Genetic parameters for lactation traits of milking ewes: protein content and composition,fat, somatic cells and individual laboratory cheese yield

The effects of some environmental variation factors and the genetic parameters for total milk traits (fat content, protein content, casein content, serum protein content, lactation mean of individual laboratory cheese yield (LILCY), lactation mean of somatic cell count (LSCC), and milk yield) were estimated from the records of 1 111 Churra ewes. Genetic parameters were estimated by multivariate REML. Heritability for fat content was low (0.10) as is usually found in the Churra breed. Heritabilities for protein content, casein content, serum protein content, LILCY, milk yield and somatic cell count were 0.31, 0.30, 0.22, 0.09, 0.26 and 0.11, respectively. The highest heritability estimates were for protein and casein contents. Casein content is not advisable as an alternative to protein content as a selection criterion for cheese yield improvement; it does not have any compelling advantages and its measurement is costly. Our results for LSCC indicated that efforts should focus on improving the level of management rather than selecting for somatic cells, in the actual conditions of the Churra breed.     

Variations at regulatory regions of the milk protein genes are associated with milk traits and coagulation properties in the Sarda sheep

Regulatory variation at the ovine casein genes could have important effects on the composition and coagulation properties of milk. Herewith, we have partially resequenced the promoters and the 3′‐UTR of the four casein genes in 25 Sarda sheep. Alignment of these sequences allowed us to identify a total of 29 SNPs. This level of polymorphism (one SNP every 250 bp) is remarkably high if compared with SNP densities estimated in human genic regions (approximately one SNP per bp). The 29 SNPs identified in our resequencing experiment, plus three previously reported SNPs mapping to the lactalbumin, alpha (LALBA) and β‐lactoglobulin (BLG, also known as progestagen‐associated endometrial protein, PAEP) genes, were genotyped with a multiplex TaqMan Open Array Real‐Time PCR assay in 760 Sarda sheep with records for milk composition and coagulation properties. Association analysis revealed the existence of significant associations of CSN1S2 and CSN3 genotypes with milk protein and casein contents. Moreover, genotypes at CSN1S1 were significantly associated with rennet coagulation time, curd firming time and curd firmness, whereas CSN2 was associated with curd firming time. These results suggest that SNPs mapping to the promoters and 3′‐UTRs of ovine casein genes may exert regulatory effects on gene expression and that they could be used for improving sheep milk quality and technological traits at the population level through marker assisted selection.     

Effects of ewes grazing sulla or ryegrass pasture for different daily durations on forage intake,milk production and fatty acid composition of cheese

Sulla (Sulla coronarium L.) forage is valued for its positive impact on ruminant production, in part due to its moderate content of condensed tannin (CT). The duration of daily grazing is a factor affecting the feed intake and milk production of ewes. In this study, the effects of grazing sulla pasture compared with annual ryegrass, and the extension of grazing from 8 to 22 h/day, were evaluated with regard to ewe forage intake and milk production, as well as the physicochemical properties and fatty acid (FA) composition of cheese. During 42 days in the spring, 28 ewes of the Comisana breed were divided into four groups (S8, S22, R8 and R22) that grazed sulla (S) or ryegrass (R) for 8 (0800 to 1600 h) or 22 h/day, and received no feeding supplement. In six cheese-making sessions, cheeses were manufactured from the 48 h bulk milk of each group. Compared with ewes grazing ryegrass, those grazing sulla had higher dry matter (DM) intake, intake rate and milk yield, and produced milk that was lower in fat and higher in casein. Ewes grazing for 22 h spent more time eating, which reduced the intake rate, increased DM and nutrient intake and milk yield, and reduced milk fat. Due to the ability of CT to inhibit the complete ruminal biohydrogenation of polyunsaturated fatty acids (PUFA), the FA composition of sulla cheese was more beneficial for consumer health compared with ryegrass cheese, having lower levels of saturated fatty acids and higher levels of PUFA and n-3 FA. The FA profile of S8 cheese was better than that of S22 cheese, as it was higher in branched-chain FA, monounsaturated FA, PUFA, rumenic acid (c9,t11-C18:2), and had a greater health-promoting index. The effect of short grazing time on sulla was attributed to major inhibition of PUFA biohydrogenating ruminal bacteria, presumably stimulated by the higher accumulation of sulla CT in the rumen, which is related to a higher intake rate over a shorter eating time. Thus, grazing sulla improved the performance of ewes, thereby increasing, especially with short grazing time, the nutritional properties of cheese fat.     

Estimates of (co)variance components and genetic parameters for body weights and first greasy fleece weight in Bharat Merino sheep

(Co)variance components and genetic parameters of weight at birth (BWT), weaning (3WT), 6, 9 and 12 months of age (6WT, 9WT and 12WT, respectively) and first greasy fleece weight (GFW) of Bharat Merino sheep, maintained at Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India, were estimated by restricted maximum likelihood, fitting six animal models with various combinations of direct and maternal effects. Data were collected over a period of 10 years (1998 to 2007). A log-likelihood ratio test was used to select the most appropriate univariate model for each trait, which was subsequently used in bivariate analysis. Heritability estimates for BWT, 3WT, 6WT, 9WT and 12WT and first GFW were 0.05 ± 0.03, 0.04 ± 0.02, 0.00, 0.03 ± 0.03, 0.09 ± 0.05 and 0.05 ± 0.03, respectively. There was no evidence for the maternal genetic effect on the traits under study. Maternal permanent environmental effect contributed 19% for BWT and 6% to 11% from 3WT to 9WT and 11% for first GFW. Maternal permanent environmental effect on the post-3WT was a carryover effect of maternal influences during pre-weaning age. A low rate of genetic progress seems possible in the flock through selection. Direct genetic correlations between body weight traits were positive and ranged from 0.36 between BWT and 6WT to 0.94 between 3WT and 6WT and between 6WT and 12WT. Genetic correlations of 3WT with 6WT, 9WT and 12WT were high and positive (0.94, 0.93 and 0.93, respectively), suggesting that genetic gain in post-3WT will be maintained if selection age is reduced to 3 months. The genetic correlations of GFW with live weights were 0.01, 0.16, 0.18, 0.40 and 0.32 for BWT, 3WT, 6WT, 9WT and 12WT, respectively. Correlations of permanent environmental effects of the dam across different traits were high and positive for all the traits (0.45 to 0.98).     

Genetic analysis for mastitis resistance and milk somatic cell score in French Lacaune dairy sheep

Genetic analysis for mastitis resistance was studied from two data sets. Firstly, risk factors for different mastitis traits, i.e. culling due to clinical or chronic mastitis and subclinical mastitis predicted from somatic cell count (SCC), were explored using data from 957 first lactation Lacaune ewes of an experimental INRA flock composed of two divergent lines for milk yield. Secondly, genetic parameters for SCC were estimated from 5 272 first lactation Lacaune ewes recorded among 38 flocks, using an animal model. In the experimental flock, the frequency of culling due to clinical mastitis (5%) was lower than that of subclinical mastitis (10%) predicted from SCC. Predicted subclinical mastitis was unfavourably associated with the milk yield level. Such an antagonism was not detected for clinical mastitis, which could result, to some extent, from its low frequency or from the limited amount of data. In practice, however, selection for mastitis resistance could be limited in a first approach to selection against subclinical mastitis using SCC. The heritability estimate of SCC was 0.15 for the lactation mean trait and varied from 0.04 to 0.12 from the first to the fifth test-day. The genetic correlation between lactation SCC and milk yield was slightly positive (0.15) but showed a strong evolution during lactation, i.e. from favourable (-0.48) to antagonistic (0.27). On a lactation basis, our results suggest that selection for mastitis resistance based on SCC is feasible. Patterns for genetic parameters within first lactation, however, require further confirmation and investigation.     

Environmental and genetic variation factors of artificial insemination success in French dairy sheep

Artificial inseminations (n = 678 168) recorded during 5 years in five French artificial insemination (AI) centres (2 'Lacaune', 1 'Manech tête rousse', 1 'Manech tête noire' and 1 'Basco béarnaise') were analysed to determine environmental and genetic factors affecting the insemination results. Analyses within centre-breed were performed using a linear model, which jointly estimates male and female fertility. This model combined four categories of data: the environmental effects related to the female, those related to the male, the non-sex-specific effects and finally the pedigree data of these males and females. After selection, the environmental female effects considered were age, synchronisation (0/1) on the previous year, total number of synchronisations during the female reproductive life, time interval between previous lambing and insemination, already dry or still lactating (0/1) when inseminated, and milk quantity produced during the previous year expressed as quartiles intra herd * year. The environmental male effects were motility and concentration of the semen. The non-sex-specific effects were the inseminator, the interaction herd * year nested within the inseminator, considered as random effects and the interaction year * season considered as a fixed effect. The main variation factors of AI success were relative to non-sex-specific effects and to female effects. Heritability estimates varied from 0.001 to 0.005 for male fertility and from 0.040 to 0.078 for female fertility. Repeatability estimates varied from 0.007 to 0.015 for male fertility and from 0.104 to 0.136 for female fertility. These parameters indicate that genetic improvement of AI results through a classical polygenic selection would be difficult. Moreover, in spite of the large quantity of variation factors fitted by the joint model, a very large residual variance remained unexplained.     

Heritability and repeatability of milk coagulation properties predicted by mid-infrared spectroscopy during routine data recording,and their relationships with milk yield and quality traits

The aim of this study was to estimate (co)variance components for milk coagulation properties (MCP) predicted by mid-infrared spectroscopy (MIRS) during routine milk recording, and to assess their relationships with yield and quality traits. A total of 63 470 milk samples from Holstein-Friesian cows were analyzed for MCP, pH and quality characteristics using MIRS. Casein to protein and protein to fat ratios were calculated from information obtained by MIRS. Records were collected across 1 year on 16 089 cows in 345 herds. The model used for genetic analysis included fixed effects of parity and stage of lactation, and random effects of herd-test-day, cow permanent environmental, animal additive genetic and residual. (Co)variance components were assessed in a Bayesian framework using the Gibbs Sampler. Estimates of heritabilities were consistent with those reported in the literature, being moderate for MCP (0.210 and 0.238 for rennet coagulation time (RCT) and curd firmness (a₃₀), respectively), milk contents (0.213 to 0.333) and pH (0.262), and low for somatic cell score (0.093) and yield traits (0.098 to 0.130). Repeatabilities were 0.391 and 0.434 for RCT and a₃₀, respectively, and genetic correlations were generally low, with estimates greater than 0.30 (in absolute value) only for a₃₀ with fat, protein and casein contents. Overall, results suggest that genetic evaluation for MCP predicted by MIRS is feasible at population level, and several repeated measures per cow during a lactation are required to estimate reliable breeding values for coagulation traits.     

Estimates of genetic parameters and genetic trends for live weight and fleece traits in Menz sheep

Menz sheep are indigenous to the highlands of Ethiopia, and highly valued for their meat and wool production. The area is characterized as a low input mixed barley-sheep production system. In 1998, a selection experiment was set up to evaluate the response of Menz sheep to selection for yearling live weight (WT12) and greasy fleece weight (GFW) combined in an economic index. In this paper, we report the results of this breeding program obtained between 1998 and 2003. Average annual genetic selection responses for WT12 and GFW were 1.506 and 0.043 kg in the selected flock and 0.392 and −0.008 kg in the control flock. Annual genetic trends in the selected flock, estimated by regressing BLUP estimated breeding values on year of birth, were 0.495 ± 0.053 kg for WT12, 0.012 ± 0.002 kg for GFW, and Birr 5.53 ± 0.55 for the aggregate breeding value (1 Ethiopian Birr = 0.115 USD). Corresponding values for the control flock were 0.276 ± 0.065 kg, 0.003 ± 0.002 kg and Birr 2.93 ± 0.69. Correlated responses in birth weight (WT0), weaning weight (WT3), 6-month weight (WT6) and staple length (STPL) in the selected flock were 0.038 ± 0.005 kg, 0.271 ± 0.03 kg, 0.388 ± 0.039 kg and 0.011 ± 0.017 cm, respectively. Heritabilities, estimated by fitting a multitrait individual animal model were 0.464 ± 0.014, 0.477 ± 0.016, 0.514 ± 0.017, 0.559 ± 0.019, 0.393 ± 0.016 and 0.339 ± 0.014 for WT0, WT3, WT6, WT12, GFW and staple length (STPL), respectively. Phenotypic and genetic correlations between all traits were positive, except for STPL and WT12. Estimates of genetic parameters and observed genetic trends confirm that selective breeding can lead to significant genetic improvement in Menz sheep.     

Effect of including genetic progress in milk yield on evaluating the use of sexed semen and other reproduction strategies in a dairy herd

The objective of this study was to explore the importance of including genetic progress in milk yield when evaluating different reproductive strategies in a dairy herd by simulation modeling. The model used in this study was SimHerd V, a dynamic and mechanistic Monte Carlo simulation model of a dairy herd including young stock. A daily increasing trend describing genetic milk yield potential of the sire population was included in the model. The inaccuracy of assuming that replacement heifers have the same (milk yield) potential as the cows present in the herd was hereby dealt with. Improving estrus detection rate from 0.45 to 0.80 increased gross margin (GM) per cow-year by €20 when genetic progress was not included in the model. When genetic progress was included in the model, then the same improvement in estrus detection decreased the GM per cow-year by €7.4. This reduced effect was explained by a lower replacement rate in consequence of the improved estrus detection and thereby a slower genetic progress in the herd. There was a reduced effect of including genetic progress on GM when surplus heifers were sold selectively based on breeding values. Repeated insemination with sexed semen on the superior half of all heifers reduced GM by €8 per cow-year when genetic progress was not included and increased the GM by €16 per cow-year when genetic progress was included in the model. Including genetic progress reduced the losses caused by lower conception and estrus detection rates and had a minimal effect with regard to postponing first insemination. This study has proven that it is important to include genetic progress in decisions on reproduction strategies in a dairy herd.     

Genetic parameters for test day milk yields of first lactation Holstein cows by random regression models

Covariance components for test day milk yield using 263 390 first lactation records of 32 448 Holstein cows were estimated using random regression animal models by restricted maximum likelihood. Three functions were used to adjust the lactation curve: the five-parameter logarithmic Ali and Schaeffer function (AS), the three-parameter exponential Wilmink function in its standard form (W) and in a modified form (W*), by reducing the range of covariate, and the combination of Legendre polynomial and W (LEG+W). Heterogeneous residual variance (RV) for different classes (4 and 29) of days in milk was considered in adjusting the functions. Estimates of RV were quite similar, rating from 4.15 to 5.29 kg². Heritability estimates for AS (0.29 to 0.42), LEG+W (0.28 to 0.42) and W* (0.33 to 0.40) were similar, but heritability estimates used W (0.25 to 0.65) were highest than those estimated by the other functions, particularly at the end of lactation. Genetic correlations between milk yield on consecutive test days were close to unity, but decreased as the interval between test days increased. The AS function with homogeneous RV model had the best fit among those evaluated.     

Genetic and phenotypic parameters for test day milk yield of Sahiwal cattle in the semi-arid tropics

A total of 19 376 test day (TD) milk yield records from the first three lactations of 1618 cows daughters of 162 sires were used to estimate genetic and phenotypic parameters and determine the relationship between daily milk yield and lactation milk yield in the Sahiwal cattle in Kenya. Variance components were estimated using animal models based on a derivative free restricted maximum likelihood procedure. Variance components were estimated using various univariate and multi-trait fixed regression test day models (TDM) that defined contemporary groups either based on the year-season of calving (YSCV) or on the year-season of TD milk sampling (YSTD). Variance components were influenced by CG which resulted in differences in heritability and repeatability estimates between TDM. Models considering YSTD resulted in higher additive genetic variances and lower residual variances compared with models in which YSCV was considered. Heritability estimates for daily yield ranged from 0.28 to 0.46, 0.38 to 0.52 and 0.33 to 0.52 in the first, second and third lactation, respectively. In the first and second lactation, the heritability estimates were highest between TD 2 and TD 4. Genetic correlations among daily milk yields ranged from 0.41 to 0.93, 0.50 to 0.83 and 0.43 to 86 in the first, second and third lactation, respectively. The phenotypic correlations were correspondingly lower. Genetic correlations were different from unit when fitting multi-trait TDM. Therefore, a multiple trait model would be more ideal in determining the genetic merit of dairy sires and bulls based on daily yield records. Genetic and phenotypic correlations between daily yield and lactation yields were high and positive. Genetic correlations ranged from 0.84 to 0.99, 0.94 to 1.00 and 0.94 to 0.97 in the first, second and third lactations, respectively. The corresponding phenotypic correlation estimates ranged from 0.50 to 0.85, 0.50 to 0.83 and 0.53 to 0.87. The high genetic correlation between daily yield and lactation yield imply that both traits are influenced by similar genes. Therefore daily yields records could be used in genetic evaluation in the Sahiwal cattle breeding programme.     

Estimation of genetic variability and heritability for biofuel feedstock yield in several populations of switchgrass

Information on heritability and predicted gains from selection for increased biomass yield for ethanol production in switchgrass is limited and may vary among breeding populations. The purpose of this study was to estimate heritability and predicted gains from selection for higher biomass yield within a lowland ecotype switchgrass population, Southern Lowland 93 (SL‐93), and two upland ecotype switchgrass populations, Southern Upland Northern Upland Early Maturing (SNU‐EM) and Southern Upland Northern Upland Late Maturing (SNU‐LM). Narrow‐sense heritabilities (h_n²) for biomass yield in each of the three populations were estimated via progeny–parent regression analysis. Half‐sib (HS) progeny families from 130 randomly selected plants from the SL‐93 population were evaluated for biomass yield in replicated trials in 2002 and 2003. Clonal parent plants were evaluated for biomass yield in separate environments to provide unbiased h_n² estimates from progeny–parent regression. Yield differences were highly significant among SL‐93 HS progenies within and over years. For the SL‐93 population, h_n² estimates were 0.13 and 0.12 based on individual plant and phenotypic family mean (PFM) selection, respectively. Predicted genetic gains (ΔG) per selection cycle were 0.15 kg dry matter (dm) plant^?1 and 0.10 kg dm plant^?1 for PFM and individual plant selection methods, respectively. For the SNU‐EM and SNU‐LM populations, year and year × HS family effects were highly significant (P < 0.01) and the HS family effect over years was nonsignificant (P < 0.05). However, HS family effects were highly significant within respective years (P < 0.01). Estimates of h_n² for the SNU‐EM and SNU‐LM populations based on PFM and individual plant selection were similar, ranging from 0.44 to 0.47; ΔG per selection cycle ranged from 0.22 to 0.33 kg dm plant^?1. The magnitudes of the estimates of additive genetic variation suggest that selection for higher biomass yield should be possible. The substantial effect of environment on biomass yields in the upland populations and the failure of families to respond similarly over years stress the importance of adequately testing biomass yield over years to assess yield.     

Associations between genetic merit for milk production and animal parameters and the fertility performance of dairy cows

Relationships between genetic merit for milk production and animal parameters and various parameters of reproductive performance were examined using multilevel binary response analysis in a study of 19 dairy herds for three successive years, representing approximately 2500 cows per year. The proportion of cows intended for rebreeding that were back in-calf again within 100 days of calving (ICR-100) and the proportion of cows that reappeared again with 365 (RR-365) and 400 days (RR-400) of a previous calving were considered in addition to the traditional measures of reproductive performance. Each 100-kg increase in genetic merit for milk yield was associated with an increased interval to first service (IFS) and calving index (CI) of 1.4 ( P < 0.001) and 1.8 days ( P < 0.001), respectively, a 0.5% increase ( P < 0.05) in calving rate to first insemination (CR-1) and 0.8% increase in RR-400. Each £10 increase in £PIN (the economically weighted yield selection index used in the UK that takes account of butterfat and protein yields) was associated with an increased IFS and CI of 1.5 ( P < 0.001) and 3.0 days ( P < 0.001), respectively. Cows with increased genetic merit for milk yield and £PIN were more likely to re-calve (RR-overall; P < 0.001). Each 1000-kg increase in 305-day milk yield was associated with an increased IFS and CI of 3.2 ( P < 0.001) and 7.8 days ( P < 0.001), respectively, and a 13.6 ( P < 0.001), 22.4 ( P < 0.001), 19.9 ( P < 0.001) and 19.0% ( P < 0.001) decrease in CR-1, ICR-100, RR-365 and RR-400, respectively. A 10-kg increase in maximum yield was associated with a 6.6-day increase in CI ( P < 0.001) and a 14.9 ( P < 0.001), 18.3 ( P < 0.001), 9.6 ( P < 0.05) and 14.2% ( P < 0.001) decrease in CR-1, ICR-100, RR-365 and RR-400, respectively. Fertility performance was also associated with season of calving, lactation number and dystocia score. Level of production had a larger effect on fertility performance than genetic merit for milk production suggesting that infertility at an individual cow level is more likely to be associated with increased production and an inability to meet the nutritional requirements of the cow.     

Genetic trends of conformation traits and genetic correlations to osteochondrosis in boars

The objective of our study was to investigate the heritabilities and genetic correlations between traits from a linear exterior assessment system and osteochondrosis (OC) measured by computed tomography (CT), and in addition, to study the genetic trend in a population where the conformation traits have been included in the breeding goal. The data material consisted of phenotypes from a total of 4571 Norsvin Landrace test boars. At the end of the test period, all boars were subjected to a detailed exterior assessment system. Within 10 days of the assessment, the boars were CT scanned for measuring OC. The total score of osteochondrosis (OCT), used in this study, is the sum of phenotypes from the assessment on the medial and lateral condyles at the distal end of both the humerus and the femur of the right and the left leg of the boar based on images from CT. The exterior assessment traits included in the study were; ‘front leg knee’ (FKNE), ‘front leg pasterns’ (FPAS), ‘front leg stance’ (FSTA), ‘front leg twisted pasterns’ (FFLK), ‘hind leg stance’, ‘hind leg pasterns’ (HPAS), ‘hind leg standing under’ (HSTU), ‘hind leg small inner toe’, ‘dipped back’, ‘arched back’ (ARCH) and ‘waddling hindquarters’ (WADL). The estimation of (co)variance components and breeding values were performed using bivariate animal genetic models. Breeding values for HSTU, HPAS, FPAS, WADL and OCT traits were additional outputs from the same bivariate analyses. The lowest heritability was found for FFLK (h²_FFLK=0.05), whereas FPAS was estimated to have the highest heritability (h²_FPAS=0.36), and OCT demonstrating a heritability of 0.29. Significant genetic correlations were found between several traits; the strongest correlation was between FSTA and FFLK (0.94), which was followed by the correlation between FPAS and FKNE (0.69). The traits ARCH and FSTA had significant genetic correlations to OCT, whereas all other genetic correlations between OCT and the conformation traits were low and not significantly different from 0. Our study shows positive genetic trends for the conformation traits included in the breeding goal. In general, low genetic correlations between conformation traits and OC were observed in our study.     

Estimation of genetic parameters for test day records of dairy traits in the first three lactations

Application of test-day models for the genetic evaluation of dairy populations requires the solution of large mixed model equations. The size of the (co)variance matrices required with such models can be reduced through the use of its first eigenvectors. Here, the first two eigenvectors of (co)variance matrices estimated for dairy traits in first lactation were used as covariables to jointly estimate genetic parameters of the first three lactations. These eigenvectors appear to be similar across traits and have a biological interpretation, one being related to the level of production and the other to persistency. Furthermore, they explain more than 95% of the total genetic variation. Variances and heritabilities obtained with this model were consistent with previous studies. High correlations were found among production levels in different lactations. Persistency measures were less correlated. Genetic correlations between second and third lactations were close to one, indicating that these can be considered as the same trait. Genetic correlations within lactation were high except between extreme parts of the lactation. This study shows that the use of eigenvectors can reduce the rank of (co)variance matrices for the test-day model and can provide consistent genetic parameters.     

Multiple-trait multiple-country genetic evaluation of Holstein bulls for female fertility and milk production traits

The aim of this study was to investigate the effect of including milk yield data in the international genetic evaluation of female fertility traits to reduce or eliminate a possible bias because of across-country selection for milk yield. Data included two female fertility traits from Great Britain, Italy and the Netherlands, together with milk yield data from the same countries and from the United States, because the genetic trends in other countries may be influenced by selection decisions on bulls in the United States. Potentially, female fertility data had been corrected nationally for within-country selection and management biases for milk yield. Using a multiple-trait multiple across-country evaluation (MT-MACE) for the analysis of female fertility traits with milk yield, across-country selection patterns both for female fertility and milk yield can be considered simultaneously. Four analyses were performed; one single-trait multiple across-country evaluation analysis including only milk yield data, one MT-MACE analysis including only female fertility traits, and one MT-MACE analysis including both female fertility and milk yield traits. An additional MT-MACE analysis was performed including both female fertility and milk yield traits, but excluding the United States. By including milk yield traits to the analysis, female fertility reliabilities increased, but not for all bulls in all the countries by trait combinations. The presence of milk yield traits in the analysis did not considerably change the genetic correlations, genetic trends or bull rankings of female fertility traits. Even though the predicted genetic merits of female fertility traits hardly changed by including milk yield traits to the analysis, the change was not equally distributed to the whole data. The number of bulls in common between the two sets of Top 100 bulls for each trait in the two analyses of female fertility traits, with and without the four milk yield traits and their rank correlations were low, not necessarily because of the absence of the US milk yield data. The joint international genetic evaluation of female fertility traits with milk yield is recommended to make use of information on several female fertility traits from different countries simultaneously, to consider selection decisions for milk yield in the genetic evaluation of female fertility traits for obtaining more accurate estimating breeding values (EBV) and to acquire female fertility EBV for bulls evaluated for milk yield, but not for female fertility.     

Sexual variation in heritability and genetic correlations of morphological traits in house sparrow (Passer domesticus)

Estimates of genetic components are important for our understanding of how individual characteristics are transferred between generations. We show that the level of heritability varies between 0.12 and 0.68 in six morphological traits in house sparrows (Passer domesticus L.) in northern Norway. Positive and negative genetic correlations were present among traits, suggesting evolutionary constraints on the evolution of some of these characters. A sexual difference in the amount of heritable genetic variation was found in tarsus length, wing length, bill depth and body condition index, with generally higher heritability in females. In addition, the structure of the genetic variance-covariance matrix for the traits differed between the sexes. Genetic correlations between males and females for the morphological traits were however large and not significantly different from one, indicating that sex-specific responses to selection will be influenced by intersexual differences in selection differentials. Despite this, some traits had heritability above 0.1 in females, even after conditioning on the additive genetic covariance between sexes and the additive genetic variances in males. Moreover, a meta-analysis indicated that higher heritability in females than in males may be common in birds. Thus, this indicates sexual differences in the genetic architecture of birds. Consequently, as in house sparrows, the evolutionary responses to selection will often be larger in females than males. Hence, our results suggest that sex-specific additive genetic variances and covariances, although ignored in most studies, should be included when making predictions of evolutionary changes from standard quantitative genetic models.     

Genotype by feeding system interaction in the genetic evaluation of Jersey cattle for milk yield

Results of studies in dairy cattle about the magnitude of the genotype-environment interaction (GEI) are variable, depending on the definitions of genotype and environment. Therefore, the objective of this study was to determine the magnitude of the interaction of genotype and feeding system (confinement and grazing) in the Mexican genetic evaluation of Jersey cattle for milk yield. The number of lactations and animals in the pedigree used were 5122 and 18 432. An animal model and the MTDFREML program were used to estimate genetic parameters and predict genetic values of the animals. Bivariate analysis was carried out considering the performance of confined and grazing cows as two different traits. Three indicator variables were used to assess GEI: (i) magnitude of the genetic correlation coefficients, (ii) correlation between predicted breeding values and (iii) frequency of coincidence in the ranking of top sires. The magnitude of GEI depended on the choice of the indicator variable. The estimate of genetic correlation coefficient less than unity (0.76; P < 0.05) suggested the presence of biologically important GEI. The differences in phenotypic averages and variances between confinement and grazing systems seem to be the main causes for the genotype by environment interaction detected. However, the correlation coefficient between breeding values from confined and grazing animals (0.96) and the frequency of coincidence between breeding values of common sires within the top 100 in confinement and grazing (0.86) indicated low-to-moderate re-ranking of animals or top sires. In addition, the high correlations between predicted breeding values of Mexican genetic evaluation and the two environments (0.99 and 0.93 for confinement and grazing) indicated that for the two feeding systems, breeding values from national analyses could be safely used.