Genomic inbreeding estimation, runs of homozygosity, and heterozygosity-enriched regions uncover signals of selection in the Quarter Horse racing line.

With the advent of genomics, significant progress has been made in the genetic improvement of livestock species, particularly through increased accuracy in predicting breeding values for selecting superior animals and the possibility of performing a high-resolution genetic scan throughout the genome of an individual. The main objectives of this study were to estimate the individual genomic inbreeding coefficient based on runs of homozygosity (FROH ), to identify and characterize runs of homozygosity and heterozygosity (ROH and ROHet, respectively; length and distribution) throughout the genome, and to map selection signatures in relevant chromosomal regions in the Quarter Horse racing line. A total of 336 animals registered with the Brazilian Association of Quarter Horse Breeders (ABQM) were genotyped. One hundred and twelve animals were genotyped using the Equine SNP50 BeadChip (Illumina, USA), with 54,602 single nucleotide polymorphisms (SNPs; 54K). The remaining 224 samples were genotyped using the Equine SNP70 BeadChip (Illumina, USA) with 65,157 SNPs (65K). To ensure data quality, we excluded animals with a call rate below 0.9. We also excluded SNPs located on non-autosomal chromosomes, as well as those with a call rate below 0.9 or a p-value below 1 × 10-5 for Hardy-Weinberg equilibrium. The results indicate moderate to high genomic inbreeding, with 46,594 ROH and 16,101 ROHet detected. In total, 30 and 14 candidate genes overlap with ROH and ROHet regions, respectively. The ROH islands showed genes linked to crucial biological processes, such as cell differentiation (CTBP1, WNT5B, and TMEM120B), regulation of glucose metabolic process (MAEA and NKX1-1), heme transport (PGRMC2), and negative regulation of calcium ion import (VDAC1). In ROHet, the islands showed genes related to respiratory capacity (OR7D19, OR7D4G, OR7D4E, and OR7D4J) and muscle repair (EGFR and BCL9). These findings could aid in selecting animals with greater regenerative capacity and developing treatments for muscle disorders in the QH breed. This study serves as a foundation for future research on equine breeds. It can contribute to developing reproductive strategies in animal breeding programs to improve and preserve the Quarter Horse breed.

Genome-wide scans for signatures of selection in Mangalarga Marchador horses using high-throughput SNP genotyping.

BACKGROUND: The detection of signatures of selection in genomic regions provides insights into the evolutionary process, enabling discoveries regarding complex phenotypic traits. In this research, we focused on identifying genomic regions affected by different selection pressures, mainly highlighting the recent positive selection, as well as understanding the candidate genes and functional pathways associated with the signatures of selection in the Mangalarga Marchador genome. Besides, we seek to direct the discussion about genes and traits of importance in this breed, especially traits related to the type and quality of gait, temperament, conformation, and locomotor system. RESULTS: Three different methods were used to search for signals of selection: Tajima's D (TD), the integrated haplotype score (iHS), and runs of homozygosity (ROH). The samples were composed of males (n = 62) and females (n = 130) that were initially chosen considering well-defined phenotypes for gait: picada (n = 86) and batida (n = 106). All horses were genotyped using a 670 k Axiom® Equine Genotyping Array​ (Axiom MNEC670). In total, 27, 104 (chosen), and 38 candidate genes were observed within the signatures of selection identified in TD, iHS, and ROH analyses, respectively. The genes are acting in essential biological processes. The enrichment analysis highlighted the following functions: anterior/posterior pattern for the set of genes (GLI3, HOXC9, HOXC6, HOXC5, HOXC4, HOXC13, HOXC11, and HOXC10); limb morphogenesis, skeletal system, proximal/distal pattern formation, JUN kinase activity (CCL19 and MAP3K6); and muscle stretch response (MAPK14). Other candidate genes were associated with energy metabolism, bronchodilator response, NADH regeneration, reproduction, keratinization, and the immunological system. CONCLUSIONS: Our findings revealed evidence of signatures of selection in the MM breed that encompass genes acting on athletic performance, limb development, and energy to muscle activity, with the particular involvement of the HOX family genes. The genome of MM is marked by recent positive selection. However, Tajima's D and iHS results point also to the presence of balancing selection in specific regions of the genome.

Imputation accuracy to whole-genome sequence in Nellore cattle.

BACKGROUND: A cost-effective strategy to explore the complete DNA sequence in animals for genetic evaluation purposes is to sequence key ancestors of a population, followed by imputation mechanisms to infer marker genotypes that were not originally reported in a target population of animals genotyped with single nucleotide polymorphism (SNP) panels. The feasibility of this process relies on the accuracy of the genotype imputation in that population, particularly for potential causal mutations which may be at low frequency and either within genes or regulatory regions. The objective of the present study was to investigate the imputation accuracy to the sequence level in a Nellore beef cattle population, including that for variants in annotation classes which are more likely to be functional. METHODS: Information of 151 key sequenced Nellore sires were used to assess the imputation accuracy from bovine HD BeadChip SNP (~ 777 k) to whole-genome sequence. The choice of the sires aimed at optimizing the imputation accuracy of a genotypic database, comprised of about 10,000 genotyped Nellore animals. Genotype imputation was performed using two computational approaches: FImpute3 and Minimac4 (after using Eagle for phasing). The accuracy of the imputation was evaluated using a fivefold cross-validation scheme and measured by the squared correlation between observed and imputed genotypes, calculated by individual and by SNP. SNPs were classified into a range of annotations, and the accuracy of imputation within each annotation classification was also evaluated. RESULTS: High average imputation accuracies per animal were achieved using both FImpute3 (0.94) and Minimac4 (0.95). On average, common variants (minor allele frequency (MAF) > 0.03) were more accurately imputed by Minimac4 and low-frequency variants (MAF ≤ 0.03) were more accurately imputed by FImpute3. The inherent Minimac4 Rsq imputation quality statistic appears to be a good indicator of the empirical Minimac4 imputation accuracy. Both software provided high average SNP-wise imputation accuracy for all classes of biological annotations. CONCLUSIONS: Our results indicate that imputation to whole-genome sequence is feasible in Nellore beef cattle since high imputation accuracies per individual are expected. SNP-wise imputation accuracy is software-dependent, especially for rare variants. The accuracy of imputation appears to be relatively independent of annotation classification.

Application of the principal component analysis, cluster analysis, and partial least square regression on crossbreed Angus-Nellore bulls feedlot finished.

Principal component analysis (PCA) and the non-hierarchical clustering analysis (K-means) were used to characterize the most important variables from carcass and meat quality traits of crossbred cattle. Additionally, partial least square (PLS) regression analysis was applied between the carcass measurements and meat quality traits on the classes defined by the cluster analysis. Ninety-seven non-castrated F1 Angus-Nellore bulls feedlot finished were used. After slaughter, hot carcass weight, carcass yield, cold carcass weight, carcass weight losses, pH, and backfat thickness (BFT) were measured. Subsequently, samples of the longissimus thoracis were collected to analyze shear force (SF), cooking loss (CL), meat color (L*, chroma, and hue), intramuscular fat, protein, collagen, moisture, and ashes. Principal component 1 (PC1) was correlated with colorimetric variables, while PC2 was correlated with carcass weights. Afterwards, three clusters (k = 3) were formed and projected in the gradient defined by PC1 and PC2 and allowed distinguishing groups with divergent values for collagen, protein, moisture, CL, SF, and BFT. Animals from high chroma group presented meat with more attractive colors and tenderness (SF = 1.97 to 4.84 kg). Subsequently, the PLS regression on the three chroma groups revealed a good fitness and the coefficients are used to predict the chroma variable from the explanatory variables, which may have practical importance in attempts to predict meat color from carcass and meat quality traits. Thus, PCA, K-means, and PLS regression confirmed the relationship between meat color and tenderness.

Sliding window haplotype approaches overcome single SNP analysis limitations in identifying genes for meat tenderness in Nelore cattle.

BACKGROUND: Traditional single nucleotide polymorphism (SNP) genome-wide association analysis (GWAA) can be inefficient because single SNPs provide limited genetic information about genomic regions. On the other hand, using haplotypes in the statistical analysis may increase the extent of linkage disequilibrium (LD) between haplotypes and causal variants and may also potentially capture epistastic interactions between variants within a haplotyped locus, providing an increase in the power and robustness of the association studies. We performed GWAA (413,355 SNP markers) using haplotypes based on variable-sized sliding windows and compared the results to a single-SNP GWAA using Warner-Bratzler shear force measured in the longissimus thorasis muscle of 3161 Nelore bulls to ascertain the optimal window size for identifying the genomic regions that influence meat tenderness. RESULTS: The GWAA using single SNPs identified eight variants influencing meat tenderness on BTA 3, 4, 9, 10 and 11. However, thirty-three putative meat tenderness QTL were detected on BTA 1, 3, 4, 5, 8, 9, 10, 11, 15, 17, 18, 24, 25, 26 and 29 using variable-sized sliding haplotype windows. Analyses using sliding window haplotypes of 3, 5, 7, 9 and 11 SNPs identified 57, 61, 42, 39, and 21% of all thirty-three putative QTL regions, respectively; however, the analyses using the 3 and 5 SNP haplotypes, cumulatively detected 88% of the putative QTL. The genes associated with variation in meat tenderness participate in myogenesis, neurogenesis, lipid and fatty acid metabolism and skeletal muscle structure or composition processes. CONCLUSIONS: GWAA using haplotypes based on variable-sized sliding windows allowed the detection of more QTL than traditional single-SNP GWAA. Analyses using smaller haplotypes (3 and 5 SNPs) detected a higher proportion of the putative QTL.

Gene expression profile of intramuscular muscle in Nellore cattle with extreme values of fatty acid.

BACKGROUND: Fatty acid type in beef can be detrimental to human health and has received considerable attention in recent years. The aim of this study was to identify differentially expressed genes in longissimus thoracis muscle of 48 Nellore young bulls with extreme phenotypes for fatty acid composition of intramuscular fat by RNA-seq technique. RESULTS: Differential expression analyses between animals with extreme phenotype for fatty acid composition showed a total of 13 differentially expressed genes for myristic (C14:0), 35 for palmitic (C16:0), 187 for stearic (C18:0), 371 for oleic (C18:1, cis-9), 24 for conjugated linoleic (C18:2 cis-9, trans11, CLA), 89 for linoleic (C18:2 cis-9,12 n6), and 110 genes for α-linolenic (C18:3 n3) fatty acids. For the respective sums of the individual fatty acids, 51 differentially expressed genes for saturated fatty acids (SFA), 336 for monounsaturated (MUFA), 131 for polyunsaturated (PUFA), 92 for PUFA/SFA ratio, 55 for ω3, 627 for ω6, and 22 for ω6/ω3 ratio were identified. Functional annotation analyses identified several genes associated with fatty acid metabolism, such as those involved in intra and extra-cellular transport of fatty acid synthesis precursors in intramuscular fat of longissimus thoracis muscle. Some of them must be highlighted, such as: ACSM3 and ACSS1 genes, which work as a precursor in fatty acid synthesis; DGAT2 gene that acts in the deposition of saturated fat in the adipose tissue; GPP and LPL genes that support the synthesis of insulin, stimulating both the glucose synthesis and the amino acids entry into the cells; and the BDH1 gene, which is responsible for the synthesis and degradation of ketone bodies used in the synthesis of ATP. CONCLUSION: Several genes related to lipid metabolism and fatty acid composition were identified. These findings must contribute to the elucidation of the genetic basis to improve Nellore meat quality traits, with emphasis on human health. Additionally, it can also contribute to improve the knowledge of fatty acid biosynthesis and the selection of animals with better nutritional quality.

Assessing the value of phenotypic information from non-genotyped animals for QTL mapping of complex traits in real and simulated populations.

BACKGROUND: QTL mapping through genome-wide association studies (GWAS) is challenging, especially in the case of low heritability complex traits and when few animals possess genotypic and phenotypic information. When most of the phenotypic information is from non-genotyped animals, GWAS can be performed using the weighted single-step GBLUP (WssGBLUP) method, which permits to combine all available information, even that of non-genotyped animals. However, it is not clear to what extent phenotypic information from non-genotyped animals increases the power of QTL detection, and whether factors such as the extent of linkage disequilibrium (LD) in the population and weighting SNPs in WssGBLUP affect the importance of using information from non-genotyped animals in GWAS. These questions were investigated in this study using real and simulated data. RESULTS: Analysis of real data showed that the use of phenotypes of non-genotyped animals affected SNP effect estimates and, consequently, QTL mapping. Despite some coincidence, the most important genomic regions identified by the analyses, either using or ignoring phenotypes of non-genotyped animals, were not the same. The simulation results indicated that the inclusion of all available phenotypic information, even that of non-genotyped animals, tends to improve QTL detection for low heritability complex traits. For populations with low levels of LD, this trend of improvement was less pronounced. Stronger shrinkage on SNPs explaining lower variance was not necessarily associated with better QTL mapping. CONCLUSIONS: The use of phenotypic information from non-genotyped animals in GWAS may improve the ability to detect QTL for low heritability complex traits, especially in populations in which the level of LD is high.

Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference.

BACKGROUND: An important goal of Zebu breeding programs is to improve reproductive performance. A major problem faced with the genetic improvement of reproductive traits is that recording the time for an animal to reach sexual maturity is costly. Another issue is that accurate estimates of breeding values are obtained only a long time after the young bulls have gone through selection. An alternative to overcome these problems is to use traits that are indicators of the reproductive efficiency of the herd and are easier to measure, such as age at first calving. Another problem is that heifers that have conceived once may fail to conceive in the next breeding season, which increases production costs. Thus, increasing heifer's rebreeding rates should improve the economic efficiency of the herd. Response to selection for these traits tends to be slow, since they have a low heritability and phenotypic information is provided only later in the life of the animal. Genome-wide association studies (GWAS) are useful to investigate the genetic mechanisms that underlie these traits by identifying the genes and metabolic pathways involved. RESULTS: Data from 1853 females belonging to the Agricultural Jacarezinho LTDA were used. Genotyping was performed using the BovineHD BeadChip (777 962 single nucleotide polymorphisms (SNPs)) according to the protocol of Illumina - Infinium Assay II ® Multi-Sample HiScan with the unit SQ ™ System. After quality control, 305 348 SNPs were used for GWAS. Forty-two and 19 SNPs had a Bayes factor greater than 150 for heifer rebreeding and age at first calving, respectively. All significant SNPs for age at first calving were significant for heifer rebreeding. These 42 SNPs were next or within 35 genes that were distributed over 18 chromosomes and comprised 27 protein-encoding genes, six pseudogenes and two miscellaneous noncoding RNAs. CONCLUSIONS: The use of Bayes factor to determine the significance of SNPs allowed us to identify two sets of 42 and 19 significant SNPs for heifer rebreeding and age at first calving, respectively, which explain 11.35 % and 6.42 % of their phenotypic variance, respectively. These SNPs provide relevant information to help elucidate which genes affect these traits.

Evaluation of the productive and reproductive performance of sexual precocity at different ages in Nellore heifers.

This study aimed to investigate the differences between productive and reproductive performance traits of sexually precocious and non-sexually precocious Nellore heifers and to evaluate the genetic correlation of sexual precocity with traits of economic importance. For this purpose, 300,000 Nellore heifers were evaluated for reproductive traits: heifer pregnancy (HP) at 14 (HP14), 18 (HP18), and 24 (HP24) months; heifer rebreeding (HR); number of progenies up to 53 months (NP53); and probability of the cow remaining in the herd until 76 months with at least 3 progenies (Stay). The growth-related traits evaluated included female yearling weight (YW); average daily gain from weaning to yearling (ADGW-Y); weight at maturity (MW); weaning weight of first progeny (WWprog); and female visual scores at yearling for conformation (Conf), precocity (Prec) and muscling (Musc). The effects of female YW and ADGW-Y in six categories on HP14, HP18, and HP24 were analyzed using Generalized linear mixed models (GLMM). Furthermore, a linear mixed model was used to evaluate the impact of HP on WWprog, MW, and reproductive performance (NP53 and Stay). Genetic correlations of HP evaluated in different months with growth and reproductive traits were estimated using a bivariate animal model. Precocious heifers (HP14) were lighter for YW and MW but had greater ADGW-Y than HP18 and HP24. The probability for HP14, HP18, and HP24 increased as the classes of YW and ADGW-Y increased. However, heifers weighing more than 326 kg had a slight reduction in the probability of becoming pregnant at HP14 and HP18. Precocious heifers (HP14 and HP18) produced their first progeny by 3 % lighter than HP24, although they had a greater NP53. Precocious heifers at 18 months (HP18) were 3 % and 6.8 % more likely to remain in the herd than HP14 and HP24 heifers, respectively. Genetic correlations between growth traits (WW, YW, ADGW-Y, and MW) and heifer pregnancy (HP14, HP18, and HP24) ranged from weak (rg = 0.27 ± 0.05) to moderate (rg = -0.47 ± 0.07). The genetic correlation between HR and HP was stronger for HP24 (0.75) against HP14 (0.58) and HP18 (0.64). Although, the genetic correlation between NP53 and Stay with HP14 was higher (rg = 0.53 and 0.45) than those observed for HP18 (rg = 0.46 and 0.38) and HP24 (rg = 0.35 and 0.39). The genetic correlation estimates between HP and visual scores were moderate and favorable for HP14. Selecting HP14 is beneficial for production systems because it increases the NP53 during the productive life without compromising heifer productivity or reproductive performance. However, attention should be given to improving the HR of heifers who become pregnant early.

Study of whole genome linkage disequilibrium in Nellore cattle.

BACKGROUND: Knowledge of the linkage disequilibrium (LD) between markers is important to establish the number of markers necessary for association studies and genomic selection. The objective of this study was to evaluate the extent of LD in Nellore cattle using a high density SNP panel and 795 genotyped steers. RESULTS: After data editing, 446,986 SNPs were used for the estimation of LD, comprising 2508.4 Mb of the genome. The mean distance between adjacent markers was 4.90 ± 2.89 kb. The minor allele frequency (MAF) was less than 0.20 in a considerable proportion of SNPs. The overall mean LD between marker pairs measured by r(2) and |D'| was 0.17 and 0.52, respectively. The LD (r(2)) decreased with increasing physical distance between markers from 0.34 (1 kb) to 0.11 (100 kb). In contrast to this clear decrease of LD measured by r(2), the changes in |D'| indicated a less pronounced decline of LD. Chromosomes BTA1, BTA27, BTA28 and BTA29 showed lower levels of LD at any distance between markers. Except for these four chromosomes, the level of LD (r(2)) was higher than 0.20 for markers separated by less than 20 kb. At distances < 3 kb, the level of LD was higher than 0.30. The LD (r(2)) between markers was higher when the MAF threshold was high (0.15), especially when the distance between markers was short. CONCLUSIONS: The level of LD estimated for markers separated by less than 30 kb indicates that the High Density Bovine SNP BeadChip will likely be a suitable tool for prediction of genomic breeding values in Nellore cattle.

Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models.

Genotype by environment interactions (GEI) have attracted increasing attention in tropical breeding programs because of the variety of production systems involved. In this work, we assessed GEI in 450-day adjusted weight (W450) Nelore cattle from 366 Brazilian herds by comparing traditional univariate single-environment model analysis (UM) and random regression first order reaction norm models for six environmental variables: standard deviations of herd-year (RRMw) and herd-year-season-management (RRMw-m) groups for mean W450, standard deviations of herd-year (RRMg) and herd-year-season-management (RRMg-m) groups adjusted for 365-450 days weight gain (G450) averages, and two iterative algorithms using herd-year-season-management group solution estimates from a first RRMw-m and RRMg-m analysis (RRMITw-m and RRMITg-m, respectively). The RRM results showed similar tendencies in the variance components and heritability estimates along environmental gradient. Some of the variation among RRM estimates may have been related to the precision of the predictor and to correlations between environmental variables and the likely components of the weight trait. GEI, which was assessed by estimating the genetic correlation surfaces, had values < 0.5 between extreme environments in all models. Regression analyses showed that the correlation between the expected progeny differences for UM and the corresponding differences estimated by RRM was higher in intermediate and favorable environments than in unfavorable environments (p < 0.0001).

Bovine gene polymorphisms related to fat deposition and meat tenderness.

Leptin, thyroglobulin and diacylglycerol O-acyltransferase play important roles in fat metabolism. Fat deposition has an influence on meat quality and consumers' choice. The aim of this study was to determine allele and genotype frequencies of polymorphisms of the bovine genes, which encode leptin (LEP), thyroglobulin (TG) and diacylglycerol O-acyltransferase (DGAT1). A further objective was to establish the effects of these polymorphisms on meat characteristics. We genotyped 147 animals belonging to the Nelore (Bos indicus), Canchim (5/8 Bos taurus + 3/8 Bos indicus), Rubia Gallega X Nelore (1/2 Bos taurus + 1/2 Bos indicus), Brangus Three-way cross (9/16 Bos taurus + 7/16 Bos indicus) and Braunvieh Three-way cross (3/4 Bos taurus + 1/4 Bos indicus) breeds. Backfat thickness, total lipids, marbling score, ribeye area and shear force were fitted, using the General Linear Model (GLM) procedure of the SAS software. The least square means of genotypes and genetic groups were compared using Tukey's test. Allele frequencies vary among the genetic groups, depending on Bos indicus versus Bos taurus influence. The LEP polymorphism segregates in pure Bos indicus Nelore animals, which is a new finding. The T allele of TG is fixed in Nelore, and DGAT1 segregates in all groups, but the frequency of allele A is lower in Nelore animals. The results showed no association between the genotypes and traits studied, but a genetic group effect on these traits was found. So, the genetic background remains relevant for fat deposition and meat tenderness, but the gene markers developed for Bos taurus may be insufficient for Bos indicus.

Selection signatures in candidate genes and QTL for reproductive traits in Nellore heifers.

The identification of selection signature genes may help to detect genomic regions that underwent artificial selection and contributed to phenotypic diversity. The aim of this study, therefore, was to detect selection signatures in candidate genes and quantitative trait locus (QTL) for reproductive traits in a Nellore population being selected for sexual precocity. A total of 2035 Nellore heifers, sourced from breeding programs focused on sexual precocity, were used. Candidate genes and some specific QTL related to reproductive traits were chosen based on published literature and Animal QTL databases, respectively, for investigation whether these regions were affected by selection. Selection signature DNA sequences were detected in the selected regions using the extended haplotype homozygosity (EHH) and relative extended haplotype homozygosity (REHH) methods. From 22,241 single nucleotide polymorphisms (SNPs) located in the candidate genes and QTL, 17,312 SNPs generated 2756 haplotype blocks. A total of 7518 EHH tests were analyzed using haplotypes with a frequency of more than 25%, for which there were 39 tests that were significant for REHH (P<0.01). Selection signature DNA sequences were detected that contained several QTLs for important reproductive traits in cattle, suggesting that reproductive traits may have been affected by selection for sexual precocity in this population. Forty-six genes were located in the selection signature regions, whereas 24 genes participated in important biological processes or pathways that may underlie sexual precocity. These results indicate there are possible molecular mechanisms related to sexual precocity in the Nellore breed.

Genomic association for sexual precocity in beef heifers using pre-selection of genes and haplotype reconstruction.

Reproductive traits are of the utmost importance for any livestock farming, but are difficult to measure and to interpret since they are influenced by various factors. The objective of this study was to detect associations between known polymorphisms in candidate genes related to sexual precocity in Nellore heifers, which could be used in breeding programs. Records of 1,689 precocious and non-precocious heifers from farms participating in the Conexão Delta G breeding program were analyzed. A subset of single nucleotide polymorphisms (SNP) located in the region of the candidate genes at a distance of up to 5 kb from the boundaries of each gene, were selected from the panel of 777,000 SNPs of the High-Density Bovine SNP BeadChip. Linear mixed models were used for statistical analysis of early heifer pregnancy, relating the trait with isolated SNPs or with haplotype groups. The model included the contemporary group (year and month of birth) as fixed effect and parent of the animal (sire effect) as random effect. The fastPHASE® and GenomeStudio® were used for reconstruction of the haplotypes and for analysis of linkage disequilibrium based on r2 statistics. A total of 125 candidate genes and 2,024 SNPs forming haplotypes were analyzed. Statistical analysis after Bonferroni correction showed that nine haplotypes exerted a significant effect (p<0.05) on sexual precocity. Four of these haplotypes were located in the Pregnancy-associated plasma protein-A2 gene (PAPP-A2), two in the Estrogen-related receptor gamma gene (ESRRG), and one each in the Pregnancy-associated plasma protein-A gene (PAPP-A), Kell blood group complex subunit-related family (XKR4) and mannose-binding lectin genes (MBL-1) genes. Although the present results indicate that the PAPP-A2, PAPP-A, XKR4, MBL-1 and ESRRG genes influence sexual precocity in Nellore heifers, further studies are needed to evaluate their possible use in breeding programs.

Quantitative study of Babesia bovis infection in beef cattle from São Paulo state, Brazil.

The qPCR technique with SYBR Green was used to estimate the prevalence and level of Babesia bovis infection in beef cattle raised in areas endemic for babesiosis in Brazil, where the animals were continuously exposed to ticks (Rhipicephalus microplus). This is the first report in which qPCR was used to quantify and compare B. bovis DNA in blood of different cattle breeds. Blood samples were collected from 150 animals (75 cows and 75 calves) of the Angus and Nelore breeds and the first generation of an Angus and Nelore cross (AxN). Blood samples from the jugular vein were used for DNA extraction and determination of packed cell volume (PCV), while samples from peripheral veins were used for microscopic parasite detection. Although no piroplasms of B. bovis were found in blood smears, DNA amplification using qPCR revealed that all of the 150 animals, except two calves and one cow, were positive. The number of copies of B. bovis DNA was higher (p<0.05) in the Angus than in the Nelore and AxN animals, for both calves and cows, but no significant difference was found between the Nelore and AxN groups. These results suggest that a heterotic effect was present, since the results from the crossbred animals significantly deviated from the mean of the two parental groups, while closely approaching that of the Nelore group. In the Nelore and AxN groups, calves showed higher infection levels than cows (p<0.05), while for the Angus group the difference was found to be non-significant. Within each animal age group, the breed groups with higher infection levels were those with lower PCV values. However, within each breed group, no significant correlations were found between the number of DNA copies and PCV according to animal age. The qPCR method applied here allowed the observation that although there are no differences in the prevalence of infection among breed groups, Nelore and AxN cattle are able to maintain infection by B. bovis at lower levels than the Angus cattle.

Assessment of GH1, CAPN1 and CAST polymorphisms as markers of carcass and meat traits in Bos indicus and Bos taurus-Bos indicus cross beef cattle.

The objective of this study was to investigate the effects of bovine GH1, CAPN1 and CAST gene polymorphisms on carcass and meat traits in Nellore and Nellore x Bos taurus beef cattle. Three hundred animals were genotyped for GH1/MspI (TC/G in intron 3), CAPN316 (AF_252504.2:g.5709C>G) and CAST/RsaI (AY_008267.1:g282C>G) and phenotyped for rib eye area, backfat thickness, intramuscular fat, shear force (SF), and myofibrillar fragmentation index (MFI). No significant associations were observed between the GH1/MspI and CAST/RsaI polymorphisms and phenotypes, although the relation between the CAST/RsaI genotypes and meat tenderness evaluated by MFI approached significant. The fact that the CAPN316 polymorphism did not show adequate segregation in Nellore cattle confirms the difficulty of using this marker in breeding programs of different Bos indicus breeds. However, the positive results of the association analysis obtained for Nellore x B. taurus crosses contributed to the validation of previous findings.

[Gastrointestinal nematode parasitism in ewes and lambs raised in São Carlos, São Paulo]. / Parasitismopor nematóides gastrintestinais em matrizes e cordeiros criados em São Carlos, São Paulo.

Gastrointestinal nematode infections were evaluated in Santa Inês crossbreed sheep (Santa Inês predominance) in a rotational grazing system and in lambs kept indoors, born from the breeding of these females with purebred Santa Ines, Dorper and Suffolk males. Fecal egg counts (FEC), fecal cultures, packed cell volume (PCV) and weights were evaluated during two years. Climate data were registered. Only animals that presented FEC higher than 4,000 and/or PCV lower than 21% were drenched with anthelmintic treatment and this rational use controlled the infection in the flock satisfactorily. An adequate diet during the rainy season and supplementation in dry period were important to increase relative resistance and resilience to parasites, since Haemonchus contortus was detected year-round in this region. The peripartum physiological condition influenced gastrointestinal nematode infections significantly. Crossbred (1/2) Santa Inês + (1/2) Dorper lambs did not show a significant difference in FEC when compared with other breeds, but they had greater live weight and reached slaughter weight earlier.

Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models

Genotype by environment interactions (GEI) have attracted increasing attention in tropical breeding programs because of the variety of production systems involved. In this work, we assessed GEI in 450-day adjusted weight (W450) Nelore cattle from 366 Brazilian herds by comparing traditional univariate single-environment model analysis (UM) and random regression first order reaction norm models for six environmental variables: standard deviations of herd-year (RRMw) and herd-year-season-management (RRMw-m) groups for mean W450, standard deviations of herd-year (RRMg) and herd-year-season-management (RRMg-m) groups adjusted for 365-450 days weight gain (G450) averages, and two iterative algorithms using herd-year-season-management group solution estimates from a first RRMw-m and RRMg-m analysis (RRMITw-m and RRMITg-m, respectively). The RRM results showed similar tendencies in the variance components and heritability estimates along environmental gradient. Some of the variation among RRM estimates may have been related to the precision of the predictor and to correlations between environmental variables and the likely components of the weight trait. GEI, which was assessed by estimating the genetic correlation surfaces, had values < 0.5 between extreme environments in all models. Regression analyses showed that the correlation between the expected progeny differences for UM and the corresponding differences estimated by RRM was higher in intermediate and favorable environments than in unfavorable environments (p < 0.0001).

Bovine gene polymorphisms related to fat deposition and meat tenderness

Leptin, thyroglobulin and diacylglycerol O-acyltransferase play important roles in fat metabolism. Fat deposition has an influence on meat quality and consumers' choice. The aim of this study was to determine allele and genotype frequencies of polymorphisms of the bovine genes, which encode leptin (LEP), thyroglobulin (TG) and diacylglycerol O-acyltransferase (DGAT1). A further objective was to establish the effects of these polymorphisms on meat characteristics. We genotyped 147 animals belonging to the Nelore (Bos indicus), Canchim (5/8 Bos taurus + 3/8 Bos indicus), Rubia Gallega X Nelore (1/2 Bos taurus + 1/2 Bos indicus), Brangus Three-way cross (9/16 Bos taurus + 7/16 Bos indicus) and Braunvieh Three-way cross (3/4 Bos taurus + 1/4 Bos indicus) breeds. Backfat thickness, total lipids, marbling score, ribeye area and shear force were fitted, using the General Linear Model (GLM) procedure of the SAS software. The least square means of genotypes and genetic groups were compared using Tukey's test. Allele frequencies vary among the genetic groups, depending on Bos indicus versus Bos taurus influence. The LEP polymorphism segregates in pure Bos indicus Nelore animals, which is a new finding. The T allele of TG is fixed in Nelore, and DGAT1 segregates in all groups, but the frequency of allele A is lower in Nelore animals. The results showed no association between the genotypes and traits studied, but a genetic group effect on these traits was found. So, the genetic background remains relevant for fat deposition and meat tenderness, but the gene markers developed for Bos taurus may be insufficient for Bos indicus.