Intronic variant in POU1F1 associated with canine pituitary dwarfism

A Nonsynonymous Substitution of Lhx3 Leads to Changes in Body Size in Dogs and Mice

Lhx3 is a LIM-homeodomain transcription factor that affects body size in mammals by regulating the secretion of pituitary hormones. Akita, Shiba Inu, and Mame Shiba Inu dogs are Japanese native dog breeds that have different body sizes. To determine whether Lhx3 plays a role in the differing body sizes of these three dog breeds, we sequenced the Lhx3 gene in the three breeds, which led to the identification of an SNP in codon 280 (S280N) associated with body size. The allele frequency at this SNP differed significantly between the large Akita and the two kinds of smaller Shiba dogs. To validate the function of this SNP on body size, we introduced this change into the Lhx3 gene of mice. Homozygous mutant mice (S279N+/+) were found to have significantly increased body lengths and weights compared to heterozygous mutant (S279N+/-) and wild-type (S279N-/-) mice several weeks after weaning. These results demonstrate that a nonsynonymous substitution in Lhx3 plays an important role in regulating body size in mammals.

Identification of novel genetic risk factors of dilated cardiomyopathy: from canine to human

BACKGROUND

Dilated cardiomyopathy (DCM) is a life-threatening heart disease and a common cause of heart failure due to systolic dysfunction and subsequent left or biventricular dilatation. A significant number of cases have a genetic etiology; however, as a complex disease, the exact genetic risk factors are largely unknown, and many patients remain without a molecular diagnosis.

METHODS

We performed GWAS followed by whole-genome, transcriptome, and immunohistochemical analyses in a spontaneously occurring canine model of DCM. Canine gene discovery was followed up in three human DCM cohorts.

RESULTS

Our results revealed two independent additive loci associated with the typical DCM phenotype comprising left ventricular systolic dysfunction and dilatation. We highlight two novel candidate genes, RNF207 and PRKAA2, known for their involvement in cardiac action potentials, energy homeostasis, and morphology. We further illustrate the distinct genetic etiologies underlying the typical DCM phenotype and ventricular premature contractions. Finally, we followed up on the canine discoveries in human DCM patients and discovered candidate variants in our two novel genes.

CONCLUSIONS

Collectively, our study yields insight into the molecular pathophysiology of DCM and provides a large animal model for preclinical studies.

Bone age assessment from articular surface and epiphysis using deep neural networks

Bone age assessment is of great significance to genetic diagnosis and endocrine diseases. Traditional bone age diagnosis mainly relies on experienced radiologists to examine the regions of interest in hand radiography, but it is time-consuming and may even lead to a vast error between the diagnosis result and the reference. The existing computer-aided methods predict bone age based on general regions of interest but do not explore specific regions of interest in hand radiography. This paper aims to solve such problems by performing bone age prediction on the articular surface and epiphysis from hand radiography using deep convolutional neural networks. The articular surface and epiphysis datasets are established from the Radiological Society of North America (RSNA) pediatric bone age challenge, where the specific feature regions of the articular surface and epiphysis are manually segmented from hand radiography. Five convolutional neural networks, i.e., ResNet50, SENet, DenseNet-121, EfficientNet-b4, and CSPNet, are employed to improve the accuracy and efficiency of bone age diagnosis in clinical applications. Experiments show that the best-performing model can yield a mean absolute error (MAE) of 7.34 months on the proposed articular surface and epiphysis datasets, which is more accurate and fast than the radiologists. The project is available at https://github.com/YameiDeng/BAANet/, and the annotated dataset is also published at https://doi.org/10.5281/zenodo.7947923.

PCYT1A Missense Variant in Vizslas with Disproportionate Dwarfism

Disproportionate dwarfism phenotypes represent a heterogeneous subset of skeletal dysplasias and have been described in many species including humans and dogs. In this study, we investigated Vizsla dogs that were affected by disproportionate dwarfism that we propose to designate as skeletal dysplasia 3 (SD3). The most striking skeletal changes comprised a marked shortening and deformation of the humerus and femur. An extended pedigree with six affected dogs suggested autosomal recessive inheritance. Combined linkage and homozygosity mapping localized a potential genetic defect to a ~4 Mb interval on chromosome 33. We sequenced the genome of an affected dog, and comparison with 926 control genomes revealed a single, private protein-changing variant in the critical interval, PCYT1A:XM_038583131.1:c.673T>C, predicted to cause an exchange of a highly conserved amino acid, XP_038439059.1:p.(Y225H). We observed perfect co-segregation of the genotypes with the phenotype in the studied family. When genotyping additional Vizslas, we encountered a single dog with disproportionate dwarfism that did not carry the mutant PCYT1A allele, which we hypothesize was due to heterogeneity. In the remaining 130 dogs, we observed perfect genotype-phenotype association, and none of the unaffected dogs were homozygous for the mutant PCYT1A allele. PCYT1A loss-of-function variants cause spondylometaphyseal dysplasia with cone-rod dystrophy (SMD-CRD) in humans. The skeletal changes in Vizslas were comparable to human patients. So far, no ocular phenotype has been recognized in dwarf Vizslas. We propose the PCYT1A missense variant as a candidate causative variant for SD3. Our data facilitate genetic testing of Vizslas to prevent the unintentional breeding of further affected puppies.