Multiple Sclerosis risk variants regulate gene expression in innate and adaptive immune cells

At least 200 single-nucleotide polymorphisms (SNPs) are associated with multiple sclerosis (MS) risk. A key function that could mediate SNP-encoded MS risk is their regulatory effects on gene expression. We performed microarrays using RNA extracted from purified immune cell types from 73 untreated MS cases and 97 healthy controls and then performed Cis expression quantitative trait loci mapping studies using additive linear models. We describe MS risk expression quantitative trait loci associations for 129 distinct genes. By extending these models to include an interaction term between genotype and phenotype, we identify MS risk SNPs with opposing effects on gene expression in cases compared with controls, namely, rs2256814 MYT1 in CD4 cells (q = 0.05) and rs12087340 RF00136 in monocyte cells (q = 0.04). The rs703842 SNP was also associated with a differential effect size on the expression of the METTL21B gene in CD8 cells of MS cases relative to controls (q = 0.03). Our study provides a detailed map of MS risk loci that function by regulating gene expression in cell types relevant to MS

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Multiple Sclerosis risk SNPs modify gene expression in immune cells

Background: Population based genome wide association studies have identified 110 single nucleotide polymorphisms (SNPs) that are associated with an increase in MS risk. These SNPs are all common, and have odds ratios of between 1.1 and 1.4. Most are found in non-protein coding regions, and their functions are largely unknown. Objectives: Importantly, recent work has shown that some non-coding SNPs can function by changing immune gene expression levels as a quantitative trait, termed expression quantitative trait loci (eQTL). We conducted studies to evaluate the effects of MS risk SNPs on gene expression in four main immune cell types. Methods: We isolated monocytes, B-cells, CD4- and CD8- T-cells from untreated relapsing MS cases (n=79) and healthy controls (n=101). To test for cis-eQTL associations, we selected all genes within +/-500kb of an MS risk SNP (2500 pairs in total). The Illumina Immunochip was used to genotype for MS risk SNPs, and gene expression was measured for each cell type by microarray. Results: We have identified MS risk eQTL associations in each immune cell type, some of which are cell type specific. We also present preliminary data showing that some MS risk SNPs could exert differential effects on gene expression in cases compared to controls. Here we report likely disease state specific eQTLs for all cell types with the top associations being: RNF26/rs9736016, B cells; MACROD1/rs694739, CD8 cells; SLC25A41/rs1077667, CD4 cells; GPR18/rs4772201, monocyte cells. Conclusions: We have shown that MS risk SNPs contribute to immune heterogeneity. It is hoped that through an understanding of the functions of individual common risk variants, it may be possible to uncover the processes and cell types that are most important for conveying the genetic risk of MS