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Unravelling the Genetic Architecture of Serum Biochemical Indicators in Sheep.

Mehmet KizilaslanYunus ArzikSedat BehremEsra YavuzStephen N WhiteMehmet Ulas Cinar
Published in: Genes (2024)
Serum biochemical indicators serve as vital proxies that reflect the physiological state and functions of different organs. The genetic parameters and molecular mechanisms underlying serum biochemical indicators of sheep ( Ovis aries ) have not been well understood. Therefore, the aim of the present study was to identify the genetic architecture and genomic loci underlying ten serum biochemical indicators in sheep, including alanine transaminase, aspartate transferase, lactate dehydrogenase, cholesterol, glucose, phosphorus, calcium, creatinine, urea and total protein levels. We implemented genetic parameter estimations and GWASs for each trait in 422 Akkaraman lambs. Overall, low to moderate heritability estimates were found in the range of 0.14-0.55. Additionally, low to high genetic correlations were observed among traits. In total, 23 SNP loci were associated with serum biochemical indicators leading to 19 genes. These were SPTA1 , MGST2 , CACUL1 , IGFBP7 , PARD3 , PHB1 , SLC15A5 , TRIM35 , RGS6 , NUP93 , CNTNAP2 , SLC7A11 , B3GALT5 , DPP10 , HST2ST1 , NRP1 , LRP1B , MAP3K9 and ENSOARG00020040484.1 , as well as LOC101103187 , LOC101117162 , LOC105611309 and LOC101118029. To our knowledge, these data provide the first associations between SPTA1 and serum cholesterol and between ENSOARG00020040484.1 and serum glucose. The current findings provide a comprehensive inventory of the relationships between serum biochemical parameters, genetic variants and disease-relevant characteristics. This information may facilitate the identification of therapeutic targets and fluid biomarkers and establish a strong framework for comprehending the pathobiology of complex diseases as well as providing targets for sheep genetic improvement programs.
Keyphrases
  • genome wide
  • copy number
  • dna methylation
  • healthcare
  • blood pressure
  • gene expression
  • risk assessment
  • high intensity