Genome-wide association study and predictive ability for growth traits in Nellore cattle

Genetic Foundations of Nellore Traits: A Gene Prioritization and Functional Analyses of Genome-Wide Association Study Results

The main goal of this study was to pinpoint functional candidate genes associated with multiple economically important traits in Nellore cattle. After quality control, 1830 genomic regions sourced from 52 scientific peer-reviewed publications were used in this study. From these, a total of 8569 positional candidate genes were annotated for reproduction, 11,195 for carcass, 5239 for growth, and 3483 for morphological traits, and used in an over-representation analysis. The significant genes (adjusted p-values < 0.05) identified in the over-representation analysis underwent prioritization analyses, and enrichment analysis of the prioritized over-represented candidate genes was performed. The prioritized candidate genes were GFRA4, RFWD3, SERTAD2, KIZ, REM2, and ANKRD34B for reproduction; RFWD3, TMEM120A, MIEF2, FOXRED2, DUSP29, CARHSP1, OBI1, JOSD1, NOP58, and LOXL1-AS1 for the carcass; ANKRD34B and JOSD1 for growth traits; and no genes were prioritized for morphological traits. The functional analysis pinpointed the following genes: KIZ (plays a crucial role in spindle organization, which is essential in forming a robust mitotic centrosome), DUSP29 (involved in muscle cell differentiation), and JOSD1 (involved in protein deubiquitination, thereby improving growth). The enrichment of the functional candidate genes identified in this study highlights that these genes play an important role in the expression of reproduction, carcass, and growth traits in Nellore cattle.

Weighted genomic prediction for growth and carcass-related traits in Nelore cattle

This study aimed to assess the impact of differential weighting in genomic regions harboring candidate causal loci on the genomic prediction accuracy and dispersion for growth and carcass-related traits in Nelore cattle. The dataset contained 168 793 phenotypic records for adjusted weight at 450 days of age (W450), 83 624 for rib eye area (REA), 24 480 for marbling (MAR) and 82 981 for subcutaneous backfat thickness (BFT) and rump fat thickness (RFT). The pedigree harbored information from 244 254 animals born between 1977 and 2016, including 6283 sires and 50 742 dams. Animals (n = 7769) were genotyped with the low-density panel (Clarifide® Nelore 3.0), and the genotypes were imputed to a panel containing 735 044 markers. A linear animal model was applied to estimate the genetic parameters and to perform the weighted single-step genome-wide association study (WssGWAS). A total of seven models for genomic prediction were evaluated combining the SNP weights obtained in the iterations of the WssGWAS and the candidate QTL. The heritability estimated for W450 (0.35) was moderate, and for carcass-related traits, the estimates were moderate for REA (0.27), MAR (0.28) and RFT (0.28), and low for BFT (0.18). The prediction accuracy for W450 incorporating reported QTL previously described in the literature along with different SNPs weights was like those described for the default ssGBLUP model. The use of the ssGWAS to weight the SNP effects displayed limited advantages for the REA prediction accuracy. Comparing the ssGBLUP with the BLUP model, a meaningful improvement in the prediction accuracy from 0.09 to 0.63 (700%) was observed for MAR. The highest prediction accuracy was obtained for BFT and RFT in all evaluated models. The application of information obtained from the WssGWAS is an alternative to reduce the genomic prediction dispersion for growth and carcass-related traits, except for MAR. Furthermore, the results obtained herein pointed out that is possible to improve the prediction accuracy and reduce the genomic prediction dispersion for growth and carcass-related traits in young animals.

Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner-Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.

High-density SNP markers elucidate the genetic divergence and population structure of Noticiana sheep breed in the Mediterranean context

Among livestock species, sheep have played an early major role in the Mediterranean area. Italy has a long history of sheep breeding and, despite a dramatic contraction in numbers, still raise several local populations that may represent a unique source of genetic diversity. The Noticiana is a breed of the south-eastern part of Sicily appreciated both for its dairy products and for its resistance to harsh environment. In this study, the high-density Illumina Ovine SNP600K BeadChip array was used for the first genome-wide characterization of 48 individuals of Noticiana sheep to investigate its diversity, the genome structure and the relationship within the context of worldwide and Italian breeds. Moreover, the runs of homozygosity (ROH) pattern and the pairwise F_ST-outliers were examined. Noticiana reported moderate levels of genetic diversity. The high percentage of short and medium length ROH segments (93% under 4 Mb) is indicative of a within breed relatedness dating back to ancient times, despite the absence of management for the mating plans and the reduced population size. In the worldwide context, the Southern Italian, Spanish and Albanian breeds overlapped in a macro cluster which also included the Noticiana sheep. The results highlighted ancestral genetic components of Noticiana shared with Comisana breed, and showed the clear separation from the other Italian sheep. This is likely the consequence of the combined effects of genetic drift, small population size and reproductive isolation. ROH islands and F_ST-outliers approaches in Noticiana identified genes and QTLs involved in milk and meat production, as well as related to the local adaptation, and therefore are consistent with the phenotypic traits of the studied breed. Although a wider sampling could be useful to deepen the genomic survey on Noticiana, these results represent a crucial starting point for the characterization of an important local genetic resource, with a view of supporting the local economy and preserving the biodiversity of the sheep species.

Genome Wide Association Study of Beef Traits in Local Alpine Breed Reveals the Diversity of the Pathways Involved and the Role of Time Stratification

Knowledge of the genetic architecture of key growth and beef traits in livestock species has greatly improved worldwide thanks to genome-wide association studies (GWAS), which allow to link target phenotypes to Single Nucleotide Polymorphisms (SNPs) across the genome. Local dual-purpose breeds have rarely been the focus of such studies; recently, however, their value as a possible alternative to intensively farmed breeds has become clear, especially for their greater adaptability to environmental change and potential for survival in less productive areas. We performed single-step GWAS and post-GWAS analysis for body weight (BW), average daily gain (ADG), carcass fleshiness (CF) and dressing percentage (DP) in 1,690 individuals of local alpine cattle breed, Rendena. This breed is typical of alpine pastures, with a marked dual-purpose attitude and good genetic diversity. Moreover, we considered two of the target phenotypes (BW and ADG) at different times in the individuals' life, a potentially important aspect in the study of the traits' genetic architecture. We identified 8 significant and 47 suggestively associated SNPs, located in 14 autosomal chromosomes (BTA). Among the strongest signals, 3 significant and 16 suggestive SNPs were associated with ADG and were located on BTA10 (50-60 Mb), while the hotspot associated with CF and DP was on BTA18 (55-62 MB). Among the significant SNPs some were mapped within genes, such as SLC12A1, CGNL1, PRTG (ADG), LOC513941 (CF), NLRP2 (CF and DP), CDC155 (DP). Pathway analysis showed great diversity in the biological pathways linked to the different traits; several were associated with neurogenesis and synaptic transmission, but actin-related and transmembrane transport pathways were also represented. Time-stratification highlighted how the genetic architectures of the same traits were markedly different between different ages. The results from our GWAS of beef traits in Rendena led to the detection of a variety of genes both well-known and novel. We argue that our results show that expanding genomic research to local breeds can reveal hitherto undetected genetic architectures in livestock worldwide. This could greatly help efforts to map genomic complexity of the traits of interest and to make appropriate breeding decisions.