奶牛重要经济性状全基因组关联分析研究进展

产奶性状是奶牛最重要的生产性状,随着平衡育种理念的提出和发展,繁殖性状、体型性状、健康性状和长寿性等功能性状也逐渐被重视并纳入育种规划中。鉴定产奶性状和功能性状主效基因或遗传标记并将之应用于奶牛标记辅助选择可望加快遗传进展。随着高密度SNP标记的高通量检测技术的发展,全基因组关联分析已成为鉴定畜禽重要经济性状基因的重要途径。文章对奶牛产奶性状和功能性状全基因组关联分析研究进展进行综述。     

奶牛重要经济性状全基因组关联分析研究进展

产奶性状是奶牛最重要的生产性状, 随着平衡育种理念的提出和发展, 繁殖性状、体型性状、健康性状和长寿性等功能性状也逐渐被重视并纳入育种规划中。鉴定产奶性状和功能性状主效基因或遗传标记并将之应用于奶牛标记辅助选择可望加快遗传进展。随着高密度SNP标记的高通量检测技术的发展, 全基因组关联分析已成为鉴定畜禽重要经济性状基因的重要途径。文章对奶牛产奶性状和功能性状全基因组关联分析研究进展进行综述。     

Genetic parameters for production,health, fertility and longevity traits in dairy cows

Milk production, fertility, longevity and health records, were extracted from databases of two milk recording organisations in the United Kingdom for the first three lactations of the Holstein–Friesian breed. These included data related to health events (mastitis and lameness), voluntarily recorded on a proportion of farms. The data were analysed to calculate disease incidence levels and to estimate genetic parameters for health traits and their relationships with production and other functional traits. The resulting dataset consisted of 124 793 lactations from 75 137 animals of 1586 sires, recorded in 2434 herds. Incidence of health events increased with parity. The overall incidence of mastitis (MAS) and lameness (LAM), defined as binary traits, were 17% and 16%, respectively. Heritability estimates for MAS and LAM were 0.04 and 0.02, respectively, obtained from repeatability linear sire models. Heritability estimates of mastitis and lameness as count traits were slightly higher, 0.05 and 0.03, respectively. Genetic correlations were obtained by bivariate analyses of all pair-wise combinations between milk 305-day yield (MY), protein 305-day yield (PY), fat 305-day yield (FY), lactation average log_e transformed lactation average somatic cell count (SCS), calving interval (CI), days to first service (DFS), non-return at 56 days (NR56), number of inseminations (NINS), mastitis (MAS), number of mastitis episodes (NMAS), lameness (LAM), number of lameness episodes (NLAM) and lifespan score (LS). As expected, MAS was correlated most strongly with SCS (0.69), which supports the use of SCS as an indicator trait for mastitis. Genetic correlations between MAS and yield and fertility traits were of similar magnitude ranging from 0.27 to 0.33. Genetic correlations between MAS with LAM and LS were 0.38 and −0.59, respectively. Not all genetic correlations between LAM and other traits were significant because of fewer numbers of lameness records. LAM had significant genetic correlations with MY (0.38), PY (0.28), CI (0.35), NINS (0.38) and LS (−0.53). The heritability estimates of mastitis and lameness were low; therefore, genetic gain through direct selection alone would be slow, yet still positive and cumulative. Direct selection against mastitis and lameness as additional traits should reduce incidence of both diseases, and simultaneously improve fertility and longevity. However, both health traits had antagonistic relationships with production traits, thus genetic gain in production would be slower.     

Genetic parameters for endocrine and traditional fertility traits,hyperketonemia and milk yield in dairy cattle

High-yielding cows may suffer from negative energy balance during early lactation, which can lead to ketosis and delayed ability of returning to cyclicity after calving. Fast recovery after calving is essential when breeding for improved fertility. Traditionally used fertility traits, such as the interval from calving to first insemination (CFI), have low heritabilities and are highly influenced by management decisions. Herd Navigator™ management program samples and analyses milk progesterone and β-hydroxybutyrate (BHB) automatically during milking. In this study, the genetic parameters of endocrine fertility traits (measured from milk progesterone) and hyperketonemia (measured from milk BHB) in early lactation were evaluated and compared with traditional fertility traits (CFI, interval from calving to the last insemination and interval from first to last insemination) and the milk yield in red dairy cattle herds in Finland. Data included observations from 14 farms from 2014 to 2017. Data were analyzed with linear animal models using DMU software and analyses were done for first parity cows. Heritability estimates for traditional fertility traits were low and varied between 0.03 and 0.07. Estimated heritabilities for endocrine fertility traits (interval from calving to the first heat (CFH) and commencement of luteal activity (C-LA)) were higher than for traditional fertility traits (0.19 to 0.33). Five slightly different hyperketonemia traits divided into two or three classes were studied. Linear model heritability estimates for hyperketonemia traits were low, however, when the threshold model was used for binary traits the estimates became slightly higher (0.07 to 0.15). Genetic correlation between CFH and C-LA for first parity cows was high (0.97) as expected since traits are quite similar. Moderate genetic correlations (0.47 to 0.52) were found between the endocrine fertility traits and early lactation milk yield. Results suggest that the data on endocrine fertility traits measured by automatic systems is a promising tool for improving fertility, specifically when more data is available. For hyperketonemia traits, dividing values into three classes instead of two seemed to work better. Based on the current study and previous studies, where higher heritabilities have been found for milk BHB traits than for clinical ketosis, milk BHB traits are a promising indicator trait for resistance to ketosis and should be studied more. It is important that this kind of data from automatic devices is made available to recording and breeding organizations in the future.     

Defining the breeding goal for a sheep breed including production and functional traits using market data

In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals.     

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.     

Review: Opportunities and challenges for small populations of dairy cattle in the era of genomics

In modern dairy cattle breeding, genomic breeding programs have the potential to increase efficiency and genetic gain. At the same time, the requirements and the availability of genotypes and phenotypes present a challenge. The set-up of a large enough reference population for genomic prediction is problematic for numerically small breeds but also for hard to measure traits. The first part of this study is a review of the current literature on strategies to overcome the lack of reference data. One solution is the use of combined reference populations from different breeds, different countries, or different research populations. Results reveal that the level of relationship between the merged populations is the most important factor. Compiling closely related populations facilitates the accurate estimation of marker effects and thus results in high accuracies of genomic prediction. Consequently, mixed reference populations of the same breed, but from different countries are more promising than combining different breeds, especially if those are more distantly related. The use of female reference information has the potential to enlarge the reference population size. Including females is advisable for small populations and difficult traits, and maybe combined with genotyping females and imputing those that are un-genotyped.The efficient use of imputation for un-genotyped individuals requires a set of genotyped related animals and well-considered selection strategies which animals to choose for genotyping and phenotyping. Small populations have to find ways to derive additional advantages from the cost-intensive establishment of genomic breeding schemes. Possible solutions may be the use of genomic information for inbreeding control, parentage verification, within-herd selection, adjusted mating plans or conservation strategies.The second part of the paper deals with the issue of high-quality phenotypes against the background of new, difficult and hard to measure traits. The use of contracted herds for phenotyping is recommended, as additional traits, when compared to standard traits used in dairy cattle breeding can be measured at set moments in time. This can be undertaken even for the recording of health traits, thus resulting in complete contemporary groups for health traits. Future traits to be recorded and used in genomic breeding programs, at least partly will be traits for which traditional selection based on widespread phenotyping is not possible. Enabling phenotyping of sufficient numbers to enable genomic selection will rely on cooperation between scientists from different disciplines and may require multidisciplinary approaches.     

Weighting fibre and morphological traits in a genetic index for an alpaca breeding programme

Nowadays, the fibre diameter (FD) is considered the main selection objective in alpaca populations all over the world. International Committee for Animal Recording recommendations define the FD and its CV as the first two traits to be considered in breeding programmes for this specie. In addition to these main criteria, other selection criteria of economic value used are comfort factor (CF) or standard deviation (s.d.); also other less important traits being used as selection objectives are these morphological traits: density (DE), crimp (CR) or lock structure (LS) for, respectively, Huacaya (HU) and Suri (SU) ecotypes, head (HE), coverage (CO) and balance (BA). The goal of this study was to establish how to implement a combined selection index starting from genetic parameters and to study the expected correlation between genetic trends by considering different alternative procedures of weighting all the involved traits, and the consequences of a wrongly proceeding way. Heritabilities and genetic and phenotypic correlations were estimated from the data set belonging to the PACOMARCA experimental farm for SU and HU. Two approaches were used to check the consequences of a set of subjective weights essayed. The coefficients of selection indexes were obtained for two sets of reference weights. In addition, equivalent weights were drawn if applied those reference values as coefficients of hypothetical selection indexes directly on phenotypes; relative expected genetic responses were computed in different cases. Results showed that almost in all cases for both ecotypes, the weight applied to CF should be surprisingly negative. Concerning genetic responses, only CO was compromised in some cases for the HU ecotype. The essayed methodology allowed explaining the differences between ecotypes in the genetic trends. The proposed methodology was shown to be effective to study the relative importance of the traits granted by the manager of a breeding scheme.     

A methodology framework for weighting genetic traits that impact greenhouse gas emission intensities in selection indexes

A methodological framework was presented for deriving weightings to be applied in selection indexes to account for the impact genetic change in traits will have on greenhouse gas emissions intensities (EIs). Although the emission component of the breeding goal was defined as the ratio of total emissions relative to a weighted combination of farm outputs, the resulting trait-weighting factors can be applied as linear weightings in a way that augments any existing breeding objective before consideration of EI. Calculus was used to define the parameters and assumptions required to link each trait change to the expected changes in EI for an animal production system. Four key components were identified. The potential impact of the trait on relative numbers of emitting animals per breeding female first has a direct effect on emission output but, second, also has a dilution effect from the extra output associated with the extra animals. Third, each genetic trait can potentially change the amount of emissions generated per animal and, finally, the potential impact of the trait on product output is accounted for. Emission intensity weightings derived from this equation require further modifications to integrate them into an existing breeding objective. These include accounting for different timing and frequency of trait expressions as well as a weighting factor to determine the degree of selection emphasis that is diverted away from improving farm profitability in order to achieve gains in EI. The methodology was demonstrated using a simple application to dairy cattle breeding in Ireland to quantify gains in EI reduction from existing genetic trends in milk production as well as in fertility and survival traits. Most gains were identified as coming through the dilution effect of genetic increases in milk protein per cow, although gains from genetic improvements in survival by reducing emissions from herd replacements were also significant. Emission intensities in the Irish dairy industry were estimated to be reduced by ~5% in the last 10 years because of genetic trends in production, fertility and survival traits, and a further 15% reduction was projected over the next 15 years because of an observed acceleration of genetic trends.     

Genome‐wide association studies for milk production traits in Valle del Belice sheep using repeated measures

Genome‐wide association studies (GWASes) have become a powerful tool for identifying genomic regions associated with important traits in livestock. Milk production traits in dairy sheep are measured at different time points during their life span. Using phenotypic data generated from longitudinal traits could improve the power of association studies but until now have received less attention in GWASes as a methodology and has not been implemented. The aim of this study was to carry out a GWAS for milk production traits in Valle del Belice sheep using repeated measures. After quality control, 469 ewes and 37 228 SNPs were retained for the analysis, and phenotypic data included 5586 test‐day records for five milk production traits (milk yield, MY; fat yield and percentage, FY and F%; protein yield and percentage, PY and P%). Nine SNPs located within or close to known genes were found to be associated with milk production traits. In particular, rs398340969, associated with both milk yield and protein yield, is located within the DCPS gene. In addition, rs425417915 and rs417079368, both associated with both fat percentage and protein percentage, are located within the TTC7B gene and at 0.37 Mb within the SUCNR1 gene respectively. In summary, the use of repeated records was beneficial for mapping genomic regions affecting milk production traits in the Valle del Belice sheep.     

Evaluation of type traits in relation to production,and their importance in early selection for milk performance in dairy buffaloes

Type traits (TTs) can contribute to breeding animals with good economic traits such as production, longevity, fertility, and profitability. Dairy buffaloes are the second largest source of milk supply in the world, and their TTs should be taken into consideration in future dairy buffalo breeding programmes. However, the relationship between TTs and milk production traits in buffalo remains largely unknown. The study aimed to establish an early selection method for buffaloes with desirable milk performance by TTs. Using 1 908 records from 678 buffaloes, the relationship between TTs and milk production traits was analysed and the optimal growth curves of TTs related to milk production traits were constructed. We examined the correlations between 45 TTs (33 body structural, 12 udder and teat morphological traits) and three milk production traits (milk yield (MY), milk fat percentage (MF), and milk protein percentage (MP)). The results showed that the highest correlation was found between MY and udder circumference (r = 0.438), teat length (r = ?0.380) or heart girth (r = ?0.341). The teat distance and teat circumference exhibited a significant negative correlation with MF and MP. Rump length was the only trait that had a significant positive correlation with milk production traits, suggesting that milk performance could be comprehensively improved by including rump length in the selection procedure. Notably, we found that high milk production traits was obtained from the buffaloes with short teats (<6 cm), small heart girth (<200 cm), large udder circumference (>104 cm), long rump (>39 cm), and small distance between teats. Moreover, an early selection method for buffaloes with excellent milk performance was developed based on the non-linear models. Brody model exhibited the best fitting effect for heart girth and rump length, while the Logistic model displayed the best fitting effect for teat length. Our findings provide theoretical basis for the early selection of buffaloes with desirable milk performance.     

Impact of production strategies and animal performance on economic values of dairy sheep traits

The objective of this study was to carry out a sensitivity analysis on the impact of various production strategies and performance levels on the relative economic values (REVs) of traits in dairy sheep. A bio-economic model implemented in the program package ECOWEIGHT was used to simulate the profit function for a semi-extensive production system with the Slovak multi-purpose breed Improved Valachian and to calculate the REV of 14 production and functional traits. The following production strategies were analysed: differing proportions of milk processed to cheese, customary weaning and early weaning of lambs with immediate sale or sale after artificial rearing, seasonal lambing in winter and aseasonal lambing in autumn. Results of the sensitivity analysis are presented in detail for the four economically most important traits: 150 days milk yield, conception rate of ewes, litter size and ewe productive lifetime. Impacts of the differences in the mean value of each of these four traits on REVs of all other traits were also examined. Simulated changes in the production circumstances had a higher impact on the REV for milk yield than on REVs of the other traits investigated. The proportion of milk processed to cheese, weaning management strategy for lambs and level of milk yield were the main factors influencing the REV of milk yield. The REVs for conception rate of ewes were highly sensitive to the current mean level of the trait. The REV of ewe productive lifetime was most sensitive to variation in ewe conception rate, and the REV of litter size was most affected by weaning strategy for lambs. On the basis of the results of sensitivity analyses, it is recommended that economic values of traits for the overall breeding objective for dairy sheep be calculated as the weighted average of the economic values obtained for the most common production strategies of Slovak dairy sheep farms and that economic values be adjusted after substantial changes in performance levels of the traits.     

Leptin promoter mutations affect leptin levels and performance traits in dairy cows

Leptin concentrations in body fluids and tissues undergo dynamic changes during the periparturient period. Polymorphisms in the leptin gene have been shown to be associated with differences in leptin concentration during late pregnancy but not during lactation. As the promoter of leptin regulates the expression of leptin, polymorphisms in this region could play an important role in the differences in leptin expression observed during the periparturient period. We sequenced the leptin promoter and discovered 20 SNP in a 1.6-kbp region of the bovine leptin promoter. Fourteen of these SNP were genotyped for all animals and these were found to be associated with leptin concentrations during late pregnancy but not during lactation. Three of these SNP are located in a 135-bp promoter region and together explained 14.3% of the variance in prepartum leptin concentrations which indicates that this region might be important for pregnancy-induced leptin synthesis. In the association study of the 14 SNP with dairy traits three were separately found to be associated with fertility, energy balance and protein yield. These might serve as markers for future breeding programmes for better fertility and energy balance without significantly influencing milk yield in dairy cattle.     

Genetic parameters estimation for preweaning traits and their relationship with reproductive,productive and morphological traits in alpaca

The aim of this study was to estimate the genetic parameters for preweaning traits and their relationship with reproductive, productive and morphological traits in alpacas. The data were collected from 2001 to 2015 in the Pacomarca experimental farm. The data set contained data from 4330 females and 3788 males corresponding to 6396 and 1722 animals for Huacaya and Suri variants, respectively. The number of records for Huacaya and Suri variants were 5494 and 1461 for birth weight (BW), 5429 and 1431 for birth withers height (BH), 3320 and 896 for both weaning weight (WW) and average daily gain (DG) from birth to weaning, 3317 and 896 for weaning withers height (WH), and 5514 and 1474 for survival to weaning. The reproductive traits analyzed were age at first calving and calving interval. The fiber traits were fiber diameter (FD), standard deviation of FD (SD), comfort factor and coefficient of variation of FD and the morphological traits studied were density, crimp in Huacaya and lock structure in Suri, head, coverage and balance. Regarding preweaning traits, model of analysis included additive, maternal and residual random effects for all traits, with sex, coat color, number of calving, month–year and contemporary group as systematic effects, and age at weaning as linear covariate for WW and WH. The most relevant direct heritabilities for Huacaya and Suri were 0.50 and 0.34 for WW, 0.36 and 0.66 for WH, 0.45 and 0.20 for DG, respectively. Maternal heritabilities were 0.25 and 0.38 for BW, 0.18 and 0.32 for BH, 0.29 and 0.39 for WW, 0.19 and 0.26 for WH, 0.27 and 0.36 for DG, respectively. Direct genetic correlations within preweaning traits were high and favorable and lower between direct and maternal genetic effects. The genetic correlations of preweaning traits with fiber traits were moderate and unfavorable. With morphological traits they were high and positive for Suri but not for Huacaya and favorable for direct genetic effect but unfavorable for maternal genetic effect with reproductive traits. If the selection objective was meat production, the selection would have to be based on the direct genetic effect for WW but not on the maternal genetic effect that has been shown to have less relevance. Other weaning traits such as WH or DG would be indirectly selected.     

Effect of leptin gene polymorphism on the breeding value of milk production traits in Iranian Holstein

New molecular techniques focused on genome analysis, open new possibilities for more accurate evaluation of economiclly important traits in farm animals. Milk production traits are typical quantitative characteristics controlled by a number of genes. Mutations in their sequences may alter animal performance as well as their breeding values. In this study, we investigated the effect of Kpn2I restriction fragment length polymorphisms in the leptin gene, on bull breeding values for milk yield, fat, and protein yield, and their percentage. In order to test for an association between the leptin single-nucleotide polymorphism in exon 2 and milk productivity, we genotyped 134 Iranian Holstein bulls. Breeding values for milk-related traits (milk yield, fat, and protein yield and percentage) were estimated using the BLUP based on an animal model. The effect of the genotypes of Kpn2I polymorphism on the breeding values for milk-related traits was examined using least square methods. The T allele frequency was 0.425. Genotypes were distributed according to the Hardy-Weinberg equilibrium. Bulls with TT genotype had higher milk, fat and protein yield compared with TC and CC bulls (P < 0.05). Bulls with CC genotype had higher protein percentage compared with TT and TC bulls (P < 0.05). The association between leptin polymorphism with milk production traits suggests that this marker may be useful for selection based on molecular information.     

Using the choice experiment method in the design of breeding goals in dairy sheep

Market failures are the main cause of poor acknowledgement of the true impact of functional sheep traits on the management and economic performance of farms, which results in their omission from the breeding goal or the estimation of non-representative economic weights in the breeding goal. Consequently, stated-preference non-market valuation techniques, which recently emerged to mitigate these problems, are necessary to estimate economic weights for functional traits. The purpose of this paper is to present an example of the use of a choice experiment (CE) in the estimation of economic weights for sheep traits for the design of breeding goals. Through a questionnaire survey the preferences of sheep farmers are recorded and their marginal willingness to pay (MWTP) for 10 production and functional traits is estimated. Data are analysed using random parameter logit models. The results reveal unobserved preference heterogeneity for fertility, adaptability to grazing and resistance to disease, thus highlighting that these traits are appreciated differently by farmers, because their needs are diverse. Positive MWTP is found for Greek breeds, high milk production and lambs with low fat deposition, for which there is high demand in Greek markets. On the other hand, MWTP for the cheese-making ability of milk is negative, stemming from the fact that sheep milk prices in Greece are not formulated according to milk composition. In addition, farmers seem to understand differences between udder shapes and attribute different values to various types. This application of the CE method indicates that communication channels among farmers and breeders should be established in order to enhance market performance and to provide orientation to the design of breeding programmes. Non-market valuation can be used complementarily to market valuation techniques, in order to provide accurate estimates for production and functional traits.     

Turning science on robust cattle into improved genetic selection decisions

More robust cattle have the potential to increase farm profitability, improve animal welfare, reduce the contribution of ruminant livestock to greenhouse gas emissions and decrease the risk of food shortages in the face of increased variability in the farm environment. Breeding is a powerful tool for changing the robustness of cattle; however, insufficient recording of breeding goal traits and selection of animals at younger ages tend to favour genetic change in productivity traits relative to robustness traits. This paper has extended a previously proposed theory of artificial evolution to demonstrate, using deterministic simulation, how choice of breeding scheme design can be used as a tool to manipulate the direction of genetic progress, whereas the breeding goal remains focussed on the factors motivating individual farm decision makers. Particular focus was placed on the transition from progeny testing or mass selection to genomic selection breeding strategies. Transition to genomic selection from a breeding strategy where candidates are selected before records from progeny being available was shown to be highly likely to favour genetic progress in robustness traits relative to productivity traits. This was shown even with modest numbers of animals available for training and when heritability for robustness traits was only slightly lower than that for productivity traits. When transitioning from progeny testing to a genomic selection strategy without progeny testing, it was shown that there is a significant risk that robustness traits could become less influential in selection relative to productivity traits. Augmentations of training populations using genotyped cows and support for industry-wide improvements in phenotypic recording of robustness traits were put forward as investment opportunities for stakeholders wishing to facilitate the application of science on robust cattle into improved genetic selection schemes.     

Effect of predictor traits on accuracy of genomic breeding values for feed intake based on a limited cow reference population

The genomic breeding value accuracy of scarcely recorded traits is low because of the limited number of phenotypic observations. One solution to increase the breeding value accuracy is to use predictor traits. This study investigated the impact of recording additional phenotypic observations for predictor traits on reference and evaluated animals on the genomic breeding value accuracy for a scarcely recorded trait. The scarcely recorded trait was dry matter intake (DMI, n = 869) and the predictor traits were fat–protein-corrected milk (FPCM, n = 1520) and live weight (LW, n = 1309). All phenotyped animals were genotyped and originated from research farms in Ireland, the United Kingdom and the Netherlands. Multi-trait REML was used to simultaneously estimate variance components and breeding values for DMI using available predictors. In addition, analyses using only pedigree relationships were performed. Breeding value accuracy was assessed through cross-validation (CV) and prediction error variance (PEV). CV groups (n = 7) were defined by splitting animals across genetic lines and management groups within country. With no additional traits recorded for the evaluated animals, both CV- and PEV-based accuracies for DMI were substantially higher for genomic than for pedigree analyses (CV: max. 0.26 for pedigree and 0.33 for genomic analyses; PEV: max. 0.45 and 0.52, respectively). With additional traits available, the differences between pedigree and genomic accuracies diminished. With additional recording for FPCM, pedigree accuracies increased from 0.26 to 0.47 for CV and from 0.45 to 0.48 for PEV. Genomic accuracies increased from 0.33 to 0.50 for CV and from 0.52 to 0.53 for PEV. With additional recording for LW instead of FPCM, pedigree accuracies increased to 0.54 for CV and to 0.61 for PEV. Genomic accuracies increased to 0.57 for CV and to 0.60 for PEV. With both FPCM and LW available for evaluated animals, accuracy was highest (0.62 for CV and 0.61 for PEV in pedigree, and 0.63 for CV and 0.61 for PEV in genomic analyses). Recording predictor traits for only the reference population did not increase DMI breeding value accuracy. Recording predictor traits for both reference and evaluated animals significantly increased DMI breeding value accuracy and removed the bias observed when only reference animals had records. The benefit of using genomic instead of pedigree relationships was reduced when more predictor traits were used. Using predictor traits may be an inexpensive way to significantly increase the accuracy and remove the bias of (genomic) breeding values of scarcely recorded traits such as feed intake.     

Strategies for defining traits when calculating economic values for livestock breeding: a review

The objective of the present review was (i) to survey different approaches for choosing the complex of traits for which economic values (EVs) are calculated, (ii) to call attention to the proper definition of traits and (iii) to discuss the manner and extent to which relationships among traits have been considered in the calculation of EVs. For this purpose, papers dealing with the estimation of EVs of traits in livestock were reviewed. The most important reasons for incompatibility of EVs for similar traits estimated in different countries and by different authors were found to be inconsistencies in trait definitions and in assumptions being made about relationships among traits. An important problem identified was how to choose the most appropriate criterion to characterise production or functional ability for a particular class of animals. Accordingly, the review covered the following three topics: (i) which trait(s) would best characterise the growth ability of an animal; (ii) how to define traits expressed repeatedly in subsequent reproductive cycles of breeding females and (iii) how to deal with traits that differ in average value between sexes or among animal groups. Various approaches that have been used to solve these problems were discussed. Furthermore, the manner in which diverse authors chose one or more traits from a group of alternatives for describing a specific biological potential were reviewed and commented on. The consequences of including or excluding relationships among economically important traits when estimating the EV for a specific trait were also examined. An important conclusion of the review is that, for a better comparability and interpretability of estimated EVs in the literature, it is desirable that clear and unique definitions of the traits, complete information on assumptions used in analytical models and details on inter-relationships between traits are documented. Furthermore, the method and the model used for the genetic evaluation of specific traits in a certain breeding organisation are important for the exact definition of traits, for which the economic values will be calculated, and for the inclusion or exclusion of relationships among traits in the calculation of the EVs in livestock breeding.     

Quantitative genetic estimates of growth-related traits in the common carp (Cyprinus carpio L.): A review

The common carp (Cyrpinus carpio L.) is the oldest cultured and the most domesticated fish species, as well as one of the most important freshwater fishes in the world. However, scientific studies on evaluating the growth-related quantitative traits in this fish are limited. Heritability, the most important parameter in selective breeding programs, was extensively studied for the growth-related traits. The values varied widely among the experiments and methods used because of the existence of common environmental, dominance and maternal effects. However, correlations in phenotypic and genetic levels first evaluated several years ago were limited. On the other hand, heterosis was widely reported and easily obtained for growth-related traits in the common carp. Meanwhile, genotype environment interaction and predic-tion of breeding values have been studied recently, and are very important in conducting selective breeding programs. The developmental quantitative genetics of growth-related traits was first analyzed in the common carp for reasonable selection during ontogeny. It is expected that genetic improvement will be achieved by carrying out direct selective breeding in the common carp.