Data-driven approaches can harness crop diversity to address heterogeneous needs for breeding products.

This perspective describes the opportunities and challenges of data-driven approaches for crop diversity management (genebanks and breeding) in the context of agricultural research for sustainable development in the Global South. Data-driven approaches build on larger volumes of data and flexible analyses that link different datasets across domains and disciplines. This can lead to more information-rich management of crop diversity, which can address the complex interactions between crop diversity, production environments, and socioeconomic heterogeneity and help to deliver more suitable portfolios of crop diversity to users with highly diverse demands. We describe recent efforts that illustrate the potential of data-driven approaches for crop diversity management. A continued investment in this area should fill remaining gaps and seize opportunities, including i) supporting genebanks to play a more active role in linking with farmers using data-driven approaches; ii) designing low-cost, appropriate technologies for phenotyping; iii) generating more and better gender and socioeconomic data; iv) designing information products to facilitate decision-making; and v) building more capacity in data science. Broad, well-coordinated policies and investments are needed to avoid fragmentation of such capacities and achieve coherence between domains and disciplines so that crop diversity management systems can become more effective in delivering benefits to farmers, consumers, and other users of crop diversity.

Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli.

The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern, and antibiotic restriction is often implemented to reduce the spread of resistance. These measures rely on the existence of deleterious fitness effects (i.e. costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. The fitness effects of AMR mutations are generally studied in laboratory reference strains grown in standard growth environments; however, the genetic and environmental context can influence the magnitude and direction of a mutation's fitness effects. In this study, we measure how three sources of variation impact the fitness effects of Escherichia coli AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji fitness landscape model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate the observed variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, which will ultimately impact their persistence in natural populations.

A predominant role of genotypic variation in both expression of sperm competition genes and paternity success in Drosophila melanogaster.

Sperm competition is a crucial aspect of male reproductive success in many species, including Drosophila melanogaster, and seminal fluid proteins (Sfps) can influence sperm competitiveness. However, the combined effect of environmental and genotypic variation on sperm competition gene expression remains poorly understood. Here, we used Drosophila Genetic Reference Panel (DGRP) inbred lines and manipulated developmental population density (i.e. larval density) to test the effects of genotype, environment and genotype-by-environment interactions (GEI) on the expression of the known sperm competition genes Sex Peptide, Acp36DE and CG9997. High larval density resulted in reduced adult body size, but expression of sperm competition genes remained unaffected. Furthermore, we found no significant GEI but genotypic effects in the expression of SP and Acp36DE. Our results also revealed GEI for relative competitive paternity success (second male paternity; P2), with genes' expression positively correlated with P2. Given the effect of genotype on the expression of genes, we conducted a genome-wide association study (GWAS) and identified polymorphisms in putative cis-regulatory elements as predominant factors regulating the expression of SP and Acp36DE. The association of genotypic variation with sperm competition outcomes, and the resilience of sperm competition genes' expression against environmental challenges, demonstrates the importance of genome variation background in reproductive fitness.

Relationships between phenotypic plasticity and epigenetic variation in two Caribbean Acropora corals.

The plastic ability for a range of phenotypes to be exhibited by the same genotype allows organisms to respond to environmental variation and may modulate fitness in novel environments. Differing capacities for phenotypic plasticity within a population, apparent as genotype by environment interactions (GxE), can therefore have both ecological and evolutionary implications. Epigenetic gene regulation alters gene function in response to environmental cues without changes to the underlying genetic sequence and likely mediates phenotypic variation. DNA methylation is currently the most well described epigenetic mechanism and is related to transcriptional homeostasis in invertebrates. However, evidence quantitatively linking variation in DNA methylation with that of phenotype is lacking in some taxa, including reef-building corals. In this study, spatial and seasonal environmental variation in Bonaire, Caribbean Netherlands was utilized to assess relationships between physiology and DNA methylation profiles within genetic clones across different genotypes of Acropora cervicornis and A. palmata corals. The physiology of both species was highly influenced by environmental variation compared to the effect of genotype. GxE effects on phenotype were only apparent in A. cervicornis. DNA methylation in both species differed between genotypes and seasons and epigenetic variation was significantly related to coral physiological metrics. Furthermore, plastic shifts in physiology across seasons were significantly positively correlated with shifts in DNA methylation profiles in both species. These results highlight the dynamic influence of environmental conditions and genetic constraints on the physiology of two important Caribbean coral species. Additionally, this study provides quantitative support for the role of epigenetic DNA methylation in mediating phenotypic plasticity in invertebrates.

Effects of environment and genotype on dispersal differ across departure, transfer and settlement in a butterfly metapopulation.

Active dispersal is driven by extrinsic and intrinsic factors at the three stages of departure, transfer and settlement. Most empirical studies capture only one stage of this complex process, and knowledge of how much can be generalized from one stage to another remains unknown. Here we use genetic assignment tests to reconstruct dispersal across 5 years and 232 habitat patches of a Glanville fritillary butterfly (Melitaea cinxia) metapopulation. We link individual dispersal events to weather, landscape structure, size and quality of habitat patches, and individual genotype to identify the factors that influence the three stages of dispersal and post-settlement survival. We found that nearly all tested factors strongly affected departure probabilities, but that the same factors explained very little variation in realized dispersal distances. Surprisingly, we found no effect of dispersal distance on post-settlement survival. Rather, survival was influenced by weather conditions, quality of the natal habitat patch, and a strong interaction between genotype and occupancy status of the settled habitat patch, with more mobile genotypes having higher survival as colonists rather than as immigrants. Our work highlights the multi-causality of dispersal and that some dispersal costs can only be understood by considering extrinsic and intrinsic factors and their interaction across the entire dispersal process.

Genotype by environment interactions in coral bleaching.

Climate-driven reef decline has prompted the development of next-generation coral conservation strategies, many of which hinge on the movement of adaptive variation across genetic and environmental gradients. This process is limited by our understanding of how genetic and genotypic drivers of coral bleaching will manifest in different environmental conditions. We reciprocally transplanted 10 genotypes of Acropora cervicornis across eight sites along a 60 km span of the Florida Reef Tract and documented significant genotype × environment interactions in bleaching response during the severe 2015 bleaching event. Performance relative to site mean was significantly different between genotypes and can be mostly explained by ensemble models of correlations with genetic markers. The high explanatory power was driven by significant enrichment of loci associated DNA repair, cell signalling and apoptosis. No genotypes performed above (or below) bleaching average at all sites, so genomic predictors can provide practitioners with 'confidence intervals' about the chance of success in novel habitats. These data have important implications for assisted gene flow and managed relocation, and their integration with traditional active restoration.

Genetic and plastic rewiring of food webs under climate change.

Climate change is altering ecological and evolutionary processes across biological scales. These simultaneous effects of climate change pose a major challenge for predicting the future state of populations, communities and ecosystems. This challenge is further exacerbated by the current lack of integration of research focused on these different scales. We propose that integrating the fields of quantitative genetics and food web ecology will reveal new insights on how climate change may reorganize biodiversity across levels of organization. This is because quantitative genetics links the genotypes of individuals to population-level phenotypic variation due to genetic (G), environmental (E) and gene-by-environment (G × E) factors. Food web ecology, on the other hand, links population-level phenotypes to the structure and dynamics of communities and ecosystems. We synthesize data and theory across these fields and find evidence that genetic (G) and plastic (E and G × E) phenotypic variation within populations will change in magnitude under new climates in predictable ways. We then show how changes in these sources of phenotypic variation can rewire food webs by altering the number and strength of species interactions, with consequences for ecosystem resilience. We also find evidence suggesting there are predictable asymmetries in genetic and plastic trait variation across trophic levels, which set the pace for phenotypic change and food web responses to climate change. Advances in genomics now make it possible to partition G, E and G × E phenotypic variation in natural populations, allowing tests of the hypotheses we propose. By synthesizing advances in quantitative genetics and food web ecology, we provide testable predictions for how the structure and dynamics of biodiversity will respond to climate change.

Genotype by heat stress interactions for production and functional traits in dairy cows from an across-generation perspective.

The aim of this study was to analyze time-lagged heat stress (HS) effects during late gestation on genetic co(variance) components in dairy cattle across generations for production, female fertility, and health traits. The data set for production and female fertility traits considered 162,492 Holstein Friesian cows from calving years 2003 to 2012, kept in medium-sized family farms. The health data set included 69,986 cows from calving years 2008 to 2016, kept in participating large-scale co-operator herds. Production traits were milk yield (MKG), fat percentage (fat%), and somatic cell score (SCS) from the first official test-day in first lactation. Female fertility traits were the nonreturn rate after 56 d (NRR56) in heifers and the interval from calving to first insemination (ICFI) in first-parity cows. Health traits included clinical mastitis (MAST), digital dermatitis (DD), and endometritis (EM) in the early lactation period in first-parity cows. Meteorological data included temperature and humidity from public weather stations in closest herd distance. The HS indicator was the temperature-humidity index (THI) during dams' late gestation, also defined as in utero HS. For the genetic analyses of production, female fertility, and health traits in the offspring generation, a sire-maternal grandsire random regression model with Legendre polynomials of order 3 for the production and of order 2 for the fertility and health traits on prenatal THI, was applied. All statistical models additionally considered a random maternal effect. THI from late gestation (i.e., prenatal climate conditions), influenced genetic parameter estimates in the offspring generation. For MKG, heritabilities and additive genetic variances decreased in a wave-like pattern with increasing THI. Especially for THI >58, the decrease was very obvious with a minimal heritability of 0.08. For fat% and SCS, heritabilities increased slightly subjected to prenatal HS conditions at THI >67. The ICFI heritabilities differed marginally across THI [heritability (h2) = 0.02-0.04]. For NRR56, MAST, and DD, curves for heritabilities and genetic variances were U-shaped, with largest estimates at the extreme ends of the THI scale. For EM, heritability increased from THI 25 (h2 = 0.13) to THI 71 (h2 = 0.39). The trait-specific alterations of genetic parameters along the THI gradient indicate pronounced genetic differentiation due to intrauterine HS for NRR56, MAST, DD, and EM, but decreasing genetic variation for MKG and ICFI. Genetic correlations smaller than 0.80 for NRR56, MAST, DD, and EM between THI 65 with corresponding traits at remaining THI indicated genotype by environment interactions. The lowest genetic correlations were identified when considering the most distant THI. For MKG, fat%, SCS, and ICFI, genetic correlations throughout were larger than 0.80, disproving concerns for any genotype by environment interactions. Variations in genetic (co)variance components across prenatal THI may be due to epigenetic modifications in the offspring genome, triggered by in utero HS. Epigenetic modifications have a persistent effect on phenotypic responses, even for traits recorded late in life. However, it is imperative to infer the underlying epigenetic mechanisms in ongoing molecular experiments.

Proofs for genotype by environment interactions considering pedigree and genomic data from organic and conventional cow reference populations.

The aim of the present study was to prove genotype by environment interactions (G × E) for production, longevity, and health traits considering conventional and organic German Holstein dairy cattle subpopulations. The full data set included 141,778 Holstein cows from 57 conventional herds and 7,915 cows from 9 organic herds. The analyzed traits were first-lactation milk yield and fat percentage (FP), the length of productive life (LPL) and the health traits mastitis, ovarian cycle disorders, and digital dermatitis in first lactation. A subset of phenotyped cows was genotyped and used for the implementation of separate cow reference populations. After SNP quality controls, the cow reference sets considered 40,830 SNP from 19,700 conventional cows and the same 40,830 SNP from 1,282 organic cows. The proof of possible G × E was made via multiple-trait model applications, considering same traits from the conventional and organic population as different traits. In this regard, pedigree (A), genomic (G) and combined relationship (H) matrices were constructed. For the production traits, heritabilities were very similar in both organic and conventional populations (i.e., close to 0.70 for FP and close to 0.40 for milk yield). For low heritability health traits and LPL, stronger heritability fluctuations were observed, especially for digital dermatitis with 0.05 ± 0.01 (organic, A matrix) to 0.33 ± 0.04 (conventional, G matrix). Quite large genetic correlations between same traits from the 2 environments were estimated for production traits, especially for high heritability FP. For LPL, the genetic correlation was 0.67 (A matrix) and 0.66 (H matrix). The genetic correlation between LPL organic with LPL conventional was 0.94 when considering the G matrix, but only 213 genotyped cows were included. For health traits, genetic correlations were throughout lower than 0.80, indicating possible G × E. Genetic correlations from the different matrices A, G, and H for health and production traits followed the same pattern, but the estimates from G for health traits were associated with quite large standard errors. In genome-wide association studies, significantly associated SNP for production traits overlapped in the conventional and organic population. In contrast, for low heritability LPL and health traits, significantly associated SNP and annotated potential candidate genes differed in both populations. In this regard, significantly associated SNP for mastitis from conventional cows were located on Bos taurus autosomes 6 and 19, but on Bos taurus autosomes 1, 10, and 22 in the organic population. For the remaining health traits and LPL, different potential candidate genes were annotated, but the different genes reflect similar physiological pathways. We found evidence of G × E for low heritability functional traits, suggesting different breeding approaches in organic and conventional populations. Nevertheless, for a verification of results and implementation of alternative breeding strategies, it is imperative to increase the organic cow reference population.

Exome sequences and multi-environment field trials elucidate the genetic basis of adaptation in barley.

Broadening the genetic base of crops is crucial for developing varieties to respond to global agricultural challenges such as climate change. Here, we analysed a diverse panel of 371 domesticated lines of the model crop barley to explore the genetics of crop adaptation. We first collected exome sequence data and phenotypes of key life history traits from contrasting multi-environment common garden trials. Then we applied refined statistical methods, including some based on exomic haplotype states, for genotype-by-environment (G×E) modelling. Sub-populations defined from exomic profiles were coincident with barley's biology, geography and history, and explained a high proportion of trial phenotypic variance. Clear G×E interactions indicated adaptation profiles that varied for landraces and cultivars. Exploration of circadian clock-related genes, associated with the environmentally adaptive days to heading trait (crucial for the crop's spread from the Fertile Crescent), illustrated complexities in G×E effect directions, and the importance of latitudinally based genic context in the expression of large-effect alleles. Our analysis supports a gene-level scientific understanding of crop adaption and leads to practical opportunities for crop improvement, allowing the prioritisation of genomic regions and particular sets of lines for breeding efforts seeking to cope with climate change and other stresses.

Population variation in early development can determine ecological resilience in response to environmental change.

As climate change transforms seasonal patterns of temperature and precipitation, germination success at marginal temperatures will become critical for the long-term persistence of many plant species and communities. If populations vary in their environmental sensitivity to marginal temperatures across a species' geographical range, populations that respond better to future environmental extremes are likely to be critical for maintaining ecological resilience of the species. Using seeds from two to six populations for each of nine species of Mediterranean plants, we characterized patterns of among-population variation in environmental sensitivity by quantifying genotype-by-environment interactions (G × E) for germination success at temperature extremes, and under two light regimes representing conditions below and above the soil surface. For eight of nine species tested at hot and cold marginal temperatures, we observed substantial among-population variation in environmental sensitivity for germination success, and this often depended on the light treatment. Importantly, different populations often performed best at different environmental extremes. Our results demonstrate that ongoing changes in temperature regime will affect the phenology, fitness, and demography of different populations within the same species differently. We show that quantifying patterns of G × E for multiple populations, and understanding how such patterns arise, can test mechanisms that promote ecological resilience.

Environmental variation impacts trait expression and selection in the legume-rhizobium symbiosis.

PREMISE: The ecological outcomes of mutualism are well known to shift across abiotic or biotic environments, but few studies have addressed how different environments impact evolutionary responses, including the intensity of selection on and the expression of genetic variance in key mutualism-related traits. METHODS: We planted 30 maternal lines of the legume Medicago lupulina in four field common gardens and compared our measures of selection on and genetic variance in nodulation, a key trait reflecting legume investment in the symbiosis, with those from a previous greenhouse experiment using the same 30 M. lupulina lines. RESULTS: We found that both the mean and genetic variance for nodulation were much greater in the greenhouse than in the field and that the form of selection on nodulation significantly differed across environments. We also found significant genotype-by-environment (G × E) effects for fitness-related traits that were generated by differences in the rank order of plant lines among environments. CONCLUSIONS: Overall, our results suggest that the expression of genotypic variation and selection on nodulation differ across environments. In the field, significant rank-order changes for plant fitness potentially help maintain genetic variation in natural populations, even in the face of directional or stabilizing selection.

Genome structure predicts modular transcriptome responses to genetic and environmental conditions.

Understanding the plasticity, robustness and modularity of transcriptome expression to genetic and environmental conditions is crucial to deciphering how organisms adapt in nature. To test how genome architecture influences transcriptome profiles, we quantified expression responses for distinct temperature-adapted genotypes of the nematode Caenorhabditis briggsae when exposed to chronic temperature stresses throughout development. We found that 56% of the 8,795 differentially expressed genes show genotype-specific changes in expression in response to temperature (genotype-by-environment interactions, GxE). Most genotype-specific responses occur under heat stress, indicating that cold vs. heat stress responses involve distinct genomic architectures. The 22 co-expression modules that we identified differ in their enrichment of genes with genetic vs. environmental vs. interaction effects, as well as their genomic spatial distributions, functional attributes and rates of molecular evolution at the sequence level. Genes in modules enriched for simple effects of either genotype or temperature alone tend to evolve especially rapidly, consistent with disproportionate influence of adaptation or weaker constraint on these subsets of loci. Chromosome-scale heterogeneity in nucleotide polymorphism, however, rather than the scale of individual genes predominates as the source of genetic differences among expression profiles, and natural selection regimes are largely decoupled between coding sequences and noncoding flanking sequences that contain cis-regulatory elements. These results illustrate how the form of transcriptome modularity and genome structure contribute to predictable profiles of evolutionary change.

Interactions between host sex and age of exposure modify the virulence-transmission trade-off.

The patterns of immunity conferred by host sex or age represent two sources of host heterogeneity that can potentially shape the evolutionary trajectory of disease. With each host sex or age encountered, a pathogen's optimal exploitative strategy may change, leading to considerable variation in expression of pathogen transmission and virulence. To date, these host characteristics have been studied in the context of host fitness alone, overlooking the effects of host sex and age on the fundamental virulence-transmission trade-off faced by pathogens. Here, we explicitly address the interaction of these characteristics and find that host sex and age at exposure to a pathogen affect age-specific patterns of mortality and the balance between pathogen transmission and virulence. When infecting age-structured male and female Daphnia magna with different genotypes of Pasteuria ramosa, we found that infection increased mortality rates across all age classes for females, whereas mortality only increased in the earliest age class for males. Female hosts allowed a variety of trade-offs between transmission and virulence to arise with each age and pathogen genotype. In contrast, this variation was dampened in males, with pathogens exhibiting declines in both virulence and transmission with increasing host age. Our results suggest that differences in exploitation potential of males and females to a pathogen can interact with host age to allow different virulence strategies to coexist, and illustrate the potential for these widespread sources of host heterogeneity to direct the evolution of disease in natural populations.

Infection rate of Aedes aegypti mosquitoes with dengue virus depends on the interaction between temperature and mosquito genotype.

Dengue fever is the most prevalent arthropod-transmitted viral disease worldwide, with endemic transmission restricted to tropical and subtropical regions of different temperature profiles. Temperature is epidemiologically relevant because it affects dengue infection rates in Aedes aegypti mosquitoes, the major vector of the dengue virus (DENV). Aedes aegypti populations are also known to vary in competence for different DENV genotypes. We assessed the effects of mosquito and virus genotype on DENV infection in the context of temperature by challenging Ae. aegypti from two locations in Vietnam, which differ in temperature regimes, with two isolates of DENV-2 collected from the same two localities, followed by incubation at 25, 27 or 32°C for 10 days. Genotyping of the mosquito populations and virus isolates confirmed that each group was genetically distinct. Extrinsic incubation temperature (EIT) and DENV-2 genotype had a direct effect on the infection rate, consistent with previous studies. However, our results show that the EIT impacts the infection rate differently in each mosquito population, indicating a genotype by environment interaction. These results suggest that the magnitude of DENV epidemics may not only depend on the virus and mosquito genotypes present, but also on how they interact with local temperature. This information should be considered when estimating vector competence of local and introduced mosquito populations during disease risk evaluation.

Beyond the single gene: How epistasis and gene-by-environment effects influence crop domestication.

Domestication is a multifaceted evolutionary process, involving changes in individual genes, genetic interactions, and emergent phenotypes. There has been extensive discussion of the phenotypic characteristics of plant domestication, and recent research has started to identify the specific genes and mutational mechanisms that control domestication traits. However, there is an apparent disconnect between the simple genetic architecture described for many crop domestication traits, which should facilitate rapid phenotypic change under selection, and the slow rate of change reported from the archeobotanical record. A possible explanation involves the middle ground between individual genetic changes and their expression during development, where gene-by-gene (epistatic) and gene-by-environment interactions can modify the expression of phenotypes and opportunities for selection. These aspects of genetic architecture have the potential to significantly slow the speed of phenotypic evolution during crop domestication and improvement. Here we examine whether epistatic and gene-by-environment interactions have shaped how domestication traits have evolved. We review available evidence from the literature, and we analyze two domestication-related traits, shattering and flowering time, in a mapping population derived from a cross between domesticated foxtail millet and its wild progenitor. We find that compared with wild progenitor alleles, those favored during domestication often have large phenotypic effects and are relatively insensitive to genetic background and environmental effects. Consistent selection should thus be able to rapidly change traits during domestication. We conclude that if phenotypic evolution was slow during crop domestication, this is more likely due to cultural or historical factors than epistatic or environmental constraints.

Adaptive Landscapes of Resistance Genes Change as Antibiotic Concentrations Change.

Most studies on the evolution of antibiotic resistance are focused on selection for resistance at lethal antibiotic concentrations, which has allowed the detection of mutant strains that show strong phenotypic traits. However, solely focusing on lethal concentrations of antibiotics narrowly limits our perspective of antibiotic resistance evolution. New high-resolution competition assays have shown that resistant bacteria are selected at relatively low concentrations of antibiotics. This finding is important because sublethal concentrations of antibiotics are found widely in patients undergoing antibiotic therapies, and in nonmedical conditions such as wastewater treatment plants, and food and water used in agriculture and farming. To understand the impacts of sublethal concentrations on selection, we measured 30 adaptive landscapes for a set of TEM ß-lactamases containing all combinations of the four amino acid substitutions that exist in TEM-50 for 15 ß-lactam antibiotics at multiple concentrations. We found that there are many evolutionary pathways within this collection of landscapes that lead to nearly every TEM-genotype that we studied. While it is known that the pathways change depending on the type of ß-lactam, this study demonstrates that the landscapes including fitness optima also change dramatically as the concentrations of antibiotics change. Based on these results we conclude that the presence of multiple concentrations of ß-lactams in an environment result in many different adaptive landscapes through which pathways to nearly every genotype are available. Ultimately this may increase the diversity of genotypes in microbial populations.

Genotypic variation in biomass allocation in response to field drought has a greater affect on yield than gas exchange or phenology.

BACKGROUND: Plant performance in agricultural and natural settings varies with moisture availability, and understanding the range of potential drought responses and the underlying genetic architecture is important for understanding how plants will respond to both natural and artificial selection in various water regimes. Here, we raised genotypes of Brassica rapa under well-watered and drought treatments in the field. Our primary goal was to understand the genetic architecture and yield effects of different drought-escape and dehydration-avoidance strategies. RESULTS: Drought treatments reduced soil moisture by 62 % of field capacity. Drought decreased biomass accumulation and fruit production by as much as 48 %, whereas instantaneous water-use efficiency and root:shoot ratio increased. Genotypes differed in the mean value of all traits and in the sensitivity of biomass accumulation, root:shoot ratio, and fruit production to drought. Bivariate correlations involving gas-exchange and phenology were largely constant across environments, whereas those involving root:shoot varied across treatments. Although root:shoot was typically unrelated to gas-exchange or yield under well-watered conditions, genotypes with low to moderate increases in root:shoot allocation in response to drought survived the growing season, maintained maximum photosynthesis levels, and produced more fruit than genotypes with the greatest root allocation under drought. QTL for gas-exchange and yield components (total biomass or fruit production) had common effects across environments while those for root:shoot were often environment-specific. CONCLUSIONS: Increases in root allocation beyond those needed to survive and maintain favorable water relations came at the cost of fruit production. The environment-specific effects of root:shoot ratio on yield and the differential expression of QTL for this trait across water regimes have important implications for efforts to improve crops for drought resistance.

Evaluation of sire by environment interactions for growth rate and backfat depth using reaction norm models in pigs.

Reaction norm models for sires were used to evaluate genotype by environment interactions for lifetime average daily gain (ADG) and backfat depth (BF) in pigs recorded at 143 days. Data for ADG and BF were available for 265 103 pigs recorded in Australia between 2000 and 2010 in nine herds. The full data set and two subsets based on minimum numbers of progeny per sire of 50 and 100 were analysed. The environmental descriptor was quantified as least square means of herd-by-birth month (HBM) contemporary groups which varied from 540 to 738 g/day for ADG and from 8.2 to 13.8 mm for BF. Several models were evaluated for estimation of variance components in terms of predictive ability for sire intercepts and slopes. The accuracy of genetic parameter estimates was improved by increasing family size, fitting models with a fixed regression coefficient on the environmental descriptor instead of fixed HBM effects and heterogeneous residual variances. Significant sire by environment interactions were found for ADG but not for BF. Heritability estimates for ADG ranged from approximately 0.21 in average environments to approximately 0.30 in the most unfavourable environments. Estimates of sire intercepts and slopes varied by 98.5 g/day and 0.253 g/day per g/day for ADG, respectively. Lowly negative correlations between sire intercept and slope do not support the hypothesis that high growth is associated with larger environmental sensitivity.