Independent genetic control of maize (Zea mays L.) kernel weight determination and its phenotypic plasticity

ZmMPK6, a mitogen-activated protein kinase, regulates maize kernel weight

Kernel weight is a critical agronomic trait in maize production. Many genes are related to kernel weight but only a few of them have been applied to maize breeding and cultivation. Here, we identify a novel function of maize mitogen-activated protein kinase 6 (ZmMPK6) in the regulation of maize kernel weight. Kernel weight was reduced in zmmpk6 mutants and increased in ZmMPK6-overexpressing lines. In addition, starch granules, starch content, protein content, and grain-filling characteristics were also affected by the ZmMPK6 expression level. ZmMPK6 is mainly localized in the nucleus and cytoplasm, widely distributed across various tissues, and is expressed during kernel development, which is consistent with its role in kernel weight. Thus, these results provide new insights into the role of ZmMPK6, a mitogen-activated protein kinase, in maize kernel weight, and could be applied to further molecular breeding for kernel quality and yield in maize.

Phenotypic Plasticity of Yield and Yield-Related Traits Contributing to the Wheat Yield in a Doubled Haploid Population

Phenotypic plasticity is the ability of an individual genotype to express phenotype variably in different environments. This study investigated the plasticity of yield-related traits of bread wheat by utilising 225 doubled haploid (DH) lines developed from cv. Westonia and cv. Kauz, through two field trials in Western Australia. Plasticity was quantified via two previously published methods: responsiveness to varying ecological conditions and slopes of reaction norms. The spikelets/spike was the most plastic trait, with an overall plasticity of 1.62. The least plastic trait was grain protein content, with an overall plasticity of 0.79. The trait hierarchy based on phenotypic plasticity was spikelets/spike > thousand kernel weight > seed number > seed length > grain yield > grain protein content. An increase in yield plasticity of 0.1 was associated with an increase in maximum yield of 4.45 kg ha-1. The plasticity of seed number and grain protein content were significantly associated with yield plasticity. The maximal yield was positively associated with spikelets/spike and grain yield, whereas it negatively associated with grain protein content. In contrast, the minimal yield was found to be negatively related to the plasticity of spikelets/spike and the plasticity of grain yield, whereas it was not related to grain protein content plasticity. Seed number and seed length exhibited plastic responses at the higher fertilisation state while remaining relatively stable at the lower fertilisation state for the wheat DH population. The finding of the current study will play a key role in wheat improvement under the changing climate. Seed length and seed number should be the breeding target for achieving stable yield in adverse environmental conditions.

Complex genetic architecture underlying the plasticity of maize agronomic traits

Phenotypic plasticity is the ability of a given genotype to produce multiple phenotypes in response to changing environmental conditions. Understanding the genetic basis of phenotypic plasticity and establishing a predictive model is highly relevant to future agriculture under a changing climate. Here we report findings on the genetic basis of phenotypic plasticity for 23 complex traits using a diverse maize population planted at five sites with distinct environmental conditions. We found that latitude-related environmental factors were the main drivers of across-site variation in flowering time traits but not in plant architecture or yield traits. For the 23 traits, we detected 109 quantitative trait loci (QTLs), 29 for mean values, 66 for plasticity, and 14 for both parameters, and 80% of the QTLs interacted with latitude. The effects of several QTLs changed in magnitude or sign, driving variation in phenotypic plasticity. We experimentally validated one plastic gene, ZmTPS14.1, whose effect was likely mediated by the compensation effect of ZmSPL6 from a downstream pathway. By integrating genetic diversity, environmental variation, and their interaction into a joint model, we could provide site-specific predictions with increased accuracy by as much as 9.9%, 2.2%, and 2.6% for days to tassel, plant height, and ear weight, respectively. This study revealed a complex genetic architecture involving multiple alleles, pleiotropy, and genotype-by-environment interaction that underlies variation in the mean and plasticity of maize complex traits. It provides novel insights into the dynamic genetic architecture of agronomic traits in response to changing environments, paving a practical way toward precision agriculture.

Explaining pre-emptive acclimation by linking information to plant phenotype

We review mechanisms for pre-emptive acclimation in plants and propose a conceptual model linking developmental and evolutionary ecology with the acquisition of information through sensing of cues and signals. The idea is that plants acquire much of the information in the environment not from individual cues and signals but instead from their joint multivariate properties such as correlations. If molecular signalling has evolved to extract such information, the joint multivariate properties of the environment must be encoded in the genome, epigenome, and phenome. We contend that multivariate complexity explains why extrapolating from experiments done in artificial contexts into natural or agricultural systems almost never works for characters under complex environmental regulation: biased relationships among the state variables in both time and space create a mismatch between the evolutionary history reflected in the genotype and the artificial growing conditions in which the phenotype is expressed. Our model can generate testable hypotheses bridging levels of organization. We describe the model and its theoretical bases, and discuss its implications. We illustrate the hypotheses that can be derived from the model in two cases of pre-emptive acclimation based on correlations in the environment: the shade avoidance response and acclimation to drought.

Kernel weight contribution to yield genetic gain of maize: a global review and US case studies

Over the past century of maize (Zea mays L.) breeding, grain yield progress has been the result of improvements in several other intrinsic physiological and morphological traits. In this study, we describe (i) the contribution of kernel weight (KW) to yield genetic gain across multiple agronomic settings and breeding programs, and (ii) the physiological bases for improvements in KW for US hybrids. A global-scale literature review concludes that rates of KW improvement in US hybrids were similar to those of other commercial breeding programs but extended over a longer period of time. There is room for a continued increase of kernel size in maize for most of the genetic materials analysed, but the trade-off between kernel number and KW poses a challenge for future yield progress. Through phenotypic characterization of Pioneer Hi-Bred ERA hybrids in the USA, we determine that improvements in KW have been predominantly related to an extended kernel-filling duration. Likewise, crop improvement has conferred on modern hybrids greater KW plasticity, expressed as a better ability to respond to changes in assimilate availability. Our analysis of past trends and current state of development helps to identify candidate targets for future improvements in maize.

Genetic Architecture of Grain Yield-Related Traits in Sorghum and Maize

Grain size, grain number per panicle, and grain weight are crucial determinants of yield-related traits in cereals. Understanding the genetic basis of grain yield-related traits has been the main research object and nodal in crop science. Sorghum and maize, as very close C4 crops with high photosynthetic rates, stress tolerance and large biomass characteristics, are extensively used to produce food, feed, and biofuels worldwide. In this review, we comprehensively summarize a large number of quantitative trait loci (QTLs) associated with grain yield in sorghum and maize. We placed great emphasis on discussing 22 fine-mapped QTLs and 30 functionally characterized genes, which greatly hinders our deep understanding at the molecular mechanism level. This review provides a general overview of the comprehensive findings on grain yield QTLs and discusses the emerging trend in molecular marker-assisted breeding with these QTLs.

Has yield plasticity already been exploited by soybean breeding programmes in Argentina?

This study focuses on the impact of genetic improvement of seed yield plasticity in soybean (Glycine max L.) in high-yielding environments (between 4000 kg ha-1 and 7000 kg ha-1) of Central Argentina. The association between seed yield and its plasticity was analysed with (i) a historical collection of 148 genotypes released to the market between 1980 and 2013 and (ii) 165 currently available commercial genotypes. The impact on seed yield of soybean breeding programmes in Argentina reveals higher genetic progress of the lowest (1.7% year-1) rather than the highest yielding genotypes (0.9% year-1). At the same time, seed yield plasticity has been exploited indirectly. Increased seed yield plasticity over time contributed to a reduction in genotypic seed yield variability (P<0.0001). Seed yield plasticity was related to seed yield in high-yielding environments (>5500 kg ha-1). Plastic genotypes showed a positive correlation with the length of the seed-filling period (r=0.5), suggesting that a longer seed-filling period could be required to maximize seed yield plasticity under high-yielding environments. To increase productivity, clarifying the value of plasticity will aid genotype selection for target environments, as well as the development of high-yielding cultivars specifically adapted to high-yielding conditions.

Genomic-based root plasticity to enhance abiotic stress adaptation and edible yield in grain crops

Phenotypic plasticity refers to changes expressed by a genotype across different environments and is one of the major means by which plants cope with environmental variability. Multi-fold differences in phenotypic plasticity have been noted across crops, with wild ancestors and landraces being more plastic than crops when under stress. Plasticity in response to abiotic stress adaptation, plant architecture, physio-reproductive and quality traits are multi-genic (QTL). Plasticity QTL (pQTL) were either collocated with main effect QTL and QEI (QTL × environment interaction) or located independently from the main effect QTL. For example, variations in root plasticity have been successfully introgressed to enhance abiotic stress adaptation in rice. The independence of genetic control of a trait and of its plasticity suggests that breeders may select for high or low plasticity in combination with high or low performance of economically important traits. Trait plasticity in stressful environments may be harnessed through breeding stress-tolerant crops. There exists a genetic cost associated with plasticity, so a better understanding of the trade-offs between plasticity and productivity is warranted prior to undertaking breeding for plasticity traits together with productivity in stress environments.

Large-scale GWAS in sorghum reveals common genetic control of grain size among cereals

Grain size is a key yield component of cereal crops and a major quality attribute. It is determined by a genotype's genetic potential and its capacity to fill the grains. This study aims to dissect the genetic architecture of grain size in sorghum. An integrated genome-wide association study (GWAS) was conducted using a diversity panel (n = 837) and a BC-NAM population (n = 1421). To isolate genetic effects associated with genetic potential of grain size, rather than the genotype's capacity to fill the grains, a treatment of removing half of the panicle was imposed during flowering. Extensive and highly heritable variation in grain size was observed in both populations in 5 field trials, and 81 grain size QTL were identified in subsequent GWAS. These QTL were enriched for orthologues of known grain size genes in rice and maize, and had significant overlap with SNPs associated with grain size in rice and maize, supporting common genetic control of this trait among cereals. Grain size genes with opposite effect on grain number were less likely to overlap with the grain size QTL from this study, indicating the treatment facilitated identification of genetic regions related to the genetic potential of grain size. These results enhance understanding of the genetic architecture of grain size in cereal, and pave the way for exploration of underlying molecular mechanisms and manipulation of this trait in breeding practices.

Genetic architecture of phenotypic means and plasticities of kernel size and weight in maize

Genetic relationships between the phenotypic means and plasticities of kernel size and weight revealed the common genetic control of these traits in maize. Kernel size and weight are crucial components of grain yield in maize, and phenotypic plasticity in these traits facilitates adaptations to changing environments. Elucidating the genetic architecture of the mean phenotypic values and plasticities of kernel size and weight may be essential for breeding climate-robust maize varieties. Here, a maize nested association mapping (CN-NAM) population and association panel were grown in different environments. A joint linkage analysis and genome-wide association mapping were performed for five kernel size and weight phenotypic traits and two phenotypic plasticity measures. The mean phenotypes and plasticities were significantly correlated. The overall results of quantitative trait locus (QTL) and candidate gene analyses indicated moderate and high levels of common genetic control for the two traits. Furthermore, the mean phenotypes or plasticities of the hundred-kernel weight and volume were commonly regulated to a high degree. One pleiotropic locus on chromosome 10 simultaneously controlled the mean phenotypic values and plasticities of kernel size and weight. Therefore, the plasticity of kernel size and weight might be indirectly selected during maize breeding; however, selecting for high or low plasticity in combination with high or low mean phenotypic values of kernel size and weight traits may be difficult.

High-throughput method for ear phenotyping and kernel weight estimation in maize using ear digital imaging

BACKGROUND

Grain yield, ear and kernel attributes can assist to understand the performance of maize plant under different environmental conditions and can be used in the variety development process to address farmer's preferences. These parameters are however still laborious and expensive to measure.

RESULTS

A low-cost ear digital imaging method was developed that provides estimates of ear and kernel attributes i.e., ear number and size, kernel number and size as well as kernel weight from photos of ears harvested from field trial plots. The image processing method uses a script that runs in a batch mode on ImageJ; an open source software. Kernel weight was estimated using the total kernel number derived from the number of kernels visible on the image and the average kernel size. Data showed a good agreement in terms of accuracy and precision between ground truth measurements and data generated through image processing. Broad-sense heritability of the estimated parameters was in the range or higher than that for measured grain weight. Limitation of the method for kernel weight estimation is discussed.

CONCLUSION

The method developed in this work provides an opportunity to significantly reduce the cost of selection in the breeding process, especially for resource constrained crop improvement programs and can be used to learn more about the genetic bases of grain yield determinants.

Phenotypic plasticity and its genetic regulation for yield, nitrogen fixation and δ13C in chickpea crops under varying water regimes

We measured yield components, nitrogen fixation, soil nitrogen uptake and carbon isotope composition (δ(13)C) in a collection of chickpea genotypes grown in environments where water availability was the main source of yield variation. We aimed to quantify the phenotypic plasticity of these traits using variance ratios, and to explore their genetic basis using FST genome scan. Fifty-five genes in three genomic regions were found to be under selection for plasticity of yield; 54 genes in four genomic regions for the plasticity of seeds per m(2); 48 genes in four genomic regions for the plasticity of δ(13)C; 54 genes in two genomic regions for plasticity of flowering time; 48 genes in five genomic regions for plasticity of nitrogen fixation and 49 genes in three genomic regions for plasticity of nitrogen uptake from soil. Plasticity of yield was related to plasticity of nitrogen uptake from soil, and unrelated to plasticity of nitrogen fixation, highlighting the need for closer attention to nitrogen uptake in legumes. Whereas the theoretical link between δ(13)C and transpiration efficiency is strong, the actual link with yield is erratic due to trade-offs and scaling issues. Genes associated with plasticity of δ(13)C were identified that may help to untangle the δ(13)C-yield relationship. Combining a plasticity perspective to deal with complex G×E interactions with FST genome scan may help understand and improve both crop adaptation to stress and yield potential.

Breeding crops for improved mineral nutrition under climate change conditions

Improvements in understanding how climate change may influence chemical and physical processes in soils, how this may affect nutrient availability, and how plants may respond to changed availability of nutrients will influence crop breeding programmes. The effects of increased atmospheric CO2 and warmer temperatures, both individually and combined, on soil microbial activity, including mycorrhizas and N-fixing organisms, are evaluated, together with their implications for nutrient availability. Potential changes to plant growth, and the combined effects of soil and plant changes on nutrient uptake, are discussed. The organization of research on the efficient use of macro- and micronutrients by crops under climate change conditions is outlined, including analysis of QTLs for nutrient efficiency. Suggestions for how the information gained can be used in plant breeding programmes are given.