Bos indicus cattle breeds are genetically distinct from Bos taurus breeds. We examined the performance of three SNP arrays, the Illumina BovineHD BeadChip (777k; Illumina Inc.), the Illumina BovineSNP50 BeadChip (50k) and the GeneSeek 70k Indicus chip (75Ki; GeneSeek) in four B. indicus breeds (Gir, Kankrej, Sahiwal and Red Sindhi) and their B. taurus crosses, along with two B. taurus breeds, Holstein and Jersey. More SNPs on both Illumina SNP chips were monomorphic in B. indicus breeds (average 20.3%-29.3% on the 777k chip, 35.5%-45.5% on the 50k chip) than in Holstein (19.7% on the 777k chip, 17.1% on the 50k chip). The proportion of monomorphic SNPs on the 75Ki chip was much lower, 4% (2.8%-7%) in B. indicus breeds, while it was 33.5% in Holstein. With on average 164,357 heterozygous loci in B. indicus breeds, the 777k SNP chip has sufficient heterozygous loci to design a chip customized for B. indicus breeds. Principal component analysis clearly differentiated B. indicus from B. taurus breeds. Differentiation among B. indicus breeds was only achieved by plotting the third and fifth principal components using 777k genotype data. Admixture analysis showed that many B. indicus animals, previously believed to be of pure origin, are in fact had mixed ancestry. The extent of linkage disequilibrium showed comparatively higher effective population sizes in four B. indicus breeds compared to two B. taurus breeds. The results of admixture analyses show that it is important to assess the genomic composition of a bull before using it in a breeding programme.

This study reports the first haplotype phased reference quality genome assembly of 'Murrah' an Indian breed of river buffalo. A mother-father-progeny trio was used for sequencing so that the individual haplotypes could be assembled in the progeny. Parental DNA samples were sequenced on the Illumina platform to generate a total of 274 Gb paired-end data. The progeny DNA sample was sequenced using PacBio long reads and 10x Genomics linked reads at 166x coverage along with 802Gb of optical mapping data. Trio binning based FALCON assembly of each haplotype was scaffolded with 10x Genomics reads and superscaffolded with BioNano Maps to build reference quality assembly of sire and dam haplotypes of 2.63Gb and 2.64Gb with just 59 and 64 scaffolds and N50 of 81.98Mb and 83.23Mb, respectively. BUSCO single copy core gene set coverage was > 91.25%, and gVolante-CEGMA completeness was >96.14% for both haplotypes. Finally, RaGOO was used to order and build the chromosomal level assembly with 25 scaffolds and N50 of 117.48 Mb (sire haplotype) and 118.51 Mb (dam haplotype). The improved haplotype phased genome assembly of river buffalo may provide valuable resources to discover molecular mechanisms related to milk production and reproduction traits.

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13The water buffalo (Bubalus bubalis) has shown enormous milk production 14 potential in many Asian countries. India is considered as the home tract of some of the best 15 buffalo breeds. However, genetic structure of the Indian river buffalo is poorly understood. 16Hence, for selection and breeding strategies, there is a need to characterize the populations 17 and understand the genetic structure of various buffalo breeds. All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/395681 doi: bioRxiv preprint first posted online Aug. 19, 2018; 2 Pandharpuri and Jaffarabadi but not others. So, there is a need to develop SNP chip based 36 on SNP markers identified by sequence information of local breeds. 37 Author Summary 38Indian buffaloes, through 13 recognised breeds, contribute about 49% in 39 total milk production and play a vital role in enhancing the economic condition of Indian 40 farmers. High density genotyping these breeds will allow us to study differences at the 41 molecular level. Evolutionary relationship and phenotypes relations with genotype could 42 be tested with high density genotyping. Breed structure analysis helps to take effective 43 breeding policy decision. In the present study, we have used the high-throughput 44 microarray based genotyping technology for SNP markers. These markers were used for 45 breed differentiation using various genetic parameters. Population structure reflected the 46 proportion of breed admixture among studied breeds. We have also tried to dig the markers 47 associated with traits based LD calculation. However, these SNPs couldn't explain obvious 48 variation up to the expected level, hence, there is need to develop an indigenous SNP chip 49 based on Indian buffalo populations. 50All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

The objective of this study was to investigate the effect of composition and size of the reference population in imputation efficiency of INDUSCHIP v2 in Indian HF crossbred cattle. Data set consisted of a total of 869 cattle from 14 Indicine breeds, 2 crossbreds (HF and Jersey crossbreds) and 2 exotic breeds (HF, Jersey) genotyped with Illumina BovineHD (Illumina, San Diego, CA) panel. Post QC, 846 animals and 449955 SNPs remained for imputation study. 3 test groups each with randomly selected 25 HFCB animals with subset genotype of INDUSCHIP v2 were created, whereas with HD genotyping data of remaining animals, 3 different categories of reference groups were created namely reference 1 (HF, Jersey, all 14 Indicine breeds, HF and Jersey crossbreds), reference 2 (HF, HF crossbred, Sahiwal, Gir and Kankrej) and reference 3 (pure HF, Sahiwal, Gir and Kankrej). Imputation efficiency of INDUSCHIP v2 was expressed in terms of concordance rate and Dosage R2 (DR2). Reference groups 1 and 2 were found to be better than Reference group 3. Further, the size of the reference population had an impact on imputation efficiency. The concordance rate and DR2 decreased with decline about population size. However, a reference population with 280 animals was found to be sufficient to obtain a concordance rate of around 95% or more and DR2 around 0.93. More number of HF, HF crossbred, Sahiwal, Gir and Kankrej animals need to be HD genotyped and incorporated in the reference population to improve the imputation efficiency of INDUSCHIP v2.

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Information from a reference population of animals with accurate breeding values is used to predict the genetic merit of a test population of animals for which such accurate phenotypic information is not available. For crosses, these procedures may be used to predict the proportion of genes of one breed in crossbred cattle when sets of genotypes from purebred animals are available as a reference. The genomic breed composition in 6326 HF crossbred animals (as a test population) performing in Gujarat was determined from SNPs (single nucleotide polymorphism) genotyped by INDUSCHIP array using ADMIXTURE software. The genotypes of 651 purebred indigenous and 120 exotic animals were used as reference genotype for determination of genomic breed composition. Unsupervised clustering analysis using ADMIXTURE software was carried out to infer ancestry ratios for 250 purebred animals using 14718 pruned INDUSCHIP SNPs. It showed that all the B. indicus animals were assigned to their respective breeds. A supervised clustering using 14718 INDUSCHIP variants was performed to infer breed proportions in 6326 crossbred animals with keeping K value as 9. As several indigenous breeds show evidence of admixture, the screening and selection for admixture in candidate bulls for breed purity can improve breeding programs. The average proportion of exotic inheritance was 55% in crossbred population. Hence, SNP genotyping gives opportunity to determine the exact breed proportions in crossbred animals and will be useful in regulation of exotic inheritance in the crossbred population for the optimum productivity of the animals reared by farmers.