Breeding progress of nitrogen use efficiency of cereal crops, winter oilseed rape and peas in long-term variety trials.

KEY MESSAGE: Grain yield and NUE increased over time while nitrogen yield did not drop significantly despite reduced nitrogen input. Selection for grain and nitrogen yield is equivalent to selection for NUE. Breeding and registration of improved varieties with high yield, processing quality, disease resistance and nitrogen use efficiency (NUE) are of utmost importance for sustainable crop production to minimize adverse environmental impact and contribute to food security. Based on long-term variety trials of cereals, winter oilseed rape and grain peas tested across a wide range of environmental conditions in Germany, we quantified long-term breeding progress for NUE and related traits. We estimated the genotypic, environmental and genotype-by-environment interaction variation and correlation between traits and derived heritability coefficients. Nitrogen fertilizer application was considerably reduced between 1995 and 2021 in the range of 5.4% for winter wheat and 28.9% for spring wheat while for spring barley it was increased by 20.9%. Despite the apparent nitrogen reduction for most crops, grain yield (GYLD) and nitrogen accumulation in grain (NYLD) was increased or did not significantly decrease. NUE for GYLD increased significantly for all crops between 12.8% and 35.2% and for NYLD between 8% and 20.7%. We further showed that the genotypic rank of varieties for GYLD and NYLD was about equivalent to the genotypic rank of the corresponding traits of NUE, if all varieties in a trial were treated with the same nitrogen rate. Heritability of nitrogen yield was about the same as that of grain yield, suggesting that nitrogen yield should be considered as an additional criterion for variety testing to increase NUE and reduce negative environmental impact.

Long-term breeding progress of yield, yield-related, and disease resistance traits in five cereal crops of German variety trials.

KEY MESSAGE: Considerable breeding progress in cereal and disease resistances, but not in stem stability was found. Ageing effects decreased yield and increased disease susceptibility indicating that new varieties are constantly needed. Plant breeding and improved crop management generated considerable progress in cereal performance over the last decades. Climate change, as well as the political and social demand for more environmentally friendly production, require ongoing breeding progress. This study quantified long-term trends for breeding progress and ageing effects of yield, yield-related traits, and disease resistance traits from German variety trials for five cereal crops with a broad spectrum of genotypes. The varieties were grown over a wide range of environmental conditions during 1988-2019 under two intensity levels, without (I1) and with (I2) fungicides and growth regulators. Breeding progress regarding yield increase was the highest in winter barley followed by winter rye hybrid and the lowest in winter rye population varieties. Yield gaps between I2 and I1 widened for barleys, while they shrank for the other crops. A notable decrease in stem stability became apparent in I1 in most crops, while for diseases generally a decrasing susceptibility was found, especially for mildew, brown rust, scald, and dwarf leaf rust. The reduction in disease susceptibility in I2 (treated) was considerably higher than in I1. Our results revealed that yield performance and disease resistance of varieties were subject to considerable ageing effects, reducing yield and increasing disease susceptibility. Nevertheless, we quantified notable achievements in breeding progress for most disease resistances. This study indicated an urgent and continues need for new improved varieties, not only to combat ageing effects and generate higher yield potential, but also to offset future reduction in plant protection intensity.

Breeding progress of disease resistance and impact of disease severity under natural infections in winter wheat variety trials.

KEY MESSAGE: Breeding progress of resistance to fungal wheat diseases and impact of disease severity on yield reduction in long-term variety trials under natural infection were estimated by mixed linear regression models. This study aimed at quantifying breeding progress achieved in resistance breeding towards varieties with higher yield and lower susceptibility for 6 major diseases, as well as estimating decreasing yields and increasing disease susceptibility of varieties due to ageing effects during the period 1983-2019. A further aim was the prediction of disease-related yield reductions during 2005-2019 by mixed linear regression models using disease severity scores as covariates. For yield and all diseases, overall progress of the fully treated intensity (I2) was considerably higher than for the intensity without fungicides and growth regulators (I1). The disease severity level was considerably reduced during the study period for mildew (MLD), tan spot (DTR) and Septoria nodorum blotch (ear) (SNB) and to a lesser extent for brown (leaf) rust (BNR) and Septoria tritici blotch (STB), however, not for yellow/stripe rust (YLR). Ageing effects increased susceptibility of varieties strongly for BNR and MLD, but were comparatively weak for SNB and DTR. Considerable yield reductions under high disease severity were predicted for STB (-6.6%), BNR (-6.5%) and yellow rust (YLR, -5.8%), but lower reductions for the other diseases. The reduction for resistant vs. highly susceptible varieties under high severity conditions was about halved for BNR and YLR, providing evidence of resistance breeding progress. The empirical evidence on the functional relations between disease severity, variety susceptibility and yield reductions based on a large-scale multiple-disease field trial data set in German winter wheat is an important contribution to the ongoing discussion on fungicide use and its environmental impact.

Genetic gain for rice yield in rainfed environments in India.

The complexity of genotype × environment interactions under drought reduces heritability, which determines the effectiveness of selection for drought tolerance and development of drought tolerant varieties. Genetic progress measured through changes in yield performance over time is important in determining the efficiency of breeding programmes in which test cultivars are replaced each year on the assumption that the new cultivars will surpass the older cultivars. The goal of our study was to determine the annual rate of genetic gain for rice grain yield in a drought-prone rainfed system in a series of multi-environment trials conducted from 2005 to 2014 under the Drought Breeding Network of Indian sites in collaboration with the International Rice Research Institute (IRRI). Our results show a positive trend in grain yield with an annual genetic yield increase of about 0.68 % under irrigated control, 0.87 % under moderate reproductive stage drought stress and 1.9 % under severe reproductive stage drought stress due to breeding efforts. The study also demonstrates the effectiveness of direct selection for grain yield under both irrigated control as well as managed drought stress screening to improve yield in typical rainfed systems. IRRI's drought breeding programme has exhibited a significant positive trend in genetic gain for grain yield over the years under both drought stress as well as favorable irrigated control conditions. Several drought tolerant varieties released from the programme have outperformed the currently grown varieties under varied conditions in the rainfed environments on farmers' fields.

Novel strategies for genomic prediction of untested single-cross maize hybrids using unbalanced historical data.

KEY MESSAGE: Weighted outperformed unweighted genomic prediction using an unbalanced dataset representative of a commercial breeding program. Moreover, the use of the two cycles preceding predictions as training set achieved optimal prediction ability. Predicting the performance of untested single-cross hybrids through genomic prediction (GP) is highly desirable to increase genetic gain. Here, we evaluate the predictive ability (PA) of novel genomic strategies to predict single-cross maize hybrids using an unbalanced historical dataset of a tropical breeding program. Field data comprised 949 single-cross hybrids evaluated from 2006 to 2013, representing eight breeding cycles. Hybrid genotypes were inferred based on their parents' genotypes (inbred lines) using single-nucleotide polymorphism markers obtained via genotyping-by-sequencing. GP analyses were fitted using genomic best linear unbiased prediction via a stage-wise approach, considering two distinct cross-validation schemes. Results highlight the importance of taking into account the uncertainty regarding the adjusted means at each step of a stage-wise analysis, due to the highly unbalanced data structure and the expected heterogeneity of variances across years and locations of a commercial breeding program. Further, an increase in the size of the training set was not always advantageous even in the same breeding program. The use of the two cycles preceding predictions achieved optimal PA of untested single-cross hybrids in a forward prediction scenario, which could be used to replace the first step of field screening. Finally, in addition to the practical and theoretical results applied to maize hybrid breeding programs, the stage-wise analysis performed in this study may be applied to any crop historical unbalanced data.

A Novel Model to Explain Extreme Feather Pecking Behavior in Laying Hens.

Feather pecking (FP) is a serious economic and welfare problem in the domestic fowl. It has recently been shown that the distribution of FP bouts within groups is heterogeneous and contains a sub-population of extreme feather peckers (EFP). The present study proposed a novel model to detect EFP hens. A mixture of two negative binomial distributions was fitted to FP data of a F2 cross of about 960 hens, and, based on the results, a calculation of the posterior probability for each hen belonging to the EFP subgroup (pEFP) was done. The fit of the mixture distribution revealed that the EFP subgroup made up a proportion of one third of the F2 cross. The EFP birds came more frequently into pecking mood and showed higher pecking intensities compared to the remaining birds. Tonic immobility and emerge box tests were conducted at juvenile and adult age of the hens to relate fearfulness to EFP. After dichotomization, all traits were analyzed in a multivariate threshold model and a genomewide association study was performed. The new trait pEFP has a medium heritability of 0.35 and is positively correlated with the fear traits. Breeding for this new trait could be an interesting option to reduce the proportion of extreme feather peckers. An index of fear related traits might serve as a proxy to breed indirectly for pEFP. GWAS revealed that all traits are typical quantitative traits with many genes and small effects contributing to the genetic variance.

A robust DF-REML framework for variance components estimation in genetic studies.

MOTIVATION: In genetic association studies, linear mixed models (LMMs) are used to test for associations between phenotypes and candidate single nucleotide polymorphisms (SNPs). These same models are also used to estimate heritability, which is central not only to evolutionary biology but also to the prediction of the response to selection in plant and animal breeding, as well as the prediction of disease risk in humans. However, when one or more of the underlying assumptions are violated, the estimation of variance components may be compromised and therefore so may the estimates of heritability and any other functions of these. Considering that datasets obtained from real life experiments are prone to several sources of contamination, which usually induce the violation of the assumption of the normality of the errors, a robust derivative-free restricted-maximum likelihood framework (DF-REML) together with a robust coefficient of determination are proposed for the LMM in the context of genetic studies of continuous traits. RESULTS: The proposed approach, in addition to the robust estimation of variance components and robust computation of the coefficient of determination, allows in particular for the robust estimation of SNP-based heritability by reducing the bias and increasing the precision of its estimates. The performance of both classical and robust DF-REML approaches is compared via a Monte Carlo simulation study. Additionally, three examples of application of the methodologies to real datasets are given in order to validate the usefulness of the proposed robust approach. Although the main focus of this article is on plant breeding applications, the proposed methodology is applicable to both human and animal genetic studies. AVAILABILITY AND IMPLEMENTATION: Source code implemented in R is available in the Supplementary Material. CONTACT: vmml@fct.unl.pt. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection.

KEY MESSAGE: Simultaneous improvement of protein content and grain yield by index selection is possible but its efficiency largely depends on the weighting of the single traits. The genetic architecture of these indices is similar to that of the primary traits. Grain yield and protein content are of major importance in durum wheat breeding, but their negative correlation has hampered their simultaneous improvement. To account for this in wheat breeding, the grain protein deviation (GPD) and the protein yield were proposed as targets for selection. The aim of this work was to investigate the potential of different indices to simultaneously improve grain yield and protein content in durum wheat and to evaluate their genetic architecture towards genomics-assisted breeding. To this end, we investigated two different durum wheat panels comprising 159 and 189 genotypes, which were tested in multiple field locations across Europe and genotyped by a genotyping-by-sequencing approach. The phenotypic analyses revealed significant genetic variances for all traits and heritabilities of the phenotypic indices that were in a similar range as those of grain yield and protein content. The GPD showed a high and positive correlation with protein content, whereas protein yield was highly and positively correlated with grain yield. Thus, selecting for a high GPD would mainly increase the protein content whereas a selection based on protein yield would mainly improve grain yield, but a combination of both indices allows to balance this selection. The genome-wide association mapping revealed a complex genetic architecture for all traits with most QTL having small effects and being detected only in one germplasm set, thus limiting the potential of marker-assisted selection for trait improvement. By contrast, genome-wide prediction appeared promising but its performance strongly depends on the relatedness between training and prediction sets.

Statistical Models and Methods for Network Meta-Analysis.

Meta-analysis, the methodology for analyzing the results from multiple independent studies, has grown tremendously in popularity over the last four decades. Although most meta-analyses involve a single effect size (summary result, such as a treatment difference) from each study, there are often multiple treatments of interest across the network of studies in the analysis. Multi-treatment (or network) meta-analysis can be used for simultaneously analyzing the results from all the treatments. However, the methodology is considerably more complicated than for the analysis of a single effect size, and there have not been adequate explanations of the approach for agricultural investigations. We review the methods and models for conducting a network meta-analysis based on frequentist statistical principles, and demonstrate the procedures using a published multi-treatment plant pathology data set. A major advantage of network meta-analysis is that correlations of estimated treatment effects are automatically taken into account when an appropriate model is used. Moreover, treatment comparisons may be possible in a network meta-analysis that are not possible in a single study because all treatments of interest may not be included in any given study. We review several models that consider the study effect as either fixed or random, and show how to interpret model-fitting output. We further show how to model the effect of moderator variables (study-level characteristics) on treatment effects, and present one approach to test for the consistency of treatment effects across the network. Online supplemental files give explanations on fitting the network meta-analytical models using SAS.

Inferring relationships between Phosphorus utilization, feed per gain, and bodyweight gain in an F2 cross of Japanese quail using recursive models.

Phosphorus utilization (PU) has received considerable attention in poultry nutrition. However, reliable estimates of genetic parameters for PU and related traits have largely not been reported until now; however, these are needed to assess whether selection for an improved PU would result in selection response. A large Japanese quail F2 cross was generated and 888 F2 individuals were phenotyped for PU, bodyweight gain (BWG), and feed per gain (F:G). Because it can reasonably be assumed that the interrelationships between these traits are complex, structural equation models were used. The structural coefficient λij describes the rate of change of trait I with respect to trait j for a model with a recursive effect of trait j on trait i Three recursive structural coefficients (λF:G,PU,λBWG,PU,λBWG,F:G) were selected a priori based on biological knowledge. The model was fitted using ASReml software. Standard errors of estimated variance components and genetic parameters were approximated using the delta method. The heritability of PU, F:G, and BWG were 0.136, 0.118, and 0.092. The structural coefficient[Formula: see text]indicates that an increase in PU leads to reduced and thus improved F:G. The estimate[Formula: see text]indicates that improved F:G leads to an increase in BWG. The overall effect of PU on BWG was[Formula: see text]i.e. an increase in PU of 1% leads to an increase of BWG of 0.374 g in the data collection period, which spanned five days. The phenotypic and genetic correlations were negative between PU and F:G as well as between BWG and F:G and were positive between PU and BWG. These correlations are driven by direct genetic effects (pleiotropic genes or genes being in linkage disequilibrium) as well as by indirect genetic effects (genes affecting trait j affected indirectly trait i). The application of structural equation models contributed to our understanding of the complex biological relationship between PU, F:G, and BWG in quails. PU shows a heritability that is sufficient to achieve a selection response when breeding for this very-hard-to-measure trait.

Genetic parameters for feather pecking and aggressive behavior in a large F2-cross of laying hens using generalized linear mixed models.

Feather pecking and aggressive pecking is a well-known problem in egg production. In the present study, genetic parameters for 4 feather-pecking-related traits were estimated using generalized linear mixed models. The traits were bouts of feather pecking delivered (FPD), bouts of feather pecking received (FPR), bouts of aggressive pecking delivered (APD), and bouts of aggressive pecking received (APR). An F2-design was established from 2 divergent selected founder lines. The lines were selected for low or high feather pecking for 10 generations. The number of F2 hens was 910. They were housed in pens with around 40 birds. Each pen was observed in 21 sessions of 20 min, distributed over 3 consecutive days. An animal model was applied that treated the bouts observed within 20 min as repeated observations. An over-dispersed Poisson distribution was assumed for observed counts and the link function was a log link. The model included a random animal effect, a random permanent environment effect, and a random day-by-hen effect. Residual variance was approximated on the link scale by the delta method. The results showed a heritability around 0.10 on the link scale for FPD and APD and of 0.04 for APR. The heritability of FPR was zero. For all behavior traits, substantial permanent environmental effects were observed. The approximate genetic correlation between FPD and APD (FPD and APR) was 0.81 (0.54). Egg production and feather eating records were collected on the same hens as well and were analyzed with a generalized linear mixed model, assuming a binomial distribution and using a probit link function. The heritability on the link scale for egg production was 0.40 and for feather eating 0.57. The approximate genetic correlation between FPD and egg production was 0.50 and between FPD and feather eating 0.73. Selection might help to reduce feather pecking, but this might result in an unfavorable correlated selection response reducing egg production. Feather eating and feather pecking are genetically correlated and this needs further investigation.

Effect of feeding level on ileal and total tract digestibility of nutrients and energy from soybean meal-based diets for piglets.

A total of 36 piglets with an initial body weight (BW) of 5.6 ± 0.7 kg, fitted with simple T-cannulas at the distal ileum, were used to evaluate the effect of three graded feeding levels (50, 75 or 100 g/kg BW(0.75) day) on apparent ileal digestibility (AID) and total tract digestibility (ATTD) of dry matter (DM), nitrogen (N) and energy, and on ATTD of organic matter (OM), ether extracts (EE), neutral detergent fibre (NDF), acid detergent fibre (ADF) and digestible (DE), metabolisable (ME) and net energy (NE) content in soybean meal (SBM)-casein-cornstarch-based diets. The AID of DM, N and energy and ATTD of NDF, ADF and EE in the diets were not affected (p > 0.05) by the feed intake (FI) level. There was a small decrease in ATTD of DM, N (CP), OM, ash and energy, and in DE, ME and NE content in the diets (p < 0.05) with increasing FI level. The net disappearance in the large intestine (in % of ileal recovery) decreased for DM, N and energy (p < 0.05) with increasing FI level. The design of the study allowed for estimating ileal endogenous loss of N and total tract endogenous loss of ash, N and EE, for estimating corresponding true ileal and total tract digestibility values, and for estimating urinary endogenous N loss. High variability in estimates of ileal endogenous N loss and total tract endogenous losses of N, EE and ash reflects great variation in individual endogenous losses between animals. Estimation of true total tract digestibility of N, EE and ash by regression analysis was affected by their decrease in ATTD with increasing FI level, as estimates for true digestibility were lower compared to their apparent values. The present results suggest that FI level can affect both apparent and true total tract nutrient digestibility in piglets.

QTL detection power of multi-parental RIL populations in Arabidopsis thaliana.

A major goal of today's biology is to understand the genetic basis of quantitative traits. This can be achieved by statistical methods that evaluate the association between molecular marker variation and phenotypic variation in different types of mapping populations. The objective of this work was to evaluate the statistical power of quantitative trait loci (QTL) detection of various multi-parental mating designs, as well as to assess the reasons for the observed differences. Our study was based on an empirical data of 20 Arabidopsis thaliana accessions, which have been selected to capture the maximum genetic diversity. The examined mating designs differed strongly with respect to the statistical power to detect QTL. We observed the highest power to detect QTL for the diallel cross with random mating design. The results of our study suggested that performing sibling mating within subpopulations of joint-linkage mapping populations has the potential to considerably increase the power for QTL detection. Our results, however, revealed that using designs in which more than two parental alleles segregate in each subpopulation increases the power even more.

The use of two-way linear mixed models in multitreatment meta-analysis.

Meta-analysis summarizes the results of a series of trials. When more than two treatments are included in the trials and when the set of treatments tested differs between trials, the combination of results across trials requires some care. Several methods have been proposed for this purpose, which feature under different labels, such as network meta-analysis or mixed treatment comparisons. Two types of linear mixed model can be used for meta-analysis. The one expresses the expected outcome of treatments as a contrast to a baseline treatment. The other uses a classical two-way linear predictor with main effects for treatment and trial. In this article, we compare both types of model and explore under which conditions they give equivalent results. We illustrate practical advantages of the two-way model using two published datasets. In particular, it is shown that between-trial heterogeneity as well as inconsistency between different types of trial is straightforward to account for.

A general method for controlling the genome-wide type I error rate in linkage and association mapping experiments in plants.

Control of the genome-wide type I error rate (GWER) is an important issue in association mapping and linkage mapping experiments. For the latter, different approaches, such as permutation procedures or Bonferroni correction, were proposed. The permutation test, however, cannot account for population structure present in most association mapping populations. This can lead to false positive associations. The Bonferroni correction is applicable, but usually on the conservative side, because correlation of tests cannot be exploited. Therefore, a new approach is proposed, which controls the genome-wide error rate, while accounting for population structure. This approach is based on a simulation procedure that is equally applicable in a linkage and an association-mapping context. Using the parameter settings of three real data sets, it is shown that the procedure provides control of the GWER and the generalized genome-wide type I error rate (GWER(k)).

Molecular marker assisted broadening of the Central European heterotic groups in rye with Eastern European germplasm.

Broadening the genetic base of heterotic pools is a key to ensure continued genetic gains in hybrid breeding and extend hybrid cultivation to new areas. In the present study, two Central European heterotic pools (Carsten and Petkus) and five Eastern European open-pollinated varieties (OPVs, Pop-1 to Pop-5) were studied with the objectives to (1) investigate the genetic diversity in OPVs and the heterotic pools using molecular and field data, (2) evaluate the molecular diversity among OPVs, (3) examine the combining ability for grain yield of the OPVs when crossed with testers in field trials, and (4) develop a strategy for targeted introgression of OPV germplasm into the heterotic pools. In total, 610 S(0) plants, 347 from OPVs and 263 from heterotic pools, were developed. Clones of the S(0) plants of OPVs were crossed with two testers belonging to each heterotic pool, while clones of heterotic pools were crossed with only the opposite tester. Testcrosses were evaluated for grain yield in multi-location trials. In addition, 589 S(0) plants were fingerprinted with 30 SSR markers. The data revealed that the Carsten pool has a narrow genetic base and should be the primary target for broadening the established heterotic pattern. Mean and genetic variance suggested that Pop-2 and Pop-4 are good candidates for introgression in Petkus pool and Pop-5 in Carsten pool. Nevertheless, introgression of Pop-5 in Carsten could reduce the genetic diversity between heterotic pools. Therefore, we suggest that either selected plants of Pop-5 should be introgressed or more Eastern European germplasm should be fingerprinted and field evaluated to identify promising germplasm for broadening the established heterotic pattern.

Variation explained in mixed-model association mapping.

Genomic mapping of complex traits across species demands integrating genetics and statistics. In particular, because it is easily interpreted, the R(2) statistic is commonly used in quantitative trait locus (QTL) mapping studies to measure the proportion of phenotypic variation explained by molecular markers. Mixed models with random polygenic effects have been used in complex trait dissection in different species. However, unlike fixed linear regression models, linear mixed models have no well-established R(2) statistic for assessing goodness-of-fit and prediction power. Our objectives were to assess the performance of several R(2)-like statistics for a linear mixed model in association mapping and to identify any such statistic that measures model-data agreement and provides an intuitive indication of QTL effect. Our results showed that the likelihood-ratio-based R(2) (R(LR)(2)) satisfies several critical requirements proposed for the R(2)-like statistic. As R(LR)(2) reduces to the regular R(2) for fixed models without random effects other than residual, it provides a general measure for the effect of QTL in mixed-model association mapping. Moreover, we found that R(LR)(2) can help explain the overlap between overall population structure modeled as fixed effects and relative kinship modeled though random effects. As both approaches are derived from molecular marker information and are not mutually exclusive, comparing R(LR)(2) values from different models provides a logical bridge between statistical analysis and underlying genetics of complex traits.

Genetic and economic evaluation of a basic breeding programme for Kenya Boran cattle.

The objective of this study is to describe the present organisational structure of Boran cattle breeding and develop a model breeding programme using a deterministic approach under the current structure of the Boran Cattle Breeders Society. A breeding unit of 13,000 cows supplying bulls to a commercial population of 39,000 cows was assumed. Selection criteria used were growth and reproduction traits while breeding objective traits targeted were growth, carcass, reproduction, survival, milk yield and feed intake traits. Higher selection intensity was possible for breeding sires resulting in higher genetic gains compared to dams even though selection accuracies were generally low. Annual genetic gains were positive except for dressing percentage, cow survival rate, and age at first calving. However, a reduction of age at first calving by 9.5 days obtained a return of Ksh 49.76. The overall monetary genetic gain obtained was Ksh 84.89 with a profit per cow per year of Ksh 377.98. The basic breeding programme could be expanded to accommodate a larger population of Boran cattle. The implications of the results are also discussed.

'Influence of conflicts of interest on public positions in the COVID-19 era, the case of Gilead Sciences' by Roussel and Raoult (2020).

Roussel and Raoult (2020) assessed the correlation between public positions taken by 98 doctors towards hydroxychloroquine and payments received from the Gilead Sciences company. The analysis presented has two major problems, the first of which can probably be fixed retrospectively, but the second of which seems irredeemable.