Genetic parameter estimates and response to selection for weight and testicular traits in Nelore cattle

We estimated genetic parameters for various phases of body and testicular growth until 550 days of age in Nelore cattle, using Bayesian inference, including correlation values and error estimates. Weight and scrotal records of 54,182 Nelore animals originating from 18 farms participating in the Brazilian Nelore Breeding Program (PMGRN) were included. The following traits were measured: weight at standard ages of 120 (W120), 210 (W210), 365 (W365), 450 (W450), and 550 (W550) days; weight gain between 120/210 (WG1), 210/365 (WG2), 365/450 (WG3), 450/550 (WG4), 120/365 (WG5), 120/450 (WG6), 120/550 (WG7), 210/450 (WG8), 210/550 (WG9), and 365/550 (WG10) days of age; scrotal circumference at 365 (SC365), 450 (SC450) and 550 (SC550) days of age, and testicular growth between 365/450 (TG1), 450/550 (TG2) and 365/550 (TG3) days of age. The model included contemporary group (current farm, year and two-month period of birth, sex, and management group) and age of dam at calving, divided into classes as fixed effects. The model also included random effects for direct additive, maternal additive and maternal permanent environmental, and residual effects. The direct heritability estimates ranged from 0.23 to 0.39, 0.13 to 0.39 and 0.32 to 0.56 for weights at standard ages, weight gains and testicular measures, respectively. The genetic correlations between weights (0.69 to 0.94) and scrotal circumferences (0.91 to 0.97) measured at standard ages were higher than those between weight gain and testicular growth (0.18 to 0.97 and 0.36 to 0.77, respectively). The weights at standard ages responded more effectively to selection, and also gave strong correlations with the other traits.     

Mathematical model of clonal selection and antibody production. II

Several modifications are proposed to a recent mathematical model (Bell, 1970) of the clonal selection and antibody production which take place when an adult animal is injected with an antigen. In the original model, antigen molecules were assumed univalent, i.e. to have only one combining site per molecule, and the first modification is an allowance for multivalent antigens by permitting an antigen molecule to interact with only one cell at a time. It is found that, for antigens with few (? 10) sites per molecule this modification is not important while for many sites per molecule, the modification will reduce the response as compared to that from the same number of independent antigenic sites. In section 3, it is seen that by restricting the number of cells which can arise in an immune response, much more realistic responses to high antigen doses are obtained. Moreover, the response is made more predictable by assuming that both target and proliferating cells are stimulated by antigen when a fraction of their receptors, between f_min and f_max, is bound to antigen. The parameter f_min is shown to determine the extent to which a molecule which can be recognized by antibodies will also serve as an immunogen giving rise to cellular proliferation and antibody production. In section 4, it is found that if more plasma cells than memory cells result from antigen stimulation, then weak stimulation will lead to a depletion of target plus memory cells and to at least partial immunological paralysis. Optimum antigen doses and times for the induction of such paralysis are examined. In section 5, precipitation of antigen-antibody mixtures is considered and it is shown that the number of doubly bound antibody molecules per antigen site determines whether precipitation will occur. This number is easily computed for heterogeneous bivalent antibodies.     

Genetic parameters and selection efficiency using part-records for production traits in strawberries

Summary The efficiency of selection for yield and fruit size using parts of the complete-season record was evaluated using data collected for individual strawberry seedlings (Fragaria x annanasa) in four genetic tests. Part-records were generated for each trait using cumulative weekly sums, and these were compared with complete records to assess the value of extended data collection. In addition, part-records were generated using data from alternate weeks of harvest. Scoring separate sets of seedlings in alternate weeks was assumed to allow a doubling of the unselected population size, halving the selection proportion and increasing selection intensity. Heritabilities estimated for part-records were often larger for mid-season cumulative part-records than for the complete-season records. Seasonal patterns for broad-sense and narrow-sense heritabilities differed, suggesting temporal expression of genes that condition yield and fruit size. Predicted genetic gains were largest using cumulative part-records between 4 and 12 weeks of the 15-week season, depending on trait and breeding objective (breeding value versus clonal value), with 8–9 weeks as a reasonable compromise. Selection using alternate-weeks records was identified as an efficient alternative to selection using total complete-season records. Superiority of the alternate-weeks option depends on the balance between increased selection intensity and decreased individual genetic information, and will differ for specific traits and program designs.     

Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model

Background

Genomic selection involves breeding value estimation of selection candidates based on high-density SNP genotypes. To quantify the potential benefit of genomic selection, accuracies of estimated breeding values (EBV) obtained with different methods using pedigree or high-density SNP genotypes were evaluated and compared in a commercial layer chicken breeding line.

Methods

The following traits were analyzed: egg production, egg weight, egg color, shell strength, age at sexual maturity, body weight, albumen height, and yolk weight. Predictions appropriate for early or late selection were compared. A total of 2,708 birds were genotyped for 23,356 segregating SNP, including 1,563 females with records. Phenotypes on relatives without genotypes were incorporated in the analysis (in total 13,049 production records).The data were analyzed with a Reduced Animal Model using a relationship matrix based on pedigree data or on marker genotypes and with a Bayesian method using model averaging. Using a validation set that consisted of individuals from the generation following training, these methods were compared by correlating EBV with phenotypes corrected for fixed effects, selecting the top 30 individuals based on EBV and evaluating their mean phenotype, and by regressing phenotypes on EBV.

Results

Using high-density SNP genotypes increased accuracies of EBV up to two-fold for selection at an early age and by up to 88% for selection at a later age. Accuracy increases at an early age can be mostly attributed to improved estimates of parental EBV for shell quality and egg production, while for other egg quality traits it is mostly due to improved estimates of Mendelian sampling effects. A relatively small number of markers was sufficient to explain most of the genetic variation for egg weight and body weight.     

Evolutionary rates for multivariate traits: the role of selection and genetic variation

A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders'' equation (), which predicts evolutionary change for a suite of phenotypic traits () as a product of directional selection acting on them (β) and the genetic variance–covariance matrix for those traits (G). Despite being empirically challenging to estimate, there are enough published estimates of G and β to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are, in part, due to genetic architecture. We find some evidence that sexually selected traits exhibit faster rates of evolution compared with life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G, we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates.     

Detection of loci affecting milk production and health traits in an elite US Holstein population using microsatellite markers

Quantitative trait loci (QTL) affecting health and milk production traits were studied in seven large half-sib US Holstein families by using the granddaughter design. Genotyping for 16 markers was completed and marker allele differences within and pooled-across families were analysed. Potential QTL were identified for somatic cell score (SCS), fat yield, fat percentage, protein yield and protein percentage. Three markers (BM203, BM4505 and BM2078) were associated with significant effects for different traits and, after further analysis, may be useful in marker-assisted selection in specific families. Comparisons between these data and previously identified QTL support the location of a QTL for milk yield and protein yield on chromosome 21.     

Analysis of water intake, dry matter intake and daily milk yield using different error covariance structures

The aim of the present study was to investigate the daily measured traits milk yield, water intake and dry matter intake with fixed and random regression models added with different error covariance structures. It was analysed whether these models deliver better model fitting in contrast to conventional fixed and random regression models. Furthermore, possible autocorrelation between repeated measures was investigated. The effect of model choice on statistical inference was also tested. Data recording was performed on the Futterkamp dairy research farm of the Chamber of Agriculture of Schleswig-Holstein. A dataset of about 21 000 observations from 178 Holstein cows was used. Average milk yield, water intake and dry matter intake were 34.9, 82.4 and 19.8 kg, respectively. Statistical analysis was performed using different linear mixed models. Lactation number, test day and the parameters to model the function of lactation day were included as fixed effects. Different structures were tested for the residuals; they were compared for their ability to fit the model using the likelihood ratio test, and Akaike's and Bayesian's information criteria. Different autocorrelation patterns were found. Adjacent repeated measures of daily milk yield were highest correlated (p1 = 0.32) in contrast to measures further apart, while for water intake and dry matter intake, the measurements with a lag of two units had the highest correlations with p2 = 0.11 and 0.12. The covariance structure of TOEPLITZ was most suitable to indicate the dependencies of the repeated measures for all traits. Generally, the most complex model, random regression with the additional covariance structure TOEPLITZ(4), provided the lowest information criteria. Furthermore, the model choice influenced the significance values of one fixed effect and therefore the general inference of the data analysis. Thus, the random regression + TOEPLITZ(4) model is recommended for use for the analysis of equally spaced datasets of milk yield, water intake and dry matter intake.     

Identification of insulin receptor systems: assessing the impact of model selection and measurement error on precision of parameter estimates using Monte Carlo study

An extensive Monte Carlo study has been carried out in order to study the effect of measurement error on the precision of parameter estimates of an insulin binding system. Hypothetical radioimmunoassay experiments were generated for insulin binding to erythrocytes. The design of experiments followed strictly the protocol of real experiments. Randomly generated error was added to the synthetic data. The standard technique, a weighted non-linear regression analysis, was employed to re-estimate parameters of a model of two receptor sites and a model of negative co-operativity. As the original parameter values were known, the differences between original and estimated values was studied for (a) measurement error in the range from 0-17%, (b) random initial estimates and (c) error-free non-specific binding. In addition, analytical estimates of parameter precision were compared with the true between-experiment variation of parameter estimates. At the measurement error of 12%, a one site model is recommended to estimate the high affinity population of the two sites model. Plausible results can be expected in 90% of experiments, the between-experiment variation being approximately 30%. The model of two receptor sites gives approximately two thirds of plausible results. The high affinity population can be estimated with the between-experiment variation of 40%, the low affinity population is virtually unidentifiable with the between-experiment variation of approximately 100% and parameter estimates biased to higher values. Only half of the results obtained from the model of negative co-operativity are plausible, the variation in parameter estimates ranges from 90-150% and estimates are biased to higher values. At the level of 12% measurement error, random initial estimates do not significantly affect the estimation process, provided initial estimates are selected from a feasible range. At the same measurement error, the error-free non-specific binding does not improve the results, indicating that the mean of six replicates may be taken as a reliable estimate of non-specific binding. The analytical estimates of the coefficient of variation systematically underestimates the true between-experiments coefficient of variation, the difference has been found to be about 50%.     

Mapping quantitative trait loci (QTL) in sheep. II. Meta-assembly and identification of novel QTL for milk production traits in sheep

An (Awassi × Merino) × Merino backcross family of 172 ewes was used to map quantitative trait loci (QTL) for different milk production traits on a framework map of 200 loci across all autosomes. From five previously proposed mathematical models describing lactation curves, the Wood model was considered the most appropriate due to its simplicity and its ability to determine ovine lactation curve characteristics. Derived milk traits for milk, fat, protein and lactose yield, as well as percentage composition and somatic cell score were used for single and two-QTL approaches using maximum likelihood estimation and regression analysis. A total of 15 significant (P < 0.01) and additional 25 suggestive (P < 0.05) QTL were detected across both single QTL methods and all traits. In preparation of a meta-analysis, all QTL results were compared with a meta-assembly of QTL for milk production traits in dairy ewes from various public domain sources and can be found on the ReproGen ovine gbrowser http://crcidp.vetsci.usyd.edu.au/cgi-bin/gbrowse/oaries_genome/. Many of the QTL for milk production traits have been reported on chromosomes 1, 3, 6, 16 and 20. Those on chromosomes 3 and 20 are in strong agreement with the results reported here. In addition, novel QTL were found on chromosomes 7, 8, 9, 14, 22 and 24. In a cross-species comparison, we extended the meta-assembly by comparing QTL regions of sheep and cattle, which provided strong evidence for synteny conservation of QTL regions for milk, fat, protein and somatic cell score data between cattle and 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.     

Application of the covariance function approach with an iterative two-stage algorithm to the estimation of parameters of a random regression test day model for dairy production traits

The covariance function approach with an iterative two-stage algorithm of LIU et al. (2000) was applied to estimate parameters for the Polish Black-and-White dairy population based on a sample of 338 808 test day records for milk, fat, and protein yields. A multiple trait sire model was used to estimate covariances of lactation stages. A third-order Legendre polynomial was subsequently fitted to the estimated (co)variances to derive (co)variances of random regression coefficients for both additive genetic and permanent environment effects. Daily and 305-day heritability estimates obtained are consistent with several studies which used both fixed and random regression test day models. Genetic correlations between any two days in milk (DIM) of the same lactation as well as genetic correlations between the same DIM of two lactations were within a biologically acceptable range. It was shown that the applied estimation procedure can utilise very large data sets and give plausible estimates of (co)variance components.     

Potential bias in inbreeding depression estimates when using pedigree relationships to assess the degree of homozygosity for loci under selection

A potential bias in estimation of inbreeding depression when using pedigree relationships to assess the degree of homozygosity for loci under selection is indicated. A comparison of inbreeding coefficients based on either pedigree or genotypic frequencies indicated that, as a result of selection, the inbreeding coefficient based on pedigree might not correspond with the random drift of allelic frequencies. Apparent differences in average levels of both inbreeding coefficients were obtained depending on the genetic model (additive versus dominance, initial allelic frequencies, heritability) and the selection system assumed (no versus mass selection). In the absence of selection, allelic frequencies within a small population change over generations due to random drift, and the pedigree-based inbreeding coefficient gives a proper assessment of the accompanying probability of increased homozygosity within a replicate by indicating the variance of allelic frequencies over replicates. With selection, in addition to random drift, directional change in allelic frequencies is not accounted for by the pedigree-based inbreeding coefficient. This result implies that estimation of inbreeding depression for traits under either direct or indirect selection, estimated by a regression of performance on pedigree-based coefficients, should be carefully interpreted.Deceased     

Anaerobic digestion model No. 1-based distributed parameter model of an anaerobic reactor: II. Model validation

In this study, an ADM1-based distributed parameter model was validated using experimental results obtained in a laboratory-scale 10 L UASB reactor. Sensitivity analysis of the model parameters was used to select four parameters for estimation by a numerical procedure while other parameters were accepted from ADM1 benchmark simulations. The parameter estimation procedure used measurements of liquid phase components obtained at different sampling points in the reactor and under different operating conditions. Model verification used real time fluorescence-based measurements of chemical oxygen demand and volatile fatty acids at four sampling locations in the reactor. Overall, the distributed parameter model was able to describe the distribution of liquid phase components in the reactor and adequately simulated the effect of external recirculation on degradation efficiency. The model can be used in the design, analysis and optimization of UASB reactors.     

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.     

Selection for litter size in pigs. II. Efficiency of closed and open selection lines*

A selection experiment on litter size in the pig was carried on for seventeen generations in an Inra experimental herd. The founder population was made up of 10 males and 120 females from the Large White breed. Selection was first performed for ten generations in a closed line, compared to a control line derived from the same founder population. Selection was carried on within sire family on the total number of piglets born in the first two litters of the dam (TB1 + TB2). After ten generations, the selection criterion became dam TB1 only. The control line was then discontinued and a panel of frozen semen from the 11th generation boars was created for later comparisons. The selected line was opened to gilt daughters of hyperprolific boars and sows, at a rate of 1/8 per generation, and the same selection procedure was applied irrespective of the origin of the gilt. During the whole experiment, the number of ova shed (OS) and the number of live embryos (LE) at 30 days in the 3rd pregnancy were recorded. These two parts of the experiment were analysed using REML estimation of genetic parameters and a BLUP-Animal Model in order to estimate the responses to selection. Significant heritabilities for TB1, TB2, OS and LE were obtained, i.e. 0.10, 0.05, 0.43 and 0.19, respectively. Significant common environment variances and covariances were estimated for nearly all traits. Significantly positive BLUP responses per generation were observed from G0 to G17 for TB1 (+0.086), TB2 (+0.078), OS (+0.197) and LE (+0.157). However, the responses were 3- to 4-fold higher in the G12–G17 interval compared to G0–G11, and they were also in fair agreement with previous estimates based on standard least-squares procedures, using the control line and the control frozen semen panel. Since G11, the selection intensity was increased by nearly 80 p. cent compared to the previous generations, and the proportion of hyperprolific ancestry increased up to 65 p. cent in the sows of the last generation. The total genetic gain of about 1.4 piglets at birth per litter could be shared between a gain due to immigration, of about 0.8 piglets per litter, and a within-line selection gain of about 0.6 piglets. Thus by combining selection and immigration in the second part of the experiment, advantage could be taken from both the genetic superiority of the immigrants and the higher internal selection intensity made possible by immigration.     

The selection of an adjuvant emulsion for polyclonal antibody production using a low-molecular-weight antigen in rabbits.

Although Freund's adjuvant has been used for decades as an immune enhancer in rabbits, adverse physiologic side effects have prompted the search for more suitable alternatives. We used osteocalcin, a bovine bone protein (M.W. 5,800), as the test antigen to evaluate four adjuvant regimens: a) primary inoculation with complete Freund's adjuvant (CFA) followed by three boosts with incomplete Freund's adjuvant (IFA), b) four serial inoculations with RIBI MPL+TDM+CWS adjuvant, c) four serial inoculations with TiterMax #R-1, and d) primary inoculation (only) with TiterMax #R-1. The antibody yield associated with the CFA/IFA regimen (mean OD = 2.152) was at least sixfold that of either TiterMax (mean OD = 0.358) or RIBI (mean OD = 0.239) multiple injection regimens. No antibody response was observed after the single injection of TiterMax antigen emulsion. Maximal antibody production occurred rapidly in response to Freund's adjuvant (day 31) as compared with TiterMax (day 74) and RIBI (day 66).     

Novel linkage mapping approach using DNA pooling in human and animal genetics. II. Detection of quantitative traits loci in dairy cattle

Selective DNA pooling is an advanced methodology for linkage mapping of quantitative trait loci (QTL) in farm animals. The principle is based on densitometric estimates of marker allele frequency in pooled DNA samples of phenotypically extreme individuals from half-sib, backcross and F(2) experimental designs in farm animals. This methodology provides a rapid and efficient analysis of a large number of individuals with short tandem repeat markers that are essential to detect QTL through the genome - wide searching approach. Several strategies involving whole genome scanning with a high statistical power have been developed for systematic search to detect the quantitative traits loci and linked loci of complex traits. In recent studies, greater success has been achieved in mapping several QTLs in Israel-Holstein cattle using selective DNA pooling. This paper outlines the currently emerged novel strategies of linkage mapping to identify QTL based on selective DNA pooling with more emphasis on its theoretical pre-requisite to detect linked QTLs, applications, a general theory for experimental half-sib designs, the power of statistics and its feasibility to identify genetic markers linked QTL in dairy cattle. The study reveals that the application of selective DNA pooling in dairy cattle can be best exploited in the genome-wide detection of linked loci with small and large QTL effects and applied to a moderately sized half-sib family of about 500 animals.     

Estimates of genetic parameters and genetic trends for growth,reproduction, milk production and milk composition traits of Awassi sheep

Genetic parameters and genetic trends for growth, reproduction, milk production and composition traits were estimated for Syrian (S) and Turkish (T) Awassi sheep and their crosses maintained at the International Center for Agricultural Research in the Dry Areas Tal Hadya station, Aleppo, Syria (now in Terbol station in Lebanon). The data were spread over 9 years. The individual breed additive effects of T were positive and significant (P<0.05) for birth weight (BW). However, the values for weaning weight (WW) and pre-weaning weight gain (WG) were negative, even though they were significant (P<0.05). These estimates were positive and significant (P<0.05) for all reproduction and milk traits, except for litter weight at birth (LWB). The additive contributions of T were 60.72±0.94 days, 1.643±0.359 kg, 13.09±0.89 days, 16.13±0.89 kg, 1.12±0.44 kg, 0.71±0.26 kg, 2.80±0.72 kg and 0.83±0.32 kg for lambing interval (LI), litter weight at weaning (LWW), lactation length, milk yield, fat yield, protein yield, total solids yield and lactose yield, respectively. The heterosis effects, both individual and maternal, were non-significant (P>0.05) for most growth traits. Crossing of T with S, however, resulted in desirable and significant (P<0.05) individual heterosis effects for all the reproduction, milk production and constituent yields. The heritability (h²) estimates, both direct and maternal, were low for BW, WW, WG and all reproductive traits indicating major influence of environmental factors, whereas milk yield and composition had medium values. Birth weight had moderate genetic correlation with WW and WG. The genetic correlation between WW and WG was high (0.724±0.951). Lambing interval had large negative genetic correlation with LWB and LWW. However, LI had medium significant correlations with all the milk production and composition traits. Larger litter weights at birth had high and negative influence on milk yield of the dam and its constituents. Genetic changes over years for all traits were non-significant. The lack of genetic change in the studied traits calls for systematic and organized selection scheme.