Project description:HLA-DRB1 alleles have been associated with several autoimmune diseases. In anti-citrullinated protein antibody positive rheumatoid arthritis (ACPA-positive RA), HLA-DRB1 shared epitope (SE) alleles are the major genetic risk factors. In order to investigate whether expression of different alleles of major histocompatibility complex (MHC) Class II genes influence functions of immune cells, we investigated transcriptomic profiles of a variety of immune cells from healthy individuals carrying different HLA-DRB1 alleles. Sequencing libraries from peripheral blood mononuclear cells, CD4+ T cells, CD8+ T cells, and CD14+ monocytes of 32 genetically pre-selected healthy female individuals were generated, sequenced and reads were aligned to the standard reference. For the MHC region, reads were mapped to available MHC reference haplotypes and AltHapAlignR was used to estimate gene expression. Using this method, HLA-DRB and HLA-DQ were found to be differentially expressed in different immune cells of healthy individuals as well as in whole blood samples of RA patients carrying HLA-DRB1 SE-positive versus SE-negative alleles. In contrast, no genes outside the MHC region were differentially expressed between individuals carrying HLA-DRB1 SE-positive and SE-negative alleles. Existing methods for HLA-DR allele-specific protein expression were evaluated but were not mature enough to provide appropriate complementary information at the protein level. Altogether, our findings suggest that immune effects associated with different allelic forms of HLA-DR and HLA-DQ may be associated not only with differences in the structure of these proteins, but also with differences in their expression levels.
Project description:Transposon insertion site sequencing (TIS) is a powerful method for associating genotype to phenotype. However, all TIS methods described to date use short nucleotide sequence reads which cannot uniquely determine the locations of transposon insertions within repeating genomic sequences where the repeat units are longer than the sequence read length. To overcome this limitation, we have developed a TIS method using Oxford Nanopore sequencing technology that generates and uses long nucleotide sequence reads; we have called this method LoRTIS (Long Read Transposon Insertion-site Sequencing). This experiment data contains sequence files generated using Nanopore and Illumina platforms. Biotin1308.fastq.gz and Biotin2508.fastq.gz are fastq files generated from nanopore technology. Rep1-Tn.fastq.gz and Rep1-Tn.fastq.gz are fastq files generated using Illumina platform. In this study, we have compared the efficiency of two methods in identification of transposon insertion sites.
Project description:We used the nanopore Cas9 targeted sequencing (nCATS) strategy to specifically sequence 125 L1HS-containing loci in parallel and measure their DNA methylation levels using nanopore long-read sequencing. Each targeted locus is sequenced at high coverage (~45X) with unambiguously mapped reads spanning the entire L1 element, as well as its flanking sequences over several kilobases. The genome-wide profile of L1 methylation was also assessed by bs-ATLAS-seq in the same cell lines (E-MTAB-10895).
Project description:Modern antigen vaccine designs and studies of human leukocyte antigen (HLA)-mediated immune responses rely heavily on the knowledge of HLA allele-specific binding motifs and computational prediction of antigen-HLA binding affinity. Breakthroughs in HLA peptidomics have considerably expanded the databases of natural HLA antigens and enabled detailed characterizations of antigen-HLA binding specificity. However, cautions must be made when analyzing HLA peptidomics data because identified peptides may be contaminants or may weakly bind to the HLA molecules. Here, a hybrid de novo peptide sequencing approach was applied to large-scale mono-allelic HLA peptidomics datasets to uncover new antigens and refine current knowledge of HLA binding motifs. Up to 12-40% contaminations in the form of tryptic peptides were identified in the peptidomics data of HLA alleles whose binding motifs do not involve an arginine or a lysine at the C-terminus. Thousands of these peptides were reported in a community database as positive antigens and might be erroneously used to train prediction models. Furthermore, unsupervised clustering of identified antigens not only revealed additional binding motifs for several HLA class I alleles but also effectively isolated outliers which were confirmed to be false positives in a binding experiment. Overall, our findings expanded the knowledge of HLA binding specificity and indicated that a more careful HLA peptidomics data interpretation protocol is needed to ensure the high quality of community antigen databases.