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1.
Animals (Basel) ; 14(11)2024 May 30.
Artículo en Inglés | MEDLINE | ID: mdl-38891676

RESUMEN

The pig industry is usually considered an intensive livestock industry, mainly supported by hybrid breeding between commercial pig breeds. However, people's pursuit of a more natural environment and higher meat quality has led to an increasing demand for eco-friendly and diverse pig feeding systems. Therefore, the importance of rearing and conserving local pig breeds is increasing. The Livni pig is a local breed with good adaptability to the environmental and fodder conditions in central Russia. In this study, we aimed to analyze the genetic diversity and population structure of Livni pigs using whole-genome single nucleotide polymorphism (SNP) data. We utilized the Porcine GGP HD BeadChip on genotype samples from old (n = 32, 2004) and modern (n = 32, 2019) populations of Livni pigs. For the museum samples of Livni pigs (n = 3), we extracted DNA from their teeth, performed genomic sequencing, and obtained SNP genotypes from the whole-genome sequences. SNP genotypes of Landrace (n = 32) and Large White (n = 32) pigs were included for comparative analysis. We observed that the allelic richness of Livni pigs was higher than those of Landrace and Large White pigs (AR = 1.775-1.798 vs. 1.703 and 1.668, respectively). The effective population size estimates (NE5 = 108 for Livni pigs, NE5 = 59 for Landrace and Large White pigs) confirmed their genetic diversity tendency. This was further supported by the length and number of runs of homozygosity, as well as the genomic inbreeding coefficient (almost twofold lower in Livni pigs compared to Landrace and Large White pigs). These findings suggest that the Livni pig population exhibits higher genetic diversity and experiences lower selection pressure compared to commercial pig populations. Furthermore, both principal component and network tree analyses demonstrated a clear differentiation between Livni pigs and transboundary commercial pigs. The TreeMix results indicated gene flow from Landrace ancestors to Livni pigs (2019) and from Large White ancestors to Livni pigs (2004), which was consistent with their respective historical breeding backgrounds. The comparative analysis of museum, old, and modern Livni pigs indicated that the modern Livni pig populations have preserved their historical genomic components, suggesting their potential suitability for future design selection programs.

2.
Genes (Basel) ; 11(8)2020 08 14.
Artículo en Inglés | MEDLINE | ID: mdl-32824045

RESUMEN

Analysis of ancient and historical DNA has great potential to trace the genetic diversity of local cattle populations during their centuries-long development. Forty-nine specimens representing five cattle breeds (Kholmogor, Yaroslavl, Great Russian, Novgorod, and Holland), dated from the end of the 19th century to the first half of the 20th century, were genotyped for nine polymorphic microsatellite loci. Using a multiple-tube approach, we determined the consensus genotypes of all samples/loci analysed. Amplification errors, including allelic drop-out (ADO) and false alleles (FA), occurred with an average frequency of 2.35% and 0.79%, respectively. A significant effect of allelic length on ADO rate (r2 = 0.620, p = 0.05) was shown. We did not observe significant differences in genetic diversity among historical samples and modern representatives of Kholmogor and Yaroslavl breeds. The unbiased expected heterozygosity values were 0.726-0.774 and 0.708-0.739; the allelic richness values were 2.716-2.893 and 2.661-2.758 for the historical and modern samples, respectively. Analyses of FST and Jost's D genetic distances, and the results of STRUCTURE clustering, showed the maintenance of a part of historical components in the modern populations of Kholmogor and Yaroslavl cattle. Our study contributes to the conservation of biodiversity in the local Russian genetic resources of cattle.


Asunto(s)
Alelos , Variación Genética , Genética de Población , Repeticiones de Microsatélite , Animales , Cruzamiento , Bovinos , Genotipo , Análisis de Componente Principal
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