Computational molecular analysis of deleterious mutations in serum amyloid A3 gene in goats and cattle

Abstract

Serum amyloid A3 (SAA3) protein found within caprine and bovine mammary epithelial cells is said to be important in disease conditions and tissue remodeling. The present investigation aimed at identifying deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in SAA3 gene of goats and cattle using an in silico assay. Amino acid sequence data of the protein of goats and SNPs of cattle were retrieved from the National Centre for Biotechnology Information (NCBI) database. Bioinformatics prediction tools used for the detection of deleterious nsSNPs were PROVEAN, SIFT, PolyPhe-2 and PANTHER. A total of eleven nsSNPs were obtained from the aligned sequences of goats, out of which two variants (R123G and G126D) were predicted to be deleterious by three out of the four algorithms. However, in cattle, four out of the eleven nsSNPs were found to be harmful to the transcribed protein. The two mutants in goats and R114Q in cattle were also found to decrease protein stability. Further confirmatory analysis however, revealed that variant R123G was highly deleterious as there were marked differences between it and the native protein in terms of total free energy, stabilizing residues, ordered and disordered regions of protein and secondary structure prediction. Similarly, Cmutant (a combination of R123G and G126D mutations) in goats and Dmutant (a combination of S77R, Q84K, S103W and R114Q mutations) in cattle also appeared to distort SAA3 protein structural landscape and function. The present deleterious nsSNPs when validated using wet lab experimental protocols could be important biological markers for disease detection and therapy in goats and cattle.

Keywords: protein, variant, prediction, marker, ruminants