Dense genotyping of immune-related loci implicates host responses to microbial exposure in Behçet's disease susceptibility.

We analyzed 1,900 Turkish Behçet's disease cases and 1,779 controls genotyped with the Immunochip. The most significantly associated SNP was rs1050502, a tag SNP for HLA-B*51. In the Turkish discovery set, we identified three new risk loci, IL1A-IL1B, IRF8, and CEBPB-PTPN1, with genome-wide significance (P < 5 × 10-8) by direct genotyping and ADO-EGR2 by imputation. We replicated the ADO-EGR2, IRF8, and CEBPB-PTPN1 loci by genotyping 969 Iranian cases and 826 controls. Imputed data in 608 Japanese cases and 737 controls further replicated ADO-EGR2 and IRF8, and meta-analysis additionally identified RIPK2 and LACC1. The disease-associated allele of rs4402765, the lead marker at IL1A-IL1B, was associated with both decreased IL-1α and increased IL-1ß production. ABO non-secretor genotypes for two ancestry-specific FUT2 SNPs showed strong disease association (P = 5.89 × 10-15). Our findings extend the list of susceptibility genes shared with Crohn's disease and leprosy and implicate mucosal factors and the innate immune response to microbial exposure in Behçet's disease susceptibility.

Filling annotation gaps in yeast genomes using genome-wide contact maps.

MOTIVATIONS: De novo sequencing of genomes is followed by annotation analyses aiming at identifying functional genomic features such as genes, non-coding RNAs or regulatory sequences, taking advantage of diverse datasets. These steps sometimes fail at detecting non-coding functional sequences: for example, origins of replication, centromeres and rDNA positions have proven difficult to annotate with high confidence. Here, we demonstrate an unconventional application of Chromosome Conformation Capture (3C) technique, which typically aims at deciphering the average 3D organization of genomes, by showing how functional information about the sequence can be extracted solely from the chromosome contact map. RESULTS: Specifically, we describe a combined experimental and bioinformatic procedure that determines the genomic positions of centromeres and ribosomal DNA clusters in yeasts, including species where classical computational approaches fail. For instance, we determined the centromere positions in Naumovozyma castellii, where these coordinates could not be obtained previously. Although computed centromere positions were characterized by conserved synteny with neighboring species, no consensus sequences could be found, suggesting that centromeric binding proteins or mechanisms have significantly diverged. We also used our approach to refine centromere positions in Kuraishia capsulata and to identify rDNA positions in Debaryomyces hansenii. Our study demonstrates how 3C data can be used to complete the functional annotation of eukaryotic genomes. AVAILABILITY AND IMPLEMENTATION: The source code is provided in the Supplementary Material. This includes a zipped file with the Python code and a contact matrix of Saccharomyces cerevisiae. CONTACT: romain.koszul@pasteur.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.