Biology subjects

Hayward, J. J.

Publications and source records attributed to Hayward, J. J..

6 recordsLinked to original sources

bioRxiv2025

Reproducibility of the evaluation of genetic variant pathogenicity based on the animal variant classification guidelines

Until recently, due to the absence of standardized guidelines tailored for veterinary use, the evaluation of genetic variant pathogenicity for single-gene diseases was based on a personal interpretation of the presented evidence, which has led to ambiguous interpretation. With the publication of the animal variant classification guidelines (AVCG), a more objective approach became available. Variants are evaluated based on twenty-three criteria and labeled as pathogenic, likely pathogenic, variant of uncertain significance, likely benign or benign. While the accuracy was thoroughly tested in the original publication, the reproducibility of the various steps involved was only briefly checked, which is why the current study was performed. Each variant from a set of 150 published likely causal variants for single-gene diseases from three species (dog, cat, horse) was independently and blindly assessed by three different reviewers, each applying the same AVCG. An overall agreement of 93% for decisions on the scope, i.e. whether they fit the inclusion criteria to allow evaluation with AVCG, was found. More importantly, the reproducibility was 65% for the pathogenicity classification and this increased to 83% clinically relevant agreement. While a direct comparison of the reproducibility with human literature is not possible for the scope, the reproducibility on pathogenicity classification is in line with reports using the human American College for Medical Genetics and Genomics and Association for Molecular Pathology guidelines for human variants. Overall, based on the current study, the reproducibility of the guidelines in veterinary species is within current expectations.

genetics↗

bioRxiv2024

Variant classification guidelines for animals to objectively evaluate genetic variant pathogenicity

Assessing the pathogenicity of a disease-associated variant in animals accurately is vital, both on a population and individual scale. At the population level, breeding decisions based on invalid DNA tests can lead to the incorrect exclusion of animals and compromise the long- term health of a population, and at the level of the individual animal, lead to incorrect treatment and even life-ending decisions. Criteria to determine pathogenicity are not standardized, hence no guidelines for animal variants are available. Here, we developed and optimized the animal variant classification guidelines, based on those developed for humans by The American College of Medical Genetics and Genomics, and demonstrated a superior classification in animals. We described methods to develop datasets for benchmarking the criteria and identified the most optimal in silico variant effect predictor tools. As the reproducibility was high, we classified 72 known disease-associated variants in cats and 40 other disease-associated variants in eight additional species.

genetics↗

bioRxiv2024

Genomic analyses identify 15 susceptibility loci and reveal HDAC2, SOX2-OT, and IGF2BP2 in a naturally-occurring canine model of gastric cancer

Gastric cancer (GC) is the fifth most common human cancer worldwide, but the genetic etiology is largely unknown. We performed a Bayesian genome-wide association study and selection analyses in a naturally-occurring canine model of GC, the Belgian Tervuren and Sheepdog breeds, to elucidate underlying genetic risk factors. We identified 15 loci with over 90% predictive accuracy for the GC phenotype. Variant filtering revealed germline putative regulatory variants for the EPAS1 (HIF2A) and PTEN genes and a coding variant in CD101. Although closely related to Tervuren and Sheepdogs, Belgian Malinois rarely develop GC. Across-breed analyses uncovered protective haplotypes under selection in Malinois at SOX2-OT and IGF2BP2. Among Tervuren and Sheepdogs, HDAC2 putative regulatory variants were present at comparatively high frequency and were associated with GC. Here, we describe a complex genetic architecture governing GC in a dog model, including genes such as PDZRN3, that have not been associated with human GC.

genomics↗

bioRxiv2021

Complex feline disease mapping using a dense genotyping array

The current feline genotyping array of 63k single nucleotide polymorphisms has proven its utility within breeds, and its use has led to the identification of variants associated with Mendelian traits in purebred cats. However, compared to single gene disorders, association studies of complex diseases, especially with the inclusion of random bred cats with relatively low linkage disequilibrium, require a denser genotyping array and an increased sample size to provide statistically significant associations. Here, we undertook a multi-breed study of 1,122 cats, most of which were admitted and phenotyped for nine common complex feline diseases at the Cornell University Hospital for Animals. Using a proprietary 340k single nucleotide polymorphism mapping array, we identified significant genome-wide associations with hyperthyroidism, diabetes mellitus, and eosinophilic keratoconjunctivitis. These results provide genomic locations for variant discovery and candidate gene screening for these important complex feline diseases, which are relevant not only to feline health, but also to the development of disease models for comparative studies.

genetics↗

bioRxiv2020

Influenza A viruses serially passaged in different MDCK cell lines exhibit limited sequence variation across their genomes, with the exception of the hemagglutinin gene

New methods for deep sequence analysis provide an opportunity to follow the emergence and dynamics of virus mutations in real time. Although viruses are commonly grown in cell culture for research and for vaccine development, the cells used to grow the virus are often not derived from the same tissue or even the same host that the virus naturally replicates in. The selective pressures of culturing virus in vitro are still only partially understood. MDCK cells are the standard cell for growing influenza viruses yet are derived from the epithelium of the canine kidney and are also heterogenous. We passaged human H3N2, H1N1 pandemic, and canine H3N2 influenza A viruses (IAV) in different lineages of MDCK cells, as well as lines engineered to express variant Sia receptors, including 2,3- and 2,6-linkages or N-glycolylneuraminic acid (Neu5Gc) or N-acetylneuraminic acid (Neu5Ac) forms. MDCK-Type II cells had lower infection efficiency and virus production, and infection appeared more dependent on protease activation of the virus. When viruses were passaged in the different cells, they exhibited only small numbers of consensus-level mutations, and most were within the HA gene. Both human IAVs showed selection for single nucleotide minority variants in the HA stem across cell types, as well as low frequency variants in the HA receptor binding site of virus passaged in cells expressing Neu5Gc. Canine H3N2 also showed minority variants near the receptor-binding site in cells expressing Neu5Gc and also in those expressing 2,6-linkages. IMPORTANCEThe genetic variation and adaptability of viruses are fundamental properties that allow their evolutionary success in the face of differing host environments and immune responses. The growth of viruses in cell culture is widely used for their study and for preparing vaccines. However, the selection pressures that cell passaging imposes on viruses are often poorly understood. We used deep sequence analysis to define, in detail, how three different influenza A viruses respond to passaging in different lineages of canine MDCK cells that are commonly used for their growth, as well as in variant cells engineered to express different forms of their cell surface receptor, sialic acid. This analysis revealed that most mutations occur in the HA gene and few sequence changes in the virus population reached high proportions. This is relevant for understanding the selective pressures of virus growth in cell culture and how it shapes evolutionary patterns.

microbiology↗

bioRxiv2019

Imputation of canine genotype array data using 365 whole-genome sequences improves power of genome-wide association studies

Genomic resources for the domestic dog have improved with the widespread adoption of a 173k SNP array platform and updated reference genome. SNP arrays of this density are sufficient for detecting genetic associations within breeds but are underpowered for finding associations across multiple breeds or in mixed-breed dogs, where linkage disequilibrium rapidly decays between markers, even though such studies would hold particular promise for mapping complex diseases and traits. Here we introduce an imputation reference panel, consisting of 365 diverse, whole-genome sequenced dogs and wolves, which increases the number of markers that can be queried in genome-wide association studies approximately 130-fold. Using previously genotyped dogs, we show the utility of this reference panel in identifying novel associations and fine-mapping for canine body size and blood phenotypes, even when causal loci are not in strong linkage disequilibrium with any single array marker. This reference panel resource will improve future genome-wide association studies for canine complex diseases and other phenotypes. Author SummaryComplex traits are controlled by more than one gene and as such are difficult to map. For complex trait mapping in the domestic dog, researchers use the current array of 173,000 variants, with only minimal success. Here, we use a method called imputation to increase the number of variants - from 173,000 to 24 million - that can be queried in canine association studies. We use sequence data from the whole genomes of 365 dogs and wolves to accurately predict variants, in a separate cohort of dogs, that are not present on the array. Using dog body size, we show that the increase in variants results in an increase in mapping power, through the identification of new associations and the narrowing of regions of interest. This imputation panel is particularly important because of its usefulness in improving complex trait mapping in the dog, which has significant implications for discovery of variants in humans with similar diseases.

genomics↗