Genetic correlations and heritability estimates for dry matter intake, weight gain and feed efficiency of Nellore cattle in feedlot

Estimation of genetic parameters for maintenance energy requirements and residual feed intake in Nellore cattle

We estimated heritabilities and genetic and phenotypic correlation estimates for maintenance energy requirements (NEmR), residual feed intake (RFI), growth, carcass and reproductive indicator traits, using data from 41 feed efficiency trials in Brazil, comprising 4381 males and females. Continuous traits were analysed using a linear animal model and threshold traits were analysed using a threshold animal model. The heritability estimates were low for RFI (0.190) and NEmR (0.193); other heritabilities were mainly moderate (growth and carcass traits) or high (sexual precocity traits). The genetic correlation of RFI with NEmR was high (0.701). The genetic correlations of NEmR were low with carcass and reproductive traits, and moderate with growth traits. Thus, selection to improve weaning weight and female sexual precocity indicator traits would not affect maintenance energy requirement. Genetic selection to reduce maintenance energy requirements is feasible and would also reduce DMI and RFI. Selection to improve RFI can be used to identify animals with lower maintenance energy requirements. Long-term selection to reduce RFI and NEmR would have favourable effects on yearling weight, carcass muscle indicator traits and female sexual precocity. Genetic (co)variance component estimates for NEmR, in conjunction with economic values of selection criteria, may be used to develop novel approaches for genetic selection to improve efficiency of beef production.

Identification of genomic regions and pathways associated with traits related to rumen acidosis in feedlot Nellore cattle

There may be an increased risk of metabolic disorders, such as rumen acidosis, in cattle fed high-concentrate diets, particularly those from Bos taurus indicus genotypes, which have shown to be more sensitive to ruminal acidification. Therefore, this study aimed to estimate (co)variance components and identify genomic regions and pathways associated with ruminal acidosis in feedlot Nellore cattle fed high-concentrate diets. It was utilized a dataset containing a total of 642 Nellore bulls that were genotyped from seven feedlot nutrition studies. The GGP Indicus 35k panel was used with the single step genome-wide association study methodology in which the effects of the markers were obtained from the genomic values estimated by the GBLUP model. A bivariate model to estimate genetic correlations between the economically important traits and indicator traits for acidosis was used. The traits evaluated in this study that were nutritionally related to rumen acidosis included average daily gain (ADG), final body weight, time spent eating (TSE), time spent ruminating, rumenitis score (RUM), rumen absorptive surface area (ASA), rumen keratinized layer thickness (KER) and hot carcass weight (HCW). The identified candidate genes were mainly involved in the negative or non-regulation of the apoptotic process, salivary secretion, and transmembrane transport. The genetic correlation between HCW and ASA was low positive (0.27 ± 0.23), and between ADG and ASA was high moderate (0.58 ± 0.59). A positive genetic correlation between RUM and all performance traits was observed, and TSE correlated negatively with HCW (-0.33 ± 0.21), ASA (-0.75 ± 0.48), and KER (-0.40 ± 0.27). The genetic association between economically important traits and indicator traits for acidosis suggested that Nellore cattle may be more sensitive to acidosis in feedlot systems.

Genomic analysis of feed efficiency traits in beef cattle using random regression models

Feed efficiency plays a major role in the overall profitability and sustainability of the beef cattle industry, as it is directly related to the reduction of the animal demand for input and methane emissions. Traditionally, the average daily feed intake and weight gain are used to calculate feed efficiency traits. However, feed efficiency traits can be analysed longitudinally using random regression models (RRMs), which allow fitting random genetic and environmental effects over time by considering the covariance pattern between the daily records. Therefore, the objectives of this study were to: (1) propose genomic evaluations for dry matter intake (DMI), body weight gain (BWG), residual feed intake (RFI) and residual weight gain (RWG) data collected during an 84-day feedlot test period via RRMs; (2) compare the goodness-of-fit of RRM using Legendre polynomials (LP) and B-spline functions; (3) evaluate the genetic parameters behaviour for feed efficiency traits and their implication for new selection strategies. The datasets were provided by the EMBRAPA-GENEPLUS beef cattle breeding program and included 2920 records for DMI, 2696 records for BWG and 4675 genotyped animals. Genetic parameters and genomic breeding values (GEBVs) were estimated by RRMs under ssGBLUP for Nellore cattle using orthogonal LPs and B-spline. Models were compared based on the deviance information criterion (DIC). The ranking of the average GEBV of each test week and the overall GEBV average were compared by the percentage of individuals in common and the Spearman correlation coefficient (top 1%, 5%, 10% and 100%). The highest goodness-of-fit was obtained with linear B-Spline function considering heterogeneous residual variance. The heritability estimates across the test period for DMI, BWG, RFI and RWG ranged from 0.06 to 0.21, 0.11 to 0.30, 0.03 to 0.26 and 0.07 to 0.27, respectively. DMI and RFI presented within-trait genetic correlations ranging from low to high magnitude across different performance test-day. In contrast, BWG and RWG presented negative genetic correlations between the first 3 weeks and the other days of performance tests. DMI and RFI presented a high-ranking similarity between the GEBV average of week eight and the overall GEBV average, with Spearman correlations and percentages of individuals selected in common ranging from 0.95 to 1.00 and 93 to 100, respectively. Week 11 presented the highest Spearman correlations (ranging from 0.94 to 0.98) and percentages of individuals selected in common (ranging from 85 to 94) of BWG and RWG with the average GEBV of the entire period of the test. In conclusion, the RRM using linear B-splines is a feasible alternative for the genomic evaluation of feed efficiency. Heritability estimates of DMI, RFI, BWG and RWG indicate enough additive genetic variance to achieve a moderate response to selection. A new selection strategy can be adopted by reducing the performance test to 56 days for DMI and RFI selection and 77 days for BWG and RWG selection.

Multi-tissue transcriptome analysis to identify candidate genes associated with weight regulation in Hanwoo cattle

While genetic markers related to meat production traits have been identified in many other cattle breeds, research on weight in Hanwoo cattle (Korean native cattle) is still insufficient. In this study, we performed expression quantitative trait loci (eQTL) analysis and differential gene expression analysis to detect candidate genes influencing the weight characteristics of 32 castrated Hanwoo cattle across 22 tissues and, we identified variants that affect gene expression levels. In total, we identified a total of 3,298 differentially expressed genes, among which we discovered key genes such as UBD, RGS2, FASN, and SCD that have functions related to adipogenesis, body weight, obesity, and lipid metabolism. Gene-set enrichment analysis revealed that candidate genes in adipose tissue are involved in metabolic pathways linked to obesity-related traits, adipose metabolism, and lipid metabolism. Additionally, we found that decreased expression of TRIM31 contributes to weight gain which can be explained by the associated candidate cis-eQTL genotypes for TRIM31 and their effect on differential gene expression between the lower and higher weight groups. Our findings revealed candidate genes associated with the weight of Hanwoo cattle and perhaps can provide comprehensive insights into the association of weight with various tissues beyond adipose tissue and muscle, indicating the potential for expanding the focus of livestock trait research.

Genotype-by-environment interactions for feed efficiency traits in Nellore cattle based on bi-trait reaction norm models

BACKGROUND

Selecting animals for feed efficiency directly impacts the profitability of the beef cattle industry, which contributes to minimizing the environmental footprint of beef production. Genetic and environmental factors influence animal feed efficiency, leading to phenotypic variability when exposed to different environmental conditions (i.e., temperature and nutritional level). Thus, our aim was to assess potential genotype-by-environment (G × E) interactions for dry matter intake (DMI) and residual feed intake (RFI) in Nellore cattle (Bos taurus indicus) based on bi-trait reaction norm models (RN) and evaluate the genetic association between RFI and DMI across different environmental gradient (EG) levels. For this, we used phenotypic information on 12,958 animals (young bulls and heifers) for DMI and RFI recorded during 158 feed efficiency trials.

RESULTS

The heritability estimates for DMI and RFI across EG ranged from 0.26 to 0.54 and from 0.07 to 0.41, respectively. The average genetic correlations (± standard deviation) across EG for DMI and RFI were 0.83 ± 0.19 and 0.81 ± 0.21, respectively, with the lowest genetic correlation estimates observed between extreme EG levels (low vs. high) i.e. 0.22 for RFI and 0.26 for DMI, indicating the presence of G × E interactions. The genetic correlation between RFI and DMI across EG levels decreased as the EG became more favorable and ranged from 0.79 (lowest EG) to 0.52 (highest EG). Based on the estimated breeding values from extreme EG levels (low vs. high), we observed a moderate Spearman correlation of 0.61 (RFI) and 0.55 (DMI) and a selection coincidence of 53.3% and 40.0% for RFI and DMI, respectively.

CONCLUSIONS

Our results show evidence of G × E interactions on feed efficiency traits in Nellore cattle, especially in feeding trials with an average daily gain (ADG) that is far from the expected of 1 kg/day, thus increasing reranking of animals.

Characterization of feed efficiency-related key signatures molecular in different cattle breeds

Feed efficiency is a major constraint in the beef industry and has a significant negative correlation with residual feed intake (RFI). RFI is widely used as a measure of feed efficiency in beef cattle and is independent of economic traits such as body weight and average daily gain. However, key traits with commonality or specificity among beef cattle breeds at the same level of RFI have not been reported. Accordingly, the present study hypothesized that signatures associated with feed efficiency would have commonality or specificity in the liver of cattle breeds at the same RFI level. By comparing and integrating liver transcriptome data, we investigated the critical signatures closely associated with RFI in beef cattle using weighted co-expression network analysis, consensus module analysis, functional enrichment analysis and protein network interaction analysis. The results showed that the consensus modules in Angus and Charolais cattle were negatively correlated, and four (turquoise, red, tan, yellow) were significantly positively correlated in Angus liver, while (turquoise, red) were significantly negatively correlated in Charolais liver. These consensus modules were found to be primarily involved in biological processes such as substance metabolism, energy metabolism and gene transcription, which may be one of the possible explanations for the difference in feed efficiency between the two beef breeds. This research also identified five key candidate genes, PLA2G12B, LCAT, MTTP, LCAT, ABCA1 and FADS1, which are closely associated with hepatic lipid metabolism. The present study has identified some modules, genes and pathways that may be the major contributors to the variation in feed efficiency among different cattle breeds, providing a new perspective on the molecular mechanisms of feed efficiency in beef cattle and a research basis for investigating molecular markers associated with feed efficiency in beef cattle.

Genomic evaluation for two-way crossbred performance in cattle

BACKGROUND

Dairy cattle production systems are mostly based on purebreds, but recently the use of crossbreeding has received increased interest. For genetic evaluations including crossbreds, several methods based on single-step genomic best linear unbiased prediction (ssGBLUP) have been proposed, including metafounder ssGBLUP (MF-ssGBLUP) and breed-specific ssGBLUP (BS-ssGBLUP). Ideally, models that account for breed effects should perform better than simple models, but knowledge on the performance of these methods is lacking for two-way crossbred cattle. In addition, the differences in the estimates of genetic parameters (such as the genetic variance component and heritability) between these methods have rarely been investigated. Therefore, the aims of this study were to (1) compare the estimates of genetic parameters for average daily gain (ADG) and feed conversion ratio (FCR) between these methods; and (2) evaluate the impact of these methods on the predictive ability for crossbred performance.

METHODS

Bivariate models using standard ssGBLUP, MF-ssGBLUP and BS-ssGBLUP for the genetic evaluation of ADG and FCR were investigated. To measure the predictive ability of these three methods, we estimated four estimators, bias, dispersion, population accuracy and ratio of population accuracies, using the linear regression (LR) method.

RESULTS

The results show that, for both ADG and FCR, the heritabilities were low with the three methods. For FCR, the differences in the estimated genetic parameters were small between the three methods, while for ADG, those estimated with BS-ssGBLUP deviated largely from those estimated with the other two methods. Bias and dispersion were similar across the three methods. Population accuracies for both ADG and FCR were always higher with MF-ssGBLUP than with ssGBLUP, while with BS-ssGBLUP the population accuracy was highest for FCR and lowest for ADG.

CONCLUSIONS

Our results indicate that in the genetic evaluation for crossbred performance in a two-way crossbred cattle production system, the predictive ability of MF-ssGBLUP and BS-ssGBLUP is greater than that of ssGBLUP, when the estimated variance components are consistent across the three methods. Compared with BS-ssGBLUP, MF-ssGBLUP is more robust in its superiority over ssGBLUP.

Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle

This study aimed to estimate prediction ability and genetic parameters for residual feed intake (RFI) calculated using a regression equation for each test (RFI_test) and for the whole population (RFI_pop) in Nellore beef cattle. It also aimed to evaluate the correlations between RFI_pop and RFI_test with growth, reproductive, and carcass traits. Genotypic and phenotypic records from 8354 animals were used. An analysis of variance (ANOVA) was performed to verify the adequacy of the regression equations applied to estimate the RFI_test and RFI_pop. The (co)variance components were obtained using the single-step genomic best linear unbiased prediction under single and two-trait animal model analyses. The genetic and phenotypic correlations between RFI_test and RFI_pop with dry matter intake, frame, growth, reproduction, and carcass-related traits were evaluated. The prediction ability and bias were estimated to compare the RFI_test and RFI_pop genomic breeding values (GEBV). The RFI_pop ANOVA showed a higher significance level (p < 0.0001) than did the RFI_test for the fixed effects. The RFI_pop displayed higher additive genetic variance estimated than the RFI_test, although the RFI_pop and RFI_test displayed similar heritabilities. Overall, the RFI_test showed higher residual correlations with growth, reproductive, and carcass traits, while the RFI_pop displayed higher genetic correlations with such traits. The GEBV for the RFI_test was slightly biased than GEBV RFI_pop. The approach to calculate the RFI influenced the decomposition and estimation of variance components and genomic prediction for RFI. The application of RFI_pop would be more appropriate for genetic evaluation purpose to adjust or correct for non-genetic effects and to decrease the prediction bias for RFI.

Estimates of genetic and phenotypic parameters for feeding behaviour and feed efficiency-related traits in Nelore cattle

The objective of this study was to obtain (co)variance components, heritability, and genetic and phenotypic correlation estimates for feed efficiency and feed behaviour-related indicator traits. Further, it aimed to predict the direct and correlated responses for feed efficiency traits when selection was applied for feeding behaviour-related traits in Nelore cattle. Phenotypic records (n = 4840) from 125 feed efficiency tests (RFI: Residual feed intake and DMI: Dry matter intake) carried out between 2011 and 2018 were considered in this study. Animals belonged to five farms located in two Brazilian geographical regions (Midwest and Southeast). Animals under similar management and environmental conditions in the feedlot were evaluated when they attained an average of 13.5 ± 4.15 months of age. Feed behaviour-related traits were also obtained, including meal criteria (MC), meal frequency (MF), average meal duration (AMD), meal duration (MD), average consumption per meal (ACM), and consumption rate (CR) through the GrowSafe System® electronic bunk system. The contemporary groups for all traits were composed of farm, management group, feed efficiency test, sex, and birth year. The (co)variance components were estimated using the restricted maximum likelihood method considering a multi-trait (n = 8) animal model. The heritability estimates for RFI (0.23 ± 0.02), DMI (0.31 ± 0.02), MF (0.65 ± 0.02), AMD (0.29 ± 0.02), ACM (0.24 ± 0.02), MD (0.41 ± 0.02), MC (0.48 ± 0.02), and CR (0.42 ± 0.02) were moderate to high. The highest genetic correlation was obtained between CR and MD (-0.91 ± 0.04), MD and AMD (0.73 ± 0.03), CR and AMD (-0.68 ± 0.04), and RFI and DMI (0.81 ± 0.02). The highest phenotypic correlation was between ACM and AMD (0.76 ± 0.02), DMI and MD (0.77 ± 0.02), and DMI and RFI (0.77 ± 0.02). Genetic improvement for feed efficiency and feeding behaviour-related traits is feasible and the results obtained herein provided valuable information regarding the genetic background of Nelore feeding behaviour-related traits. The genetic association between feeding behaviour and feed efficiency-related traits suggested that animals spending less time feeding at a low feeding rate also had lower DMI and higher feed efficiency (RFI), and likely had lower energy maintenance requirements. The relative efficiency of selection showed that feeding behaviour-related traits were not adequate indicator traits to improve RFI and DMI. The DMI might be an effective selection criterion to improve RFI and reduce the herd's maintenance requirements.

Heritability and variance component estimation for feed and water intake behaviors of feedlot cattle

Feed and water intake are two important aspects of cattle production that greatly impact the profitability, efficiency, and sustainability of producers. Feed and, to a lesser degree, water intake have been studied previously; however, there is little research on their associated animal behaviors and there is a lack of standardized phenotypes for these behaviors. Feed and water intakes obtained with an Insentec system (Hokofarm Group, The Netherlands) from 830 crossbred steers were used to compute five intake behaviors for both feed and water: daily sessions (DS), intake rate (IR), session size (SS), time per session (TS), and session interval (SI). Variance components and heritabilities were estimated for each trait. Heritabilities for feed intake behaviors were 0.50 ± 0.12, 0.63 ± 0.12, 0.40 ± 0.13, 0.35 ± 0.12, and 0.60 ± 0.12 for DS, IR, SS, TS, and SI, respectively. Heritabilities for water intake behaviors were 0.56 ± 0.11, 0.88 ± 0.07, 0.70 ± 0.11, 0.54 ± 0.12, and 0.80 ± 0.10 for NS, IR, SS, TS, and SI, respectively. Daily dry matter intake (DDMI) and daily water intake (DWI) had heritabilities of 0.57 ± 0.11 and 0.44 ± 0.11. Phenotypic correlations varied between pairs of traits (-0.83 to 0.82). Genetic correlations between DDMI and feed intake behaviors were moderate to high, while genetic correlations between DWI and water intake behaviors were low to moderate. Several significant single nucleotide polymorphisms (SNP) were identified for the feed and water intake behaviors. Genes and previously reported quantitative trait loci near significant SNPs were evaluated. The results indicated that feed and water intake behaviors are influenced by genetic factors and are heritable, providing one additional route to evaluate or manipulate feed and water intake.

Multi-transcriptomics reveals RLMF axis-mediated signaling molecules associated with bovine feed efficiency

The regulatory axis plays a vital role in interpreting the information exchange and interactions among mammal organs. In this study on feed efficiency, it was hypothesized that a rumen-liver-muscle-fat (RLMF) regulatory axis exists and scrutinized the flow of energy along the RLMF axis employing consensus network analysis from a spatial transcriptomic standpoint. Based on enrichment analysis and protein-protein interaction analysis of the consensus network and tissue-specific genes, it was discovered that carbohydrate metabolism, energy metabolism, immune and inflammatory responses were likely to be the biological processes that contribute most to feed efficiency variation on the RLMF regulatory axis. In addition, clusters of genes related to the electron respiratory chain, including ND (2,3,4,4L,5,6), NDUF (A13, A7, S6, B3, B6), COX (1,3), CYTB, UQCR11, ATP (6,8), clusters of genes related to fatty acid metabolism including APO (A1, A2, A4, B, C3), ALB, FG (A, G), as well as clusters of the ribosomal-related gene including RPL (8,18A,18,15,13, P1), the RPS (23,27A,3A,4X), and the PSM (A1-A7, B6, C1, C3, D2-D4, D8 D9, E1) could be the primary effector genes responsible for feed efficiency variation. The findings demonstrate that high feed efficiency cattle, through the synergistic action of the regulatory axis RLMF, may improve the efficiency of biological processes (carbohydrate metabolism, protein ubiquitination, and energy metabolism). Meanwhile, high feed efficiency cattle might enhance the ability to respond to immunity and inflammation, allowing nutrients to be efficiently distributed across these organs associated with digestion and absorption, energy-producing, and energy-storing organs. Elucidating the distribution of nutrients on the RLMF regulatory axis could facilitate an understanding of feed efficiency variation and achieve the study on its molecular regulation.

Heritability and genetic correlations between marbling in longissimus dorsi muscle and conventional economic traits in Nellore beef cattle

In Nellore beef cattle, studies addressing genetic correlations between ultrasound marbling content and other economically important traits are still incipient. Therefore, this work aimed to estimate heritability and genetic correlations between ultrasound marbling content in the longissimus dorsi muscle (MARB) and growth, reproductive, feed efficiency, and carcass-related traits in a Nellore beef cattle population from Brazil. Phenotypic records of 614,395 Nellore animals were used and included adjusted weight at 210 (W210) and 450 (W450) days of age, adult cow weight (AW), early heifer pregnancy (EH), stayability (STAY), adjusted scrotal circumference at 365 days of age (SC365), ribeye area (REA), subcutaneous backfat thickness (BF), rump fat thickness (RF), and marbling (MARB). The genetic parameters for all traits but EH and STAY were estimated considering a linear animal model, whereas for those two nonlinear traits, a threshold animal model was used. The direct and correlated response to selection for MARB versus the other traits, and the relative efficiency of selection, were also calculated. The heritability estimate for MARB was 0.31 and for the other conventional evaluated traits was low to moderate, with values ranging from 0.14 to 0.41. The genetic correlations between MARB and growth, reproductive, feed efficiency, and carcass-related trait were very low, with values close to zero, with similar correlated responses. The MARB displayed adequate genetic variability to respond to selection and crossbreeding programs looking forward to higher meat quality and differential market standards for the Nellore beef. The selection for growth, reproductive, feed efficiency, and carcass-related traits would not affect MARB in Nellore beef cattle and vice versa. Therefore, this trait should be included as a selection criterion in the Nellore breeding program.

Selection criteria for feed efficiency-related traits and their association with growth, reproductive and carcass traits in Nelore cattle

Context Livestock feed costs have a higher impact on the profitability of beef production systems and are directly related to feed efficiency. However, these traits are hard and have high costs to measure, reducing the availability of phenotypic records and reliability of genetic evaluations. Thus, the use of genomic information can increase the robustness of genetic studies that address them. Aims The aim of the present study was to estimate genetic parameters for feed efficiency, growth, reproductive and carcass traits in Nelore cattle and the correlated response among them, using genomic information. Methods Residual feed intake (RFI), dry-matter intake, feed conversion ratio, feed efficiency (FE), residual average daily gain (RG), residual feed intake and average daily gain (RIG), birthweight, weight at 120, 240, 365 and 450 days of age, scrotal circumference at 365 and 450 days of age, rib-eye area, backfat thickness and rump fat thickness were evaluated. The genetic parameters were estimated using the single-step genomic best linear unbiased prediction approach. Key results The FE-related traits showed low to moderate heritability ranging from 0.07 to 0.23. Feed efficiency-related traits showed low genetic correlations with reproductive (–0.24 to 0.27), carcass (–0.17 to 0.27) and growth (–0.19 to 0.24) traits, except for growth with dry-matter intake (0.32–0.56) and weight at 365 days of age with FE (–0.40). Conclusions The selection to improve growth, reproductive and carcass traits would not change RFI, RG and RIG. The choice of the most adequate selection criterion depends on the production system, that is, RFI might be used for low-input beef cattle systems, and RIG would be used for more intensive and without-any-dietary-restrictions beef cattle systems. Implications The estimates of heritability and genetic correlations suggest that genetic selection for feed efficiency using RFI, RG and RIG in Nellore cattle leads to higher genetic gain than does that using FE and feed conversion ratio without affecting other profitability traits.

Genomic prediction ability for feed efficiency traits using different models and pseudo-phenotypes under several validation strategies in Nelore cattle

There is a growing interest to improve feed efficiency (FE) traits in cattle. The genomic selection was proposed to improve these traits since they are difficult and expensive to measure. Up to date, there are scarce studies about the implementation of genomic selection for FE traits in indicine cattle under different scenarios of pseudo-phenotypes, models, and validation strategies on a commercial large scale. Thus, the aim was to evaluate the feasibility of genomic selection implementation for FE traits in Nelore cattle applying different models and pseudo-phenotypes under validation strategies. Phenotypic and genotypic information from 4 329 and 3 467 animals were used, respectively, which were tested for residual feed intake, DM intake, feed efficiency, feed conversion ratio, residual BW gain, and residual intake and BW gain. Six prediction methods were used: single-step genomic best linear unbiased prediction, Bayes A, Bayes B, Bayes Cπ, Bayesian least absolute shrinkage and selection operator (BLASSO), and Bayes R. Phenotypes adjusted for fixed effects (Y*), estimated breeding value (EBV), and EBV deregressed (DEBV) were used as pseudo-phenotypes. The validation approaches used were: (1) random: the data was randomly divided into ten subsets and the validation was done in each subset at a time; (2) age: the partition into training and testing sets was based on year of birth and testing animals were born after 2016; and (3) EBV accuracy: the data was split into two groups, being animals with accuracy above 0.45 the training set; and below 0.45 the validation set. In the analyses that used the Y* as pseudo-phenotype, prediction ability (PA) was obtained by dividing the correlation between pseudo-phenotype and genomic EBV (GEBV) by the square root of the heritability of the trait. When EBV and DEBV were used as the pseudo-phenotype, the simple correlation of this quantity with the GEBV was considered as PA. The prediction methods show similar results for PA and bias. The random cross-validation presented higher PA (0.17) than EBV accuracy (0.14) and age (0.13). The PA was higher for Y* than for EBV and DEBV (30.0 and 34.3%, respectively). Random validation presented the highest PA, being indicated for use in populations composed mainly of young animals and traits with few generations of data recording. For high heritability traits, the validation can be done by age, enabling the prediction of the next-generation genetic merit. These results would support breeders to identify genomic approaches that are more viable for genomic prediction for FE-related traits.

Genetic parameters associated with meat quality of Nellore cattle at different anatomical points of longissimus: Brazilian standards

The present study estimated genetic parameters and evaluated the genetic and phenotypic correlations between meat quality characteristics of Nellore cattle evaluated at different anatomical points of the longissimus. Data from 1329 Nellore young bulls were used to evaluate, in the 5th and 12th ribs, marbling score (MAR), shear force (SF), cooking weight losses (CWL) and intramuscular fat (IMF). In addition, the subcutaneous fat thickness was measured at the 12th rib (SFT₁₂) and between the last lumbar and the first sacral vertebrae (SFT_LR), in the separation of loin and round. Results yielded moderate heritability coefficients for evaluated characteristics, except CWL. High genetic correlations (0.61) were found between measurements of SFT₁₂ and SFT_LR. MAR, IMF and SF were evaluated at the 5th and 12th rib. Meat quality and subcutaneous fat thickness measured at different anatomical points of the longissimus are genetically correlated and can be used in genetic selection programs to improve meat quality characteristics in Nellore cattle.

Genetic parameters and genome-wide association study regarding feed efficiency and slaughter traits in Charolais cows

Residual energy intake (REI) on two successive diets (hay and maize based) and slaughter traits, including visceral organs, were phenotyped in 584 adult purebred Charolais cows. To investigate the relationships between these traits and their genetic determinism, we first estimated the genetic parameters, including correlations, using REML modeling under WOMBAT software. The animals were then genotyped on the BovineSNP50 SNPchip before being imputed to the 600K density and genome wide association study was performed with GCTA software. We found low heritability for REI (h2 = 0.12 in each of the diet phases). Although the phenotypic correlation between the two diet phases was moderate (0.36), the genetic correlation was high (0.83), indicating a common genetic determinism for feed efficiency regardless of the diet. Correlations between REI and slaughter traits were negative regarding muscle-related traits and positive for fat-related traits, indicating that efficient animals generally had a more muscular carcass. It was also seen that feed efficiency was genetically and phenotypically correlated with smaller organs when expressed as a proportion of their empty body weight. From the GWAS analysis, seven QTLs were found to be associated with a trait at the genome-wide level of significance and 18 others at the chromosome-wide level. One important QTL was detected in BTA 2, reflecting the essential effect of the myostatin gene on both carcass composition and relative organ weight. Three QTLs were detected for REI during the maize diet phase on BTA 13, 19, and 28, the latter being significant at the genome-wide level. The QTLs on BTA 19 mapped into the TANC2 gene and the QTLs on BTA 28 into the KIF1BP gene, which are both known to interact with the same protein (KIF1A). However, no obvious functional link between these genes and feed efficiency could be made. Among the other QTLs detected, one association on BTA 4 with liver proportion mapped to the candidate gene WASL, which has previously been shown to be differentially expressed in liver cells and linked to feed restriction or cancer development. No QTLs were found to be common between feed efficiency and any slaughter traits.

Relationship between feed efficiency and slaughter traits of French Charolais bulls

Improving feed efficiency is of interest to French beef producers so as to increase their profitability. To enable this improvement through selection, genetic correlations with production traits need to be quantified. The objective of this study was to estimate the genetic parameters for growth, feed efficiency (FE), and slaughter performance of young beef bulls of the French Charolais breed. Three feed efficiency criteria were calculated: residual feed intake (RFI), residual gain (RG), and ratio of FE. Data on feed intake, growth, and FE were available for 4,675 Charolais bulls tested in performance test stations and fed with pelleted diet. Between 1985 and 1989, 60 among 510 of these bulls were selected to procreate one generation of 1,477 progeny bulls which received the same pelleted diet at the experimental farm in Bourges. In addition to feed intake, growth, and FE traits, these terminal bulls also had slaughter traits of carcass yield, carcass composition, and weight of visceral organs collected. Genetic parameters were estimated using linear mixed animal models. Between performance test bulls and terminal bulls, the genetic correlation of RFI was 0.80 ± 0.18; it was 0.70 ± 0.21 for RG and 0.46 ± 0.20 for FE. For carcass traits, RFI was negatively correlated with carcass yield (-0.18 ± 0.14) and muscle content (-0.47 ± 0.14) and positively with fat content (0.48 ± 0.13). Conversely, RG and FE were positively correlated with carcass yield and muscle content and negatively with fat content. For the three FE criteria, efficient animals had leaner carcass. For visceral organs (as a proportion of empty body weight), RFI was genetically correlated with the proportions of the 5th quarter (0.51 ± 0.17), internal fat (0.36 ± 0.14), abomasum (0.46 ± 0.20), intestines (0.38 ± 0.17), liver (0.36 ± 0.16), and kidneys (0.73 ± 0.11). Conversely, RG and FE were negatively associated with these traits. The high-energy expenditure associated with the high-protein turnover in visceral organs may explain this opposite relationship between FE and the proportion of visceral organs. Selection for final weight and RFI increased growth and FE in progeny, and also improved carcass yield and muscle content in the carcass. To conclude, determinations of growth and feed intake in performance test stations are effective to select bulls to improve their growth, FE, and muscle content in carcass.