Data and pedigree information used in the present study were 3,022 records of kids obtained from the breeding station of Raini goat. The studied traits were birth weight (BW), weaning weight (WW), average daily gain from birth to weaning (ADG) and Kleiber ratio at weaning (KR). The model included the fixed effects of sex of kid, type of birth, age of dam, year of birth, month of birth, and age of kid (days) as covariate that had significant effects, and random effects direct additive genetic, maternal additive genetic, maternal permanent environmental effects and residual. (Co) variance components were estimated using univariate and multivariate analysis by WOMBAT software applying four animal models including and ignoring maternal effects. Likelihood ratio test used to determine the most appropriate models. Heritability (h(a)(2)) estimates for BW, WW, ADG, and KR according to suitable model were 0.12 ± 0.05, 0.08 ± 0.06, 0.10 ± 0.06, and 0.06 ± 0.05, respectively. Estimates of the proportion of maternal permanent environmental effect to phenotypic variance (c(2)) were 0.17 ± 0.03, 0.07 ± 0.03, and 0.07 ± 0.03 for BW, WW, and ADG, respectively. Genetic correlations among traits were positive and ranged from 0.53 (BW-ADG) to 1.00 (WW-ADG, WW-KR, and ADG-KR). The maternal permanent environmental correlations between BW-WW, BW-ADG, and WW-ADG were 0.54, 0.48, and 0.99, respectively. Results indicated that maternal effects, especially maternal permanent environmental effects are an important source of variation in pre-weaning growth trait and ignoring those in the model redound incorrect genetic evaluation of kids.
CpG islands (CGIs) are an important group of CpG dinucleotides in the guanine-and cytosinerich regions as they harbour functionally relevant epigenetic loci for whole genome studies. As a matter of fact, since there has not been a formal comparative analysis of CGIs in domestic even-toed ungulate genomes, this study was performed to serve this comparison. The Hidden Markov Model was used to detect CGIs in the genomes. The results indicated that the CGIs number and CGI densities had scant variations across genomes. The goat genome had the highest number of CGIs (99 070), whereas the alpaca genome had the highest CGI density (43.39 CGIs/Mb). Significant positive correlations were observed among CGI densities with chromosome pair number, observed CpG/expected CpG, recombination rate, and gene density. When the size of chromosomes increased, the CGI densities decreased and a trend of higher CGI densities in the telomeric regions was observed. Only 10.96% of CGIs were methylated underscoring this postulation that the majority of CGIs remains to be unmethylated. The highest amount of the methylated CGIs was observed in the introns, intergenic, and coding (CDS) regions and the lowest amount of the methylated CGIs was observed in the promoter regions, implying that the DNA methylation of CGIs may control gene expression at the genome level. Detected differences between even-toed ungulate and other vertebrate genomes showed that CGI densities varied greatly among the genomes. These findings would contribute to better understanding the even-toed ungulate (epi) genomes, the role of CGIs in epigenomic functions and molecular evolution.
Survival records from 1,763 Kermani lambs born between 1996 and 2004 from 294 ewes and 81 rams were used to determine genetic and non-genetic factors affecting lamb survival. Traits included were lamb survival across five periods from birth to 7, 14, 56, 70, and 90 days of age. Traits were analyzed under Weibull proportional hazard sire models. Several binary analyses were also conducted using animal models. Statistical models included the fixed class effects of sex of lamb, month and year of birth, a covariate effect of birth weight, and random genetic effects of both sire (in survival analyses) and animal (in binary analyses). The average survival to 90 days of age was 94.8%. Hazard rates ranged from 1.00 (birth to 90 days of age) to 1.73 (birth to 7 days of age) between the two sexes indicating that male lambs were at higher risk of mortality than females (P < 0.01). This study also revealed a curvilinear relationship between lamb survival and lamb birth weight, suggesting that viability and birth weight could be considered simultaneously in the selection programs to obtain optimal birth weight in Kermani lambs. Estimates of heritabilities from survival analyses were medium and ranged from 0.23 to 0.29. In addition, heritability estimates obtained from binary analyses were low and varied from 0.04 to 0.09. The results of this study suggest that progress in survival traits could be possible through managerial strategies and genetic selection.
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