ABSTRACT
Chronic kidney disease (CKD) affects 10% of the human population, with only a small fraction genetically defined. CKD is also common in dogs and has been diagnosed in nearly all breeds, but its genetic basis remains unclear. Here, we performed a Bayesian mixed model genome-wide association analysis for canine CKD in a boxer population of 117 canine cases and 137 controls, and identified 21 genetic regions associated with the disease. At the top markers from each CKD region, the cases carried an average of 20.2 risk alleles, significantly higher than controls (15.6 risk alleles). An ANOVA test showed that the 21 CKD regions together explained 57% of CKD phenotypic variation in the population. Based on whole genome sequencing data of 20 boxers, we identified 5,206 variants in LD with the top 50 BayesR markers. Following comparative analysis with human regulatory data, 17 putative regulatory variants were identified and tested with electrophoretic mobility shift assays. In total four variants, three intronic variants from the MAGI2 and GALNT18 genes, and one variant in an intergenic region on chr28, showed alternative binding ability for the risk and protective alleles in kidney cell lines. Many genes from the 21 CKD regions, RELN, MAGI2, FGFR2 and others, have been implicated in human kidney development or disease. The results from this study provide new information that may enlighten the etiology of CKD in both dogs and humans.
Subject(s)
Genome-Wide Association Study , Renal Insufficiency, Chronic , Dogs , Humans , Animals , Bayes Theorem , Renal Insufficiency, Chronic/genetics , Renal Insufficiency, Chronic/veterinary , Renal Insufficiency, Chronic/epidemiology , Kidney , Alleles , Polymorphism, Single NucleotideABSTRACT
BACKGROUND: Many wild species have suffered drastic population size declines over the past centuries, which have led to 'genomic erosion' processes characterized by reduced genetic diversity, increased inbreeding, and accumulation of harmful mutations. Yet, genomic erosion estimates of modern-day populations often lack concordance with dwindling population sizes and conservation status of threatened species. One way to directly quantify the genomic consequences of population declines is to compare genome-wide data from pre-decline museum samples and modern samples. However, doing so requires computational data processing and analysis tools specifically adapted to comparative analyses of degraded, ancient or historical, DNA data with modern DNA data as well as personnel trained to perform such analyses. RESULTS: Here, we present a highly flexible, scalable, and modular pipeline to compare patterns of genomic erosion using samples from disparate time periods. The GenErode pipeline uses state-of-the-art bioinformatics tools to simultaneously process whole-genome re-sequencing data from ancient/historical and modern samples, and to produce comparable estimates of several genomic erosion indices. No programming knowledge is required to run the pipeline and all bioinformatic steps are well-documented, making the pipeline accessible to users with different backgrounds. GenErode is written in Snakemake and Python3 and uses Conda and Singularity containers to achieve reproducibility on high-performance compute clusters. The source code is freely available on GitHub ( https://github.com/NBISweden/GenErode ). CONCLUSIONS: GenErode is a user-friendly and reproducible pipeline that enables the standardization of genomic erosion indices from temporally sampled whole genome re-sequencing data.
Subject(s)
Computational Biology , Genome , Animals , Endangered Species , Genomics , Reproducibility of Results , SoftwareABSTRACT
Multiple myeloma (MM) is an incurable and aggressive plasma cell malignancy characterized by a complex karyotype with multiple structural variants (SVs) and copy-number variations (CNVs). Linked-read whole-genome sequencing (lrWGS) allows for refined detection and reconstruction of SVs by providing long-range genetic information from standard short-read sequencing. This makes lrWGS an attractive solution for capturing the full genomic complexity of MM. Here we show that high-quality lrWGS data can be generated from low numbers of cells subjected to fluorescence-activated cell sorting (FACS) without DNA purification. Using this protocol, we analyzed MM cells after FACS from 37 patients with MM using lrWGS. We found high concordance between lrWGS and fluorescence in situ hybridization (FISH) for the detection of recurrent translocations and CNVs. Outside of the regions investigated by FISH, we identified >150 additional SVs and CNVs across the cohort. Analysis of the lrWGS data allowed for resolution of the structure of diverse SVs affecting the MYC and t(11;14) loci, causing the duplication of genes and gene regulatory elements. In addition, we identified private SVs causing the dysregulation of genes recurrently involved in translocations with the IGH locus and show that these can alter the molecular classification of MM. Overall, we conclude that lrWGS allows for the detection of aberrations critical for MM prognostics and provides a feasible route for providing comprehensive genetics. Implementing lrWGS could provide more accurate clinical prognostics, facilitate genomic medicine initiatives, and greatly improve the stratification of patients included in clinical trials.
Subject(s)
Multiple Myeloma , DNA Copy Number Variations , Genomics , Humans , In Situ Hybridization, Fluorescence , Multiple Myeloma/diagnosis , Multiple Myeloma/genetics , Translocation, Genetic , Whole Genome SequencingABSTRACT
Natural killer (NK) cells play roles in viral clearance and early surveillance against malignant transformation, yet our knowledge of the underlying mechanisms controlling their development and functions remain incomplete. To reveal cell fate-determining pathways in NK cell progenitors (NKP), we utilized an unbiased approach and generated comprehensive gene expression profiles of NK cell progenitors. We found that the NK cell program was gradually established in the CLP to preNKP and preNKP to rNKP transitions. In line with FOXO1 and FOXO3 being co-expressed through the NK developmental trajectory, the loss of both perturbed the establishment of the NK cell program and caused stalling in both NK cell development and maturation. In addition, we found that the combined loss of FOXO1 and FOXO3 caused specific changes to the composition of the non-cytotoxic innate lymphoid cell (ILC) subsets in bone marrow, spleen, and thymus. By combining transcriptome and chromatin profiling, we revealed that FOXO TFs ensure proper NK cell development at various lineage-commitment stages through orchestrating distinct molecular mechanisms. Combined FOXO1 and FOXO3 deficiency in common and innate lymphoid cell progenitors resulted in reduced expression of genes associated with NK cell development including ETS-1 and their downstream target genes. Lastly, we found that FOXO1 and FOXO3 controlled the survival of committed NK cells via gene regulation of IL-15Rß (CD122) on rNKPs and bone marrow NK cells. Overall, we revealed that FOXO1 and FOXO3 function in a coordinated manner to regulate essential developmental genes at multiple stages during murine NK cell and ILC lineage commitment.
Subject(s)
Forkhead Box Protein O1 , Forkhead Box Protein O3 , Killer Cells, Natural , Lymphoid Progenitor Cells , Animals , Cell Differentiation/immunology , Forkhead Box Protein O1/immunology , Forkhead Box Protein O3/immunology , Immunity, Innate , Killer Cells, Natural/cytology , Killer Cells, Natural/immunology , Lymphoid Progenitor Cells/cytology , Lymphoid Progenitor Cells/immunology , Mice , Mice, Inbred C57BLABSTRACT
The development of B cells relies on an intricate network of transcription factors critical for developmental progression and lineage commitment. In the B cell developmental trajectory, a temporal switch from predominant Foxo3 to Foxo1 expression occurs at the CLP stage. Utilizing VAV-iCre mediated conditional deletion, we found that the loss of FOXO3 impaired B cell development from LMPP down to B cell precursors, while the loss of FOXO1 impaired B cell commitment and resulted in a complete developmental block at the CD25 negative proB cell stage. Strikingly, the combined loss of FOXO1 and FOXO3 resulted in the failure to restrict the myeloid potential of CLPs and the complete loss of the B cell lineage. This is underpinned by the failure to enforce the early B-lineage gene regulatory circuitry upon a predominantly pre-established open chromatin landscape. Altogether, this demonstrates that FOXO3 and FOXO1 cooperatively govern early lineage restriction and initiation of B-lineage commitment in CLPs.
Subject(s)
Hematopoiesis , Lymphoid Progenitor Cells , B-Lymphocytes/metabolism , Forkhead Box Protein O1/genetics , Forkhead Box Protein O1/metabolism , Hematopoiesis/genetics , Lymphoid Progenitor Cells/metabolism , Precursor Cells, B-Lymphoid/metabolismABSTRACT
Despite the success of genome-wide association studies, much of the genetic contribution to complex traits remains unexplained. Here, we analyse high coverage whole-genome sequencing data, to evaluate the contribution of rare genetic variants to 414 plasma proteins. The frequency distribution of genetic variants is skewed towards the rare spectrum, and damaging variants are more often rare. We estimate that less than 4.3% of the narrow-sense heritability is expected to be explained by rare variants in our cohort. Using a gene-based approach, we identify Cis-associations for 237 of the proteins, which is slightly more compared to a GWAS (N = 213), and we identify 34 associated loci in Trans. Several associations are driven by rare variants, which have larger effects, on average. We therefore conclude that rare variants could be of importance for precision medicine applications, but have a more limited contribution to the missing heritability of complex diseases.
Subject(s)
Genome-Wide Association Study , Multifactorial Inheritance , Blood Proteins/genetics , Genetic Predisposition to Disease , Genetic Variation , Humans , Multifactorial Inheritance/genetics , Polymorphism, Single Nucleotide , Whole Genome SequencingABSTRACT
Over the last six decades, populations of the bumblebees Bombus sylvicola and Bombus balteatus in Colorado have experienced decreases in tongue length, a trait important for plant-pollinator mutualisms. It has been hypothesized that this observation reflects selection resulting from shifts in floral composition under climate change. Here we used morphometrics and population genomics to determine whether morphological change is ongoing, investigate the genetic basis of morphological variation, and analyse population structure in these populations. We generated a genome assembly of B. balteatus. We then analysed whole-genome sequencing data and morphometric measurements of 580 samples of both species from seven high-altitude localities. Out of 281 samples originally identified as B. sylvicola, 67 formed a separate genetic cluster comprising a newly-discovered cryptic species ("incognitus"). However, an absence of genetic structure within species suggests that gene flow is common between mountains. We found a significant decrease in tongue length between bees collected between 2012-2014 and in 2017, indicating that morphological shifts are ongoing. We did not discover any genetic associations with tongue length, but a SNP related to production of a proteolytic digestive enzyme was implicated in body size variation. We identified evidence of covariance between kinship and both tongue length and body size, which is suggestive of a genetic component of these traits, although it is possible that shared environmental effects between colonies are responsible. Our results provide evidence for ongoing modification of a morphological trait important for pollination and indicate that this trait probably has a complex genetic and environmental basis.
Subject(s)
Gene Flow , Pollination , Animals , Bees/genetics , Gene Flow/genetics , Genomics , Phenotype , TongueABSTRACT
Pyometra is one of the most common diseases in female dogs, presenting as purulent inflammation and bacterial infection of the uterus. On average 20% of intact female dogs are affected before 10 years of age, a proportion that varies greatly between breeds (3-66%). The clear breed predisposition suggests that genetic risk factors are involved in disease development. To identify genetic risk factors associated with the disease, we performed a genome-wide association study (GWAS) in golden retrievers, a breed with increased risk of developing pyometra (risk ratio: 3.3). We applied a mixed model approach comparing 98 cases, and 96 healthy controls and identified an associated locus on chromosome 22 (p = 1.2 × 10-6, passing Bonferroni corrected significance). This locus contained five significantly associated SNPs positioned within introns of the ATP-binding cassette transporter 4 (ABCC4) gene. This gene encodes a transmembrane transporter that is important for prostaglandin transport. Next generation sequencing and genotyping of cases and controls subsequently identified four missense SNPs within the ABCC4 gene. One missense SNP at chr22:45,893,198 (p.Met787Val) showed complete linkage disequilibrium with the associated GWAS SNPs suggesting a potential role in disease development. Another locus on chromosome 18 overlapping the TESMIN gene, is also potentially implicated in the development of the disease.
Subject(s)
ATP-Binding Cassette Transporters/genetics , Dog Diseases/genetics , Pyometra/veterinary , Age of Onset , Animals , Case-Control Studies , Chromosome Mapping , Dogs , Female , Gene Frequency , Genetic Predisposition to Disease , Genome-Wide Association Study , Polymorphism, Single Nucleotide , Pyometra/geneticsABSTRACT
Herbs and spices are some of the most vulnerable products in terms of fraud and adulteration in the food sector. Although standard analytical methods are accurate for quality control of specific lead or marker compounds, they cannot accurately assess the entire species composition of many marketed products. Complementary analytical approaches are thus often used for comprehensive screening of herbs and spices. In this study we evaluate DNA metabarcoding for the identification and authentication of 62 products, containing basil, oregano, and paprika collected from different retailers and importers in Norway. Our results show varying degrees of discrepancy between the constituent species and those listed on the product labels, despite high product authenticity. We suggest the false positives result from the sensitivity of DNA metabarcoding and filtering thresholds should be integrated into protocols to reduce false positives. Our results highlight how integrating DNA metabarcoding into the toolbox of analytical methods for quality control of fresh and/or processed plant-based food can improve product quality.
ABSTRACT
Small populations are often exposed to high inbreeding and mutational load that can increase the risk of extinction. The Sumatran rhinoceros was widespread in Southeast Asia, but is now restricted to small and isolated populations on Sumatra and Borneo, and most likely extinct on the Malay Peninsula. Here, we analyse 5 historical and 16 modern genomes from these populations to investigate the genomic consequences of the recent decline, such as increased inbreeding and mutational load. We find that the Malay Peninsula population experienced increased inbreeding shortly before extirpation, which possibly was accompanied by purging. The populations on Sumatra and Borneo instead show low inbreeding, but high mutational load. The currently small population sizes may thus in the near future lead to inbreeding depression. Moreover, we find little evidence for differences in local adaptation among populations, suggesting that future inbreeding depression could potentially be mitigated by assisted gene flow among populations.
Subject(s)
Conservation of Natural Resources , Endangered Species , Perissodactyla/genetics , Animals , Borneo , Endangered Species/history , Female , Gene Flow , Genetic Variation , Genome , History, 21st Century , History, Ancient , Inbreeding , Indonesia , Loss of Function Mutation , Male , Mutation , Population Density , Selection, GeneticABSTRACT
Evidence is accumulating that gene flow commonly occurs between recently diverged species, despite the existence of barriers to gene flow in their genomes. However, we still know little about what regions of the genome become barriers to gene flow and how such barriers form. Here, we compare genetic differentiation across the genomes of bumblebee species living in sympatry and allopatry to reveal the potential impact of gene flow during species divergence and uncover genetic barrier loci. We first compared the genomes of the alpine bumblebee Bombus sylvicola and a previously unidentified sister species living in sympatry in the Rocky Mountains, revealing prominent islands of elevated genetic divergence in the genome that colocalize with centromeres and regions of low recombination. This same pattern is observed between the genomes of another pair of closely related species living in allopatry (B. bifarius and B. vancouverensis). Strikingly however, the genomic islands exhibit significantly elevated absolute divergence (dXY) in the sympatric, but not the allopatric, comparison indicating that they contain loci that have acted as barriers to historical gene flow in sympatry. Our results suggest that intrinsic barriers to gene flow between species may often accumulate in regions of low recombination and near centromeres through processes such as genetic hitchhiking, and that divergence in these regions is accentuated in the presence of gene flow.
Subject(s)
Bees/genetics , Gene Flow , Genome, Insect , Reproductive Isolation , Sympatry , Animals , Evolution, Molecular , Recombination, GeneticABSTRACT
Ancient DNA has significantly improved our understanding of the evolution and population history of extinct megafauna. However, few studies have used complete ancient genomes to examine species responses to climate change prior to extinction. The woolly rhinoceros (Coelodonta antiquitatis) was a cold-adapted megaherbivore widely distributed across northern Eurasia during the Late Pleistocene and became extinct approximately 14 thousand years before present (ka BP). While humans and climate change have been proposed as potential causes of extinction [1-3], knowledge is limited on how the woolly rhinoceros was impacted by human arrival and climatic fluctuations [2]. Here, we use one complete nuclear genome and 14 mitogenomes to investigate the demographic history of woolly rhinoceros leading up to its extinction. Unlike other northern megafauna, the effective population size of woolly rhinoceros likely increased at 29.7 ka BP and subsequently remained stable until close to the species' extinction. Analysis of the nuclear genome from a â¼18.5-ka-old specimen did not indicate any increased inbreeding or reduced genetic diversity, suggesting that the population size remained steady for more than 13 ka following the arrival of humans [4]. The population contraction leading to extinction of the woolly rhinoceros may have thus been sudden and mostly driven by rapid warming in the Bølling-Allerød interstadial. Furthermore, we identify woolly rhinoceros-specific adaptations to arctic climate, similar to those of the woolly mammoth. This study highlights how species respond differently to climatic fluctuations and further illustrates the potential of palaeogenomics to study the evolutionary history of extinct species.
Subject(s)
Archaeology/methods , DNA, Ancient/analysis , Perissodactyla/genetics , Animals , Climate Change , Extinction, Biological , Fossils , Genome/genetics , Genomics/methods , Population Density , Population DynamicsABSTRACT
The advent of novel sequencing techniques has unraveled a tremendous diversity on Earth. Genomic data allow us to understand ecology and function of organisms that we would not otherwise know existed. However, major methodological challenges remain, in particular for multicellular organisms with large genomes. Arbuscular mycorrhizal (AM) fungi are important plant symbionts with cryptic and complex multicellular life cycles, thus representing a suitable model system for method development. Here, we report a novel method for large scale, unbiased nuclear sorting, sequencing, and de novo assembling of AM fungal genomes. After comparative analyses of three assembly workflows we discuss how sequence data from single nuclei can best be used for different downstream analyses such as phylogenomics and comparative genomics of single nuclei. Based on analysis of completeness, we conclude that comprehensive de novo genome assemblies can be produced from six to seven nuclei. The method is highly applicable for a broad range of taxa, and will greatly improve our ability to study multicellular eukaryotes with complex life cycles.
Subject(s)
Computational Biology/methods , Eukaryota/genetics , Genome , Genomics , Algorithms , Fungi/genetics , Genomics/methods , WorkflowABSTRACT
Osteosarcoma is a debilitating bone cancer that affects humans, especially children and adolescents. A homologous form of osteosarcoma spontaneously occurs in dogs, and its differential incidence observed across breeds allows for the investigation of tumor mutations in the context of multiple genetic backgrounds. Using whole-exome sequencing and dogs from three susceptible breeds (22 golden retrievers, 21 Rottweilers, and 23 greyhounds), we found that osteosarcoma tumors show a high frequency of somatic copy-number alterations (SCNA), affecting key oncogenes and tumor-suppressor genes. The across-breed results are similar to what has been observed for human osteosarcoma, but the disease frequency and somatic mutation counts vary in the three breeds. For all breeds, three mutational signatures (one of which has not been previously reported) and 11 significantly mutated genes were identified. TP53 was the most frequently altered gene (83% of dogs have either mutations or SCNA in TP53), recapitulating observations in human osteosarcoma. The second most frequently mutated gene, histone methyltransferase SETD2, has known roles in multiple cancers, but has not previously been strongly implicated in osteosarcoma. This study points to the likely importance of histone modifications in osteosarcoma and highlights the strong genetic similarities between human and dog osteosarcoma, suggesting that canine osteosarcoma may serve as an excellent model for developing treatment strategies in both species.Significance: Canine osteosarcoma genomics identify SETD2 as a possible oncogenic driver of osteosarcoma, and findings establish the canine model as a useful comparative model for the corresponding human disease. Cancer Res; 78(13); 3421-31. ©2018 AACR.
Subject(s)
Dog Diseases/genetics , Histone-Lysine N-Methyltransferase/genetics , Osteosarcoma/genetics , Animals , DNA Copy Number Variations , DNA Mutational Analysis , Disease Models, Animal , Dog Diseases/pathology , Dogs , Female , Genetic Predisposition to Disease , Humans , Male , Mutation , Osteosarcoma/pathology , Tumor Suppressor Protein p53/genetics , Exome SequencingABSTRACT
Here, we present two perspectives on the task of predicting post translational modifications (PTMs) from local sequence fragments using machine learning algorithms. The first is the description of the fundamental steps required to construct a PTM predictor from the very beginning. These steps include data gathering, feature extraction, or machine-learning classifier selection. The second part of our work contains the detailed discussion of more advanced problems which are encountered in PTM prediction task. Probably the most challenging issues which we have covered here are: (1) how to address the training data class imbalance problem (we also present statistics describing the problem); (2) how to properly set up cross-validation folds with an approach which takes into account the homology of protein data records, to address this problem we present our folds-over-clusters algorithm; and (3) how to efficiently reach for new sources of learning features. Presented techniques and notes resulted from intense studies in the field, performed by our and other groups, and can be useful both for researchers beginning in the field of PTM prediction and for those who want to extend the repertoire of their research techniques.
Subject(s)
Computational Biology/methods , Protein Processing, Post-Translational/genetics , Proteins/chemistry , Software , Algorithms , Amino Acid Sequence/genetics , Machine Learning , Proteins/genetics , Sequence Analysis, ProteinABSTRACT
BACKGROUND: Canine atopic dermatitis (CAD) is a chronic inflammatory skin disease triggered by allergic reactions involving IgE antibodies directed towards environmental allergens. We previously identified a ~1.5 Mb locus on canine chromosome 27 associated with CAD in German shepherd dogs (GSDs). Fine-mapping indicated association closest to the PKP2 gene encoding plakophilin 2. RESULTS: Additional genotyping and association analyses in GSDs combined with control dogs from five breeds with low-risk for CAD revealed the top SNP 27:19,086,778 (p = 1.4 × 10(-7)) and a rare ~48 kb risk haplotype overlapping the PKP2 gene and shared only with other high-risk CAD breeds. We selected altogether nine SNPs (four top-associated in GSDs and five within the ~48 kb risk haplotype) that spanned ~280 kb forming one risk haplotype carried by 35 % of the GSD cases and 10 % of the GSD controls (OR = 5.1, p = 5.9 × 10(-5)), and another haplotype present in 85 % of the GSD cases and 98 % of the GSD controls and conferring a protective effect against CAD in GSDs (OR = 0.14, p = 0.0032). Eight of these SNPs were analyzed for transcriptional regulation using reporter assays where all tested regions exerted regulatory effects on transcription in epithelial and/or immune cell lines, and seven SNPs showed allelic differences. The DNA fragment with the top-associated SNP 27:19,086,778 displayed the highest activity in keratinocytes with 11-fold induction of transcription by the risk allele versus 8-fold by the control allele (pdifference = 0.003), and also mapped close (~3 kb) to an ENCODE skin-specific enhancer region. CONCLUSIONS: Our experiments indicate that multiple CAD-associated genetic variants located in cell type-specific enhancers are involved in gene regulation in different cells and tissues. No single causative variant alone, but rather multiple variants combined in a risk haplotype likely contribute to an altered expression of the PKP2 gene, and possibly nearby genes, in immune and epithelial cells, and predispose GSDs to CAD.
Subject(s)
Dermatitis, Atopic/veterinary , Dog Diseases/genetics , Enhancer Elements, Genetic/genetics , Genetic Loci/genetics , Genetic Predisposition to Disease/genetics , Plakophilins/genetics , Polymorphism, Single Nucleotide , Animals , Cell Line , Dermatitis, Atopic/genetics , Dogs , Haplotypes/genetics , HumansABSTRACT
UNLABELLED: High-throughput genotyping and sequencing technologies facilitate studies of complex genetic traits and provide new research opportunities. The increasing popularity of genome-wide association studies (GWAS) leads to the discovery of new associated loci and a better understanding of the genetic architecture underlying not only diseases, but also other monogenic and complex phenotypes. Several softwares are available for performing GWAS analyses, R environment being one of them. RESULTS: We present cgmisc, an R package that enables enhanced data analysis and visualization of results from GWAS. The package contains several utilities and modules that complement and enhance the functionality of the existing software. It also provides several tools for advanced visualization of genomic data and utilizes the power of the R language to aid in preparation of publication-quality figures. Some of the package functions are specific for the domestic dog (Canis familiaris) data. AVAILABILITY AND IMPLEMENTATION: The package is operating system-independent and is available from: https://github.com/cgmisc-team/cgmisc CONTACT: marcin.kierczak@imbim.uu.se. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Subject(s)
Computer Graphics , Genome-Wide Association Study/methods , Genomics/methods , Software , Animals , Dogs , Genotype , Humans , Loss of Heterozygosity , PhenotypeABSTRACT
Hypothyroidism is a complex clinical condition found in both humans and dogs, thought to be caused by a combination of genetic and environmental factors. In this study we present a multi-breed analysis of predisposing genetic risk factors for hypothyroidism in dogs using three high-risk breeds--the Gordon Setter, Hovawart and the Rhodesian Ridgeback. Using a genome-wide association approach and meta-analysis, we identified a major hypothyroidism risk locus shared by these breeds on chromosome 12 (p = 2.1x10(-11)). Further characterisation of the candidate region revealed a shared ~167 kb risk haplotype (4,915,018-5,081,823 bp), tagged by two SNPs in almost complete linkage disequilibrium. This breed-shared risk haplotype includes three genes (LHFPL5, SRPK1 and SLC26A8) and does not extend to the dog leukocyte antigen (DLA) class II gene cluster located in the vicinity. These three genes have not been identified as candidate genes for hypothyroid disease previously, but have functions that could potentially contribute to the development of the disease. Our results implicate the potential involvement of novel genes and pathways for the development of canine hypothyroidism, raising new possibilities for screening, breeding programmes and treatments in dogs. This study may also contribute to our understanding of the genetic etiology of human hypothyroid disease, which is one of the most common endocrine disorders in humans.