Selection in the presence of a genotype by environment interaction: response in environmental sensitivity

Partner or perish: tree microbiomes and climate change

Understanding the complex relationships between plants, their microbiomes, and environmental changes is crucial for improving growth and survival, especially for long-lived tree species. Trees, like other plants, maintain close associations with a multitude of microorganisms on and within their tissues, forming a 'holobiont'. However, a comprehensive framework for detailed tree-microbiome dynamics, and the implications for climate adaptation, is currently lacking. This review identifies gaps in the existing literature, emphasizing the need for more research to explore the coevolution of the holobiont and the full extent of climate change impact on tree growth and survival. Advancing our knowledge of plant-microbial interactions presents opportunities to enhance tree adaptability and mitigate adverse impacts of climate changes on trees.

Effect of selection for growth rate on the rabbit (Oryctolagus cuniculus) immune system and its response after experimental Staphylococcus aureus infection

The aim of the work was to evaluate if genetic selection for daily gain may affect the immune system. Two experiments were performed. The first one involved 80 rabbit females and their first two litters to explore the effect of selection on the ability of animals to maintain immune competence. Two generations from a line selected for average daily gain (ADG) were evaluated (VR19 generation 19th, n = 43; VR37 generation 37th, n = 37). In females, the effect of selection and its interaction with physiological state were not significant for any trait. In litters, the selection criterion increased the granulocyte to lymphocyte ratio. The second experiment involved 73 19-week-old females (VR19, n = 39; VR37, n = 34) to explore the effect of genetic selection on immune response after S. aureus infection. The VR37 rabbit females had lower counts for total lymphocytes, CD5+, CD4+, CD8+, CD25+, monocytes, the CD4+/CD8+ ratio and platelets than those of VR19 (-14, -21, -25, -15, -33, -18, -11 and -11%, respectively; P < 0.05). VR37 had less erythema (-8.4 percentage points; P < 0.05), fewer nodules (-6.5 percentage points; P < 0.05) and a smaller nodule size (-0.65 cm3 on 7 day post-inoculation; P < 0.05) compared to VR19. Our study suggests that genetic selection for average daily gain does not negatively affect the maintenance of a competent immune system or the ability to establish immune response. It seems that such selection may improve the response to S. aureus infections.

Genotype-by-environment interactions modulate the rate of microevolution in reproductive timing in humans

Evidence from natural populations shows that changes in environmental conditions can cause rapid modifications in the evolutionary potential of phenotypes, partly through genotype-by-environment interactions (G×E). Therefore, the overall rate of microevolution should depend on fluctuations in environmental conditions, even when directional selection is sustained over several generations. We tested this hypothesis in a preindustrial human population that experienced a microevolutionary change in age at first reproduction (AFR) of mothers, using the annual infant mortality rate (IMR) as an indicator of environmental conditions during their early life. Using quantitative genetics analyses, we found that G×Es explained a nonnegligible fraction of the additive genetic variance in AFR and in relative fitness, as well as of the genetic covariance between AFR and fitness (i.e., the Robertson-Price covariance). The covariance was stronger for individuals exposed to unfavorable early-life environmental conditions. Our results unravel the presence of G×Es in an important life history trait and its impact on the rate of microevolution, which appears to have been sensitive to short-term fluctuations in local environmental conditions.

Genomic analysis of the slope of the reaction norm for body weight in Australian sheep

Background

Selection of livestock based on their robustness or sensitivity to environmental variation could help improve the efficiency of production systems, particularly in the light of climate change. Genetic variation in robustness arises from genotype-by-environment (G × E) interactions, with genotypes performing differently when animals are raised in contrasted environments. Understanding the nature of this genetic variation is essential to implement strategies to improve robustness. In this study, our aim was to explore the genetics of robustness in Australian sheep to different growth environments using linear reaction norm models (RNM), with post-weaning weight records of 22,513 lambs and 60 k single nucleotide polymorphisms (SNPs). The use of scale-corrected genomic estimated breeding values (GEBV) for the slope to account for scale-type G × E interactions was also investigated.

Results

Additive genetic variance was observed for the slope of the RNM, with genetic correlations between low- and high-growth environments indicating substantial re-ranking of genotypes (0.44–0.49). The genetic variance increased from low- to high-growth environments. The heritability of post-weaning body weight ranged from 0.28 to 0.39. The genetic correlation between intercept and slope of the reaction norm for post-weaning body weight was low to moderate when based on the estimated (co)variance components but was much higher when based on back-solved SNP effects. An initial analysis suggested that a region on chromosome 11 affected both the intercept and the slope, but when the GEBV for the slope were conditioned on the GEBV for the intercept to remove the effect of scale-type G × E interactions on SNP effects for robustness, a single genomic region on chromosome 7 was found to be associated with robustness. This region included genes previously associated with growth traits and disease susceptibility in livestock.

Conclusions

This study shows a significant genetic variation in the slope of RNM that could be used for selecting for increased robustness of sheep. Both scale-type and rank-type G × E interactions contributed to variation in the slope. The correction for scale effects of GEBV for the slope should be considered when analysing robustness using RNM. Overall, robustness appears to be a highly polygenic trait.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-022-00734-6.

Sustainable Intensification of Beef Production in the Tropics: The Role of Genetically Improving Sexual Precocity of Heifers

Simple Summary

Tropical pasture-based beef production systems play a vital role in global food security. The importance of promoting sustainable intensification of such systems has been debated worldwide. Demand for beef is growing together with concerns over the impact of its production on the environment. Implementing sustainable livestock intensification programs relies on animal genetic improvement. In tropical areas, the lack of sexual precocity is a bottleneck for cattle efficiency, directly impacting the sustainability of production systems. In the present review we present and discuss the state of the art of genetic evaluation for sexual precocity in Bos indicus beef cattle, covering the definition of measurable traits, genetic parameter estimates, genomic analyses, and a case study of selection for sexual precocity in Nellore breeding programs.

Abstract

Increasing productivity through continued animal genetic improvement is a crucial part of implementing sustainable livestock intensification programs. In Zebu cattle, the lack of sexual precocity is one of the main obstacles to improving beef production efficiency. Puberty-related traits are complex, but large-scale data sets from different “omics” have provided information on specific genes and biological processes with major effects on the expression of such traits, which can greatly increase animal genetic evaluation. In addition, genetic parameter estimates and genomic predictions involving sexual precocity indicator traits and productive, reproductive, and feed-efficiency related traits highlighted the feasibility and importance of direct selection for anticipating heifer reproductive life. Indeed, the case study of selection for sexual precocity in Nellore breeding programs presented here show that, in 12 years of selection for female early precocity and improved management practices, the phenotypic means of age at first calving showed a strong decreasing trend, changing from nearly 34 to less than 28 months, with a genetic trend of almost −2 days/year. In this period, the percentage of early pregnancy in the herds changed from around 10% to more than 60%, showing that the genetic improvement of heifer’s sexual precocity allows optimizing the productive cycle by reducing the number of unproductive animals in the herd. It has a direct impact on sustainability by better use of resources. Genomic selection breeding programs accounting for genotype by environment interaction represent promising tools for accelerating genetic progress for sexual precocity in tropical beef cattle.

Accelerating Adaptation of Forest Trees to Climate Change Using Individual Tree Response Functions

In forest tree breeding, assisted migration has been proposed to accelerate the adaptive response to climate change. Response functions are currently fitted across multiple populations and environments, enabling selections of the most appropriate seed sources for a specific reforestation site. So far, the approach has been limited to capturing adaptive variation among populations, neglecting tree-to-tree variation residing within a population. Here, we combined the response function methodology with the in-situ breeding approach, utilizing progeny trials of European larch (Larix decidua) across 21 test sites in Austria ranging from Alpine to lowland regions. We quantified intra-population genetic variance and predicted individual genetic performance along a climatic gradient. This approach can be adopted in most breeding and conservation programs, boosting the speed of adaptation under climate change.

Prospects for sustainability of pig production in relation to climate change and novel feed resources

Pig production systems provide multiple benefits to humans. However, the global increase in meat consumption has profound consequences for our earth. This perspective describes two alternative scenarios for improving the sustainability of future pig production systems. The first scenario is a high input-high output system based on sustainable intensification, maximizing animal protein production efficiency on a limited land surface at the same time as minimizing environmental impacts. The second scenario is a reduced input-reduced output system based on selecting animals that are more robust to climate change and are better adapted to transform low quality feed (local feeds, feedstuff co-products, food waste) into meat. However, in contrast to the first scenario, the latter scenario results in reduced predicted yields, reduced production efficiency and possibly increased costs to the consumer. National evaluation of the availability of local feed and feedstuff co-product alternatives, determination of limits to feed sourced from international markets, available land for crop and livestock production, desired production levels, and a willingness to politically enforce policies through subsidies and/or penalties are some of the considerations to combine these two scenarios. Given future novel sustainable alternatives to livestock animal protein, it may become reasonable to move towards an added general premium price on 'protein from livestock animals' to the benefit of promoting higher incomes to farmers at the same time as covering the extra costs of, politically enforced, welfare of livestock animals in sustainable production systems. © 2020 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer's early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal's sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme-dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment-specific scheme-low EC (-3.0 and -1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28-0.56 for SC and 0.26-0.49 for HP, using RNM_H, and 0.26-0.52 for SC and 0.22-0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (-3.0) and favorable (3.0) EC levels were 0.30 for HP and -0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals' genetic merit and re-ranking of animals on different environmental conditions. SNP marker-environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment-specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates.

Genetics and genomics of uniformity and resilience in livestock and aquaculture species: A review

Genetic control of residual variance offers opportunities to increase uniformity and resilience of livestock and aquaculture species. Improving uniformity and resilience of animals will improve health and welfare of animals and lead to more homogenous products. Our aims in this review were to summarize the current models and methods to study genetic control of residual variance, genetic parameters and genomic results for residual variance and discuss future research directions. Typically, the genetic coefficient of variation is high (median = 0.27; range 0-0.86) and the heritability of residual variance is low (median = 0.01; range 0-0.10). Higher heritabilities can be achieved when increasing the number of records per animal. Divergent selection experiments have supported the feasibility of selecting for high or low residual variance. Genomic studies have revealed associations in regions related to stress, including those from the heat shock protein family. Although the number of studies is growing, genetic control of residual variance is still poorly understood, but big data and genomics offer great opportunities.

Morphological divergence in the West African shorthorn Lagune cattle populations from Benin

This study explored the potential role of agro-ecology in shaping the morphology of Lagune cattle population of Benin. A total of 708 adult Lagune cattle were sampled randomly from nine provenances in two agro-ecological zones (AEZs) and were assessed for eight qualitative and twelve linear body measurements. Data were analyzed using generalized linear model procedures (PROC GLM) followed by the multiple comparison of least square means (LSMEAN) according to the Tukey-Kramer method and multivariate analytical methods, including canonical discrimination analysis (CDA) and hierarchical ascendant classification. Irrespective of AEZ and sex, the body length (102.3 ± 9.31 cm) was greater than the wither height (93.1 ± 7.39 cm) and the body index smaller than 0.85. However, there were significant differences between the two AEZs for most of the measured morphometric and qualitative traits. Moreover, a male-biased sexual size dimorphism was recorded. The CDA based on only four basic body measurements (rump height, body length, heart girth, and ear length) and the calculated Mahalanobis distances suggest that the populations from the two AEZs are distinct and could be further considered ecotypes. Nevertheless, the overall moderate classification rate (70%) of the individual animals into their group of origin indicates interbreeding between the two populations. The pairwise Mahalanobis distances between provenances in the same AEZ were also significant. Together, these results provide supporting evidence for the existence of subdivisions in the Lagune cattle populations from South Benin. The high morphological diversity in the Lagune cattle recorded in the present study could serve as a starting point for the development of efficient selection and sound subpopulation management strategies but also for further phenotypic and genetic characterizations.

Genetic correlation between growth and reproductive performance of beef females depends on environment

In tropical production systems, beef cattle are raised in highly heterogeneous environments. Heterogeneity is, therefore, expected to exist in the (co)variance components for traits of economic interest in different production environments. The main objective of the present study was to estimate genetic correlations between growth traits and reproductive performance of beef females, depending on the environment. The present study was conducted in the tropical region of Brazil, applying a multiple-trait random regression animal model to field records of heifer pregnancy (HP), hip height, bodyweight at ~18 months of age (BW18) and postweaning weight gain (PWG) from 20 893 Nelore females. As evidence of genotype by environment interaction (G × E), heterogeneity of genetic variance across environments was observed mainly for HP, PWG and BW18. Moreover, the estimates of genetic correlation within these traits reached values lower than unity on the environmental gradient. The genetic correlation among growth traits tended to be stronger in favourable environments, a fact that should favour correlated responses under these conditions. In contrast, the genetic correlations between growth traits and HP tended to become weaker and even exhibited little evidence of antagonism in more favourable environments. On the basis of these findings, selection for higher growth in extreme favourable environments should result in little or no damage to HP as a correlated response. All these results lead us to believe that the G × E is an important factor to be considered in genetic evaluations of beef cattle raised in tropical environments.

Long-term implications of feed energy source in different genetic types of reproductive rabbit females: III. Fitness and productivity

The specialization process associated with genetic selection could be associated with functional disorders, affecting the reproductive success of females (fitness). We hypothesized that by modulating energy acquisition and allocation of females we could balance productivity and reproductive success. To test this hypothesis, we used 203 rabbit females belonging to three genetic types: H (n=66) maternal line specialized in prolificacy, LP (n=67) generalist maternal line, R (n=70) paternal line specialized in growth rate. We fed each genetic type with two diets specifically designed to promote milk yield (AF) or body reserves recovery (CS). We controlled females between their first and fifth reproductive cycles, recording traits related with productivity and fitness of females. H females fed CS had on average 11.2±0.43 kits with an individual weight of 54±1.2 g at birth and 525±11 g at weaning. Their conception rate when multiparous was 44% and their survival rate at the end of the experiment 30%. When they were fed AF, the individual weight of kits was 3.8 g heavier (P<0.05) at birth and 38 g heavier at weaning (P<0.05), the conception rate when multiparous increased 23 percentage points (P<0.05) and the survival rate at the end of the experiment 25 percentage points (P<0.05). LP females fed CS had on average 10.8±0.43 kits with an individual weight of 52±1.2 g at birth and 578±11 g at weaning. Their conception rate when multiparous was 79% and their survival rate at the end of the experiment 75%. When they were fed AF, it only increased individual weight of kits at weaning (+39 g; P<0.05). R females fed CS had on average 8.4±0.43 kits with an individual weight of 60±1.2 g at birth and 568±11 g at weaning. Their conception rate when multiparous was 60% and their survival rate at the end of the experiment 37%. When they were fed AF, they presented 1.4 kits less at birth (P<0.05) but heavier at birth (+4.9 g; P<0.05) and at weaning (+37 g; P<0.05). Therefore, we observed that genetic types prioritized different fitness components and that diets could affected them. In this sense, seems that more specialized genetic types, were more sensitive to diets than the more generalist type.

Interactions between sire family and production environment (temperate vs. tropical) on performance and thermoregulation responses in growing pigs

The aim of this study was to evaluate the effect of 2 climatic environments (temperate [TEMP] vs. tropical humid [TROP]) on production and thermoregulation traits in growing pigs. A backcross design involving Large White (LW; heat sensitive) and Creole (CR; heat tolerant) pigs was studied. The same 10 F LW × CR boars were mated with related LW sows in each environment. A total of 1,298 backcross pigs ( = 634 pigs from 11 batches for the TEMP environment and = 664 pigs from 12 batches for the TROP environment) were phenotyped on BW (every 15 d from wk 11 to 23 of age), voluntary feed intake (ADFI, from wk 11 to 23), backfat thickness (BFT; at wk 19 and 23), skin temperature (ST; at wk 19 and 23), and rectal temperature (RT; at wk 19, 21, and 23). The feed conversion ratio was computed for the whole test period (11 to 23 wk). The calculation of the temperature-humidity index showed an average difference of 2.4°C between the TEMP and TROP environments. The ADG and ADFI were higher in the TEMP environment than in the TROP environment (834 vs. 754 g/d and 2.20 vs. 1.80 kg/d, respectively; < 0.001). Body temperatures were higher in the TROP environment than in the TEMP environment (35.9 vs. 34.8°C for ST and 39.5 vs. 39.3°C for RT, respectively; < 0.001). Most of the studied traits (i.e., BW, BFT, ADG, ADFI, and RT) were affected by sire family × environment interactions ( < 0.05), resulting in "robust" and "sensitive" families. Our results show a family dependency in the relationships between heat resistance and robustness, suggesting the possibility of finding genotypes with high production and low heat sensitivity. Further research is needed to confirm the genetic × environment interaction and to detect QTL related to heat tolerance.

Effects of Diet and Genetics on Growth Performance of Pigs in Response to Repeated Exposure to Heat Stress

Heat stress (HS) is one of the costliest issues in the U.S. pork industry. Aims of the present study were to determine the consequences of repeated exposure to HS on growth performance, and the effects of a high fiber diet, the genetic potential for high lean tissue accretion, and the genetic potential for residual feed intake (RFI) on resilience to HS. Barrows (n = 97) from three genetic lines (commercial, high RFI, low RFI) where subjected three times to a 4-day HS treatment (HS1, HS2, and HS3) which was preceded by a 9-day neutral (TN) adaptation period (TN1) and alternated by 7-day periods of neutral temperatures (TN2, TN3, and TN4). Body weight gain (BWG), feed intake (FI), feed conversion efficiency (FCE), RFI, and the drop in BWG and FI between TN and HS were estimated for each period, and slaughter traits were measured at the end of TN4. Commercial pigs had lower FI when fed a high fiber diet compared to a regular diet (2.70 ± 0.08 vs. 2.96 ± 0.08 kg/d; P < 0.05), while no differences were found for BWG, RFI or FCE. HS reduced FI, BWG, and FCE, increased RFI, and resulted in leaner pigs that generate smaller carcasses at slaughter. In TN, commercial pigs grew faster than the low and high RFI pigs (1.22 ± 0.06 vs. 0.720 ± 0.05 and 0.657 ± 0.07; P < 0.001) but growth rates were not significantly different between the lines during HS. Growth rates for the low RFI and high RFI pigs were similar both during TN and during HS. Pigs of interest for genetic improvement are those that are able to maintain growth rates during HS. Our results show that response in growth to HS was repeatable over subsequent 4-d HS cycles, which suggests the potential for including this response in the breeding index. The best performing animals during HS are likely those that are not highly superior for growth in TN.

Genotype by environment (climate) interaction improves genomic prediction for production traits in US Holstein cattle

Genotype by environment interaction (G × E) in dairy cattle productive traits has been shown to exist, but current genetic evaluation methods do not take this component into account. As several environmental descriptors (e.g., climate, farming system) are known to vary within the United States, not accounting for the G × E could lead to reranking of bulls and loss in genetic gain. Using test-day records on milk yield, somatic cell score, fat, and protein percentage from all over the United States, we computed within herd-year-season daughter yield deviations for 1,087 Holstein bulls and regressed them on genetic and environmental information to estimate variance components and to assess prediction accuracy. Genomic information was obtained from a 50k SNP marker panel. Environmental effect inputs included herd (160 levels), geographical region (7 levels), geographical location (2 variables), climate information (7 variables), and management conditions of the herds (16 total variables divided in 4 subgroups). For each set of environmental descriptors, environmental, genomic, and G × E components were sequentially fitted. Variance components estimates confirmed the presence of G × E on milk yield, with its effect being larger than main genetic effect and the environmental effect for some models. Conversely, G × E was moderate for somatic cell score and small for milk composition. Genotype by environment interaction, when included, partially eroded the genomic effect (as compared with the models where G × E was not included), suggesting that the genomic variance could at least in part be attributed to G × E not appropriately accounted for. Model predictive ability was assessed using 3 cross-validation schemes (new bulls, incomplete progeny test, and new environmental conditions), and performance was compared with a reference model including only the main genomic effect. In each scenario, at least 1 of the models including G × E was able to perform better than the reference model, although it was not possible to find the overall best-performing model that included the same set of environmental descriptors. In general, the methodology used is promising in accounting for G × E in genomic predictions, but challenges exist in identifying a unique set of covariates capable of describing the entire variety of environments.

Thermal sensitivity of growth indicates heritable variation in 1-year-old rainbow trout (Oncorhynchus mykiss)

BACKGROUND

Rainbow trout is an important aquaculture species, which has a worldwide distribution across various production environments. The diverse locations of trout farms involve remarkable variation in environmental factors such as water temperature, which is of major importance for the performance of fish. Thus, robust fish that could thrive under different and suboptimal thermal conditions is a desirable goal for trout breeding. Using a split-family experimental design (40 full-/half-sib groups) for a rainbow trout population derived from the Finnish national breeding program, we studied how two different rearing temperatures (14 and 20 °C) affect feed intake, growth rate and feed conversion ratio in 1-year-old fish. Furthermore, we quantified the additive genetic (co-)variation for daily growth coefficient (DGC) and its thermal sensitivity (TS), defined as the slope of the growth reaction norm between the two temperatures.

RESULTS

The fish showed consistently lower feed intake, faster growth and better feed conversion ratio at the lower temperature. Heritability of TS of DGC was moderate ([Formula: see text]). The co-heritability parameter derived from selection index theory, which describes the heritable variance of TS, was negative when the intercept was placed at the lower temperature (-0.28). This resulted in moderate accuracy of selection. At the higher temperature, co-heritability of TS was positive (0.20). The genetic correlation between DGC and its TS was strongly negative (-0.64) when the intercept was at the lower temperature and positive (0.38) but not significantly different from zero at the higher temperature.

CONCLUSIONS

The considerable amount of genetic variation in TS of growth indicates a potential for selection response and thus for targeted genetic improvement in TS. The negative genetic correlation between DGC and its TS suggests that selection for high growth rate at the lower temperature will result in more temperature-sensitive fish. Instead, the correlated response of TS is less pronounced if the selection for a higher DGC occurred at the higher temperature. It seems possible to control the correlated genetic change of TS while selecting for fast growth across environments, especially if measurements from both environments are available and breeding values for reaction norm slope are directly included in the selection index.

Genomic Selection Improves Response to Selection in Resilience by Exploiting Genotype by Environment Interactions

Genotype by environment interactions (GxE) are very common in livestock and hamper genetic improvement. On the other hand, GxE is a source of genetic variation: genetic variation in response to environment, e.g., environmental perturbations such as heat stress or disease. In livestock breeding, there is tendency to ignore GxE because of increased complexity of models for genetic evaluations and lack of accuracy in extreme environments. GxE, however, creates opportunities to increase resilience of animals toward environmental perturbations. The main aim of the paper is to investigate to which extent GxE can be exploited with traditional and genomic selection methods. Furthermore, we investigated the benefit of reaction norm (RN) models compared to conventional methods ignoring GxE. The questions were addressed with selection index theory. GxE was modeled according to a linear RN model in which the environmental gradient is the contemporary group mean. Economic values were based on linear and non-linear profit equations. Accuracies of environment-specific (G)EBV were highest in intermediate environments and lowest in extreme environments. RN models had higher accuracies of (G)EBV in extreme environments than conventional models ignoring GxE. Genomic selection always resulted in higher response to selection in all environments than sib or progeny testing schemes. The increase in response was with genomic selection between 9 and 140% compared to sib testing and between 11 and 114% compared to progeny testing when the reference population consisted of 1 million animals across all environments. When the aim was to decrease environmental sensitivity, the response in slope of the RN model with genomic selection was between 1.09 and 319 times larger than with sib or progeny testing and in the right direction in contrast to sib and progeny testing that still increased environmental sensitivity. This shows that genomic selection with large reference populations offers great opportunities to exploit GxE to increase resilience of animals.

Genotype by environment interactions for productivity and resistance to gastro-intestinal nematode parasites in Red Maasai and Dorper sheep

Red Maasai and Dorper sheep were evaluated for their resistance to gastro-intestinal (GI) nematode parasites (predominantly Haemonchus contortus), productivity and productive efficiency (assessed on a metabolizable energy basis) in experiments undertaken at the Kenyan coast (sub-humid environment) and the Kenya highlands (semi-arid environment). In both ewes and lambs there were few significant genotype by environment (G X E) interactions for either resistance (assessed by faecal egg counts-FEC) or resilience (assessed by blood packed red cell volume-PCV) to GI nematodes. Red Maasai sheep were consistently more resistant (low FEC) and more resilient (high PCV) than Dorper sheep. However, there were significant G X £ interactions for ewe reproductive performance and for ewe and lamb mortality rates and live weights. These interactions were due to very poor performance of the Dorper compared to the Red Maasai in the sub-humid coastal environment and to the much improved performance of the Dorper in the semi-arid environment. When these component traits were combined into estimates of flock productivity and productive efficiency there were highly significant GXE interactions with the Red Maasai sheep being considerably more efficient than Dorper sheep in the sub-humid environment, while in the semi-arid environment there was a negligible breed difference in productive efficiency. The results are discussed in terms of breeding strategies for smallholder farmers and pastoralists managing sheep in low-input systems in sub-humid and semi-arid environments.

Genotype by environment interaction and breeding for robustness in livestock

The increasing size of the human population is projected to result in an increase in meat consumption. However, at the same time, the dominant position of meat as the center of meals is on the decline. Modern objections to the consumption of meat include public concerns with animal welfare in livestock production systems. Animal breeding practices have become part of the debate since it became recognized that animals in a population that have been selected for high production efficiency are more at risk for behavioral, physiological and immunological problems. As a solution, animal breeding practices need to include selection for robustness traits, which can be implemented through the use of reaction norms analysis, or though the direct inclusion of robustness traits in the breeding objective and in the selection index. This review gives an overview of genotype × environment interactions (the influence of the environment, reaction norms, phenotypic plasticity, canalization, and genetic homeostasis), reaction norms analysis in livestock production, options for selection for increased levels of production and against environmental sensitivity, and direct inclusion of robustness traits in the selection index. Ethical considerations of breeding for improved animal welfare are discussed. The discussion on animal breeding practices has been initiated and is very alive today. This positive trend is part of the sustainable food production movement that aims at feeding 9.15 billion people not just in the near future but also beyond.

Genetics of Growth Reaction Norms in Farmed Rainbow Trout

Rainbow trout is farmed globally under diverse uncontrollable environments. Fish with low macroenvironmental sensitivity (ES) of growth is important to thrive and grow under these uncontrollable environments. The ES may evolve as a correlated response to selection for growth in one environment when the genetic correlation between ES and growth is nonzero. The aims of this study were to quantify additive genetic variance for ES of body weight (BW), defined as the slope of reaction norm across breeding environment (BE) and production environment (PE), and to estimate the genetic correlation (r_{g(int, sl)}) between BW and ES. To estimate heritable variance of ES, the coheritability of ES was derived using selection index theory. The BW records from 43,040 rainbow trout performing either in freshwater or seawater were analysed using a reaction norm model. High additive genetic variance for ES (9584) was observed, inferring that genetic changes in ES can be expected. The coheritability for ES was either -0.06 (intercept at PE) or -0.08 (intercept at BE), suggesting that BW observation in either PE or BE results in low accuracy of selection for ES. Yet, the r_{g(int, sl)} was negative (-0.41 to -0.33) indicating that selection for BW in one environment is expected to result in more sensitive fish. To avoid an increase of ES while selecting for BW, it is possible to have equal genetic gain in BW in both environments so that ES is maintained stable.

Effects of genotype, environment, and their interactions on honey bee health in Europe

There are several reports of honey bee populations in Europe which survive without treatment for Varroa. However, when evaluated outside their native area, higher survival and resistance traits were not observed in colonies of a survivor population. Varroa infestation is strongly influenced by environmental factors, probably affecting threshold levels on a European scale. In a Europe-wide experiment colonies of local origin survived significantly longer than colonies of non-local origin, clearly indicating the presence of genotype-environment interactions. Transmission by Varroa selects for virulent strains of DWV, but it is currently unknown how these may interact with different genotypes of bees. The distribution of Nosema ceranae is significantly affected by environment, but there is at least one Nosema-resistant population.

Seasonal sensitivity of genotypes in the humid tropics and its application to chicken breeding

Abstract. The study was aimed at elucidating the effect of seasons, namely the early wet (EW), late wet (LW), early dry (ED) and late dry (LD) seasons, on genotype sensitivity, its magnitude and application for selection and management of chickens of Bovan Nera (BN) and ISA Brown (IB) origins. Breeding and hatching records from 1999 to 2008 were collected from CHI (Ajanla) Farms and hatchery records, Ibadan, Nigeria. Cock weight (CW), hen weight (HW), hen-house egg production (HHP), egg weight (EW), fertility of egg set (FES) and pullet day-old chicks (PDC) hatched were examined. ANOVA revealed that there was significant (P < 0.05) genotype × season interaction effect. This interaction was observed between genotypic values when compared between seasons within parameters. Within-season sensitivity parameters indicated that BN was more sensitive than IB in HW and FES for all seasons. In ED and LD seasons, sensitivity values were inconsistent in pattern with output levels of FES, HES and PDC hatched because of interaction between genotypes and seasons. Within the LW season, all sensitivity indices for genotypes were consistent in magnitude with productive and reproductive values. Therefore, a genotype's seasonal sensitivity indices could be utilized for direct antagonistic selection in LW season between genotypes in humid tropics.

Genetic effects of polymorphisms in myogenic regulatory factors on chicken muscle fiber traits

The myogenic regulatory factors is a family of transcription factors that play a key role in the development of skeletal muscle fibers, which are the main factors to affect the meat taste and texture. In the present study, we performed candidate gene analysis to identify single-nucleotide polymorphisms in the MyoD, Myf5, MyoG, and Mrf4 genes using polymerase chain reaction-single strand conformation polymorphism in 360 Erlang Mountain Chickens from three different housing systems (cage, pen, and free-range). The general linear model procedure was used to estimate the statistical significance of association between combined genotypes and muscle fiber traits of chickens. Two polymorphisms (g.39928301T>G and g.11579368C>T) were detected in the Mrf4 and MyoD gene, respectively. The diameters of thigh and pectoralis muscle fibers were higher in birds with the combined genotypes of GG-TT and TT-CT (p<0.05). Moreover, the interaction between housing system and combined genotypes has no significant effect on the traits of muscle fiber (p>0.05). Our findings suggest that the combined genotypes of TT-CT and GG-TT might be advantageous for muscle fiber traits, and could be the potential genetic markers for breeding program in Erlang Mountain Chickens.

Genotype by environment interaction and model comparison for growth traits of Santa Ines sheep

The objectives of the present study were to compare alternative models for the genetic evaluation and assess the importance of genotype by environment interaction (G×E) in the estimation of genetic parameters and genetic evaluation of birth weight (BW), weight at 60 days of age (W60) and weight at 180 days of age (W180) of Santa Ines sheep. Data comprise 7622 BW, 4673 W60 and 2830 W180 records from animals born in 44 Brazilian herds. Four models were used for the analyses: animal model (AM) with homogeneous residual variance (1), or heterogeneous residual variance (2), hierarchical reaction norms model (HRNM) with homogeneous (1) or heterogeneous residual variance (2). The models that best fit the BW, W60 and W180 data were AM2, HRNM1 and HRNM2 respectively. Thus, models for genetic evaluation that consider heterogeneity of variances are recommended to evaluate growth traits of sheep. The correlation between intercept and slope of the HRNM was higher than 0.70 for all traits studied, indicating that animals with higher average breeding values responded better to improvement in environmental conditions, a fact characterizing the scale effect of G×E. Therefore, G×E is an important factor to be considered in the estimation of genetic parameters and genetic evaluation of growth traits of sheep.

Genetics of ascites resistance and tolerance in chicken: a random regression approach

Resistance and tolerance are two complementary mechanisms to reduce the detrimental effects of parasites, pathogens, and production diseases on host performance. Using body weight and ascites data on domesticated chicken Gallus gallus domesticus, we demonstrate the use of random regression animal model and covariance functions to estimate genetic parameters for ascites resistance and tolerance and illustrate the way individual variation in resistance and tolerance induce both genotype re-ranking and changes in variation of host performance along increasing ascites severity. Tolerance to ascites displayed significant genetic variance, with the estimated breeding values of tolerance slope ranging from strongly negative (very sensitive genotype) to weakly negative (less sensitive). Resistance to ascites had heritability of 0.34. Both traits are hence expected to respond to selection. The two complementary defense strategies, tolerance and resistance, were genetically independent. Ascites induced changes to the correlations between ascites resistance and body weight, with the genetic correlations being weak when birds were ascites-free but moderately negative when both healthy and affected birds were present. This likely results because ascites reduces growth, and thus high ascites incidence is genetically related to low adult body weight. Although ascites induced elevated phenotypic and genetic variances in body weight of affected birds, heritability displayed negligible changes across healthy and affected birds. Ascites induced moderate genotype re-ranking in body weight, with the genetic correlation of healthy birds with mildly affected birds being unity but with severely affected birds 0.45. This study demonstrates a novel approach for exploring genetics of defense traits and their impact on genotype-by-environment interactions.

Linear reaction norm models for genetic merit prediction of Angus cattle under genotype by environment interaction

The objectives of this work were to assess alternative linear reaction norm (RN) models for genetic evaluation of Angus cattle in Brazil. That is, we investigated the interaction between genotypes and continuous descriptors of the environmental variation to examine evidence of genotype by environment interaction (G×E) in post-weaning BW gain (PWG) and to compare the environmental sensitivity of national and imported Angus sires. Data were collected by the Brazilian Angus Improvement Program from 1974 to 2005 and consisted of 63,098 records and a pedigree file with 95,896 animals. Six models were implemented using Bayesian inference and compared using the Deviance Information Criterion (DIC). The simplest model was M(1), a traditional animal model, which showed the largest DIC and hence the poorest fit when compared with the 4 alternative RN specifications accounting for G×E. In M(2), a 2-step procedure was implemented using the contemporary group posterior means of M(1) as the environmental gradient, ranging from -92.6 to +265.5 kg. Moreover, the benefits of jointly estimating all parameters in a 1-step approach were demonstrated by M(3). Additionally, we extended M(3) to allow for residual heteroskedasticity using an exponential function (M(4)) and the best fitting (smallest DIC) environmental classification model (M(5)) specification. Finally, M(6) added just heteroskedastic residual variance to M(1). Heritabilities were less at harsh environments and increased with the improvement of production conditions for all RN models. Rank correlations among genetic merit predictions obtained by M(1) and by the best fitting RN models M(3) (homoskedastic) and M(5) (heteroskedastic) at different environmental levels ranged from 0.79 and 0.81, suggesting biological importance of G×E in Brazilian Angus PWG. These results suggest that selection progress could be optimized by adopting environment-specific genetic merit predictions. The PWG environmental sensitivity of imported North American origin bulls (0.046 ± 0.009) was significantly larger (P < 0.05) than that of local sires (0.012 ± 0.013). Moreover, PWG of progeny of imported sires exceeded that of native sires in medium and superior production levels. On the other hand, Angus cattle locally selected in Brazil tended to be more robust to environmental changes and hence be more suitable when production environments for potential progeny is uncertain.

Genotype × environment interaction for long-yearling weight in Canchim cattle quantified by reaction norm analysis

The objective of this study was to investigate the presence of genotype × environment interactions (G×E) for long-yearling weight in Canchim cattle (5/8 Charolais + 3/8 zebu) in Brazil using reaction norms (RN). The hierarchical RN model included the fixed effect of age of the animal (linear coefficient) and random effects of contemporary groups and additive animal genetic intercept and slope of the RN and contemporary group effects as random effects. Contemporary groups as the most elemental representation of management conditions in beef cattle were chosen to represent the environmental covariate of the RN. The deviance information criteria demonstrated that a homoskedastic residual RN model provided a better data fit compared with a heteroskedastic counterpart and with a traditional animal model, which had the worst fit. The environmental gradient for long-yearling weight based on contemporary group effects ranged from -105 to 150 kg. The additive direct variance and heritability estimates increased with increasing environmental gradient from 74.33 ± 22.32 to 1,922.59 ± 258.99 kg(2) and from 0.08 ± 0.02 to 0.68 ± 0.03, respectively. The high genetic correlation (0.90 ± 0.03) between the intercept and the slope of the RN shows that animals with the greatest breeding values best responded to environmental improvement, characterizing scale effect as the source of G×E for long-yearling weight. The phenotypic plasticity demonstrated by the slope of the RN of the animal indicates the possibility to change genotype expression along the environmental gradient through selection. The results demonstrate the importance of accounting for G×E in the genetic evaluation of this population.

Genotype x environment interaction as it relates to egg production in turkeys (Meleagris gallopavo)

Genotype x environment (GxE) interactions can reduce the accuracy of a model to predict the performance of an animal and have an undesirable influence if not accounted for when estimating breeding values. Consequently, identification of these GxE is necessary when considering a turkey breeding program. Reranking based on the genetic prediction of turkey egg production, fertility, and hatchability in different seasons was indicative of a potential GxE interaction. Quantification of the GxE interactions was based on the genetic correlation estimated when traits were expressed in different seasons. Egg production was expressed as the percentage of days with an egg produced; fertility represented the proportion of hatched eggs that contained a fertile embryo; and hatchability was defined as the percentage of fertile eggs that produced a live bird. Variance components and heritability for egg production, fertility, and hatchability were estimated using ASReml. The heritability (h(2)) of egg production was calculated to be 0.32 for both lines with the phenotypic and genetic variance, 141.3 and 45.58 (percent days with egg produced)(2) and 118.3 and 38.35 (percent days with egg produced)(2) for female and male lines, respectively. The h(2) estimates for fertility were 0.08 in both lines with and of 293.3%(2) and 24.03%(2), and 576.9%(2) and 48.43%(2) for female and male lines, respectively. The hatchability h(2), and estimates were 0.09, 267.1%(2), and 24.44%(2), respectively, for the female line and 0.15, 582.2%(2), and 90.01%(2) for the male line, respectively. Based on an animal model, the variance components were used to calculate estimated breeding values for each trait. The annual fluctuation in estimated breeding values resulted in the need to evaluate egg number, fertility, and hatchability as 2 traits, summer and winter lay. The correlation between the 2 traits was less than unity (female line: r(egg production) = 0.76, r(fertility) = -0.20, r(hatchability) = 0.75 and male line: r(egg production) = 0.86, r(fertility) = 0.19, r(hatchability) = 0.68) suggesting a GxE interaction, and animals will significantly rerank in genetic predictions for these reproductive phenotypes in different seasons of lay. Egg production, fertility, and hatchability in turkeys could be considered as 2 distinct traits in an animal model based on season of lay.

Model for fitting longitudinal traits subject to threshold response applied to genetic evaluation for heat tolerance

A semi-parametric non-linear longitudinal hierarchical model is presented. The model assumes that individual variation exists both in the degree of the linear change of performance (slope) beyond a particular threshold of the independent variable scale and in the magnitude of the threshold itself; these individual variations are attributed to genetic and environmental components. During implementation via a Bayesian MCMC approach, threshold levels were sampled using a Metropolis step because their fully conditional posterior distributions do not have a closed form. The model was tested by simulation following designs similar to previous studies on genetics of heat stress. Posterior means of parameters of interest, under all simulation scenarios, were close to their true values with the latter always being included in the uncertain regions, indicating an absence of bias. The proposed models provide flexible tools for studying genotype by environmental interaction as well as for fitting other longitudinal traits subject to abrupt changes in the performance at particular points on the independent variable scale.

Inbreeding – lessons from animal breeding, evolutionary biology and conservation genetics

Abstract Increased rates of inbreeding are one side effect of breeding programmes designed to give genetic progress for traits of economic importance in livestock. Inbreeding leads to inbreeding depression for traits showing dominance, and will ultimately lead to a decrease in genetic variance within populations. Here we review theoretical and experimental literature from animal breeding, evolutionary biology and conservation genetics on the consequences of inbreeding in terms of trait means and genetic and environmental variance components. The genetic background for these effects is presented and the experimental literature interpreted in relation to them. Furthermore, purging of deleterious alleles and the variable nature of effects of inbreeding on populations are discussed. Based on the literature, we conclude that inbreeding in animal breeding must be controlled very efficiently to maintain long-term sustainable livestock production in the future. The tools to do this efficiently exist, and much can be learnt on inbreeding from the literature in fields only distantly related to animal breeding.

Up hill, down dale: quantitative genetics of curvaceous traits

'Repeated' measurements for a trait and individual, taken along some continuous scale such as time, can be thought of as representing points on a curve, where both means and covariances along the trajectory can change, gradually and continually. Such traits are commonly referred to as 'function-valued' (FV) traits. This review shows that standard quantitative genetic concepts extend readily to FV traits, with individual statistics, such as estimated breeding values and selection response, replaced by corresponding curves, modelled by respective functions. Covariance functions are introduced as the FV equivalent to matrices of covariances. Considering the class of functions represented by a regression on the continuous covariable, FV traits can be analysed within the linear mixed model framework commonly employed in quantitative genetics, giving rise to the so-called random regression model. Estimation of covariance functions, either indirectly from estimated covariances or directly from the data using restricted maximum likelihood or Bayesian analysis, is considered. It is shown that direct estimation of the leading principal components of covariance functions is feasible and advantageous. Extensions to multi-dimensional analyses are discussed.

Associations Among Descriptors of Herd Management and Phenotypic and Genetic Levels of Health and Fertility

The objective of this paper was to investigate the association of descriptors of herd environment with phenotypic levels and breeding values of fertility and health traits. Analyses were performed for 82,080 first-lactation heifers and 173,787 multiparous cows. Fourteen environmental parameters were defined that described herd environment, such as average protein production, average somatic cell score (SCS), average calving interval, and average body condition score (BCS). Herds with lower average SCS had, in general, more desirable values for almost all analyzed traits (i.e., days to first service was 7 d shorter), as did herds with lower average calving interval (i.e., 2.8% lower incidence of predicted mastitis). Herds with higher average protein production had slightly poorer fertility but more desirable values for all other analyzed traits (i.e., 5.1% less predicted mastitis, 0.4 lower SCS, and 0.6 higher BCS). Variance components and breeding values of sires were estimated by applying a random regression on the environmental parameters. In general, genetic variances varied generally only slightly across environments. However, based on data exclusively for heifers, the genetic variance for number of inseminations was 4.1 times higher in herds with a higher number of inseminations, 1.9 times higher for survival in herds with higher fat to protein ratio, and 1.7 times higher for predicted mastitis in herds with higher number of inseminations. Based on the heifer data, the lowest estimated genetic correlation across environments was 0.76 (SE 0.21) for first-service conception between herds with differing average BCS. The minimum based on the cow data was 0.65 (SE 0.10) for survival between herds with differing average ages at calving. The relative importance of some fertility traits compared with yield traits doubled across environments. Possible reranking of individual animals within a population and the changes in genetic variance across environments suggests that environment-specific breeding values should be estimated for use in customized selection indices.

Breeding robust pigs

Past developments in livestock breeding have led to considerable genetic change in production traits, but the follow-up of nutrition and management is often incomplete. The pig production sector is moving to hotter climates, and to more intensive and limiting conditions. This increases demands for animal robustness. Robustness can be implemented as a breeding objective trait just like production traits. Breeding for robustness is feasible, but requires substantial investment in data and technology. As for all low-heritability traits with complicated data recording, DNA markers provide a useful tool to support selection; this requires good association studies and ongoing multiple marker development. Breeding for increased robustness must be implemented in balance with breeding for increased production. It is therefore useful to define robustness in terms of performance-relevant issues. A convenient approach is through the environmental sensitivity of the expression of genetic production potential. Environmental sensitivity illustrates loss of flexibility to deal with intensive or limiting conditions, due to unbalanced resource allocation. It can be quantified for individual animals in terms of reaction norm parameters, which can be used as estimated breeding values to support selection. The challenges of implementing such a system will be (i) the set-up of proper data collection in a wide range of environmental settings; (ii) the development of proper data processing tools; (iii) the design of suitable breeding objectives and selection criteria, including MAS; and (iv) the successful integration of the first 3 objectives.

A resource allocation model describing consequences of artificial selection under metabolic stress

Long-term selection on production results in increased environmental sensitivity. This often is expressed through decreased fertility and increased health problems. The phenomenon has been described in all common farm animal species. One theory is that potential resource intake is insufficient to express production potential. Additional resources are drawn away from fitness-related traits, such as fertility and health, to further increase observed production. In addition, resources for maintaining fitness depend on the demands by the environment. In a harsh environment, more resources are required for fitness-related traits than in an optimal environment. Literature results show that selection in an optimal environment will increase sensitivity to less optimal environments. The objectives of this paper were to increase understanding of the underlying mechanism behind the development of environmental sensitivity and to gain insight into correlated response(s) when selection is on observed production. A resource allocation model was defined where observed production depended on production potential, resource intake potential, and the allocation of resources to production or fitness, including maintenance, health, and reproduction. Penalties for reproductive performance and probability of survival were included when the proportion of resources assigned to fitness dropped below a certain, environment-related, threshold. Mass selection was practiced on observed production during 40 generations using stochastic simulation. Depending on the heritabilities of the underlying components and on the environment, selection on observed production resulted in a decrease in reproductive rate and in the development of environmental sensitivity when resource intake becomes limiting. Correlations of observed production with underlying components changed across generations, following a nonlinear pattern. The proposed model is simple, but increases the understanding of underlying mechanisms and consequences of selection for production when resources are limiting.