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1.
Gene ; 921: 148541, 2024 Aug 30.
Article in English | MEDLINE | ID: mdl-38723784

ABSTRACT

Camels play a crucial socio-economic role in sustaining the livelihoods of millions in arid and semi-arid regions. They possess remarkable physiological attributes which enable them to thrive in extreme environments, and provide a source of meat, milk and transportation. With their unique traits, camels embody an irreplaceable source of untapped genomic knowledge. This study introduces Axiom-MaruPri, a medium-density SNP chip meticulously designed and validated for both Camelus bactrianus and Camelus dromedarius. Comprising of 182,122 SNP markers, derived from the re-sequenced data of nine Indian dromedary breeds and the double-humped Bactrian camel, this SNP chip offers 34,894 markers that display polymorphism in both species. It achieves an estimated inter-marker distance of 14 Kb, significantly enhancing the coverage of the camel genome. The medium-density chip has been successfully genotyped using 480 camel samples, achieving an impressive 99 % call rate, with 96 % of the 182,122 SNPs being highly reliable for genotyping. Phylogenetic analysis and Discriminant Analysis of Principal Components yield clear distinctions between Bactrian camels and dromedaries. Moreover, the discriminant functions substantially enhance the classification of dromedary camels into different breeds. The clustering of various camel breeds reveals an apparent correlation between geographical and genetic distances. The results affirm the efficacy of this SNP array, demonstrating high genotyping precision and clear differentiation between Bactrian and dromedary camels. With an enhanced genome coverage, accuracy and economic efficiency the Axiom_MaruPri SNP chip is poised to advance genomic breeding research in camels. It holds the potential to serve as an invaluable genetic resource for investigating population structure, genome-wide association studies and implementing genomic selection in domesticated camelid species.


Subject(s)
Camelus , Oligonucleotide Array Sequence Analysis , Polymorphism, Single Nucleotide , Animals , Camelus/genetics , Oligonucleotide Array Sequence Analysis/methods , Phylogeny , Domestication , Breeding/methods , Genotype , Genotyping Techniques/methods
2.
Gene ; 885: 147691, 2023 Nov 15.
Article in English | MEDLINE | ID: mdl-37544337

ABSTRACT

Goats are the supporting pillars of rural economy contributing significantly to meat and milk production in India. It is a species targeted for fulfilling the interdependent goals of poverty reduction and creation of employment for supporting the rural income. The increased demand for goat products necessitates their genetic characterization and improvement to augment the production of native breeds. Bi-allelic, genome wide, densely placed single nucleotide polymorphism (SNP) markers are most suitable for this purpose. This paper describes the design and validation of an Affymetrix Axiom-based high-density (HD) SNP chip for goats. The array was designed using a panel of 225 samples from 15 diverse goat breeds of India. In total, more than 38 million high quality SNPs were subjected to stringent filtering and 626,975 SNPs were finally tiled on the array. The average coverage of SNPs in our chip is one SNP per four kilobase (kb), providing a denser coverage of the goat genome than previously available arrays. The HD chip (Axiom_Cahi) was validated by genotyping 443 samples from 26 indigenous goat breeds/populations. The results revealed 95.83% markers to be highly informative and polymorphic in Indian goats. Multivariate analysis indicated population structuring, as 15 breeds could be segregated using the designed array. Phylogenetic analysis suggested stratification of breeds by geographic proximity. This HD SNP chip for goats is a valuable resource for genomic selection, genome wide association as well as population genetic studies in goats.


Subject(s)
Genome-Wide Association Study , Goats , Animals , Phylogeny , Goats/genetics , Genomics , Genome , Polymorphism, Single Nucleotide
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