High-throughput genotype based population structure analysis of selected buffalo breeds

Abstract

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 No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint .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 No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

Population demographic history and population structure for Pakistani Nili-Ravi breeding bulls based on SNP genotyping to identify genomic regions associated with male effects for milk yield and body weight

“…We observed the maximum LD score for chromosome 10 and largest LD block for chromosome Y. Similar results observed the LD decline at approximately 50 kb, with an average r 2 ≥ 0.2 in Chinese crossbred buffalo groups [Jianghan × Nili-Ravi × Mediterranean and Nili-Ravi × Murrah × local (Fuzhong or Xilin)] [ 67 ] and an r 2 value from 0.412 to 0.139 in Indian Nili-Ravi buffalo [ 68 ], which is much lower than that found in our study. However, comparing our findings directly with previous reports is difficult because of differences in the scale of sampling, given that the level of LD decreases with increasing sample size [ 69 ].…”

Performance of Illumina® BovineHD BeadChip in genotyping Indian riverine buffalo breeds

“…The results indicated that the selected SNPs may not be informative enough to reveal differences in Indian buffalo breeds. In a similar work, Thakor et al (2021) could differentiate phenotypically distinct breeds like Surti, Pandharpuri, and Jaffarabadi using SNPs in Axiom™ Buffalo Genotyping Array (90 K) but not others like Banni, Mehsana, Murrah and Niliravi. In a related development, Sudhakar et al (2021) studied false positive results of Deficiency of Uridine Monophosphate Synthase (DUMPS) in buffaloes which were tested using polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) tools developed for cattle and reported that using SNP detection genomic tools developed for a species requires genome sequencing for validation before using in a new species/population.…”