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

Authors :
Dharamshibhai N. Rank
Dhruv Bhatia
A Sudhakar
Prakash B Thakor
Ankit T. Hinsu
Tejas M. Shah
Chaitanya G. Joshi
Nilesh Nayee
Source :
Translational Animal Science
Publication Year :
2021
Publisher :
Oxford University Press, 2021.

Abstract

India is considered as the home tract of some of the best buffalo breeds. However, the genetic structure of the Indian river buffalo is poorly understood. Hence, there is a need to characterize the populations and understand the genetic structure of various buffalo breeds for selection and to design breeding strategies. In this study, we have analyzed genetic variability and population structure of seven buffalo breeds from their respective geographical regions using Axiom Buffalo Genotyping Array. Diversity, as measured by expected heterozygosity, ranged from 0.364 in Surti to 0.384 in Murrah breed, and pair-wise FST values revealed the lowest genetic distance between Murrah and Nili-Ravi (0.0022), while the highest between Surti and Pandharpuri (0.030). Principal component analysis and structure analysis unveiled the differentiation of Surti, Pandharpuri, and Jaffarabadi in first two principal components and at K = 4, respectively, while remaining breeds were grouped together as a separate single cluster and admixed. Murrah and Mehsana showed early linkage disequilibrium (LD) decay, while Surti breed showed late decay. In LD blocks to quantitative trait locis (QTLs) concordance analysis, 4.65% of concordance was observed with 873 LD blocks overlapped with 2,330 QTLs. Overall, total 4,090 markers were identified from all LD blocks for six types of traits. Results of this study indicated that these single-nucleotide polymorphism (SNP) markers could differentiate phenotypically distinct breeds like Surti, Pandharpuri, and Jaffarabadi but not others. So, there is a need to develop SNP chip based on SNP markers identified by sequence information of local breeds.

Details

Language :
English
ISSN :
25732102
Volume :
5
Issue :
2
Database :
OpenAIRE
Journal :
Translational Animal Science
Accession number :
edsair.doi.dedup.....5ba7fe9277a3f9fdbdd6b06c2c661964