Genome-wide association study on legendre random regression coefficients for the growth and feed intake trajectory on Duroc Boars
Open Access
- 30 May 2015
- journal article
- research article
- Published by Springer Nature in BMC Genomic Data
- Vol. 16 (1) , 1-11
Abstract
Feed intake and growth are economically important traits in swine production. Previous genome wide association studies (GWAS) have utilized average daily gain or daily feed intake to identify regions that impact growth and feed intake across time. The use of longitudinal models in GWAS studies, such as random regression, allows for SNPs having a heterogeneous effect across the trajectory to be characterized. The objective of this study is therefore to conduct a single step GWAS (ssGWAS) on the animal polynomial coefficients for feed intake and growth. Corrected daily feed intake (DFI Adj ) and average daily weight measurements (DBW Avg ) on 8981 (n = 525,240 observations) and 5643 (n = 283,607 observations) animals were utilized in a random regression model using Legendre polynomials (order = 2) and a relationship matrix that included genotyped and un-genotyped animals. A ssGWAS was conducted on the animal polynomials coefficients (intercept, linear and quadratic) for animals with genotypes (DFIAdj: n = 855; DBWAvg: n = 590). Regions were characterized based on the variance of 10-SNP sliding windows GEBV (WGEBV). A bootstrap analysis (n =1000) was conducted to declare significance. Heritability estimates for the traits trajectory ranged from 0.34-0.52 to 0.07-0.23 for DBWAvg and DFIAdj, respectively. Genetic correlations across age classes were large and positive for both DBWAvg and DFIAdj, albeit age classes at the beginning had a small to moderate genetic correlation with age classes towards the end of the trajectory for both traits. The WGEBV variance explained by significant regions (P < 0.001) for each polynomial coefficient ranged from 0.2-0.9 to 0.3-1.01 % for DBWAvg and DFIAdj, respectively. The WGEBV variance explained by significant regions for the trajectory was 1.54 and 1.95 % for DBWAvg and DFIAdj. Both traits identified candidate genes with functions related to metabolite and energy homeostasis, glucose and insulin signaling and behavior. We have identified regions of the genome that have an impact on the intercept, linear and quadratic terms for DBWAvg and DFIAdj. These results provide preliminary evidence that individual growth and feed intake trajectories are impacted by different regions of the genome at different times.Keywords
Funding Information
- USDA-Food and Agricultural Sciences National Needs Graduate Fellowship (ᅟ)
- Smithfield Premium Genetics (ᅟ)
This publication has 52 references indexed in Scilit:
- Genome wide analysis reveals single nucleotide polymorphisms associated with fatness and putative novel copy number variants in three pig breedsBMC Genomics, 2013
- Ensembl 2013Nucleic Acids Research, 2012
- Genome-wide association mapping including phenotypes from relatives without genotypesGenetics Research, 2012
- Abnormal anthropometric measurements and growth pattern in male adolescent idiopathic scoliosisEuropean Spine Journal, 2011
- Genomic breeding value prediction and QTL mapping of QTLMAS2010 data using Bayesian MethodsBMC Proceedings, 2011
- Deficiency of liver sinusoidal scavenger receptors stabilin-1 and -2 in mice causes glomerulofibrotic nephropathy via impaired hepatic clearance of noxious blood factorsJournal of Clinical Investigation, 2011
- Role of Insulin-Like Growth Factor-Binding Protein 5 (IGFBP5) in Organismal and Pancreatic β-Cell GrowthMolecular Endocrinology, 2010
- A Unified Approach to Genotype Imputation and Haplotype-Phase Inference for Large Data Sets of Trios and Unrelated IndividualsThe American Journal of Human Genetics, 2009
- Detection and modelling of time-dependent QTL in animal populationsGenetics Selection Evolution, 2008
- Tripeptidyl peptidase II promotes fat formation in a conserved fashionEMBO Reports, 2007