Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multi-trait and random regression mature weight heritability and breeding value estimates in Nelore cattle

Mature weight breeding values were estimated using a multi-trait animal model (MM) and a random regression animal model (RRM). Data consisted of 82 064 weight records from 8 145 animals, recorded from birth to eight years of age. Weights at standard ages were considered in the MM. All models included contemporary groups as fixed effects, and age of dam (linear and quadratic effects) and animal age as covariates. In the RRM, mean trends were modelled through a cubic regression on orthogonal polynomials of animal age and genetic maternal and direct and maternal permanent environmental effects were also included as random. Legendre polynomials of orders 4, 3, 6 and 3 were used for animal and maternal genetic and permanent environmental effects, respectively, considering five classes of residual variances. Mature weight (five years) direct heritability estimates were 0.35 (MM) and 0.38 (RRM). Rank correlation between sires' breeding values estimated by MM and RRM was 0.82. However, selecting the top 2% (12) or 10% (62) of the young sires based on the MM predicted breeding values, respectively 71% and 80% of the same sires would be selected if RRM estimates were used instead. The RRM modelled the changes in the (co)variances with age adequately and larger breeding value accuracies can be expected using this model. © South African Society for Animal Science.

Estimating an Aggregate Economic Genotype to Facilitate Breeding and Selection of Strawberry Genotypes in Southeast Queensland

The Queensland strawberry (Fragaria ×ananassa) breeding program in subtropical Australia aims to improve sustainable profitability for the producer. Selection must account for the relative economic importance of each trait and the genetic architecture underlying these traits in the breeding population. Our study used estimates of the influence of a trait on production costs and profitability to develop a profitability index (PI) and an economic weight (i.e., change in PI for a unit change in level of trait) for each trait. The economic weights were then combined with the breeding values for 12 plant and fruit traits on over 3000 genotypes that were represented in either the current breeding population or as progenitors in the pedigree of these individuals. The resulting linear combination (i.e., sum of economic weight × breeding value for all 12 traits) estimated the overall economic worth of each genotype as H, the aggregate economic genotype. H values were validated by comparisons among commercial cultivars and were also compared with the estimated gross margins. When the H value of ‘Festival’ was set as zero, the H values of genotypes in the pedigree ranged from –0.36 to +0.28. H was highly correlated (R2 = 0.77) with the year of selection (1945–98). The gross margins were highly linearly related (R2 > 0.98) to H values when the genotype was planted on less than 50% of available area, but the relationship was non-linear [quadratic with a maximum (R2 > 0.96)] when the planted area exceeded 50%. Additionally, with H values above zero, the variation in gross margin increased with increasing H values as the percentage of area planted to a genotype increased. High correlations among some traits allowed the omission of any one of three of the 12 traits with little or no effect on ranking (Spearman’s rank correlation 0.98 or greater). Thus, these traits may be dropped from the aggregate economic genotype, leading to either cost reductions in the breeding program or increased selection intensities for the same resources. H was efficient in identifying economically superior genotypes for breeding and deployment, but because of the non-linear relationship with gross margin, calculation of a gross margin for genotypes with high H is also necessary when cultivars are deployed across more than 50% of the available area.

Pre-emptive breeding to combine superior eating quality in tropical super sweet corn with resistance to major diseases

This report presents the process and outcomes of a five year project, which employed genetics and breeding approach for integrating disease resistance,agronomy and quality traits that enhances sustainable productivity improvement in sweet corn production. The report outlines a molecular markers based approach to introgress quantitative traits loci that are believed to contribute to resistance to downy mildew, a potentially devastating disease that threatens sweet corn and other similar crops. It also details the approach followed to integrate resistances for other major diseases such as southern rust (caused by Puccinia polysora Underw), Northern Corn Leaf Blight (Exserohilum turcicum) with improved agronomy and eating quality. The report explains the importance of heterosis (hybrid vigour) and combining ability in the development of useful sweet corn hybrids. It also explains the relevance of parental performance to predict its breeding value and the performance of its hybrids.

Association of an insulin-like growth factor 1 gene microsatellite with phenotypic variation and estimated breeding values of growth traits in Canchim cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparison of selective genotyping strategies for prediction of breeding values in a population undergoing selection

Genomewide marker information can improve the reliability of breeding value predictions for young selection candidates in genomic selection. However, the cost of genotyping limits its use to elite animals, and how such selective genotyping affects predictive ability of genomic selection models is an open question. We performed a simulation study to evaluate the quality of breeding value predictions for selection candidates based on different selective genotyping strategies in a population undergoing selection. The genome consisted of 10 chromosomes of 100 cM each. After 5,000 generations of random mating with a population size of 100 (50 males and 50 females), generation G(0) (reference population) was produced via a full factorial mating between the 50 males and 50 females from generation 5,000. Different levels of selection intensities (animals with the largest yield deviation value) in G(0) or random sampling (no selection) were used to produce offspring of G(0) generation (G(1)). Five genotyping strategies were used to choose 500 animals in G(0) to be genotyped: 1) Random: randomly selected animals, 2) Top: animals with largest yield deviation values, 3) Bottom: animals with lowest yield deviations values, 4) Extreme: animals with the 250 largest and the 250 lowest yield deviations values, and 5) Less Related: less genetically related animals. The number of individuals in G(0) and G(1) was fixed at 2,500 each, and different levels of heritability were considered (0.10, 0.25, and 0.50). Additionally, all 5 selective genotyping strategies (Random, Top, Bottom, Extreme, and Less Related) were applied to an indicator trait in generation G(0), and the results were evaluated for the target trait in generation G(1), with the genetic correlation between the 2 traits set to 0.50. The 5 genotyping strategies applied to individuals in G(0) (reference population) were compared in terms of their ability to predict the genetic values of the animals in G(1) (selection candidates). Lower correlations between genomic-based estimates of breeding values (GEBV) and true breeding values (TBV) were obtained when using the Bottom strategy. For Random, Extreme, and Less Related strategies, the correlation between GEBV and TBV became slightly larger as selection intensity decreased and was largest when no selection occurred. These 3 strategies were better than the Top approach. In addition, the Extreme, Random, and Less Related strategies had smaller predictive mean squared errors (PMSE) followed by the Top and Bottom methods. Overall, the Extreme genotyping strategy led to the best predictive ability of breeding values, indicating that animals with extreme yield deviations values in a reference population are the most informative when training genomic selection models.

A short critical history of the application of genomics to animal breeding

Two scientific schools have been in coexistence from the beginning of genetics, one of them searching for factors of inheritance and the other one applying biometrical models to study the relationships between relatives. With the development of molecular genetics, the possibilities of detecting genes having a noticeable effect in traits augmented. Some genes with large or medium effects were localized in animals, although the most common result was to detect markers linked to these genes, allowing the possibility of assisting selection programs with markers. When a large amount of simple and inexpensive markers were available, the SNPs, new possibilities were opened since they did not need the presence of genes of large or medium effect controlling a trait, because the whole genome was scanned. Using a large amount of SNPs permits having a prediction of the breeding value at birth accurate enough to be used in some cases, like dairy cattle, to halve its generation interval. In other animal breeding programs, the implementation of genomic selection is less clear and the way in which it can be useful should be carefully studied. The need for large populations for associating phenotypic data and markers, plus the need for repeating the process continuously, complicates its application in some cases. The implementation of the information provided by the SNPs in current genetic programs has led to the development of complex statistical tools, joining the efforts of the two schools, factorial and biometrical, that nowadays work closely related.

A Genetic Analysis of Lysosomal Enzyme Activities in Brahman Cattle

Analyses of variance and co variance were carried out on the activities of three lysosomal enzymes in mononuclear blood cells from Brahman cattle. These were hexosaminidase (HEX), beta-D-galacto-sidase (GAL) and acid alpha-glucosidase (GLU) which had been measured in blood mononuclear cells from 1752 cattle from 6 herds in a Pompe's disease control programme. Herd of origin and date of bleeding significantly affected the level of activity of all enzymes. In addition, HEX and GAL were affected by age and HEX by the sex of the animal bled. Estimates of heritability from sire variances were 0.29:t 0.09 for HEX, 0.31 :t 0.09 for GAL and 0.44:t 0.09 for GLU. Genetic correlations between all enzymes were positive. The data indicate the existence of a major gene causing Pompe's disease and responsible for 16% of the genetic variation in GLU. One standard deviation of selection differential for high GLU should almost eliminate Pompe's disease from the population. The effi-ciency of selection would be aided by estimating the breeding value for GLU using measurements of HEX and GLU and taking account of an animal's sex, age, date of bleeding and herd of origin.

Multi-trait assessment of early-in-life female, male and genomic measures for use in genetic selection to improve female reproductive performance of Brahman cattle

Early-in-life female and male measures with potential to be practical genetic indicators were chosen from earlier analyses and examined together with genomic measures for multi-trait use to improve female reproduction of Brahman cattle. Combinations of measures were evaluated on the genetic gains expected from selection of sires and dams for each of age at puberty (AGECL, i.e. first observation of a corpus luteum), lactation anoestrous interval in 3-year-old cows (LAI), and lifetime annual weaning rate (LAWR, i.e. the weaning rate of cows based on the number of annual matings they experienced over six possible matings). Selection was on an index of comparable records for each combination. Selection intensities were less than theoretically possible but assumed a concerted selection effort was able to be made across the Brahman breed. The results suggested that substantial genetic gains could be possible but need to be confirmed in other data. The estimated increase in LAWR in 10 years, for combinations without or with genomic measures, ranged from 8 to 12 calves weaned per 100 cows from selection of sires, and from 12 to 15 calves weaned per 100 cows from selection of sires and dams. Corresponding reductions in LAI were 60-103 days or 94-136 days, and those for AGECL were 95-125 or 141-176 days, respectively. Coat score (a measure of the sleekness or wooliness of the coat) and hip height in females, and preputial eversion and liveweight in males, were measures that may warrant wider recording for Brahman female reproduction genetic evaluation. Pregnancy-test outcomes from Matings 1 and 2 also should be recorded. Percentage normal sperm may be important to record for reducing LAI and scrotal size and serum insulin-like growth factor-I concentration in heifers at 18 months for reducing AGECL. Use of a genomic estimated breeding value (EBV) in combination with other measures added to genetic gains, especially at genomic EBV accuracies of 40%. Accuracies of genomic EBVs needed to approach 60% for the genomic EBV to be the most important contributor to gains in the combinations of measures studied.

Establishment of satellite nucleus of genetically improved farmed tilapia (GIFT strain) in Bangladesh

The aim of this study was to evaluate growth performance of the GIFT (Genetically Improved Farmed Tilapia) strain after one generation of selection for increased body weight at Bangladesh Fisheries Research Institute. Founder stock comprised of 30 families having 300 individuals of the GIFT strain were introduced from Malaysia through \X!orldFish Center in March 2005. The founder stock was reared in 100 m2 hapa for three months and then individually tagged using Passive Integrated Transponder (PIT) at the weight between 30 and 40 g. After tagging, all the fish were communally grown out in pond until harvest. Breeding value for body weight was estimated using SAS and ASREML ranging from 4.17 to 9.70 g for males and 4.24 to 9.36 g for females. The best 40 females and 40 males from the founder stock were then selected to produce progeny of the first generation (F-1). From each family 25 female and 25 male fingerlings were sampled and tagged using PIT. A total of 2,000 tagged fish from 40 families were stocked in a pond (1000 m2) for a continuation of the selection program. In addition, surplus fish after tagging were also reared together with progeny of the founder stock in cistern ecology for growth evaluation. The mean weight of the F-1 generation of GIFT fish was 7.2% greater than that of the founder population (non selected population).

Prospecting candidate SNPs for backfat in Canchim beef cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Heritabilities and genetic correlations for reproductive traits in an F2 reciprocal cross chicken population

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Selection for higher body weight in Nelore cattle is effective in achieving an increase of longissimus muscle area without reducing subcutaneous fat thickness

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comparações entre os valores genéticos para características de crescimento de bovinos da raça Nelore preditos com modelos de dimensão finita ou infinita

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)