Benchmarking in a beef cattle breeding program: Lessons from the best breeders.

Beef cattle breeding programs offer genetic evaluations and consulting services on animal breeding practices to help breeders improve the genetic merit of their herds. Some breeders are more willing to apply best practices and technologies than others. Consequently, the average genetic merit and genetic trends differ across herds. We benchmarked some parameters of an average herd (AVE) and the corresponding parameters of herds with higher genetic merit (TOP), both participating in a commercial Nellore breeding program. Expected progeny differences (EPD) for growth, reproductive and carcass traits and a selection index (SI) of animals born from 2005 to 2019 on 128 farms located in Brazil, Bolivia and Paraguay were used to compute the AVE parameters. The 20 herds with higher mean SI of animals born in the last five birth seasons were classified as TOP herds. The mean SI and EPD of animals born in the last five seasons in the TOP herds were, respectively, 89% and 79% to 206% higher (p ≤ 0.001) than those of animals from the AVE herd. Genetic trends over the entire period were also higher (50% for SI and 31% to 88% separately for each trait, p ≤ 0.006) in the TOP herds compared to the AVE herd. Although the difference in the numbers of cows, bulls and calves between the TOP and AVE herds did not reach statistical significance (p = 0.175, p = 0.273 and p = 0.061, respectively), the numbers of progeny per cow and per bull were 21% (p = 0.012) and 26% (p = 0.047) higher in the TOP herds, respectively. Multiple ovulation and embryo transfer and in vitro fertilization and embryo transfer (MOET/IVF) accounted for a higher percentage of births in the TOP herds compared to AVE (24.6% vs. 12.5%, p = 0.002). The generation interval was 17% shorter (p < 0.001) in the TOP herds compared to AVE. The average inbreeding coefficient of animals from the TOP herds (1.08 ± 0.52%) did not differ (p = 0.78) from that of AVE animals (1.26 ± 0.96%). In general, AVE herds are evolving in the desirable direction but differences in genetic merit between AVE and TOP herds are increasing over time. The more frequent use of MOET/IVF, a lower cow-to-bull ratio, and a larger family size (progeny per cow or per bull) can help achieve larger selection differentials and increase genetic trends and average genetic merits of TOP herds compared to AVE herds.

Genome-Wide Analyses Reveal the Genetic Architecture and Candidate Genes of Indicine, Taurine, Synthetic Crossbreds, and Locally Adapted Cattle in Brazil.

Cattle population history, breeding systems, and geographic subdivision may be reflected in runs of homozygosity (ROH), effective population size (N e), and linkage disequilibrium (LD) patterns. Thus, the assessment of this information has become essential to the implementation of genomic selection on purebred and crossbred cattle breeding programs. In this way, we assessed the genotype of 19 cattle breeds raised in Brazil belonging to taurine, indicine, synthetic crossbreds, and Iberian-derived locally adapted ancestries to evaluate the overall LD decay patterns, N e, ROH, and breed composition. We were able to obtain a general overview of the genomic architecture of cattle breeds currently raised in Brazil and other tropical countries. We found that, among the evaluated breeds, different marker densities should be used to improve the genomic prediction accuracy and power of genome-wide association studies. Breeds showing low N e values indicate a recent inbreeding, also reflected by the occurrence of longer ROH, which demand special attention in the matting schemes to avoid extensive inbreeding. Candidate genes (e.g., ABCA7, PENK, SPP1, IFNAR1, IFNAR2, SPEF2, PRLR, LRRTM1, and LRRTM4) located in the identified ROH islands were evaluated, highlighting biological processes involved with milk production, behavior, rusticity, and fertility. Furthermore, we were successful in obtaining the breed composition regarding the taurine and indicine composition using single-nucleotide polymorphism (SNP) data. Our results were able to observe in detail the genomic backgrounds that are present in each breed and allowed to better understand the various contributions of ancestor breeds to the modern breed composition to the Brazilian cattle.

Genomic evaluation for novel stayability traits in Nellore cattle.

Cow stayability plays a major role on the overall profitability of the beef cattle industry, as it is directly related to reproductive efficiency and cow's longevity. Stayability (STAY63) is usually defined as the ability of the cow to calve at least three times until 76 months of age. This is a late-measured and lowly heritable trait, which consequently constrains genetic progress per time unit. Thus, the use of genomic information associated with novel stayability traits measured earlier in life will likely result in higher prediction accuracy and faster genetic progress for cow longevity. In this study, we aimed to compare pedigree-based and single-step GBLUP (ssGBLUP) methods as well as to estimate genetic correlations between the proposed stayability traits: STAY42, STAY53 and STAY64, which are measured at 52, 64 and 76 months of cow's age, considering at least 2, 3 and 4 calving, respectively. ssGBLUP yielded the highest prediction accuracy for all traits. The heritability estimates for STAY42, STAY53, STAY63 and STAY64 were 0.090, 0.151, 0.152 and 0.143, respectively. The genetic correlations between traits ranged from 0.899 (STAY42 and STAY53) to 0.985 (STAY53 and STAY63). The high genetic correlation between STAY42 and STAY53 suggests that besides being related to cow longevity, STAY53 is also associated with the early-stage reproductive efficiency. Thus, STAY53 is recommended as a suitable selection criterion for reproductive efficiency due to its higher heritability, favourable genetic correlation with other traits, and measured earlier in life, compared with the conventional stayability trait, that is STAY63.

Comparison between in vitro embryo production using Y-sorted sperm and timed artificial insemination with non-sorted sperm to produce crossbred calves.

Due to the increasing use of in vitro embryo production (IVEP) and the importance of crossbreeding for beef production, pregnancy rates of Nelore recipients were evaluated following Fixed Time Embryo Transfer with fresh or vitrified IVEP embryos produced with Y-sorted sperm of Angus bulls (B. taurus) or Fixed Time Artificial Insemination using non-sorted sperm. For IVEP in Experiment 1, oocytes were obtained using Ovum Pick Up (OPU) (n = 84 embryos) or from ovaries from a slaughterhouse (SLAUGHTER, n = 66 embryos). In Experiment 2, with oocytes obtained by OPU, IVEP embryos were fresh (FRESH, n = 271) or after vitrification/warming (VITRIFIED, n = 79) and PR was compared with FTAI (n = 239). In Experiment 1, cleavage rates were 63.8% and 39.1% for OPU and SLAUGHTER groups, respectively (P = 0.02), and blastocyst rates were 30.5% and 14.7%, respectively (P = 0.09). The PR was similar when considering the source of oocytes (OPU = 35.7%; SLAUGHTER = 25.8%; P = 0.17). In Experiment 2, there was no difference in PR for FRESH or VITRIFIED embryos (34.3% and 30.4%, respectively, P = 0.72), but lesser than FTAI (47.7, P = 0.002). It is concluded that the IVEP with Y-sorted sperm associated with vitrification or embryos produced with oocytes from different sources did not affect PR when there was transfer of crossbred embryos into recipients, and can optimize large-scale application of IVEP technology; however, FTAI pregnancy rates with non-sex sorted sperm were greater.

Genomic Variants Revealed by Invariably Missing Genotypes in Nelore Cattle.

High density genotyping panels have been used in a wide range of applications. From population genetics to genome-wide association studies, this technology still offers the lowest cost and the most consistent solution for generating SNP data. However, in spite of the application, part of the generated data is always discarded from final datasets based on quality control criteria used to remove unreliable markers. Some discarded data consists of markers that failed to generate genotypes, labeled as missing genotypes. A subset of missing genotypes that occur in the whole population under study may be caused by technical issues but can also be explained by the presence of genomic variations that are in the vicinity of the assayed SNP and that prevent genotyping probes from annealing. The latter case may contain relevant information because these missing genotypes might be used to identify population-specific genomic variants. In order to assess which case is more prevalent, we used Illumina HD Bovine chip genotypes from 1,709 Nelore (Bos indicus) samples. We found 3,200 missing genotypes among the whole population. NGS re-sequencing data from 8 sires were used to verify the presence of genomic variations within their flanking regions in 81.56% of these missing genotypes. Furthermore, we discovered 3,300 novel SNPs/Indels, 31% of which are located in genes that may affect traits of importance for the genetic improvement of cattle production.