Sequence comparison of mitochondrial tRNA genes and origin of light strand replication in Bos taurus and Nellore (Bos indicus) breeds

Although the complete bovine mitochondrial DNA molecule has been previously sequencedand sequence comparisons of the mitochondrial displacement loop have been performed, detailed sequence information is limited on coding regions of mitochondrial DNA within and among breeds of Bos taurus and Bos indicus. This study analysed polymorphism of the mitochondrial DNA transfer RNA genes for trypto-phan, alanine, asparagine, cysteine, tyrosine and the origin of light strand replication among Ayrshire, Canadian, Belgium Blue, Brown Swiss, Hereford, Jersey, Limousine, Piedmon-taise, Red Angus, Simmental (Bos taurus) and a Nellore (Bos indicus). Nucleotide sequence analysis of a 420-bp fragment of mitochondrial DNA comprising the five transfer RNA genes showed 100% homology among single individuals of the Bos taurus breeds. The Nellore breed showed guanine to adenine substitutions in the DHU arm of asparagine tRNA and in the origin of light-strand replication. This equates to a 0.5% sequence difference between the Nellore andBos taurus breeds and may reflect an independent evolutionary origin of the species.     

Polymorphism analysis in genes of the somatotropic axis in Nellore cattle selected for growth

The somatotropic axis consists of genes that are involved in muscular development. These genes are potential regions of study to identify possible QTL for economically important traits in beef cattle. The aim of this study was to verify the existence of GH1, POU1F1, and GHR polymorphisms in Nellore cattle to verify the influence of selection in these mutations and to analyse the association between molecular markers and body weight at different ages, yearling hip height, carcass fat thickness and loin eye area. Six hundred forty-five animals from the Centro APTA Bovinos de Corte, were genotyped by PCR–RFLP techniques. The association analyses were performed with general mixed models taking into consideration the effect of one marker, and other model taking into consideration interactions between two molecular markers. Only the molecular markers rs81109601 on GH1 and rs109136815 on GHR were polymorphic; however, they were not found to be under selection. The association of the GHR rs109136815 marker and loin eye area was observed (p < 0.05), as well as the effect of interaction between the markers and the female body weight at 550 days of age (p < 0.04). The interaction effect should be considered in situations where the interactivity between two genes is known.     

Development of an equation to predict net protein requirements for the growth of Zebu beef cattle

The accurate estimation of protein requirements for beef cattle is a key factor in increasing livestock profitability and decreasing the environmental impacts of excessive N excretion due to mismatching between assumed requirements and diet formulation. A meta-analysis was conducted to evaluate and validate a new equation to predict the net protein requirements for growth (NPg) of Zebu beef cattle. For the development of the new approach, a database of 552 observations comprised of bulls, steers, and heifers of different genetic groups (Zebu, beef crossbreed, and dairy crossbreed) was assembled. The new approach was evaluated and compared to current models devised by the international nutrient requirements system committees (Agricultural Research Council, 1980; Beef Cattle Nutrient Requirements Model, 2016; BR-CORTE, 2016) to predict NPg. The model evaluation was performed through the model evaluation system (version 3.1.16) using an independent data set (n = 177 observations). An equation was considered the best estimator of NPg if the following conditions were met: (1) the intercept and slope of the regression between ordinary residues and/or predicted NPg values must have been equal to zero and one, respectively; and (2) the greatest concordance correlation coefficient (CCC) and determination coefficient (R), and lowest mean squared error of prediction (MSEP) were attained. Based on the regression models of the observed v. predicted NPg of Zebu beef cattle, both the new approach and that of the ARC (1980) correctly estimated NPg, since the intercept and slope were not different (P > 0.05) from zero and one, respectively. Additionally, the new approach’s determination coefficient was the greatest and the closest to one. The fact that the new model achieved a higher CCC and lower MSEP than the existing models indicated its superior reproducibility and accuracy. The equations proposed by BR-CORTE (2016) and the BCNRM (2016) did not correctly estimate NPg in that the intercept and slope were different (P < 0.01) from zero and one, respectively. Thus, the equations proposed by the new approach and the ARC (1980) accurately and precisely estimated NPg and are recommended for Zebu cattle. Furthermore, the inclusion of equivalent empty BW (EQEBW) in the new approach improves the estimation of NPg. We suggest the use of the following equation to calculate NPg for Zebu beef cattle: NPg = 176.01 × EBG – 0.381 × EQEBW^0.75 × EBG^1.035 (R = 0.80 and CCC = 0.75); where NPg = net protein requirements for growth, EBG = empty body gain, and EQEBW = equivalent empty BW.     

Bayesian inference in genetic parameter estimation of visual scores in Nellore beef-cattle

The aim of this study was to estimate the components of variance and genetic parameters for the visual scores which constitute the Morphological Evaluation System (MES), such as body structure (S), precocity (P) and musculature (M) in Nellore beef-cattle at the weaning and yearling stages, by using threshold Bayesian models. The information used for this was gleaned from visual scores of 5,407 animals evaluated at the weaning and 2,649 at the yearling stages. The genetic parameters for visual score traits were estimated through two-trait analysis, using the threshold animal model, with Bayesian statistics methodology and MTGSAM (Multiple Trait Gibbs Sampler for Animal Models) threshold software. Heritability estimates for S, P and M were 0.68, 0.65 and 0.62 (at weaning) and 0.44, 0.38 and 0.32 (at the yearling stage), respectively. Heritability estimates for S, P and M were found to be high, and so it is expected that these traits should respond favorably to direct selection. The visual scores evaluated at the weaning and yearling stages might be used in the composition of new selection indexes, as they presented sufficient genetic variability to promote genetic progress in such morphological traits.     

Neither plasma progesterone concentrations nor exogenous eCG affects rates of ovulation or pregnancy in fixed-time artificial insemination (FTAI) protocols for puberal Nellore heifers

The objective was to evaluate the effects of plasma progesterone (P4) concentrations and exogenous eCG on ovulation and pregnancy rates of pubertal Nellore heifers in fixed-time artificial insemination (FTAI) protocols. In Experiment 1 (Exp. 1), on Day 0 (7 d after ovulation), heifers (n = 15) were given 2 mg of estradiol benzoate (EB) im and randomly allocated to receive: an intravaginal progesterone-releasing device containing 0.558 g of P4 (group 0.5G, n = 4); an intravaginal device containing 1 g of P4 (group 1G, n = 4); 0.558 g of P4 and PGF_2α (PGF; 150 μg d-cloprostenol, group 0.5G/PGF, n = 4); or 1 g of P4 and PGF (group 1G/PGF, n = 3). On Day 8, PGF was given to all heifers and intravaginal devices removed; 24 h later (Day 9), all heifers were given 1 mg EB im. In Exp. 2, pubertal Nellore heifers (n = 292) were treated as in Exp. 1, with FTAI on Day 10 (30 to 36 h after EB). In Exp. 3, pubertal heifers (n = 459) received the treatments described for groups 0.5G/PGF and 1G/PGF and were also given 300 IU of eCG im (groups 0.5G/PGF/eCG and 1G/PGF/eCG) at device removal (Day 8). In Exp. 1, plasma P4 concentrations were significantly higher in heifers that received 1.0 vs 0.588 g P4, and were significantly lower in heifers that received PGF on Day 0. In Exp. 2 and 3, there were no significant differences among groups in rates of ovulation (65-77%) or pregnancy (Exp. 2: 26-33%; Exp. 3: 39-43%). In Exp. 3, diameter of the dominant ovarian follicle on Day 9 was larger in heifers given 0.558 g vs 1.0 g P4 (10.3 ± 0.2 vs 9.3 ± 0.2 mm; P < 0.01). In conclusion, lesser amounts of P4 in the intravaginal device or PGF on Day 0 decreased plasma P4 from Days 1 to 8 and increased diameter of the dominant follicle on Day 9. However, neither of these nor 300 IU of eCG on Day 8 significantly increased rates of ovulation or pregnancy.     

Sequence Variation Of the α-Lactalbumin Gene In Holstein and Nellore Cows

The α-lactalbumin is a subunit of lactose-synthase, an enzyme responsible for lactose production, a disaccharide that influences milk production. Sequence variations of bovine α -lactalbumin have been associated with differences in milk yield. This study aimed to analyze allelic frequency differences at position ? 1689 (g. A > G) and + 15 (g. A > G) of the α-lactalbumin gene in Holstein (Bos taurus) and Nellore (Bos indicus) cows. Blood samples were analyzed from 34 Holstein, 104 Nellore, and 99 Dairy Nellore cows using PCR-RFLP. The different RFLP patterns were sequenced and a novel sequence variation on nucleotide ? 46 was identified. An adenine at this position was designated as the A allele and a guanine was designated B allele. The frequencies of alleles A ? 1689, A ? 46, and A + 15 differed between Holstein and both Nellore breeds. The results show that differences in α-lactalbumin allelic variants in the 5′-flanking and the 5′-UTR region might be associated with differences in milk production between Holstein cows and cows from Nellore breeds. However, the lack of difference between Nellore and Dairy Nellore suggests that other sequence variantions that regulate milk production might be responsible for the selection of Dairy Nellore cows with superior milk production.     

Body condition score of Nellore beef cows: a heritable measure to improve the selection of reproductive and maternal traits

Despite the economic importance of beef cattle production in Brazil, female reproductive performance, which is strongly associated with production efficiency, is not included in the selection index of most breeding programmes due to low heritability and difficulty in measure. The body condition score (BCS) could be used as an indicator of these traits. However, so far little is known about the feasibility of using BCS as a selection tool for reproductive performance in beef cattle. In this study, we investigated the sources of variation in the BCS of Nellore beef cows, quantified its association with reproductive and maternal traits and estimated its heritability. BCS was analysed using a logistic model that included the following effects: contemporary group at weaning, cow weight and hip height, calving order, reconception together with the weight and scores of conformation and early finishing assigned to calves at weaning. In the genetic analysis, variance components of BCS were estimated through Bayesian inference by fitting an animal model that also included the aforementioned effects. The results showed that BCS was significantly associated with all of the reproductive and maternal variables analysed. The estimated posterior mean of heritability of BCS was 0.24 (highest posterior density interval at 95%: 0.093 to 0.385), indicating an involvement of additive gene action in its determination. The present findings show that BCS can be used as a selection criterion for Nellore females.     

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.     

Effect of progesterone concentrations,follicle diameter,timing of artificial insemination,and ovulatory stimulus on pregnancy rate to synchronized artificial insemination in postpubertal Nellore heifers

Two experiments were designed to evaluate the effects of treatments with low versus high serum progesterone (P₄) concentrations on factors associated with pregnancy success in postpubertal Nellore heifers submitted to either conventional or fixed timed artificial insemination (FTAI). Heifers were synchronized with a new controlled internal drug release device (CIDR; 1.9 g of P₄ [CIDR1]) or a CIDR previously used for 18 days (CIDR3) plus 2 mg of estradiol (E₂) benzoate on Day 0 and 12.5 mg of prostaglandin F2α on Day 7. In experiment 1 (n = 723), CIDR were removed on Day 7 or 9 and heifers were inseminated after estrus detection. In experiment 2 (n = 1083), CIDR were all removed on Day 9 and FTAI was performed either 48 hours later in heifers that received E₂ cypionate (ECP) on Day 9 (0.5 mg; E48) or 54 or 72 hours later in conjunction with administration of GnRH (100 μg; G54 or G72). Synchronization with CIDR1 resulted in greater serum P₄ concentrations and smaller follicle diameters on Days 7 and 9 in both experiments. In experiment 1, treatment with CIDR for 9 days decreased the interval from CIDR removal to estrus (Day 7, 3.76 ± 0.08 days vs. Day 9, 2.90 ± 0.07; P < 0.01) and improved conception (Day 7, 57.1% vs. Day 9, 65.8%; P = 0.05) and pregnancy rates (Day 7, 37.6% vs. Day 9, 45.3%; P = 0.04). In experiment 2, treatment with ECP improved (P < 0.01) the proportion of heifers in estrus (E48, 40.9%^a; G54, 17.1%^c; and G72, 32.0%^b), but the pregnancy rate was not affected (P = 0.64) by treatments (E48, 38.8%; G54, 35.5%; G72, 37.5%). Synchronization with CIDR3 increased follicle diameter at FTAI (CIDR1, 11.07 ± 0.10 vs. CIDR3, 11.61 ± 0.10 mm; P < 0.01), ovulation rate (CIDR1, 82.8% vs. CIDR3, 88.0%; P < 0.01) and did not affect conception (CIDR1, 42.2 vs. CIDR3, 45.1%; P = 0.38) or pregnancy rates (CIDR1, 34.7 vs. CIDR3, 39.4%; P = 0.11). In conclusion, length of treatment with P₄ affected the fertility of heifers bred based on estrus detection. When the heifers were submitted to FTAI protocol, follicle diameter at FTAI (≤10.7 mm, 23.6%; 10.8–15.7 mm, 51.5%; ≥15.8 mm, 30.0%; P < 0.01) was the main factor that affected conception and pregnancy rates.