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The objectives of this study were to estimate the additive and dominance variance component of several weight and ultrasound scanned body composition traits in purebred and combined cross-bred sheep populations based on single nucleotide polymorphism ( SNP) marker genotypes and then to investigate the effect of fitting additive and dominance effects on accuracy of genomic evaluation. Additive and dominance variance components were estimated in a mixed model equation based on 'average information restricted maximum likelihood' using additive and dominance (co)variances between animals calculated from 48,599 SNP marker genotypes. Genomic prediction was based on genomic best linear unbiased prediction ( GBLUP), and the accuracy of prediction was assessed based on a random 10-fold cross-validation. Across different weight and scanned body composition traits, dominance variance ranged from 0.0% to 7.3% of the phenotypic variance in the purebred population and from 7.1% to 19.2% in the combined cross-bred population. In the combined cross-bred population, the range of dominance variance decreased to 3.1% and 9.9% after accounting for heterosis effects. Accounting for dominance effects significantly improved the likelihood of the fitting model in the combined cross-bred population. This study showed a substantial dominance genetic variance for weight and ultrasound scanned body composition traits particularly in cross-bred population; however, improvement in the accuracy of genomic breeding values was small and statistically not significant. Dominance variance estimates in combined cross-bred population could be overestimated if heterosis is not fitted in the model. [ABSTRACT FROM AUTHOR]

Heritabilities and genetic correlations for milk production traits were estimated from first-parity test day records on 1022 Philippine dairy buffalo cows. Traits analysed included milk (MY), fat (FY) and protein (PY) yields, and fat (Fat%) and protein (Prot%) concentrations. Varying orders of Legendre polynomials (Legm) as well as the Wilmink function (Wil) were used in random regression models. These various models were compared based on log likelihood, Akaike's information criterion, Bayesian information criterion and genetic variance estimates. Six residual variance classes were sufficient for MY, FY, PY and Fat%, while seven residual classes for Prot%. Multivariate analysis gave higher estimates of genetic variance and heritability compared with univariate analysis for all traits. Heritability estimates ranged from 0.25 to 0.44, 0.13 to 0.31 and 0.21 to 0.36 for MY, FY and PY, respectively. Wilmink's function was the better fitting function for additive genetic effects for all traits. It was also the preferred function for permanent environment effects for Fat% and Prot%, but for MY, FY and PY, the Legm was the appropriate function. Genetic correlations of MY with FY and PY were high and they were moderately negative with Fat% and Prot%. To prevent deterioration in Fat% and Prot% and improve milk quality, more weight should be applied to milk component traits. [ABSTRACT FROM AUTHOR]

Genetic correlations for body measurements and subjectively scored traits between foals and studbook horses were estimated using bivariate linear mixed models. Observations for nine foal and eleven studbook traits in Finnhorses on 6529 foals and 6596 studbook horses and in Standardbred trotters on 3069 foals and 2112 studbook horses were available from the Finnish horse breeding shows. The number of sires with progeny in both foal and studbook data was 203 in Finnhorse and 145 in Standardbred trotters. Estimates of heritability for body measurements in foals and studbook horses using univariate models were high in both breeds (0.41-0.84). Heritability estimates for subjectively scored traits using univariate models were generally higher for foals (0.08-0.46) than for studbook horses (0.06-0.21) in both breeds. Genetic correlations between foals and studbook horses for body measurements were highly positive ranging from 0.74 to 0.96 in Finnhorses and from 0.79 to 0.99 in Standardbred trotters. Low to highly positive genetic correlations between foals and studbook horses for subjectively scored traits were obtained in Finnhorse trotters, whereas in Standardbred trotters genetic correlations for subjectively scored traits varied from moderately negative to highly positive. Higher estimates of heritability for foal traits and generally high genetic correlations between the foal and studbook traits indicate that an early selection for conformation traits would be efficient in the breeding programmes. [ABSTRACT FROM AUTHOR]

Three microsatellite markers on goat chromosome 23 adjacent to the MHC were used to test for quantitative trait loci (QTL) affecting faecal worm egg count (WEC) and leukocyte traits in ten Australian Angora and twelve Australian Cashmere half-sib families (n = 16–57 per family). Data were collected from 280 Angora and 347 Cashmere kids over a 3- and 4-year period. A putative QTL affecting trichostrongyle WEC was found in two small families at the 5% chromosome-wise threshold level. The biggest QTL effect for WEC of 1.65 standard deviations (σp) was found within the region of OarCP73- BM1258. A significant QTL affecting blood eosinophil counts at the 1% chromosome–wise threshold level was detected at marker BM1258 (at 26 cM) in two Angora and Cashmere families. The magnitude of the putative QTL was 0.69 and 0.85 σp in Angora and Cashmere families, respectively. Due to the comparatively low power of the study these findings should be viewed as indicative rather than definitive. [ABSTRACT FROM AUTHOR]

Optimal selection on a single identified quantitative trait locus (QTL) with four modes of inheritance: normal autosomal, sex-limited, imprinting and X-linked, was evaluated in four breeding structures: single line selection (SLS), two-way crossing (2WC), three-way crossing (3WC) and reciprocal crossing (RC) by comparing extra benefit from mate selection over index selection to demonstrate effectiveness of mate selection in exploiting non-additive QTL. The results showed that the superiority varied at different QTL inheritance modes, initial favourable allele frequencies and breeding structures. The superiority tended to decrease with the increase of the favourable allele frequency except for over-dominant QTL and imprinted QTL in all breeding structures. Less superiority (below 9%) was observed for a recessive and a fully dominant QTL than for an over-dominant QTL (up to 27.11%). Normal autosomal and sex-linked QTL led to a similar trend of superiority from mate selection but the magnitude of the superiority with the latter was slightly higher than with the former for most combinations of the parameters. A high superiority (6.41–41.54%) was observed from mate selection over index selection for an imprinted QTL. A maternally imprinted QTL tended to lead to higher superiority from mate selection than a paternally imprinted QTL. X-linked QTL led to less superiority from mate selection than the other modes of QTL. A larger superiority from mate selection was observed for a recessive and a fully dominant QTL in structures 3WC and 2WC than structures RC and SLS. The superiority from autosomal QTL and X-linked QTL was lower in the structure RC than in other structures examined. [ABSTRACT FROM AUTHOR]

Summary: With the new opportunities from DNA technology, multitier breeding schemes have the potential to become more effective and more integrated. Integrated breeding schemes can also be better adapted to account for potential genotype by environment interactions (G × E) between tiers. In this case, phenotypic and genotype information from lower tiers becomes more valuable as it involves measurement of traits that directly represent the breeding objective. The objective of this study was to compare scenarios that represented different selection strategies and their economic effectiveness in fine‐wool commercial sheep operations that exploit multitier breeding structures. Genomic selection (GS) applied in the multiplier and the commercial tier presented the largest additional revenue among all scenarios, as it resulted in the largest amount of genetic progress. The largest benefits from GS were outweighed by the genotyping costs, which made DNA parentage the most feasible strategy for the multiplier tier, resulting in the highest cumulative net present value (CNPV). The benefits of phenotypes and genotype information from the commercial environment were larger in the presence of G × E between the nucleus and the commercial tier. The CNPV was larger with a 50% reduction in genotyping costs, which increased the returns of GS scenarios by 2.7‐fold on average. Higher selection intensity when selecting multiplier rams also resulted in larger benefits. In this case, returns for the breeding scheme were 3.5‐fold higher when 33% of multiplier males were selected based on commercial information, compared to scenarios selecting 50% of the available multiplier rams. The benefits of collecting commercial phenotypes and genotypes were long term, which means that return on investment often took more than 10 years to be achieved, and were largely dependent on two‐stage selection to reduce cost while maintaining selection efficiency and on the cost of a genotype test. [ABSTRACT FROM AUTHOR]

A multi-trait (MT) random regression (RR) test day (TD) model has been developed for genetic evaluation of somatic cell scores for Australian dairy cattle, where first, second and third lactations were considered as three different but correlated traits. The model includes herd-test-day, year-season, age at calving, heterosis and lactation curves modelled with Legendre polynomials as fixed effects, and random genetic and permanent environmental effects modelled with Legendre polynomials. Residual variance varied across the lactation trajectory. The genetic parameters were estimated usingasreml. The heritability estimates ranged from 0.05 to 0.16. The genetic correlations between lactations and between test days within lactations were consistent with most of the published results. Preconditioned conjugate gradient algorithm with iteration on data was implemented for solving the system of equations. For reliability approximation, the method of Tier and Meyer was used. The genetic evaluation system was validated with Interbull validation method III by comparing proofs from a complete evaluation with those from an evaluation based on a data set excluding the most recent 4 years. The genetic trend estimate was in the allowed range and correlations between the two sets of proofs were very high. Additionally, the RR model was compared to the previous test day model. The correlations of proofs between both models were high (0.97) for bulls with high reliabilities. The correlations of bulls decreased with increasing incompleteness of daughter performance information. The correlations between the breeding values from two consecutive runs were high ranging from 0.97 to 0.99. The MT RR TD model was able to make effective use of available information on young bulls and cows, and could offer an opportunity to breeders to utilize estimated breeding values for first and later lactations. [ABSTRACT FROM AUTHOR]

Genetic parameters for carcass and meat quality traits of about 18-month-old Merino rams (n = 5870), the progeny of 543 sires from three research resource flocks, were estimated. The estimates of heritability for hot carcass weight (HCW) and the various fat and muscle dimension measurements were moderate and ranged from 0.20 to 0.37. The brightness of meat (colour L*, 0.18 ± 0.03 standard error) and meat pH (0.22 ± 0.03) also had moderate estimates of heritability, although meat relative redness (colour a*, 0.10 ± 0.03) and relative yellowness (colour b*, 0.10 ± 0.03) were lower. Heritability estimates for live weights were moderate and ranged from 0.29 to 0.41 with significant permanent maternal environmental effects (0.13 to 0.10). The heritability estimates for the hogget wool traits were moderate to high and ranged from 0.27 to 0.60. The ultrasound measurements of fat depth (FATUS) and eye muscle depth (EMDUS) on live animals were highly genetically correlated with the corresponding carcass measurements (0.69 ± 0.09 FATC and 0.77 ± 0.07 EMD). Carcass tissue depth (FATGR) had moderate to low genetic correlations with carcass muscle measurements [0.18 ± 0.10 EMD and 0.05 ± 0.10 eye muscle area (EMA)], while those with FATC were negative. The genetic correlation between EMD and eye muscle width (EMW) was 0.41 ± 0.08, while EMA was highly correlated with EMD (0.89 ± 0.0) and EMW (0.78 ± 0.04). The genetic correlations for muscle colour with muscle measurements were moderately negative, while those with fat measurements were close to zero. Meat pH was positively correlated with muscle measurements (0.14 to 0.17) and negatively correlated with fat measurements (−0.06 to −0.18). EMDUS also showed a similar pattern of correlations to EMD with meat quality indicator traits, although FATUS had positive correlations with these traits which were generally smaller than their standard error. The genetic correlations among the meat colour traits were high and positive while those with meat pH were high and negative, which were all in the favourable direction. Generally, phenotypic correlations were similar or slightly lower than the corresponding genetic correlations. There were generally small to moderate negative genetic correlations between clean fleece weight (CFW) and carcass fat traits while those with muscle traits were close to zero. As the Merino is already a relatively lean breed, this implies that particular attention should be given to this relationship in Merino breeding programmes to prevent the reduction of fat reserves as a correlated response to selection for increased fleece weight. The ultrasound scan traits generally showed a similar pattern to the corresponding carcass fat and muscle traits. There was a small unfavourable genetic correlation between CFW and meat pH (0.19 ± 0.07). [ABSTRACT FROM AUTHOR]

Data from seven research resource flocks across Australia were combined to provide accurate estimates of genetic correlations among production traits in Merino sheep. The flocks represented contemporary Australian Merino fine, medium and broad wool strains over the past 30 years. Over 110 000 records were available for analysis for each of the major wool traits, and 50 000 records for reproduction and growth traits with over 2700 sires and 25 000 dams. Individual models developed from the single trait analyses were extended to the various combinations of two-trait models to obtain genetic correlations among six wool traits [clean fleece weight (CFW), greasy fleece weight, fibre diameter (FD), yield, coefficient of variation of fibre diameter and standard deviation of fibre diameter], four growth traits [birth weight, weaning weight, yearling weight (YWT), and hogget weight] and four reproduction traits [fertility, litter size, lambs born per ewe joined, lambs weaned per ewe joined (LW/EJ)]. This study has provided for the first time a comprehensive matrix of genetic correlations among these 14 wool, growth and reproduction traits. The large size of the data set has also provided estimates with very low standard errors. A moderate positive genetic correlation was observed between CFW and FD (0.29 ± 0.02). YWT was positively correlated with CFW (0.23 ± 0.04), FD (0.17 ± 0.04) and LWEJ (0.58 ± 0.06), while LW/EJ was negatively correlated with CFW (−0.26 ± 0.05) and positively correlated with FD (0.06 ± 0.04) and LS (0.68 ± 0.04). These genetic correlations, together with the estimates of heritability and other parameters provide the basis for more accurate prediction of outcomes in complex sheep-breeding programmes designed to improve several traits. [ABSTRACT FROM AUTHOR]