Uncovering structural variants associated with body weight and obesity risk in labrador retrievers: a genome-wide study

Abstract

Although obesity in the domestic dog (Canis lupus familiaris) is known to decrease well-being and shorten lifespan, the genetic risk variants associated with canine obesity remain largely unknown. In our study, which focused on the obesity-prone Labrador Retriever breed, we conducted a genome-wide analysis to identify structural variants linked to body weight and obesity. Obesity status was based on a 5-point body condition score (BCS) and the obese dog group included all dogs with a BCS of 5, along with dogs with the highest body weight within the BCS 4 group. Data from whole-gene sequencing of fifty dogs, including 28 obese dogs, were bioinformatically analyzed to identify potential structural variants that varied in frequency between obese and healthy dogs. The seven most promising variants were further analyzed by droplet digital PCR in a group of 110 dogs, including 63 obese. Our statistical evidence suggests that common structural mutations in or near six genes, specifically ALPL, KCTD8, SGSM1, SLC12A6, RYR3, and VPS26C, may contribute to the variability observed in body weight and body condition scores among Labrador Retriever dogs. These findings emphasize the need for additional research to validate the associations and explore the specific functions of these genes in relation to canine obesity.

Keywords: ALPL; KCTD8; RYR3; SGSM1; SLC12A6; VPS26C; labrador retriever; obesity.

FIGURE 1

Localization of six ddPCR-amplified fragments exhibiting overlap with structural variants that hold potential implications for body weight and obesity susceptibility in Labrador.

FIGURE 2

Composite boxplot illustrating the relationship between body weight and copy number across six distinct genes. Each boxplot within the composition showcases the distribution of body weight values associated with varying copy number states for a specific gene. The median body weight within each gene’s copy number category is indicated by the central line within the box, with the top and bottom edges of the box representing the third and first quartiles, respectively. Whiskers extend to 1.5 times the interquartile range (IQR) from the box boundaries, encompassing the majority of data points. Outliers, depicted as individual data points, are situated beyond the whiskers. The Y-axis represents body weight (grams), while the X-axis designates the six different genes and their respective copy number states. The Y-axis represents body weight (in kilograms), corrected by age (as a covariate), sex, neuter status and presence of the POMC deletion (presence of 14-bp Del variant). Owing to the limited size of certain groups, they are omitted from the plot for clarity. p-values (p) refer to the effects of polymorphisms estimated in linear regression model.

FIGURE 3

Distribution of genotypes (here identified by the number of copies of a DNA fragment in the genome) in groups of obese and healthy dogs. p-values (p) refer to the effect of copy number on the risk of obesity as estimated in logistic regression model.

FIGURE 4

Logarithmic scale illustration of odds ratios (OR) with 95% confidence intervals (CI) for six distinct genes. The X-axis denotes the logarithm of odds ratios, where a value of 0 signifies no effect. Values greater than zero mean that the risk of obesity increases with the number of copies of the DNA fragment. Each gene’s odds ratio is represented by a point estimate on the log scale, accompanied by a 95% CI illustrated as an error bar. The inclusion of confidence intervals offers insights into the precision and significance of the odds ratio estimates.