Genetics of body fat mass and related traits in a pig population selected for leanness

Abstract

Obesity is characterized as the excessive accumulation of body fat and has a complex genetic foundation in humans including monogenic high-risk mutations and polygenic contributions. Domestic pigs represent a valuable model on an obesity-promoting high-caloric diet while constantly evaluated for body characteristics. As such, we investigated the genetics of obesity-related traits, comprising subcutaneous fat thickness, lean mass percentage, and growth rate, in a pig population. We conducted genome-wide association analyses using an integrative approach of single-marker regression models and multi-marker Bayesian analyses. Thus, we identified 30 genomic regions distributed over 14 different chromosomes contributing to the variation in obesity-related traits. In these regions, we validated the association of four candidate genes that are functionally connected to the regulation of appetite, processes of adipogenesis, and extracellular matrix formation. Our findings revealed fundamental genetic factors which deserves closer attention regarding their roles in the etiology of obesity.

Genomics of Heat Tolerance in Reproductive Performance Investigated in Four Independent Maternal Lines of Pigs

“…Genes associated with body characteristics have also been reported. This includes PLOD1 and NRXN3 , which have been associated with traits such as diaphragm weight, carcass length, spinal curvature and belly weight (Lindholm-Perry et al, 2010 ; Li et al, 2011 ; Sato et al, 2016 ) and various other candidate genes (e.g., AASS, AP3D1, CPT1A, DOCK1, FASN, LRRK2, PDE1C, PPA2, PSMD1, SCUBE1, SLC27A6, SNAI2, TFAP2B, TMPRSS4, UBAP2, WDR47 ) previously linked to carcass fatness, fatty acid biosynthesis, average daily gain, and body weight in various pig breeds, including LW and LR (Edwards et al, 2008 ; Li et al, 2011 ; Fontanesi et al, 2012 , 2014 ; Do et al, 2013 ; Fowler et al, 2013 ; Nonneman et al, 2013 ; Choi et al, 2016 ; Sato et al, 2016 ; Reyer et al, 2017 ; Lee et al, 2019 ; Zappaterra et al, 2019 ). Some candidate genes, such as CADPS2 , were also associated with feeding behavior, e.g., number of daily visits to the feeder in Duroc pigs (Do et al, 2013 ).…”

A novel automated system to acquire biometric and morphological measurements and predict body weight of pigs via 3D computer vision1

“…In fact, several factors can influence fat deposition, such as nutrition and genetics. For example, Reyer et al (2017) studied the genetics of body fat mass of pigs from the same breeding line and observed that animals took from 124 to 167 d to reach 110 kg of BW, with a lean mass ranging from 56% to 66%, and subcutaneous fat thickness from 4.5 to 14 mm. These differences in body composition may imply in differences in shape and biometric measures for animals of the same weight class, which will increase the error in predicting BW with the current methods.…”

Genome-wide association studies for 30 haematological and blood clinical-biochemical traits in Large White pigs reveal genomic regions affecting intermediate phenotypes

“…The genomic windows explaining more than the 0.043% of genetic variance were considered non-random associations. However, a more stringent and reliable threshold, ranging from 0.2 to 1.00 (which means from ~5X to ~25X the expected variance), is generally applied to consider as QTLs the identified regions, with a threshold value of %Var = 0.5 commonly adopted 28,47,51–55 . Here, a medium moderate threshold, equal to 0.7 (~17X the expected variance), was used: (i) to declare the presence of QTLs and (ii) to confirm those identified via the single-marker single-trait approach.…”