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

The objective of this study was to develop and validate a customized cost-effective single nucleotide polymorphism (SNP) panel for genetic improvement of feed efficiency in beef cattle. The SNPs identified in previous association studies and through extensive analysis of candidate genomic regions and genes, were screened for their functional impact and allele frequency in Angus and Hereford breeds used as validation candidates for the panel. Association analyses were performed on genotypes of 159 SNPs from new samples of Angus (n = 160), Hereford (n = 329), and Angus-Hereford crossbred (n = 382) cattle using allele substitution and genotypic models in ASReml. Genomic heritabilities were estimated for feed efficiency traits using the full set of SNPs, SNPs associated with at least one of the traits (at P ≤ 0.05 and P < 0.10), as well as the Illumina bovine 50K representing a widely used commercial genotyping panel. A total of 63 SNPs within 43 genes showed association (P ≤ 0.05) with at least one trait. The minor alleles of SNPs located in the GHR and CAST genes were associated with decreasing effects on residual feed intake (RFI) and/or RFI adjusted for backfat (RFIf), whereas minor alleles of SNPs within MKI67 gene were associated with increasing effects on RFI and RFIf. Additionally, the minor allele of rs137400016 SNP within CNTFR was associated with increasing average daily gain (ADG). The SNPs genotypes within UMPS, SMARCAL, CCSER1, and LMCD1 genes showed significant over-dominance effects whereas other SNPs located in SMARCAL1, ANXA2, CACNA1G, and PHYHIPL genes showed additive effects on RFI and RFIf. Gene enrichment analysis indicated that gland development, as well as ion and cation transport are important physiological mechanisms contributing to variation in feed efficiency traits. The study revealed the effect of the Jak-STAT signaling pathway on feed efficiency through the CNTFR, OSMR, and GHR genes. Genomic heritability using the 63 significant (P ≤ 0.05) SNPs was 0.09, 0.09, 0.13, 0.05, 0.05, and 0.07 for ADG, dry matter intake, midpoint metabolic weight, RFI, RFIf, and backfat, respectively. These SNPs contributed to genetic variation in the studied traits and thus can potentially be used or tested to generate cost-effective molecular breeding values for feed efficiency in beef cattle. [ABSTRACT FROM AUTHOR]

Genomic selection is becoming a standard tool in livestock breeding programs, particularly for traits that are hard to measure. Accuracy of genomic selection can be improved by increasing the quantity and quality of data and potentially by improving analytical methods. Adding genotypes and phenotypes from additional breeds or crosses often improves the accuracy of genomic predictions but requires specific methodology. A model was developed to incorporate breed composition estimated from genotypes into genomic selection models. This method was applied to age at puberty data in female beef cattle (as estimated from age at first observation of a corpus luteum) from a mix of Brahman and Tropical Composite beef cattle. In this dataset, the new model incorporating breed composition did not increase the accuracy of genomic selection. However, the breeding values exhibited slightly less bias (as assessed by deviation of regression of phenotype on genomic breeding values from the expected value of 1). Adding additional Brahman animals to the Tropical Composite analysis increased the accuracy of genomic predictions and did not affect the accuracy of the Brahman predictions. [ABSTRACT FROM AUTHOR]

High intramuscular fat (IMF) awards price premiums to beef producers and is associated with meat quality and flavor. Studying gene interactions and pathways that affect IMF might unveil causative physiological mechanisms and inform genomic selection, leading to increased accuracy of predictions of breeding value. To study gene interactions and pathways, a gene network was derived from genetic markers associated with direct measures of IMF, other fat phenotypes, feedlot performance, and a number of meat quality traits relating to body conformation, development, and metabolism that might be plausibly expected to interact with IMF biology. Marker associations were inferred from genomewide association studies (GWAS) based on high density genotypes and 29 traits measured on 10,181 beef cattle animals from 3 breed types. For the network inference, SNP pairs were assessed according to the strength of the correlation between their additive association effects across the 29 traits. The co-association inferred network was formed by 2,434 genes connected by 28,283 edges. Topological network parameters suggested a highly cohesive network, in which the genes are strongly functionally interconnected. Pathway and network analyses pointed towards a trio of transcription factors (TF) as key regulators of carcass IMF: PPARGC1A, HNF4G, and FOXP3. Importantly, none of these genes would have been deemed as significantly associated with IMF from the GWAS. Instead, a total of 313 network genes show significant co-association with the 3 TF. These genes belong to a wide variety of biological functions, canonical pathways, and genetic networks linked to IMF-related phenotypes. In summary, our GWAS and network predictions are supported by the current literature and suggest a cooperative role for the 3 TF and other interacting genes including CAPN6, STC2, MAP2K4, EYA1, COPS5, XKR4, NR2E1, TOX, ATF1, ASPH, TGS1, and TTPA as modulators of carcass and meat quality traits in beef cattle. [ABSTRACT FROM AUTHOR]

Interest in genetic improvement of carcass and tenderness traits of beef cattle using genome-based selection (GS) and marker-assisted management programs is increasing. The success of such a program depends on the presence of linkage disequilibrium between the observed markers and the underlying QTL as well as on the relationship between the discovery, validation, and target populations. For molecular breeding values (MBV) predicted for a target population using SNP markers, reliabilities of these MBV can be obtained from validation analyses conducted in an independent population distinct from the discovery set. The objective of this study was to test MBV predicted for carcass and tenderness traits of beef cattle in a Canadian-based validation population that is largely independent of a United States-based discovery set. The discovery data set comprised of genotypes and phenotypes from >2,900 multibreed beef cattle while the validation population consisted of 802 crossbred feeder heifers and steers. A bivariate animal model that fitted actual phenotype and MBV was used for validation analyses. The reliability of MBV was defined as square of the genetic correlation (R²g) that represents the proportion of the additive genetic variance explained by the SNP markers. Several scenarios involving different starting marker panels (384, 3K, 7K, and 50K) and different sets of SNP selected to compute MBV (50, 100, 200, 375, 400, 600, and 800) were investigated. Validation results showed that the most reliable MBV (R²g) were 0.34 for HCW, 0.36 for back fat thickness, 0.28 for rib eye area, 0.30 for marbling score, 0.25 for yield grade, and 0.38 for Warner-Bratzler shear force across the different scenarios explored. The results indicate that smaller SNP panels can be developed for use in genetic improvement of beef carcass and tenderness traits to exploit GS benefits. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Animal Science is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Animal Science is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The candidate gene approach was used to identify genes associated with residual feed intake (RFI) in beef steers. The approach uses prior knowledge of gene functions to predict their biological role in the variation observed in a trait. It is suited to identify genes associ-ated with complex traits where each gene has a relatively small effect. First, positional candidate genes were identi-fied within the genomic positions of previously reported QTL associated with component traits related to RFI such as dry matter intake (DMI), growth, feed conversion ratio (FCR), average daily gain (ADG), and energy balance. Secondly, the positional candidate genes were prioritized into functional candidate genes according to their bio-logical functions and their relationship with the biological processes associated with RFI including carbohydrate, fat and protein metabolism, thermoregulation, immunity and muscle activity. Single nucleotide polymorphisms (SNPs) located within the functional candidate genes were identified using mRNA sequences and prioritized into functional classes such as non-synonymous (nsS-NP), synonymous (sSNP) or intronic SNP. A total of 117 nsSNP were considered as functional SNP and genotyped in steers at the University of Alberta ranch in Kinsella. Multiple marker association analysis in ASReml was performed using RFI data obtained from 531 beef steers. Twenty-five SNP were significantly associated with RFI (P < 0.05) accounting for 19.7% of the phenotypic varia-tion. Using SIFT program to predict the effect of the SNP on the function of the corresponding protein, 3 of the 25 SNP were predicted to cause a significant effect on pro-tein function (P < 0.05). One of the 3 SNP was located in the GHR gene and was also associated with a significant effect on the tertiary structure of the GHR protein (P < 0.05) as modeled using SWISSModel software. Least square means for each genotype were estimated and an over-dominance effect was observed for the SNP located in the GHR, CAST, ACAD 11 and UGT3A1 genes. In addi-tion, 2 other SNP showed a dominance effect and 3 genes had an additive effect. Gene network analysis performed in Ingenuity pathway analysis (1PA) software (Ingenuity Systems, www.ingenuity.com) indicated that the signifi-cant genes were involved in biological pathways such as lipid, protein and energy metabolism, electron transport and membrane signaling. The genes in this study, if vali-dated in other beef cattle populations, may be useful for marker assisted selection for feed efficiency. [ABSTRACT FROM AUTHOR]

There is concern in the beef industry that selecting bulls for feed efficiency based on residual feed intake (RFI) may have a negative impact on bull repro-ductive performance and fertility. Here we investigated the impact of selection of bulls for low RFI on breeding soundness evaluation (BSE), reproductive performance, and fertility of bulls under natural service in multisire mating groups on pasture. Of the 412 RFI-tested bulls available, 98 (23.8%) were culled for performance, type, temperament, or other reasons, and 88 (21.4%) were culled for failing BSE, for an overall cull rate of 45.1%. From among the 314 bulls subjected to BSE, 32 (10.2%), 20 (6.4%), and 36 (11.4%) were culled for poor feet and legs, scrotal circumference, and semen quality, respectively. The BSE traits were not different (P > 0.10) between bulls categorized as either inefficient (+RFI) or efficient (-RFI), but the proportion of bulls that failed to meet the 60% minimum sperm motility requirement tended (P = 0.07) to be greater in the -RFI group than in the +RFI group (10.2% vs. 4.4%, respectively). In a subpopulation of 115 bulls, individual progressive spenn motility was greater {P < 0.05) in +RFI (85%) than -RFI (80%) bulls. A multisire natural mating experiment was conducted during 2 consecutive breeding seasons (2006 to 2007 and 2007 to 2008) using 18 +RFI and 18 -RFI bulls. The overall calving rate (calves born/cows exposed) was 72.9%. Mean number of progeny per sire was significantly greater (P <0.01) in -RFI bulls (18.3) than in +RFI bulls (11.8). Selection for feed efficiency based on RFI appears to have no detrimental impact on reproductive performance and fertility in beef bulls bred in multisire groups on pasture. However, the decreased sperm motility and the greater number of progeny per sire associated with -RFI status need further investigation. [ABSTRACT FROM AUTHOR]

The molecular mechanisms that regulate fat deposition in bovine adipose tissue have not been well studied. To elucidate the genes and gene networks involved in bovine fat development, transcriptional profiles of backfat (BF) tissues from Hereford x Aberdeen Angus (HEAN, a = 6) and Charolais x Red Angus (CHRA, a = 6) steers with high or low BF thickness were characterized by digital gene expression-tag profiling. Approximately 9.8 to 21.9 million tags were obtained for each library, and a total of 18,034 genes were identified. In total, 650 genes were found to be differentially expressed, with a greater than 1.5-fold difference between the 2 crossbreds (Benjamini-Hochberg false discovery rate ~ 0.05). The majority of differentially expressed genes that were more highly expressed in CHRA vs. HEAN were associated with development, whereas the differentially expressed genes with greater expression in HEAN vs. CHRA were overrepresented in biological processes such as metabolism and immune response. Thirty-six and 152 differentially expressed genes were detected between animals with high (n = 3) and low (n = 3) BF thickness in HEAN and CHRA, respectively (Benjamini-Hochberg false discovery rate ≤0.05). The differentially expressed genes between high and low groups in CHRA were related to cell proliferation and development processes. In addition, lipid metabolism was 1 of the top 5 molecular and cellular functions identified in both crossbreds. Ten and 17 differentially expressed genes were found to be involved in fat metabolism in HEAN and CHRA, respectively. Genes associated with obesity, such as PTX3 (pentraxin 3, long) and SERPINE1 (serpin peptidase inhibitor, dade E, member 1), were more highly expressed (P < 0.05) in the subset of CHRA animals with greater BF thickness. Our study revealed that the expression patterns of genes in BF tissues differed depending on the genetic background of the cattle. [ABSTRACT FROM AUTHOR]

This study set out to examine the genetic parameters and genetic correlations of feed efficiency traits in steers (n = 490) fed grower or finisher diets in two feeding periods. A bivariate model was used to estimate phenotypic and genetic parameters using steers that received the grower and finisher diets in successive feeding periods while a repeated animal model was used to estimate the permanent environmental effects. Genetic correlations between the grower-fed and finisher-fed regimes were 0.50 ± 0.48 and 0.78 ± 0.43 for RFI and G:F, respectively. The moderate genetic correlation between the two feeding regimes may indicate the presence of genotype-by-environment interaction (GEI) for RFI. Permanent environmental effects (expressed in percentage of phenotypic variance) were detected in the grower-fed steers for ADG (38%), DMI (30%), RFI (18%) and G:F (40%) and also in the finisher-fed steers for ADG (28%), DMI (35%), MWT (23%) and RFI (10%). Heritability estimates were 0.08 ± 0.10 and 0.14 ± 0.15 for the grower-fed steers while 0.42 ± 0.16 and 0.40 ± 17 for the finisher-fed steers for RFI and G:F, respectively. The dependency of the RFI on the feeding regime may have serious implications when selecting animals in the beef industry. Due to higher cost of grains, feed efficiency in the feedlot might be over emphasized while efficiency in the cow herd and the backgrounding segments may have less emphasis. These results may also favor the retention (for subsequent breeding) of cows whose steers were efficient in the feedlot sector. Therefore, comprehensive feeding trials may be necessary in order to provide more insight into the mechanisms surrounding GEI in steers. [ABSTRACT FROM AUTHOR]

Data from a 3yr feeding trial data of crossbred steers (n = 331) was used to examine the relationship between feeding behavior traits and feed efficiency in steers fed grower and finisher diets, successively. There were two feeding periods each year whereby the steers were fed a grower diet in the first feeding period (P1) and a finisher diet in the second feeding period (P2). Each feeding period lasted for a minimum of 10 weeks, ad-libitum. In addition to feed intake, records on three measures of feeding behavior (feeding duration (FD), headdown time (HDT) and feeding frequency (FF)) were collected using the GrowSafe feeding system. Residual feed intake (RFI) was calculated by regression, after which the steers were classified as low (< 0.5SD), medium (± 0.5SD) or high (> 0.5SD) from the mean. The steers had greater (P < 0.001) FD, HDT and FF when the grower diet was fed but greater feeding rate (FR) when the finisher diet was fed. Including the measures of feeding behavior as covariates to the feed intake prediction model containing ADG, metabolic mid-weight and ultrasound back-fat accounted for more variation in DMI than models that did not contain these additional parameters. The FD and HDT were significantly different (P < 0.05) among the RFI classes regardless of the feeding period while no differences (P > 0.90) were found for FR among the RFI classes. For the growing period and finishing period, respectively, FD had phenotypic correlations with HDT (0.79, 0.83), FF (0.14, 0.55), DMI (0.38, 0.34) and FR (-0.34, -0.21). Heritability estimates in P1 and P2 for FD, HDT and FF were 0.25 ± 0.16, 0.14 ± 0.11; 0.14 ± 0.15, 0.09 ± 0.10; and 0.56 ± 0.19, 0.59 ± 0.18, respectively. Genetic correlations between P1 and P2 were 0.91 ± 0.26, 0.93 ± 0.37 and 0.94 ± 0.11 for FD, HDT and FF, respectively. The results suggest that it may be appropriate to include feeding behavior traits as covariates to indicate measure(s) of animal activity in the calculation of RFI. Feeding behavior phenotypes were greater during the grower-fed period than the finisher-fed period. During these feeding periods, efficient steers exhibited fewer FF, shorter FD and shorter HDT than inefficient steers. [ABSTRACT FROM AUTHOR]

This 3-yr study used 490 steers to determine whether feedlot steers changed their feed efficiency (FE) ranking when fed a grower diet, then a finisher diet. The steers were crossbreds and were between 5 to 7 mo of age. There were 2 feeding periods each year. Within each year, approximately 90 steers had their diet switched from a grower to a finisher diet (feed-swap group), whereas another 90 steers were fed either the grower (grower-fed group) or the finisher (finisher-fed group) diet throughout the feeding trial. Each feeding test lasted for a minimum of 10 wk, and all steers were fed ad libitum. Individual animal feed intakes were collected using the GrowSafe feeding system, and BW were measured every 2 wk. Residual feed intake (RFI), G:F, and Kleiber ratio (KR) were computed at the end of each feeding period. For each measure of efficiency, animals were classified as low, medium, or high based on 0.5 SD from the mean. The majority of steers did not maintain the previous efficiency class in the second period. Approximately 58, 51, and 51% of steers in the feed-swap group, finisher-fed group, and the grower-fed group, respectively, changed their RFI measure by 0.5 SD. A low rank correlation occurred in all test groups but was less in the feed-swap group. Spearman rank correlations between the 2 feeding periods in the feed-swap group were 0.33, 0.20, and 0.31 for RFI, G:F, and KR, respectively. Classifications based on G:F and KR showed that a greater number of steers (P < 0.05) in the feed-swap group did not maintain their FE class from 1 feeding regimen to the other, whereas classification based on RFI did not show any difference (P > 0.05) between the proportions of individuals that changed or maintained their FE class. In the groups without a feed-swap, there was no difference (P > 0.05) in the proportion of steers that changed or maintained the same FE class for all FE measures. Our results suggest that diet type and feeding period affect the FE ranking in beef steers. A feedlot diet is ideal for evaluating the FE potential of steers for feedlot profitability; however, we suggest that tests involving less dense diets should be examined in an effort to understand the relationships between FE and feeder profitability. [ABSTRACT FROM AUTHOR]

This study sought to assess whether residual feed intake (RFI) calculated by regressing feed intake (DMI) on growth rate (ADG) and metabolic mid-BW in 3 different ways led to similar estimates of genetic parameters and variance components for young growing cattle tested for feed intake in fall and winter seasons. A total of 378 beef steers in 5 cohorts were fed a typical high energy feedlot diet and had free-choice access to feed and water. Feed intake data were collected in fall or winter seasons. Climate data were obtained from the University of Alberta Kinsella meteorological station and Vikings AGCM station. Individual animal RFI was obtained by either fitting a regression model to each test group separately (RFIC), fitting a regression model to pooled data consisting of all cohorts but including test group as a fixed effect (RFIO), or fitting a regression to pooled data with test group as a fixed effect but within seasonal (fall-winter or winterspring) groups (RFIS). Two animal models (M1 and M2) that differed by the inclusion of fixed effects of test group or season, respectively, were used to evaluate RFI measurements. Feed intake was correlated with air temperature, relative humidity, solar radiation, and wind speed (-0.26, 0.23, 0.30, -0.14 for fall-winter and 0.31, -0.04, 0.14, 0.16 for winter-spring, respectively), but the nature and magnitude of the correlations were different for the 2 seasons. Single trait direct heritability, model likelihood, direct genetic variance, and EBV accuracy estimates were greatest for RFIC and least for RFIO for both M1 and M2 models. A significant genetic correlation was also observed between RFIO and ADG, but not for RFIC and RFIS. Including a season effect (M2) in the genetic evaluation of RFIO resulted in the smallest heritability, model LogL, EBV accuracy, and largest residual variance estimates. These results, though not conclusive, suggest a possible effect; of seasonality on feed intake and thus feed efficiency. [ABSTRACT FROM AUTHOR]

Feed intake and efficiency are economically important traits because feed is the greatest variable cost in beef production. Feed efficiency can be measured as residual feed intake (RFI), which is the difference between actual DM1 of an animal and the expected DM1 based on its BW and growth rate. Feed conversion ratio (FCR) is the inverse of gross feed efficiency and is the ratio of DM1 to ADG. A total of 2,633 SNP across the 29 bovine autosomes were analyzed in 464 steers sired by Angus, Charolais, or Alberta Hybrid bulls for associations with RFI. A total of 150 SNP were associated with RFI at P < 0.05 of which 23 were significant at P < 0.01. Nine of the SNP pairs show high linkage disequilibrium (r2 > 0.80), so only 1 of the SNP pairs was used in further multiple-marker analyses. Two methods were used to create a panel of SNP that were maximally informative for RFI based on the data. In the first method, 141 unique SNP were combined in a single multivariate model and a backward elimination model was used to drop SNP until all SNP left in the model were significant at P < 0.05. The SNP had greater effects when combined in the multivariate model than when tested individually. In the second method, the estimates from the 141 SNP were used to create a sequential molecular breeding value (MBV) according to the compound covariate prediction (CCP) procedure. The sequential MBV was built by adding the estimated effects one at a time, but only keeping SNP effects in the sequential MBV if the test statistic and the proportion of variance explained were improved. Predictabilities of the 2 methods were compared by regressing RFI on a final MBV created from SNP that remained in each analytical model. The MBV from the compound covariate prediction model produced an r2 of 0.497, whereas the multivariate model MBV had a decreased r2 of 0.416. The significant SNP were also tested for associations with DM1 and FCR. The SNP showed different combinations of associations with the 4 traits, including some that were only associated with RFI. About 9.5% of the SNP from the 2 models were within 5 cM of previously identified RFI QTL and pin- point areas to further explore for positional candidate genes. In conclusion, this study has identified a panel of SNP with significant effects on RFI that need to be validated in an independent population and provides continued progress toward selecting markers for use in marker-assisted selection for feed efficiency in beef cattle. [ABSTRACT FROM AUTHOR]

ABSTRACT: Several studies have reported the presence of carcass quality QTL on BTA14 and BTA26, with no specific genes being conclusively linked as their cause. The aim of this study was to identify polymorphisms in genes known to affect lipid metabolism in other species and to assess their association with carcass quality traits. Two genes located on BTA14, 2,4 clienoyl CoA reductase 1 (DEGR1) and core binding factor, runt domain, α subunit 2, translocated to 1 gen (cBFA2T1), have been previously evaluated in other species and found to contain polymorphisms influencing lipid metabolism. A gene on BTA26, fibroblast growth factor 8 (FCF8), has in recent studies been linked to several QTL affecting obesity in mice, indicating its potential for regulating adiposity in other species. Sequencing analysis identified 9 polymorphisms in DEGR1, 4 in cBFA2T1, and 4 in FCF8. Multiple sequence alignment of DEGR1 among cattle, humans, and mice showed that 4 of these mutations lie in conserved regions across these species. Using 464 Angus, Charolais, and crossbred animals produced associations with ultrasound marbling score (cBFA2T1, P = 0.019), ultrasoi.md backfat (DECR1, P = 0.012), carcass back-fat (FGF8, P = 0.004), and lean meat yield (FGF8, 1' = 0.005). Quantitative trait loci analysis includirig a set of previously genotyped markers on BTA14, and 1 DECR1 polymorphism resulted in several significant QTL peaks: ultrasound backfat (UBF) at 91 cM, lean meat yield at 86 cM, carcass gradefat at 15 cM, and yield grade at 87 cM, all at the P < 0.05 level. Using DECR1 as a genetic covariate removed the UBF QTL, indicating that this SNP was contributing to the variation observed in UBF. A similar analysis was performed on BTA26 using 1 of the FCF8 polymorphisms. Results showed significant peaks for lean meat yield at 2 cM and for yield grade at 25 cM, both at P < 0.01, and for carcass backfat at 25 cM (P < 0.05). Removal of FCF8 SNP in further analysis resulted in the disappearance of the carcass hackfat QTL. These results suggest that polymorphisms discovered in DECR1, cBFA2T1, and FCF8 may play a role in the lipid metabolism pathway affecting carcass quality traits in beef cattle. However, further studies are needed to confirm that these polymorphisms are responsible for the differences observed in carcass quality in beef cattle. [ABSTRACT FROM AUTHOR]

Canada is committed to reducing its greenhouse gas emissions to 6% below 1990 amounts between 2008 and 2012, and methane is one of several greenhouse gases being targeted for reduction. Methane production from ruminants is one area in which the agriculture sector can contribute to reducing our global impact. Through mathematical modeling, we can further our understanding of factors that control methane production, improve national or global greenhouse gas inventories, and investigate mitigation strategies to reduce overall emissions. The purpose of this study was to compile an extensive database of methane production values measured on beef cattle, and to generate linear and nonlinear equations to predict methane production from variables that describe the diet. Extant methane prediction equations were also evaluated. The linear equation developed with the smallest root mean square prediction error (RMSPE, % observed mean) and residual variance (RV) was Eq. I: CH4, MJ/d = 2.72 (±0.543) + [0.0937 (+0.0117) × ME intake, MJ/dJ + [4.31 (±0.215) × Cellulose, kg/dj - [6.49 (±0.800) × Hemicellulose, kg/d] - [7.44 (±0.521) × Fat, kg/dI [RMSPE = 26.9%, with 94% of mean square prediction error (MSPE) being random error; RV = 1.13]. Equa- tions based on ratios of one diet variable to another were also generated, and Eq. P, CH4, MJ/d = 2.50 (±0.649) - [0.367 (±0.0191) × (Starch:ADF)] + [0.766 (±0.116) × DM1, kg/d], resulted in the smallest RMSPE values among these equations (RMSPE = 28.6%, with 93.6% of MSPE from random error; RV = 1.35). Among the nonlinear equations developed, Eq. W, CH4, MJ/d = 10.8 (±1.45) × (1 - e{-0.141 (±0.0381) × DMI, kg/d}) performed well (RMSPE = 29.0%, with 93.6% of MSPE from random error; RV = 3.06) as did Eq. W3, CH4, MJ/d = 10.8 (±1.45) × (1 - e.{{-|-0.034 × (NFC/NDF) + 0.228] × DM1, kg/d}] (RMSPE = 28.0%, with 95% of MSPE from random error). Extant equations from a previous publication by the authors performed comparably with, if not better than in some cases, the newly developed equations. Equation selection by users should be based on RV and RMSPE analysis, input variables available to the user, and the diet fed, because the equation selected must account for divergence from a "normal" diet (e.g., high-concentrate diets, high-fat diets). [ABSTRACT FROM AUTHOR]

Feed intake and feed efficiency are economically important traits in beef cattle because feed is the greatest variable cost in production. Feed efficiency can be measured as feed conversion ratio (FCR, intake per unit gain) or residual feed intake (RFI, measured as DMI corrected for BW and growth rate, and sometimes a measure of body composition, usually carcass fatness, RFIbf). The goal of this study was to fine map QTL for these traits in beef cattle using 2,194 markers on 24 autosomes. The animals used were from 20 half-sib families originating from Angus, Charolais, and University of Alberta Hybrid bulls. A mixed model with random sire and fixed QTL effect nested within sire was used to test each location (cM) along the chromosomes. Threshold levels were determined at the chromosome and genome levels using 20,000 permutations. In total, 4 QTL exceeded the genome-wise threshold of P < 0.001, 3 exceeded at P < 0.01, 17 at P < 0.05, and 30 achieved significance at the chromosome-wise threshold level (at least P < 0.05). No QTL were detected on BTA 8, 16, and 27 above the 5% chromosome-wise significance threshold for any of the traits. Nineteen chromosomes contained RFI QTL significant at the chromosome-wise level. The RFIbf QTL results were generally similar to those of RFI, the positions being similar, but occasionally differing in the level of significance. Compared with RFI, fewer QTL were detected for both FCR and DMI, 12 and 4 QTL, respectively, at the genome-wise thresholds. Some chromosomes contained FCR QTL, but not RFI QTL, but all DMI QTL were on chromosomes where RFI QTL were detected. The most significant QTL for RFI was located on BTA 3 at 82 cM (P = 7.60 × 10-5), for FCR on BTA 24 at 59 cM (P = 0.0002), and for DM1 on BTA 7 at 54 cM (P = 1.38 × 10-5). The RFI QTL that showed the most consistent results with previous RFI QTL mapping studies were on BTA 1, 7, 18, and 19. The identification of these QTL provides a starting point to identify genes affecting feed intake and efficiency for use in marker-assisted selection and management. [ABSTRACT FROM AUTHOR]

Feed efficiency is an economically important trait in beef cattle. Net feed efficiency, measured as residual feed intake (RFI), is the difference between actual feed intake and the predicted feed intake required for maintenance and gain of the animal. SNPs that show associations with RFI may be useful quantitative trait nucleotides for marker-assisted selection. This study identified associations between SNPs underlying five RFI QTL on five bovine chromosomes (BTA2, 5, 10, 20 and 29) with measures of dry matter intake (DMI), RFI and feed conversion ratio (FCR) in beef cattle. Six SNPs were found to have effects on RFI ( P < 0.05). The largest single SNP allele substitution effect for RFI was −0.25 kg/day located on BTA2. The combined effects of the SNPs found significant in this experiment explained 6.9% of the phenotypic variation of RFI. Not all the RFI SNPs showed associations with DMI and FCR even though these traits are highly correlated with RFI ( r = 0.77 and r = 0.62 respectively). This shows that these SNPs may be affecting the underlying biological mechanisms of feed efficiency beyond feed intake control and weight gain efficiency. These SNPs can be used in marker-assisted selection but first it will be important to verify these effects in independent populations of cattle. [ABSTRACT FROM AUTHOR]

Feed intake and feed efficiency of beef cattle are economically relevant traits. The study was conducted to identify QTL for feed intake and feed efficiency of beef cattle by using genotype information from 100 microsatellite markers and 355 SNP genotyped across 400 progeny of 20 Angus, Charolais, or Alberta Hybrid bulls. Traits analyzed include feedlot ADG, daily DMI, feed-to-gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F)], and residual feed intake (RFI). A mixed model with sire as random and QTL effects as fixed was used to generate an F-statistic profile across and within families for each trait along each chromosome, followed by empirical permutation tests to determine significance thresholds for QTL detection. Putative QTL for ADG (chromosome-wise P < 0.05) were detected across families on chromosomes 5 (130 cM), 6 (42 cM), 7 (84 cM), 11 (20 cM), 14 (74 cM), 16 (22 cM), 17 (9 cM), 18 (46 cM), 19 (53 cM), and 28 (23 cM). For DMI, putative QTL that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (93 cM), 3 (123 cM), 15 (31 cM), 17 (81 cM), 18 (49 cM), 20 (56 cM), and 26 (69 cM) in the across-family analyses. Putative across-family QTL influencing F:G that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 3 (62 cM), 5 (129 cM), 7 (27 cM), 11 (16 cM), 16 (30 cM), 17 (81 cM), 22 (72 cM), 24 (55 cM), and 28 (24 cM). Putative QTL influencing RFI that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (90 cM), 5 (129 cM), 7 (22 cM), 8 (80 cM), 12 (89 cM), 16 (41 cM), 17 (19 cM), and 26 (48 cM) in the across-family analyses. In addition, a total of 4, 6, 1, and 8 chromosomes showed suggestive evidence (chromosome-wise, P < 0.10) for putative ADG, DMI, F:G, and RFI QTL, respectively. Most of the QTL detected across families were also detected within families, although the locations across families were not necessarily the locations within families, which is likely because of differences among families in marker informativeness for the different linkage groups. The locations and direction of some of the QTL effects reported in this study suggest potentially favorable pleiotropic effects for the underlying genes. Further studies will be required to confirm these QTL in other populations so that they can be fine-mapped for potential applications in marker-assisted selection and management of beef cattle. [ABSTRACT FROM AUTHOR]

Feed intake and efficiency of growth are economically important traits of beef cattle. This study determined the relationships of daily DMI, feed:gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F) and therefore increases as the efficiency of gain decreases and vice versa, residual feed intake (RFI), and partial efficiency of growth (efficiency of ADG, PEG) with growth and carcass merit of beef cattle. Residual feed intake was calculated from phenotypic regression (RFIp) or genetic regression (RFIg) of ADG and metabolic BW on DMI. An F1 half-sib pedigree file containing 28 sires, 321 dams, and 464 progeny produced from crosses between Alberta Hybrid cows and Angus, Charolais, or Alberta Hybrid bulls was used. Families averaged 20 progeny per sire (range = 3 to 56). Performance, ultrasound, and DMI data was available on all progeny, of which 381 had carcass data. Phenotypic and genetic parameters were obtained using SAS and ASREML software, respectively. Differences in RFIp and RFIg, respectively, between the most and least efficient steers (i.e., steers with the lowest PEG) were 5.59 and 6.84 kg of DM/d. Heritabilities for DMI, F:G, PEG, RFIp, and RFIg were 0.54 ± 0.15, 0.41 ± 0.15, 0.56 ± 0.16, 0.21 ± 0.12, and 0.42 ± 0.15, respectively. The genetic (r = 0.92) and phenotypic (r = 0.97) correlations between RFIp and RFIg indicated that the 2 indices are very similar. Both indices of RFI were favorably correlated phenotypically (P < 0.001) and genetically with DMI, F:G, and PEG. Residual feed intake was tendentiously genetically correlated with ADG (r = 0.46 ± 0.45) and metabolic BW (r = 0.27 ± 0.33), albeit with high SE. Genetically, RFIg was independent of ADG and BW but showed a phenotypic correlation with ADG (r = -0.21; P < 0.05). Daily DMI was correlated genetically (r = 0.28) and phenotypically (r = 0.30) with F:G. Both DMI and F:G were strongly correlated with ADG (r > 0.50), but only DMI had strong genetic (r = 0.87 ± 0.10) and phenotypic (r = 0.65) correlations with metabolic BW. Generally, the phenotypic and genetic correlations of RFI with carcass merit were not different from zero, except genetic correlations of RFI with ultrasound and carcass LM area and carcass lean yield and phenotypic correlations of RFI with backfat thickness (P < 0.01). Daily DMI had moderate to high phenotypic (P < 0.01) and genetic correlations with all the ultrasound and carcass traits. Depending on how RFI technology is applied, adjustment for body composition in addition to growth may be required to minimize the potential for correlated responses to selection in cattle. [ABSTRACT FROM AUTHOR]

Feeding behavior and temperament may be useful in genetic evaluations either as indicator traits for other economically relevant traits or because the behavior traits may have a direct economic value. We determined the variation in feeding behavior and temperament of beef cattle sired by Angus, Charolais, or Hybrid bulls and evaluated their associations with performance, efficiency, and carcass merit. The behavior traits were daily feeding duration, feeding head down (HD) time, feeding frequency (FF), and flight speed (FS, as a measure of temperament). A pedigree file of 813 animals forming 28 paternal half-sib families with about 20 progeny per sire was used. Performance, feeding behavior, and efficiency records were available on 464 animals of which 381 and 302 had records on carcass merit and flight speed, respectively. Large SE reflect the number of animals used. Direct heritability estimates were 0.28 ± 0.12 for feeding duration, 0.33 ± 0.12 for HD, 0.38 ± 0.13 for FF, and 0.49 ± 0.18 for FS. Feeding duration had a weak positive genetic (rg) correlation with HD (rg = 0.25 ± 0.32) and FS (rg = 0.42 ± 0.26) but a moderate negative genetic correlation with FF (rg = -0.40 ± 0.30). Feeding duration had positive phenotypic (rp) and genetic correlations with DMI (rp = 0.27; rg = 0.56 ± 0.20) and residual feed intake (RFI; rp = 0.49; rg = 0.57 ± 0.28) but was unrelated phenotypically with feed conversion ratio [FCR; which is the reciprocal of the efficiency of growth (G:F)]. Feeding duration was negatively correlated with FCR (rg = -0.25 ± 0.29). Feeding frequency had a moderate to high negative genetic correlation with DMI (rg = -0.74 ± 0.15), FCR (rg = -0.52 ± 0.21), and RFI (rg = -0.77 ± 0.21). Flight speed was negatively correlated phenotypically with DMI (rp = -0.35) but was unrelated phenotypically with FCR or RFI. On the other hand, FS had a weak negative genetic correlation with DMI (rg = -0.11 ± 0.26), a moderate genetic correlation with FCR (rg = 0.40 ± 0.26), and a negative genetic correlation with RFI (rg = -0.59 ± 0.45). The results indicate that behavior traits may contribute to the variation in the efficiency of growth of beef cattle, and there are potential correlated responses to selection to improve efficiency. Feeding behavior and temperament may need to be included in the definition of beef cattle breeding goals, and approaches such as the culling of unmanageable cattle and the introduction of correct handling facilities or early life provision of appropriate experiences to improve handling will be useful. [ABSTRACT FROM AUTHOR]

Leptin is the hormone product of the obese gene that is synthesized and predominantly expressed by adipocytes. This study estimated the genetic variation in serum leptin concentration and evaluated the genetic and phenotypic relationships of serum leptin concentration with performance, efficiency of gain, and carcass merit. There were 464 steers with records for serum leptin concentration, performance, and efficiency of gain and 381 steers with records for carcass traits. The analyses included a total of 813 steers, including those without phenotypic records. Phenotypic and genetic parameter estimates were obtained using SAS and ASREML, respectively. Serum leptin concentration was moderately heritable (h² = 0.34 ± 0.13) and averaged 13.91 (SD = 5.74) ng/mL. Sire breed differences in serum leptin concentration correlated well with breed differences in body composition. Specifically, the serum leptin concentration was 20% greater in Angus-sired steers compared with Charolais-sired steers (P < 0.001). Consequently, ultrasound backfat (27%), carcass 12th-rib fat (31%), ultrasound marbling (14%), and carcass marbling (15%) were less in Charolais- than Angus-sired steers (P < 0.001). Conversely, carcass LM area (P < 0.05) and carcass lean meat yield (P < 0.001) were greater in Charolais- compared with Angus-sired steers. Steers with greater serum leptin concentration also had greater DMI (P < 0.001), greater residual feed intake (P = 0.04), and partial efficiency of growth (P = 0.01), but did not differ in feed conversion ratio (P > 0.10). Serum leptin concentration was correlated phenotypically with ultrasound backfat (r = 0.41; P < 0.00 1), carcass 12th-rib fat (r = 0.42; P < 0.001), ultrasound marbling (r = 0.25; P < 0.01), carcass marbling (r = 0.28; P < 0.01), ultrasound LM area (r = -0.19; P < 0.01), carcass LM area (r = -0.17; P < 0.05), lean meat yield (r = -0.38; P < 0.001), and yield grade (r = 0.32; P <0.001). The corresponding genetic correlations were generally greater than the phenotypic correlations and included ultrasound backfat (r = 0.76 ± 0.19), carcass 12th-rib fat (r = 0.54 ± 0.23), ultrasound marbling (r = 0.27 ± 0.22), carcass marbling (r = 0.76 ± 0.21), ultra- sound LM area (r = -0.71 ± 0.19), carcass LM area (r = -0.75 ± 0.20), lean meat yield (r = -0.59 ± 0.22), and yield grade (r = 0.39 ± 0.26). Serum leptin concentration can be a valuable tool that can be incorporated into appropriate selection programs to favorably improve the carcass merit of cattle. [ABSTRACT FROM AUTHOR]

This study was conducted to determine the optimum test duration and the effect of missing data on accuracy of measuring feed efficiency and its 4 related traits ADG, DMI, feed conversion ratio, and residual feed intake in beef cattle using data from 456 steers with 5,397 weekly averaged feed intakes and BW repeated measurements taken over 91 d. Data were collected using the GrowSafe System at the University of Alberta Kinsella Research Station. The changes and relative changes in phenotypic residual variances and correlations (Pearson and Spearman) among data from shortened test durations (7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, or 84 d) and a 91-d test were used to determine the optimum test duration for the 4 traits. The traits were fitted to a mixed model with repeated measures using SAS. Test durations for ADG, DMI, feed conversion ratio, and residual feed intake could be shortened to 63, 35, 42, and 63 d, respectively, without significantly reducing the accuracy of the tests when BW was measured weekly. The accuracy of the test was not compromised when up to 30% of the records were randomly removed after the first 35 d on test. These results have valuable and practical implications for performance and feed efficiency testing in beef cattle. [ABSTRACT FROM AUTHOR]

Residual feed intake (RFI) is the difference between the actual and expected feed intake of an animal based on its BW and growth rate over a specified period. The biological mechanisms underlying the variation in feed efficiency in animals with similar BW and growth rate are not well understood. This study determined the relationship of feedlot feed efficiency, performance, and feeding behavior with digestion and energy partitioning of 27 steers. The steers were selected from a total of 306 animals based on their RFI following feedlot tests at the University of Alberta Kinsella Research Station. Selected steers were ranked into high RFI (RFI >0.5 SD above the mean, n = 11), medium RFI (RFI ± 0.5 SD above and below the mean, n = 8), and low RFI (RFI <-0.5 SD below the mean, n = 8). The respective BW ± SD for the RFI groups were 495.6 ± 12.7, 529.1 ± 18.6, and 501.2 ± 15.5 kg. Digestibility and calorimetry trials were performed on a corn-or barley-based concentrate diet in yr 1 and 2, respectively, at 2.5 × maintenance requirements. Mean DMI (g/kg of BW0.75) during the measurements for high-, medium-, and low-RFI groups, respectively, were 82.7 ±2.0, 78.8±2.6, and 81.8 ± 2.5 and did not differ (P > 0.10). Residual feed intake was correlated with daily methane production and energy lost as methane (r = 0.44; P < 0.05). Methane production was 28 and 24% less in low-RFI animals compared with high- and medium-RFI animals, respectively. Residual feed intake tended to be associated (P < 0.10) with apparent digestibilities of DM (r = -0.33) and CP (r = -0.34). The RFI of steers was correlated with DE (r = -0.41; P < 0.05), ME (r = -0.44; P < 0.05), heat production (HP; r = 0.68; P < 0.001), and retained energy (RE; r = -0.67; P < 0.001; energy values are expressed in kcal/kg of BW0.75). Feedlot partial efficiency of growth was correlated (P < 0.01) with methane production (r = -0.55), DE (r = 0.46), ME (r = 0.49), HP (r = -0.50), and RE (r = 0.62). With the exception of HP (r = 0.37; P < 0.05), feed conversion ratio was unrelated to the traits considered in the study. Feeding duration was correlated (P < 0.01) with apparent digestibility of DM (r = -0.55), CP (r = -0.47), methane production (r = 0.51), DE (r = -0.52), ME (r = -0.55), and RE (r = -0.60). These results have practical implications for the selection of animals that eat less at a similar BW and growth rate and for the environmental sustainability of beef production. [ABSTRACT FROM AUTHOR]

Studies with different populations arc required to properly characterize the robustness of associations of polymorphisms in candidate genes with economically important traits across beef cattle populations before this sort of genetic information can be used efficiently in breeding and management decisions. The objective of this study was to evaluate the association of previously reported SNP in the bovine leptin gene with carcass and meat quality traits from a large sample of crossbred beef cattle. Five SNP (UASMSI UASMS2, UASMS3, E2JW, and E2FB) were genotyped on 1,111 crossbred bulls, heifers, and steers. The measured traits included fat, lean, and bone yield (%) by partial rib dissection, grade fat, LM area, HCW, quality grade, LM i.m. fat, and tenderness evaluation of LM and semitendinosus muscle. Only four SNP were analyzed (UASMS1, UASMS2, E2JW, and E2FB), because UASMS1 and UASMS3 were completely linked. A univariate mixed-inheritance animal model was used to evaluate the association of either genotypes or haplotypes with the traits. The two leptin exon 2 SNP were associated with fat and lean yield and grade fat (E2JW, P < 0.01, E2FB, P < 0.05), and they interacted in their effect on LM tenderness (P < 0.01). The leptin promoter SNP were either not associated with any of the traits (UASMS2) or with fat yield only (UASMS1). Three haplotypes (TCAC, CCAT, TTAC) were at high frequency in the population (88%) and had similar effects on all the traits. Compared with the common haplotypes, one haplotype (CCTT) showed a significantly different effect on fat and lean yield and grade fat (P < 0.01), and one haplotype (TTTT) had a different effect on LM tenderness (P < 0.03). Therefore, important associations between SNP within the leptin gene with lean yield, fatness (fat yield and subcutaneous fat), and tenderness were detected. Results confirm some of the previously reported associations, but diverge with respect to others, showing that further efforts are required to validate some prospective associations. [ABSTRACT FROM AUTHOR]