• Animal Bioscience
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• v.34 no.7
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• pp.1116-1122
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• 2021

Objective: The aim was to characterize the genetic diversity evolution of the registered Mexican Charolais cattle population by pedigree analysis. Methods: Data consisted of 331,390 pedigree records of animals born from 1934 to 2018. Average complete generation equivalent, generation interval, effective population size (N_e), and effective numbers of founders (f_e), ancestors (f_a), and founder genomes (N_g) were calculated for seven five-year periods. The inbreeding coefficient was calculated per year of birth, from 1984 to 2018, whereas the gene contribution of the most influential ancestors was calculated for the latter period. Results: Average complete generation equivalent consistently increased across periods, from 4.76, for the first period (1984 through 1988), to 7.86, for the last period (2014 through 2018). The inbreeding coefficient showed a relative steadiness across the last seventeen years, oscillating from 0.0110 to 0.0145. During the last period, the average generation interval for the father-offspring pathways was nearly 1 yr. longer than that of the mother-offspring pathways. The effective population size increased steadily since 1984 (105.0) and until 2013 (237.1), but showed a minor decline from 2013 to 2018 (233.2). The population displayed an increase in the f_a since 1984 and until 2008; however, showed a small decrease during the last decade. The effective number of founder genomes increased from 1984 to 2003, but revealed loss of genetic variability during the last fifteen years (from 136.4 to 127.7). The f_a:f_e ratio suggests that the genetic diversity loss was partially caused by formation of genetic bottlenecks in the pedigree; in addition, the N_g:f_a ratio indicates loss of founder alleles due to genetic drift. The most influential ancestor explained 1.8% of the total genetic variability in the progeny born from 2014 to 2018. Conclusion: Inbreeding, N_e, f_a, and N_g are rather beyond critical levels; therefore, the current genetic status of the population is not at risk.

• Animal Bioscience
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• v.36 no.5
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• pp.692-703
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• 2023

Objective: The main goals of this investigation were to i) assess the population structure and genetic diversity and ii) determine the efficiency of the ongoing breeding program in a closed flock of Angora rabbits through pedigree analysis. Methods: The pedigree records of 6,145 animals, born between 1996 to 2020 at NTRS, ICAR-CSWRI, Garsa were analyzed using ENDOG version 4.8 software package. The genealogical information, genetic conservation index and parameters based on gene origin probabilities were estimated. Results: Analysis revealed that, 99.09% of the kits had both parents recorded in the whole dataset. The completeness levels for the whole pedigree were 99.12%, 97.12%, 90.66%, 82.49%, and 74.11% for the 1st, 2nd, 3rd, 4th, and 5th generations, respectively, reflecting well-maintained pedigree records. The maximum inbreeding, average inbreeding and relatedness were 36.96%, 8.07%, and 15.82%, respectively. The mean maximum, mean equivalent and mean completed generations were 10.28, 7.91, and 5.51 with 0.85%, 1.19%, and 1.85% increase in inbreeding, respectively. The effective population size estimated from maximum, equivalent and complete generations were 58.50, 27.05, and 42.08, respectively. Only 1.51% of total mating was highly inbred. The effective population size computed via the individual increase in inbreeding was 42.83. The effective numbers of founders (f_e), ancestors (f_a), founder genomes (f_g) and non-founder genomes (f_ng) were 18, 16, 6.22, and 9.50, respectively. The fe/fa ratio was 1.12, indicating occasional bottlenecks had occurred in the population. The six most influential ancestors explained 50% of genes contributed to the gene pool. The average generation interval was 1.51 years and was longer for the sire-offspring pathway. The population lost 8% genetic diversity over time, however, considerable genetic variability still existed in the closed Angora population. Conclusion: This study provides important and practical insights to manage and maintain the genetic variability within the individual flock and the entire population.