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      Natural Polymorphisms in Tap2 Influence Negative Selection and CD4∶CD8 Lineage Commitment in the Rat

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          Abstract

          Genetic variation in the major histocompatibility complex (MHC) affects CD4∶CD8 lineage commitment and MHC expression. However, the contribution of specific genes in this gene-dense region has not yet been resolved. Nor has it been established whether the same genes regulate MHC expression and T cell selection. Here, we assessed the impact of natural genetic variation on MHC expression and CD4∶CD8 lineage commitment using two genetic models in the rat. First, we mapped Quantitative Trait Loci (QTLs) associated with variation in MHC class I and II protein expression and the CD4∶CD8 T cell ratio in outbred Heterogeneous Stock rats. We identified 10 QTLs across the genome and found that QTLs for the individual traits colocalized within a region spanning the MHC. To identify the genes underlying these overlapping QTLs, we generated a large panel of MHC-recombinant congenic strains, and refined the QTLs to two adjacent intervals of ∼0.25 Mb in the MHC-I and II regions, respectively. An interaction between these intervals affected MHC class I expression as well as negative selection and lineage commitment of CD8 single-positive (SP) thymocytes. We mapped this effect to the transporter associated with antigen processing 2 ( Tap2) in the MHC-II region and the classical MHC class I gene(s) ( RT1-A) in the MHC-I region. This interaction was revealed by a recombination between RT1-A and Tap2, which occurred in 0.2% of the rats. Variants of Tap2 have previously been shown to influence the antigenicity of MHC class I molecules by altering the MHC class I ligandome. Our results show that a restricted peptide repertoire on MHC class I molecules leads to reduced negative selection of CD8SP cells. To our knowledge, this is the first study showing how a recombination between natural alleles of genes in the MHC influences lineage commitment of T cells.

          Author Summary

          Peptides from degraded cytoplasmic proteins are transported via TAP into the endoplasmic reticulum for loading onto MHC class I molecules. TAP is encoded by Tap1 and Tap2, which in rodents are located close to the MHC class I genes. In the rat, genetic variation in Tap2 gives rise to two different transporters: a promiscuous A variant (TAP-A) and a more restrictive B variant (TAP-B). It has been proposed that the class I molecule in the DA rat (RT1-A a) has co-evolved with TAP-A and it has been shown that RT1-A a antigenicity is changed when co-expressed with TAP-B. To study the contribution of different allelic combinations of RT1-A and Tap2 to the variation in MHC expression and T cell selection, we generated DA rats with either congenic or background alleles in the RT1-A and Tap2 loci. We found increased numbers of mature CD8SP cells in the thymus of rats which co-expressed RT1-A a and TAP-B. This increase of CD8 cells could be explained by reduced negative selection, but did not correlate with RT1-A a expression levels on thymic antigen presenting cells. Thus, our results identify a crucial role of the TAP and the quality of the MHC class I repertoire in regulating T cell selection.

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          Most cited references84

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          Intensely punctate meiotic recombination in the class II region of the major histocompatibility complex.

          There is considerable interest in understanding patterns of linkage disequilibrium (LD) in the human genome, to aid investigations of human evolution and facilitate association studies in complex disease. The relative influences of meiotic crossover distribution and population history on LD remain unclear, however. In particular, it is uncertain to what extent crossovers are clustered into 'hot spots, that might influence LD patterns. As a first step to investigating the relationship between LD and recombination, we have analyzed a 216-kb segment of the class II region of the major histocompatibility complex (MHC) already characterized for familial crossovers. High-resolution LD analysis shows the existence of extended domains of strong association interrupted by patchwork areas of LD breakdown. Sperm typing shows that these areas correspond precisely to meiotic crossover hot spots. All six hot spots defined share a remarkably similar symmetrical morphology but vary considerably in intensity, and are not obviously associated with any primary DNA sequence determinants of hot-spot activity. These hot spots occur in clusters and together account for almost all crossovers in this region of the MHC. These data show that, within the MHC at least, crossovers are far from randomly distributed at the molecular level and that recombination hot spots can profoundly affect LD patterns.
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            Regulation of CD8+ T cell development by thymus-specific proteasomes.

            Proteasomes are responsible for generating peptides presented by the class I major histocompatibility complex (MHC) molecules of the immune system. Here, we report the identification of a previously unrecognized catalytic subunit called beta5t. beta5t is expressed exclusively in cortical thymic epithelial cells, which are responsible for the positive selection of developing thymocytes. Although the chymotrypsin-like activity of proteasomes is considered to be important for the production of peptides with high affinities for MHC class I clefts, incorporation of beta5t into proteasomes in place of beta5 or beta5i selectively reduces this activity. We also found that beta5t-deficient mice displayed defective development of CD8(+) T cells in the thymus. Our results suggest a key role for beta5t in generating the MHC class I-restricted CD8(+) T cell repertoire during thymic selection.
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              A method for fine mapping quantitative trait loci in outbred animal stocks.

              High-resolution mapping of quantitative trait loci (QTL) in animals has proved to be difficult because the large effect sizes detected in crosses between inbred strains are often caused by numerous linked QTLs, each of small effect. In a study of fearfulness in mice, we have shown it is possible to fine map small-effect QTLs in a genetically heterogeneous stock (HS). This strategy is a powerful general method of fine mapping QTLs, provided QTLs detected in crosses between inbred strains that formed the HS can be reliably detected in the HS. We show here that single-marker association analysis identifies only two of five QTLs expected to be segregating in the HS and apparently limits the strategy's usefulness for fine mapping. We solve this problem with a multipoint analysis that assigns the probability that an allele descends from each progenitor in the HS. The analysis does not use pedigrees but instead requires information about the HS founder haplotypes. With this method we mapped all three previously undetected loci [chromosome (Chr.) 1 logP 4.9, Chr. 10 logP 6.0, Chr. 15 logP 4.0]. We show that the reason for the failure of single-marker association to detect QTLs is its inability to distinguish opposing phenotypic effects when they occur on the same marker allele. We have developed a robust method of fine mapping QTLs in genetically heterogeneous animals and suggest it is now cost effective to undertake genomewide high-resolution analysis of complex traits in parallel on the same set of mice.
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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
                February 2014
                20 February 2014
                : 10
                : 2
                : e1004151
                Affiliations
                [1 ]Section for Medical Inflammation Research, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
                [2 ]Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom
                [3 ]Physiological Genomics and Medicine Group, Medical Research Council Clinical Sciences Centre, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, United Kingdom
                [4 ]Rheumatology Unit, Department of Medicine, Karolinska University Hospital, Stockholm, Sweden
                [5 ]Medical Proteomics, Department of Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden and Science for Life Laboratory, Solna, Sweden
                [6 ]Department of Clinical Neuroscience, Karolinska Institutet, Neuroimmunology Unit, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
                [7 ]Medical Psychology Unit, Department of Psychiatry & Forensic Medicine, Institute of Neurosciences, School of Medicine, Autonomous University of Barcelona, Bellaterra, Barcelona, Spain
                Georgia Institute of Technology, United States of America
                Author notes

                ¶ Membership of the EURATRANS Consortium is provided in the Acknowledgments.

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: JT RH. Performed the experiments: JT SH ACYY UN AB EL KM ST AJY MJo. Analyzed the data: JT SH AB DE KM AJY AG MJa PS TO AFT RAZ TJA RM JF RH. Wrote the paper: JT SH.

                Article
                PGENETICS-D-13-00308
                10.1371/journal.pgen.1004151
                3930506
                24586191
                4ed87d15-321c-481f-82ab-734153a68d6c
                Copyright @ 2014

                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
                : 1 February 2013
                : 16 December 2013
                Page count
                Pages: 21
                Funding
                This study was funded by grants from the Crafoord Foundation, Kock and Österlund Foundations, Knut and Alice Wallenberg Foundation, the Swedish Association against Rheumatism, the Swedish Medical Research Council, and the Swedish Foundation for Strategic Research. The research leading to these results has received funding from the European Community's Seventh Framework Program (FP7/2007-2013) under grant agreement N° HEALTH-F4-2010-241504 (EURATRANS), as well as MASTERSWITCH (HEALTH-F2-2008-223404) and the Spanish MICINN (PSI2009-10532) and “La Marató de TV3 N° 092630”. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine
                Clinical immunology
                Immune cells
                Immune system
                Major histocompatibility complex

                Genetics
                Genetics

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