Efficiency Traits Research Articles

A High-Density Genetic Linkage Map and Fine Mapping of QTL For Feed Conversion Efficiency in Common Carp (Cyprinus carpio).

Feed conversion efficiency (FCE) is an economically crucial trait in fish, however, little progress has been made in genetics and genomics for this trait because phenotypes of the trait are difficult to measure. In this study, we constructed a high-density and high-resolution genetic linkage map with 28,416 SNP markers for common carp (Cyprinus carpio) based on high throughput genotyping with the carp 250K single nucleotide polymorphism (SNP) array in a full-sib F1 family of mirror carp (Cyprinus carpio) consisting of 141 progenies. The linkage map contained 11,983 distinct loci and spanned 3,590.09 cM with an average locus interval of 0.33 cM. A total of 17 QTL for the FCE trait were detected on four LGs (LG9, LG20, LG28, and LG32), explaining 8.9–15.9% of the phenotypic variations. One major cluster containing eight QTL (qFCE1-28, qFCE2-28, qFCE3-28, qFCE4-28, qFCE5-28, qFCE6-28, qFCE7-28, and qFCE8-28) was detected on LG28. Two clusters consisting of four QTL (qFCE1-32, qFCE2-32, qFCE3-32, and qFCE4-32) and three QTL (qFCE1-20, qFCE2-20, and qFCE3-20) were detected on LG32 and LG20, respectively. Nine candidate genes (ACACA, SCAF4, SLC2A5, TNMD, PCDH1, FOXO, AGO1, FFAR3, and ARID1A) underlying the feed efficiency trait were also identified, the biological functions of which may be involved in lipid metabolism, carbohydrate metabolism, energy deposition, fat accumulation, digestion, growth regulation, and cell proliferation and differentiation according to GO (Gene Ontology). As an important tool, high-density and high-resolution genetic linkage maps play a crucial role in the QTL fine mapping of economically important traits. Our novel findings provided new insights that elucidate the genetic basis and molecular mechanism of feed efficiency and the subsequent marker-assisted selection breeding in common carp.

Economic values of reproductive, growth, feed efficiency and carcass traits in Nellore cattle.

A bioeconomic model was developed to calculate the economic value (ev) of reproductive and growth performance, feed efficiency and carcass traits of a seedstock Nellore herd. Data from a full-cycle cattle operation (1,436 dams) located in the Brazilian Cerrado were assessed. The ev was calculated by the difference in profit before and after one-unit improvement in the trait, with others remaining unchanged. The ev was standardized by the phenotypic standard deviation of each trait. Preweaning average daily gain (ADG) was the most economically important trait evaluated (R$ 58.04/animal/year), followed by age at first calving (R$ 44.35), postweaning ADG (R$ 31.43), weight at 450days (R$ 25.36), accumulated productivity (R$ 21.43), ribeye area (R$ 21.35), calving interval (R$ 19.97), feed efficiency (R$ 15.24), carcass dressing per cent (R$ 8.27), weight at 120days (R$ 6.22), weight at 365days (R$ 6.06), weight at weaning (210days, R$ 5.82), stayability (R$ 5.70) and the probability of early calving (R$ 0.32). The effects of all traits on profits are evidence that their selection may result in the economic and genetic progress of the herd if there is genetic variability.

Estimation of genetic parameter for feed efficiency and resilience traits in three pig breeds

Recently, automatic feeders have become popular for collecting daily feed intake data in the pig industry, making it possible to evaluate genetic effects on feed efficiency and resilience traits, expressed as day-to-day fluctuations in feeding records. This study aimed to understand the influence of genetic factors on feed efficiency traits, including residual intake and BW gain (RIG), and resilience traits, as well as to compare the differences in genetic parameter estimates among three purebred pig breeds. A total of 6 103 pigs from three breeds (Large White: 1 193 pigs, Landrace: 3 010 pigs, and Duroc: 1 900 pigs) were raised in a specific pathogen-free environment. The growth and feed intake records during the testing period were obtained using automatic feeders, and the average daily gain (ADG) and average feed intake (AFI) were calculated. Feed conversion ratio (FCR), residual feed intake (RFI), residual gain, and RIG were calculated as feed efficiency traits, and the log-transformed variance of deviation for the daily feed intake (LnVar_FI), daily occupation time (LnVar_OC), and the daily number of visits to the feeder (LnVar_VT) was calculated as resilience traits. After estimating the genetic parameters for each breed, a meta-analysis was performed to obtain the weighted mean of heritability estimates (hm2) and genetic correlation estimates (GCm) for the three breeds. The hm2 were moderate and ranged from 0.31 to 0.39 for feed efficiency traits and 0.31 to 0.40 for resilience traits, and there were no significant differences in heritability estimates among the three breeds except for AFI, RFI, and RIG. For feed efficiency traits, the FCR and RIG showed favourably moderate GCm with AFI (0.29 and −0.33, respectively) and ADG (−0.39 and 0.31, respectively). For resilience traits, the LnVar_FI and LnVar_VT showed favourably low to moderate GCm with FCR (0.33 and 0.28, respectively) and RIG (−0.37 and 0.28, respectively), and there were no genetic relationships of LnVar_OC with FCR and RIG (the absolute value of GCm was 0.01). There was no significant difference in the genetic correlation estimates among the three breeds for feed efficiency and resilience traits. Our results suggest that feed efficiency and resilience traits were heritable, and resilience traits showed favourable or no genetic correlation with feed efficiency traits. In addition, the influence of genetic factors on feed efficiency and resilience traits could be the same among breeds.

Apart From the Diet, the Ruminal Microbiota of Lambs Is Modified in Relation to Their Genetic Potential for Feed Efficiency or Feeding Behavior

Using two successive types of diets (100% concentrate and 67% forage), this study explores the relationship between the ruminal microbiota of 78 Romane lambs and their feed efficiency (residual feed intake trait) or feeding behavior (feeding rate trait). Analysis was carried out phenotypically by correlating feed efficiency or feeding behavior traits with the relative abundance of bacteria at the phylum, family, and genus levels, and then genetically by comparing the microbiota of lambs selected for extreme breeding values for residual feed intake or feeding rate. Our results confirmed the major effect of diet on the ruminal microbiota composition. The microbiota of lambs consuming a forage-based diet was distinguished by higher microbial diversity and also by higher relative abundance of Firmicutes, whereas Bacteriodetes and Actinobacteria were relatively more abundant in the microbiota of lambs consuming a concentrate-based diet. Moreover, the comparison of lambs divergent for residual feed intake breeding values revealed that regardless of diet, more efficient lambs possessed a ruminal microbiota enriched in Coprococcus, Moryella, [Eubacterium] Brachy group, and [Eubacterium] hallii group, but depleted in Lachnospiraceae FD2005 and Shuttleworthia. The connection between microbiota composition and feeding rate was more tenuous, with no link between the abundance of particular genera and lambs genetically divergent for feeding rate.

Genetic variability in the feeding behavior of crossbred growing cattle and associations with performance and feed efficiency.

The objectives of the present study were to estimate genetic parameters for several feeding behavior traits in growing cattle, as well as the genetic associations among and between feeding behavior and both performance and feed efficiency traits. An additional objective was to investigate the use of feeding behavior traits as predictors of genetic merit for feed intake. Feed intake and live-weight data on 6,088 growing cattle were used of which 4,672 had ultrasound data and 1,548 had feeding behavior data. Feeding behavior traits were defined based on individual feed events or meal events (where individual feed events were grouped into meals). Univariate and bivariate animal linear mixed models were used to estimate (co)variance components. Heritability estimates (± SE) for the feeding behavior traits ranged from 0.19 ± 0.08 for meals per day to 0.61 ± 0.10 for feeding time per day. The coefficient of genetic variation per trait varied from 5% for meals per day to 22% for the duration of each feed event. Genetically heavier cattle, those with a higher daily energy intake (MEI), or those that grew faster had a faster feeding rate, as well as a greater energy intake per feed event and per meal. Better daily feed efficiency (i.e., lower residual energy intake) was genetically associated with both a shorter feeding time per day and shorter meal time per day. In a validation population of 321 steers and heifers, the ability of estimated breeding values (EBV) for MEI to predict (adjusted) phenotypic MEI was demonstrated; EBVs for MEI were estimated using multi-trait models with different sets of predictor traits such as liveweight and/or feeding behaviors. The correlation (± SE) between phenotypic MEI and EBV for MEI marginally improved (P < 0.001) from 0.64 ± 0.03 to 0.68 ± 0.03 when feeding behavior phenotypes from the validation population were included in a genetic evaluation that already included phenotypic mid-test metabolic live-weight from the validation population. This is one of the largest studies demonstrating that significant exploitable genetic variation exists in the feeding behavior of young crossbred growing cattle; such feeding behavior traits are also genetically correlated with several performance and feed efficiency metrics. Nonetheless, there was only a marginal benefit to the inclusion of time-related feeding behavior phenotypes in a genetic evaluation for MEI to improve the precision of the EBVs for this trait.

Revealing Pathways Associated with Feed Efficiency and Meat Quality Traits in Slow-Growing Chickens.

Simple SummaryKorat is a new chicken breed with high-protein meat, low fat, and low purine content. However, the effects of improving the breed’s feed efficiency, which would enhance production, on meat quality are unknown. Hence, understanding the genetic architecture underlying feed efficiency and meat quality traits in chicken offers new opportunities toward genetic improvement. Through a weighted gene co-expression network analysis on Korat chickens, the presented results provide new information on the molecular pathways that play important roles in FE and meat quality that could help achieve the optimum feed efficiency while maintaining meat quality in Korat chickens.Here, molecular pathways and genes involved in the feed efficiency (FE) and thigh-meat quality of slow-growing Korat chickens were investigated. Individual feed intake values and body weights were collected weekly to the calculate feed conversion ratios (FCR) and residual feed intake. The biochemical composition and meat quality parameters were also measured. On the basis of extreme FCR values at 10 weeks of age, 9 and 12 birds from the high and the low FCR groups, respectively, were selected, and their transcriptomes were investigated using the 8 × 60 K Agilent chicken microarray. A weighted gene co-expression network analysis was performed to determine the correlations between co-expressed gene modules and FE, thigh-meat quality, or both. Groups of birds with different FE values also had different nucleotide, lipid, and protein contents in their thigh muscles. In total, 38 modules of co-expressed genes were identified, and 12 were correlated with FE and some meat quality traits. A functional analysis highlighted several enriched functions, such as biological processes, metabolic processes, nucleotide metabolism, and immune responses. Several molecular factors were involved in the interactions between FE and meat quality, including the assembly competence domain, baculoviral IAP repeat containing 5, cytochrome c oxidase assembly factor 3, and myosin light chain 9 genes.

Phenotypic association among performance, feed efficiency and methane emission traits in Nellore cattle.

Enteric methane (CH4) emissions are a natural process in ruminants and can result in up to 12% of energy losses. Hence, decreasing enteric CH4 production constitutes an important step towards improving the feed efficiency of Brazilian cattle herds. The aim of this study was to evaluate the relationship between performance, residual feed intake (RFI), and enteric CH4 emission in growing Nellore cattle (Bos indicus). Performance, RFI and CH4 emission data were obtained from 489 animals participating in selection programs (mid-test age and body weight: 414±159 days and 356±135 kg, respectively) that were evaluated in 12 performance tests carried out in individual pens (n = 95) or collective paddocks (n = 394) equipped with electronic feed bunks. The sulfur hexafluoride tracer gas technique was used to measure daily CH4 emissions. The following variables were estimated: CH4 emission rate (g/day), residual methane emission and emission expressed per mid-test body weight, metabolic body weight, dry matter intake (CH4/DMI), average daily gain, and ingested gross energy (CH4/GE). Animals classified as negative RFI (RFI<0), i.e., more efficient animals, consumed less dry matter (P <0.0001) and emitted less g CH4/day (P = 0.0022) than positive RFI animals (RFI>0). Nonetheless, more efficient animals emitted more CH4/DMI and CH4/GE (P < 0.0001), suggesting that the difference in daily intake between animals is a determinant factor for the difference in daily enteric CH4 emissions. In addition, animals classified as negative RFI emitted less CH4 per kg mid-test weight and metabolic weight (P = 0.0096 and P = 0.0033, respectively), i.e., most efficient animals could emit less CH4 per kg of carcass. In conclusion, more efficient animals produced less methane when expressed as g/day and per kg mid-test weight than less efficient animals, suggesting lower emissions per kg of carcass produced. However, it is not possible to state that feed efficiency has a direct effect on enteric CH4 emissions since emissions per kg of consumed dry matter and the percentage of gross energy lost as CH4 are higher for more efficient animals.

PSVII-28 Genetic analysis of frame score and performance traits in Nellore cattle–growth, carcass and efficiency traits

Abstract We evaluated a novel frame score system for Nellore cattle raised on pasture (Guimarães et al., 2020 J, Anim. Sci. 98 (Suppl. 4)). Growth traits included age-adjusted weights (kg) at birth (W0), 120 (W120), 210 (W210) and 450 (W450) days of age, and adult weight (AW). Carcass traits (by ultrasound) included ribeye area (REA, cm2), 12th-13th rib backfat (BF, mm), rump fat (RF, mm), and intramuscular fat (IMF, %). Feed efficiency traits included residual feed intake (RFI, kg of DM/d) and DM intake (DMI, kg/d). We applied the previously developed equations (that also include hip height (HH, cm) and age to 12,049 records from the National Association of Breeders and Researchers (ANCP) database:FSmales= -20.35 + 0.1305*REA + 0.2633*BF - 0.5901*RF+ 0.1139*HH + 0.0056*AGEFSfemales = -11.87 + 0.1316*REA - 0.2457*BF - 0.6218*RF + 0.1139*HH + 0.0009507*AGEThe (co)variance components and genetic parameters were estimated using a linear animal model or a threshold animal model depending on the trait. The heritability estimate for frame score was moderate (0.30). Estimated genetic correlations were moderate for growth traits (W0, 0.51; W120, 0.41; W210, 0.35; W450, 0.29; AW, 0.39). Estimated genetic correlations for carcass and efficiency traits ranged from low to high (REA, 0.50; BF, -0.25; RF, -0.84; IMF, -0.15; DMI, 0.29; RFI, 0.10). The estimates support the notion that larger frame animals are heavier, leaner and later maturing, and less feed efficient. The new frame score may be a useful tool for genetic selection of animals that are best suited to their environment.

166 Livestock Resiliency: Concepts and Approaches

Abstract Genetic improvement of health, welfare, efficiency, and fertility traits is challenging due to expensive and fuzzy phenotypes, the polygenic nature of traits, antagonistic genetic correlations to production traits and low heritabilities. Nevertheless, many organizations have introduced large-scale genetic evaluations for such traits in routine selection indexes. Medium and high-density arrays can be applied in genomic selection strategies to improve breeding value accuracy, and also in genome-wide association studies (GWAS) to identify causative mutations responsible for economically important traits. Genomic information is particularly helpful when traits have low heritability. The objective here is to provide a framework for including health, welfare, efficiency, and fertility traits taken from large-scale genetic and genomic analyses and identifying areas of potential improvement in terms of trait definition and performance testing. General tendencies between trait groups confirmed that a number of moderate unfavourable correlations (+/-0.20 or higher) exist between economically important trait complexes and health, welfare, and fertility traits. A number of trait complexes were identified in which “closer-to-biology” phenotypes could provide clear improvements to routine genetic and genomic selection programs. Here we outline development of these phenotypes and describe their collection. While conventional variance component estimation methods have underpinned the genomic component of some traits of economic interest, performance testing for health, welfare, efficiency, and fertility traits remains an elusive goal for breeding programs. Although our results are encouraging, there is much to be done in terms of trait definition and obtaining better measures of physiological parameters for wide-scale application in breeding programs. Close collaboration between veterinarians, physiologists, and geneticists is necessary to attain meaningful advancement in such areas. We would like to acknowledge the support and funding from all national and international partners involved in the RDGP project through the Large Scale Applied Research Project program from Genome Canada

Comparison of different selection traits for identification of phosphorus use efficient lines in mungbean.

Phosphorus (P) is one of the major constraints for crop growth and development, owing to low availability and least mobility in many tropical soil conditions. Categorization of existing germplasm under P deficient conditions is a prerequisite for the selection and development of P efficient genotypes in the mungbean. In the present investigation, 36 diverse genotypes were categorized for phosphorus use efficiency traits using four different techniques for identification of phosphorus use efficient mungbean genotypes. The studied genotypes were categorized for P efficiency based on efficiency, responsiveness, and stress tolerance score of genotypes under normal and low P conditions. The mean values of traits, root dry mass, root to shoot ratio, and P utilization efficiency are significantly higher under low P conditions indicating the high responsiveness of traits to P deficiency. The presence of significant interaction between genotypes and P treatment indicates the evaluated genotypes were significantly affected by P treatment for studied traits. The total P uptake showed significant and positive correlations with root dry mass, shoot dry mass, total dry mass,and P concentration under both P regimes. Out of the four techniques used for the categorization of genotypes for P efficiency, three techniques revealed that the genotype PUSA 1333, followed by Pusa Vishal, PUSA 1031, and Pusa Ratna is efficient. The categorization based on stress tolerance score is the finest way to study variation and for the selection of contrasting genotypes for P efficiency. The identified P efficient genotypes would be valuable resources for genetic enhancement of P use efficiency in mungbean breeding.

PSXII-9 Modeling genetic differences of combined broiler chicken populations in single-step GBLUP

Abstract The objectives of this study were to model the inclusion of a group of external birds into a local broiler chicken population for the purpose of genomic evaluations and evaluating the behavior of two accuracy estimators under different model specifications. The pedigree was composed by 242,413 birds and genotypes were available for 107,216 birds. A five-trait model that included one growth, two yield, and two efficiency traits was used for the analyses. The strategies to model the introduction of external birds were to include a fixed effect representing the origin of parents and to use UPG or metafounders. Genomic estimated breeding values (GEBV) were obtained with single-step GBLUP (ssGBLUP) using the Algorithm for Proven and Young (APY). Bias, dispersion, and accuracy of GEBV for the validation birds, i.e., from the most recent generation, were computed. The bias and dispersion were estimated with the LR-method, whereas accuracy was estimated by the LR-method and predictive ability. Models with fixed UPG and estimated inbreeding or random UPG resulted in similar GEBV. The inclusion of an extra fixed effect in the model made the GEBV unbiased and reduced the inflation, while models without such an effect were significantly biased. Genomic predictions with metafounders were slightly biased and inflated due to the unbalanced number of observations assigned to each metafounder. When combining local and external populations, the greatest accuracy and smallest bias can be obtained by adding an extra fixed effect to account for the origin of parents plus UPG with estimated inbreeding or random UPG. To estimate the accuracy, the LR-method is more consistent among models, whereas predictive ability greatly depends on the model specification, that is, on the fixed effects included in the model. When changing model specification, the largest variation for the LR-method was 20%, while for predictive ability was 110%.

48 Genomic Studies of Feed Efficiency and Component Traits in American Mink

Abstract Feed costs are the largest expense in mink production systems. Therefore, improvement of feed efficiency (FE) is the best way to use limited resources efficiently and increase the mink industry’s sustainability. The objectives of this project are to 1) identify the genetic relationships among different FE measures and their component traits, and 2) discover the genetic architecture of FE and implement genomic selection for FE traits to increase the genetic gain in American mink. Final body weight (FBW), final body length (FBL), daily feed intake (DFI), average daily gain (ADG), feed conversion ratio (FCR), residual feed intake (RFI), residual gain (RG), residual intake and gain (RIG) and Kleiber ratio (KR) traits were measured based on the phenotypic records on 1,088 American mink from the Canadian Center for Fur Animal Research (Nova Scotia, Canada). Univariate models were applied to test the significance of sex, color type, age, and nested Row(Year) as fixed effects and random maternal effect. Genetic parameters were estimated via bivariate models using ASReml-R 4. Estimated heritabilities (±SE) were 0.38±0.10, 0.36±0.10, 0.25±0.10, 0.34±0.09, 0.38±0.08, 0.37±0.07, 0.29±0.10, 0.32±0.10 and 0.34±0.10 for FBW, FBL, DFI, ADG, FCR, RFI, RG, RIG and KR, respectively. RFI showed non-significant (P &amp;gt;0.05) genetic correlations with component traits such as FBW (0.00±0.17) and FBL (0.30±0.16) but significant (P &amp;lt; 0.05) high genetic correlation with DFI (0.74±0.09), indicating that selection based on RFI will reduce the feed intake without any negative effects on the size and growth. The estimated genetic parameters for FE traits suggested the possibility to implement genetic/genomic selection to improve the FE in American mink. Consequently, the ongoing project on genetic mapping and genomic selection will enhance the knowledge of FE and improve the efficacy of selection for more feed-efficient mink.

PSXV-24 Effects of dietary beet pulp on growth performance, beef quality, rumen fermentation characteristics, and blood parameters in Korean cattle steers

Abstract We investigated the effects of feeding beet pulp (BP) instead of corn flake (CF) on growth performance, beef quality, ruminal fermentation, and blood parameters in Korean cattle steers. Eighteen Korean cattle steers (body weight, 732 ± 12.6 kg; age, 31.2 ± 0.16 months) were divided into the CF and BP groups. The approximately 92% of dry matter of the requirement was offered as a concentrate portion, and the 8% was offered as an oat straw. The 85% of concentrate portion was provided by the pelleted basal concentrate, and the remaining 15% with CF or BP for 12 weeks. Average daily gain, feed efficiency, and carcass traits were not affected by feeding BP. The proportion of ruminal iso-butyrate (P = 0.004), iso-valerate (P = 0.001), and valerate (P = 0.01) were lower in the BP group compared to the CF group. Blood glucose (P = 0.06) and non-esterified fatty acids (P = 0.09) concentrations tended to be higher in the BP group than in the CF group. The results suggest that BP could be a good energy source without affecting the growth performance and beef quality in Korean cattle steers.

168 Use of Genomic Tools to Improve Production Efficiency, Health Resilience and Carbon Footprint of Beef Production

Abstract The aim is to present validation studies that demonstrate the benefits of genomic retained heterozygosity, genomic enhanced expected progeny differences (gEPDs) for feed efficiency and carcass traits, as well as DNA pooling technologies, to the beef industry. Team members of Livestock Gentec are global leaders in beef genomics research as evidenced by their leadership roles on the Canadian Cattle Genome Project, 1,000 Bull Genomes Project, gEPDs for Commercial Cattle Project and the Functional Annotation of ANimal Genomes initiative. These large-scale projects have created databases of 380 whole bovine sequence genomes, &amp;gt;24,000 cattle genotypes imputed to sequence variants using Run 6 genotypes from 1000 Bull Genomes project, and &amp;gt;20,000 cattle with associated phenotypes for feed efficiency, carcass quality, cow fertility and methane emissions. The use of admixture analysis, genome wide association studies, and genomic prediction have resulted in new genomic tools that aid in mate selection, improve herd heterosis, female fertility, lifetime productivity and health resilience, and improve accuracy (acc. &amp;gt;0.36) of gEPDs for 18 traits in crossbred cattle. Genomic retained heterozygosity has a benefit of $161/female over five parities while decreasing morbidity of calves and improving the carbon intensity of beef production. Multi-trait selection studies using gEPDs for residual feed intake (acc. &amp;gt; 0.35) have demonstrated annual rates of genetic progress of 0.7%. Validation studies have reported that sires with superior gEPDs for increased marbling, decreased grade fat, increased ribeye and increased carcass weight (acc. &amp;gt; 0.45) produced progeny with improved AAA retail cut yield (59.9 vs 56.7%). DNA pooling shows potential for cheaper genotyping while providing information on pooled records related to sire contribution, heterosis and performance as influenced by genetics. The application of these genomic tools has potential to improve calf crop percentage, health resilience, and retail cut yield while decreasing the carbon footprint of beef production.

PSVI-20 Extent of genetic variation in feeding behavior and genetic associations with performance and feed efficiency in crossbred growing cattle

Abstract To the best of our knowledge, the genetic variability in feeding behavior, as well as relationships with performance and feed efficiency, has not been investigated in a cattle population of greater than 1,500 animals. Our objective was to quantify the genetic parameters of several feeding behavior traits, and their genetic associations with both performance and feed efficiency traits, in crossbred growing cattle. Feed intake and live-weight data were available on 6,088 bulls, steers and heifers; of these, 4,672 cattle had backfat and muscle ultrasound data, and 1,548 steers and heifers had feeding behavior data. Genetic (co)variance parameters were estimated using animal linear mixed models; fixed effects included test group, heterosis, recombination loss, dam parity, age in months at the end of test, and the two-way interaction between age in months at the end of test and sex. Heritability was estimated to be 0.51 (0.097), 0.61 (0.100), 0.44 (0.093), 0.48 (0.094), and 0.47 (0.095) for feed events per day, feeding time per day, feeding rate, feed event duration, and energy intake per feed event, respectively. Coefficients of genetic variation ranged from 0.11 (feeding time per day) to 0.22 (feed event duration). Genetically heavier cattle with a higher energy intake per day, and faster growth rate, had a faster feeding rate and a greater energy intake per feed event. Genetic correlations between feeding behavior and feed efficiency were generally not different from zero, however, there was a genetic correlation of 0.36 (0.11) between feeding time per day and residual energy intake. Significant heritable and exploitable genetic variation exists in several feeding behavior traits in crossbred growing cattle which are also correlated with several performance traits. As some feeding behavior traits may be relatively less resource intensive to measure, they could be useful as predictor traits in beef cattle genetic evaluations.

44 Accuracy of Genomic Predictions over Time in Broilers

Abstract The objectives of this research were to investigate trends for accuracy of genomic predictions over time in a broiler population accumulating data, and to test if data from distant generations are useful in maintaining the accuracy of genomic predictions in selection candidates. The data contained 820k phenotypes for a growth trait (GROW), 200k for two feed efficiency traits (FE1 and FE2), and 42k for a dissection trait (DT). The pedigree included 1.2M animals across 7 years, over 100k from the last 4 years were genotyped. Accuracy was calculated by the linear regression method. Before genotypes became available for training populations, accuracy was nearly stable despite the accumulation of phenotypes and pedigrees. When the first year of genomic data was included in the training population, accuracy increased 56, 77, 39, and 111% for GROW, FE1, FE2, and DT, respectively. With genomic information, the accuracies increased every year except the last one, when they declined for GROW and FE2. The decay of accuracy over time was evaluated in progeny, grand-progeny, and great-grand-progeny of training populations. Without genotypes, the average decline in accuracy across traits was 41% from progeny to grand-progeny, and 19% from grand-progeny to great-grand-progeny. Whit genotypes, the average decline across traits was 14% from progeny to grand-progeny, and 2% from grand-progeny to great-grand-progeny. The accuracies in the last 3 generations were the same when the training population included 5 or 2 years of data, and a marginal decrease was observed when the training population included only 1 year of data. Training sets including genomic information provided an increased accuracy and persistence of genomic predictions compared to training sets without genomic data. The two most recent years of data were enough to maintain the accuracy of predictions in selection candidates.

PSX-B-19 Behaviour of cows while being tested for methane emissions using the greenfeed system

Abstract Increased focus on sustainability is driving a need for environmental efficiency traits in dairy cattle breeding. Breeding for reduced emission of methane, an inevitable product of fermentation in ruminants, is increasingly being explored. Methods to measure methane emissions vary but can be impacted by cow behaviour. As part of an on-going project to develop genomic tools for breeding resilient dairy cows, we explored changes in cow behaviour over time during methane emission measurements. First lactation heifers (n = 49) were tested in tie-stall housing at a research herd in Ontario, Canada. Animals were tested over 5 consecutive days at 08:00h, 12:00h, and 16:00h each day for a 10-min period using the GreenFeed system (C-Lock Inc., Rapid City, SD, USA). The frequency of movement (body shifts and leg lifts) and the number of seconds the cow removed her head from the machine were recorded. The effect of day on the average frequency of movements or time the cow’s head was outside of the machine was assessed using a repeated measures model. In general, cows moved their legs the most on day 1 of testing (76 ± 5.0 movements per 10 min), after which it numerically decreased (e.g., day 5: 68 ± 5.0 movements per 10 min, P = 0.1110). A similar effect was observed for seconds the cow had her head out of the machine (P = 0.0650). Cows spent an average of 39 ± 5.7 sec with their head outside of the machine on day 1 versus 25 ± 3.6 sec on day 5 (P = 0.0499). These preliminary results suggest that cows adapt to the testing conditions; however, changes in their behaviour were minor and do not intervene with recording of methane emissions using the GreenFeed system.

PSXIII-29 Late-Breaking: Relationships between feed efficiency traits, gas emissions, and calculated heat production and respiratory quotients in mature beef cows

Abstract This research evaluated relationships between feed efficiency measurements including residual feed intake (RFI), gain to feed ratio (G:F) and enteric gas production of methane (CH4), carbon dioxide (CO2), oxygen, (O2) along with calculated respiratory quotient (RQ) and heat production (HP) of mature beef cows. Sixty pregnant multiparous Angus beef cows were measured for individual intake for 10 weeks leading up to parturition. Cows were individually fed using the Insentec feeding system to measure individual feed intake. Pens of cows were rotated weekly to the C-Lock Greenfeed trailer (C-Lock Inc.) to measure gas production for a minimum 2 periods per group. Cows were weighed, body condition scored, and ultrasound performed for rib and rump fat depth every 28 days and calf birth weight was recorded. Pearson correlations were conducted to determine relationships between gas exchange measurements and feed efficiency measures. The model for RFI included ADG, pregnancy corrected BW, and ultrasound measures of rib and rump fat (R2= 0.32). Methane emissions were 263±40.3 g CH4/d in dry lot, and daily enteric CH4 emissions per kg of pregnancy corrected body weight ranging from 0.26 to 0.53 g CH4/kg pcBW. Pearson correlations found positive correlations between DMI and CH4 and CO2 (P ≤ 0.001). Pregnancy corrected BW was also positively correlated with total O2 consumption and calculated HP (P ≤ 0.001) and negatively correlated with RQ (P = 0.04). However, RFI and feed conversion ratio were not significantly correlated with gas measurements, or calculated HP or RQ (P ≥ 0.1), although DMI/kg of BW tended (P = 0.098) to be negatively correlated with O2 consumption. In conclusion, accurately identifying feed efficiency in mature beef cows continues to be a challenge. However, the inclusion of gas exchange measures and calorimetry measurements may be able to better assess metabolic efficiency in mature beef cattle.

The value of gut microbiota to predict feed efficiency and growth of rabbits under different feeding regimes

Gut microbiota plays an important role in nutrient absorption and could impact rabbit feed efficiency. This study aims at investigating such impact by evaluating the value added by microbial information for predicting individual growth and cage phenotypes related to feed efficiency. The dataset comprised individual average daily gain and cage-average daily feed intake from 425 meat rabbits, in which cecal microbiota was assessed, and their cage mates. Despite microbiota was not measured in all animals, consideration of pedigree relationships with mixed models allowed the study of cage-average traits. The inclusion of microbial information into certain mixed models increased their predictive ability up to 20% and 46% for cage-average feed efficiency and individual growth traits, respectively. These gains were associated with large microbiability estimates and with reductions in the heritability estimates. However, large microbiabililty estimates were also obtained with certain models but without any improvement in their predictive ability. A large proportion of OTUs seems to be responsible for the prediction improvement in growth and feed efficiency traits, although specific OTUs taxonomically assigned to 5 different phyla have a higher weight. Rabbit growth and feed efficiency are influenced by host cecal microbiota, thus considering microbial information in models improves the prediction of these complex phenotypes.

Genomic Selection and Genome-wide Association Study for Feed-Efficiency Traits in a Farmed Nile Tilapia (Oreochromis niloticus) Population.

Nile tilapia is a key aquaculture species with one of the highest production volumes globally. Genetic improvement of feed efficiency via selective breeding is an important goal, and genomic selection may expedite this process. The aims of this study were to 1) dissect the genetic architecture of feed-efficiency traits in a Nile tilapia breeding population, 2) map the genomic regions associated with these traits and identify candidate genes, 3) evaluate the accuracy of breeding value prediction using genomic data, and 4) assess the impact of the genetic marker density on genomic prediction accuracies. Using an experimental video recording trial, feed conversion ratio (FCR), body weight gain (BWG), residual feed intake (RFI) and feed intake (FI) traits were recorded in 40 full-sibling families from the GIFT (Genetically Improved Farmed Tilapia) Nile tilapia breeding population. Fish were genotyped with a ThermoFisher Axiom 65 K Nile tilapia SNP array. Significant heritabilities, ranging from 0.12 to 0.22, were estimated for all the assessed traits using the genomic relationship matrix. A negative but favourable genetic correlation was found between BWG and the feed-efficiency related traits; −0.60 and −0.63 for FCR and RFI, respectively. While the genome-wide association analyses suggested a polygenic genetic architecture for all the measured traits, there were significant QTL identified for BWG and FI on chromosomes seven and five respectively. Candidate genes previously found to be associated with feed-efficiency traits were located in these QTL regions, including ntrk3a, ghrh and eif4e3. The accuracy of breeding value prediction using the genomic data was up to 34% higher than using pedigree records. A SNP density of approximately 5,000 SNPs was sufficient to achieve similar prediction accuracy as the full genotype data set. Our results highlight the potential of genomic selection to improve feed efficiency traits in Nile tilapia breeding programmes.