A comparison of genetic and genomic breeding values in Saanen and Alpine goats

Nowadays, several countries are developing or adopting genomic selection in the dairy goat sector. The most used method to estimate breeding values is Single-Step Genomic Best Linear Unbiased Prediction (ssGBLUP) which offers several advantages in terms of computational process and accuracy of the estimated breeding values (EBVs). Saanen and Alpine are the predominant dairy goat breeds in Italy, and both have similar breeding programs where EBVs for productive traits are currently calculated using BLUP. This work describes the implementation of genomic selection for these two breeds in Italy, aligning with the selection practices already carried out in the international landscape. The available dataset included 3 611 genotyped animals, 11 470 lactation records, five traits (milk, protein and fat yields, and fat and protein percentages), and three-generation pedigrees. EBVs were estimated using BLUP, GBLUP, and ssGBLUP both with single and multiple trait approaches. The methods were compared in terms of correlation between EBVs and genetic trends. Results were also validated with the linear regression method excluding part of the phenotypic data. In both breeds, EBVs and GEBVs were strongly correlated and the trend of each trait was similar comparing the three methods. The average increase in accuracy across traits and methods amounted to +13 and +10% from BLUP to ssGBLUP for Alpine and Saanen breeds, respectively. Results indicated higher prediction accuracy and correlation for GBLUP and ssGBLUP compared to BLUP, implying that the use of genotypes increases the accuracy of EBVs, particularly in the absence of phenotypic data. Therefore, ssGBLUP is likely to be the most effective method to enhance genetic gain in Italian Saanen and Alpine goats.

Impact of heat stress on genetic evaluation of oocyte and embryo production in Gir dairy cattle

Identifying and selecting genotypes tolerant to heat stress might improve reproductive traits in dairy cattle, including oocyte and embryo production. The temperature-humidity index (THI) was used, via random regression models, to investigate the impact of heat stress on genetic parameters and breeding values of oocyte and embryo production in Gir dairy cattle. We evaluated records of total oocytes (TO), viable oocytes (VO), cleaved embryos (CE), and viable embryos (VE) from dairy Gir donors. Twenty-four models were tested, considering age at ovum pick-up (AOPU) and THI means as a regressor in the genetic evaluation. We computed THI in eight periods, from 0 to 112 days before ovum pick-up, which were adjusted by different orders of Legendre polynomials (second, third, and fourth). The best-fit model according to Akaike's information criterion (AIC) and Model Posterior Probabilities (MPP) considered Legendre polynomials of third order and THI means of 112 days for TO, fourth order and 56 days for VO, second order and 28 days for CE, and second order and 42 days for VE, respectively. The heritability (h2) estimates across AOPU and THI scales ranged from 0.34 to 0.62 for TO, 0.31 to 0.58 for VO, 0.26 to 0.39 for CE, and 0.15 to 0.26 for VE, respectively. The fraction of the phenotypic variance explained by the permanent environment in different AOPU and THI scales ranged from 0.03 to 0.25 for TO, 0.05 to 0.26 for VO, 0.09 to 0.36 for CE, and 0.15 to 0.27 for VE, respectively. Spearman's rank correlation between the estimated breeding values in different AOPU and THI scale from the top 5% sires and females ranged from 0.18 to 0.90 for TO, 0.31 to 0.95 for VO, 0.14 to 0.85 for CE, and 0.47 to 0.94 for VE, respectively. The h2 estimates for all evaluated traits varied from moderate to high magnitude across AOPU and THI scales, indicating that genetic selection can result in rapid genetic progress for the evaluated traits. There was a reranking among the best animals in different AOPU and THI. It is possible to select dairy Gir cattle tolerant to heat stress to improve oocyte and embryo production.

Understanding the underlying genetic mechanisms for age at first calving, inter-calving period and scrotal circumference in Bonsmara cattle

BACKGROUND

Reproduction is a key feature of the sustainability of a species and thus represents an important component in livestock genetic improvement programs. Most reproductive traits are lowly heritable. In order to gain a better understanding of the underlying genetic basis of these traits, a genome-wide association was conducted for age at first calving (AFC), first inter-calving period (ICP) and scrotal circumference (SC) within the South African Bonsmara breed. Phenotypes and genotypes (120,692 single nucleotide polymorphisms (SNPs) post editing) were available on 7,128 South African Bonsmara cattle; the association analyses were undertaken using linear mixed models.

RESULTS

Genomic restricted maximum likelihood analysis of the 7,128 SA Bonsmara cattle yielded genomic heritability's of 0.183 (SE = 0.021) for AFC, 0.207 (SE = 0.022) for ICP and 0.209 (SE = 0.019) for SC. A total of 16, 23 and 51 suggestive (P ≤ 4 × 10-6) SNPs were associated with AFC, ICP and SC, while 11, 11 and 44 significant (P ≤ 4 × 10-7) SNPs were associated with AFC, ICP and SC respectively. A total of 11 quantitative trait loci (QTL) and 11 candidate genes were co-located with these associated SNPs for AFC, with 10 QTL harbouring 11 candidate genes for ICP and 41 QTL containing 40 candidate genes for SC. The QTL identified were close to genes previously associated with carcass, fertility, growth and milk-related traits. The biological pathways influenced by these genes include carbohydrate catabolic processes, cellular development, iron homeostasis, lipid metabolism and storage, immune response, ovarian follicle development and the regulation of DNA transcription and RNA translation.

CONCLUSIONS

This was the first attempt to study the underlying polymorphisms associated with reproduction in South African beef cattle. Genes previously reported in cattle breeds for numerous traits bar AFC, ICP or SC were detected in this study. Over 20 different genes have not been previously reported in beef cattle populations and may have been associated due to the unique genetic composite background of the SA Bonsmara breed.

Genome-wide association mapping and genomic prediction of agronomical traits and breeding values in Iranian wheat under rain-fed and well-watered conditions

BACKGROUND

The markers detected by genome-wide association study (GWAS) make it possible to dissect genetic structure and diversity at many loci. This can enable a wheat breeder to reveal and used genomic loci controlling drought tolerance. This study was focused on determining the population structure of Iranian 208 wheat landraces and 90 cultivars via genotyping-by-sequencing (GBS) and also on detecting marker-trait associations (MTAs) by GWAS and genomic prediction (GS) of wheat agronomic traits for drought-tolerance breeding. GWASs were conducted using both the original phenotypes (pGWAS) and estimated breeding values (eGWAS). The bayesian ridge regression (BRR), genomic best linear unbiased prediction (gBLUP), and ridge regression-best linear unbiased prediction (rrBLUP) approaches were used to estimate breeding values and estimate prediction accuracies in genomic selection.

RESULTS

Population structure analysis using 2,174,975 SNPs revealed four genetically distinct sub-populations from wheat accessions. D-Genome harbored the lowest number of significant marker pairs and the highest linkage disequilibrium (LD), reflecting different evolutionary histories of wheat genomes. From pGWAS, BRR, gBLUP, and rrBLUP, 284, 363, 359 and 295 significant MTAs were found under normal and 195, 365, 362 and 302 under stress conditions, respectively. The gBLUP with the most similarity (80.98 and 71.28% in well-watered and rain-fed environments, correspondingly) with the pGWAS method in the terms of discovered significant SNPs, suggesting the potential of gBLUP in uncovering SNPs. Results from gene ontology revealed that 29 and 30 SNPs in the imputed dataset were located in protein-coding regions for well-watered and rain-fed conditions, respectively. gBLUP model revealed genetic effects better than other models, suggesting a suitable tool for genome selection in wheat.

CONCLUSION

We illustrate that Iranian landraces of bread wheat contain novel alleles that are adaptive to drought stress environments. gBLUP model can be helpful for fine mapping and cloning of the relevant QTLs and genes, and for carrying out trait introgression and marker-assisted selection in both normal and drought environments in wheat collections.

Cluster analysis to explore additive-genetic patterns for the identification of sheep resistant, resilient and susceptible to gastrointestinal nematodes

Infection caused by gastrointestinal nematodes is an important issue for animal health and production. Controlling worm infections improves the sustainability of the sheep industry. Genetic selection of animals that are resistant to gastrointestinal nematodes is another strategy to render sheep production more sustainable by decreasing the use of anthelmintics. The aims of this study were (1) to explore the additive-genetic pattern of EBVs for Famacha© (FAM), packed-cell volume (PVC), and fecal egg counts (FEC) of Santa Ines sheep, (2) to propose a classification of animals that are resistant, resilient and susceptible to gastrointestinal nematodes based on their additive-genetic patterns, and (3) to identify the most suitable animals for selection based on their genetic pattern. A dataset of 2,241 records from 747 animals was used to predict the breeding values for indicator traits of resistance to gastrointestinal nematodes with THRGIBBS1F90 and to carry out cluster analyses was used R software. Three clusters of animals were found in the population using hierarchical cluster analysis of the breeding values for FAM, PCV and FEC. Each cluster was characterized by different additive-genetic patterns identified by k-means non-hierarchical cluster analysis. Among a total of 747 animals, 196 were classified as resistant, 288 as resilient, and 263 as susceptible. Cluster analysis is a valuable tool for data screening that permits to evaluate only selection candidates based on their additive-genetic pattern for gastrointestinal nematode resistance. EBVs for FEC were decisive to divide the population into resilient, resistant and susceptible animals. It is also important to include the EBVs for PCV and FAM to adequately distinguish resistant from resilient animals. Finally, the resistant cluster consisted of the most desirable animals to be used as selection candidates in order to genetically improve resistance to infection with gastrointestinal nematodes. This cluster contained animals with the most appropriate additive-genetic pattern to achieve the breeding goal, with positive breeding values for PCV and negative breeding values for FAM and FEC.

Selection indexes using principal component analysis for reproductive, beef and milk traits in Simmental cattle

Selection indexes in dual-purpose cattle should include beef, milk and reproductive traits. The principal component analysis is a multivariate technique that allows researchers to explore relationships between explanatory variables and traits of interest. The objective of this study was to construct selection indexes for tropical dual-purpose Simmental cattle based on principal components. The evaluated traits were weight at 8 months of age; age at first calving; cumulative first-lactation milk yield at 60, 150, 210 and 305 days; and first calving interval. The selection indexes were estimated as the sum of the products of the estimated breeding values for the seven traits times their respective eigenvectors for the first three principal components. The three selection indexes from principal components analysis generated favourable expected genetic progress for all the traits. However, a selection index with a high expected genetic progress for all traits could not be obtained. The principal component analysis allows breeders to have a selection index that simultaneously improves milk, beef and reproductive traits in dual-purpose Simmental cattle. Because a selection index yielding high expected genetic progress for all traits could not be achieved, the decision to use a specific selection index will depend on the specific conditions of the market, the local needs and the farmer preference.

Correlations between single nucleotide polymorphisms in bovine CD209, SLC11A1, SP110 and TLR2 genes and estimated breeding values for several traits in Spanish Holstein cattle

Little is known about the correlations between the genetic susceptibility/resistance to Mycobacterium avium subsp. paratuberculosis (Map) infection and the estimated breeding values for type, production and functional traits. Previously, we identified 70 combinations of five single nucleotide polymorphisms (SNPs) in four bovine innate immune genes (SLC11A1, SP110, TLR2, CD209) that are associated with the genetic risk of paratuberculosis (PTB) or Johne's disease progression, which can be graded as low (LOWIN), latent (LATIN), or patent (PATIN) risk. Other possible combinations of these 5 SNPs were grouped in the average group (AVERIN). In the current study, differences in estimated breeding values (EBVs) for several traits were analyzed using linear models in a large cohort of Holstein cows (N = 15656) genotyped across Spain in 2016 or 2017. After the assignment of each genotyped cow to a risk group, cows within the PATIN risk group (N = 1448) had a superior combined genetic index (2797.57), type genetic index (524.62), milk yield (653.92 kg), protein yield (21.77 kg), fat yield (24.82 kg) and economic merit index (125 Euros) compared with the other three risk groups. Statistically significant differences in the longevity scores between the cows that were included in the PATIN risk group (108.85) and the LOWIN (107.82) and AVERIN (107.92) groups were also observed. The associations between the genetic risk groups and PTB diagnostic results were validated in a population of 99 cows from a Spanish farm with a high prevalence of PTB. Significant differences in ELISA readings between the PATIN (65.49 %) and the AVERIN (15.97 %), LATIN (2.11 %), and LOWIN (3.27 %) groups were observed. In addition, significant differences in Map DNA copies/gram of feces were observed between the PATIN and the other three risk groups. These results together with the substantial economic impact of PTB in dairy cattle support the selection of the animals with less susceptibility to PTB in the Spanish breeding program.

Genetic parameters and estimated breeding values of insect bite hypersensitivity in Belgian Warmblood horses

Genetic factors involved in susceptibility to insect bite hypersensitivity (IBH) in Belgian Warmblood horses (BWP) were investigated. Data relating to 3409 horses were collected using a questionnaire, administered to owners during sport competitions, BWP breeding days, breeder visits and after phone calls. Horses were classified as IBH-affected or unaffected, based on two 'disease classifiers': a lifetime record, based on owner information (life_status) and another based on whether or not the horse was showing clinical signs at the time of questioning (clin_status). IBH prevalence was 10% based on life_status, and 6.2% based on clin_status. The heritabilities estimated using threshold animal models varied from 0.65 to 0.78 on the underlying scale (0.18-0.26 on the observed scale). These research findings indicate that susceptibility to IBH is a heritable trait in BWP.