Grand Canyon in the United States brought legal action against the Arizona State University and its researchers for using genetic data for unauthorised purposes - namely, genetic research into schizophrenia, migration, and inbreeding. The litigation raises questions about informed consent, negligence, and larger matters of human rights. Section four explores the legal and ethical issues raised by the Genographic Project. It considers the aims and objectives of the venture, and the criticisms levelled against it by Indigenous communities, and anti-biotechnology groups. It examines the response of the United Nations Permanent Forum on Indigenous Issues to the Genographic Project. It charts the debate over the protection of traditional knowledge in various international fora. The conclusion recommends a number of measures to better regulate large-scale biology projects involving the participation of Indigenous communities.

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We present a new haplotype-based approach for inferring local genetic ancestry of individuals in an admixed population. Most existing approaches for local ancestry estimation ignore the latent genetic relatedness between ancestral populations and treat them as independent. In this article, we exploit such information by building an inheritance model that describes both the ancestral populations and the admixed population jointly in a unified framework. Based on an assumption that the common hypothetical founder haplotypes give rise to both the ancestral and the admixed population haplotypes, we employ an infinite hidden Markov model to characterize each ancestral population and further extend it to generate the admixed population. Through an effective utilization of the population structural information under a principled nonparametric Bayesian framework, the resulting model is significantly less sensitive to the choice and the amount of training data for ancestral populations than state-of-the-art algorithms. We also improve the robustness under deviation from common modeling assumptions by incorporating population-specific scale parameters that allow variable recombination rates in different populations. Our method is applicable to an admixed population from an arbitrary number of ancestral populations and also performs competitively in terms of spurious ancestry proportions under a general multiway admixture assumption. We validate the proposed method by simulation under various admixing scenarios and present empirical analysis results from a worldwide-distributed dataset from the Human Genome Diversity Project.

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Gap junctions are clustered channels between contacting cells through which direct intercellular communication via diffusion of ions and metabolites can occur. Two hemichannels, each built up of six connexin protein subunits in the plasma membrane of adjacent cells, can dock to each other to form conduits between cells. We have recently screened mouse and human genomic data bases and have found 19 connexin (Cx) genes in the mouse genome and 20 connexin genes in the human genome. One mouse connexin gene and two human connexin genes do not appear to have orthologs in the other genome. With three exceptions, the characterized connexin genes comprise two exons whereby the complete reading frame is located on the second exon. Targeted ablation of eleven mouse connexin genes revealed basic insights into the functional diversity of the connexin gene family. In addition, the phenotypes of human genetic disorders caused by mutated connexin genes further complement our understanding of connexin functions in the human organism. In this review we compare currently identified connexin genes in both the mouse and human genome and discuss the functions of gap junctions deduced from targeted mouse mutants and human genetic disorders.

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In this paper, we describe the accomplishments of the initial phase of the Human Genome Project, with particular attention to the progress made toward achieving the defined goals for constructing genetic and physical maps of the human genome and determining the sequence of human DNA, identifying the complete set of human genes, and analyzing the need for adequate policies for using the information about human genetics in ways that maximize the benefits for individuals and society.

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This article describes the history of the Human Genome Project, how the human genome was sequenced, and analyses the likely impact which the results will have on the diagnosis, scientific understanding and, ultimately, treatment of ocular disease in the future.

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The human genome project was a grand scientific enterprise which attracted both hyperbole and ridicule alike. The project was lauded as “the moon shot of the life sciences”, the “holy grail of man”, “the code of codes”, and “the book of life”. Such rhetoric has also received scorn. President George Bush senior managed to deflate the pretensions of the project with the accidental slip that it was the “human gnome initiative”. In The Sequence, Kevin Davies seeks to go beyond such metaphors, and provide a candid and honest account of the race of the human genome project. The author is indebted to the authoritative book The Gene Wars, which considered the early struggles over the human genome project. Robert Cook-Deegan observes that there was initially much debate over whether there should be a Human Genome Project at all: The debate became one of “big” science versus “small” science. The reliance on systematic technology development and goal-directed gene-mapping efforts presaged a new style for biology, one that elicited excitement from those attracted to whiz-bang technologies but drew gasps of revulsion from those who aspired to cultivate biology on a more modest scale and with decentralized organisation. The battle was, among other things, over whose vision would control the budget and which scientific aesthetic would prevail.

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South Asian populations harbor a high degree of genetic diversity, due in part to demographic history. Two studies on genome-wide variation in Indian populations have shown that most Indian populations show varying degrees of admixture between ancestral north Indian and ancestral south Indian components. As a result of this structure, genetic variation in India appears to follow a geographic cline. Similarly, Indian populations seem to show detectable differences in diabetes and obesity prevalence between different geographic regions of the country. We tested the hypothesis that genetic variation at diabetes-and obesity-associated loci may be potentially related to different genetic ancestries. We genotyped 2977 individuals from 61 populations across India for 18 SNPs in genes implicated in T2D and obesity. We examined patterns of variation in allele frequency across different geographical gradients and considered state of origin and language affiliation. Our results show that most of the 18 SNPs show no significant correlation with latitude, the geographic cline reported in previous studies, or by language family. Exceptions include KCNQ1 with latitude and THADA and JAK1 with language, which suggests that genetic variation at previously ascertained diabetes-associated loci may only partly mirror geographic patterns of genome-wide diversity in Indian populations.

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The non-classical human leukocyte antigen (HLA) class I genes present a very low rate of variation. So far, only 10 HLA-E alleles encoding three proteins have been described, but only two are frequently found in worldwide populations. Because of its historical background, Brazilians are very suitable for population genetic studies. Therefore, 104 bone marrow donors from Brazil were evaluated for HLA-E exons 14. Seven variation sites were found, including two known single nucleotide polymorphisms (SNPs) at positions +424 and +756 and five new SNPs at positions +170 (intron 1), +1294 (intron 3), +1625, +1645 and +1857 (exon 4). Haplotyping analysis did show eight haplotypes, three of them known as E*01:01:01, E*01:03:01 and E*01:03:02:01 and five HLA-E new alleles that carry the new variation sites. The HLA-E*01:01:01 allele was the predominant haplotype (62.50%), followed by E*01:03:02:01 (24.52%). Selective neutrality tests have disclosed an interesting pattern of selective pressures in which balancing selection is probably shaping allele frequency distributions at an SNP at exon 3 (codon 107), sequence diversity at exon 4 and the non-coding regions is facing significant purifying pressure. Even in an admixed population such as the Brazilian one, the HLA-E locus is very conserved, presenting few polymorphic SNPs in the coding region.

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Abstract Background Recent medical and biological technology advances have stimulated the development of new testing systems that have been providing huge, varied amounts of molecular and clinical data. Growing data volumes pose significant challenges for information processing systems in research centers. Additionally, the routines of genomics laboratory are typically characterized by high parallelism in testing and constant procedure changes. Results This paper describes a formal approach to address this challenge through the implementation of a genetic testing management system applied to human genome laboratory. We introduced the Human Genome Research Center Information System (CEGH) in Brazil, a system that is able to support constant changes in human genome testing and can provide patients updated results based on the most recent and validated genetic knowledge. Our approach uses a common repository for process planning to ensure reusability, specification, instantiation, monitoring, and execution of processes, which are defined using a relational database and rigorous control flow specifications based on process algebra (ACP). The main difference between our approach and related works is that we were able to join two important aspects: 1) process scalability achieved through relational database implementation, and 2) correctness of processes using process algebra. Furthermore, the software allows end users to define genetic testing without requiring any knowledge about business process notation or process algebra. Conclusions This paper presents the CEGH information system that is a Laboratory Information Management System (LIMS) based on a formal framework to support genetic testing management for Mendelian disorder studies. We have proved the feasibility and showed usability benefits of a rigorous approach that is able to specify, validate, and perform genetic testing using easy end user interfaces.

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Description based on: March 1993; title from cover.

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Thesis (Ph.D.)--University of Washington, 2016-06

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Photographs from the February 1997 Bermuda meeting. Courtesy of Gert-Jan van Ommen.

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Four years after the completion of the Human Genome Project, the US National Institutes for Health launched the Human Microbiome Project on 19 December 2007. Using metaphor analysis, this article investigates reporting in English-language newspapers on advances in microbiomics from 2003 onwards, when the word “microbiome” was first used. This research was said to open up a “new frontier” and was conceived as a “second human genome project”, this time focusing on the genomes of microbes that inhabit and populate humans rather than focusing on the human genome itself. The language used by scientists and by the journalists who reported on their research employed a type of metaphorical framing that was very different from the hyperbole surrounding the decipherment of the “book of life”. Whereas during the HGP genomic successes had been mainly framed as being based on a unidirectional process of reading off information from a passive genetic or genomic entity, the language employed to discuss advances in microbiomics frames genes, genomes and life in much more active and dynamic ways.