A Simple Repeat Polymorphism in the MITF-M Promoter Is a Key Regulator of White Spotting in Dogs

The white spotting locus (S) in dogs is colocalized with the MITF (microphtalmia-associated transcription factor) gene. The phenotypic effects of the four S alleles range from solid colour (S) to extreme white spotting (sw). We have investigated four candidate mutations associated with the sw allele, a SINE insertion, a SNP at a conserved site and a simple repeat polymorphism all associated with the MITF-M promoter as well as a 12 base pair deletion in exon 1B. The variants associated with white spotting at all four loci were also found among wolves and we conclude that none of these could be a sole causal mutation, at least not for extreme white spotting. We propose that the three canine white spotting alleles are not caused by three independent mutations but represent haplotype effects due to different combinations of causal polymorphisms. The simple repeat polymorphism showed extensive diversity both in dogs and wolves, and allele-sharing was common between wolves and white spotted dogs but was non-existent between solid and spotted dogs as well as between wolves and solid dogs. This finding was unexpected as Solid is assumed to be the wild-type allele. The data indicate that the simple repeat polymorphism has been a target for selection during dog domestication and breed formation. We also evaluated the significance of the three MITF-M associated polymorphisms with a Luciferase assay, and found conclusive evidence that the simple repeat polymorphism affects promoter activity. Three alleles associated with white spotting gave consistently lower promoter activity compared with the allele associated with solid colour. We propose that the simple repeat polymorphism affects cooperativity between transcription factors binding on either flanking sides of the repeat. Thus, both genetic and functional evidence show that the simple repeat polymorphism is a key regulator of white spotting in dogs.Peer reviewe

Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data

Transcriptomic analyses are commonly used to identify differentially expressed genes between patients and controls, or within individuals across disease courses. These methods, whilst effective, cannot encompass the combinatorial effects of genes driving disease. We applied rule-based machine learning (RBML) models and rule networks (RN) to an existing paediatric Systemic Lupus Erythematosus (SLE) blood expression dataset, with the goal of developing gene networks to separate low and high disease activity (DA1 and DA3). The resultant model had an 81% accuracy to distinguish between DA1 and DA3, with unsupervised hierarchical clustering revealing additional subgroups indicative of the immune axis involved or state of disease flare. These subgroups correlated with clinical variables, suggesting that the gene sets identified may further the understanding of gene networks that act in concert to drive disease progression. This included roles for genes (i) induced by interferons (IFI35 and OTOF), (ii) key to SLE cell types (KLRB1 encoding CD161), or (iii) with roles in autophagy and NF-κB pathway responses (CKAP4). As demonstrated here, RBML approaches have the potential to reveal novel gene patterns from within a heterogeneous disease, facilitating patient clinical and therapeutic stratification.ISSN:2045-232

The HLA region in ANCA-associated vasculitis : characterisation of genetic associations in a Scandinavian patient population

Objective: The antineutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAV) are inflammatory disorders with ANCA autoantibodies recognising either proteinase 3 (PR3-AAV) or myeloperoxidase (MPO-AAV). PR3-AAV and MPO-AAV have been associated with distinct loci in the human leucocyte antigen (HLA) region. While the association between MPO-AAV and HLA has been well characterised in East Asian populations where MPO-AAV is more common, studies in populations of European descent are limited. The aim of this study was to thoroughly characterise associations to the HLA region in Scandinavian patients with PR3-AAV as well as MPO-AAV. Methods: Genotypes of single-nucleotide polymorphisms (SNPs) located in the HLA region were extracted from a targeted exome-sequencing dataset comprising Scandinavian AAV cases and controls. Classical HLA alleles were called using xHLA. After quality control, association analyses were performed of a joint SNP/classical HLA allele dataset for cases with PR3-AAV (n=411) and MPO-AAV (n=162) versus controls (n=1595). Disease-associated genetic variants were analysed for association with organ involvement, age at diagnosis and relapse, respectively. Results: PR3-AAV was significantly associated with both HLA-DPB1*04:01 and rs1042335 at the HLADPB1 locus, also after stepwise conditional analysis. MPO-AAV was significantly associated with HLADRB1*04:04. Neither carriage of HLA-DPB1*04:01 alleles in PR3-AAV nor of HLA-DRB1*04:04 alleles in MPO-AAV were associated with organ involvement, age at diagnosis or relapse. Conclusions: The association to the HLA region was distinct in Scandinavian cases with MPO-AAV compared with cases of East Asian descent. In PR3-AAV, the two separate signals of association to the HLD-DPB1 region mediate potentially different functional effects