High-resolution genome screen for bone mineral density in heterogeneous stock rat

We previously demonstrated that skeletal mass, structure, and biomechanical properties vary considerably in heterogeneous stock (HS) rat strains. In addition, we observed strong heritability for several of these skeletal phenotypes in the HS rat model, suggesting that it represents a unique genetic resource for dissecting the complex genetics underlying bone fragility. The purpose of this study was to identify and localize genes associated with bone mineral density in HS rats. We measured bone phenotypes from 1524 adult male and female HS rats between 17 and 20 weeks of age. Phenotypes included dual-energy X-ray absorptiometry (DXA) measurements for bone mineral content and areal bone mineral density (aBMD) for femur and lumbar spine (L3-L5), and volumetric BMD measurements by CT for the midshaft and distal femur, femur neck, and fifth lumbar vertebra (L5). A total of 70,000 polymorphic single-nucleotide polymorphisms (SNPs) distributed throughout the genome were selected from genotypes obtained from the Affymetrix rat custom SNPs array for the HS rat population. These SNPs spanned the HS rat genome with a mean linkage disequilibrium coefficient between neighboring SNPs of 0.95. Haplotypes were estimated across the entire genome for each rat using a multipoint haplotype reconstruction method, which calculates the probability of descent for each genotyped locus from each of the eight founder HS strains. The haplotypes were tested for association with each bone density phenotype via a mixed model with covariate adjustment. We identified quantitative trait loci (QTLs) for BMD phenotypes on chromosomes 2, 9, 10, and 13 meeting a conservative genomewide empiric significance threshold (false discovery rate [FDR] = 5%; p < 3 × 10(-6)). Importantly, most QTLs were localized to very small genomic regions (1-3 megabases [Mb]), allowing us to identify a narrow set of potential candidate genes including both novel genes and genes previously shown to have roles in skeletal development and homeostasis

Fine mapping of bone structure and strength QTLs in heterogeneous stock rat

We previously demonstrated that skeletal structure and strength phenotypes vary considerably in heterogeneous stock (HS) rats. These phenotypes were found to be strongly heritable, suggesting that the HS rat model represents a unique genetic resource for dissecting the complex genetic etiology underlying bone fragility. The purpose of this study was to identify and localize genes associated with bone structure and strength phenotypes using 1524 adult male and female HS rats between 17 to 20 weeks of age. Structure measures included femur length, neck width, head width; femur and lumbar spine (L3-5) areas obtained by DXA; and cross-sectional areas (CSA) at the midshaft, distal femur and femoral neck, and the 5th lumbar vertebra measured by CT. In addition, measures of strength of the whole femur and femoral neck were obtained. Approximately 70,000 polymorphic SNPs distributed throughout the rat genome were selected for genotyping, with a mean linkage disequilibrium coefficient between neighboring SNPs of 0.95. Haplotypes were estimated across the entire genome for each rat using a multipoint haplotype reconstruction method, which calculates the probability of descent at each locus from each of the 8 HS founder strains. The haplotypes were then tested for association with each structure and strength phenotype via a mixed model with covariate adjustment. We identified quantitative trait loci (QTLs) for structure phenotypes on chromosomes 3, 8, 10, 12, 17 and 20, and QTLs for strength phenotypes on chromosomes 5, 10 and 11 that met a conservative genome-wide empiric significance threshold (FDR=5%; P<3×10(-6)). Importantly, most QTLs were localized to very narrow genomic regions (as small as 0.3 Mb and up to 3 Mb), each harboring a small set of candidate genes, both novel and previously shown to have roles in skeletal development and homeostasis

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

Contains fulltext : 136368.pdf (publisher's version ) (Open Access)Genetic variation in the major histocompatibility complex (MHC) affects CD4ratioCD8 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 CD4ratioCD8 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 CD4ratioCD8 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 approximately 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

Fourteen sequence variants that associate with multiple sclerosis discovered by meta-analysis informed by genetic correlations

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked FilesA meta-analysis of publicly available summary statistics on multiple sclerosis combined with three Nordic multiple sclerosis cohorts (21,079 cases, 371,198 controls) revealed seven sequence variants associating with multiple sclerosis, not reported previously. Using polygenic risk scores based on public summary statistics of variants outside the major histocompatibility complex region we quantified genetic overlap between common autoimmune diseases in Icelanders and identified disease clusters characterized by autoantibody presence/absence. As multiple sclerosis-polygenic risk scores captures the risk of primary biliary cirrhosis and vice versa (P = 1.6 x 10(-7), 4.3 x 10(-9)) we used primary biliary cirrhosis as a proxy-phenotype for multiple sclerosis, the idea being that variants conferring risk of primary biliary cirrhosis have a prior probability of conferring risk of multiple sclerosis. We tested 255 variants forming the primary biliary cirrhosis-polygenic risk score and found seven multiple sclerosis-associating variants not correlated with any previously established multiple sclerosis variants. Most of the variants discovered are close to or within immune-related genes. One is a low-frequency missense variant in TYK2, another is a missense variant in MTHFR that reduces the function of the encoded enzyme affecting methionine metabolism, reported to be dysregulated in multiple sclerosis brain.Swedish Research Council Knut and Alice Wallenberg Foundation AFA Foundation Swedish Brain Foundatio

Locus for severity implicates CNS resilience in progression of multiple sclerosis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) that results in significant neurodegeneration in the majority of those affected and is a common cause of chronic neurological disability in young adults(1,2). Here, to provide insight into the potential mechanisms involved in progression, we conducted a genome-wide association study of the age-related MS severity score in 12,584 cases and replicated our findings in a further 9,805 cases. We identified a significant association with rs10191329 in the DYSF-ZNF638 locus, the risk allele of which is associated with a shortening in the median time to requiring a walking aid of a median of 3.7 years in homozygous carriers and with increased brainstem and cortical pathology in brain tissue. We also identified suggestive association with rs149097173 in the DNM3-PIGC locus and significant heritability enrichment in CNS tissues. Mendelian randomization analyses suggested a potential protective role for higher educational attainment. In contrast to immune-driven susceptibility(3), these findings suggest a key role for CNS resilience and potentially neurocognitive reserve in determining outcome in MS

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

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

Regulation of class I expression by classical and inverse cim.

<p>(A) CD68+ cells were stained on the cell surface with OX18 (anti-class Ia and Ib). Histograms show representative samples from DA, DA.1H and DA.1H derived strains with different alleles of <i>RT1-A</i> and <i>Tap2</i> as stated on top. Data from all individuals are shown in scatterplot (far right); * significant compared to DA.1H (1H); ** significant compared to DA. (B) CD68+ cells stained with a class Ia specific antibody (F16-4-4). (C) T cells from animals shown in (A) stained intracellularly with OX18 (scatterplot) and F16-4-4 (histogram). (D–E) Subsets of leukocytes from DA and DA.1IR85 spleen stained extracellularly (D) and intracellularly (E) with OX18. Data are representative of 6 individuals per group. (F) Surface expression of MHC class I (OX18) on CD68+ cells from DA and DA.1U congenic strains. (G) CD68+ cells (same as in F) stained with F16-4-4. Vertical lines in scatterplots show mean values. Representative results of at least two independent experiments are shown.</p

Physical map of the rat MHC region.

<p>The map was constructed according to the NCBI build 3.4 genome assembly. Genes (left) are depicted according to scale (positions in Mb), except for positions indicated with crotchets. The gross organization of MHC-Ia, II, III and Ib -regions are adopted from Hurt et al. <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004151#pgen.1004151-Hurt1" target="_blank">[9]</a>. Recombinant congenic strains are shown as gray vertical bars with dashed lines representing congenic borders (intervals of unknown genotype). Markers, short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs), are shown in italic numbers. Numbers with asterisks at the top and bottom of the figure represent the position of the closest negative (DA) marker. Genes in <i>Tcs1</i> are red and in <i>Tcs2</i> blue (see box for definitions). Inset shows the organization of the human (HLA) and rat (RT1) MHC regions. Non-recombinant congenic strains, which have fragments spanning the entire MHC region, are not shown. xMHC-II, extended MHC class II region; xMHC-I, extended MHC class I region.</p