Genome-wide association study and genomic heritabilities for blood protein levels in Lori-Bakhtiari sheep

Abstract

Serum protein levels are related to physiological and pathological status of animals and could be affected by both genetic and environmental factors. This study aimed to evaluate genetic variation of serum protein profile in sheep. Blood samples were randomly collected from 96 Lori-Bakhtiari ewes, a heavy meat-type breed. Total protein, albumin, globulin, α1, α2, β and γ globulins and IgG levels were measured in blood serum. The samples were genotyped using the Illumina OvineSNP50 BeadChip. The studied traits adjusted for age, birth type, birth season and estimate of breeding value for body weight were considered as pseudo-phenotypes in genome-wide association analysis. In the GWAS model, the first five principal components were fitted as covariates to correct the biases due to possible population stratification. The Plink, R and GCTA software were used for genome-wide association analysis, construction of Q-Q and Manhattan plots and estimation of genetic variances, respectively. Noticeable genomic heritabilities ± SE were estimated for total and γ globulins (0.868 ± 0.262 and 0.831 ± 0.364, respectively), but other protein fractions had zero or close to zero estimates. Based on the Bonferroni adjusted p values, four QTLs located on 181.7 Mbp of OAR3, 107.7 Mbp of OAR4, 86.3 Mbp of OAR7 and 83.0 Mbp of OAR8 were significantly associated with α1, β, β and γ globulins, respectively. The results showed that the PKP2, IGF2R, SLC22A1 and SLC22A2 genes could be considered as candidate genes for blood serum proteins. The present study showed significant genetic variations of some blood protein fractions.

Unravelling the Genetic Architecture of Serum Biochemical Indicators in Sheep

“…To the best of our knowledge and according to animal QTL database, no published study has systematically demonstrated the genetic parameters among some or all the 10 serum biochemical indicators and genomic loci using a GWAS of SNPs in lambs [53]. Additionally, only one study was observed to have focused on the genetic basis of protein levels in sheep [12]. The aim of the current study was to identify the underlying genetic architecture for blood serum indicators in lambs.…”

“…Animal welfare and health status have paramount importance for all livestock enterprises since any deviation from good health might have adverse effects on the profitability, productivity, and sustainability of production systems [12]. Mounting evidence suggest that serum biochemical parameters have a wide range of associations with disease resistance, resilience, immune functions, productivity, and feed efficiency in various livestock species [7,[13][14][15][16][17].…”

“…To date, various genomic loci were associated with serum biochemical parameters in human as well as in livestock such as pigs, cattle and ducks [4,5,7,10,33,34]. However, only one study has been identified that specifically investigates the genomic heritabilities and QTL associated exclusively with serum protein levels in sheep [12].…”

Estimates of genomic heritability and genome-wide association studies for blood parameters in Akkaraman sheep

“…The acceleration of technological advancements in the field of genomics, followed by the assembly of reference genome sequences of different species, has been greatest the contribution to the identification of genes associated with complex traits 20 – 22 . Furthermore, the genetic background of economically important livestock traits such as disease resistance, milk yield, meat yield, and hematological parameters have been revealed by associating phenotype and genotype data with a linear mixed model based analysis, which is the commonly used approach in GWAS 7 , 15 , 17 , 23 , 24 . In this study, genomic heritability estimates for 19 blood parameters were obtained in Akkaraman sheep, which is a widespread indigenous sheep breed in Türkiye.…”

Estimates of Genomic Heritability and the Marker-Derived Gene for Re(Production) Traits in Xinggao Sheep

“…Association maps and the significant SNPs are visualized with a threshold line in a Manhattan plot. The Manhattan plot and Q-Q plot were plotted using R v. 4.1.2 [ 32 ]. The calculation formula of inflation factor (λ) [ 33 ] is: (a) p _value = gwas$ p , (b) z = qnorm( p _value/2), (c) λ= round(median(z 2 , na.rm = TRUE)/0.454, 3).…”