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Search: WFRF:(Sali M) > (2010-2014)

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1.
  • Schlessinger, Avner, et al. (author)
  • Comparison of human solute carriers
  • 2010
  • In: Protein Science. - : Wiley. - 0961-8368 .- 1469-896X. ; 19:3, s. 412-428
  • Journal article (peer-reviewed)abstract
    • Solute carriers are eukaryotic membrane proteins that control the uptake and efflux of solutes, including essential cellular compounds, environmental toxins, and therapeutic drugs. Solute carriers can share similar structural features despite weak sequence similarities. Identification of sequence relationships among solute carriers is needed to enhance our ability to model individual carriers and to elucidate the molecular mechanisms of their substrate specificity and transport. Here, we describe a comprehensive comparison of solute carriers. We link the proteins using sensitive profile-profile alignments and two classification approaches, including similarity networks. The clusters are analyzed in view of substrate type, transport mode, organism conservation, and tissue specificity. Solute carrier families with similar substrates generally cluster together, despite exhibiting relatively weak sequence similarities. In contrast, some families cluster together with no apparent reason, revealing unexplored relationships. We demonstrate computationally and experimentally the functional overlap between representative members of these families. Finally, we identify four putative solute carriers in the human genome. The solute carriers include a biomedically important group of membrane proteins that is diverse in sequence and structure. The proposed classification of solute carriers, combined with experiment, reveals new relationships among the individual families and identifies new solute carriers. The classification scheme will inform future attempts directed at modeling the structures of the solute carriers, a prerequisite for describing the substrate specificities of the individual families.
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2.
  • Mychaleckyj, Josyf C., et al. (author)
  • HLA genotyping in the international Type 1 Diabetes Genetics Consortium
  • 2010
  • In: Clinical Trials. - : SAGE Publications. - 1740-7753 .- 1740-7745. ; 7:1 suppl., s. 75-87
  • Journal article (peer-reviewed)abstract
    • Background Although human leukocyte antigen (HLA) DQ and DR loci appear to confer the strongest genetic risk for type 1 diabetes, more detailed information is required for other loci within the HLA region to understand causality and stratify additional risk factors. The Type 1 Diabetes Genetics Consortium (T1DGC) study design included high-resolution genotyping of HLA-A, B, C, DRB1, DQ, and DP loci in all affected sibling pair and trio families, and cases and controls, recruited from four networks worldwide, for analysis with clinical phenotypes and immunological markers. Purpose In this article, we present the operational strategy of training, classification, reporting, and quality control of HLA genotyping in four laboratories on three continents over nearly 5 years. Methods Methods to standardize HLA genotyping at eight loci included: central training and initial certification testing; the use of uniform reagents, protocols, instrumentation, and software versions; an automated data transfer; and the use of standardized nomenclature and allele databases. We implemented a rigorous and consistent quality control process, reinforced by repeated workshops, yearly meetings, and telephone conferences. Results A total of 15,246 samples have been HLA genotyped at eight loci to four-digit resolution; an additional 6797 samples have been HLA genotyped at two loci. The genotyping repeat rate decreased significantly over time, with an estimated unresolved Mendelian inconsistency rate of 0.21%. Annual quality control exercises tested 2192 genotypes (4384 alleles) and achieved 99.82% intra-laboratory and 99.68% inter-laboratory concordances. Limitations The chosen genotyping platform was unable to distinguish many allele combinations, which would require further multiple stepwise testing to resolve. For these combinations, a standard allele assignment was agreed upon, allowing further analysis if required. Conclusions High-resolution HLA genotyping can be performed in multiple laboratories using standard equipment, reagents, protocols, software, and communication to produce consistent and reproducible data with minimal systematic error. Many of the strategies used in this study are generally applicable to other large multi-center studies. Clinical Trials 2010; 7: S75-S87. http://ctj.sagepub.com.
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