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      ddRAD sequencing based genotyping of six indigenous dairy cattle breeds of India to infer existing genetic diversity and population structure

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          Abstract

          The present investigation aimed to identify genome wide SNPs and to carry out diversity and population structure study using ddRAD-seq based genotyping of 58 individuals of six indigenous milch cattle breeds ( Bos indicus) such as Sahiwal, Gir, Rathi, Tharparkar, Red Sindhi and Kankrej of India. A high percentage of reads (94.53%) were mapped to the Bos taurus (ARS-UCD1.2) reference genome assembly. Following filtration criteria, a total of 84,027 high quality SNPs were identified across the genome of 6 cattle breeds with the highest number of SNPs observed in Gir (34,743), followed by Red Sindhi (13,092), Kankrej (12,812), Sahiwal (8956), Tharparkar (7356) and Rathi (7068). Most of these SNPs were distributed in the intronic regions (53.87%) followed by intergenic regions (34.94%) while only 1.23% were located in the exonic regions. Together with analysis of nucleotide diversity (π = 0.373), Tajima’s D (D value ranging from − 0.295 to 0.214), observed heterozygosity (H O ranging from 0.464 to 0.551), inbreeding coefficient (F IS ranging from − 0.253 to 0.0513) suggested for the presence of sufficient within breed diversity in the 6 major milch breeds of India. The phylogenetic based structuring, principal component and admixture analysis revealed genetic distinctness as well as purity of almost all of the 6 cattle breeds. Overall, our strategy has successfully identified thousands of high-quality genome wide SNPs that will further enrich the Bos indicus representation basic information about genetic diversity and structure of 6 major Indian milch cattle breeds which should have implications for better management and conservation of valuable indicine cattle diversity.

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Cutadapt removes adapter sequences from high-throughput sequencing reads

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              PLINK: a tool set for whole-genome association and population-based linkage analyses.

              Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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                Author and article information

                Contributors
                mmukesh_26@hotmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                9 June 2023
                9 June 2023
                2023
                : 13
                : 9379
                Affiliations
                [1 ]GRID grid.506029.8, Animal Biotechnology Division, , ICAR-National Bureau of Animal Genetic Resources, ; Karnal, Haryana India
                [2 ]GRID grid.419332.e, ISNI 0000 0001 2114 9718, Animal Biotechnology Center, , ICAR-National Dairy Research Institute, ; Karnal, Haryana India
                [3 ]ICAR-NBAGR, Karnal, Haryana 132001 India
                Article
                32418
                10.1038/s41598-023-32418-6
                10256769
                37296129
                0ed963a9-cabb-4d62-86b9-93c39bea6648
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 2 September 2022
                : 27 March 2023
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                © Springer Nature Limited 2023

                Uncategorized
                biotechnology,genomics,phylogenomics
                Uncategorized
                biotechnology, genomics, phylogenomics

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