Reply to: "Experimental aspects of copy number variant assays at CCL3L1".

Nature medicine (Impact Factor: 28.05). 10/2009; 15(10):1117-20. DOI: 10.1038/nm1009-1117
Source: PubMed
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    ABSTRACT: Defensins represent an evolutionary ancient family of antimicrobial peptides that play diverse roles in human health and disease. Defensins are cationic cysteine-containing multifunctional peptides predominantly expressed by epithelial cells or neutrophils. Defensins play a key role in host innate immune responses to infection and, in addition to their classically described role as antimicrobial peptides, have also been implicated in immune modulation, fertility, development, and wound healing. Aberrant expression of defensins is important in a number of inflammatory diseases as well as modulating host immune responses to bacteria, unicellular pathogens, and viruses. In parallel with their role in immunity, in other species, defensins have evolved alternative functions, including the control of coat color in dogs. Defensin genes reside in complex genomic regions that are prone to structural variations and some defensin family members exhibit copy number variation (CNV). Structural variations have mediated, and continue to influence, the diversification and expression of defensin family members. This review highlights the work currently being done to better understand the genomic architecture of the β-defensin locus. It evaluates current evidence linking defensin CNV to autoimmune disease (i.e., Crohn's disease and psoriasis) as well as the contribution CNV has in influencing immune responses to HIV infection.
    Frontiers in Immunology 03/2015; 6:115. DOI:10.3389/fimmu.2015.00115
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    ABSTRACT: The impact of host genetic variation on determining the differential outcomes after HIV infection has been studied by two approaches: targeting of candidate genes and genome-wide association studies (GWASs). The overlap in genetic variants that has been identified by these two means has essentially been restricted to variants near to the human leukocyte antigen (HLA) class I genes, although variation in the CCR5 locus, which was first shown to have an effect on HIV outcomes using the candidate gene approach, does reach significance genome-wide when very large samples sizes (i.e. thousands) are used in GWAS. Overall, many of the variants identified by the candidate gene approach are likely to be spurious, as no additional variants apart from a novel variant near the HLA-C gene have been consistently identified by GWAS. Variants with low frequency and/or low impact on HIV outcomes are likely to exist in the genome and there could be many of them, but these are not identifiable, given current GWAS sample sizes. Several loci centrally involved in the immune response, including the immunoglobulin genes, T-cell receptor loci, or leukocyte receptor complex, are either poorly covered on the GWAS chips or difficult to interpret due to their repetitive nature and/or the presence of insertion/deletion polymorphisms in the region. These loci warrant further interrogation, but genetic characterization of these regions across a range of individuals will first be required. Finally, synergistic interactions between loci may affect outcome after infection, as suggested by associations of specific, functionally relevant HLA and killer cell immunoglobulin-like receptor variants with HIV disease outcomes, and these require further consideration as well.
    AIDS (London, England) 11/2013; 27(18):2831-2839. DOI:10.1097/01.aids.0000432536.85335.c8 · 6.56 Impact Factor
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    ABSTRACT: Recent advances in high-throughout sequencing technologies have made it possible to accurately assign copy number (CN) at CN variable loci. However, current analytic methods often perform poorly in regions in which complex CN variation is observed. Here we report the development of a read depth-based approach, CNVrd2, for investigation of CN variation using high-throughput sequencing data. This methodology was developed using data from the 1000 Genomes Project from the CCL3L1 locus, and tested using data from the DEFB103A locus. In both cases, samples were selected for which paralog ratio test data were also available for comparison. The CNVrd2 method first uses observed read-count ratios to refine segmentation results in one population. Then a linear regression model is applied to adjust the results across multiple populations, in combination with a Bayesian normal mixture model to cluster segmentation scores into groups for individual CN counts. The performance of CNVrd2 was compared to that of two other read depth-based methods (CNVnator, cn.mops) at the CCL3L1 and DEFB103A loci. The highest concordance with the paralog ratio test method was observed for CNVrd2 (77.8/90.4% for CNVrd2, 36.7/4.8% for cn.mops and 7.2/1% for CNVnator at CCL3L1 and DEF103A). CNVrd2 is available as an R package as part of the Bioconductor project:
    Frontiers in Genetics 08/2014; 5:248. DOI:10.3389/fgene.2014.00248