Literature DB >> 26931356

Skeletal variation in Tennessee Walking Horses maps to the LCORL/NCAPG gene region.

E A Staiger1, M A Al Abri2, K M Pflug3, S E Kalla4, D M Ainsworth4, D Miller5, T Raudsepp6, N B Sutter7, S A Brooks8.   

Abstract

Conformation has long been a driving force in horse selection and breed creation as a predictor for performance. The Tennessee Walking Horse (TWH) ranges in size from 1.5 to 1.7 m and is often used as a trail, show, and pleasure horse. To investigate the contribution of genetics to body conformation in the TWH, we collected DNA samples, body measurements, and gait/training information from 282 individuals. We analyzed the 32 body measures with a principal component analysis. Principal component (PC)1 captured 28.5% of the trait variance, while PC2 comprised just 9.5% and PC3 6.4% of trait variance. All 32 measures correlated positively with PC1, indicating that PC1 describes overall body size. We genotyped 109 horses using the EquineSNP70 bead chip and marker association assessed the data using PC1 scores as a phenotype. Mixed-model linear analysis (EMMAX) revealed a well-documented candidate locus on ECA3 (raw P = 3.86 × 10(-9)) near the LCORL gene. A custom genotyping panel enabled fine-mapping of the PC1 body-size trait to the 3'-end of the LCORL gene (P = 7.09 × 10(-10)). This position differs from other reports suggesting single nucleotide polymorphisms (SNPs) upstream of the LCORL coding sequence regulate expression of the gene and, therefore, body size in horses. Fluorescent in situ hybridization analysis defined the position of a highly homologous 5 kb retrogene copy of LCORL (assigned to unplaced contigs of the EquCab 2.0 assembly) at ECA9 q12-q13. This is the first study to identify putative causative SNPs within the LCORL transcript itself, which are associated with skeletal size variation in horses.
Copyright © 2016 the American Physiological Society.

Entities:  

Keywords:  LCORL indel; Tennessee Walking Horse; genome-wide association study; horse size; retrogene

Mesh:

Year:  2016        PMID: 26931356     DOI: 10.1152/physiolgenomics.00100.2015

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


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