Deciphering local adaptation of native Indian cattle (Bos indicus) breeds using landscape genomics and in-silico prediction of deleterious SNP effects on protein structure and function

India has 50 registered breeds of native cattle (Bos indicus) which are locally adapted to diverse environmental conditions. This study aimed to investigate the genomic basis of adaptation of native Indian cattle and to predict the impact of key SNPs on the amino acid changes that affect protein function. The Illumina 777 K BovineHD BeadChip was used to genotype 178 native cattle belonging to contrasting landscapes and agro-climatic conditions. The genotype-environment association was investigated with R. SamBada, using 5,74,382 QC passed SNPs and 11 predictor variables (10 multi-collinearity controlled environmental variables and 1 variable as “score of PCA” on ancestry coefficients of individuals). In total, 1,12,780 models were selected as significant (q < 0.05) based on G score. The pathway ontology of the annotated genes revealed many important pathways and genes having a direct and indirect role in cold and hot adaptation. Only ten SNP variants had a SIFT score of < 0.05 (deleterious), and only two of them, each lying in the genes CRYBA1 and USP18, were predicted to be deleterious with high confidence. RaptorX predicted the tertiary structures of proteins encoded by wild and mutant variants of these genes. The quality of the models was determined using Ramachandran plots and RaptorX parameters, indicating that they are accurate. RaptorX and I-Mutant 2.0 softwares revealed significant differences among wild and mutant proteins. Adaptive alleles identified in the present investigation might be responsible for the local adaptation of these cattle breeds.