Technological perspectives for plant breeding

Genetic variation for grain nutritional profile and yield potential in sorghum and the possibility of selection for drought tolerance under irrigated conditions

BACKGROUND

Increasing grain nutritional value in sorghum (Sorghum bicolor) is a paramount breeding objective, as is increasing drought resistance (DR), because sorghum is grown mainly in drought-prone areas. The genetic basis of grain nutritional traits remains largely unknown. Marker-assisted selection using significant loci identified through genome-wide association study (GWAS) shows potential for selecting desirable traits in crops. This study assessed natural variation available in sorghum accessions from around the globe to identify novel genes or genomic regions with potential for improving grain nutritional value, and to study associations between DR traits and grain weight and nutritional composition.

RESULTS

We dissected the genetic architecture of grain nutritional composition, protein content, thousand-kernel weight (TKW), and plant height (PH) in sorghum through GWAS of 163 unique African and Asian accessions under irrigated and post-flowering drought conditions. Several QTLs were detected. Some were significantly associated with DR, TKW, PH, protein, and Zn, Mn, and Ca contents. Genomic regions on chromosomes 1, 2, 4, 8, 9, and 10 were associated with TKW, nutritional, and DR traits; colocalization patterns of these markers indicate potential for simultaneous improvement of these traits. In African accessions, markers associated with TKW were mapped to six regions also associated with protein, Zn, Ca, Mn, Na, and DR, suggesting the potential for simultaneous selection for higher grain nutrition and TKW. Our results indicate that it may be possible to select for increased DR on the basis of grain nutrition and weight potential.

CONCLUSIONS

This study provides a valuable resource for selecting landraces for use in plant breeding programs and for identifying loci that may contribute to grain nutrition and weight with the hope of producing cultivars that combine improved yield traits, nutrition, and DR.

Recent advancements in the breeding of sorghum crop: current status and future strategies for marker-assisted breeding

Sorghum is emerging as a model crop for functional genetics and genomics of tropical grasses with abundant uses, including food, feed, and fuel, among others. It is currently the fifth most significant primary cereal crop. Crops are subjected to various biotic and abiotic stresses, which negatively impact on agricultural production. Developing high-yielding, disease-resistant, and climate-resilient cultivars can be achieved through marker-assisted breeding. Such selection has considerably reduced the time to market new crop varieties adapted to challenging conditions. In the recent years, extensive knowledge was gained about genetic markers. We are providing an overview of current advances in sorghum breeding initiatives, with a special focus on early breeders who may not be familiar with DNA markers. Advancements in molecular plant breeding, genetics, genomics selection, and genome editing have contributed to a thorough understanding of DNA markers, provided various proofs of the genetic variety accessible in crop plants, and have substantially enhanced plant breeding technologies. Marker-assisted selection has accelerated and precised the plant breeding process, empowering plant breeders all around the world.

Priming crop plants with rosemary (Salvia rosmarinus Spenn, syn Rosmarinus officinalis L.) extract triggers protective defense response against pathogens

Plant bioactive compounds provide novel straightforward approaches to control plant diseases. Rosemary (Salvia rosmarinus)-derived extracts carry many prominent pharmacological activities, including antimicrobial and antioxidant, mainly due to its phenolic compounds, rosmarinic acid (RA), carnosic acid and carnosol. However, the effects of these extracts on plant diseases are still unknown, which constrains its potential application as bioprotectant in the agricultural production. In this study we demonstrate the antiviral effect of the aqueous rosemary extract (ARE) against tobacco necrosis virus strain A (TNVA) in ARE-treated tobacco (Nicotiana tabacum) plants. Our results show that ARE-treatment enhances plant defense response, contributing to reduce virus replication and systemic movement in tobacco plants. RA, the main phenolic compound detected in this extract, is one of the main inducers of TNVA control. The ARE-induced protection in TNVA-infected plants was characterized by the expression of H₂O₂ scavengers and defense-related genes, involving salicylic acid- and jasmonic acid-regulated pathways. Furthermore, treatment with ARE in lemon (Citrus limon) and soybean (Glycine max) leaves protects the plants against Xanthomonas citri subsp. citri and Diaporthe phaseolorum var. meridionalis, respectively. Additionally, ARE treatment also promotes growth and development, suggesting a biostimulant activity in soybean. These results open the way for the potential use of ARE as a bioprotective agent in disease management.

Climate change challenges plant breeding

Plant breeding is important to cope with climate change impacts, complementing crop management and policy interventions to ensure global food production. However, changes in environmental factors also affect the objectives, efficiency, and genetic gains of the current plant breeding system. In this review, we summarize the challenges prompted by climate change to breeding climate-resilient crops and the limitations of the next-generation breeding approach in addressing climate change. It is anticipated that the integration of multi-disciplines and technologies into three schemes of genotyping, phenotyping, and envirotyping will result in the delivery of climate change-ready crops in less time.

The extended day length promotes earlier flowering of bermudagrass

Day length is a very critical environmental factor affecting plant growth and development. The extension of light application time has been shown to promote flowering in the long-day plant and to shorten breeding time in some crops. However, previous research on the regulation of bermudagrass flowering by light application time is scarce. Therefore, this study investigated the effect of day length on the growth and flowering of bermudagrass by prolonging the light application time in a controlled greenhouse. Three different light application times were set up in the experiment: 22/2 h (22 hours light/2 hours dark), 18/6 h (18 hours light/6 hours dark), 14/10 h (14 hours light/10 hours dark). Results showed that extending the light application time not only promoted the growth of bermudagrass (plant height, fresh weight, dry weight) but also its nutrient uptake (nitrogen (N) and phosphorous (P) content). In addition, daily light integrals were different when flowering under different light application times. Most importantly, under the 22/2 h condition, flowering time was successfully reduced to 44 days for common bermudagrass (Cynodon dactylon [L.] pers) genotype A12359 and 36 days for African bermudagrass (Cynodon transvaalensis Burtt-Davy) genotype ABD11. This study demonstrated a successful method of bermudagrass flowering earlier than usual time by manipulating light application time which may provide useful insights for bermudagrass breeding.

Integrating speed breeding with artificial intelligence for developing climate-smart crops

INTRODUCTION

In climate change, breeding crop plants with improved productivity, sustainability, and adaptability has become a daunting challenge to ensure global food security for the ever-growing global population. Correspondingly, climate-smart crops are also the need to regulate biomass production, which is imperative for the maintenance of ecosystem services worldwide. Since conventional breeding technologies for crop improvement are limited, time-consuming, and involve laborious selection processes to foster new and improved crop varieties. An urgent need is to accelerate the plant breeding cycle using artificial intelligence (AI) to depict plant responses to environmental perturbations in real-time.

MATERIALS AND METHODS

The review is a collection of authorized information from various sources such as journals, books, book chapters, technical bulletins, conference papers, and verified online contents.

CONCLUSIONS

Speed breeding has emerged as an essential strategy for accelerating the breeding cycles of crop plants by growing them under artificial light and temperature conditions. Furthermore, speed breeding can also integrate marker-assisted selection and cutting-edged gene-editing tools for early selection and manipulation of essential crops with superior agronomic traits. Scientists have recently applied next-generation AI to delve deeper into the complex biological and molecular mechanisms that govern plant functions under environmental cues. In addition, AIs can integrate, assimilate, and analyze complex OMICS data sets, an essential prerequisite for successful speed breeding protocol implementation to breed crop plants with superior yield and adaptability.

Custom-made design of metabolite composition in N. benthamiana leaves using CRISPR activators

Transcriptional regulators based on CRISPR architecture expand our ability to reprogramme endogenous gene expression in plants. One of their potential applications is the customization of plant metabolome through the activation of selected enzymes in a given metabolic pathway. Using the previously described multiplexable CRISPR activator dCasEV2.1, we assayed the selective enrichment in Nicotiana benthamiana leaves of four different flavonoids, namely, naringenin, eriodictyol, kaempferol, and quercetin. After careful selection of target genes and guide RNAs combinations, we created successful activation programmes for each of the four metabolites, each programme activating between three and seven genes, and with individual gene activation levels ranging from 4- to 1500-fold. Metabolic analysis of the flavonoid profiles of each multigene activation programme showed a sharp and selective enrichment of the intended metabolites and their glycosylated derivatives. Remarkably, principal component analysis of untargeted metabolic profiles clearly separated samples according to their activation treatment, and hierarchical clustering separated the samples into five groups, corresponding to the expected four highly enriched metabolite groups, plus an un-activated control. These results demonstrate that dCasEV2.1 is a powerful tool for re-routing metabolic fluxes towards the accumulation of metabolites of interest, opening the door for the custom-made design of metabolic contents in plants.

Comparison of single-trait and multi-trait genomic predictions on agronomic and disease resistance traits in spring wheat

This study performed comprehensive analyses on the predictive abilities of single-trait and two multi-trait models in three populations. Our results demonstrated the superiority of multi-traits over single-trait models across seven agronomic and four to seven disease resistance traits of different genetic architecture. The predictive ability of multi-trait and single-trait prediction models has not been investigated on diverse traits evaluated under organic and conventional management systems. Here, we compared the predictive abilities of 25% of a testing set that has not been evaluated for a single trait (ST), not evaluated for multi-traits (MT1), and evaluated for some traits but not others (MT2) in three spring wheat populations genotyped either with the wheat 90K single nucleotide polymorphisms array or DArTseq. Analyses were performed on seven agronomic traits evaluated under conventional and organic management systems, four to seven disease resistance traits, and all agronomic and disease resistance traits simultaneously. The average prediction accuracies of the ST, MT1, and MT2 models varied from 0.03 to 0.78 (mean 0.41), from 0.05 to 0.82 (mean 0.47), and from 0.05 to 0.92 (mean 0.67), respectively. The predictive ability of the MT2 model was significantly greater than the ST model in all traits and populations except common bunt with the MT1 model being intermediate between them. The MT2 model increased prediction accuracies over the ST and MT1 models in all traits by 9.0-82.4% (mean 37.3%) and 2.9-82.5% (mean 25.7%), respectively, except common bunt that showed up to 7.7% smaller accuracies in two populations. A joint analysis of all agronomic and disease resistance traits further improved accuracies within the MT1 and MT2 models on average by 21.4% and 17.4%, respectively, as compared to either the agronomic or disease resistance traits, demonstrating the high potential of the multi-traits models in improving prediction accuracies.

Induction of useful mutations in Triticum aestivum in the conditions of the radionuclide-contaminated alienation zone of the Chornobyl Power Plant

Induced mutagenesis opens great perspectives for radical genetic improvement of cultivated plants. Scientists seeking new sources and methodological approaches to improve the frequency and extend the range of mutations have drawn attention to the Zone of Alienation around the Chornobyl Nuclear Power Plant, where unique conditions of the influence of mutagenic factors have developed, and therefore needs to be studied for possible use of its territory in propagating parent material for selective breeding of wheat. Plants of winter wheat of Albatros Odesky and Zymoiarka varieties were grown within 10 km of the Chernobyl Plant, inside the Alienation Zone, in Chystohalivka, Kopachi and Yaniv villages of Chornobyl district of Kyiv Oblast. The exposure occurred in the dose of 7.2 ∙ 10–12– 50.0 ∙ 10–12 A/kg. As the control, we used the territory of the Research Institute of Physiology of Plants and Genetics of the Academy of Sciences of Ukraine (Hlevaha urbanized settlement of Vasylkivsky District of Kyiv Oblast), where the power of the exposure dose equaled 0.93 ∙ 10–12 A/kg. Frequency and spectrum of mutant forms were determined in M2–M3 generations according to the ratio of the number of families with mutagenic plants to studied M2 families. Among the observed mutations, we determined the share of the ones important for selective breeding. Chronic ionizing radiation throughout the vegetation period of winter wheat increased the level of noticeable mutations, the frequency of which exceeded the control parameters by 8.0–14.9 times. In the conditions of cultivation of winter wheat in the territory of Kopachi village, where the dose was the lowest, we recorded a high level of mutation variability which exceeded the control parameters by 8.0–9.2 times and was notably different from the frequency of mutations induced by radionuclide contamination of soil in the territories of Chystohalivka and Yaniv villages. The mutation range contained 12–20 types and depended on the density of soil contamination with radio nuclides, magnitude of exposure dose and genotype of plants. The predominant mutations were the ones related to the duration of vegetation period, length of the stem, morphology and awns of the ear. Among the detected mutations, the important selective ones accounted for 24.3–49.3%, predominant being low height, intense growth and long cylindrical ear. Because beneficial agronomic traits are highly likely to be inherited in complex with mutations that reduce the productivity of winter wheat, efficiency of direct selection of mutant forms that are valuable for selective breeding is limited. Enlargement of genetic diversity of the initial selection material using the radionuclide-induced mutagenesis resulting from contamination creates the possibility of using it in cross breeding for the purpose of implementing selective breeding genetic programs of improving wheat varieties.

Evaluation of RGB and Multispectral Unmanned Aerial Vehicle (UAV) Imagery for High-Throughput Phenotyping and Yield Prediction in Barley Breeding

With advances in plant genomics, plant phenotyping has become a new bottleneck in plant breeding and the need for reliable high-throughput plant phenotyping techniques has emerged. In the face of future climatic challenges, it does not seem appropriate to continue to solely select for grain yield and a few agronomically important traits. Therefore, new sensor-based high-throughput phenotyping has been increasingly used in plant breeding research, with the potential to provide non-destructive, objective and continuous plant characterization that reveals the formation of the final grain yield and provides insights into the physiology of the plant during the growth phase. In this context, we present the comparison of two sensor systems, Red-Green-Blue (RGB) and multispectral cameras, attached to unmanned aerial vehicles (UAV), and investigate their suitability for yield prediction using different modelling approaches in a segregating barley introgression population at three environments with weekly data collection during the entire vegetation period. In addition to vegetation indices, morphological traits such as canopy height, vegetation cover and growth dynamics traits were used for yield prediction. Repeatability analyses and genotype association studies of sensor-based traits were compared with reference values from ground-based phenotyping to test the use of conventional and new traits for barley breeding. The relative height estimation of the canopy by UAV achieved high precision (up to r = 0.93) and repeatability (up to R2 = 0.98). In addition, we found a great overlap of detected significant genotypes between the reference heights and sensor-based heights. The yield prediction accuracy of both sensor systems was at the same level and reached a maximum prediction accuracy of r2 = 0.82 with a continuous increase in precision throughout the entire vegetation period. Due to the lower costs and the consumer-friendly handling of image acquisition and processing, the RGB imagery seems to be more suitable for yield prediction in this study.

Sorghum breeding in the genomic era: opportunities and challenges

The importance and potential of the multi-purpose crop sorghum in global food security have not yet been fully exploited, and the integration of the state-of-art genomics and high-throughput technologies into breeding practice is required. Sorghum, a historically vital staple food source and currently the fifth most important major cereal, is emerging as a crop with diverse end-uses as food, feed, fuel and forage and a model for functional genetics and genomics of tropical grasses. Rapid development in high-throughput experimental and data processing technologies has significantly speeded up sorghum genomic researches in the past few years. The genomes of three sorghum lines are available, thousands of genetic stocks accessible and various genetic populations, including NAM, MAGIC, and mutagenised populations released. Functional and comparative genomics have elucidated key genetic loci and genes controlling agronomical and adaptive traits. However, the knowledge gained has far away from being translated into real breeding practices. We argue that the way forward is to take a genome-based approach for tailored designing of sorghum as a multi-functional crop combining excellent agricultural traits for various end uses. In this review, we update the new concepts and innovation systems in crop breeding and summarise recent advances in sorghum genomic researches, especially the genome-wide dissection of variations in genes and alleles for agronomically important traits. Future directions and opportunities for sorghum breeding are highlighted to stimulate discussion amongst sorghum academic and industrial communities.

Harnessing Sorghum Landraces to Breed High-Yielding, Grain Mold-Tolerant Cultivars With High Protein for Drought-Prone Environments

Intermittent drought and an incidence of grain mold disease are the two major constraints affecting sorghum production and productivity. The study aimed at developing drought-tolerant sorghum varieties possessing a high protein content and tolerance to grain mold with stable performance using additive main effects and multiplicative interaction (AMMI) and genotype and genotype × environment interaction (GGE) biplot methods. Systematic hybridization among the 11 superior landraces resulted in subsequent pedigree-based breeding and selection from 2010 to 2015 evolved 19 promising varieties of grains such as white, yellow, and brown pericarp grains. These grain varieties were evaluated for their adaptability and stability for yield in 13 rainfed environments and for possessing tolerance to grain mold in three hot spot environments. A variety of yellow pericarp sorghum PYPS 2 (3,698 kg/ha; 14.52% protein; 10.70 mg/100 g Fe) possessing tolerance to grain mold was identified as a stable variety by using both AMMI and GGE analyses. Four mega-environments were identified for grain yield and fodder yield. Sorghum varieties PYPS 2, PYPS 4, PYPS 8, and PYPS 11 were highly stable in E2 with a low grain mold incidence. Besides meeting the nutritional demand of smallholder farmers under dryland conditions, these varieties are suitable for enhancing sorghum productivity under the present climate change scenario.

A novel way to identify specific powdery mildew resistance genes in hybrid barley cultivars

Powdery mildew, a common cereal disease caused by the fungus Blumeria graminis, is a major limiting factor of barley production and genetic resistance is the most appropriate protection against it. To aid the breeding of new cultivars and their marketing, resistance genes can be postulated in homogeneous accessions. Although hybrid cultivars (F1) should be homogeneous, they are often not genetically uniform, especially if more than two genotypes are involved in their seed production or due to undesirable self-pollination, out-crossing and mechanical admixtures. To overcome these problems the accepted method of postulating specific resistance genes based on comparing response type arrays (RTAs) of genetically homogeneous cultivars with RTAs of standard genotypes was substituted by analysing the frequency of response types to clusters of pathogen isolates in segregating F2 generations. This method combines a genetic and phytopathological approach for identifying resistance genes. To assess its applicability six hybrid cultivars were screened and from three to seven with a total of 14 resistance genes were found. Two genes were newly located at the Mla locus and their heritability determined. In addition, three unknown dominant genes were detected. This novel, comprehensive and efficient method to identifying resistance genes in hybrid cultivars can also be applied in other cereals and crops.

Dynamical climatic model for time to flowering in Vigna radiata

BACKGROUND

Phenology data collected recently for about 300 accessions of Vigna radiata (mungbean) is an invaluable resource for investigation of impacts of climatic factors on plant development.

RESULTS

We developed a new mathematical model that describes the dynamic control of time to flowering by daily values of maximal and minimal temperature, precipitation, day length and solar radiation. We obtained model parameters by adaptation to the available experimental data. The models were validated by cross-validation and used to demonstrate that the phenology of adaptive traits, like flowering time, is strongly predicted not only by local environmental factors but also by plant geographic origin and genotype.

CONCLUSIONS

Of local environmental factors maximal temperature appeared to be the most critical factor determining how faithfully the model describes the data. The models were applied to forecast time to flowering of accessions grown in Taiwan in future years 2020-2030.

A Revolution toward Gene-Editing Technology and Its Application to Crop Improvement

Genome editing is a relevant, versatile, and preferred tool for crop improvement, as well as for functional genomics. In this review, we summarize the advances in gene-editing techniques, such as zinc-finger nucleases (ZFNs), transcription activator-like (TAL) effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeats (CRISPR) associated with the Cas9 and Cpf1 proteins. These tools support great opportunities for the future development of plant science and rapid remodeling of crops. Furthermore, we discuss the brief history of each tool and provide their comparison and different applications. Among the various genome-editing tools, CRISPR has become the most popular; hence, it is discussed in the greatest detail. CRISPR has helped clarify the genomic structure and its role in plants: For example, the transcriptional control of Cas9 and Cpf1, genetic locus monitoring, the mechanism and control of promoter activity, and the alteration and detection of epigenetic behavior between single-nucleotide polymorphisms (SNPs) investigated based on genetic traits and related genome-wide studies. The present review describes how CRISPR/Cas9 systems can play a valuable role in the characterization of the genomic rearrangement and plant gene functions, as well as the improvement of the important traits of field crops with the greatest precision. In addition, the speed editing strategy of gene-family members was introduced to accelerate the applications of gene-editing systems to crop improvement. For this, the CRISPR technology has a valuable advantage that particularly holds the scientist's mind, as it allows genome editing in multiple biological systems.

Breeder friendly phenotyping

The word phenotyping can nowadays invoke visions of a drone or phenocart moving swiftly across research plots collecting high-resolution data sets on a wide array of traits. This has been made possible by recent advances in sensor technology and data processing. Nonetheless, more comprehensive often destructive phenotyping still has much to offer in breeding as well as research. This review considers the 'breeder friendliness' of phenotyping within three main domains: (i) the 'minimum data set', where being 'handy' or accessible and easy to collect and use is paramount, visual assessment often being preferred; (ii) the high throughput phenotyping (HTP), relatively new for most breeders, and requiring significantly greater investment with technical hurdles for implementation and a steeper learning curve than the minimum data set; (iii) detailed characterization or 'precision' phenotyping, typically customized for a set of traits associated with a target environment and requiring significant time and resources. While having been the subject of debate in the past, extra investment for phenotyping is becoming more accepted to capitalize on recent developments in crop genomics and prediction models, that can be built from the high-throughput and detailed precision phenotypes. This review considers different contexts for phenotyping, including breeding, exploration of genetic resources, parent building and translational research to deliver other new breeding resources, and how the different categories of phenotyping listed above apply to each. Some of the same tools and rules of thumb apply equally well to phenotyping for genetic analysis of complex traits and gene discovery.

Conventional and Molecular Techniques from Simple Breeding to Speed Breeding in Crop Plants: Recent Advances and Future Outlook

In most crop breeding programs, the rate of yield increment is insufficient to cope with the increased food demand caused by a rapidly expanding global population. In plant breeding, the development of improved crop varieties is limited by the very long crop duration. Given the many phases of crossing, selection, and testing involved in the production of new plant varieties, it can take one or two decades to create a new cultivar. One possible way of alleviating food scarcity problems and increasing food security is to develop improved plant varieties rapidly. Traditional farming methods practiced since quite some time have decreased the genetic variability of crops. To improve agronomic traits associated with yield, quality, and resistance to biotic and abiotic stresses in crop plants, several conventional and molecular approaches have been used, including genetic selection, mutagenic breeding, somaclonal variations, whole-genome sequence-based approaches, physical maps, and functional genomic tools. However, recent advances in genome editing technology using programmable nucleases, clustered regularly interspaced short palindromic repeats (CRISPR), and CRISPR-associated (Cas) proteins have opened the door to a new plant breeding era. Therefore, to increase the efficiency of crop breeding, plant breeders and researchers around the world are using novel strategies such as speed breeding, genome editing tools, and high-throughput phenotyping. In this review, we summarize recent findings on several aspects of crop breeding to describe the evolution of plant breeding practices, from traditional to modern speed breeding combined with genome editing tools, which aim to produce crop generations with desired traits annually.