Weighted single‐step genome‐wide association study and pathway analyses for feed efficiency traits in Nellore cattle

2020 ◽  
Vol 138 (1) ◽  
pp. 23-44 ◽  
Author(s):  
Ludmilla C. Brunes ◽  
Fernando Baldi ◽  
Fernando B. Lopes ◽  
Raysildo B. Lôbo ◽  
Rafael Espigolan ◽  
...  
2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Bingru Zhao ◽  
Hanpeng Luo ◽  
Xixia Huang ◽  
Chen Wei ◽  
Jiang Di ◽  
...  

Abstract Background Genetic improvement of wool and growth traits is a major goal in the sheep industry, but their underlying genetic architecture remains elusive. To improve our understanding of these mechanisms, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale transcriptome data for five wool traits and one growth trait in Merino sheep: mean fibre diameter (MFD), coefficient of variation of the fibre diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW). Results Our dataset comprised 7135 individuals with phenotype data, among which 1217 had high-density (HD) genotype data (n = 372,534). The genotypes of 707 of these animals were imputed from the Illumina Ovine single nucleotide polymorphism (SNP) 54 BeadChip to the HD Array. The heritability of these traits ranged from 0.05 (CVFD) to 0.36 (MFD), and between-trait genetic correlations ranged from − 0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating the GWAS signals with RNA-seq data from 500 samples (representing 87 tissue types from 16 animals), we detected tissues that were relevant to each of the six traits, e.g. liver, muscle and the gastrointestinal (GI) tract were the most relevant tissues for LW, and leukocytes and macrophages were the most relevant cells for CN. For the six traits, 54 quantitative trait loci (QTL) were identified covering 81 candidate genes on 21 ovine autosomes. Multiple candidate genes showed strong tissue-specific expression, e.g. BNC1 (associated with MFD) and CHRNB1 (LW) were specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several of these candidate genes were significantly (FDR < 0.05) associated with similar traits in humans, e.g. BNC1 was significantly associated with MFD in sheep and with hair colour in humans, and CHRNB1 was significantly associated with LW in sheep and with body mass index in humans. Conclusions Our findings provide novel insights into the biological and genetic mechanisms underlying wool and growth traits, and thus will contribute to the genetic improvement and gene mapping of complex traits in sheep.


2014 ◽  
Vol 131 (3) ◽  
pp. 210-216 ◽  
Author(s):  
M.H.A. Santana ◽  
Y.T. Utsunomiya ◽  
H.H.R. Neves ◽  
R.C. Gomes ◽  
J.F. Garcia ◽  
...  

animal ◽  
2019 ◽  
Vol 13 (11) ◽  
pp. 2447-2456 ◽  
Author(s):  
É.F. Silva ◽  
M.S. Lopes ◽  
P.S. Lopes ◽  
E. Gasparino

PLoS ONE ◽  
2015 ◽  
Vol 10 (2) ◽  
pp. e0114919 ◽  
Author(s):  
Francesco Tiezzi ◽  
Kristen L. Parker-Gaddis ◽  
John B. Cole ◽  
John S. Clay ◽  
Christian Maltecca

2019 ◽  
Vol 9 (11) ◽  
pp. 3833-3841 ◽  
Author(s):  
Agustin Barria ◽  
Rodrigo Marín-Nahuelpi ◽  
Pablo Cáceres ◽  
María E. López ◽  
Liane N. Bassini ◽  
...  

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 8-8
Author(s):  
Gabriella R Dodd ◽  
Breno O Fragomeni ◽  
Kent A Gray ◽  
Yijian Huang

Abstract The purpose of this study was to perform a genome-wide association study to determine the genomic regions associated with heat stress tolerance in swine as well as analyze the accuracy of prediction. Phenotypic information on carcass weight was available for 227,043 individuals from commercial farms in North Carolina and Missouri. Individuals were a commercial cross of a Duroc sire and a dam resulting from a Landrace and Large White cross. Genotypic information was available for 8,232 animals with 33,581 SNP. The pedigree file contained 553,448 animals. A 78 on the Temperature Humidity Index (THI) was used as a threshold for heat stress. A two-trait analysis was used with the phenotypes heat stress (trait one) and non-heat stress (trait two). Variance components were calculated via AIREML and breeding values were calculated using single step GBLUP (ssGBLUP). The heritability for trait one and two were calculated at 0.25 and 0.20, respectively, and the genetic correlation was calculated as 0.63. Validation was calculated for 163 genotyped sires with progeny in the last generation. The GEBV of complete data was used as the benchmark, and the accuracy was determined as the correlation between the GEBV of the reduced and complete data for the validation sires. Weighted ssGBLUP did not increase the accuracies, both methods showed a maximum accuracy of 0.32 for trait one and 0.54 for trait two. Manhattan Plots for trait one, trait two, and the difference between the two were created from the results of the two-trait analysis. Windows explaining around 1% of the genetic variance were identified. The only difference between the two traits was a peak at chromosome 14. The genetic correlation suggests different mechanisms for growth under heat stress. The GWAS results show that both traits are highly polygenic, with few genomic regions explaining more than 1% of variance.


Sign in / Sign up

Export Citation Format

Share Document