Unraveling genetic admixture in the Indian crossbred cattle by different approaches using Bovine 50K BeadChip.

With the upsurge of crossbreeding in India, the admixture levels are highly unpredictable in the composite breeds. Hence, in the present study, 72 Vrindavani animals were assessed for the level of admixture from their known ancestors that are Holstein-Friesian, Jersey, Brown Swiss, and Hariana, through three different software, namely, STRUCTURE, ADMIXTURE, and frappe. The genotype data for ancestral breeds were obtained from a public repository, i.e., DRYAD. The Frieswal crossbred cattle along with ancestral breeds like Holstein-Friesian and Sahiwal were also investigated for the level of admixture with the help of the above-mentioned software. The Frieswal population was found to comprise an average of 62.49, 61.12, and 61.21% of Holstein-Friesian and 37.50, 38.88, and 38.80% of Sahiwal estimated through STRUCTURE, ADMIXTURE, and frappe, respectively. The Vrindavani population was found to consist of on average 39.5, 42.4, and 42.3% of Holstein-Friesian; 22.9, 22.3, and 21.7% of Jersey; 10.7, 10.6, and 11.9% of Brown Swiss; and 26.9, 24.7, and 24.1% of Hariana blood estimated through STRUCTURE, ADMIXTURE, and frappe, respectively. A greater degree of variation was noted in the results from STRUCTURE vs. frappe, STRUCTURE vs. ADMIXTURE than in ADMIXTURE vs. frappe. From this study, we conclude that the admixture analysis based on a single software should be validated through the use of many different approaches for better prediction of admixture levels.

Revelation of genomic breed composition in a crossbred cattle of India with the help of Bovine50K BeadChip.

The aim of the present study was to assess the population structure and admixture levels in the Vrindavani composite population in India by using Bovine50KSNP BeadChip data. Genotypic data were generated for randomly selected animals (n = 72) of Vrindavani population and the data for parental breeds i.e., Hariana (n = 10), Holstein-Friesian (n = 63), Jersey (n = 28) and Brown Swiss (n = 22) were retrieved from a public repository. The indices of population structure were calculated using PLINK software and R-program. The merged dataset was analysed for assessing admixture levels and population stratification using three different approaches i.e., principal component analysis (PCA), multi-dimensional scaling (MDS) approach and the model-based approach in STRUCTURE software. The average minor allele frequency (MAF) value for Vrindavani population was estimated to be 0.235. Vrindavani population was found to possess an average ancestry of 39.5, 22.9, 26.9, and 10.7% inheritance levels from Holstein Friesian, Jersey, Hariana and Brown Swiss cattle breeds, respectively.

Population structure and admixture analysis in Frieswal crossbred cattle of India - a pilot study.

The present study was aimed to assess parameters related to genetic diversity, population structure and admixture in the Frieswal crossbred cattle of India. A total of three datasets were analyzed during this study. Dataset A (n = 80) consisted of data on two purebred populations, i.e., Shorthorn (n = 35) and Brahman (n = 25) and one crossbred strain Santa Gertrudis (n = 20). The dataset B (n = 71) consisted of data on three populations that included Holstein-Friesian (n = 30), Sahiwal (n = 27) and Frieswal (n = 14) cattle. The dataset C included data on all the six breeds under study. Dataset C was used to assess the indices of population structure and genetic diversity of different breeds prior to and after LD pruning. For Frieswal cattle strain, the proportion of polymorphic SNPs and MAF levels was 84.54% and 0.24, respectively. Frieswal strain maintained appreciable genetic diversity with observed heterozygosity measure of 0.414. PCA plots for three datasets depicted effective stratification of different breeds in the respective datasets. The genomic clustering levels of Sahiwal and Holstein-Friesian were found to be 98.45 and 99.89%, respectively, while the admixture of Frieswal was estimated to be about 61.5 and 38.5% from Holstein-Friesian and Sahiwal breeds, respectively.

Ancestry informative markers derived from discriminant analysis of principal components provide important insights into the composition of crossbred cattle.

The cost of SNP genotyping to screen different breeds and to estimate the exact proportion of ancestry level is quite high, which can be compensated through deriving a small panel of ancestry informative markers (AIMs). Hence, we carried out the present study to provide an insight into ancestry level inferred from a panel of informative markers in the crossbred Vrindavani population developed at ICAR-IVRI, India. We have performed a new method i.e., discriminant analysis of principal components (DAPC) for the first time on the dataset of Vrindavani cattle. To confirm our method, we had performed DAPC on two other well-known crossbred cattle, i.e., Frieswal and Beefmaster. Three sets of panels (500, 1000 and 2000 markers) were tested for clustering of individuals. Among all the panels, we found the panel (1000 markers) with DAPC based contribution method was of the smallest size and comparatively of the highest accuracy.