Strawberry phenotypic plasticity in flowering time is driven by interaction between genetic loci and temperature.

The flowering time (FT), which determines when fruits or seeds can be harvested, is subject to phenotypic plasticity, i.e. the ability of a genotype to display different phenotypes in response to environmental variations. Here, we investigated how the environment affects the genetic architecture of FT in cultivated strawberry (Fragaria ×ananassa) and modifies its QTL effects. To this end, we used a bi-parental segregating population grown for two years at widely divergent latitudes (5 European countries) and combined climatic variables with genomic data (Affymetrix® SNP array). Examination, using different phenological models, of the response of FT to photoperiod, temperature and global radiation, indicated that temperature is the main driver of FT in strawberry. We next characterized in the segregating population the phenotypic plasticity of FT by using three statistical approaches that generated plasticity parameters including reaction norm parameters. We detected 25 FT QTL summarized into 10 unique QTL. Mean values and plasticity parameters QTL were co-localized in three of them, including the major 6D_M QTL whose effect is strongly modulated by temperature. The design and validation of a genetic marker for the 6D_M QTL offers great potential for breeding programs, for example for selecting early-flowering strawberry varieties well adapted to different environmental conditions.

Genetic evaluations and genome-wide association studies for specific digital dermatitis diagnoses in dairy cows considering genotype × housing system interactions.

The present study aimed to use detailed phenotyping for the claw disorder digital dermatitis (DD) considering specific DD stages in 2 housing systems (conventional cubicle barns [CON] and compost-bedded pack barns [CBPB]) to infer possible genotype × housing system interactions. The DD stages included 2,980 observations for the 3 traits DD-sick, DD-acute, and DD-chronic from 1,311 Holstein-Friesian and 399 Fleckvieh-Simmental cows. Selection of the 5 CBPB and 5 CON herds was based on a specific protocol to achieve a high level of herd similarity with regard to climate, feeding, milking system, and location, but with pronounced housing-system differences. Five other farms had a "mixed system" with 2 subherds, one representing CBPB and the other one CON. The CBPB system was represented by 899 cows (1,530 observations), and 811 cows (1,450 observations) represented the CON system. The average disease prevalence was 20.47% for DD-sick, 13.88% for DD-acute, and 5.34% for DD-chronic, with a higher prevalence in CON than in CBPB. After quality control of 50K genotypes, 38,495 SNPs from 926 cows remained for the ongoing genomic analyses. Genetic parameters for DD-sick, DD-acute, and DD-chronic were estimated by applying single-step approaches for single-trait repeatability animal models considering the whole dataset, and separately for the CON and CBPB subsets. Genetic correlations between same DD traits from different housing systems, and between DD-sick, DD-chronic, and DD-acute, were estimated via bivariate animal models. Heritabilities based on the whole dataset were 0.16 for DD-sick, 0.14 for DD-acute, and 0.11 for DD-chronic. A slight increase of heritabilities and genetic variances was observed in CON compared with the "well-being" CBPB system, indicating a stronger genetic differentiation of diseases in a more challenging environment. Genetic correlations between same DD traits recorded in CON or CBPB were close to 0.80, disproving obvious genotype × housing system interactions. Genetic correlations among DD-sick, DD-acute and DD-chronic ranged from 0.58 to 0.81. SNP main effects and SNP × housing system interaction effects were estimated simultaneously via GWAS, considering only the phenotypes from genotyped cows. Ongoing annotations of potential candidate genes focused on chromosomal segments 100 kb upstream and downstream from the significantly associated candidate SNP. GWAS for main effects indicated heterogeneous Manhattan plots especially for DD-acute and DD-chronic, indicating particularities in disease pathogenesis. Nevertheless, a few shared annotated potential candidate genes, that is, METTL25, AFF3, PRKG1, and TENM4 for DD-sick and DD-acute, were identified. These genes have direct or indirect effects on disease resistance or immunology. For the SNP × housing system interaction, the annotated genes ASXL1 and NOL4L on BTA 13 were relevant for DD-sick and DD-acute. Overall, the very similar genetic parameters for the same traits in different environments and negligible genotype × housing system interactions indicate only minor effects on genetic evaluations for DD due to housing-system particularities.

Genotype-by-environment interactions influence the composition of the Drosophila seminal proteome.

Ejaculate proteins are key mediators of post-mating sexual selection and sexual conflict, as they can influence both male fertilization success and female reproductive physiology. However, the extent and sources of genetic variation and condition dependence of the ejaculate proteome are largely unknown. Such knowledge could reveal the targets and mechanisms of post-mating selection and inform about the relative costs and allocation of different ejaculate components, each with its own potential fitness consequences. Here, we used liquid chromatography coupled with tandem mass spectrometry to characterize the whole-ejaculate protein composition across 12 isogenic lines of Drosophila melanogaster that were reared on a high- or low-quality diet. We discovered new proteins in the transferred ejaculate and inferred their origin in the male reproductive system. We further found that the ejaculate composition was mainly determined by genotype identity and genotype-specific responses to larval diet, with no clear overall diet effect. Nutrient restriction increased proteolytic protein activity and shifted the balance between reproductive function and RNA metabolism. Our results open new avenues for exploring the intricate role of genotypes and their environment in shaping ejaculate composition, or for studying the functional dynamics and evolutionary potential of the ejaculate in its multivariate complexity.

Genotype specific and microbiome effects of hypoxia in the model organism Daphnia magna.

The fitness of the host is highly influenced by the interplay between the host and its associated microbiota. The flexible nature of these microbiota enables them to respond swiftly to shifts in the environment, which plays a key role in the host's capacity to withstand environmental stresses. To understand the role of the microbiome in host tolerance to hypoxia, one of the most significant chemical changes occurring in water ecosystems due to climate change, we performed a reciprocal gut transplant experiment with the freshwater crustacean Daphnia magna. In a microbiome transplant experiment, two genotypes of germ-free recipients were inoculated with gut microbiota from Daphnia donors of their own genotype or from the other genotype, that had been either pre-exposed to normoxic or hypoxic conditions. We found that D. magna individuals had a higher survival probability in hypoxia if their microbiome had been pre-exposed to hypoxia. The bacterial communities of the recipients changed over time with a reduction in alpha diversity, which was stronger when donors were pre-exposed to a hypoxic environment. While donor genotype had no influence on the long-term survival probability in hypoxia, donor genotypes was the most influential factor of the microbial community 3 days after the transplantation. Our results indicate that microbiome influencing factors mediate host fitness in a hypoxic environment in a time depending way.

Efficacy of drought-tolerant and insect-protected transgenic TELA® maize traits in Nigeria.

Assessment of efficacy of drought tolerance (DT) and insect protection (Bt) genes in maize genotypes is invaluable for commercialization and production of transgenic maize in Nigeria. Seven maize hybrids, known as TELA® maize, with stacked events of Bt insect protection (MON89034) and drought tolerance (MON87460; DroughtGard®) and their respective non-GM versions (isohybrids) developed through the TELA Maize Project were evaluated in confined field trial site at Zaria in 2020 and 2021. The objective was to assess the efficacy of stacked DT and Bt genes to seek deregulation and commercialization of both traits in Nigeria. Significant (P < 0.05-0.01) differences were observed among genotypes (G), environments (E) and genotype × environment interaction (GEI) for grain yield and most other traits under stem borer (moth species) and fall armyworm infested, drought stress, and optimum-moisture conditions, except E and GEI under drought. TELA® GM hybrids with Bt MON89034 had 19% higher yield than their non-GM isogenic versions, and 40% higher yield than the commercial checks under the target pests infestation. The foliar damage score of all the TELA® GM genotypes was ≤ 2 relative to their non-GM isogenic versions which scored ≥ 4, indicating the effectiveness of the Bt MON89034 gene in conferring resistance against stem borer and fall armyworm. Under moderate drought, pairwise comparison showed TELA® GM Hybrid 1-1 and Hybrid 2-1 had 12.4-20.4% higher (P < 0.01) yield than their isogenic versions. Under optimum-moisture condition with pests controlled, the TELA® GM and their isogenic hybrids were similar, but both had 32% higher yield than the commercial checks. Adoption of TELA® GM technology by farmers as adaptation strategy to cope with climate change, will ensure sustainability of maize production and productivity in Nigeria.

White Lupin Drought Tolerance: Genetic Variation, Trait Genetic Architecture, and Genome-Enabled Prediction.

White lupin is a high-protein crop requiring drought tolerance improvement. This study focused on a genetically-broad population of 138 lines to investigate the phenotypic variation and genotype × environment interaction (GEI) for grain yield and other traits across drought-prone and moisture-favourable managed environments, the trait genetic architecture and relevant genomic regions by a GWAS using 9828 mapped SNP markers, and the predictive ability of genomic selection (GS) models. Water treatments across two late cropping months implied max. available soil water content of 60-80% for favourable conditions and from wilting point to 15% for severe drought. Line yield responses across environments featured a genetic correlation of 0.84. Relatively better line yield under drought was associated with an increased harvest index. Two significant QTLs emerged for yield in each condition that differed across conditions. Line yield under stress displayed an inverse linear relationship with the onset of flowering, confirmed genomically by a common major QTL. An adjusted grain yield computed as deviation from phenology-predicted yield acted as an indicator of intrinsic drought tolerance. On the whole, the yield in both conditions and the adjusted yield were polygenic, heritable, and exploitable by GS with a high predictive ability (0.62-0.78). Our results can support selection for climatically different drought-prone regions.

Host-Associated Rhizobial Fitness: Dependence on Nitrogen, Density, Community Complexity, and Legume Genotype.

The environmental context of the nitrogen-fixing mutualism between leguminous plants and rhizobial bacteria varies over space and time. Variation in resource availability, population density, and composition likely affect the ecology and evolution of rhizobia and their symbiotic interactions with hosts. We examined how host genotype, nitrogen addition, rhizobial density, and community complexity affected selection on 68 rhizobial strains in the Sinorhizobium meliloti-Medicago truncatula mutualism. As expected, host genotype had a substantial effect on the size, number, and strain composition of root nodules (the symbiotic organ). The understudied environmental variable of rhizobial density had a stronger effect on nodule strain frequency than the addition of low nitrogen levels. Higher inoculum density resulted in a nodule community that was less diverse and more beneficial but only in the context of the more selective host genotype. Higher density resulted in more diverse and less beneficial nodule communities with the less selective host. Density effects on strain composition deserve additional scrutiny as they can create feedback between ecological and evolutionary processes. Finally, we found that relative strain rankings were stable across increasing community complexity (2, 3, 8, or 68 strains). This unexpected result suggests that higher-order interactions between strains are rare in the context of nodule formation and development. Our work highlights the importance of examining mechanisms of density-dependent strain fitness and developing theoretical predictions that incorporate density dependence. Furthermore, our results have translational relevance for overcoming establishment barriers in bioinoculants and motivating breeding programs that maintain beneficial plant-microbe interactions across diverse agroecological contexts. IMPORTANCE Legume crops establish beneficial associations with rhizobial bacteria that perform biological nitrogen fixation, providing nitrogen to plants without the economic and greenhouse gas emission costs of chemical nitrogen inputs. Here, we examine the influence of three environmental factors that vary in agricultural fields on strain relative fitness in nodules. In addition to manipulating nitrogen, we also use two biotic variables that have rarely been examined: the rhizobial community's density and complexity. Taken together, our results suggest that (i) breeding legume varieties that select beneficial strains despite environmental variation is possible, (ii) changes in rhizobial population densities that occur routinely in agricultural fields could drive evolutionary changes in rhizobial populations, and (iii) the lack of higher-order interactions between strains will allow the high-throughput assessments of rhizobia winners and losers during plant interactions.

Parenting moderates the etiology of callous-unemotional traits in middle childhood.

BACKGROUND: Callous-unemotional (CU) traits are associated with chronic and escalating trajectories of antisocial behavior. Extant etiologic studies suggest that heritability estimates for CU traits vary substantially, while also pointing to an environmental association between parenting and CU traits. METHODS: We used twin modeling to estimate additive genetic (A), shared environmental (C), and nonshared environmental (E) influences on CU traits, measured with the Inventory of Callous-Unemotional Traits (ICU) and its subscales. Our sample included 600 twin pairs (age 6-11, 230 monozygotic) from neighborhoods with above-average levels of family poverty, a risk factor for antisocial behavior. We examined the extent to which correlations between parenting, measured via parent and child report on the Parental Environment Questionnaire, and CU traits reflected genetic versus environmental factors. Then, we tested whether parenting moderated the heritability of CU traits. RESULTS: In the context of lower-income neighborhoods, CU traits were moderately to highly heritable (A = 54%) with similar moderate-to-high nonshared environmental influences (E = 46%). Bivariate models revealed that associations between CU traits and warm parenting were genetic (rA = .22) and environmental (rE = .19) in origin, whereas associations between CU traits and harsh parenting were largely genetic in origin (rA = .70). The heritability of CU traits decreased with increasing parental warmth and decreasing harshness. CONCLUSIONS: Callous-unemotional traits are both genetic and environmental in origin during middle childhood, but genetic influences are moderated by parenting quality. Parenting may be an important target for interventions, particularly among youth with greater genetic risk.

Genotype × environment interaction obscures genetic sources of variation in seed size in Dithyrea californica but provides the opportunity for selection on phenotypic plasticity.

PREMISE: In many species, seed size influences individual fitness, but its heritability is low, impeding its evolution. In heterogeneous environments, even if heritability of seed size is low, genetic variation in phenotypic plasticity for seed size may provide the opportunity for selection, but this possibility has rarely been investigated in wild species. The evolutionary trajectory of seed size depends on whether additive, maternal, or non-additive genetic variance dominates; moreover, the expression of any of these sources of variance may be environment-dependent, reflecting genetic variation in plasticity. In this study, we examined these sources of variation in seed size and their response to drought in Dithyrea californica. METHODS: We used a diallel design to estimate variance components for seed size in three greenhouse-raised populations sampled from California and northern Mexico. We replicated diallels in two watering treatments to examine genetic parameters and genotype × environment interactions affecting seed size. We estimated general (GCA) and specific (SCA) combining ability, reciprocal effects (RGCA and RSCA), and their interactions with water availability, and we sought evidence that sexual conflict influences seed size. RESULTS: Norms of reaction revealed genetic variation in plasticity for seed size in each population. Seed size in D. californica is determined by the combination of watering treatment, GCA and RGCA; parental identity and water availability do not consistently affect seed size, and we detected no evidence for sexual conflict. CONCLUSIONS: Multiple sources of genetic variation in phenotypic plasticity for seed size have the potential to influence its evolutionary trajectory in heterogenous environments.

The Collective Behavior of Ant Groups Depends on Group Genotypic Composition.

Recently, researchers have documented variation between groups in collective behavior. However, how genetic variation within and between groups contributes to population-level variation for collective behavior remains unclear. Understanding how genetic variation of group members relates to group-level phenotypes is evolutionarily important because there is increasing evidence that group-level behavioral variation influences fitness and that the genetic architecture of group-level traits can affect the evolutionary dynamics of traits. Social insects are ideal for studying the complex relationship between individual and group-level variation because they exhibit behavioral variation at multiple scales of organization. To explore how the genetic composition of groups affects collective behavior, we constructed groups of pharaoh ants (Monomorium pharaonis) from 33 genetically distinct colonies of known pedigree. The groups consisted of either all workers from the same single colony or workers from two genetically different colonies, and we assayed the exploration and aggression of the groups. We found that collective exploration, but not aggression, depended on the specific genotypic combination of group members, i.e., we found evidence for genotype-by-genotype epistasis for exploration. Group collective behavior did not depend on the pedigree relatedness between genotypes within groups. Overall, this study highlights that specific combinations of genotypes influence group-level phenotypes, emphasizing the importance of considering nonadditive effects of genotypic interactions between group members.

Crop variety management for climate adaptation supported by citizen science.

Crop adaptation to climate change requires accelerated crop variety introduction accompanied by recommendations to help farmers match the best variety with their field contexts. Existing approaches to generate these recommendations lack scalability and predictivity in marginal production environments. We tested if crowdsourced citizen science can address this challenge, producing empirical data across geographic space that, in aggregate, can characterize varietal climatic responses. We present the results of 12,409 farmer-managed experimental plots of common bean (Phaseolus vulgaris L.) in Nicaragua, durum wheat (Triticum durum Desf.) in Ethiopia, and bread wheat (Triticum aestivum L.) in India. Farmers collaborated as citizen scientists, each ranking the performance of three varieties randomly assigned from a larger set. We show that the approach can register known specific effects of climate variation on varietal performance. The prediction of variety performance from seasonal climatic variables was generalizable across growing seasons. We show that these analyses can improve variety recommendations in four aspects: reduction of climate bias, incorporation of seasonal climate forecasts, risk analysis, and geographic extrapolation. Variety recommendations derived from the citizen science trials led to important differences with previous recommendations.

Field-Relevant New Sources of Resistance to Anthracnose Caused by Colletotrichum truncatum in a Mungbean Mini-Core Collection.

Anthracnose is a prevalent disease of mungbean in Asian countries and Sub-Saharan Africa. It is caused by multiple Colletotrichum species. The high levels of anthracnose resistance in mungbean have not been studied in depth in India, but genetic resistance is desired. In this study, we identified the causal agent of mungbean anthracnose in two regions of India as Colletotrichum truncatum through morphological and molecular methods. A set of 296 mungbean mini-core accessions developed by WorldVeg was screened under a natural disease pressure from July to September (kharif season) in 2016, 2017, and 2018 in Hyderabad (a hot spot for anthracnose) to identify anthracnose resistance. Based on disease severity scores, 22 accessions were consistently anthracnose resistant under the categories of immune, highly resistant, and resistant with scores ranging from ≥1.0 to ≤3.0 during the period of study. Furthermore, based on the agronomic performance, anthracnose resistance in Hyderabad, and other desirable traits, a subset of 74 mungbean accessions was selected from 296 mini-core accessions. These accessions were evaluated under natural disease pressure from July to September in 2018 and 2019 in Palampur (another hot spot for anthracnose) to determine the variation in anthracnose resistance. Out of the 74 accessions, two accessions were resistant in 2018; in 2019, one was immune, nine were highly resistant, and 15 were resistant. Combined analysis of variance of 65 accessions common in Hyderabad and Palampur revealed highly significant effects of environment, genotype (accessions), and genotype × environment interaction on the disease severity. The combined GGE biplot analysis of data across years and locations confirmed that the seven accessions MC-24, MC-51, MC-75, MC-127, MC-207, MC-208, and MC-292 were resistant during 2016 to 2018 in Hyderabad, and only in 2019 in Palampur, and the same accessions were moderately resistant in 2018 in Palampur. The seven resistant accessions identified from both test locations could be used as potential donors in the anthracnose resistance breeding program.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Genetic basis of phenotypic plasticity and genotype × environment interactions in a multi-parental tomato population.

Deciphering the genetic basis of phenotypic plasticity and genotype × environment interactions (G×E) is of primary importance for plant breeding in the context of global climate change. Tomato (Solanum lycopersicum) is a widely cultivated crop that can grow in different geographical habitats and that displays a great capacity for expressing phenotypic plasticity. We used a multi-parental advanced generation intercross (MAGIC) tomato population to explore G×E and plasticity for multiple traits measured in a multi-environment trial (MET) comprising optimal cultural conditions together with water deficit, salinity, and heat stress over 12 environments. Substantial G×E was observed for all the traits measured. Different plasticity parameters were estimated by employing Finlay-Wilkinson and factorial regression models and these were used together with genotypic means for quantitative trait loci (QTL) mapping analyses. In addition, mixed linear models were also used to investigate the presence of QTL × environment interactions. The results highlighted a complex genetic architecture of tomato plasticity and G×E. Candidate genes that might be involved in the occurrence of G×E are proposed, paving the way for functional characterization of stress response genes in tomato and for breeding climate-adapted cultivars.

Grain yield genetic gains and changes in physiological related traits for CIMMYT's High Rainfall Wheat Screening Nursery tested across international environments.

The effects of climate change together with the projected future demand represents a huge challenge for wheat production systems worldwide. Wheat breeding can contribute to global food security through the creation of genotypes exhibiting stress tolerance and higher yield potential. The objectives of our study were to (i) estimate the annual grain yield (GY) genetic gain of High Rainfall Wheat Yield Trials (HRWYT) grown from 2007 (15th HRWYT) to 2016 (24th HRWYT) across international environments, and (ii) determine the changes in physiological traits associated with GY genetic improvement. The GY genetic gains were estimated as genetic progress per se (GYP) and in terms of local checks (GYLC). In total, 239 international locations were classified into two groups: high- and low-rainfall environments based on climate variables and trial management practices. In the high-rainfall environment, the annual genetic gains for GYP and GYLC were 3.8 and 1.17 % (160 and 65.1 kg ha-1 yr-1), respectively. In the low-rainfall environment, the genetic gains were 0.93 and 0.73 % (40 and 33.1 kg ha-1 yr-1), for GYP and GYLC respectively. The GY of the lines included in each nursery showed a significant phenotypic correlation between high- and low-rainfall environments in all the examined years and several of the five best performing lines were common in both environments. The GY progress was mainly associated with increased grain weight (R2 = 0.35 p < 0.001), days to maturity (R2 = 0.20, p < 0.001) and grain filling period (R2 = 0.06, p < 0.05). These results indicate continuous GY genetic progress and yield stability in the HRWYT germplasm developed and distributed by CIMMYT.

Development and Proof-of-Concept Application of Genome-Enabled Selection for Pea Grain Yield under Severe Terminal Drought.

Terminal drought is the main stress limiting pea (Pisum sativum L.) grain yield in Mediterranean environments. This study aimed to investigate genotype × environment (GE) interaction patterns, define a genomic selection (GS) model for yield under severe drought based on single nucleotide polymorphism (SNP) markers from genotyping-by-sequencing, and compare GS with phenotypic selection (PS) and marker-assisted selection (MAS). Some 288 lines belonging to three connected RIL populations were evaluated in a managed-stress (MS) environment of Northern Italy, Marchouch (Morocco), and Alger (Algeria). Intra-environment, cross-environment, and cross-population predictive ability were assessed by Ridge Regression best linear unbiased prediction (rrBLUP) and Bayesian Lasso models. GE interaction was particularly large across moderate-stress and severe-stress environments. In proof-of-concept experiments performed in a MS environment, GS models constructed from MS environment and Marchouch data applied to independent material separated top-performing lines from mid- and bottom-performing ones, and produced actual yield gains similar to PS. The latter result would imply somewhat greater GS efficiency when considering same selection costs, in partial agreement with predicted efficiency results. GS, which exploited drought escape and intrinsic drought tolerance, exhibited 18% greater selection efficiency than MAS (albeit with non-significant difference between selections) and moderate to high cross-population predictive ability. GS can be cost-efficient to raise yields under severe drought.

Grapevine field experiments reveal the contribution of genotype, the influence of environment and the effect of their interaction (G×E) on the berry transcriptome.

Changes in the performance of genotypes in different environments are defined as genotype × environment (G×E) interactions. In grapevine (Vitis vinifera), complex interactions between different genotypes and climate, soil and farming practices yield unique berry qualities. However, the molecular basis of this phenomenon remains unclear. To dissect the basis of grapevine G×E interactions we characterized berry transcriptome plasticity, the genome methylation landscape and within-genotype allelic diversity in two genotypes cultivated in three different environments over two vintages. We identified, through a novel data-mining pipeline, genes with expression profiles that were: unaffected by genotype or environment, genotype-dependent but unaffected by the environment, environmentally-dependent regardless of genotype, and G×E-related. The G×E-related genes showed different degrees of within-cultivar allelic diversity in the two genotypes and were enriched for stress responses, signal transduction and secondary metabolism categories. Our study unraveled the mutual relationships between genotypic and environmental variables during G×E interaction in a woody perennial species, providing a reference model to explore how cultivated fruit crops respond to diverse environments. Also, the pivotal role of vineyard location in determining the performance of different varieties, by enhancing berry quality traits, was unraveled.

Pea genomic selection for Italian environments.

BACKGROUND: A thorough verification of the ability of genomic selection (GS) to predict estimated breeding values for pea (Pisum sativum L.) grain yield is pending. Prediction for different environments (inter-environment prediction) has key importance when breeding for target environments featuring high genotype × environment interaction (GEI). The interest of GS would increase if it could display acceptable prediction accuracies in different environments also for germplasm that was not used in model training (inter-population prediction). RESULTS: Some 306 genotypes belonging to three connected RIL populations derived from paired crosses between elite cultivars were genotyped through genotyping-by-sequencing and phenotyped for grain yield, onset of flowering, lodging susceptibility, seed weight and winter plant survival in three autumn-sown environments of northern or central Italy. The large GEI for grain yield and its pattern (implying larger variation across years than sites mainly due to year-to-year variability for low winter temperatures) encouraged the breeding for wide adaptation. Wider within-population than between-population variation was observed for nearly all traits, supporting GS application to many lines of relatively few elite RIL populations. Bayesian Lasso without structure imputation and 1% maximum genotype missing rate (including 6058 polymorphic SNP markers) was selected for GS modelling after assessing different GS models and data configurations. On average, inter-environment predictive ability using intra-population predictions reached 0.30 for yield, 0.65 for onset of flowering, 0.64 for seed weight, and 0.28 for lodging susceptibility. Using inter-population instead of intra-population predictions reduced the inter-environment predictive ability to 0.19 for grain yield, 0.40 for onset of flowering, 0.28 for seed weight, and 0.22 for lodging susceptibility. A comparison of GS vs phenotypic selection (PS) based on predicted genetic gains per unit time for same selection costs suggested greater efficiency of GS for all traits under various selection scenarios. For yield, the advantage in predicted efficiency of GS over PS was at least 80% using intra-population predictions and 20% using inter-population predictions. A genome-wide association study confirmed the highly polygenic control of most traits. CONCLUSIONS: Genome-enabled predictions can increase the efficiency of pea line selection for wide adaptation to Italian environments relative to phenotypic selection.

Heritabilities and genetic correlations in the same traits across different strata of herds created according to continuous genomic, genetic, and phenotypic descriptors.

The most common approach in dairy cattle to prove genotype by environment interactions is a multiple-trait model application, and considering the same traits in different environments as different traits. We enhanced such concepts by defining continuous phenotypic, genetic, and genomic herd descriptors, and applying random regression sire models. Traits of interest were test-day traits for milk yield, fat percentage, protein percentage, and somatic cell score, considering 267,393 records from 32,707 first-lactation Holstein cows. Cows were born in the years 2010 to 2013, and kept in 52 large-scale herds from 2 federal states of north-east Germany. The average number of genotyped cows per herd (45,613 single nucleotide polymorphism markers per cow) was 133.5 (range: 45 to 415 genotyped cows). Genomic herd descriptors were (1) the level of linkage disequilibrium (r2) within specific chromosome segments, and (2) the average allele frequency for single nucleotide polymorphisms in close distance to a functional mutation. Genetic herd descriptors were the (1) intra-herd inbreeding coefficient, and (2) the percentage of daughters from foreign sires. Phenotypic herd descriptors were (1) herd size, and (2) the herd mean for nonreturn rate. Most correlations among herd descriptors were close to 0, indicating independence of genomic, genetic, and phenotypic characteristics. Heritabilities for milk yield increased with increasing intra-herd linkage disequilibrium, inbreeding, and herd size. Genetic correlations in same traits between adjacent levels of herd descriptors were close to 1, but declined for descriptor levels in greater distance. Genetic correlation declines were more obvious for somatic cell score, compared with test-day traits with larger heritabilities (fat percentage and protein percentage). Also, for milk yield, alterations of herd descriptor levels had an obvious effect on heritabilities and genetic correlations. By trend, multiple trait model results (based on created discrete herd classes) confirmed the random regression estimates. Identified alterations of breeding values in dependency of herd descriptors suggest utilization of specific sires for specific herd structures, offering new possibilities to improve sire selection strategies. Regarding genomic selection designs and genetic gain transfer into commercial herds, cow herds for the utilization in cow training sets should reflect the genomic, genetic, and phenotypic pattern of the broad population.

Genotype × environment interaction on tocochromanol and plastochromanol-8 content in seeds of doubled haploids obtained from F1 hybrid black × yellow seeds of winter oilseed rape (Brassica napus L.).

BACKGROUND: The aim of the study was to determine the effect of genotype × environment interaction on the levels of α-, ß-, γ- and δ-tocopherol (α-T, ß-T, γ-T and δ-T, respectively) and plastochromanol-8 (PC-8) in seeds of 17 doubled haploids (DHs) obtained from the F1 hybrid derived from crossing black (DH H2 -26) × yellow (DH Z-114) seeds of winter oilseed rape. RESULTS: The content of tocopherols in the tested DH lines ranged from 415.6 to 540.1 mg kg-1 seeds, while PC-8 content ranged from 56.3 to 89.0 mg kg-1 seeds. The α-T/γ-T ratio reached a level of 0.78-1.29. Studies have shown that heritability for α-T, ß-T, γ-T, total-T and PC-8 is mainly due to genotypic variation. For the δ-T homologue the level was dependent on environmental effect. CONCLUSION: The obtained DH lines population of oilseed rape is characterized by high heritability coefficients for α-T, ß-T, γ-T, total-T and PC-8 levels, which indicates a greater influence of genotype than the environment on the content of these compounds. Among all studied doubled haploids, seven DHs were selected which were characterized by stable contents of α-T, ß-T, γ-T, δ-T and total-T with the simultaneous stable content of PC-8. © 2017 Society of Chemical Industry.

Genetic analyses using GGE model and a mixed linear model approach, and stability analyses using AMMI bi-plot for late-maturity alpha-amylase activity in bread wheat genotypes.

Low falling number and discounting grain when it is downgraded in class are the consequences of excessive late-maturity α-amylase activity (LMAA) in bread wheat (Triticum aestivum L.). Grain expressing high LMAA produces poorer quality bread products. To effectively breed for low LMAA, it is necessary to understand what genes control it and how they are expressed, particularly when genotypes are grown in different environments. In this study, an International Collection (IC) of 18 spring wheat genotypes and another set of 15 spring wheat cultivars adapted to South Dakota (SD), USA were assessed to characterize the genetic component of LMAA over 5 and 13 environments, respectively. The data were analysed using a GGE model with a mixed linear model approach and stability analysis was presented using an AMMI bi-plot on R software. All estimated variance components and their proportions to the total phenotypic variance were highly significant for both sets of genotypes, which were validated by the AMMI model analysis. Broad-sense heritability for LMAA was higher in SD adapted cultivars (53%) compared to that in IC (49%). Significant genetic effects and stability analyses showed some genotypes, e.g. 'Lancer', 'Chester' and 'LoSprout' from IC, and 'Alsen', 'Traverse' and 'Forefront' from SD cultivars could be used as parents to develop new cultivars expressing low levels of LMAA. Stability analysis using an AMMI bi-plot revealed that 'Chester', 'Lancer' and 'Advance' were the most stable across environments, while in contrast, 'Kinsman', 'Lerma52' and 'Traverse' exhibited the lowest stability for LMAA across environments.