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Fertility traits, such as heifer pregnancy, are economically important in cattle production systems, and are therefore, used in genetic selection programs. The aim of this study was to identify single nucleotide polymorphisms (SNPs) using RNA-sequencing (RNA-Seq) data from ovary, uterus, endometrium, pituitary gland, hypothalamus, liver, longissimus dorsi muscle, and adipose tissue in 62 candidate genes associated with heifer puberty in cattle. RNA-Seq reads were assembled to the bovine reference genome (UMD 3.1.1) and analyzed in five cattle breeds; Brangus, Brahman, Nellore, Angus, and Holstein. Two approaches used the Brangus data for SNP discovery 1) pooling all samples, and 2) within each individual sample. These approaches revealed 1157 SNPs. These were compared with those identified in the pooled samples of the other breeds. Overall, 172 SNPs within 13 genes (CPNE5, FAM19A4, FOXN4, KLF1, LOC777593, MGC157266, NEBL, NRXN3, PEPT-1, PPP3CA, SCG5, TSG101, and TSHR) were concordant in the five breeds. Using Ensembl's Variant Effector Predictor, we determined that 12% of SNPs were in exons (71% synonymous, 29% nonsynonymous), 1% were in untranslated regions (UTRs), 86% were in introns, and 1% were in intergenic regions. Since these SNPs were discovered in RNA, the variants were predicted to be within exons or UTRs. Overall, 160 novel transcripts in 42 candidate genes and five novel genes overlapping five candidate genes were observed. In conclusion, 1157 SNPs were identified in 62 candidate genes associated with puberty in Brangus cattle, of which, 172 were concordant in the five cattle breeds. Novel transcripts and genes were also identified.

We evaluated the impact of cytoplasmic lineage effects (Lc) for growth traits on genetic evaluation, including the genetic covariance between direct and maternal effects (σ am ). Pedigree data from 496,190 Nellore animals and observations on birth weight (BW, N = 243,391), weaning weight (WW, N = 431,681), and post-weaning weight gain adjusted to 345 days (PWG, N = 172,131) were analyzed. Four univariate models were used to obtain estimates of (co)variance components using the restricted maximum likelihood method in the BLUPF90 program. Model 1 included Lc and σ am . Model 2 included Lc and σ am was set to zero. Model 3 did not include Lc. Model 4 did not include Lc and σ am was set to zero. These models considered the effects of the Lc as random. Phenotypic variance obtained through cytoplasmic lineage effects was determined for all traits, ranging from 0.07 to 0.15, 0.15 to 0.03, and 0.05 to 0.03% for BW, WW, and PWG, respectively, for models 1 and 2. Correlations between direct and maternal genetic components were positive for WW and negative for BW and PWG. No differences were observed for genetic parameter estimates or animal ranking with the inclusion of σ am . For BW, the likelihood ratio suggested that model 1 best fits the data, while model 4 was the most appropriate for WW and PWG. Thus, these models are recommended for genetic evaluations. Despite the low magnitude of cytoplasmic lineages, this effect could predict breeding value and improve the selection of animals for BW in this Nellore population., Competing Interests: The authors declare no conflict of interest.

We obtained heritability and (co)variance component estimates for slaughter conformation scores at 420 days of age (SCS420), age at calving (first, AFC; second, ASC), calving occurrence until 38 months of age (CP38), weight at 420 days of age (W420), and scrotal circumference at 420 days (SC420) in Canchim (5/8 Charolais + 3/8 Zebu) cattle. A total of 23,168 records of Canchim animals, including 12,493 females and 10,675 males, were analyzed. SCS420 indicated carcass structure, muscle development, and subcutaneous fat deposition. The slaughter conformation score of each animal was relative to the whole contemporary group; 1 corresponded to the lowest expression of the trait and 6 to the highest. Heritabilities, and genetic and residual correlation estimates between SCS420 and reproductive and weight traits, were estimated by multitrait analyses using an animal model with Bayesian inference, employing a linear model for AFC, ASC, SC420, and W420 and a threshold model for CP38 and SCS420. Heritability estimates for SCS420, AFC, ASC, CP38, W420, and SC420 were 0.11, 0.15, 0.15, 0.15, 0.30, and 0.30, respectively. Genetic correlation estimates between SCS420 and the other traits were 0.08 (AFC), 0.58 (ASC), 0.08 (CP38), 0.43 (W420), and 0.17 (SC420). Visual slaughter conformation scores respond to individual selection and can be used as selection criteria in Canchim cattle. Selection to improve sexual precocity would not be effective in improving carcass conformation and composition, and selection for animals with high breeding values for yearling weight may improve slaughter conformation at the yearling stage.

The aim of this study was to estimate genetic and phenotypic associations of growth traits with carcass and meat traits in Nellore cattle. Data from male and female animals were used for weaning weight (WW; N = 241,416), yearling weight (YW, N = 126,596), weight gain from weaning to yearling (GWY, N = 78,687), and yearling hip height (YHH, N = 90,720), respectively; 877 male animals were used for hot carcass weight (HCW) and 884 for longissimus muscle area (LMA), backfat thickness (BT), marbling score (MS), and shear force (SF). The variance components were estimated by the restricted maximum likelihood method using three-trait animal models that included WW. The model for WW included direct and maternal additive genetic, maternal permanent environmental, and residual effects as random effects; contemporary group as fixed effects; and age of dam at calving and age of animal as covariates (linear and quadratic effects). For the other traits, maternal effects and the effect of age of dam at calving were excluded from the model. Heritability ranged from 0.10 ± 0.12 (LMA) to 0.44 ± 0.007 (YW). Genetic correlations ranged from -0.40 ± 0.38 (WW x LMA) to 0.55 ± 0.10 (HCW x YW). Growth, carcass, and meat traits have sufficient genetic variability to be included as selection criteria in animal breeding programs.

The objective of this study was to estimate genetic parameters for 305-day cumulative milk yield (MY305) and its association with test-day milk yield (TDMY) in Saanen and Alpine goats in order to provide information that allows the use of TDMY as selection criteria. This was done using standard multi-trait and reduced rank models. Data from 1157 lactations, including the first three kiddings, and 5435 test-day records from 683 Saanen and 449 Alpine goats were used. MY305 was analyzed together with TDMY by multi-trait analysis, from the first to tenth test-day, using records of the first three lactations as repeated measures. Three multi-trait models were used: a standard (SM) and two reduced rank models that fitted the first two (PC2) and three (PC3) genetic principal components. Akaike and Schwarz Bayesian information criteria were used to compare models. Heritability for TDMY estimated with the SM ranged from 0.20 to 0.66, whereas the range calculated from the PC2 model was 0.16 to 0.63. Genetic correlations between TDMY and MY305 were positive and moderate to high, ranging from 0.56 to 0.98 when estimated with the SM, and 0.91 to 1.00 when estimated with the PC2. The standard multi-trait model produced estimates that were more accurate than the reduced rank models. Although the SM provided the worst fit according to the two model selection criteria, it was the best in this dataset.

The objective of this study was to evaluate associations between single nucleotide polymorphism (SNP) markers and carcass traits measured postmortem in Nellore cattle. Records of loin eye area (LEA) and backfat thickness (BF) from 740 males and records of hot carcass weight (HCW) from 726 males were analyzed. All of the animals were genotyped using the BovineHD BeadChip. Association analyses were performed by the restricted maximum likelihood method that considered one SNP at a time. Significant SNPs were identified on chromosomes 2 and 6 for LEA and on chromosomes 7, 1, and 2 for BF. For HCW, associations with SNPs were found on chromosomes 13, 14, and 28, in addition to genome regions that were directly related to this trait, such as the EFCAB8 and VSTM2L genes, and to bone development (RHOU). Some SNPs were located in very close proximity to genes involved in basal metabolism (BLCAP, NNAT, CTNNBL1, TGM2, and LOC100296770) and the immune system (BPI).

The objective of this study was to quantify the magnitude of genotype-environment interaction (GxE) effects on age at first calving (AFC), scrotal circumference (SC), and yearling weight (YW) in Nellore cattle using reaction norms. For the study, 89,152 weight records of female and male Nellore animals obtained at yearling age were used. Genetic parameters were estimated with a single-trait random-regression model using Legendre polynomials as base functions. The heritability estimates were of low to medium magnitude for AFC (0.05 to 0.47) and of medium to high magnitude for SC (0.32 to 0.51) and YW (0.13 to 0.72), and increased as the environmental gradient became more favorable. The genetic correlation estimates ranged from 0.25 to 1.0 for AFC, from 0.71 to 1.0 for SC, and from 0.42 to 1.0 for YW. High Spearman correlation coefficients were obtained for the three traits, ranging from 0.97 to 0.99. The reaction norms along the environmental gradient of 10 sires each with the highest or lowest breeding value for YW predicted by single-trait analysis demonstrated more plastic phenotypes for YW and more robust phenotypes for SC. The effect of GxE was most important for YW and AFC with respect to SC. When animals are selected for higher SC or YW or lower AFC, considering or not the GxE effect, it is expected that the same animals will be selected. The reaction norms obtained based on sire breeding values along the environmental gradient showed that animals with extreme breeding values respond differently as environmental conditions improve.

The objective of this study was to identify associations between known polymorphisms in genes related to adipose tissue and sexual precocity in Nellore cattle. A total of 1689 precocious and non-precocious heifers belonging to farms participating in Conexão Delta G breeding program were studied. SNPs from the Illumina High-Density Bovine SNP BeadChip were used. This chip contains 777,000 SNPs located within the region of the candidate genes at a distance of up to 5 kb, considering that linkage disequilibrium (LD) exists at this distance. Linear models were used for statistical analysis. The fastPHASE and GenomeStudio programs were used for haplotype reconstruction and LD analysis based on r2 statistics. Fifty-seven candidate genes and 443 SNPs were analyzed: among the latter, 370 SNPs formed 83 haplotypes, while the remaining SNPs were studied separately. Statistical analysis showed that only three haplotypes, one haplotype consisting of two SNPs located in the FABP4 gene and two haplotypes consisting of four and two SNPs located in the PPP3CA gene, had a significant effect on sexual precocity at P < 0.05. It can be concluded that the FABP4 and PPP3CA genes influence sexual precocity and may therefore be used in selection programs designed to improve sexual precocity in Nellore cattle.

The objective of this study was to estimate the genetic and environmental parameters for carcass, carcass part, and organ weights in a paternal strain of broiler chickens that was selected mainly for body weight at 42 days of age (BW42) to provide support for poultry genetic improvement programs. A total of 1448 chickens were used that resulted from the expansion of a pure paternal strain named TT, which was developed by Embrapa Suínos e Aves. The following weights were evaluated: BW42, chilled carcass, wing, drumstick meat, thigh meat, breast meat, breast fillet, back, liver, heart (HRT), and gizzard (GIZ). The variance component was estimated by the restricted maximum likelihood method using a multi-trait animal model. The general model included the additive genetic and residual random effects and the fixed effect of the sex-hatch group (10 levels). The heritability estimates ranged from 0.27 ± 0.06 for HRT to 0.44 ± 0.08 for GIZ. These results indicated that all the traits have enough additive genetic variability to respond to selection. The genetic correlation estimates between BW42 and the carcass and carcass part weights were high and positive. However, the genetic correlation estimates between BW42 and organ weights were low. In this population, the carcass traits might respond indirectly to selection applied to BW42. It can be concluded that selection to increase BW42 is not effective in improving broiler organ weight. Therefore, to obtain suitable genetic improvement for these traits, the selection indexes for broilers should include organ weight-based criteria.

The aim of this study was to identify single-nucleotide polymorphisms (SNPs) in buffaloes associated with milk yield and content, in addition to somatic cell scores based on the cross-species transferability of SNPs from cattle to buffalo. A total of 15,745 SNPs were analyzed, of which 1562 showed 1% significance and 4742 with 5% significance, which were associated for all traits studied. After application of Bonferroni's correction for multiple tests of the traits analyzed, we found 2 significant SNPs placed on cattle chromosomes BTA15 and BTA20, which are homologous to buffalo chromosomes BBU16 and BBU19, respectively. In this genome association study, we found several significant SNPs affecting buffalo milk production and quality. Furthermore, the use of the high-density bovine BeadChip was suitable for genomic analysis in buffaloes. Although extensive chromosome arm homology was described between cattle and buffalo, the exact chromosomal position of SNP markers associated with these economically important traits in buffalo can be determined only through buffalo genome sequencing.

To define the best strategies for genomic association studies and genomic selection, it is necessary to determine the extent of linkage disequilibrium (LD) and the genetic structure of the study population. The current study evaluated the transference of genomic information contained in the Illumina BovineHD BeadChip from cattle to buffaloes, and assessed the extent of the LD in buffaloes. Of the 688,593 bovine single nucleotide polymorphism (SNP) that were successfully genotyped from the 384 buffalo samples, only 16,580 markers were polymorphic, and had minor allele frequencies greater than 0.05. A total of 16,580 polymorphic SNPs were identified, which were uniformly distributed throughout the autosomes, because the density and mean distance between markers were similar for all autosomes. The average minor allele frequency for the 16,580 SNPs was 0.23. The overall mean LD for pairs of adjacent markers was 0.29 and 0.71, when measured as for r2 and |D'|, respectively. The 16,580 polymorphic SNPs were matched to Bos taurus chromosome in the current bovine genome assembly (Btau 4.2), and could be utilized in association studies. In conclusion, the Illumina BovineHD BeadChip contains approximately 16,580 polymorphic markers for the water buffalo, which are broadly distributed across the genome. These data could be used in genomic association and genomic selection studies; however, it might be necessary to develop a panel with specific SNP markers for water buffaloes.

The objective of this study was to estimate variance components and genetic parameters for accumulated 305-day milk yield (MY305) over multiple ages, from 24 to 120 months of age, applying random regression (RRM), repeatability (REP) and multi-trait (MT) models. A total of 4472 lactation records from 1882 buffaloes of the Murrah breed were utilized. The contemporary group (herd-year-calving season) and number of milkings (two levels) were considered as fixed effects in all models. For REP and RRM, additive genetic, permanent environmental and residual effects were included as random effects. MT considered the same random effects as did REP and RRM with the exception of permanent environmental effect. Residual variances were modeled by a step function with 1, 4, and 6 classes. The heritabilities estimated with RRM increased with age, ranging from 0.19 to 0.34, and were slightly higher than that obtained with the REP model. For the MT model, heritability estimates ranged from 0.20 (37 months of age) to 0.32 (94 months of age). The genetic correlation estimates for MY305 obtained by RRM (L23.res4) and MT models were very similar, and varied from 0.77 to 0.99 and from 0.77 to 0.99, respectively. The rank correlation between breeding values for MY305 at different ages predicted by REP, MT, and RRM were high. It seems that a linear and quadratic Legendre polynomial to model the additive genetic and animal permanent environmental effects, respectively, may be sufficient to explain more parsimoniously the changes in MY305 genetic variation with age.

We estimated heritability for subsequent rebreeding (SR) of heifers and genetic correlations between this trait and weaning weight (WW), weight gain from weaning to yearling (WG), age at first calving (AFC), and mature cow weight (MW), in order to evaluate whether SR could be included as selection criterion in Nellore cattle. The SR of heifers was defined by attributing a value of 1 (success) or 0 (failure) to heifers that calved or not, respectively, given that they had calved once before. Records from 127,430 Nellore animals were analyzed. Genetic parameters were estimated by Bayesian inference using a nonlinear (threshold) animal model for SR and a linear animal model for the other traits in three-trait analyses, including SR and WW in all analyses. The posterior means of heritability for SR, WW, WG, AFC, and MW were 0.18 ± 0.02, 0.21 ± 0.01, 0.30 ± 0.01, 0.21 ± 0.01, and 0.45 ± 0.04, respectively. The posterior mean estimates of genetic correlations between SR and WW, WG, AFC, and MW were -0.20 ± 0.06, 0.31 ± 0.07, -0.77 ± 0.05, and -0.15 ± 0.09, respectively. Based on these genetic correlations, selection for higher gains for WG and younger AFC should result in an increase in heifer SR rates, while long-term selection for increasing WW should promote unfavorable responses in heifer SR. The use of breeding values for heifer SR as a selection criterion of Nellore bulls could increase heifer SR rate without significant changes in MW.

We investigated genetic associations between mature cow weight (MW) and weaning weight (WW), yearling weight (YW), weight gain from birth to weaning (GBW), weight gain from weaning to yearling (GWY), weaning hip height (WHH), yearling hip height (YHH), scrotal circumference (SC), and age at first calving (AFC). Data from 127,104 Nellore animals born between 1993 and 2006, belonging to Agropecuária Jacarezinho Ltda., were analyzed. (Co)variance components were obtained by the restricted maximum likelihood method, applying an animal model in a multi-traits analysis. The model included direct genetic and residual effects as random effects, the fixed effects of contemporary group, and the linear and quadratic effects of animal age at recording (except for AFC, GBW, and GWY) and age of cow at calving as covariates (except for MW). The numbers of days from birth to weaning and from weaning to yearling were included as covariates for GBW and GWY, respectively. Estimated direct heritabilities were 0.43 ± 0.02 (MW), 0.33 ± 0.01 (WW), 0.36 ± 0.01 (YW), 0.28 ± 0.02 (GBW), 0.31 ± 0.01 (GWY), 0.44 ± 0.02 (WHH), 0.48 ± 0.02 (YHH), 0.44 ± 0.01 (SC), and 0.16 ± 0.03 (AFC). Genetic correlations between MW and productive traits were positive and of medium to high magnitude (ranging from 0.47 ± 0.03 to 0.71 ± 0.01). A positive and low genetic correlation was observed between MW and SC (0.24 ± 0.04). A negative genetic correlation (-0.19 ± 0.03) was estimated between MW and AFC. Selection to increase weight or weight gains at any age, as well as hip height, will change MW in the same direction. Selection for higher SC may lead to a long-term increase in MW. The AFC can be included in selection indices to improve the reproductive performance of beef cattle without significant changes in MW.

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression analyses, all female weight records from birth to eight years of age (data set I) were considered. From this general data set, a subset was created (data set II), which included only nine weight records: at birth, weaning, 365 and 550 days of age, and 2, 3, 4, 5, and 6 years of age. Data set II was analyzed using random regression and multi-trait models. The model of analysis included the contemporary group as fixed effects and age of dam as a linear and quadratic covariable. In the random regression analyses, average growth trends were modeled using a cubic regression on orthogonal polynomials of age. Residual variances were modeled by a step function with five classes. Legendre polynomials of fourth and sixth order were utilized to model the direct genetic and animal permanent environmental effects, respectively, while third-order Legendre polynomials were considered for maternal genetic and maternal permanent environmental effects. Quadratic polynomials were applied to model all random effects in random regression models on B-spline functions. Direct genetic and animal permanent environmental effects were modeled using three segments or five coefficients, and genetic maternal and maternal permanent environmental effects were modeled with one segment or three coefficients in the random regression models on B-spline functions. For both data sets (I and II), animals ranked differently according to expected breeding value obtained by random regression or multi-trait models. With random regression models, the highest gains in accuracy were obtained at ages with a low number of weight records. The results indicate that random regression models provide more accurate expected breeding values than the traditionally finite multi-trait models. Thus, higher genetic responses are expected for beef cattle growth traits by replacing a multi-trait model with random regression models for genetic evaluation. B-spline functions could be applied as an alternative to Legendre polynomials to model covariance functions for weights from birth to mature age.

Buffalo milk has excellent physical and chemical qualities as a consequence of the high percentage of constituents. This milk property is desirable for the dairy industry because it facilitates manufacture of mozzarella cheese. We estimated genetic parameters for milk yield, milk fat and protein and their effects on mozzarella cheese production using Bayesian inference. Using information from 4907 lactation records of buffaloes, genetic and non-genetic parameters were estimated for accumulated 305-day milk yield (MY), milk fat (%F) and protein (%P) percentages and mozzarella production per lactation (MP). The (co)variance components were obtained by Bayesian inference using a multiple trait model, which included as fixed effects contemporary group, milking number and buffalo age at calving as covariables (linear and quadratic), along with the additive genetic, permanent environmental and residual random effects. Mean a posteriori heritability distributions for MY, %F, %P, and MP were 0.25, 0.30, 0.38, and 0.23, respectively. The genetic correlation estimates between MY with %P and %F were negative and moderate. Positive genetic correlation estimates varying from 0.19 (%P/MP) to 0.95 (MY/MP) were obtained among the traits. Milk yield, milk components, and mozzarella production in Murrah buffaloes have enough genetic variation for selection purposes. We conclude that selection to increase milk yield would be effective in improving mozzarella production.