Semen characteristics of purebred and crossbred male rabbits.
Ontology highlight
ABSTRACT:
SUBMITTER: El-Tarabany MS
PROVIDER: S-EPMC4447379 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Publications
Semen characteristics of purebred and crossbred male rabbits.
El-Tarabany Mahmoud Salah MS El-Bayomi Khairy K Abdelhamid Tamer T
PloS one 20150528 5
The aim of this investigation was to evaluate the semen quality traits of purebred male rabbits and their crosses under subtropical Egyptian conditions. A full 3 x 3 diallel crossing was performed for producing the first generation progeny of New Zealand White (N), Flander (F) and Rex (R) breeds. The highest ejaculate volume (p< 0.05) and percentage of live sperms (p<0.01) with the lowest percentage of sperm cell morphological abnormalities (p<0.05) had been recorded in the NF bucks. Moreover, t ...[more]
Similar Datasets
Project description:BackgroundThe two main genetic types in Iberian pig production show important phenotypic differences in growth, fattening and tissue composition since early developmental stages. The objective of this work was the evaluation of muscle transcriptome profile in piglets of both genetic types, in order to identify genes, pathways and regulatory factors responsible for their phenotypic differences. Contemporary families coming from pure Iberian pigs (IB) or from crossing with Duroc boars (DU×IB) were generated. Piglets (14 from each genetic type) were slaughtered at weaning (28 days) and longissimus dorsi was sampled for composition and gene expression studies. RNA was obtained and hybridized to Affymetrix Porcine Genechip expression arrays.ResultsLoin muscle chemical composition showed significant differences between genetic types in intramuscular fat content (6.1% vs. 4.3% in IB and DUxIB animals, respectively, P = 0.009) and in saturated (P = 0.019) and monounsaturated fatty acid proportions (P = 0.044). The statistical analysis of gene expression data allowed the identification of 256 differentially expressed (DE) genes between genetic types (FDR < 0.10), 102 upregulated in IB and 154 upregulated in DU×IB. Transcript differences were validated for a subset of DE genes by qPCR. We observed alteration in biological functions related to extracellular matrix function and organization, cellular adhesion, muscle growth, lipid metabolism and proteolysis. Candidate genes with known effects on muscle growth were found among the DE genes upregulated in DU×IB. Genes related to lipid metabolism and proteolysis were found among those upregulated in IB. Regulatory factors (RF) potentially involved in the expression differences were identified by calculating the regulatory impact factors. Twenty-nine RF were found, some of them with known relationship with tissue development (MSTN, SIX4, IRX3), adipogenesis (CEBPD, PPARGC1B), or extracellular matrix processes (MAX, MXI1). Correlation among the expression of these RF and DE genes show relevant differences between genetic types.ConclusionThese results provide valuable information about genetic mechanisms determining the phenotypic differences on growth and meat quality between the genetic types studied, mainly related to the development and function of the extracellular matrix and also to some metabolic processes as proteolysis and lipid metabolism. Transcription factors and regulatory mechanisms are proposed for these altered biological functions.
| S-EPMC4070551 | biostudies-literature
Project description:For swine breeding programs, testing and selection programs are usually within purebred (PB) populations located in nucleus units that are generally managed differently and tend to have a higher health level than the commercial herds in which the crossbred (CB) descendants of these nucleus animals are expected to perform. This approach assumes that PB animals selected in the nucleus herd will have CB progeny that have superior performance at the commercial level. There is clear evidence that this may not be the case for all traits of economic importance and, thus, including data collected at the commercial herd level may increase the accuracy of selection for commercial CB performance at the nucleus level. The goal for this study was to estimate genetic parameters for five maternal reproductive traits between two PB maternal nucleus populations (Landrace and Yorkshire) and their CB offspring: Total Number Born (TNB), Number Born Alive (NBA), Number Born Alive > 1 kg (NBA > 1 kg), Total Number Weaned (TNW), and Litter Weight at Weaning (LWW). Estimates were based on single-step GBLUP by analyzing any two combinations of a PB and the CB population, and by analyzing all three populations jointly. The genomic relationship matrix between the three populations was generated by using within-population allele frequencies for relationships within a population, and across-population allele frequencies for relationships of the CB with the PB animals. Utilization of metafounders for the two PB populations had no effect on parameter estimates, so the two PB populations were assumed to be genetically unrelated. Joint analysis of two (one PB plus CB) vs. three (both PB and CB) populations did not impact estimates of heritability, additive genetic variance, and genetic correlations. Heritabilities were generally similar between the PB and CB populations, except for LWW and TNW, for which PB populations had about four times larger estimates than CB. Purebred-crossbred genetic correlations (rpc) were larger for Landrace than for Yorkshire, except for NBA > 1 kg. These estimates of rpc indicate that there is potential to improve selection of PB animals for CB performance by including CB information for all traits in the Yorkshire population, but that noticeable additional gains may only occur for NBA > 1 kg and TNW in the Landrace population.
| S-EPMC8557628 | biostudies-literature
Project description:This study assessed the accuracy and bias of genomic prediction (GP) in purebred Holstein (H) and Jersey (J) as well as crossbred (H and J) validation cows using different reference sets and prediction strategies. The reference sets were made up of different combinations of 36,695 H and J purebreds and crossbreds. Additionally, the effect of using different sets of marker genotypes on GP was studied (conventional panel: 50k, custom panel enriched with, or close to, causal mutations: XT_50k, and conventional high-density with a limited custom set: pruned HDnGBS). We also compared the use of genomic best linear unbiased prediction (GBLUP) and Bayesian (emBayesR) models, and the traits tested were milk, fat, and protein yields. On average, by including crossbred cows in the reference population, the prediction accuracies increased by 0.01-0.08 and were less biased (regression coefficient closer to 1 by 0.02-0.16), and the benefit was greater for crossbreds compared to purebreds. The accuracy of prediction increased by 0.02 using XT_50k compared to 50k genotypes without affecting the bias. Although using pruned HDnGBS instead of 50k also increased the prediction accuracy by about 0.02, it increased the bias for purebred predictions in emBayesR models. Generally, emBayesR outperformed GBLUP for prediction accuracy when using 50k or pruned HDnGBS genotypes, but the benefits diminished with XT_50k genotypes. Crossbred predictions derived from a joint pure H and J reference were similar in accuracy to crossbred predictions derived from the two separate purebred reference sets and combined proportional to breed composition. However, the latter approach was less biased by 0.13. Most interestingly, using an equalized breed reference instead of an H-dominated reference, on average, reduced the bias of prediction by 0.16-0.19 and increased the accuracy by 0.04 for crossbred and J cows, with a little change in the H accuracy. In conclusion, we observed improved genomic predictions for both crossbreds and purebreds by equalizing breed contributions in a mixed breed reference that included crossbred cows. Furthermore, we demonstrate, that compared to the conventional 50k or high-density panels, our customized set of 50k sequence markers improved or matched the prediction accuracy and reduced bias with both GBLUP and Bayesian models.
| S-EPMC7767986 | biostudies-literature
Project description:BackgroundIn pigs, crossbreeding aims at exploiting heterosis, but heterosis is difficult to quantify. Heterozygosity at genetic markers is easier to measure and could potentially be used as an indicator of heterosis. The objective of this study was to investigate the effect of heterozygosity on various maternal and production traits in purebred and crossbred pigs. The proportion of heterozygosity at genetic markers across the genome for each individual was included in the prediction model as a fixed regression across or within breeds.ResultsEstimates of regression coefficients of heterozygosity showed large effects for some traits. For maternal traits, regression coefficient estimates were always in a favourable direction, while for production, meat and slaughter quality traits, they were both favourable and unfavourable. Traits with the largest estimated effects of heterozygosity were total number born, litter weight at 3 weeks, weight at 150 days, and age at 40 kg. Estimates of regression coefficients on heterozygosity differed between breeds. Traits with the largest effect of heterozygosity also showed a significant (P < 0.05) increase in prediction accuracy when heterozygosity was included in the model compared to the model without heterozygosity.ConclusionsFor traits with the largest estimates of regression coefficients on heterozygosity, the inclusion of heterozygosity in the model improved prediction accuracy. Using models that include heterozygosity would result in selecting different animals for breeding, which has the potential to improve genetic gain for these traits. This is most beneficial when crossbreds or several breeds are included in the estimation of breeding values and is relevant to all species, not only pigs. Thus, our results show that including heterozygosity in the model is beneficial for some traits, likely due to dominant gene action.
| S-EPMC6396501 | biostudies-literature
Project description:BackgroundGenomic selection can be applied to select purebreds for crossbred performance (CP). The average performance of crossbreds can be considered as the summation of two components, i.e. the breed average (BA) of the parental breeds and heterosis (H) present in crossbreds. Selection of pure breeds for CP based on genomic estimated breeding values for crossbred performance (GEBV-C) or for purebred performance (GEBV-P) may differ in their ability to exploit BA and H and can affect the merit of crossbreds in both the short and long term. Selection based on GEBV-C is beneficial for CP, because H in crossbreds is efficiently exploited, whereas selection on GEBV-P results in more genetic progress in pure breeds, which increases the BA component of CP. To investigate the outcome of selection on GEBV-C and GEBV-P in both the short and long term, a two-way crossbreeding program was simulated to test the following hypotheses: (1) does selection on GEBV-P result in higher long-term CP compared to selection on GEBV-C and (2) does selection on a combination of GEBV-P and GEBV-C lead to more long-term gain in CP than selection on either separately.MethodsWe investigated the performance of crossbreds in a two-way crossbreeding program across 40 generations and considered different criteria to select purebred parents that ranged from selection on purebred performance to selection for CP with different weights on genomic evaluations based on purebred and CP. These criteria were compared under three genetic models to investigate the effects of the amount of dominance variance, absence of over-dominance, and the structure of the reference population on CP, both in the short and long term.Results and conclusionsAlthough beneficial in the short to medium term, genomic selection in pure breeds on a criterion that specifically targets CP was inferior to selection for purebred performance in the long term. A selection criterion that maximizes a combination of short- and long-term responses in CP, should improve the components that define crossbred merit (i.e., BA and H) simultaneously.
| S-EPMC5865367 | biostudies-literature
Project description:Genomic selection has been widely implemented in dairy cattle breeding when the aim is to improve performance of purebred animals. In pigs, however, the final product is a crossbred animal. This may affect the efficiency of methods that are currently implemented for dairy cattle. Therefore, the objective of this study was to determine the accuracy of predicted breeding values in crossbred pigs using purebred genomic and phenotypic data. A second objective was to compare the predictive ability of SNPs when training is done in either single or multiple populations for four traits: age at first insemination (AFI); total number of piglets born (TNB); litter birth weight (LBW); and litter variation (LVR). We performed marker-based and pedigree-based predictions. Within-population predictions for the four traits ranged from 0.21 to 0.72. Multi-population prediction yielded accuracies ranging from 0.18 to 0.67. Predictions across purebred populations as well as predicting genetic merit of crossbreds from their purebred parental lines for AFI performed poorly (not significantly different from zero). In contrast, accuracies of across-population predictions and accuracies of purebred to crossbred predictions for LBW and LVR ranged from 0.08 to 0.31 and 0.11 to 0.31, respectively. Accuracy for TNB was zero for across-population prediction, whereas for purebred to crossbred prediction it ranged from 0.08 to 0.22. In general, marker-based outperformed pedigree-based prediction across populations and traits. However, in some cases pedigree-based prediction performed similarly or outperformed marker-based prediction. There was predictive ability when purebred populations were used to predict crossbred genetic merit using an additive model in the populations studied. AFI was the only exception, indicating that predictive ability depends largely on the genetic correlation between PB and CB performance, which was 0.31 for AFI. Multi-population prediction was no better than within-population prediction for the purebred validation set. Accuracy of prediction was very trait-dependent.
| S-EPMC4528314 | biostudies-literature
Project description:Considering the current low prices for coarse wool (fibre diameter > 30 µm), a grading up transition to a shedding flock may eliminate wool harvesting costs and increase sheep farm profit. This transition could be achieved by breeding non-shedding ewes with Wiltshire rams. A bio-economic system-dynamics model of a pastoral sheep farming enterprise was used to simulate this grading up transition from 2580 Romney ewes to a similarly-sized flock of fully shedding third or fourth cross Wiltshire-Romney ewes. The total annual sheep feed demand was constrained within a ±5% range to minimise disruption to the on-farm beef cattle enterprise. Wool harvesting expenses were eliminated after seven years of transition, and with reduced feed demand for wool growth, the post-transition shedding flocks had more ewes producing more lambs and achieving greater annual profit compared with the base Romney flock. The net present values of transition were 7% higher than the maintenance of the base Romney flock with a farmgate wool price of $2.15/kg. Results suggest that coarse wool-producing farmers should consider a grading up transition to a shedding flock, and the collection of data on the production of Wiltshire-Romney sheep in New Zealand would improve the accuracy of model predictions.
| S-EPMC7695207 | biostudies-literature
Project description:Crossbreeding is a common practice among commercial sheep producers to improve animal performance. However, genetic evaluation of U.S. sheep is performed within breed type (terminal sire, semi-prolific, and western range). While incorporating crossbred records may improve assessment of purebreds, it requires accounting for heterotic and breed effects in the evaluation. The objectives of this study were to: 1) describe the development of a paternal composite (PC) line, 2) determine the effect of direct and maternal heterosis on growth traits of crossbred lambs, 3) estimate (co)variance components for direct and maternal additive, and uncorrelated maternal environmental, effects, and 4) provide an interpretation of the estimates of random effects of genetic groups, and to use those solutions to compare the genetic merit of founding breed subpopulations. Data included purebred and crossbred records on birth weight (BN; n = 14,536), pre-weaning weight measured at 39 or 84 d (WN; n = 9,362) depending on year, weaning weight measured at 123 d (WW; n = 9,297), and post-weaning weight measured at 252 d (PW; n = 1,614). Mean (SD) body weights were 5.3 (1.1), 16.8 (3.9) and 28.0 (7.6), 39.1 (7.2), and 54.2 (8.7) kg for BN, WN (at the two ages), WW, and PW, respectively. In designed experiments, the Siremax, Suffolk, Texel, Polypay, Columbia, Rambouillet, and Targhee breeds were compared within the same environment. Estimates of heterotic effects and covariance components were obtained using a multiple trait animal model. Genetic effects based on founders' breeds were significant and included in the model. Percent estimates of direct heterosis were 2.89 ± 0.61, 2.60 ± 0.65, 4.24 ± 0.56, and 6.09 ± 0.86, and estimates of maternal heterosis were 1.92 ± 0.87, 4.64 ± 0.80, 3.95 ± 0.66, and 4.04 ± 0.91, for BN, WN, WW, and PW, respectively. Correspondingly, direct heritability estimates were 0.17 ± 0.02, 0.13 ± 0.02, 0.17 ± 0.02, and 0.46 ± 0.04 for BN, WN, WW, and PW. Additive maternal effects accounted for trivial variation in PW. For BN, WN, and WW, respectively, maternal heritability estimates were 0.16 ± 0.02, 0.10 ± 0.02, and 0.07 ± 0.01. Uncorrelated maternal environmental effects accounted for little variation in any trait. Direct and maternal heterosis had considerable impact on growth traits, emphasizing the value of crossbreeding and the need to account for heterosis, in addition to breed effects, if crossbred lamb information is included in genetic evaluation.
| S-EPMC9191838 | biostudies-literature
Project description:Heat stress causes infertility in male rabbits in summer. This study was conducted to determine the effects of heat stress on semen quality and seminal plasma metabolites of male rabbits. To achieve these objectives, the temperature and humidity index (THI) was used to determine the stress state of male rabbits during different months, thereby the rabbits were divided into heat stress and no heat stress groups. The quality of the semen and the biochemical indices of seminal plasma were then analyzed. Next the plasma metabolites of rabbits in both groups were evaluated using the ultra-high performance liquid chromatography-mass spectroscopy (UPLC-MS)/MS technique. Our results showed that the THI value of the rabbit housing in May was 20.94 (no heat stress). The THI value of the housing in August was 29.10 (heat stress group, n = 10). Compared with the non-heat stress group, the sperm motility, density, and pH in the heat stress group (n = 10) were significantly decreased (P < 0.01); the semen volume decreased significantly (P < 0.05); and the sperm malformation rate increased significantly (P < 0.01). The number of grade A sperm significantly decreased, while the numbers of B and C grade sperm significantly increased (P < 0.01). The total sperm output (TSO), total motile sperm (TMS), and total functional sperm fraction (TFSF) decreased significantly (P < 0.01). Heat stress protein 70 (HSP70) and acid phosphatase (ACP) in the seminal plasma of rabbits in the heat stress group (n = 20) were significantly increased (P < 0.01). Seminal plasma testosterone (T), α-glucosidase (α-Glu), and fructose decreased significantly (P < 0.01). The concentrations of Mg2+ (P < 0.05), Na+ (P < 0.01), and K+ (P < 0.01) in metal ions were significantly decreased. These findings indicated that heat stress severely affected the quality of the male rabbit semen. Furthermore, UPLC-MS/MS technology was used to analyze the seminal plasma samples of rabbits in the heat stress group and non-heat stress group (n = 9 for each group). In total, 346 metabolites were identified, with variable importance in project (VIP) > 1.0, fold change (FC) > 1.5 or < 0.667, and P < 0.05 as the threshold. A total of 71 differential metabolites were matched, including stearic acid, betaine, arachidonic acid, L-malic acid, and indole. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differential metabolites revealed 51 metabolic pathways, including synthesis and degradation of ketones, serine and threonine metabolism, tryptophan metabolism, and the citric acid cycle. Our study has shown that the sperm motility, sperm pH value, and sperm density of male rabbits decreased significantly under heat stress, and the sperm malformation rate increased significantly. Furthermore, the quality of semen was shown to deteriorate and the energy metabolism pathway was disturbed. These findings provide a theoretical reference for alleviating the adaptive heat stress in male rabbits.
| S-EPMC10103697 | biostudies-literature
Project description:INGA FOOD S. A., as a Spanish company that produces and commercializes fattened pigs, has produced a hybrid Iberian sow called CASTÚA by crossing the Retinto and Entrepelado varieties. The selection of the parental populations is based on selection criteria calculated from purebred information, under the assumption that the genetic correlation between purebred and crossbred performance is high; however, these correlations can be less than one because of a GxE interaction or the presence of non-additive genetic effects. This study estimated the additive and dominance variances of the purebred and crossbred populations for litter size, and calculated the additive genetic correlations between the purebred and crossbred performances. The dataset consisted of 2030 litters from the Entrepelado population, 1977 litters from the Retinto population, and 1958 litters from the crossbred population. The individuals were genotyped with a GeneSeek® GGP Porcine70K HDchip. The model of analysis was a 'biological' multivariate mixed model that included additive and dominance SNP effects. The estimates of the additive genotypic variance for the total number born (TNB) were 0.248, 0.282 and 0.546 for the Entrepelado, Retinto and Crossbred populations, respectively. The estimates of the dominance genotypic variances were 0.177, 0.172 and 0.262 for the Entrepelado, Retinto and Crossbred populations. The results for the number born alive (NBA) were similar. The genetic correlations between the purebred and crossbred performance for TNB and NBA-between the brackets-were 0.663 in the Entrepelado and 0.881 in Retinto poplulations. After backsolving to obtain estimates of the SNP effects, the additive genetic variance associated with genomic regions containing 30 SNPs was estimated, and we identified four genomic regions that each explained > 2% of the additive genetic variance in chromosomes (SSC) 6, 8 and 12: one region in SSC6, two regions in SSC8, and one region in SSC12.
| S-EPMC8774905 | biostudies-literature