Biological nitrification inhibitor-trait enhances nitrogen uptake by suppressing nitrifier activity and improves ammonium assimilation in two elite wheat varieties.

Synthetic nitrification inhibitors (SNI) and biological nitrification inhibitors (BNI) are promising tools to limit nitrogen (N) pollution derived from agriculture. Modern wheat cultivars lack sufficient capacity to exude BNIs, but, fortunately, the chromosome region (Lr#n-SA) controlling BNI production in Leymus racemosus, a wild relative of wheat, was introduced into two elite wheat cultivars, ROELFS and MUNAL. Using BNI-isogenic-lines could become a cost-effective, farmer-friendly, and globally scalable technology that incentivizes more sustainable and environmentally friendly agronomic practices. We studied how BNI-trait improves N-uptake, and N-use, both with ammonium and nitrate fertilization, analysing representative indicators of soil nitrification inhibition, and plant metabolism. Synthesizing BNI molecules did not mean a metabolic cost since Control and BNI-isogenic-lines from ROELFS and MUNAL presented similar agronomic performance and plant development. In the soil, ROELFS-BNI and MUNAL-BNI plants decreased ammonia-oxidizing bacteria (AOB) abundance by 60% and 45% respectively, delaying ammonium oxidation without reducing the total abundance of bacteria or archaea. Interestingly, BNI-trait presented a synergistic effect with SNIs since made it also possible to decrease the AOA abundance. ROELFS-BNI and MUNAL-BNI plants showed a reduced leaf nitrate reductase (NR) activity as a consequence of lower soil NO 3 - formation and a higher amino acid content compared to BNI-trait lacking lines, indicating that the transfer of Lr#-SA was able to induce a higher capacity to assimilate ammonium. Moreover, the impact of the BNI-trait in wheat cultivars was also noticeable for nitrate fertilization, with improved N absorption, and therefore, reducing soil nitrate content.

Enlisting wild grass genes to combat nitrification in wheat farming: A nature-based solution.

Active nitrifiers and rapid nitrification are major contributing factors to nitrogen losses in global wheat production. Suppressing nitrifier activity is an effective strategy to limit N losses from agriculture. Production and release of nitrification inhibitors from plant roots is termed "biological nitrification inhibition" (BNI). Here, we report the discovery of a chromosome region that controls BNI production in "wheat grass" Leymus racemosus (Lam.) Tzvelev, located on the short arm of the "Lr#3Nsb" (Lr#n), which can be transferred to wheat as T3BL.3NsbS (denoted Lr#n-SA), where 3BS arm of chromosome 3B of wheat was replaced by 3NsbS of L. racemosus We successfully introduced T3BL.3NsbS into the wheat cultivar "Chinese Spring" (CS-Lr#n-SA, referred to as "BNI-CS"), which resulted in the doubling of its BNI capacity. T3BL.3NsbS from BNI-CS was then transferred to several elite high-yielding hexaploid wheat cultivars, leading to near doubling of BNI production in "BNI-MUNAL" and "BNI-ROELFS." Laboratory incubation studies with root-zone soil from field-grown BNI-MUNAL confirmed BNI trait expression, evident from suppression of soil nitrifier activity, reduced nitrification potential, and N2O emissions. Changes in N metabolism included reductions in both leaf nitrate, nitrate reductase activity, and enhanced glutamine synthetase activity, indicating a shift toward ammonium nutrition. Nitrogen uptake from soil organic matter mineralization improved under low N conditions. Biomass production, grain yields, and N uptake were significantly higher in BNI-MUNAL across N treatments. Grain protein levels and breadmaking attributes were not negatively impacted. Wide use of BNI functions in wheat breeding may combat nitrification in high N input-intensive farming but also can improve adaptation to low N input marginal areas.

Target Population of Environments for Wheat Breeding in India: Definition, Prediction and Genetic Gains.

In this study, we defined the target population of environments (TPE) for wheat breeding in India, the largest wheat producer in South Asia, and estimated the correlated response to the selection and prediction ability of five selection environments (SEs) in Mexico. We also estimated grain yield (GY) gains in each TPE. Our analysis used meteorological, soil, and GY data from the international Elite Spring Wheat Yield Trials (ESWYT) distributed by the International Maize and Wheat Improvement Center (CIMMYT) from 2001 to 2016. We identified three TPEs: TPE 1, the optimally irrigated Northwestern Plain Zone; TPE 2, the optimally irrigated, heat-stressed North Eastern Plains Zone; and TPE 3, the drought-stressed Central-Peninsular Zone. The correlated response to selection ranged from 0.4 to 0.9 within each TPE. The highest prediction accuracies for GY per TPE were derived using models that included genotype-by-environment interaction and/or meteorological information and their interaction with the lines. The highest prediction accuracies for TPEs 1, 2, and 3 were 0.37, 0.46, and 0.51, respectively, and the respective GY gains were 118, 46, and 123 kg/ha/year. These results can help fine-tune the breeding of elite wheat germplasm with stable yields to reduce farmers' risk from year-to-year environmental variation in India's wheat lands, which cover 30 million ha, account for 100 million tons of grain or more each year, and provide food and livelihoods for hundreds of millions of farmers and consumers in South Asia.

Genomic Selection for Grain Yield in the CIMMYT Wheat Breeding Program-Status and Perspectives.

Genomic breeding technologies offer new opportunities for grain yield (GY) improvement in common wheat. In this study, we have evaluated the potential of genomic selection (GS) in breeding for GY in wheat by modeling a large dataset of 48,562 GY observations from the International Maize and Wheat Improvement Center (CIMMYT), including 36 yield trials evaluated between 2012 and 2019 in Obregón, Sonora, Mexico. Our key objective was to determine the value that GS can add to the current three-stage yield testing strategy at CIMMYT, and we draw inferences from predictive modeling of GY using 420 different populations, environments, cycles, and model combinations. First, we evaluated the potential of genomic predictions for minimizing the number of replications and lines tested within a site and year and obtained mean prediction accuracies (PAs) of 0.56, 0.5, and 0.42 in Stages 1, 2, and 3 of yield testing, respectively. However, these PAs were similar to the mean pedigree-based PAs indicating that genomic relationships added no value to pedigree relationships in the yield testing stages, characterized by small family-sizes. Second, we evaluated genomic predictions for minimizing GY testing across stages/years in Obregón and observed mean PAs of 0.41, 0.31, and 0.37, respectively when GY in the full irrigation bed planting (FI BP), drought stress (DS), and late-sown heat stress environments were predicted across years using genotype × environment (G × E) interaction models. Third, we evaluated genomic predictions for minimizing the number of yield testing environments and observed that in Stage 2, the FI BP, full irrigation flat planting and early-sown heat stress environments (mean PA of 0.37 ± 0.12) and the reduced irrigation and DS environments (mean PA of 0.45 ± 0.07) had moderate predictabilities among them. However, in both predictions across years and environments, the PAs were inconsistent across years and the G × E models had no advantage over the baseline model with environment and line effects. Overall, our results provide excellent insights into the predictability of a quantitative trait like GY and will have important implications on the future design of GS for GY in wheat breeding programs globally.

Retrospective Quantitative Genetic Analysis and Genomic Prediction of Global Wheat Yields.

Breeding for grain yield (GY) in bread wheat at the International Maize and Wheat Improvement Center (CIMMYT) involves three-stage testing at Obregon, Mexico in different selection environments (SEs). To understand the efficiency of selection in the SEs, we performed a large retrospective quantitative genetics study using CIMMYT's yield trials evaluated in the SEs (2013-2014 to 2017-2018), the South Asia Bread Wheat Genomic Prediction Yield Trials (SABWGPYTs) evaluated in India, Pakistan, and Bangladesh (2014-2015 to 2017-2018), and the Elite Spring Wheat Yield Trials (ESWYTs) evaluated in several sites globally (2003-2004 to 2016-2017). First, we compared the narrow-sense heritabilities in the Obregon SEs and target sites and observed that the mean heritability in the SEs was 44.2 and 92.3% higher than the mean heritabilities in the SABWGPYT and ESWYT sites, respectively. Second, we observed significant genetic correlations between a SE in Obregon and all the five SABWGPYT sites and 65.1% of the ESWYT sites. Third, we observed high ratios of response to indirect selection in the SEs of Obregon with a mean of 0.80 ± 0.21 and 2.6 ± 5.4 in the SABWGPYT and ESWYT sites, respectively. Furthermore, our results also indicated that for all the SABWGPYT sites and 82% of the ESWYT sites, a response greater than 0.5 can be achieved by indirect selection for GY in Obregon. We also performed genomic prediction for GY in the target sites using the performance of the same lines in the SEs of Obregon and observed moderate mean prediction accuracies of 0.24 ± 0.08 and 0.28 ± 0.08 in the SABWGPYT and ESWYT sites, respectively using the genotype x environment (GxE) model. However, we observed similar accuracies using the baseline model with environment and line effects and no advantage of modeling GxE interactions. Overall, this study provides important insights into the suitability of the Obregon SEs in breeding for GY, while the variable genomic predictabilities of GY and the high year-to-year GY fluctuations reported, highlight the importance of multi-environment testing across time and space to stave off GxE induced uncertainties in varietal yields.

Novel Sources of Wheat Head Blast Resistance in Modern Breeding Lines and Wheat Wild Relatives.

Wheat head blast (WHB), caused by the fungus Magnaporthe oryzae pathotype triticum, is a devastating disease affecting South America and South Asia. Despite 30 years of intensive effort, the 2NVS translocation from Aegilops ventricosa contains the only useful source of resistance to WHB effective against M. oryzae triticum isolates. The objective of this study was to identify non-2NVS sources of resistance to WHB among elite cultivars, breeding lines, landraces, and wild-relative accessions. Over 780 accessions were evaluated under field and greenhouse conditions in Bolivia, greenhouse conditions in Brazil, and at two biosafety level-3 laboratories in the United States. The M. oryzae triticum isolates B-71 (2012), 008 (2015), and 16MoT001 (2016) were used for controlled experiments, while isolate 008 was used for field experiments. Resistant and susceptible checks were included in all experiments. Under field conditions, susceptible spreaders were inoculated at the tillering stage to guarantee sufficient inoculum. Disease incidence and severity were evaluated as the average rating for each 1-m-row plot. Under controlled conditions, heads were inoculated after full emergence and individually rated for percentage of diseased spikelets. The diagnostic marker Ventriup-LN2 was used to test for the presence of the 2NVS translocation. Four non-2NVS spring wheat International Maize and Wheat Improvement Center breeding lines (CM22, CM49, CM52, and CM61) and four wheat wild-relatives (A. tauschii TA10142, TA1624, TA1667, and TA10140) were identified as resistant (<5% of severity) or moderately resistant (5 to <25% severity) to WHB. Experiments conducted at the seedling stage showed little correlation with disease severity at the head stage. M. oryzae triticum isolate 16MoT001 was significantly more aggressive against 2NVS-based varieties. The low frequency of WHB resistance and the increase in aggressiveness of newer M. oryzae triticum isolates highlight the threat that the disease poses to wheat production worldwide and the urgent need to identify and characterize new resistance genes that can be used in breeding for durably resistant varieties.

Genetic Contribution of Synthetic Hexaploid Wheat to CIMMYT's Spring Bread Wheat Breeding Germplasm.

Synthetic hexaploid (SH) wheat (AABBD'D') is developed by artificially generating a fertile hybrid between tetraploid durum wheat (Triticum turgidum, AABB) and diploid wild goat grass (Aegilops tauschii, D'D'). Over three decades, the International Maize and Wheat Improvement Center (CIMMYT) has developed and utilized SH wheat to bridge gene transfer from Ae. tauschii and durum wheat to hexaploid bread wheat. This is a unique example of success utilizing wild relatives in mainstream breeding at large scale worldwide. Our study aimed to determine the genetic contribution of SH wheat to CIMMYT's global spring bread wheat breeding program. We estimated the theoretical and empirical contribution of D' to synthetic derivative lines using the ancestral pedigree and marker information using over 1,600 advanced lines and their parents. The average marker-estimated D' contribution was 17.5% with difference in genome segments suggesting application of differential selection pressure. The pedigree-based contribution was correlated with marker-based estimates without providing chromosome segment specific variation. Results from international yield trials showed that 20% of the lines were synthetic derived with an average D' contribution of 15.6%. Our results underline the importance of SH wheat in maintaining and enhancing genetic diversity and genetic gain over years and is important for development of a more targeted introgression strategy. The study provides retrospective view into development and utilization of SH in the CIMMYT Global Wheat Program.

Threat of wheat blast to South Asia's food security: An ex-ante analysis.

New biotic stresses have emerged around the globe over the last decades threatening food safety and security. In 2016, scientists confirmed the presence of the devastating wheat-blast disease in Bangladesh, South Asia-its first occurrence outside South America. Severely blast-affected wheat fields had their grain yield wiped out. This poses a severe threat to food security in a densely-populated region with millions of poor inhabitants where wheat is a major staple crop and per capita wheat consumption has been increasing. As an ex ante impact assessment, this study examined potential wheat-blast scenarios in Bangladesh, India, and Pakistan. Based on the agro-climatic conditions in the epicenter, where the disease was first identified in Bangladesh in 2016, this study identified the correspondingly vulnerable areas in India, Pakistan and Bangladesh amounting to 7 million ha. Assuming a conservative scenario of 5-10% for blast-induced wheat production loss, this study estimated the annual potential wheat loss across the sampled countries to be 0.89-1.77 million tons, equivalent to USD 132-264 million. Such losses further threaten an already-precarious national food security, putting pressure on wheat imports and wheat prices. The study is a call for action to tackle the real wheat-blast threat in South Asia.

Suppression of soil nitrification by plants.

Nitrification, the biological oxidation of ammonium to nitrate, weakens the soil's ability to retain N and facilitates N-losses from production agriculture through nitrate-leaching and denitrification. This process has a profound influence on what form of mineral-N is absorbed, used by plants, and retained in the soil, or lost to the environment, which in turn affects N-cycling, N-use efficiency (NUE) and ecosystem health and services. As reactive-N is often the most limiting in natural ecosystems, plants have acquired a range of mechanisms that suppress soil-nitrifier activity to limit N-losses via N-leaching and denitrification. Plants' ability to produce and release nitrification inhibitors from roots and suppress soil-nitrifier activity is termed 'biological nitrification inhibition' (BNI). With recent developments in methodology for in-situ measurement of nitrification inhibition, it is now possible to characterize BNI function in plants. This review assesses the current status of our understanding of the production and release of biological nitrification inhibitors (BNIs) and their potential in improving NUE in agriculture. A suite of genetic, soil and environmental factors regulate BNI activity in plants. BNI-function can be genetically exploited to improve the BNI-capacity of major food- and feed-crops to develop next-generation production systems with reduced nitrification and N2O emission rates to benefit both agriculture and the environment. The feasibility of such an approach is discussed based on the progresses made.

Research investment implications of shifts in the global geography of wheat stripe rust.

Breeding new crop varieties with resistance to the biotic stresses that undermine crop yields is tantamount to increasing the amount and quality of biological capital in agriculture. However, the success of genes that confer resistance to pests induces a co-evolutionary response that depreciates the biological capital embodied in the crop, as pests evolve the capacity to overcome the crop's new defences. Thus, simply maintaining this biological capital, and the beneficial production and economic outcomes it bestows, requires continual reinvestment in new crop defences. Here we use observed and modelled data on stripe rust occurrence to gauge changes in the geographic spread of the disease over recent decades. We document a significant increase in the spread of stripe rust since 1960, with 88% of the world's wheat production now susceptible to infection. Using a probabilistic Monte Carlo simulation model we estimate that 5.47 million tonnes of wheat are lost to the pathogen each year, equivalent to a loss of US$979 million per year. Comparing the cost of developing stripe-rust-resistant varieties of wheat with the cost of stripe-rust-induced yield losses, we estimate that a sustained annual research investment of at least US$32 million into stripe rust resistance is economically justified.

Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers.

The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed.

Investigating the efficiency of the single backcrossing breeding strategy through computer simulation.

A strategy combining single backcrossing with selected bulk breeding has been successfully used in wheat improvement at CIMMYT to introgress rust resistant genes from donor parents to elite adapted cultivars. In this research, the efficiency of this breeding strategy was compared to other crossing and selection strategies through computer simulation. Results indicated this breeding strategy has advantages in retaining or improving the adaptation of the recurrent parents, and at the same time transferring most of the desired donor genes in a wide range of scenarios. Two rounds of backcrossing have advantages when the adaptation of donor parents is much poorer than that of the adapted parents, but the advantage of three rounds of backcrossing over two rounds is minimal. We recommend using the single backcrossing breeding strategy (SBBS) when three conditions are met: (1) multiple genes govern the phenotypic traits to be transferred from donor parents to adapted parents, (2) the donor parents have some favorable genes that may contribute to the improvement of adaptation in the recipient parents, and (3) conventional phenotypic selection is being applied, or individual genotypes cannot be precisely identified. We envisage that all three conditions commonly exist in modern breeding programs, and therefore believe that SBBS could be applied widely. However, we do not exclude the use of repeated backcrossing if the transferred genes can be precisely identified by closely linked molecular markers, and the donor parents have extremely poor adaptation.