Meta-analysis of average estimates of genetic parameters for growth, reproduction and milk production traits in goats

Developmental programming of reproduction in sheep and goat: Association of fraternity size and sex ratio with reproductive performance of ewes and does at the first pregnancy

Various prenatal factors including the number of littermates (fraternity size) and exposure to male littermate (fraternity sex ratio) during fetal period have been reported to influence postnatal fertility in the mammals. The present research was conducted to study the association of fraternity size and sex ratio with reproductive performance of nulliparous ewes and does. To this end, data associated with number of littermates, exposure to male littermate, birth weight, age at first pregnancy, as well as litter size, sex ratio of offspring, litter weight, and birth weight of female and male offspring after the first parturition retrieved from the database of sheep (n = 536 Romane and 289 Blanche du Massif Central ewes) and goat (n = 174 Alpine and 267 Saanen does) flocks. Fraternity size was negatively associated with birth weight of ewes and does (P < 0.05). Exposure to male littermate during fetal period was associated with younger age at first pregnancy and larger litter size in the does (P < 0.05), but not in the ewes (P > 0.05). Exposure to male littermate during fetal period was positively associated with the odds of male-biased litters in the ewes and does (P < 0.05). Fraternity size was positively associated with litter weight in the does (P < 0.05), but not in the ewes (P > 0.05). In conclusion, the present study showed that the number and sex of littermates during fetal period could impact postnatal reproduction of ewes and does. In this context, some associations, particularly those related to exposure to male littermate during fetal period, were only observed in does, which implicates that the effect of androgens on developmental programming of reproduction may be species-specific.

Genetic parameters for reproductive traits and somatic cell score in U.S. dairy goats

There are no studies regarding the estimation of genetic parameters and genetic trends for reproductive traits and somatic cells in goats. Their knowledge allows optimization of selection schemes. The objective of this study was to estimate genetic parameters and genetic and phenotypic trends for age at first kidding (AFK), kidding interval (KIN) and somatic cell score (SCS). Analyses were conducted within and across seven US goat breeds, namely, Nubian (NU), Alpine (AL), LaMancha (LM), Toggenburg (TO), Saanen (SA), Nigerian Dwarf (ND) and Oberhasli (OB), and a set of all of these breeds (AB). The restricted maximum likelihood methodology and trivariate animal models were used. Genetic and phenotypic trends were estimated using regression models. The average and standard deviation of AFK, KIN and SCS for AB were 573.6 ± 178.5 days, 418.8 ± 125.5 days and 4.67 ± 2.23 Log2, respectively. The heritabilities (h2) and standard errors of AFK, KIN and SCS for AB were 0.28 ± 0.02, 0.04 ± 0.02 and 0.22 ± 0.01, respectively. The h2 ranged from 0.15 (SA) to 0.37 (NU) for AFK, from 0.04 (AB) to 0.10 (AL) for KIN, and from 0.11 (TO) to 0.26 (LM and ND) for SCS. Genetic correlations between AFK and KIN and between AFK and SCS for AB were positive and weak (0.07 and 0.12, respectively) but significant (P < 0.01). Genetic correlations between SCS and KIN were significant (P < 0.01) for all the breeds and ranged from -0.15 (NU) to 0.44 (AL). Genetic correlations between AFK and SCS in the NU and AL breeds were similar (approximately 0.21). A positive genetic trend was found for KIN in the SA breed, which caused an increase in the number of days between consecutive kiddings. The genetic trend of SCS for the NU, AL and ND breeds was negative and decreased annually, which is beneficial for producers. These first results show the intensity and direction of some favorable/unfavorable relationships between AFK or KIN and SCS Log2 in some U.S. goat genetic groups.

Breeding objectives for Central Highland goats using participatory and bio-economic modelling approaches

The breeding objectives of Central Highland goats rearing under a low-input production system were defined through a participatory proportional piling method and bio-economic model. Additionally, the economic values and relative economic value of the breeding objective traits were derived. A participatory proportional piling method was used to estimate the relative weights of farmers attached to a list of goat traits identified, and the relative weights were statistically evaluated using a generalized multinomial logit model analysis. A bio-economic model was used to compute the economic values of the identified traits. The most important traits for selection of does according to farmer's preference were body size, coat colour, post-weaning growth rate and weaning rate with a relative weight (odds ratio) of 1.58, 1.38, 1.37 and 1.13, respectively. Goats with dark red followed by light red coat colour were the most preferred (p < 0.001) by goat keepers compared with white-coloured goats. Farmers were more likely (p < 0.001) to allocate higher scores for does-bearing twins than for single and triplet-bearing does. Using the bio-economic model (economic value and relative economic value), post-weaning growth rate, weaning rate, and six-month weight (body size) were identified as the most important traits and if the mean of these traits is changed by one genetic standard deviation, the change in profit will range from 2.06 to 3.03 $ doe-1  year-1 . Therefore, the most important traits for the selection of Central Highland goats according to the economic-based method were post-weaning weight gain, weaning rate and body size (six-month weight). Besides, coat colour was the second preferred trait by goat keepers next to body size. Thus, this aesthetical trait should be included in the designed breeding programme besides economically important quantitative traits. The combination of the participatory proportional piling method and bio-economic model would give better insights to explore the trait preferences of farmers and enhance profitability. The economic values of traits estimated in this study can be used for the construction of selection indices for Central Highland goats.

Estimation of crossbreeding and genetic parameters for reproductive traits of Boer x Central Highland goats in Ethiopia

Additive genetic and non-additive parameters for reproductive traits of Boer x Central Highland goats were estimated. Pedigree and performance records comprised of Central Highland and their crosses with Boer goats were collected from 2009 to 2018 in the Sirinka Agricultural Research Center sheep and goat breeding station. Least-squares means for genotypes were obtained using a general linear model procedure in SAS. To estimate crossbreeding parameters, breed additive, heterotic, and recombination effects were fitted as fixed covariates instead of genotypes. Variance, heritability, and repeatability estimates were estimated through the AI-REML algorithm using WOMBAT software. Genotype did not significantly (P>0.05) influence most of the reproductive traits studied except for gestation length. The additive effect for litter size at birth (LSB), total litter birth weight (LBW), total litter weaning weight (LWW), litter size at weaning (LSW), and gestation length (GL) was estimated to be -0.004 kid, 0.08 kg, -3.18 kg, -0.54 kid, and 3.69 days, respectively. The contribution of heterosis to LSB, LWW, and GL of crossbred goats was negative, while the estimates for LBW and LSW were positive. However, Boer goats' heterosis effect and direct additive contribution to reproductive traits were insignificant (P>0.05) except for LSW. The recombination effect was negligible and not significant (P>0.05) for all traits examined. The direct heritability estimate for LSB, LWB, LWW, LSW, and GL were 0.050, 0.098, 0.086, 0.018, and 0.00, respectively. The repeatability estimates for LSB, LWB, LWW, LSW, and GL were 0.149, 0.116, 0.099, 0.086, and 0.061, respectively. The result indicates that improvement in reproductive traits would not be expected by crossing Boer with Central Highland goats. In addition, heritability estimates indicate that the improvement of reproductive traits through selection will be small, and the repeatability estimates indicate that multiple records have to be used to make a decision of culling or selection.

Review: Feeding strategies for rearing replacement dairy goats - from birth to kidding

Goat kid rearing is a key profit driver and the cornerstone of future herd productivity in dairy systems. As goat kids get older, and progress from liquid (i.e., colostrum, milk) to solid feed (i.e., concentrate, hay, pasture), there is a reduction not only in feed cost but also in labour cost, disease susceptibility and mortality rates. Hence, research on rearing dairy goats has traditionally focused on improving early neonatal performance. However, recent research reveals that early-life nutrition may have long-term effects, and consequently, impact the lifetime productive performance and health of dairy goats. Therefore, this literature review has collected research on the various aspects of rearing replacement dairy goat kids in different production systems. It summarises research on areas such as colostrum management (i.e., colostrum quality, time, volume and frequency of colostrum feeding), liquid feeding in preweaned kids (i.e., maternal suckling vs artificial, restricted vs unrestricted), weaning strategies (i.e., abrupt vs step-down), and postweaning to postpubertal nutrition in replacement dairy goats, whilst highlighting gaps in the existing literature, and areas where it would be beneficial to refine and validate current recommendations. Such information can be used in the development of management plans to maximise the benefits of early-life nutrition on the long-term productivity of dairy goats.

Meta-analysis of genetic parameters for growth traits in meat, wool and dual-purpose sheep breeds in the world using a random-effects model

BACKGROUND

There is large variation in genetic parameters in literature for growth traits in sheep. Reliable estimation of genetic parameters is required for developing breeding programmes.

OBJECTIVES

The aim of this study was to aggregate results of different studies by meta-analysis to improve reliability of estimated parameters.

METHODS

In the current study, 221 papers that have been published between 1995 and 2021 were reviewed. Using a random-effects model in the Comprehensive Meta-Analysis software, direct and maternal heritabilities, as well as, genetic and phenotypic correlations between growth traits were estimated in meat (M), wool (W) and dual-purpose (D) sheep breeds. The growth traits in this study were birth weight, 3-month weight, 6-month weight, 9-month weight and yearling weight.

RESULTS

The combined direct heritability was the lowest for birth weight (0.190 ± 0.004, 0.198 ± 0.003 and 0.196 ± 0.004 for M, W and D breeds, respectively) and the highest for yearling weight (0.264 ± 0.010, 0.304 ± 0.005 and 0.285 ± 0.020 for M, W and D breeds, respectively). The maternal heritability was the lowest for yearling weight (0.085 ± 0.003, 0.055 ± 0.002 and 0.052 ± 0.005 for M, W and D breeds, respectively) and the highest for 6-month weight (0.240 ± 0.088, 0.164 ± 0.001 and 0.162 ± 0.006 for M, W and D breeds, respectively). The phenotypic and genetic correlations were lower between the weights measured at more distant intervals. The lowest genetic correlation was observed between birth weight and yearling weight (0.290 ± 0.051 for W breeds).

CONCLUSIONS

The small standard errors could indicate that the aggregation of results from different studies improved the reliability of estimated parameters and reduced range of 95% confidence intervals. Hence, the results could be used with greater level of confidence in sheep breeding programmes.

Candidate Genes and Their Expressions Involved in the Regulation of Milk and Meat Production and Quality in Goats (Capra hircus)

Simple Summary

During the present decade, highly selected caprine farming has increased in popularity due to the hardiness and adaptability inherent to goats. Recent advances in genetics have enabled the improvement in goat selection efficiency. The present review explores how genetic technologies have been applied to the goat-farming sector in the last century. The main candidate genes related to economically relevant traits are reported. The major source of income in goat farming derives from the sale of milk and meat. Consequently, yield and quality must be specially considered. Meat-related traits were evaluated considering three functional groups (weight gain, carcass quality and fat profile). Milk traits were assessed in three additional functional groups (milk production, protein and fat content).

Abstract

Despite their pivotal position as relevant sources for high-quality proteins in particularly hard environmental contexts, the domestic goat has not benefited from the advances made in genomics compared to other livestock species. Genetic analysis based on the study of candidate genes is considered an appropriate approach to elucidate the physiological mechanisms involved in the regulation of the expression of functional traits. This is especially relevant when such functional traits are linked to economic interest. The knowledge of candidate genes, their location on the goat genetic map and the specific phenotypic outcomes that may arise due to the regulation of their expression act as a catalyzer for the efficiency and accuracy of goat-breeding policies, which in turn translates into a greater competitiveness and sustainable profit for goats worldwide. To this aim, this review presents a chronological comprehensive analysis of caprine genetics and genomics through the evaluation of the available literature regarding the main candidate genes involved in meat and milk production and quality in the domestic goat. Additionally, this review aims to serve as a guide for future research, given that the assessment, determination and characterization of the genes associated with desirable phenotypes may provide information that may, in turn, enhance the implementation of goat-breeding programs in future and ensure their sustainability.

Animal Board Invited Review: Meta-analysis of genetic parameters for resilience and efficiency traits in goats and sheep

Genetic selection focused purely on production traits has proven very successful in improving the productive performance of livestock. However, heightened environmental and infectious disease challenges have raised the need to also improve the resilience of animals to such external stressors, as well as their efficiency in utilising available resources. A better understanding of the relationship between efficiency and production and health traits is needed to properly account for it in breeding programmes and to produce animals that can maintain high production performance in a range of environmental conditions with minimal environmental footprint. The aim of this study was to perform a meta-analysis of genetic parameters for production, efficiency and health traits in sheep and goats. The dataset comprised 963 estimates of heritability and 572 genetic correlations collated from 162 published studies. A threelevel meta-analysis model was fitted. Pooled heritability estimates for milk production traits ranged between 0.27 ± 0.03 and 0.48 ± 0.13 in dairy goats and between 0.21 ± 0.06 and 0.33 ± 0.07 in dairy sheep. In meat sheep, the heritability of efficiency traits ranged from 0.09 ± 0.02 (prolificacy) up to 0.32 ± 0.14 (residual feed intake). For health traits, pooled heritability was 0.07 ± 0.01 (faecal egg count) and 0.21 ± 0.01 (somatic cell score) in dairy goats and 0.14 ± 0.04 (faecal egg count) and 0.13 ± 0.02 (somatic cell score) in dairy sheep. In meat sheep, the heritability of disease resistance and survival traits ranged between 0.07 ± 0.02 (mastitis) and 0.50 ± 0.10 (breech strike). Pooled estimates of genetic correlations between resilience and efficiency traits in dairy goats were not significantly different from zero with the exception of somatic cell score and fat content (-0.19 ± 0.01). In dairy sheep, only the unfavourable genetic correlation between somatic cell score and protein content (0.12 ± 0.03) was statistically significant. In meat sheep only, the correlations between growth and faecal egg count (-0.28 ± 0.11) as well as between growth and dagginess (-0.33 ± 0.13) were statistically significant and favourable. Results of this meta-analysis provide evidence of genetic antagonism between production and health in dairy sheep and goats. This was not observed in meat sheep where most of the pooled estimates had high standard errors and were non-significant. Based on the obtained results, it seems feasible to simultaneously improve efficiency and health in addition to production by including the different types of traits in the breeding goal. However, a better understanding of potential trade-offs between these traits would be beneficial. Particularly, more studies focused on reproduction and resilience traits linked to the animal's multi-trait response to challenges are required.

Converting multi-trait breeding objectives into operative selection indexes to ensure genetic gains in low-input sheep and goat breeding programmes

Small ruminant breeding programmes in low-input production systems are best organised at the community level. Participant farmers have to agree on goal traits and their relative importance. When BLUP breeding values of goal traits are not available in time, appropriate selection indexes can be used to aid visual selection. Taking Ethiopian Abergelle goat and Bonga sheep community-based breeding programmes (CBBPs) as an example, breeding objective functions were defined and selection indexes were constructed and evaluated. Breeding goals for Abergelle goats included early sale weight, survival and milk production. Breeding goals for Bonga included the number of offspring born, sale weight and survival. Economic weights of objective traits can be used in several ways depending on measured traits and the reliability of their genetic parameters. Selection indexes included combinations of objective traits measured on candidates and their dams and situations when Abergelle communities prefer to restrict genetic changes in number of offspring born or adult weight and when Bonga communities prefer to restrict changes in adult weight. Genetic and economic gains were evaluated as well as sensitivity to feed cost assumptions and to repeated dam records. After independent culling on preponderant traits such as coat colour and horn/tail type, sires in Abergelle goat community breeding programmes should be selected on indexes including at least own early live weight and their dams average milk production records. Sires for Bonga sheep programmes should be selected on own early live weight and desirably also on their dam's number of offspring born. Sensitivity to feed cost assumptions was negligible but repeated measurements of dam records improved index accuracies considerably. Restricting genetic changes in number of offspring born or adult weight is not recommended.

Selection Criteria for Improving Fertility in Spanish Goat Breeds: Estimation of Genetic Parameters and Designing Selection Indices for Optimal Genetic Responses

The aim of this study was to estimate genetic parameters for several female fertility criteria and to choose the most suitable selection index in Spanish Florida and Payoya goat breeds. In this study, we analyzed as fertility traits, the age at first kidding (AgFiKid), and the interval between the first and second kiddings (Int12Kid), between the second, third, and remaining kiddings (Int3toKid), and between all kiddings (IntAllKid) in 51,123 and 22,049 Florida and Payoya females, respectively. Genetic parameters were estimated by fitting animal models using restricted maximum likelihood (REML) methodology. We proposed six selection indices to compare the genetic responses for all traits included, based on a new selection index theory. The heritability and repeatability estimates of the traits were low, as expected. The genetic correlations among fertility traits covered a wide range of values from 0.07 (AgFiKid-Int12Kid) to 0.71 (Int3toKid-IntAllKid) in Florida and from -0.02 (AgFiKid-Int12Kid) to 0.82 (Int3toKid-IntAllKid) in Payoya. Overall, the results of this study indicate that IntAllKid gives the highest genetic responses in both breeds but is expressed late in a female's life. However, AgFiKid and Int12Kid could be recommended as early selection criteria for female fertility in both breeds.

Estimation of additive and non-additive genetic variance component for growth traits in Adani goats

Non-additive genetic effects are important to increase the accuracy of estimating genetic parameters for growth traits. The aim of this study was to estimate genetic parameters and variance components, specially dominance and epistasis genetic effects, for growth traits (birth weight (BW), weaning weight (WW), 3 (W3), 6 (W6), 9 (W9), and 12 (W12) month weight) in Adani goats. Analyses were carried out using Bayesian method via Gibbs sampler animal model by fitting of 18 different models. All fixed effects (sex, type of birth, age of dam, and year) showed significant effects on BW, WW, W3, and W6, whereas the type of birth and age of dam were not significant on W9 and W12. With the best model, direct heritability estimates were 0.347, 0.178, 0.158, 0.359, 0.278, and 0.281 for BW, WW, W3, W6, W9, and W12 traits, respectively. Maternal permanent environmental effect was significant for BW and WW, but maternal genetic effect was significant only for W3. Dominance and epitasis effects were significant almost for all traits and as a proportion of phenotypic variance were ranged from 0.115 to 0.258 and 0.107 to 0.218, respectively. The range of accuracy of breeding values estimated for growth traits with appropriate evaluation models was from 0.521 to 0.652, 0.616 to 0.694, and 0.548 to 0.684 for the all animals, 10% of the best males and 50% of the best females, respectively. When dominance and epistasis effects added to models, the error variance was reduced and the accuracy of estimated breeding values increased. The accuracy of the best model showed a significant difference with the accuracy of other models (p < 0.01). The result of the present study suggests that non-additive genetic effects should be in genetic evaluation models for goat growth traits because of its effect on accuracy of estimated breeding values.