Detailed genetic analysis of feeding behaviour in Romane lambs and links with residual feed intake

Genetic parameters of feeding behaviour traits in ducks bred for foie gras production

The mule duck accounts for over 90% of French foie gras production, a sector where feed represents two-thirds of production costs. This study focuses on analysing the feeding behaviours of the mule duck and its parental populations (Pekin and Muscovy) using automated feeders. To assess feed efficiency, feed conversion ratio and residual feed intake were analysed, along with six traits derived at the daily and meal levels. Genetic parameters were estimated separately in purebred populations, as well as with a joint crossbred model that estimated the parental contributions to the hybrid crossbred performances. In relation to higher feed intakes and much-reduced feeding times (P < 0.001), the feeding rate in the Pekin population was twice as high as in the Muscovy population (19 g/min vs 9 g/min), while the mule duck exhibited a large heterosis for this trait (29 g/min). Feeding traits exhibited moderate (0.38 ± 0.11) to high (0.65 ± 0.11) heritabilities. Similar correlation patterns were observed between feeding traits in the two parental populations. In the Pekin line, the feed conversion ratio did not significantly correlate with feeding traits except for daily feed intake. However, in the Muscovy population, it was negatively correlated with the number of meals (-0.51 ± 0.21) and positively with meal feed intake and meal duration (+0.79 ± 0.17 and + 0.71 ± 0.26, respectively). The contributions of the two parental species to the hybrid's performance differed, with the Pekin contributing more to feeding and meat traits compared to the Muscovy. They were similar only for liver weight. Additionally, unfavourable correlations between meat traits and liver traits were estimated in both pathways. Genetic relationships between feeding traits and slaughter traits varied by parental origin, suggesting different strategies for improving hybrid performance in the two parental species. However, in both pathways, genetic correlations between feed conversion ratio and meat traits (breast muscle and thigh weights) were favourable (<-0.42 ± 0.18), whereas they were unfavourable (>0.41 ± 0.20) for fatty liver weight. Altogether, improving liver traits and feed efficiency in the hybrid through selection in the parental populations could be enhanced by considering feeding traits recorded with electronic feeders, provided that adverse correlations are properly accounted for in a multitrait index.

Performance, feed efficiency, feeding behavior, and cortisol concentration of lambs ranked for Residual Feed Intake and Residual Intake and Gain

This study aimed to evaluate the performance, feed efficiency, feeding behavior, and cortisol concentrations of lambs ranked into different groups of Residual Feed Intake (RFI) and Residual Intake and Gain (RIG). Forty Santa Inês lambs with a mean initial age of 120 ± 30 days and mean initial (IBW) and final body weight (FBW) of 28.9 ± 3.2 and 43.7 ± 3.9 kg, respectively, were used. The animals were fed at an automatic feed and water station (Intergado®) for 60 days and classified at the end of the experiment as low-RFI/RIG, medium-RFI/RIG, and high-RFI/RIG according to RFI and RIG. Performance, feed efficiency measures, ingestive behavior, temperament, and cortisol concentrations were measured, and Pearson's correlation analysis was performed to evaluate the relationship between the variables studied. The variables that differed most between RFI groups were dry matter intake, feed conversion, and feed efficiency, with better values in efficient animals (RFI-). Regarding the RGI groups, the average daily gain of animals classified as RIG- was 19.37% lower than that of animals classified as RIG± and 39.28% lower than that of animals classified as RIG+. Only the hourly feeding rate per day (p = 0.04) differed significantly between RFI and RIG classes, while no differences were observed for the ingestive behavior variables or cortisol. The number of visits to the feed bunk (total, with or without intake) showed no correlation with any performance or efficiency measure. Identifying animals ranked into different RFI and RIG classes shows that more efficient animals have a lower feed intake for the same weight gain and spend less time at the feed bunk.

Eating Time as a Genetic Indicator of Methane Emissions and Feed Efficiency in Australian Maternal Composite Sheep

Previous studies have shown reduced enteric methane emissions (ME) and residual feed intake (RFI) through the application of genomic selection in ruminants. The objective of this study was to evaluate feeding behaviour traits as genetic indicators for ME and RFI in Australian Maternal Composite ewes using data from an automated feed intake facility. The feeding behaviour traits evaluated were the amount of time spent eating per day (eating time; ETD; min/day) and per visit (eating time per event; ETE; min/event), daily number of events (DNE), event feed intake (EFI; g/event) and eating rate (ER; g/min). Genotypes and phenotypes of 445 ewes at three different ages (post-weaning, hogget, and adult) were used to estimate the heritability of ME, RFI, and the feeding behaviour traits using univariate genomic best linear unbiased prediction models. Multivariate models were used to estimate the correlations between these traits and within each trait at different ages. The response to selection was evaluated for ME and RFI with direct selection models and indirect models with ETE as an indicator trait, as this behaviour trait was a promising indicator based on heritability and genetic correlations. Heritabilities were between 0.12 and 0.18 for ME and RFI, and between 0.29 and 0.47 for the eating behaviour traits. In our data, selecting for more efficient animals (low RFI) would lead to higher methane emissions per day and per kg of dry matter intake. Selecting for more ETE also improves feed efficiency but results in more methane per day and per kg dry matter intake. Based on our results, ETE could be evaluated as an indicator trait for ME and RFI under an index approach that allows simultaneous selection for improvement in emissions and feed efficiency. Selecting for ETE may have a tremendous impact on the industry, as it may be easier and cheaper to obtain than feed intake and ME data. As the data were collected using individual feeding units, the findings on this research should be validated under grazing conditions.

Quality of breeding value predictions from longitudinal analyses, with application to residual feed intake in pigs

Background

An important goal in animal breeding is to improve longitudinal traits. The objective of this study was to explore for longitudinal residual feed intake (RFI) data, which estimated breeding value (EBV), or combination of EBV, to use in a breeding program. Linear combinations of EBV (summarized breeding values, SBV) or phenotypes (summarized phenotypes) derived from the eigenvectors of the genetic covariance matrix over time were considered, and the linear regression method (LR method) was used to facilitate the evaluation of their prediction accuracy.

Results

Weekly feed intake, average daily gain, metabolic body weight, and backfat thickness measured on 2435 growing French Large White pigs over a 10-week period were analysed using a random regression model. In this population, the 544 dams of the phenotyped animals were genotyped. These dams did not have own phenotypes. The quality of the predictions of SBV and breeding values from summarized phenotypes of these females was evaluated. On average, predictions of SBV at the time of selection were unbiased, slightly over-dispersed and less accurate than those obtained with additional phenotypic information. The use of genomic information did not improve the quality of predictions. The use of summarized instead of longitudinal phenotypes resulted in predictions of breeding values of similar quality.

Conclusions

For practical selection on longitudinal data, the results obtained with this specific design suggest that the use of summarized phenotypes could facilitate routine genetic evaluation of longitudinal traits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-022-00722-w.

Evaluation of the Links between Lamb Feed Efficiency and Rumen and Plasma Metabolomic Data

Feed efficiency is one of the keystones that could help make animal production less costly and more environmentally friendly. Residual feed intake (RFI) is a widely used criterion to measure feed efficiency by regressing intake on the main energy sinks. We investigated rumen and plasma metabolomic data on Romane male lambs that had been genetically selected for either feed efficiency (line rfi−) or inefficiency (line rfi+). These investigations were conducted both during the growth phase under a 100% concentrate diet and later on under a mixed diet to identify differential metabolite expression and to link it to biological phenomena that could explain differences in feed efficiency. Nuclear magnetic resonance (NMR) data were analyzed using partial least squares discriminant analysis (PLS-DA), and correlations between metabolites’ relative concentrations were estimated to identify relationships between them. High levels of plasma citrate and malate were associated with genetically efficient animals, while high levels of amino acids such as L-threonine, L-serine, and L-leucine as well as beta-hydroxyisovalerate were associated with genetically inefficient animals under both diets. The two divergent lines could not be discriminated using rumen metabolites. Based on phenotypic residual feed intake (RFI), efficient and inefficient animals were discriminated using plasma metabolites determined under a 100% concentrate diet, but no discrimination was observed with plasma metabolites under a mixed diet or with rumen metabolites regardless of diet. Plasma amino acids, citrate, and malate were the most discriminant metabolites, suggesting that protein turnover and the mitochondrial production of energy could be the main phenomena that differ between efficient and inefficient Romane lambs.

Characterization of grazing behaviour microstructure using point-of-view cameras

Grazing patterns, intake structure, and diet selection are dynamic responses to animals' feeding environment. This study uses video sequences from animal-borne cameras to capture time- and scale-dependent grazing behaviour variables related to sward explanatory conditions. We observed grazing 'through' the sheep's eyes using point-of-view (POV) cameras coupled with event logging software. Time-specific sward features were measured by sampling 'really' grazed patches identified by applying a global navigation satellite system (GNSS) precision-grazing approach. Sward variables on a Mediterranean native sward were measured for two years during the active spring plant-growth cycle. Overall, the results demonstrate that POV cameras were able to capture grazing behaviour fine-tuning to changes in sward characteristics. Sheep compensate for the decrease in sward quantity and nutritive value by increasing the size and duration at each behavioural scale (i.e., meal, bout, and station) while increasing the bout rate and decreasing the station rate. Diet composition also changed as sward matured. The proportion of forbs in the diet remained high in early and late spring, and forbs and legumes were preferred to grasses in early spring. Grazing selectivity was more pronounced in late spring, with sheep favouring the middle stratum of the sward's vertical structure, preferring green vegetative material, while enlarging the feeding niches' span and spending more time at each niche, consequently reducing the station rate. Although data collected by individual animal-borne POV cameras were representative of the flock behaviour, they may underestimate the total grazing time outside major meals. The results indicate that the use of animal-borne video cameras is suitable for assessing variations in sheep grazing behaviour patterns in complex swards.

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.

New residual feed intake criterion for longitudinal data

Background

Residual feed intake (RFI) is one measure of feed efficiency, which is usually obtained by multiple regression of feed intake (FI) on measures of production, body weight gain and tissue composition. If phenotypic regression is used, the resulting RFI is generally not genetically independent of production traits, whereas if RFI is computed using genetic regression coefficients, RFI and production traits are independent at the genetic level. The corresponding regression coefficients can be easily derived from the result of a multiple trait model that includes FI and production traits. However, this approach is difficult to apply in the case of multiple repeated measurements of FI and production traits. To overcome this difficulty, we used a structured antedependence approach to account for the longitudinality of the data with a phenotypic regression model or with different genetic and environmental regression coefficients [multi- structured antedependence model (SAD) regression model].

Results

After demonstrating the properties of RFI obtained by the multi-SAD regression model, we applied the two models to FI and production traits that were recorded for 2435 French Large White pigs over a 10-week period. Heritability estimates were moderate with both models. With the multi-SAD regression model, heritability estimates were quite stable over time, ranging from 0.14 ± 0.04 to 0.16 ± 0.05, while heritability estimates showed a U-shaped profile with the phenotypic regression model (ranging from 0.19 ± 0.06 to 0.28 ± 0.06). Estimates of genetic correlations between RFI at different time points followed the same pattern for the two models but higher estimates were obtained with the phenotypic regression model. Estimates of breeding values that can be used for selection were obtained by eigen-decomposition of the genetic covariance matrix. Correlations between these estimated breeding values obtained with the two models ranged from 0.66 to 0.83.

Conclusions

The multi-SAD model is preferred for the genetic analysis of longitudinal RFI because, compared to the phenotypic regression model, it provides RFI that are genetically independent of production traits at all time points. Furthermore, it can be applied even when production records are missing at certain time points.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00641-2.

Detection of unrecorded environmental challenges in high-frequency recorded traits, and genetic determinism of resilience to challenge, with an application on feed intake in lambs

BACKGROUND

Resilient animals can remain productive under different environmental conditions. Rearing in increasingly heterogeneous environmental conditions increases the need of selecting resilient animals. Detection of environmental challenges that affect an entire population can provide a unique opportunity to select animals that are more resilient to these events. The objective of this study was two-fold: (1) to present a simple and practical data-driven approach to estimate the probability that, at a given date, an unrecorded environmental challenge occurred; and (2) to evaluate the genetic determinism of resilience to such events.

METHODS

Our method consists of inferring the existence of highly variable days (indicator of environmental challenges) via mixture models applied to frequently recorded phenotypic measures and then using the inferred probabilities of the occurrence of an environmental challenge in a reaction norm model to evaluate the genetic determinism of resilience to these events. These probabilities are estimated for each day (or other time frame). We illustrate the method by using an ovine dataset with daily feed intake (DFI) records.

RESULTS

Using the proposed method, we estimated the probability of the occurrence of an unrecorded environmental challenge, which proved to be informative and useful for inclusion as a covariate in a reaction norm animal model. We estimated the breeding values for sensitivity of the genetic potential for DFI of animals to environmental challenges. The level and slope of the reaction norm were negatively correlated (- 0.46 ± 0.21).

CONCLUSIONS

Our method is promising and appears to be viable to identify unrecorded events of environmental challenges, which is useful when selecting resilient animals and only productive data are available. It can be generalized to a wide variety of phenotypic records from different species and used with large datasets. The negative correlation between level and slope indicates that a hypothetical selection for increased DFI may not be optimal depending on the presence or absence of stress. We observed a reranking of individuals along the environmental gradient and low genetic correlations between extreme environmental conditions. These results confirm the existence of a G [Formula: see text] E interaction and show that the best animals in one environmental condition are not the best in another one.

Candidate serum metabolite biomarkers of residual feed intake and carcass merit in sheep

Mutton and lamb sales continue to grow globally at a rate of 5% per year. However, sheep farming struggles with low profit margins due to high feed costs and modest carcass yields. Selecting those sheep expected to convert feed efficiently and have high carcass merit, as early as possible in their life cycle, could significantly improve the profitability of sheep farming. Unfortunately, direct measurement of feed conversion efficiency (via residual feed intake [RFI]) and carcass merit is a labor-intensive and expensive procedure. Thus, indirect, marker-assisted evaluation of these traits has been explored as a means of reducing the cost of its direct measurement. One promising and potentially inexpensive route to discover biomarkers of RFI and/or carcass merit is metabolomics. Using quantitative metabolomics, we profiled the blood serum metabolome (i.e., the sum of all measurable metabolites) associated with sheep RFI and carcass merit and identified candidate biomarkers of these traits. The study included 165 crossbred ram-lambs that underwent direct measurement of feed consumption to determine their RFI classification (i.e., low vs. high) using the GrowSafe System over a period 40 d. Carcass merit was evaluated after slaughter using standardized methods. Prior to being sent to slaughter, one blood sample was drawn from each animal, and serum prepared and frozen at -80 °C to limit metabolite degradation. A subset of the serum samples was selected based on divergent RFI and carcass quality for further metabolomic analyses. The analyses were conducted using three analytical methods (nuclear magnetic resonance spectroscopy, liquid chromatography mass spectrometry, and inductively coupled mass spectrometry), which permitted the identification and quantification of 161 unique metabolites. Biomarker analyses identified three significant (P < 0.05) candidate biomarkers of sheep RFI (AUC = 0.80), seven candidate biomarkers of carcass yield grade (AUC = 0.77), and one candidate biomarker of carcass muscle-to-bone ratio (AUC = 0.74). The identified biomarkers appear to have roles in regulating energy metabolism and protein synthesis. These results suggest that serum metabolites could be used to categorize and predict sheep for their RFI and carcass merit. Further validation using a larger (3×) and more diverse cohort of sheep is required to confirm these findings.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding

Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.

Genetic parameters estimates for ewes' behavioural reactivity towards their litter after lambing

In livestock, improving maternal reactivity towards the litter is an important issue in breeding strategies to promote production and animal welfare. As of yet, no studies have investigated the within-breed genetic variation of maternal reactivity in sheep. The objective of this study was to estimate the genetic parameters of maternal reactivity traits. A total of 1,095 primiparous and 1,441 multiparous Romane ewes were phenotyped 24 hr postlambing using a behavioural test (arena test, AT) over a 10-year experimental period. The test consisted of three successive phases evaluating the ewe's attraction to her litter, reactivity to separation from her litter, and reactivity to a conflict between attraction to her litter and avoidance of a motionless human. The ewes were reared exclusively on rangelands (South of France) and lambed outdoors in the spring. High-pitched bleating and low-pitched bleating in the AT were mostly highly heritable (0.39-0.46). Heritabilities were moderate for proximity to the litter in the presence of a human (0.27) and low for locomotion and vigilance in the AT (0.09-0.15). The measurements of a given behaviour in the three phases of the AT were highly genetically correlated. Few genetic correlations were found between the different behavioural traits in the AT, the highest correlations being between high-pitched bleating and low-pitched bleating (-0.43 to -0.77). In conclusion, our findings demonstrate moderate-to-high heritability for maternal reactivity traits. These traits could be included in genetic selection schemes to enhance maternal attachment provided there is no unfavourable link with other production traits.

Genetic parameters for feed efficiency in Romane rams and responses to single-generation selection

Feeding costs represent one of the highest expenditures in animal production systems. Breeding efficient animals that express their growth potential while eating less is therefore a major objective for breeders. We estimated the genetic parameters for feed intake, feed efficiency traits (residual feed intake (RFI) and feed conversion ratio (FCR)), growth and body composition traits in the Romane meat sheep breed. In these traits, selection responses to single-generation divergent selection on RFI were evaluated. From 2009 to 2016, a total of 951 male lambs were tested for 8 weeks starting from 3 months of age. They were weighed at the beginning and at the end of the testing period. Backfat thickness and muscle depth were recorded at the end of the testing period through ultrasound measurements. Feed intake was continuously recorded over the testing period using the automatic concentrate feeders. The heritability of RFI was estimated at 0.45 ± 0.08, which was higher than the heritability of FCR (0.30 ± 0.08). No significant genetic correlations were observed between RFI and growth traits. A favourable low negative genetic correlation was estimated between RFI and muscle depth (-0.30 ± 0.15), though additional data are needed to confirm these results. The selection of low RFI sires based on their breeding values led to the production of lambs eating significantly less concentrate (3% decrease in the average daily feed intake), but with the same growth as lambs from sires selected based on high RFI breeding values. We concluded that in meat sheep, RFI is a heritable trait that is genetically independent of post-weaning growth and body composition traits. A one-generation divergent selection based on RFI breeding values highlighted that substantial gains in feeding costs can be expected in selection schemes for meat sheep breeds.