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Genome-wide association study on legendre random regression coefficients for the growth and feed intake trajectory on Duroc Boars

BACKGROUND: 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 s...

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Detalles Bibliográficos
Autores principales: Howard, Jeremy T., Jiao, Shihui, Tiezzi, Francesco, Huang, Yijian, Gray, Kent A., Maltecca, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4449572/
https://www.ncbi.nlm.nih.gov/pubmed/26024912
http://dx.doi.org/10.1186/s12863-015-0218-8
Descripción
Sumario:BACKGROUND: 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. RESULTS: 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 (DFI(Adj): n = 855; DBW(Avg): 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 DBW(Avg) and DFI(Adj), respectively. Genetic correlations across age classes were large and positive for both DBW(Avg) and DFI(Adj), 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 DBW(Avg) and DFI(Adj), respectively. The WGEBV variance explained by significant regions for the trajectory was 1.54 and 1.95 % for DBW(Avg) and DFI(Adj). Both traits identified candidate genes with functions related to metabolite and energy homeostasis, glucose and insulin signaling and behavior. CONCLUSIONS: We have identified regions of the genome that have an impact on the intercept, linear and quadratic terms for DBW(Avg) and DFI(Adj). These results provide preliminary evidence that individual growth and feed intake trajectories are impacted by different regions of the genome at different times. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12863-015-0218-8) contains supplementary material, which is available to authorized users.