Genetic and phenotypic parameters of milk yield, milk composition and age at first kidding in Saanen goats from Mexico

Assessing genetic parameters for first parity reproductive traits for early selection in Saanen × Beetal goats of India

The present study aimed to evaluate the genetic parameters of first parity reproductive traits. Information on 762 reproductive records on Saanen × Beetal (S × B) goats reared for approximately five decades was collected from ICAR-National Dairy Research Institute, Karnal, Haryana (1973-2020). For genetic analysis, single-trait and multiple-trait animal models were used. Gibbs sampler for animal model (GSAM) approach was used for estimating (co)variance components of reproductive traits. Six different single-trait animal models (with or without maternal and environmental effects) were used and the deviance information criterion (DIC) determined the best model. The least squares mean for age at first service (AFS), age at first kidding (AFK), service period (SP), dry period (DP), gestation length (GL), kidding interval (KI), litter weight (LW), number of kids born (NKB) and number of female kids born (NFKB) in first parity were 526.99 ± 4.86, 662.96 ± 5.03, 219.11 ± 6.25, 109.38 ± 6.00, 150.48 ± 0.27, 356.63 ± 4.80 days, 3.87 ± 0.05 kg, 1.27 ± 0.02 and 0.67 ± 0.03, respectively. Lower heritability estimates for these reproductive traits revealed a sparse scope for genetic improvement. Multivariate analysis using Model 1 was carried out to evaluate the genetic and phenotypic correlation of these nine reproductive traits. The genetic correlation of DP and SP was negatively with LW, NKB and NFKB, which is favourable as reduction in SP and DP can improve these economically important traits through indirect selection. Consistent efforts towards genetic improvement of these goat flock poses a promising future for meat industry owing to high prolificacy and good reproductive potential in this flock.

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.

Estimation of genetic parameters and genetic change of first parity reproductive traits in Alpine × Beetal goats

The study of reproductive traits is crucial for improving genetic potential of goats because of their significant utility in meat production. Hence, genetic analysis was conducted for reproductive traits on Alpine × Beetal goats using animal model for first parity data. Information on 1462 reproductive records were collected over five decades from ICAR-National Dairy Research Institute, Karnal, Haryana (1971-2021). Single-trait and multi-trait animal models were used for genetic analysis. Estimates of (co)variance components and genetic parameters were obtained using Gibbs Sampler for Animal Model due to non-normal distribution of data. Six single-trait animal models (including or excluding maternal and environmental effects) were fitted and best models were determined based on Deviance Convergence Criterion values. The prolificacy for the A × B goats for first parity data was 32%, having 68% single births, 31% twins and 1% triplets/quadruplets. The least squares mean for age at first service (AFS), age at first kidding (AFK), service period (SP), dry period (DP), gestation length (GL), kidding interval (KI), litter weight (LW), number of kids born (NKB) and number of females kids born (NFKB) in first parity were 546.15 ± 4.10 days, 679.05 ± 4.07 days, 226.51 ± 4.02 days, 67.96 ± 2.76 days, 150.74 ± 0.13 days, 362.53 ± 3.35 days, 3.99 ± 0.04 kg, 1.32 ± 0.02 and 0.64 ± 0.02, respectively. The heritability estimates obtained from best model for AFS, AFK, GL, KI, SP, and DP were 0.12 ± 0.00, 0.10 ± 0.00, 0.09 ± 0.01, 0.03 ± 0.00, 0.04 ± 0.00, and 0.05 ± 0.00, respectively. For NKB, NFKB and LW, heritability estimates were 0.16 ± 0.01, 0.03 ± 0.03, and 0.04 ± 0.00, respectively. These results imply lower heritability estimates for reproductive traits, and hence meagre scope for selection for further improvement. Maternal effects contributed significantly for traits such as GL, NKB and NFKB. Genetic correlation for number of female kids born was negative with SP and DP which is favourable. Furthermore, genetic correlation was negative for dry period and litter weight which is favourable as number of kids born and litter weight are traits of direct economic importance. Results reveal high genetic potential of this breed for meat industry owing to high prolificacy, provided consistent efforts are made for the genetic improvement of this germplasm.

Dairy goats' management and performance under smallholder farming systems in Eastern Africa: the systematic review and meta-analysis

The systematic review and meta-analysis study was conducted to describe dairy goat management practices among smallholder farmers in Kenya and Tanzania. The study also evaluated the effects of breed and upgrade level (50%, 75% and > 75%) on growth and lactation performances. Google Scholar was used to search for dairy goats' studies followed by an eligibility check. Eligible studies were assessed for risk of bias using RoB 2.0 (Cochrane risk-of-bias in randomised trial) and ROBINS-I (Risk of Bias Assessment in Non-Randomised Studies of Interventions). Smallholder farmers were mainly stall-feeding natural pasture and crop residues to goats with supplementation limited by the high costs of concentrate feeds. Forage cultivation and conservation were limited by the scarcity of land and improved forage planting materials, low technical know-how and high labour demand. Similarly, farmers had limited access to formal market, veterinary and extension services. Prevalence of infectious diseases, antibiotic resistance and pre-weaning kid mortality were high. Nevertheless, there were breed effects (p < 0.05) on pre-weaning growth and weaning weight but not lactation parameters. However, Saanen goats had relatively higher lactation length (252 days) and yield (637 l) than other goat breeds. Daily milk and lactation yields, pre-weaning growth and growth rate (post-weaning) varied significantly among upgrade levels (p < 0.05) and were highest in > 75% level. It was concluded that Saanen goats and > 75% were the best breed and upgrade level for goat milk production in smallholder farms due to high lactation performance. Improving the different managerial aspects of smallholder dairy goat farming is of paramount importance if the dairy goats' performance, farm income, food safety and security are to be improved in Eastern Africa.

Methionine Supplementation during Pregnancy of Goats Improves Kids' Birth Weight, Body Mass Index, and Postnatal Growth Pattern

The last third of gestation is a period of high energy and protein demand for the dam to support fetal growth and the following onset of lactation. Methionine is an essential amino acid that contributes to protein formation, fetal development, and milk synthesis; thus, is likely to have positive effects on the weight and size of the newborn and, afterward, milk yield and milk composition, which may improve growth patterns of the progeny. To test these hypotheses, we used 60 pregnant multiparous Alpine goats with similar live weights and gestational ages (~Day 100 of pregnancy; Mean ± SD; 1410 ± 14 days old and 50.4 ± 6.6 kg) and were separated into two groups: control and supplemented with the delivery. Treatments were T-MET (n = 30; received 1% herbal methionine Optimethione® dry matter based on from Day 100 of the pregnancy to delivery) or T-CTL (n = 30; served as the control and did not receive methionine). The methionine powder provided individual supplementation and was adjusted every week as the live weight and dry matter intake changed. At birth, the weight, body mass index (BMI), birth type, and sex of the kids were determined. Subsequently, the progeny was weighed weekly up to weaning. Two weeks after parturition, the milk composition was recorded weekly, and the milk yield was recorded monthly. The maternal live weight at the start (Mean ± SEM; T-CTL: 50.5 ± 1.1 vs. T-MET: 50.3 ± 1.3 kg) and end (T-CTL: 54.2 ± 1.3 vs. T-MET: 52.8 ± 1.4 kg) of the experiment did not differ statistically among treatments (p > 0.05); however, daily live weight changes tended to differ between groups (T-CTL: 73 ± 10 vs. T-MET: 51 ± 7 g day−1; p = 0.06). The birth weight (T-CTL: 3.1 ± 0.1 vs. T-MET: 3.5 ± 0.1 kg; p < 0.001), daily live weight change (T-CTL: 121 ± 6 vs. T-MET: 141 ± 6 g day−1; p < 0.01), and weaning weight (T-CTL: 8.3 ± 0.2 vs. T-MET: 9.3 ± 0.3 kg; p < 0.01) differed between treatments. The BMI at birth (T-CTL: 0.28 ± 0.01 vs. T-MET: 0.3 ± 0.01 units kg m−2; p < 0.01) and at weaning (T-CTL: 0.85 ± 0.1 kg vs. T-MET: 1.00 ± 0.06 units kg m−2; p < 0.05) differed between treatments. Milk components (protein, fat, lactose, and solids non-fat) and milk yield were similar between treatments (p > 0.05). It is concluded that the inclusion of methionine in the maternal goat diet during the last third of gestation increases the birth and growth variables of the progeny but without significant influence on the milk yield and composition.

Effect of Non-Genetic Factors on Reproduction of Extensive versus Intensive Florida Dairy Goats

The main objective of this study was to evaluate the effect of the production system and other environmental/phenotype factors on age at first kidding (AFK), kidding interval (KI) and prolificacy of 19,772 Florida goats reared between 2000 and 2019 on 49 dairy farms (38 farms intensively managed and 11 extensively managed with grazing). AFK was lower on intensive (490.2 ± 0.9 days; n = 13,345) than on extensive farms (511.7 ± 2.5 days; n = 2357; p < 0.001), and highest during the spring season (533.9 ± 2.7 days; n = 1932; p < 0.001) in both production systems. The average KI was 355.7 ± 0.4 days, mainly varying according to dry period, kidding season and lactation number and kidding type (p < 0.01). A significant interaction between production system, kidding season and dry period was observed with the highest AFK on intensive farms during spring and summer for goats presenting a dry period of up to six months. The overall prolificacy (1.64 ± 0.01) increased in recent years in both systems, and it was affected by the production system, but with different patterns; so, the highest prolificacy of primiparous and multiparous goats was observed on extensive and intensive farms, respectively. Besides that, the prolificacy and other reproductive parameters, such as AFK, significantly increased in the last decade, which could be related to management improvements. Besides that, the existence of inter-annual variations should be considered to compare data between farms and years, and to establish the farms’ objectives according to their production systems and production goals.

Milk production and quality patterns of double-purpose goats grazing in arid rangelands

Lactation curves are a valuable tool for improving flock production efficiency, adjusting flock sizes, and improving farmers' income in grazing-based livestock production. Therefore, we used natural cubic splines to estimate (a) a general flock production pattern throughout a year, (b) an average lactation curve, and (c) patterns of milk chemical components in dual-purpose goats grazing in arid plant communities in the Sierra de San Francisco, Baja California Peninsula, during years of abundant precipitation. Also, milk chemical composition was compared between flocks. Annual flock milk production showed a wiggly pattern with two greater waves in summer and spring. The average individual lactation curve (kg/doe/day) and production curves of fat, protein, lactose, and ashes (g/doe/day) showed a decreasing and wiggly pattern across 35-week lactation; the greatest average daily production was in week 2. Milk, protein, lactose, and ash production curves had similar persistency values that were greater than those of the fat production curve. Milk production had a high-positive correlation with fat production and very high-positive correlations with protein, lactose, and ash production. Density (g/ml) and fat, protein, lactose, and ash contents (%) showed a ditch-shaped pattern across lactation, with greater values at the end. Goat flocks grazing across plant communities produced different quality milk. Thus, native plant communities are a valuable resource that favors a great fat content and moderate protein content in local goat milk. Also, breeding programs must pay attention that an increment in individual milk production could decrease fat and protein production, which are valuable for cheesemaking.

Estimation of genetic parameters for early reproduction traits in Beetal goat

The evaluation of early reproduction traits in Beetal goat was performed for possible effects of genetic and non-genetic factors on litter size at birth (LSB), litter size at weaning (LSW), litter weight at birth (LWB), litter weight at weaning (LWW) and age at first kidding (AFK). The data records consisted of information of pedigree and targeted traits pertained to 223 does born to 25 sires and 122 dams between the years 2004 to 2019. A general linear model was used for assessment of non-genetic factors such as period of birth, type of birth and dam's weight at kidding on studied traits. Genetic evaluation of targeted traits was done to estimate variance components and genetic parameters under dyadic mixed modelling. The estimates of least-square means for LSB, LSW, LWB, LWW and AFK were observed as 1.27 ± 0.03, 1.25 ± 0.03, 3.24 ± 0.07 kg, 13.08 ± 0.30 kg and 27.56 ± 0.58 months, respectively. Only the period of birth showed significant (P < 0.05) effects for targeted traits in this study. The estimates of direct heritability for LSB, LSW, LWB, LWW and AFK were low in magnitude as 0.08, 0.03, 0.10, 0.03 and 0.06, respectively. The moderate to high genetic and phenotypic correlations among litter traits indicate simultaneous improvement for these traits. It was concluded that low ranged direct heritability estimates for targeted traits indicated modest scope for genetic improvement of reproductive efficiency in Beetal goat through selection and, therefore, adoption of improved managerial practices is necessary to improve reproductive efficiency of Beetal goat.

Genetic analysis of lifetime productivity traits in goats

As part of the development of a breeding programme for dairy goats to support sustainable production in organic farming, the overall aim of the present study was to identify traits that can be used as selection criteria for lifetime productivity. The breeding goal is high lifetime productivity with a good milk composition and a good level of robustness in the animals, especially within grazing systems. The lifetime productivity traits analysed in this study were the length of the animal's productive life (LPL), the lifetime efficiency (LEF), and the animal's milk yield efficiency with respect the total number of lactating days (EDM); the average fat and protein content over the animal's lifetime, the fat-to-protein ratio (FPR), and the urea content (UC) were also included as indirect health traits and potential indicators of robustness in dairy goats. The traits' influencing factors, phenotypic and genetic correlations, and heritability were examined. Furthermore, factors influencing milk yield in the first 120 d of lactation during the animal's first lactation were analysed. The aim of investigating milk yield during the first lactation was to consider a connection between early performance recoding in the life of an animal and LPL, LEF, and EDM. In total, lactation and pedigree data from 9192 dairy goats of the common German Fawn (GF) and German White (GW) dairy breeds were used. Prerequisites were that the investigated birth cohorts had to have definitively completed their lifetime production, and a high proportion of goats had to have completed extended lactation. The data analysis showed that breed did not influence milk yield. The age at first kidding, the average number of kids born during the animal's lifetime, and the lactation length did influence the milk yield. This applies to the milk yield during the first 120 d of the first lactation as well as over the lifetime of an animal. Considering the influencing factors, the results showed that LPL was genetically and positively correlated with LEF and EDM ( r g = 0.65 ± 0.06 and 0.29 ± 0.07 respectively). The heritability of LPL, LEF, and EDM was 0.22 ± 0.02 , 0.29 ± 0.03 , and 0.44 ± 0.03 respectively. Regarding the lifetime milk composition, the heritability of protein and fat content, FPR, and UC was 0.63 ± 0.02 , 0.52 ± 0.02 , 0.32 ± 0.03 , and 0.47 ± 0.04 respectively. The heritability regarding the milk yield during the first 120 d of the first lactation was 0.34 ± 0.03 . We found that the milk yield during the first 120 d of the first lactation showed a genetic correlation with LPL, LEF, and EDM of 0.30 ± 0.08 , 0.82 ± 0.04 , and 0.89 ± 0.03 respectively. In summary, LPL, LEF, and EDM are suitable traits to indicate lifetime productivity in dairy goats. An additional indicator for lifetime productivity could be the milk yield during the first 120 d of the first lactation. Moreover, FPR and UC appear to be promising indicator traits for the health and robustness of dairy goats. The present study showed the importance of considering extended lactation in selective breeding programmes as well as the importance of modelling extended lactation in the breeding value estimation.

Genetic parameters for somatic cell score, milk yield and type traits in Nigerian Dwarf goats

Objective

This study was conducted to estimate multi-trait genetic parameters for somatic cell score (SCS), milk yield and type traits in Nigerian Dwarf (ND) goats from the United States.

Methods

Data from 1,041 ND goats in the United States with kiddings in 95 herds were used to estimate multi-trait genetic parameters for SCS, milk (MILK), fat (FAT), and protein (PROT) yields, and 14 type traits. An 18-trait mixed linear animal model for lactation mean SCS (Log₂), MILK, FAT, PROT, and 14 type traits was applied. A factor analytic approach (FA1) in ASReml software was used to obtain convergence.

Results

Averages for SCS were low (2.85±1.29 Log₂), and were 314±110.6, 20.9±7.4, and 14±4.9 kg, respectively, for MILK, FAT, and PROT. Heritabilities for SCS, MILK, FAT, and PROT were 0.32, 0.16, 0.16, and 0.10, respectively. The highest heritabilities for type traits were for stature (0.72), teat diameter (0.49), and rump width (0.48), and the lowest estimates were for dairyness (0.003) and medial suspensory ligament (0.03). Genetic correlations of SCS with MILK, FAT, and PROT were positive but low (0.25, 0.18, and 0.23, respectively). Genetic and phenotypic correlations between MILK, FAT, and PROT were high and positive (≥0.66). Absolute values of genetic correlations involving SCS with type traits were generally low or no different from zero. Most of the phenotypic correlations involving SCS with type traits were low. No serious unfavorable genetic correlations between milk yield traits and SCS or between milk yield traits or SCS and type traits were found.

Conclusion

Genetic variation exists in the ND breed for most studied traits. The development of selection programs based on these estimates may help accelerate favorable multi-trait genetic changes in this breed.

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.

Integrating Casein Complex SNPs Additive, Dominance and Epistatic Effects on Genetic Parameters and Breeding Values Estimation for Murciano-Granadina Goat Milk Yield and Components

Assessing dominance and additive effects of casein complex single-nucleotide polymorphisms (SNPs) (αS1, αS2, β, and κ casein), and their epistatic relationships may maximize our knowledge on the genetic regulation of profitable traits. Contextually, new genomic selection perspectives may translate this higher efficiency into higher accuracies for milk yield and components' genetic parameters and breeding values. A total of 2594 lactation records were collected from 159 Murciano-Granadina goats (2005-2018), genotyped for 48 casein loci-located SNPs. Bonferroni-corrected nonparametric tests, categorical principal component analysis (CATPCA), and nonlinear canonical correlations were performed to quantify additive, dominance, and interSNP epistatic effects and evaluate the outcomes of their inclusion in quantitative and qualitative milk production traits' genetic models (yield, protein, fat, solids, and lactose contents and somatic cells count). Milk yield, lactose, and somatic cell count heritabilities increased considerably when the model including genetic effects was considered (0.46, 0.30, 0.43, respectively). Components standard prediction errors decreased, and accuracies and reliabilities increased when genetic effects were considered. Conclusively, including genetic effects and relationships among these heritable biomarkers may improve model efficiency, genetic parameters, and breeding values for milk yield and composition, optimizing selection practices profitability for components whose technological application may be especially relevant for the cheese-making dairy sector.

Genetic correlations and trends for traits of economic importance in dairy buffalo

Context The planning and execution of selection programs requires estimates of the genetic correlations between traits. As genetic change is achieved for a given trait, it is important to consider possible genetic changes for other traits. Understanding the magnitude and direction of genetic correlations can assist in selection decisions. Aims The aim of the present study was to estimate the genetic correlations of reproductive traits with productive traits and with percentages of fat and protein in the milk of dairy buffalo. Additionally, genetic trends were estimated for the traits under study over the years. Methods Data from 11530 complete lactations of 3431 female buffalo were used. The following traits were analysed: milk, fat and protein yields; percentages of fat and protein; age at first calving; and calving interval. The (co)variance components were estimated by Bayesian inference in multi-trait analyses, considering a linear animal model. To calculate the genetic trends, the average annual genetic values were regressed on the year of birth. Key results The means of genetic correlations estimated between reproductive (age at first calving and calving interval) and productive (milk, fat and protein yields) traits were positive, but of moderate to low magnitude. The association between the reproductive and milk quality (fat and protein percentages) traits were negative and of low magnitude. Genetic trends for the productive traits were positive (5.25 ± 0.63, 0.15 ± 0.034 and 0.09 ± 0.038 kg/year for milk, fat and protein yields respectively). Genetic trends for the reproductive traits of age at first calving and calving interval increased by 0.47 ± 0.09 and 0.48 ± 0.10 days/year respectively. In terms of milk quality, however, the percentages of fat and protein decreased by 0.016 ± 0.003 and 0.011 ± 0.001%/year respectively. Conclusions Genetic gains in productive traits may elevate the number of days at first calving and extend the calving interval, in addition to leading to the production of milk of lower quality. Implications The use of a multi-trait selection index is an alternative, as it combines information from different sources, such that an optimal selection criterion can be achieved over time by virtue of its emphasis on appropriate weighting for all traits.

Genetic parameters for total lactation yields of milk, fat, protein, and somatic cell score in New Zealand dairy goats

The aim of this study was to estimate genetic parameters for lactation yields of milk (MY), fat (FY), protein (PY), and somatic cell score (SCS) of New Zealand dairy goats. The analysis used 64,604 lactation records from 23,583 does, kidding between 2004 and 2017, distributed in 21 flocks and representing 915 bucks. Estimates of genetic and residual (co) variances, heritabilities, and repeatabilities were obtained using a multiple-trait repeatability animal model. The model included the fixed effects of contemporary group (does kidding in the same flock and year), age of the doe (in years), and as covariates, kidding day, proportion of Alpine, Nubian, Toggenburg, and "unknown" breeds (Saanen was used as the base breed), and heterosis. Random effects included additive animal genetic and doe permanent environmental effects. Estimates of heritabilities were 0.25 for MY, 0.24 for FY, 0.24 for PY, and 0.21 for SCS. The phenotypic correlations between MY, FY, and PY ranged from 0.90 to 0.96, and the genetic correlations ranged from 0.81 to 0.93. These results indicate lactation yield traits exhibit useful heritable variation and that multiple trait selection for these traits could improve milk revenue produced from successive generations of New Zealand dairy goats.

Linking genetic merit to sparse behavioral data: behavior and genetic effects on lamb growth in Soay sheep

Wild quantitative genetic studies have focused on a subset of traits (largely morphological and life history), with others, such as behaviors, receiving much less attention. This is because it is challenging to obtain sufficient data, particularly for behaviors involving interactions between individuals. Here, we explore an indirect approach for pilot investigations of the role of genetic differences in generating variation in parental care. Variation in parental genetic effects for offspring performance is expected to arise from among-parent genetic variation in parental care. Therefore, we used the animal model to predict maternal breeding values for lamb growth and used these predictions to select females for field observation, where maternal and lamb behaviors were recorded. Higher predicted maternal breeding value for lamb growth was associated with greater suckling success, but not with any other measures of suckling behavior. Though our work cannot explicitly estimate the genetic basis of the specific traits involved, it does provide a strategy for hypothesis generation and refinement that we hope could be used to justify data collection costs needed for confirmatory studies. Here, results suggest that behavioral genetic variation is involved in generating maternal genetic effects on lamb growth in Soay sheep. Though important caveats and cautions apply, our approach may extend the ability to initiate more genetic investigations of difficult-to-study behaviors and social interactions in natural populations.

Does the Acknowledgement of αS1-Casein Genotype Affect the Estimation of Genetic Parameters and Prediction of Breeding Values for Milk Yield and Composition Quality-Related Traits in Murciano-Granadina?

Simple Summary

Genetic evaluations and the selection of breeding animals require the accurate estimation of genetic parameters for economically important traits. As a result, dairy livestock has evolved in response to the needs of producers and consumers. Genetic selection in goats has been mostly based on quantitative traits such as milk yield, fat, protein, and dry matter. However, as reported by the increased heritability values of these parameters after the inclusion of the different allelic variants of αS1 casein in evaluation models, the selection of animals carrying this gene could result in a more efficient genetic selection. High levels of genetic polymorphism (89.58% of polymorphic SNP—as only five out of the 48 SNPs assessed were monomorphic) that are related to greater production of coagulable proteins in milk, a fact that could be associated with a higher yield and improved curd firmness properties.

Abstract

A total of 2090 lactation records for 710 Murciano-Granadina goats were collected during the years 2005–2016 and analyzed to investigate the influence of the αS1-CN genotype on milk yield and components (protein, fat, and dry matter). Goats were genetically evaluated, including and excluding the αS1-CN genotype, in order to assess its repercussion on the efficiency of breeding models. Despite no significant differences being found for milk yield, fat and dry matter heritabilities, protein production heritability considerably increased after aS1-CN genotype was included in the breeding model (+0.23). Standard errors suggest that the consideration of genotype may improve the model’s efficiency, translating into more accurate genetic parameters and breeding values (PBV). Genetic correlations ranged from −0.15 to −0.01 between protein/dry matter and milk yield/protein and fat content, while phenotypic correlations were −0.02 for milk/protein and −0.01 for milk/fat or protein content. For males, the broadest range for reliability (R_AP) (0.45–0.71) was similar to that of females (0.37–0.86) when the genotype was included. PBV ranges broadened while the maximum remained similar (0.61–0.77) for males and females (0.62–0.81) when the genotype was excluded, respectively. Including the αS1-CN genotype can increase production efficiency, milk profitability, milk yield, fat, protein and dry matter contents in Murciano-Granadina dairy breeding programs.

Genetic and phenotypic aspects of early reproductive performance in Raeini Cashmere goats

This study used pedigree information and data collected from 1979 to 2012 at the Raeini Cashmere goat breeding station, located in Baft City in Kerman Province in southeastern Iran. Genetic and phenotypic parameters for early reproductive traits of breeding does, including total numbers of kids born at first kidding (LSB1), total numbers of kids weaned at first kidding (LSW1), total birth weight of all kids born at first kidding (LWB1), total weaning weight of all kids weaned at first kidding (LWW1), and age at first kidding (AFK), were estimated using a Bayesian approach via Gibbs sampling. Posterior means for heritability estimates of LSB1, LSW1, LWB1, LWW1, and AFK were statistically significant, with values of 0.12, 0.23, 0.17, 0.15, and 0.46, respectively. Low-to-moderate additive genetic variation was present for the studied reproductive traits. Estimated genetic correlations among LSB1, LSW1, LWB1, and LWW1 were statistically significant and ranged from 0.12 between LWB1 and LWW1 to 0.72 between LSB1 and LSW1. Corresponding phenotypic correlation estimates were also statistically significant and ranged from 0.04 between LWB1 and LWW1 to 0.55 between LSB1 and LSW1. Posterior means of genetic and phenotypic correlations between AFK and other studied traits were statistically significant only for LSB1 and LWB1. For LSB1, LSW1, LWB1, and LWW1, we conclude that genetic and phenotypic improvement in any of these traits in Raeini Cashmere does would favorably influence all of the other traits. However, does that first kidded at younger ages have smaller litters at birth and lower litter birth weights at their first parity.

Pseudopregnancy and aseasonal breeding in dairy goats: genetic basis of fertility and impact on lifetime productivity

Until recently, the main selection focus in UK dairy goats has been on milk yield. To develop a selection index suitably weighted for a variety of traits, it is important to understand the genetic relationships between production, health and fertility traits. This study focussed on three aspects of reproduction that are of interest to goat breeders. (1) Out of season (OOS) kidding ability: goats are highly seasonal breeders so achieving consistent, year-round dairy production presents a challenge. It may be possible to select for extended or shifted breeding cycles, however, there are no published studies on the genetic basis of seasonal kidding ability, and a genetic correlation with milk production in dairy goats; (2) age at first kidding (AFK): a reduced AFK offers the opportunity for more rapid genetic improvement, as well as reducing the amount of time and resources required to raise the animals to producing age; (3) pseudopregnancy (PPG): as it is difficult to diagnose pregnancy within 30 days of mating, high herd levels of PPG could add a significant delay in breeding replacement animals, or commencing a new lactation. Using records from 9546 goats, the objective of this study was to investigate the genetic relationships between the reproductive traits described above, and the production traits 520-day milk yield (MY520), lifetime milk yield (MYLife) and lifetime number of days in milk (DIMLife). The 'out of season' phenotype was defined as week of kidding relative to the 4 weeks of the year where the highest average number of births occur. Incidences of PPG that occurred during the first lactation were used as cases, while goats with none were assigned as controls. Relevant fixed and random effects were fitted in the models. In line with other reproduction traits, heritability estimates were low ranging from 0.08 to 0.11. A negative genetic correlation was found between AFK and MY520 (-0.22±0.10), whereas a positive genetic correlation was found between PPG and DIMLife (0.58±0.11). Pseudopregnancy and OOS were positively genetically correlated (0.36±0.15). All other genetic correlations were very low. The results of this study indicate that selection for the reproductive traits analysed is feasible, without adversely affecting MYLife.

Estimation of genetic parameters and genetic trends for milk yield traits in Jamunapari goats in semiarid tropics

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The heritability for milk yield traits were moderate to high.

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The repeatability estimates were moderate to high for milk yield traits.

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The genetic trends for milk yield traits were positive.

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Phenotypic trends for MY90, MY140 and TMY were positive.

The Jamunapari goats are reared as dairy animals in semi-arid conditions, therefore it is necessary to evaluate the genetic potential for the genetic improvement of milk production traits. The data comprised of 2217 phenotypic records for milk yield at 90 days (MY90) and 140 days (MY140), total milk yield (TMY) and lactation length (LL) obtained from the progeny of 173 sires and 446 dams during the period 1990–2013. The data were analysed using mixed linear models exploring random effects due to direct additive, maternal and permanent environment variance due to animal. The most appropriate genetic models for milk yield traits were those that included permanent environment effects due to the animal. The direct additive heritability estimates were 0.15 ± 0.05, 0.26 ± 0.07, 0.25 ± 0.08 for MY90, MY140 and TMY, respectively. The additive heritability estimate for LL was low and non-significant at 0.02 ± 0.03. The repeatability estimates were moderate to high ranging from 0.68 to 0.73 for milk yield traits. The repeatability for lactation length was 0.20 ± 0.03. Maternal variances were low ranging from 0.03 for MY90 to 0.13 for TMY. There was an increase in mean milk yield of 0.25, 0.70 and 0.72 kg/year respectively at 90 and 140 days, and for TMY. Genetic trends and phenotypic trends for MY90, MY140 and TMY were positive and indicated significant improvement in milk traits due to selective breeding.

Estimation of genetic parameters for productive life, reproduction, and milk-production traits in US dairy goats

Heritabilities and correlations for milk yield (MY), fat yield (FY), protein yield (PY), combined fat and protein yield (FPY), fat percentage (F%), protein percentage (P%), age at first kidding (AFK), interval between the first and second kidding (KI), and real and functional productive life at 72mo (FPL72) of 33,725 US dairy goats, were estimated using animal models. Productive life was defined as the total days in production until 72mo of age (PL72) for goats having the opportunity to express the trait. Functional productive life was obtained by correcting PL72 for MY, FY, PY, and final type score (FS). Six selection indexes were used, including or excluding PL72, with 6 groups of different economic weights, to estimate the responses to selection considering MY, FY, PY, and PL72 as selection criteria. The main criteria that determined the culling of a goat from the herd were low FS, MY, and FY per lactation. Heritability estimates were 0.22, 0.17, 0.37, 0.37, 0.38, 0.39, 0.54, 0.64, 0.09, and 0.16 for PL72, FPL72, MY, FY, PY, FPY, F%, P%, KI, and AFK, respectively. Most genetic correlations between the evaluated traits and PL72 or FPL72 were positive, except for F% (-0.04 and -0.06, respectively), P% (-0.002 and -0.03, respectively), and AFK (-0.03 and -0.01, respectively). The highest genetic correlations were between FPL72 and MY (0.39) and between PL72 and MY (0.33). Most phenotypic correlations between the traits evaluated and FPL72 and PL72 were positive (>0.23 and >0.26, respectively), except for F% (-0.004 and -0.02, respectively), P% (-0.05 and -0.02), KI (-0.01 and -0.07), and AFK (-0.08 and -0.08). The direct selection for PL72 increased it by 102.28d per generation. The use of MY, FY, PY, KI, or AFK as selection criteria increased PL72 by 39.21, 27.33, 35.90, -8.28, or 2.77d per generation, respectively. The inclusion of PL72 as selection criterion increased the expected response per generation from 0.15 to 17.35% in all selection indices studied.

Additive and dominance effects of the α(s1)-casein locus on milk yield and composition traits in dairy goats

The objective of this study was to evaluate the effects of the CSN1S1 locus polymorphism on 305-d records of milk, fat, protein, lactose and total solids yields, fat, protein, lactose and total solids contents in Mexican dairy goats. A total of 514 lactation records belonging to Alpine (n=60), Saanen (n=105) and Toggenburg (n=74) goats, born from 2003 to 2006 in three herds were used. Discrimination between alleles E, F, N, A* (CSN1S1 A, G, H, I, O1 and O2) and B* (CSN1S1 B1, B2, B3, B4, C and L) were made by amplification of fragments of the gene CSN1S1 and digestion with the restriction endonuclease XmnI. In order to estimate additive and dominance effects, data sets including (1) all genotypes, and (2) only homozygote genotypes, were analysed using linear mixed models. The allele A*, had significant additive effects for protein content (0·21±0·07%; P=0·002) and total solids content (0·66±0·23%; P=0·005) when compared with allele F. An unfavourable additive effect of allele A* on milk yield was found in the Alpine breed (-81·4±40·2; P=0·046) when compared with allele F. Favourable dominance effects were found for some genotypes (P<0·05) for milk yield (A*N and B*N), fat yield (A*N and B*E), protein yield (A*N and B*E), lactose yield (A*N) and total solids yield (A*N). Also, unfavourable dominance effects were found (P<0·05) for protein content (A*B* and A*N) and total solids content (A*B*, A*N, and A*F). Allele A* was the only one with a positive effect for protein content. Significant allele-year interaction effects were also observed. The presence of significant dominance effects, estimated between specific pairs of alleles, challenged the purely additive nature of the genetic effect at the CSN1S1 locus. Implications from use of CSN1S1 effects in goat breeding programmes are presented.

Aspectos ambientais e genéticos de características reprodutivas e produtiva em cabras leiteiras utilizando amostragem de Gibbs

Objetivou-se estudar efeitos ambientais e genéticos sobre cabras mestiças, exploradas para a produção leiteira. Foram estimados componentes de covariância e parâmetros genéticos das características: idade ao primeiro parto; intervalo de partos e produção de leite em análise uni e multicaracterística, mediante a estatística Bayesiana sob modelo animal. As análises genéticas foram realizadas com cadeias de 1.000.000 de ciclos. Considerou-se o burn-in dos 100.000 valores iniciais, tomados a cada 300 ciclos, para se obter a distribuição a posteriori com 3.000 amostras. As médias obtidas para idade ao primeiro parto, intervalo de partos e produção de leite foram 581,68 ± 79,44; 322,89 ± 132,02 dias e 226,99 ± 89,72kg de leite, respectivamente. Todos os efeitos incluídos no modelo foram significativos, exceto o tipo de nascimento para o intervalo de partos e produção de leite. As herdabilidades, em análise unicaracterística, foram 0,14; 0,05 e 0,10 para idade ao primeiro parto, intervalo de partos e produção de leite, respectivamente. Na mesma ordem, em análise multicaracterística, as herdabilidades foram de 0,16; 0,06 e 0,11. As estimativas de repetibilidade, para as características intervalo de partos e produção de leite, foram 0,10 e 0,20 respectivamente. As características estudadas mostraram-se fortemente influenciadas pelo ambiente. Os valores da repetibilidade indicam a necessidade de se tomar mais medidas antes da decisão de manter ou descartar o animal. As análises multicaracterísticas levaram a estimativas ligeiramente maiores de herdabilidade.

Breed differences over time and heritability estimates for production and reproduction traits of dairy goats in the United States

To aid in improvement of breeding programs for production and reproduction traits of US dairy goats, breed differences over time were documented and genetic parameters were estimated. Data were from herds with ≥2 breeds (Alpine, LaMancha, Nubian, Oberhasli, Saanen, or Toggenburg), but only purebred data were analyzed. Three kidding periods were examined: 1976 through 1984, 1985 through 1994, and 1995 through 2005. Univariate repeatability mixed models were used to estimate least squares means by kidding period-breed and genetic parameters for milk, fat, and protein yields, combined fat and protein yield, fat and protein percentages, protein:fat ratio, age at first kidding, and kidding interval. Trends across kidding periods were favorable for most yield traits for all breeds but generally unfavorable for reproduction traits. Saanens had the highest milk (1,063 to 1,125 kg) and protein yields (31 to 33 kg). Nubians had the highest fat yields (37 to 40 kg) and lowest milk yields (791 to 851 kg). Oberhaslis had the lowest fat (31 to 33 kg) and protein (23 to 27 kg) yields. Alpines had the largest increase in milk yield (7.4%); Oberhaslis had the largest increase in protein (17.4%) and combined fat and protein (13.2%) yields. Combined fat and protein yield was higher for Nubians, Saanens, and Alpines (65 to 72 kg) than for LaManchas, Toggenburgs, and Oberhaslis (53 to 67 kg). Nubians had the highest fat (4.7 to 4.8%) and protein (3.6 to 3.8%) percentages. Only Nubians increased in fat percentage (2.1%); protein percentage increased most for Toggenburgs (7.4%) and Alpines (7.1%). Protein:fat ratio was highest for Toggenburgs (0.84 to 0.89) and lowest for Nubians (0.76 to 0.81), but Nubians had the largest increase in protein:fat ratio (6.6%). Saanens were oldest at first kidding (509 to 589 d), and Toggenburgs and LaManchas generally were youngest (435 to 545 d); age at first kidding increased most for Alpines (21.8%) and LaManchas (21.6%). Kidding intervals generally were shorter for Oberhaslis, LaManchas, and Nubians (350 to 377 d) than for Toggenburgs, Alpines, and Saanens (373 to 387 d). Kidding interval increased most for Nubians (3.9%) and Saanens (3.8%) and decreased only for Oberhaslis (5.4%). Heritability estimates across breeds were 0.35 for milk and fat yields, 0.37 for protein yield and protein:fat ratio, 0.36 for combined fat and protein yield, 0.52 for fat percentage, 0.54 for protein percentage, 0.23 for age at first kidding, and 0.05 for kidding interval. Genetic selection within breed is feasible for production and reproduction traits of US dairy goats.

Short communication: genetic and environmental relationships between milk yield and kidding interval in dairy goats

First-parity 305-d milk yield and intervals between first and second kiddings from 1975 through 2005 were analyzed to estimate genetic and environmental parameters for United States Alpine, LaMancha, Nubian, Saanen, and Toggenburg dairy goats. The data set included 43,612 does with first-parity milk yield and 25,863 does with first kidding interval. Parameters were estimated by REML using bivariate mixed models within and across breeds. Fixed effects were month and herd-year of kidding within breed and month and breed-herd-year of kidding across breeds. Random effects were animal and residual. The heritability estimate for first-parity milk yield was 0.36+/-0.01 across breeds and ranged from 0.35 to 0.38 within breed; heritability for first kidding interval was 0.05+/-0.01 across breeds and ranged from 0.00 to 0.15 within breed. The estimate of the genetic correlation between first-parity milk yield and first kidding interval was positive (unfavorable) across breeds (0.35+/-0.09). Estimates of environmental correlations within and across breeds were positive (0.16-0.25). The presence of unfavorable genetic relationships between milk yield and kidding interval indicates a need to include reproductive performance as a selection criterion.