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      Co-evolution of Human Leukocyte Antigen (HLA) Class I Ligands with Killer-Cell Immunoglobulin-Like Receptors (KIR) in a Genetically Diverse Population of Sub-Saharan Africans

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          Abstract

          Interactions between HLA class I molecules and killer-cell immunoglobulin-like receptors (KIR) control natural killer cell (NK) functions in immunity and reproduction. Encoded by genes on different chromosomes, these polymorphic ligands and receptors correlate highly with disease resistance and susceptibility. Although studied at low-resolution in many populations, high-resolution analysis of combinatorial diversity of HLA class I and KIR is limited to Asian and Amerindian populations with low genetic diversity. At the other end of the spectrum is the West African population investigated here: we studied 235 individuals, including 104 mother-child pairs, from the Ga-Adangbe of Ghana. This population has a rich diversity of 175 KIR variants forming 208 KIR haplotypes, and 81 HLA-A, -B and -C variants forming 190 HLA class I haplotypes. Each individual we studied has a unique compound genotype of HLA class I and KIR, forming 1–14 functional ligand-receptor interactions. Maintaining this exceptionally high polymorphism is balancing selection. The centromeric region of the KIR locus, encoding HLA-C receptors, is highly diverse whereas the telomeric region encoding Bw4-specific KIR3DL1, lacks diversity in Africans. Present in the Ga-Adangbe are high frequencies of Bw4-bearing HLA-B*53:01 and Bw4-lacking HLA-B*35:01, which otherwise are identical. Balancing selection at key residues maintains numerous HLA-B allotypes having and lacking Bw4, and also those of stronger and weaker interaction with LILRB1, a KIR-related receptor. Correspondingly, there is a balance at key residues of KIR3DL1 that modulate its level of cell-surface expression. Thus, capacity to interact with NK cells synergizes with peptide binding diversity to drive HLA-B allele frequency distribution. These features of KIR and HLA are consistent with ongoing co-evolution and selection imposed by a pathogen endemic to West Africa. Because of the prevalence of malaria in the Ga-Adangbe and previous associations of cerebral malaria with HLA-B*53:01 and KIR, Plasmodium falciparum is a candidate pathogen.

          Author Summary

          Natural killer cells are white blood cells with critical roles in human health that deliver front-line immunity against pathogens and nurture placentation in early pregnancy. Controlling these functions are cell-surface receptors called KIR that interact with HLA class I ligands expressed on most cells of the body. KIR and HLA are both products of complex families of variable genes, but present on separate chromosomes. Many HLA and KIR variants and their combinations associate with resistance to specific infections and pregnancy syndromes. Previously we identified basic components of the system necessary for individual and population survival. Here, we explore the system at its most genetically diverse by studying the Ga-Adangbe population from Ghana in West Africa. Co-evolution of KIR receptors with their HLA targets is ongoing in the Ga-Adangbe, with every one of 235 individuals studied having a unique set of KIR receptors and HLA class I ligands. In addition, one critical combination of receptor and ligand maintains alternative forms that either can or cannot interact with their ‘partner.’ This balance resembles that induced by malfunctioning variants of hemoglobin that confer resistance to malaria, a candidate disease for driving diversity and co-evolution of KIR and HLA class I in the Ga-Adangbe.

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          Most cited references98

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          DnaSP, DNA polymorphism analyses by the coalescent and other methods.

          DnaSP is a software package for the analysis of DNA polymorphism data. Present version introduces several new modules and features which, among other options allow: (1) handling big data sets (approximately 5 Mb per sequence); (2) conducting a large number of coalescent-based tests by Monte Carlo computer simulations; (3) extensive analyses of the genetic differentiation and gene flow among populations; (4) analysing the evolutionary pattern of preferred and unpreferred codons; (5) generating graphical outputs for an easy visualization of results. The software package, including complete documentation and examples, is freely available to academic users from: http://www.ub.es/dnasp
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            The genetic structure and history of Africans and African Americans.

            Africa is the source of all modern humans, but characterization of genetic variation and of relationships among populations across the continent has been enigmatic. We studied 121 African populations, four African American populations, and 60 non-African populations for patterns of variation at 1327 nuclear microsatellite and insertion/deletion markers. We identified 14 ancestral population clusters in Africa that correlate with self-described ethnicity and shared cultural and/or linguistic properties. We observed high levels of mixed ancestry in most populations, reflecting historical migration events across the continent. Our data also provide evidence for shared ancestry among geographically diverse hunter-gatherer populations (Khoesan speakers and Pygmies). The ancestry of African Americans is predominantly from Niger-Kordofanian (approximately 71%), European (approximately 13%), and other African (approximately 8%) populations, although admixture levels varied considerably among individuals. This study helps tease apart the complex evolutionary history of Africans and African Americans, aiding both anthropological and genetic epidemiologic studies.
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              A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data. III. Cladogram estimation.

              We previously developed a cladistic approach to identify subsets of haplotypes defined by restriction endonuclease mapping or DNA sequencing that are associated with significant phenotypic deviations. Our approach was limited to segments of DNA in which little recombination occurs. In such cases, a cladogram can be constructed from the restriction site or sequence data that represents the evolutionary steps that interrelate the observed haplotypes. The cladogram is used to define a nested statistical design to identify mutational steps associated with significant phenotypic deviations. The central assumption behind this strategy is that any undetected mutation causing a phenotypic effect is embedded within the same evolutionary history that is represented by the cladogram. The power of this approach depends upon the confidence one has in the particular cladogram used to draw inferences. In this paper, we present a strategy for estimating the set of cladograms that are consistent with a particular sample of either restriction site or nucleotide sequence data and that includes the possibility of recombination. We first evaluate the limits of parsimony in constructing cladograms. Once these limits have been determined, we construct the set of parsimonious and nonparsimonious cladograms that is consistent with these limits. Our estimation procedure also identifies haplotypes that are candidates for being products of recombination. If recombination is extensive, our algorithm subdivides the DNA region into two or more subsections, each having little or no internal recombination. We apply this estimation procedure to three data sets to illustrate varying degrees of cladogram ambiguity and recombination.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                October 2013
                October 2013
                31 October 2013
                : 9
                : 10
                : e1003938
                Affiliations
                [1 ]Departments of Structural Biology and Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, United States of America
                [2 ]Center for Genetics, Children's Hospital Oakland Research Institute, Oakland, California, United States of America
                [3 ]Department of Pathology, Stanford University School of Medicine, Stanford, California, United States of America
                [4 ]Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Ghana
                [5 ]Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
                [6 ]Centre National de la Recherche Scientifique, Laboratoire d'Analyse, Topologie, Probabilités - Unité Mixte de Recherche 7353, Equipe ATIP, Aix-Marseille Université, Marseille, France
                Georgia Institute of Technology, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: PJN LAR. Performed the experiments: PJN NNG HGH MJP. Analyzed the data: PJN JAH LAR. Contributed reagents/materials/analysis tools: LAG EMR KAK PP. Wrote the paper: PJN JAH PP.

                Article
                PGENETICS-D-13-01215
                10.1371/journal.pgen.1003938
                3814319
                24204327
                7fc73a2b-b95a-42a2-b2d1-9ede5030fd89
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 May 2013
                : 16 September 2013
                Page count
                Pages: 18
                Funding
                This study was supported by National Institutes of Health grant AI17892 to PP. The original sample collection in Ghana was funded by The Wellcome Trust (040328). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article

                Genetics
                Genetics

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