Examinando por Materia "Genotyping"

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Genome-wide association study of fiber diameter in alpacas
(MDPI, 2023-10-25) More, Manuel; Veli Rivera, Eudosio Amancio; Cruz, Alan; Gutiérrez, Juan Pablo; Gutiérrez, Gustavo; Ponce de León, F. Abel
The aim of this study was the identification of candidate genomic regions associated with fiber diameter in alpacas. DNA samples were collected from 1011 female Huacaya alpacas from two geographical Andean regions in Peru (Pasco and Puno), and three alpaca farms within each region. The samples were genotyped using an Affymetrix Custom Alpaca genotyping array containing 76,508 SNPs. After the quality controls, 960 samples and 51,742 SNPs were retained. Three association study methodologies were performed. The GWAS based on a linear model allowed us to identify 11 and 35 SNPs (−log10(p-values) > 4) using information on all alpacas and alpacas with extreme values of fiber diameter, respectively. The haplotype and marker analysis method allowed us to identify nine haplotypes with standardized haplotype heritability higher than six standard deviations. The selection signatures based on cross-population extended haplotype homozygosity (XP-EHH) allowed us to identify 180 SNPs with XP-EHH values greater than |3|. Four candidate regions with adjacent SNPs identified via two association methods of analysis are located on VPA6, VPA9, VPA29 and one chromosomally unassigned scaffold. This study represents the first analysis of alpaca whole genome association with fiber diameter, using a recently assembled alpaca SNP microarray.
Genome-wide single nucleotide polymorphisms reveal the genetic diversity and population structure of Creole goats from northern Peru
(Elsevier, 2024-04-24) Corredor Arizapana, Flor Anita; Figueroa Venegas, Deyanira Antonella; Estrada Cañari, Richard; Burgos Paz, William; Salazar Coronel, Wilian; Cruz Góngora, Wilder; Lobato Gálvez, Roiser Honorio; Injante Silva, Pedro Hugo; Godoy Padilla, David José; Barrantes Bravo, Christian Alfredo; Ganoza Roncal, Jorge Juan; Cruz Luis, Juancarlos Alejandro; Arbizu Berrocal, Carlos Irvin
Goat farming constitutes a significant source of income for farmers in northern Peru. There is currently an absence of information about the genetics of Peruvian Creole goats that would enable us to understand their origins and genetic spread. The objective of this study was to estimate the genetic diversity of Creole goats from northern Peru using SNP markers. This study involved the collection of 192 male Creole goats from three key goat production geographical departments in northern Peru. These goat samples were genotyped using the GGPGoat70k SNP panel. To explore the genetic influence of other breeds on Peruvian Creole goats, our dataset was combined with previously published SNP genotypes. External data set includes multiple breeds genotypes sampled from Argentina, Brazil, Spain, and Alpine breed from Italy, France, and Switzerland. After quality control 52,832 autosomal SNPs were used to assess genetic diversity in the Peruvian goats. For the population structure analysis of the merged data 20,513 common SNPs were used. Estimations for expected heterozygosity (He), observed heterozygosity (Ho), and inbreeding coefficient (FIS) were computed for the Peruvian groups. AMOVA, principal component analysis and ADMIXTURE were conducted to evaluate the population structure in the two data sets, Peru and merged. The results revealed a considerable genetic diversity, with Ho values ranging from 0.40 to 0.41 for the Peruvian sampling groups, and inbreeding coefficient was notably low for Peruvian goat. The population structure analysis demonstrated a distinction (p < 0.05) from other breeds. These findings suggest a level of genetic differentiation of the Peruvian goat population among other breeds, although further research is needed considering samples from other Peruvian areas. We expect this study will contribute to define genetic management strategies to prevent the loss of genetic diversity in Peruvian goat populations and for upcoming advancements in this field.