Search

Further characterization of genetic structural variations should strongly focus on small and endangered local breeds given their role in unraveling genes and structural variants underlying selective pressures and phenotype variation. A comprehensive genome-wide assessment of copy number variations (CNVs) based on whole-genome re-sequencing data was performed on three Brazilian locally adapted cattle breeds (Caracu Caldeano, Crioulo Lageano, and Pantaneiro) using the ARS-UCD1.2 genome assembly. Data from 36 individuals with an average coverage depth of 14.07× per individual was used. A total of 24 945 CNVs were identified distributed among the breeds (Caracu Caldeano = 7285, Crioulo Lageano = 7297, and Pantaneiro = 10 363). Deletion events were 1.75-2.07-fold higher than duplications, and the total length of CNVs is composed mostly of a high number of segments between 10 and 30 kb. CNV regions (CNVRs) are not uniformly scattered throughout the genomes (n = 463), and 105 CNVRs were found overlapping among the studied breeds. Functional annotation of the CNVRs revealed variants with high consequence on protein sequence harboring relevant genes, in which we highlighted the BOLA-DQB, BOLA-DQA5, CD1A, β-defensins, PRG3, and ULBP21 genes. Enrichment analysis based on the gene list retrieved from the CNVRs disclosed over-represented terms (p < 0.01) strongly associated with immunity and cattle resilience to harsh environments. Additionally, QTL associated with body conformation and dairy-related traits were also unveiled within the CNVRs. These results provide better understanding of the selective forces shaping the genome of such cattle breeds and identify traces of natural selection pressures by which these populations have been exposed to challenging environmental conditions., (© 2023 Stichting International Foundation for Animal Genetics.)

The aim of this work was to evaluate the impact of applying genomic information in pedigree uncertainty situations on genetic evaluations for growth- and cow productivity-related traits in Nelore commercial herds. Records for accumulated cow productivity (ACP) and adjusted weight at 450 days of age (W450) were used, as well as genotypes of registered and commercial herd animals, genotyped with the Clarifide Nelore 3.1 panel (~29,000 SNPs). The genetic values for commercial and registered populations were estimated using different approaches that included (ssGBLUP) or did not include genomic information (BLUP), with different pedigree structures. Different scenarios were tested, varying the proportion of young animals with unknown sires (0, 25, 50, 75, and 100%), and unknown maternal grandsires (0, 25, 50, 75, and 100%). The prediction accuracies and abilities were calculated. The estimated breeding value accuracies decreased as the proportion of unknown sires and maternal grandsires increased. The genomic estimated breeding value accuracy using the ssGBLUP was higher in scenarios with a lower proportion of known pedigree when compared to the BLUP methodology. The results obtained with the ssGBLUP showed that it is possible to obtain reliable direct and indirect predictions for young animals from commercial herds without pedigree structure., (© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)

This study aimed to estimate prediction ability and genetic parameters for residual feed intake (RFI) calculated using a regression equation for each test (RFI test ) and for the whole population (RFI pop ) in Nellore beef cattle. It also aimed to evaluate the correlations between RFI pop and RFI test with growth, reproductive, and carcass traits. Genotypic and phenotypic records from 8354 animals were used. An analysis of variance (ANOVA) was performed to verify the adequacy of the regression equations applied to estimate the RFI test and RFI pop . The (co)variance components were obtained using the single-step genomic best linear unbiased prediction under single and two-trait animal model analyses. The genetic and phenotypic correlations between RFI test and RFI pop with dry matter intake, frame, growth, reproduction, and carcass-related traits were evaluated. The prediction ability and bias were estimated to compare the RFI test and RFI pop genomic breeding values (GEBV). The RFI pop ANOVA showed a higher significance level (p < 0.0001) than did the RFI test for the fixed effects. The RFI pop displayed higher additive genetic variance estimated than the RFI test , although the RFI pop and RFI test displayed similar heritabilities. Overall, the RFI test showed higher residual correlations with growth, reproductive, and carcass traits, while the RFI pop displayed higher genetic correlations with such traits. The GEBV for the RFI test was slightly biased than GEBV RFI pop . The approach to calculate the RFI influenced the decomposition and estimation of variance components and genomic prediction for RFI. The application of RFI pop would be more appropriate for genetic evaluation purpose to adjust or correct for non-genetic effects and to decrease the prediction bias for RFI., (© 2022. The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.)

This study aimed to investigate the prediction ability for growth and maternal traits using different low-density customized SNP arrays selected by informativeness and distribution of markers across the genome employing single-step genomic BLUP (ssGBLUP). Phenotypic records for adjusted weight at 210 and 450 days of age were utilized. A total of 945 animals were genotyped with high-density chip, and 267 individuals born after 2008 were selected as validation population. We evaluated 11 scenarios using five customized density arrays (40 k, 20 k, 10 k, 5 k and 2 k) and the HD array was used as desirable scenario. The GEBV predictions and BIF (Beef Improvement Federation) accuracy were obtained with BLUPF90 family programs. Linear regression was used to evaluate the prediction ability, inflation, and bias of GEBV of each customized array. An overestimation of partial GEBVs in contrast with complete GEBVs and increase of BIF accuracy with the density arrays diminished were observed. For all traits, the prediction ability was higher as the array density increased and it was similar with customized arrays higher than 10 k SNPs. Level of inflation was lower as the density array increased of and was higher for MW210 effect. The bias was susceptible to overestimation of GEBVs when the density customized arrays decreased. These results revealed that the BIF accuracy is sensible to overestimation using low-density customized arrays while the prediction ability with least 10,000 informative SNPs obtained from the Illumina BovineHD BeadChip shows accurate and less biased predictions. Low-density customized arrays under ssGBLUP method could be feasible and cost-effective in genomic selection., (© 2022. The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.)

Gene-gene interactions cause hidden genetic variation in natural populations and could be responsible for the lack of replication that is typically observed in complex traits studies. This study aimed to identify gene-gene interactions using the empirical Hilbert-Schmidt Independence Criterion method to test for epistasis in beef fatty acid profile traits of Nellore cattle. The dataset contained records from 963 bulls, genotyped using a 777 962k SNP chip. Meat samples of Longissimus muscle, were taken to measure fatty acid composition, which was quantified by gas chromatography. We chose to work with the sums of saturated (SFA), monounsaturated (MUFA), polyunsaturated (PUFA), omega-3 (OM3), omega-6 (OM6), SFA:PUFA and OM3:OM6 fatty acid ratios. The SNPs in the interactions where P < 10 - 8 were mapped individually and used to search for candidate genes. Totals of 602, 3, 13, 23, 13, 215 and 169 candidate genes for SFAs, MUFAs, PUFAs, OM3s, OM6s and SFA:PUFA and OM3:OM6 ratios were identified respectively. The candidate genes found were associated with cholesterol, lipid regulation, low-density lipoprotein receptors, feed efficiency and inflammatory response. Enrichment analysis revealed 57 significant GO and 18 KEGG terms ( P < 0.05), most of them related to meat quality and complementary terms. Our results showed substantial genetic interactions associated with lipid profile, meat quality, carcass and feed efficiency traits for the first time in Nellore cattle. The knowledge of these SNP-SNP interactions could improve understanding of the genetic and physiological mechanisms that contribute to lipid-related traits and improve human health by the selection of healthier meat products., (© 2021 Stichting International Foundation for Animal Genetics.)

The multiple sire system (MSS) is a common mating scheme in extensive beef production systems. However, MSS does not allow paternity identification and lead to inaccurate genetic predictions. The objective of this study was to investigate the implementation of single-step genomic BLUP (ssGBLUP) in different scenarios of uncertain paternity in the evaluation for 450-day adjusted liveweight (W450) and age at first calving (AFC) in a Nellore cattle population. To estimate the variance components using BLUP and ssGBLUP, the relationship matrix (A) with different proportions of animals with missing sires (MS) (scenarios 0, 25, 50, 75, and 100% of MS) was created. The genotyped animals with MS were randomly chosen, and ten replicates were performed for each scenario and trait. Five groups of animals were evaluated in each scenario: PHE, all animals with phenotypic records in the population; SIR, proven sires; GEN, genotyped animals; YNG, young animals without phenotypes and progeny; and YNGEN, young genotyped animals. The additive genetic variance decreased for both traits as the proportion of MS increased in the population when using the regular REML. When using the ssGBLUP, accuracies ranged from 0.13 to 0.47 for W450 and from 0.10 to 0.25 for AFC. For both traits, the prediction ability of the direct genomic value (DGV) decreased as the percentage of MS increased. These results emphasize that indirect prediction via DGV of young animals is more accurate when the SNP effects are derived from ssGBLUP with a reference population with known sires. The ssGBLUP could be applied in situations of uncertain paternity, especially when selecting young animals. This methodology is shown to be accurate, mainly in scenarios with a high percentage of MS., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V.)

The aim of this study was to assess the distribution of runs of homozygosity (ROH) and autozygosity islands in the composite Montana Tropical ® beef cattle to explore hotspot regions which could better characterize the different biological types within the composite breed. Montana animals (n = 1,436) were genotyped with the GGP-LD BeadChip (~30,000 markers). ROH was identified in every individual using the plink v1.90 software. Medium and long ROH prevailed in the genome, which accounted for approximately 74% of all ROH detected. On an average, 2.0% of the genome was within ROH, agreeing with the pedigree-based inbreeding coefficient. The Montana cattle with a higher proportion of productive breed types showed the highest number of autozygosity islands (n = 17), followed by those with a higher proportion of breeds adapted to tropical environments (n = 15). Enriched terms (p < .05) associated with the immune and inflammatory response, homeostasis, reproduction, mineral absorption, and lipid metabolism were described within the autozygosity islands. In this regard, over-represented GO terms and KEGG pathways described in this population may play a key role in providing information to explore the genetic and biological mechanisms together with the genomic regions underlying each biological type that favoured their optimal performance ability in tropical and subtropical regions., (© 2019 Blackwell Verlag GmbH.)

The aim of this study was to estimate genetic parameters and identify genomic regions associated with carcass traits obtained by ultrasound and visual scores in Nellore cattle. Data from ~66,000 animals from the National Association of Breeders and Researchers (ANCP) were used. The variance components for backfat thickness, rump fat thickness and Longissimus muscle area (LMA) were estimated considering a linear model whereas a threshold model for body structure (BS), finishing precocity (FP) and musculature (MS) traits. The SNP solutions were estimated using the ssGBLUP approach by considering windows of 10 consecutive SNPs. Regions that accounted for more than 1.0% of the additive genetic variance were used. Genes identified within the significant windows, such as FOXA3, AP2S1, FKRP, NPASI and ATP6V1G1, were found to be related with MS, while OMA1 and FFGY with BS and FP traits. The PLTP, TNNC2 and GPAT2 genes were found in the regions associated with LMA, as well as TKT, FNDC5 and CHRND can strongly be related with fat deposition. Gene enrichment analysis revealed processes that might be directly influenced the organism growth and development. These results should help to better understand the genetic and physiological mechanisms regulating growth and body composition, muscle tissue development and subcutaneous fat expression, and this information might be useful for future genomic studies in Nellore cattle., (© 2018 Blackwell Verlag GmbH.)