The objective of this study was to evaluate the factors influencing in vitro embryo production in the Gir breed in a commercial embryo transfer program in Brazil. Data from 15,894 follicular aspirations in 3682 Gir dairy donors were analyzed and the average number of viable oocytes per donor (VON), proportion of viable oocytes (VOP), blastocyst rate (BLR), and pregnancy rate (PR) were evaluated. First, the collection records were distributed across the seasons, and the results showed that VOP was higher in summer (75.0 %) and spring (74.1 %), while BLR was higher in spring (22.5 %). The donors were subsequently grouped into seven age classes, in which the highest VOP was observed in animals aged 6-8 years (75.2 %), 8-10 years (75.7 %), and 10-12 years (75.9 %). Regarding the BLR, the highest values were observed in donors older than 4 years. Donors were also grouped as heifers or cows, with cows (22.42 %) showing a higher BLR than heifers (20.05 %). Next, the effect of seasons on PR after fresh embryo transfer was evaluated, with spring (43.8 %) and winter (43.5 %) presenting the highest PR. Finally, pregnancy rates were compared following the transfer of fresh or vitrified embryos, showing a higher PR for fresh embryos (41.1 %) than for vitrified ones (34.6 %). Therefore, season, as well as the age and category of Gir donors, influence in vitro production. Additionally, vitrification reduces the survival of in vitro-produced Gir dairy embryos.

Count traits are usually explored in livestock breeding programs, and they usually do not fit into normal distribution, requiring alternatives to adjust the phenotype to estimate accurate genetic parameters and breeding values. Alternatively, distribution such as Poisson can be used to evaluate count traits. This study aimed to compare and discuss the genetic evaluation for oocyte and embryo counts considering Gaussian (untransformed variable — LIN; transformed by logarithm — LOG; transformed by Anscombe — ANS) and Poisson (POI) distributions. The data comprised 11,343 total oocytes (TO), viable oocytes (VO), cleaved embryos (CE), and viable embryo (VE) records of ovum pick-up from 1740 Dairy Gir heifers and cows. The genetic parameters and breeding values were estimated by the MCMCglmm package of the R software. The posterior means of heritability varied from 0.40 (LIN) to 0.49 (POI) for TO, 0.39 (LIN) to 0.49 (POI) for VO, 0.30 (LOG) to 0.41 (POI) for cleaved embryos, and 0.19 (LIN) to 0.32 (POI) for viable embryos. The posterior means of repeatability varied from 0.56 (LIN) to 0.65 (POI) for TO, 0.53 (LOG) to 0.63 (POI) for VO, 0.44 (LOG) to 0.60 (POI) for CE, and 0.36 (LOG) to 0.56 (POI) for VE. Deviance information criterion and mean squared residuals indicated that POI model should be used for the genetic evaluation of embryo and oocyte count traits. Spearman’s rank correlation between estimated breeding value (EBV) for embryo and oocyte count traits computed by POI, LOG, and ANS models was high (ranging from 0.77 to 0.99), indicating little reranking among the best animals. The POI model is the most adequate for genetic evaluation, resulting in more reliable EBV of oocyte and embryo count traits for Dairy Gir cattle.

The interspecific abalone hybrid of Haliotis rubra x H. laevigata is an important commercial species for abalone aquaculture in Australia. A selective breeding program is in operation to genetically improve hybrid performance for total weight, meat yield, and appearance traits (epipodium pattern and foot colour). This study provides estimates of heterosis for these traits and genetic parameters for the two parental species and their hybrid populations, measured using 73,107 individuals collected over 14 generations. Measurements were made at 1.5 and 2.5 years for total weight, meat yield and appearance traits. Genetic variation was significant for all eval-uated traits and was predominantly due to additive genetic variation. The heritability (h2) estimates of total weight at 2.5 years for H. rubra and H. laevigata was 0.54 +/- 0.03 and 0.45 +/- 0.02, respectively, but higher in the hybrid population (0.57 +/- 0.01). For other traits the h2 estimates of hybrid populations were within the range of those for pure species. The range of h2 (with SE) at 2.5 years for meat yield, epipodium pattern and foot colour were 0.27 (0.06) to 0.78 (0.04), 0.35 (0.05) to 0.62 (0.03), and 0.18 (0.03) to 0.30 (0.02), respectively. Heterosis was present for all traits except foot colour. Effects were strongest for total weight, with a 67% gain over the mid parent value, and less for meat yield, epipodium pattern, and foot colour with gains of 6%, 9% and 6% over mid parent value, respectively. Genetic correlations between pure species performance and hybrid performance for total weight were 0.45 (0.17) for H. rubra and 0.75 (0.06) for H. laevigata and ranged from 0.27 to 0.85 for other traits. These correlations were a basis for decisions about the commercial breeding strategy. The strategy adopted is a form of reciprocal recurrent selection which uses a hybrid progeny test. Selection is based on estimation of additive hybrid effects and measurements are made on both hybrid and pure species which are treated as separate and correlated traits.

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 (h 2 ) 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 h 2 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.

BACKGROUND:Host resilience (HR) to parasites can affect the performance of animals. Therefore, the aim of this study was to present a detailed investigation of the genetic mechanisms of HR to ticks (TICK), gastrointestinal nematodes (GIN), and Eimeria spp. (EIM) in Nellore cattle that were raised under natural infestation and a prophylactic parasite control strategy. In our study, HR was defined as the slope coefficient of body weight (BW) when TICK, GIN, and EIM burdens were used as environmental gradients in random regression models. In total, 1712 animals were evaluated at five measurement events (ME) at an average age of 331, 385, 443, 498, and 555 days, which generated 7307 body weight (BW) records. Of the 1712 animals, 1075 genotyped animals were used in genome-wide association studies to identify genomic regions associated with HR.RESULTS:Posterior means of the heritability estimates for BW ranged from 0.09 to 0.54 across parasites and ME. The single nucleotide polymorphism (SNP)-derived heritability for BW at each ME ranged from a low (0.09 at ME.331) to a moderate value (0.23 at ME.555). Those estimates show that genetic progress can be achieved for BW through selection. Both genetic and genomic associations between BW and HR to TICK, GIN, and EIM confirmed that parasite infestation impacted the performance of animals. Selection for BW under an environment with a controlled parasite burden is an alternative to improve both, BW and HR. There was no impact of age of measurement on the estimates of genetic variance for HR. Five quantitative trait loci (QTL) were associated with HR to EIM but none with HR to TICK and to GIN. These QTL contain genes that were previously shown to be associated with the production of antibody modulators and chemokines that are released in the intestinal epithelium.CONCLUSIONS:Selection for BW under natural infestation and controlled parasite burden, via prophylactic parasite control, contributes to the identification of animals that are resilient to nematodes and Eimeria ssp. Although we verified that sufficient genetic variation existed for HR, we did not find any genes associated with mechanisms that could justify the expression of HR to TICK and GIN.

This study evaluate the impact of the reuse of the intravaginal progesterone implant (DIP), the body condition score and the racial composition on the pregnancy rate of Nelore and Angus heifers (F1) and Nelore cows of different categories submitted to different protocols of TAI, from a database of 3,093 females submitted to the same hormonal induction protocol and from the mating season of a commercial farm in the north of Minas Gerais. The racial com- position influenced the pregnancy rate of heifers, with rates of 55.11% for Nellore heifers and 64.36% for ½ Angus, showing that the ½ Angus breed has 1.55 times more chances of successful gestation compared to the breed Nellore. There is no effect of the progesterone implant until the third use on the pregnancy rate of the heifers evaluated. The increase of one unit in the body condition score on the scale of 1 to 5 implies 1.9109 or 91.09% times more success in pregnancy. The category of calving cows did not significantly affect the pregnancy rate in the evaluated herd, with pregnancy rates of 58.1%, 62.8%, 77.7% and 62.9% for primiparous, early primiparous, secondary and multiparous, respectively. The introduction of ½ Angus heifers to explore the effects of heterosis and complementarity between breeds is a viable alternative. Cows, when well managed in the postpartum period, obtain pregnancy rates higher than that observed in the national average.

The purpose of the present study was to evaluate the principal component analysis (PCA) to guide technical assistance regarding several dairy farms’ issues, which includes improving microbiological quality and physical-chemical composition of raw refrigerated milk. Data of monthly analysis of fat, protein, lactose, dry defatted stratum, somatic cell count, total bacterial count, milk temperature of 8,101 samples of milk from expansion tanks and production of 78 farms located in the northern region of Minas Gerais, Brazil were processed. Descriptive statistical measures and Pearson correlation coefficient were estimated involving all evaluated traits during the dry and rainy seasons. In addition, multivariate analyses were performed using PCA. The results showed that two farm sites were negatively related to milk quality in both seasons. One farm stood out positively, being able to be used as a herd management model to drive technical assistance actions. Thus, PCA is efficient in simplifying large amounts of data, allowing simpler and faster technical herd management interpretation.

-The objective of this work is to estimate genetic parameters and breeding values to improve embryo and oocyte production, using repeatability and random regression models (RRM) for Gir dairy cattle. We used 11,398 records of ovum pick-up from 1,747 dairy Gir donors and evaluated sixteen different models: the traditional repeatability model and fifteen RRM, each of which considered a different combination of Legendre polynomial regressors to describe the additive genetic and permanent environment effects. The 4G1P model (four regressors for the genetic effect and one regressor for the permanent environment effect) is the most suitable model to analyze the number of viable and total oocytes, while the 3G1P is the best model to analyze the number of cleaved and viable embryos, according to the values of the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). The heritability estimated with the RRM was higher than that estimated with the repeatability model. The high repeatability reported for oocyte and embryo count traits indicates that donors, which had high oocyte and embryo counts in the first ovum pick-up, should maintain this result in the next ovum pick-up. Genetic correlations between adjacent ages were high and positive, while genetic correlations between extreme ages were weak. We observed a reranking of the top sires and females (heifers and cows) over the period evaluated. The reliability of the estimated breeding values by RRM showed changes across age, and the expected genetic gains by RRM are larger. This shows that RRM is most suitable alternative for the evaluation and selection of oocyte and embryo count traits.

Background: Host resilience (HR) to parasites can affect growth in pastured raised cattle. This study is a detailed investigation of the genetic mechanisms of HR to ticks (TICK), gastrointestinal nematodes (GIN), and Eimeria spp. (EIM) under natural infestation. HR was defined as the slope coefficient of random regression models of body weight (BW) when TICK, GIN, and EIM burdens were used as environmental gradients. The BW was evaluated in five measurement events (ME): when animals were 331, 385, 443, 498, and 555 days old on average. 7307 BW records were available from 1712 animals weighted at least in one ME. Out of those, 1075 animals had valid genotypic information after quality control analysis that were used in genome-wide association studies (GWAS) and GWAS meta-analyses to identify genomic regions associated with HR. Results: Both the genetic correlations between intercept and HR to each parasite, and the genetic correlations between BW measured in animals submitted to different parasite burden indicated that there was genotype x parasite burden interaction for BW, and selection for BW under environment with controlled parasite burden might be an efficient strategy to improve both, BW and HR. Furthermore, there was no impact of age of measurement on genetic variance estimates for HR to different parasites. However, genetic correlation between HR to the same parasite measured in different ages ranged from low to moderate in magnitude, with a posteriori means (high posterior density interval with 90% of samples) varying from 0.13 (-0.05; 0.35) to 0.40 (0.15; 0.63) for TICK, from 0.11 (-0.06; 0.29) to 0.52 (0.37; 0.67) for GIN and from 0.25 (0.07; 0.43) to 0.56 (0.34; 0.77) for EIM. Conclusions: These results indicate the importance of age of measurement in studies on HR. HR to GIN and EIM can be used as a complementary tool to parasitic control management, and a multiple trait selection method that combine BW and HR to parasites should be used in parasitic endemic areas to avoid economic losses due parasitic diseases.

Genetic correlation is the outcome of linkage disequilibrium and/or pleiotropic genes. As such, identifying which genes take part in the genetic control of genetically correlated traits can help us better understand the relationship between economic traits and promote more efficient breeding programs. We aim to estimate the genetic correlations between growth, reproduction and parasite burden traits and to identify functional candidate genes (FCG) underlying these correlations. Six traits were evaluated, comprising two of growth (body weight - BW and average daily gain - ADG), one reproductive trait (scrotal circumference - SC) and three related to parasite burden (tick count - TICK, gastrointestinal nematode eggs per gram of feaces - GIN, and Eimeria spp. oocysts per gram of faeces - EIM). The genetic correlations were estimated using a multiple-trait model. A total of 21,667 SNP markers were used to perform a single-step GWAS and to identify genomic windows explaining at least 1% of the genetic variance for the studied traits. The posterior means and highest posterior density intervals of the genetic correlations were positive and of moderate magnitudes for the pairs of traits BW-ADG (0.64; 0.52, 0.76), BW-SC (0.38; 0.26, 0.50), BW-TICK (0.39; 0.25, 0.76), ADG-SC (0.27; 0.11, 0.43), and TICK-EIM (0.33; 0.12, 0.53). Only the pair ADG-EIM presented a negative correlation (-0.22; -0.39, -0.05). All the other pairs showed genetic correlations close to zero. Additionally, functional analyses were performed and FCGs were selected based on their roles in biological processes for each of the traits. The effects of the SNPs were calculated as a proportion of the genetic standard deviation. Seven FCGs (SLC16A4, KCNA2, LAMTOR5, DUSP10, MAP3K1, TPMT, and KIF13A) were identified for more than one trait. Regardless of the genetic correlation values (lowmoderate), there were FCGs which could influence both correlated traits. There were SNPs mapped in FCGs that might be used to promote genetic improvement in multiple traits. There are common FCGs that might control production, reproduction and parasite burden traits in beef cattle and contribute to genetic correlation values.

The existence of buffering mechanisms is an emerging property of biological networks, and this results in the buildup of robustness through evolution. So far, there are no explicit methods to find loci implied in buffering mechanisms. However, buffering can be seen as interaction with genetic background. Here we develop this idea into a tractable model for quantitative genetics, in which the buffering effect of one locus with many other loci is condensed into a single statistical effect, multiplicative on the total additive genetic effect. This allows easier interpretation of the results and simplifies the problem of detecting epistasis from quadratic to linear in the number of loci. Using this formulation, we construct a linear model for genome-wide association studies that estimates and declares the significance of multiplicative epistatic effects at single loci. The model has the form of a variance components, norm reaction model and likelihood ratio tests are used for significance. This model is a generalization and explanation of previous ones. We test our model using bovine data: Brahman and Tropical Composite animals, phenotyped for body weight at yearling and genotyped at high density. After association analysis, we find a number of loci with buffering action in one, the other, or both breeds; these loci do not have a significant statistical additive effect. Most of these loci have been reported in previous studies, either with an additive effect or as footprints of selection. We identify buffering epistatic SNPs present in or near genes reported in the context of signatures of selection in multi-breed cattle population studies. Prominent among these genes are those associated with fertility (INHBA, TSHR, ESRRG, PRLR, and PPARG), growth (MSTN, GHR), coat characteristics (KIT, MITF, PRLR), and heat resistance (HSPA6 and HSPA1A). In these populations, we found loci that have a nonsignificant statistical additive effect but a significant epistatic effect. We argue that the discovery and study of loci associated with buffering effects allow attacking the difficult problems, among others, of the release of maintenance variance in artificial and natural selection, of quick adaptation to the environment, and of opposite signs of marker effects in different backgrounds. We conclude that our method and our results generate promising new perspectives for research in evolutionary and quantitative genetics based on the study of loci that buffer effect of other loci.

Background Twenty-five phenotypes were measured as indicators of bull fertility (1099 Brahman and 1719 Tropical Composite bulls). Measurements included sperm morphology, scrotal circumference, and sperm chromatin phenotypes such as DNA fragmentation and protamine deficiency. We estimated the heritability of these phenotypes and carried out genome-wide association studies (GWAS) within breed, using the bovine high-density chip, to detect quantitative trait loci (QTL). Results Our analyses suggested that both sperm DNA fragmentation and sperm protamine deficiency are heritable (h 2 from 0.10 to 0.22). To confirm these first estimates of heritability, further studies on sperm chromatin traits, with larger datasets are necessary. Our GWAS identified 12 QTL for bull fertility traits, based on at least five polymorphisms (P < 10 −8 ) for each QTL. Five QTL were identified in Brahman and another seven in Tropical Composite bulls. Most of the significant polymorphisms detected in both breeds and nine of the 12 QTL were on chromosome X. The QTL were breed-specific, but for some traits, a closer inspection of the GWAS results revealed suggestive single nucleotide polymorphism (SNP) associations (P < 10 −7 ) in both breeds. For example, the QTL for inhibin level in Braham could be relevant to Tropical Composites too (many polymorphisms reached P < 10 −7 in the same region). The QTL for sperm midpiece morphological abnormalities on chromosome X (QTL peak at 4.92 Mb, P < 10 −17 ) is an example of a breed-specific QTL, supported by 143 significant SNPs (P < 10 −8 ) in Brahman, but absent in Tropical Composites. Our GWAS results add evidence to the mammalian specialization of the X chromosome, which during evolution has accumulated genes linked to spermatogenesis. Some of the polymorphisms on chromosome X were associated to more than one genetically correlated trait (correlations ranged from 0.33 to 0.51). Correlations and shared polymorphism associations support the hypothesis that these phenotypes share the same underlying cause, i.e. defective spermatogenesis. Conclusions Genetic improvement for bull fertility is possible through genomic selection, which is likely more accurate if the QTL on chromosome X are considered in the predictions. Polymorphisms associated with male fertility accumulate on this chromosome in cattle, as in humans and mice, suggesting its specialization.

This study aimed at estimating genetic parameters of sex-influenced production traits, evaluating the impact of genotype-by-sex interaction, and identifying the selection criteria that could be included in multiple-trait genetic evaluation to increase the rate of genetic improvement in both sexes. To achieve this goal, we used 10 male and 10 female phenotypes, which were measured in a population of 2111 Australian Brahman cattle genotyped at high-density. Heritability estimates ranged from very low (0.03 ± 0.03 for cows’ days to calving at first calving opportunity, DC1), to moderate (0.33 ± 0.08 for cows’ adult body weight, AWTc), and to high (0.95 ± 0.07 for cows’ hip height, HHc). Genetic correlation (rg) estimates between male and female homologous traits were favorable and ranged from moderate to high values, which indicate that selection for any of the traits in one sex would lead to a correlated response with the equivalent phenotype in the other sex. However, the estimated direct response was greater than the indirect response. Moreover, Pearson correlations between estimated breeding values obtained from each sex separately and from female and male homologous traits combined into a single trait in univariate analysis ranged from 0.74 to 0.99, which indicate that small ranking variation might appear if male and female traits are included as single or separate phenotypes. Genetic correlations between male growth and female reproductive traits were not significant, ranging from − 0.07 ± 0.13 to 0.45 ± 0.65. However, selection to improve HHc and AWTc in cows may reduce the percentage of normal sperm at 24 months of age (PNS24), possibly due to correlated effects in the same traits in males, which are related to late maturing animals. Hip height in cows and PNS24, as well as blood insulin-like growth factor 1 (IGF1) concentration in bulls at 6 months of age are efficient selection criteria to improve male growth and female reproductive traits, simultaneously. In the presence of genotype-by-sex interactions, selection for traits in each sex results in high rates of genetic improvement, however, for the identification of animals with the highest breeding value, data for males and females may be considered a single trait.

The comprehensive analyses of longitudinal traits under sequential selection could improve genetic parameters estimates and lead to more accurate selection decisions. The objective of this study was to evaluate statistical models for analyzing longitudinal traits under sequential selection. We used single trait (STM), multiple trait (MTM) and random regression model with linear splines polynomials (RRM) to estimate genetic parameters for body weight records of Nellore young bulls. First, we used a complete dataset (DS100) with 60,550 body weight records of 12,110 young bulls. Two additional datasets were also obtained from DS100. They were obtained with a sequential selection of 85% (DS85) and 70% (DS70) of heaviest animals. In addition, some datasets with the same number of records as DS85 and DS70 were also obtained with random sampling of 85% (RS85) and 70% (RS70) of body weight records at each age. Body weights were standardized at 330, 385, 440, 495 and 550 days of age for STM and MTM analysis. In RRM, the knots of linear splines were fitted at 250, 330, 385, 440, 495, 550 and 597 days of age. The estimates of additive genetic, residual and phenotypic variances from STM analysis of DS85 and DS70 were lower than the corresponding estimates from STM analysis of DS100. However, the estimates of genetic and environmental parameters from MTM and RRM analysis of DS100, DS85 and DS70 were similar. The reduction of dataset size with random sampling (RS85 and RS70) did not affect the estimates of genetic and environmental parameters from STM, MTM and RRM analysis. MTM and RRM are adequate for genetic evaluation of the longitudinal traits under sequential selection, but RRM presents some advantages over MTM. RRM with linear splines does not need previous adjustments of the body weights for standard ages and it also provides estimates of genetic and environmental parameters directly at the same points as the corresponding traits in MTM.

Progesterone signaling and uterine function are crucial in terms of pregnancy establishment. To investigate how the uterine tissue and its secretion changes in relation to puberty, we sampled tissue and uterine fluid from six pre- and six post-pubertal Brahman heifers. Post-pubertal heifers were sampled in the luteal phase. Gene expression of the uterine tissue was investigated with RNA-sequencing, whereas the uterine fluid was used for protein profiling with mass spectrometry. A total of 4034 genes were differentially expressed (DE) at a nominal P-value of 0.05, and 26 genes were significantly DE after Bonferroni correction (P < 3.1 × 10-6 ). We also identified 79 proteins (out of 230 proteins) that were DE (P < 1 × 10-5 ) in the uterine fluid. When we compared proteomics and transcriptome results, four DE proteins were identified as being encoded by DE genes: OVGP1, GRP, CAP1 and HBA. Except for CAP1, the other three had lower expression post-puberty. The function of these four genes hypothetically related to preparation of the uterus for a potential pregnancy is discussed in the context of puberty. All DE genes and proteins were also used in pathway and ontology enrichment analyses to investigate overall function. The DE genes were enriched for terms related to ribosomal activity. Transcription factors that were deemed key regulators of DE genes are also reported. Transcription factors ZNF567, ZNF775, RELA, PIAS2, LHX4, SOX2, MEF2C, ZNF354C, HMG20A, TCF7L2, ZNF420, HIC1, GTF3A and two novel genes had the highest regulatory impact factor scores. These data can help to understand how puberty influences uterine function.

Three hundred mixed parity sows of a high prolificacy genetic line were used to evaluate the impact of the supplementation of different levels of feed flavor during lactation on their productive and reproductive performance under tropical conditions. Sows were distributed in a completely randomized experimental design among 3 dietary treatments: control diet (T1) and other two diets with different levels of inclusion (T2 = 250 and T3 = 500 g/ton) of a feed flavor during 24 d lactation and WEI. The average minimum and maximum ambient temperatures and daily relative humidity measured during the experimental period were 17.4 and 34.7 degrees C, and 38.0% and 93.8%, respectively. The treatments influenced (P < 0.001) the sows voluntary feed intake, the T3 sows showed a higher intake than T2 and higher than T1 (6.60 vs. 6.02 vs. 5.08 kg/d, respectively). When compared among sows fed the feed flavor, the higher level of inclusion (T3) showed a +9.6% higher (P < 0.001) feed intake than T2 sows. The sows from T3 showed a higher (P = 0.039) number of weaned piglets when compared to T2 and higher than T1 (13.45 vs. 13.07 vs. 12.95, respectively). There was an effect of the treatment (P < 0.001) on litter daily gain where litters from T3 sows showed a higher daily gain when compared to T2 and T1 (3.37 vs. 2.75 vs. 2.58 kg/d, respectively). Average weaning weight was also higher (P < 0.001) for piglets from T3 sows when compared to T2 and Ti (7.00 vs. 6.16 vs. 5.86 kg, respectively). Average daily milk production was higher (P < 0.001) in the T3 sows when compared with the T2 and T1 fed sows (12.99 vs. 9.55 vs. 8.59 kg/d, respectively). The weaning-to-oestrus interval did not differ among treatments and averaged 4.3 d (P > 0.10). Respiratory frequency was influenced (P = 0.027) by treatments, whereas T3 sows showed on average a higher respiratory rate when compared with T2 and T1 (82.7 vs. 79.6 vs. 65.4 movements/min, respectively). The treatments influenced (P < 0.001) the rectal temperatures, where on average T1 sows showed lower values when compared to T2 and T3 fed sows (38.8 vs. 39.1 vs. 39.3 degrees C, respectively). In conclusion, this experiment has demonstrated that the strategic use of feed flavor to stimulate sows voluntary feed intake can benefit milk production and as a consequence improve litter performance all of which can help attenuate the negative effects of heat stress conditions on the nursing sow.

This study aimed to verify if random regression models using linear splines (RRMLS) are suitable for identifying genetic parameters in multiple-breed populations and also to investigate whether an interaction exists between the breeding value (BV) of sires and their progeny breed group. Ten populations were simulated by crossing 2 breeds with distinct genetic variance and nonzero segregation variance. To obtain the genetic parameters, 2 models were used: a multiple-trait model (MULT), in which the trait was considered distinct when evaluated in each group (1/2P1 + 1/2P2, 5/8P1 + 3/8P2, and 3/4P1 + 1/4P2), and a RRMLS with the spline polynomial knots adjusted to these same groups. The genetic parameters estimated through MULT and RRMLS did not differ from the simulated values. The correlations between BV (simulated and estimated) of animals were high and varied from 0.74 to 0.76, which indicates the efficiency of using MULT and RRMLS for predicting BV. Using field data, the traits age at first calving (AFC), first lactation length (LL), and 305-d milk yield (MY-305) from a multiple-breed population of Holstein-Gyr cattle were analyzed. The BV of animals were modeled through RRMLS with 3, 5, and 7 knots, distributed in accordance with the fraction of Holstein breed in each progeny breed group. It was verified that RRMLS with 7 knots for adjusting mean trajectories and genetic effects, with homogeneous residual variance, best fit AFC and LL. For MY-305, the best fit for mean trajectory and genetic effects was the RRMLS with 5 knots and with homogeneous residual variance. The posterior means of heritability varied from 0.21 to 0.48, 0.21 to 0.38, and 0.10 to 0.33 for AFC, LL, and MY-305, respectively. Estimates from genetic parameters obtained by using RRMLS with field data showed that this model is a useful tool for genetic evaluations of populations formed by a great number of breed groups. An interaction occurred between the BV of sires and their progeny breed group, and the genetic parameters for AFC, LL, and MY-305 traits from a multiple-breed population depend on breed composition of the progeny from which the evaluations are based.

A combined matrix that exploits genealogy together with marker-based information could improve the selection of elite individuals in breeding programs. We present genetic parameters for adaptive and growth traits in beef cattle by exploring linear combinations of pedigree-based (A) and marker-based (G) relationship matrices. We use a data set with 2,111 Brahman (BB) and 2,550 Tropical Composite (TC) cattle with genotypes for 729,068 SNP, and phenotypes for five traits. A weighted relationship matrix (WRM) combining G and A was constructed as WRM = λG + (1 - λ)A. The weight (λ) was explored at values from 0.0 to 1.0, at 0.1 intervals. Additionally, four alternative G matrices, in the WRM, were evaluated according to the selection of SNP used to generate them: 1) Gw: all autosomal SNP with minor allele frequency (MAF) > 1%; 2) Gg: autosomal SNP with MAF > 1% and mapped inside to gene coding regions; 3) Gp: autosomal SNP with MAF > 1% and previously reported to have significant pleiotropic effect in these two populations; and 4) Gc: autosomal SNP with MAF > 1% and with significant correlated effects previously reported in both BB and TC populations. In addition, two A matrices were evaluated: 1) A: all relationships between animals were considered after tracing back known ancestors; and 2) Ad: a distorted A matrix where a random 1% of the off-diagonal nonzero values were set to zero to simulate relationship errors. Five independent Ad matrices were explored each with a different random 1% of relationships masked. Criteria for comparing the resulting WRM included estimates of heritability (h2) and cross-validation accuracy (ACC) of genomic estimated breeding values. The choice of WRM had a greater impact on h2 than on ACC estimates. The 1% errors introduced in pedigree relationships generated large distortion in genetic parameters and ACC estimates. However, employing a λ > 0.7 was an efficient mechanism to compensate for the errors in A. Additionally, although significant (P-value < 0.0001), we found no consistent relationship between the type of SNP used to compute G and h2 or ACC estimates. We devised the optimal value of λ for maximum h2 and ACC at λ = 0.7 suggesting a 70% and 30% weighting to genomic and genealogical information, respectively, as an optimal strategy to compensate for pedigree errors, to improve genetic parameters estimates and lead to more accurate selection decisions.

This study aimed to evaluate associations among final weight (FW), average daily gain (ADG), scrotal circumference (SC), and visual score (VS) of beef cattle in performance tests on pasture or in feedlots. Genetic parameters for FW, ADG, SC, and VS of young Nellore bulls performance-tested on pasture or in feedlots were evaluated by mixed model. The performance test and final age were considered as fixed effects and additive genetic and residual effects were considered as random effects. Additive genetic and residual variances for final weight and average daily gain were smaller on pasture than in feedlots. There was no difference between genetic and residual variances and heritability for scrotal circumference on pasture or in feedlots. Genetic variance and heritability for visual score on pasture were smaller than those in feedlots. The posterior means (and highest posterior density intervals with 90% of samples (HPD90) in parentheses) for heritability were 0.46 (0.42; 0.50) and 0.49 (0.41; 0.55) for FW, 0.25 (0.22; 0.29) and 0.25 (0.19; 0.30) for ADG, 0.56 (0.51; 0.61) and 0.60 (0.51; 0.68) for SC, and 0.31 (0.27; 0.34) and 0.42 (0.36; 0.48) for VS on pasture or in feedlots, respectively. The genetic correlations (posterior means with HPD90 in parentheses) were 0.74 (0.69; 0.79) and 0.67 (0.58; 0.77) between FW and ADG; 0.49 (0.43; 0.55) and 0.60 (0.53; 0.68) for FW and SC; 0.79 (0.75; 0.83) and 0.85 (0.80; 0.90) for FW and VS; 0.37 (0.29; 0.46) and 0.34 (0.19; 0.50) for ADG and SC; 0.65 (0.59; 0.71) and 0.74 (0.64; 0.84) for ADG and VS; and 0.46 (0.39; 0.52) and 0.53 (0.44; 0.62) for SC and VS, obtained on pasture or in feedlots, respectively. The genetic and residual (co) variances of growth, scrotal circumference, and visual score of beef cattle vary across environments; however, genetic and residual correlation and efficiency of correlated response among these traits remain constant on pasture or in feedlots.

Chromosomal regions that were associated (P < 0.01) with scrotal circumference (SC) and percentage of morphologically normal sperm (PNS) are reported according to genome-wide association studies in Tropical Composite cattle. Bulls were genotyped with Illumina SNP chips and association analyses were performed using animal models. Chromosome X had several SNP associated with SC, PNS or both traits (7,859 SNP). Polymorphisms associated with SC and PNS can contribute to new methods of estimating breeding values , which may enhance the selection of bulls with improved reproductive performance.