Exploring potential of pearl millet germplasm association panel for association mapping of drought tolerance traits

Pearl millet a promising fodder crop for changing climate: a review

The agricultural sector faces colossal challenges amid environmental changes and a burgeoning human population. In this context, crops must adapt to evolving climatic conditions while meeting increasing production demands. The dairy industry is anticipated to hold the highest value in the agriculture sector in future. The rise in the livestock population is expected to result in an increased demand for fodder feed. Consequently, it is crucial to seek alternative options, as crops demand fewer resources and are resilient to climate change. Pearl millet offers an apposite key to these bottlenecks, as it is a promising climate resilience crop with significantly low energy, water and carbon footprints compared to other crops. Numerous studies have explored its potential as a fodder crop, revealing promising performance. Despite its capabilities, pearl millet has often been overlooked. To date, few efforts have been made to document molecular aspects of fodder-related traits. However, several QTLs and candidate genes related to forage quality have been identified in other fodder crops, which can be harnessed to enhance the forage quality of pearl millet. Lately, excellent genomic resources have been developed in pearl millet allowing deployment of cutting-edge genomics-assisted breeding for achieving a higher rate of genetic gains. This review would facilitate a deeper understanding of various aspects of fodder pearl millet in retrospect along with the future challenges and their solution. This knowledge may pave the way for designing efficient breeding strategies in pearl millet thereby supporting sustainable agriculture and livestock production in a changing world.

Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet

MAIN CONCLUSION

Pearl millet wild relatives harbour novel alleles which could be utilized to broaden genetic base of cultivated species. Genomics-informed pre-breeding is needed to speed up introgression from wild to cultivated gene pool in pearl millet. Rising episodes of intense biotic and abiotic stresses challenge pearl millet production globally. Wild relatives provide a wide spectrum of novel alleles which could address challenges posed by climate change. Pre-breeding holds potential to introgress novel diversity in genetically narrow cultivated Pennisetum glaucum from diverse gene pool. Practical utilization of gene pool diversity remained elusive due to genetic intricacies. Harnessing promising traits from wild pennisetum is limited by lack of information on underlying candidate genes/QTLs. Next-Generation Omics provide vast scope to speed up pre-breeding in pearl millet. Genomic resources generated out of draft genome sequence and improved genome assemblies can be employed to utilize gene bank accessions effectively. The article highlights genetic richness in pearl millet and its utilization with a focus on harnessing next-generation Omics to empower pre-breeding.

Integration of genome-wide association studies, metabolomics, and transcriptomics reveals phenolic acid- and flavonoid-associated genes and their regulatory elements under drought stress in rapeseed flowers

Introduction

Biochemical and metabolic processes help plants tolerate the adverse effects of drought. In plants accumulating bioactive compounds, understanding the genetic control of the biosynthesis of biochemical pathways helps the discovery of candidate gene (CG)-metabolite relationships.

Methods

The metabolic profile of flowers in 119 rapeseed (Brassica napus) accessions was assessed over two irrigation treatments, one a well-watered (WW) condition and the other a drought stress (DS) regime. We integrated information gained from 52,157 single-nucleotide polymorphism (SNP) markers, metabolites, and transcriptomes to identify linked SNPs and CGs responsible for the genetic control of flower phenolic compounds and regulatory elements.

Results

In a genome-wide association study (GWAS), of the SNPs tested, 29,310 SNPs were qualified to assess the population structure and linkage disequilibrium (LD), of which several SNPs for radical scavenging activity (RSA) and total flavanol content (TFLC) were common between the two irrigation conditions and pleiotropic SNPs were found for chlorogenic and coumaric acids content. The principal component analysis (PCA) and stepwise regression showed that chlorogenic acid and epicatechin in WW and myricetin in DS conditions were the most important components for RSA. The hierarchical cluster analysis (HCA) showed that vanillic acid, myricetin, gallic acid, and catechin were closely associated in both irrigation conditions. Analysis of GWAS showed that 60 CGs were identified, of which 18 were involved in stress-induced pathways, phenylpropanoid pathway, and flavonoid modifications. Of the CGs, PAL1, CHI, UGT89B1, FLS3, CCR1, and CYP75B137 contributed to flavonoid biosynthetic pathways. The results of RNA sequencing (RNA-seq) revealed that the transcript levels of PAL, CHI, and CYP75B137 known as early flavonoid biosynthesis-related genes and FLS3, CCR1, and UGT89B1 related to the later stages were increased during drought conditions. The transcription factors (TFs) NAC035 and ERF119 related to flavonoids and phenolic acids were upregulated under drought conditions.

Discussion

These findings expand our knowledge on the response mechanisms to DS, particularly regarding the regulation of key phenolic biosynthetic genes in rapeseed. Our data also provided specific linked SNPs for marker-assisted selection (MAS) programs and CGs as resources toward realizing metabolomics-associated breeding of rapeseed.

Redesigning crop varieties to win the race between climate change and food security

Climate change poses daunting challenges to agricultural production and food security. Rising temperatures, shifting weather patterns, and more frequent extreme events have already demonstrated their effects on local, regional, and global agricultural systems. Crop varieties that withstand climate-related stresses and are suitable for cultivation in innovative cropping systems will be crucial to maximize risk avoidance, productivity, and profitability under climate-changed environments. We surveyed 588 expert stakeholders to predict current and novel traits that may be essential for future pearl millet, sorghum, maize, groundnut, cowpea, and common bean varieties, particularly in sub-Saharan Africa. We then review the current progress and prospects for breeding three prioritized future-essential traits for each of these crops. Experts predict that most current breeding priorities will remain important, but that rates of genetic gain must increase to keep pace with climate challenges and consumer demands. Importantly, the predicted future-essential traits include innovative breeding targets that must also be prioritized; for example, (1) optimized rhizosphere microbiome, with benefits for P, N, and water use efficiency, (2) optimized performance across or in specific cropping systems, (3) lower nighttime respiration, (4) improved stover quality, and (5) increased early vigor. We further discuss cutting-edge tools and approaches to discover, validate, and incorporate novel genetic diversity from exotic germplasm into breeding populations with unprecedented precision, accuracy, and speed. We conclude that the greatest challenge to developing crop varieties to win the race between climate change and food security might be our innovativeness in defining and boldness to breed for the traits of tomorrow.

Green revolution to genome revolution: driving better resilient crops against environmental instability

Crop improvement programmes began with traditional breeding practices since the inception of agriculture. Farmers and plant breeders continue to use these strategies for crop improvement due to their broad application in modifying crop genetic compositions. Nonetheless, conventional breeding has significant downsides in regard to effort and time. Crop productivity seems to be hitting a plateau as a consequence of environmental issues and the scarcity of agricultural land. Therefore, continuous pursuit of advancement in crop improvement is essential. Recent technical innovations have resulted in a revolutionary shift in the pattern of breeding methods, leaning further towards molecular approaches. Among the promising approaches, marker-assisted selection, QTL mapping, omics-assisted breeding, genome-wide association studies and genome editing have lately gained prominence. Several governments have progressively relaxed their restrictions relating to genome editing. The present review highlights the evolutionary and revolutionary approaches that have been utilized for crop improvement in a bid to produce climate-resilient crops observing the consequence of climate change. Additionally, it will contribute to the comprehension of plant breeding succession so far. Investing in advanced sequencing technologies and bioinformatics will deepen our understanding of genetic variations and their functional implications, contributing to breakthroughs in crop improvement and biodiversity conservation.

Genetic and genomic interventions in crop biofortification: Examples in millets

Micronutrient malnutrition is a serious threat to the developing world's human population, which largely relies on a cereal-based diet that lacks diversity and micronutrients. Besides major cereals, millets represent the key sources of energy, protein, vitamins, and minerals for people residing in the dryland tropics and drought-prone areas of South Asia and sub-Saharan Africa. Millets serve as multi-purpose crops with several salient traits including tolerance to abiotic stresses, adaptation to diverse agro-ecologies, higher productivity in nutrient-poor soils, and rich nutritional characteristics. Considering the potential of millets in empowering smallholder farmers, adapting to changing climate, and transforming agrifood systems, the year 2023 has been declared by the United Nations as the International Year of Millets. In this review, we highlight recent genetic and genomic innovations that can be explored to enhance grain micronutrient density in millets. We summarize the advances made in high-throughput phenotyping to accurately measure grain micronutrient content in cereals. We shed light on genetic diversity in millet germplasm collections existing globally that can be exploited for developing nutrient-dense and high-yielding varieties to address food and nutritional security. Furthermore, we describe the progress made in the fields of genomics, proteomics, metabolomics, and phenomics with an emphasis on enhancing the grain nutritional content for designing competitive biofortified varieties for the future. Considering the close genetic-relatedness within cereals, upcoming research should focus on identifying the genetic and genomic basis of nutritional traits in millets and introgressing them into major cereals through integrated omics approaches. Recent breakthroughs in the genome editing toolbox would be crucial for mainstreaming biofortification in millets.

Deciphering trait associated morpho-physiological responses in pearlmillet hybrids and inbred lines under salt stress

Pearl millet is a staple food for more than 90 million people residing in highly vulnerable hot arid and semi-arid regions of Africa and Asia. These regions are more prone to detrimental effects of soil salinity on crop performance in terms of reduced biomass and crop yields. We investigated the physiological mechanisms of salt tolerance to irrigation induced salinity stress (EC_iw ~3, 6 & 9 dSm^-1) and their confounding effects on plant growth and yield in pearl millet inbred lines and hybrids. On average, nearly 30% reduction in above ground plant biomass was observed at EC_iw ~6 dSm^-1 which stretched to 56% at EC_iw ~9 dSm^-1 in comparison to best available water. With increasing salinity stress, the crop performance of test hybrids was better in comparison to inbred lines; exhibiting relatively higher stomatal conductance (gS; 16%), accumulated lower proline (Pro; -12%) and shoot Na⁺/K⁺(-31%), synthesized more protein (SP; 2%) and sugars (TSS; 32%) compensating in lower biomass (AGB; -22%) and grain yield (GY: -14%) reductions at highest salinity stress of EC_iw ~9 dSm^-1. Physiological traits modeling underpinning plant salt tolerance and adaptation mechanism illustrated the key role of 7 traits (AGB, Pro, SS, gS, SPAD, Pn, and SP) in hybrids and 8 traits (AGB, Pro, PH, Na⁺, K⁺, Na⁺/K⁺, SPAD, and gS) in inbred lines towards anticipated grain yield variations in salinity stressed pearl millet. Most importantly, the AGB alone, explained >91% of yield variation among evaluated hybrids and inbreed lines at EC_iw ~9 dSm^-1. Cumulatively, the better morpho-physiological adaptation and lesser yield reduction with increasing salinity stress in pearl millet hybrids (HHB 146, HHB 272, and HHB 234) and inbred lines (H77/833-2-202, ICMA 94555 and ICMA 843-22) substantially complemented in increased plant salt tolerance and yield stability over a broad range of salinity stress. The information generated herein will help address in deciphering the trait associated physiological alterations to irrigation induced salt stress, and developing potential hybrids in pearl millet using these parents with special characteristics.

Development of a new AgriSeq 4K mid-density SNP genotyping panel and its utility in pearl millet breeding

Pearl millet is a crucial nutrient-rich staple food in Asia and Africa and adapted to the climate of semi-arid topics. Since the genomic resources in pearl millet are very limited, we have developed a brand-new mid-density 4K SNP panel and demonstrated its utility in genetic studies. A set of 4K SNPs were mined from 925 whole-genome sequences through a comprehensive in-silico pipeline. Three hundred and seventy-three genetically diverse pearl millet inbreds were genotyped using the newly-developed 4K SNPs through the AgriSeq Targeted Genotyping by Sequencing technology. The 4K SNPs were uniformly distributed across the pearl millet genome and showed considerable polymorphism information content (0.23), genetic diversity (0.29), expected heterozygosity (0.29), and observed heterozygosity (0.03). The SNP panel successfully differentiated the accessions into two major groups, namely B and R lines, through genetic diversity, PCA, and structure models as per their pedigree. The linkage disequilibrium (LD) analysis showed Chr3 had higher LD regions while Chr1 and Chr2 had more low LD regions. The genetic divergence between the B- and R-line populations was 13%, and within the sub-population variability was 87%. In this experiment, we have mined 4K SNPs and optimized the genotyping protocol through AgriSeq technology for routine use, which is cost-effective, fast, and highly reproducible. The newly developed 4K mid-density SNP panel will be useful in genomics and molecular breeding experiments such as assessing the genetic diversity, trait mapping, backcross breeding, and genomic selection in pearl millet.

Genomic footprints of selection in early-and late-flowering pearl millet landraces

Pearl millet is among the top three-cereal production in one of the most climate vulnerable regions, sub-Saharan Africa. Its Sahelian origin makes it adapted to grow in poor sandy soils under low soil water regimes. Pearl millet is thus considered today as one of the most interesting crops to face the global warming. Flowering time, a trait highly correlated with latitude, is one of the key traits that could be modulated to face future global changes. West African pearl millet landraces, can be grouped into early- (EF) and late-flowering (LF) varieties, each flowering group playing a specific role in the functioning and resilience of Sahelian smallholders. The aim of this study was thus to detect genes linked to flowering but also linked to relevant traits within each flowering group. We thus investigated genomic and phenotypic diversity in 109 pearl millet landrace accessions, i.e., 66 early-flowering and 43 late-flowering, grown in the groundnut basin, the first area of rainfed agriculture in Senegal dominated by dry cereals (millet, maize, and sorghum) and legumes (groundnuts, cowpeas). We were able to confirm the role of PhyC gene in pearl millet flowering and identify several other genes that appear to be as much as important, such as FSR12 and HAC1. HAC1 and two other genes appear to be part of QTLs previously identified and deserve further investigation. At the same time, we were able to highlight a several genes and variants that could contribute to the improvement of pearl millet yield, especially since their impact was demonstrated across flowering cycles.

Genetic insights in pearl millet breeding in the genomic era: challenges and prospects

Pearl millet, a vital staple food and an important cereal, is emerging as crop having various end-uses as feed, food as well as fodder. Advancement in high-throughput sequencing technology has boosted up pearl millet genomic research in past few years. The available draft genome of pearl millet providing an insight into the advancement of several breeding lines. Comparative and functional genomics have untangled several loci and genes regulating adaptive and agronomic traits in pearl millet. Additionally, the knowledge achieved has far away from being applicable in real breeding practices. We believe that the best path ahead is to adopt genome-based approaches for tailored designing of pearl millet as multi-functional crop with outstanding agronomic traits for various end uses. Presently review highlight several novel concepts and techniques in crop breeding, and summarize the recent advances in pearl millet genomic research, peculiarly genome-wide association dissections of several novel alleles and genes for agronomically important traits.

Maximizing value of genetic sequence data requires an enabling environment and urgency

Severe price spikes of the major grain commodities and rapid expansion of cultivated area in the past two decades are symptoms of a severely stressed global food supply. Scientific discovery and improved agricultural productivity are needed and are enabled by unencumbered access to, and use of, genetic sequence data. In the same way the world witnessed rapid development of vaccines for COVID-19, genetic sequence data afford enormous opportunities to improve crop production. In addition to an enabling regulatory environment that allowed for the sharing of genetic sequence data, robust funding fostered the rapid development of coronavirus diagnostics and COVID-19 vaccines. A similar level of commitment, collaboration, and cooperation is needed for agriculture.

NIR Instruments and Prediction Methods for Rapid Access to Grain Protein Content in Multiple Cereals

Achieving global goals for sustainable nutrition, health, and wellbeing will depend on delivering enhanced diets to humankind. This will require instantaneous access to information on food-source quality at key points of agri-food systems. Although laboratory analysis and benchtop NIR spectrometers are regularly used to quantify grain quality, these do not suit all end users, for example, stakeholders in decentralized agri-food chains that are typical in emerging economies. Therefore, we explored benchtop and portable NIR instruments, and the methods that might aid these particular end uses. For this purpose, we generated NIR spectra for 328 grain samples from multiple cereals (finger millet, foxtail millet, maize, pearl millet, and sorghum) with a standard benchtop NIR spectrometer (DS2500, FOSS) and a novel portable NIR-based instrument (HL-EVT5, Hone). We explored classical deterministic methods (via winISI, FOSS), novel machine learning (ML)-driven methods (via Hone Create, Hone), and a convolutional neural network (CNN)-based method for building the calibrations to predict grain protein out of the NIR spectra. All of the tested methods enabled us to build relevant calibrations out of both types of spectra (i.e., R² ≥ 0.90, RMSE ≤ 0.91, RPD ≥ 3.08). Generally, the calibration methods integrating the ML techniques tended to enhance the prediction capacity of the model. We also documented that the prediction of grain protein content based on the NIR spectra generated using the novel portable instrument (HL-EVT5, Hone) was highly relevant for quantitative protein predictions (R² = 0.91, RMSE = 0.97, RPD = 3.48). Thus, the presented findings lay the foundations for the expanded use of NIR spectroscopy in agricultural research, development, and trade.

Breeding Drought-Tolerant Pearl Millet Using Conventional and Genomic Approaches: Achievements and Prospects

Pearl millet [Pennisetum glaucum (L.) R. Br.] is a C4 crop cultivated for its grain and stover in crop-livestock-based rain-fed farming systems of tropics and subtropics in the Indian subcontinent and sub-Saharan Africa. The intensity of drought is predicted to further exacerbate because of looming climate change, necessitating greater focus on pearl millet breeding for drought tolerance. The nature of drought in different target populations of pearl millet-growing environments (TPEs) is highly variable in its timing, intensity, and duration. Pearl millet response to drought in various growth stages has been studied comprehensively. Dissection of drought tolerance physiology and phenology has helped in understanding the yield formation process under drought conditions. The overall understanding of TPEs and differential sensitivity of various growth stages to water stress helped to identify target traits for manipulation through breeding for drought tolerance. Recent advancement in high-throughput phenotyping platforms has made it more realistic to screen large populations/germplasm for drought-adaptive traits. The role of adapted germplasm has been emphasized for drought breeding, as the measured performance under drought stress is largely an outcome of adaptation to stress environments. Hybridization of adapted landraces with selected elite genetic material has been stated to amalgamate adaptation and productivity. Substantial progress has been made in the development of genomic resources that have been used to explore genetic diversity, linkage mapping (QTLs), marker-trait association (MTA), and genomic selection (GS) in pearl millet. High-throughput genotyping (HTPG) platforms are now available at a low cost, offering enormous opportunities to apply markers assisted selection (MAS) in conventional breeding programs targeting drought tolerance. Next-generation sequencing (NGS) technology, micro-environmental modeling, and pearl millet whole genome re-sequence information covering circa 1,000 wild and cultivated accessions have helped to greater understand germplasm, genomes, candidate genes, and markers. Their application in molecular breeding would lead to the development of high-yielding and drought-tolerant pearl millet cultivars. This review examines how the strategic use of genetic resources, modern genomics, molecular biology, and shuttle breeding can further enhance the development and delivery of drought-tolerant cultivars.

Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping

Environmental stresses from climate change can alter source-sink relations during plant maturation, leading to premature senescence and decreased yields. Elucidating the genetic control of natural variations for senescence in wheat (Triticum aestivum) can be accelerated using recent developments in unmanned aerial vehicle (UAV)-based imaging techniques. Here, we describe the use of UAVs to quantify senescence in wheat using vegetative indices (VIs) derived from multispectral images. We detected senescence with high heritability, as well as its impact on grain yield (GY), in a doubled-haploid population and parent cultivars at various growth time points (TPs) after anthesis in the field. Selecting for slow senescence using a combination of different UAV-based VIs was more effective than using a single ground-based vegetation index. We identified 28 quantitative trait loci (QTL) for vegetative growth, senescence, and GY using a 660K single-nucleotide polymorphism array. Seventeen of these new QTL for VIs from UAV-based multispectral imaging were mapped on chromosomes 2B, 3A, 3D, 5A, 5D, 5B, and 6D; these QTL have not been reported previously using conventional phenotyping methods. This integrated approach allowed us to identify an important, previously unreported, senescence-related locus on chromosome 5D that showed high phenotypic variation (up to 18.1%) for all UAV-based VIs at all TPs during grain filling. This QTL was validated for slow senescence by developing kompetitive allele-specific PCR markers in a natural population. Our results suggest that UAV-based high-throughput phenotyping is advantageous for temporal assessment of the genetics underlying for senescence in wheat.

Metabolite Diversity and Metabolic Genome-Wide Marker Association Studies (Mgwas) for Health Benefiting Nutritional Traits in Pearl Millet Grains

As efforts are made to increase food security, millets are gaining increasing importance due to their excellent nutritional credentials. Among the millets, pearl millet is the predominant species possessing several health benefiting nutritional traits in its grain that are helpful in mitigating chronic illnesses such as type−2 diabetes and obesity. In this paper, we conducted metabolomic fingerprinting of 197 pearl millet inbred lines drawn randomly from within the world collection of pearl millet germplasm and report the extent of genetic variation for health benefitting metabolites in these genotypes. Metabolites were extracted from seeds and assessed using flow infusion high-resolution mass spectrometry (FIE-HRMS). Metabolite features (m/z), whose levels significantly differed among the germplasm inbred lines, were identified by ANOVA corrected for FDR and subjected to functional pathway analysis. A number of health-benefiting metabolites linked to dietary starch, antioxidants, vitamins, and lipid metabolism-related compounds were identified. Metabolic genome-wide association analysis (mGWAS) performed using the 396 m/z as phenotypic traits and the 76 K SNP as genotypic variants identified a total of 897 SNPs associated with health benefiting nutritional metabolite at the -log p-value ≤ 4.0. From these associations, 738 probable candidate genes were predicted to have an important role in starch, antioxidants, vitamins, and lipid metabolism. The mGWAS analysis focused on genes involved in starch branching (α-amylase, β-amylase), vitamin-K reductase, UDP-glucuronosyl, and UDP-glucosyl transferase (UGTs), L-ascorbate oxidase, and isoflavone 2′-monooxygenase genes, which are known to be linked to increases in human health benefiting metabolites. We demonstrate how metabolomic, genomic, and statistical approaches can be utilized to pinpoint genetic variations and their functions linked to key nutritional properties in pearl millet, which in turn can be bred into millets and other cereals crops using plant breeding methods.

Progressive Genomic Approaches to Explore Drought- and Salt-Induced Oxidative Stress Responses in Plants under Changing Climate

Drought and salinity are the major environmental abiotic stresses that negatively impact crop development and yield. To improve yields under abiotic stress conditions, drought- and salinity-tolerant crops are key to support world crop production and mitigate the demand of the growing world population. Nevertheless, plant responses to abiotic stresses are highly complex and controlled by networks of genetic and ecological factors that are the main targets of crop breeding programs. Several genomics strategies are employed to improve crop productivity under abiotic stress conditions, but traditional techniques are not sufficient to prevent stress-related losses in productivity. Within the last decade, modern genomics studies have advanced our capabilities of improving crop genetics, especially those traits relevant to abiotic stress management. This review provided updated and comprehensive knowledge concerning all possible combinations of advanced genomics tools and the gene regulatory network of reactive oxygen species homeostasis for the appropriate planning of future breeding programs, which will assist sustainable crop production under salinity and drought conditions.

Pearl Millet: A Climate-Resilient Nutricereal for Mitigating Hidden Hunger and Provide Nutritional Security

Pearl millet [Pennisetum glaucum (L.) R. Br.] is the sixth most important cereal crop after rice, wheat, maize, barley and sorghum. It is widely grown on 30 million ha in the arid and semi-arid tropical regions of Asia and Africa, accounting for almost half of the global millet production. Climate change affects crop production by directly influencing biophysical factors such as plant and animal growth along with the various areas associated with food processing and distribution. Assessment of the effects of global climate changes on agriculture can be helpful to anticipate and adapt farming to maximize the agricultural production more effectively. Pearl millet being a climate-resilient crop is important to minimize the adverse effects of climate change and has the potential to increase income and food security of farming communities in arid regions. Pearl millet has a deep root system and can survive in a wide range of ecological conditions under water scarcity. It has high photosynthetic efficiency with an excellent productivity and growth in low nutrient soil conditions and is less reliant on chemical fertilizers. These attributes have made it a crop of choice for cultivation in arid and semi-arid regions of the world; however, fewer efforts have been made to study the climate-resilient features of pearl millet in comparison to the other major cereals. Several hybrids and varieties of pearl millet were developed during the past 50 years in India by both the public and private sectors. Pearl millet is also nutritionally superior and rich in micronutrients such as iron and zinc and can mitigate malnutrition and hidden hunger. Inclusion of minimum standards for micronutrients-grain iron and zinc content in the cultivar release policy-is the first of its kind step taken in pearl millet anywhere in the world, which can lead toward enhanced food and nutritional security. The availability of high-quality whole-genome sequencing and re-sequencing information of several lines may aid genomic dissection of stress tolerance and provide a good opportunity to further exploit the nutritional and climate-resilient attributes of pearl millet. Hence, more efforts should be put into its genetic enhancement and improvement in inheritance to exploit it in a better way. Thus, pearl millet is the next-generation crop holding the potential of nutritional richness and the climate resilience and efforts must be targeted to develop nutritionally dense hybrids/varieties tolerant to drought using different omics approaches.

Assessment of Ensemble Learning to Predict Wheat Grain Yield Based on UAV-Multispectral Reflectance

Grain yield is increasingly affected by climate factors such as drought and heat. To develop resilient and high-yielding cultivars, high-throughput phenotyping (HTP) techniques are essential for precise decisions in wheat breeding. The ability of unmanned aerial vehicle (UAV)-based multispectral imaging and ensemble learning methods to increase the accuracy of grain yield prediction in practical breeding work is evaluated in this study. For this, 211 winter wheat genotypes were planted under full and limited irrigation treatments, and multispectral data were collected at heading, flowering, early grain filling (EGF), and mid-grain filling (MGF) stages. Twenty multispectral vegetation indices (VIs) were estimated, and VIs with heritability greater than 0.5 were selected to evaluate the models across the growth stages under both irrigation treatments. A framework for ensemble learning was developed by combining multiple base models such as random forest (RF), support vector machine (SVM), Gaussian process (GP), and ridge regression (RR). The R2 values between VIs and grain yield for individual base models were ranged from 0.468 to 0.580 and 0.537 to 0.598 for grain yield prediction in full and limited irrigation treatments across growth stages, respectively. The prediction results of ensemble models were ranged from 0.491 to 0.616 and 0.560 to 0.616 under full and limited irrigation treatments respectively, and were higher than that of the corresponding base learners. Moreover, the grain yield prediction results were observed high at mid grain filling stage under both full (R2 = 0.625) and limited (R2 = 0.628) irrigation treatments through ensemble learning based stacking of four base learners. Further improvements in ensemble learning models can accelerate the use of UAV-based multispectral data for accurate predictions of complex traits like grain yield in wheat.

QTL mapping of root traits in wheat under different phosphorus levels using hydroponic culture

Background

Phosphorus (P) is an important in ensuring plant morphogenesis and grain quality, therefore an efficient root system is crucial for P-uptake. Identification of useful loci for root morphological and P uptake related traits at seedling stage is important for wheat breeding. The aims of this study were to evaluate phenotypic diversity of Yangmai 16/Zhongmai 895 derived doubled haploid (DH) population for root system architecture (RSA) and biomass related traits (BRT) in different P treatments at seedling stage using hydroponic culture, and to identify QTL using 660 K SNP array based high-density genetic map.

Results

All traits showed significant variations among the DH lines with high heritabilities (0.76 to 0.91) and high correlations (r = 0.59 to 0.98) among all traits. Inclusive composite interval mapping (ICIM) identified 34 QTL with 4.64–20.41% of the phenotypic variances individually, and the log of odds (LOD) values ranging from 2.59 to 10.43. Seven QTL clusters (C1 to C7) were mapped on chromosomes 3DL, 4BS, 4DS, 6BL, 7AS, 7AL and 7BL, cluster C5 on chromosome 7AS (AX-109955164 - AX-109445593) with pleiotropic effect played key role in modulating root length (RL), root tips number (RTN) and root surface area (ROSA) under low P condition, with the favorable allele from Zhongmai 895.

Conclusions

This study carried out an imaging pipeline-based rapid phenotyping of RSA and BRT traits in hydroponic culture. It is an efficient approach for screening of large populations under different nutrient conditions. Four QTL on chromosomes 6BL (2) and 7AL (2) identified in low P treatment showed positive additive effects contributed by Zhongmai 895, indicating that Zhongmai 895 could be used as parent for P-deficient breeding. The most stable QTL QRRS.caas-4DS for ratio of root to shoot dry weight (RRS) harbored the stable genetic region with high phenotypic effect, and QTL clusters on 7A might be used for speedy selection of genotypes for P-uptake. SNPs closely linked to QTLs and clusters could be used to improve nutrient-use efficiency.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07425-4.

Genetic Variation for Nitrogen Use Efficiency Traits in Global Diversity Panel and Parents of Mapping Populations in Pearl Millet

Nitrogen (N) is one of the primary macronutrients required for crop growth and yield. This nutrient is especially limiting in the dry and low fertility soils where pearl millet [Pennisetum glaucum (L.) R. Br] is typically grown. Globally, pearl millet is the sixth most important cereal grown by subsistence farmers in the arid and semi-arid regions of sub-Saharan Africa and the Indian subcontinent. Most of these agro-ecologies have low N in the root zone soil strata. Therefore, there is an immense need to identify lines that use nitrogen efficiently. A set of 380 diverse pearl millet lines consisting of a global diversity panel (345), parents of mapping populations (20), and standard checks (15) were evaluated in an alpha-lattice design with two replications, 25 blocks, a three-row plot for 11 nitrogen use efficiency (NUE) related traits across three growing seasons (Summer 2017, Rainy 2017, and Summer 2018) in an N-depleted precision field under three different N levels (0%-N0, 50%-N50, 100%-N100 of recommended N, i.e., 100 kg ha-1). Analysis of variance revealed significant genetic variation for NUE-related traits across treatments and seasons. Nitrogen in limited condition (N0) resulted in a 27.6 and 17.6% reduction in grain yield (GY) and dry stover yield (DSY) compared to N50. Higher reduction in GY and DSY traits by 24.6 and 23.6% were observed under N0 compared to N100. Among the assessed traits, GY exhibited significant positive correlations with nitrogen utilization efficiency (NUtE) and nitrogen harvest index (NHI). This indicated the pivotal role of N remobilization to the grain in enhancing yield levels. Top 25 N-insensitive (NIS-top grain yielders) and N-sensitive (NS-poor grain yielders) genotypes were identified under low N conditions. Out of 25 NIS lines, nine genotypes (IP 10820, IP 17720, ICMB 01222-P1, IP 10379, ICMB 89111-P2, IP 8069, ICMB 90111-P2, ICMV IS89305, and ICMV 221) were common with the top 25 lines for N100 level showing the genotype plasticity toward varying N levels. Low N tolerant genotypes identified from the current investigation may help in the identification of genomic regions responsible for NUE and its deployment in pearl millet breeding programs through marker-assisted selection (MAS).

Genomic resources in plant breeding for sustainable agriculture

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965-85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.

Physiological and Proteomic Signatures Reveal Mechanisms of Superior Drought Resilience in Pearl Millet Compared to Wheat

Presently, pearl millet and wheat are belonging to highly important cereal crops. Pearl millet, however, is an under-utilized crop, despite its superior resilience to drought and heat stress in contrast to wheat. To investigate this in more detail, we performed comparative physiological screening and large scale proteomics of drought stress responses in drought-tolerant and susceptible genotypes of pearl millet and wheat. These chosen genotypes are widely used in breeding and farming practices. The physiological responses demonstrated large differences in the regulation of root morphology and photosynthetic machinery, revealing a stay-green phenotype in pearl millet. Subsequent tissue-specific proteome analysis of leaves, roots and seeds led to the identification of 12,558 proteins in pearl millet and wheat under well-watered and stress conditions. To allow for this comparative proteome analysis and to provide a platform for future functional proteomics studies we performed a systematic phylogenetic analysis of all orthologues in pearl millet, wheat, foxtail millet, sorghum, barley, brachypodium, rice, maize, Arabidopsis, and soybean. In summary, we define (i) a stay-green proteome signature in the drought-tolerant pearl millet phenotype and (ii) differential senescence proteome signatures in contrasting wheat phenotypes not capable of coping with similar drought stress. These different responses have a significant effect on yield and grain filling processes reflected by the harvest index. Proteome signatures related to root morphology and seed yield demonstrated the unexpected intra- and interspecies-specific biochemical plasticity for stress adaptation for both pearl millet and wheat genotypes. These quantitative reference data provide tissue- and phenotype-specific marker proteins of stress defense mechanisms which are not predictable from the genome sequence itself and have potential value for marker-assisted breeding beyond genome assisted breeding.

Identifying Anti-Oxidant Biosynthesis Genes in Pearl Millet [Pennisetum glaucum (L.) R. Br.] Using Genome-Wide Association Analysis

Pearl millet [Pennisetum glaucum (L.) R Br.] is an important staple food crop in the semi-arid tropics of Asia and Africa. It is a cereal grain that has the prospect to be used as a substitute for wheat flour for celiac patients. It is an important antioxidant food resource present with a wide range of phenolic compounds that are good sources of natural antioxidants. The present study aimed to identify the total antioxidant content of pearl millet flour and apply it to evaluate the antioxidant activity of its 222 genotypes drawn randomly from the pearl millet inbred germplasm association panel (PMiGAP), a world diversity panel of this crop. The total phenolic content (TPC) significantly correlated with DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging activity (% inhibition), which ranged from 2.32 to 112.45% and ferric-reducing antioxidant power (FRAP) activity ranging from 21.68 to 179.66 (mg ascorbic acid eq./100 g). Genome-wide association studies (GWAS) were conducted using 222 diverse accessions and 67 K SNPs distributed across all the seven pearl millet chromosomes. Approximately, 218 SNPs were found to be strongly associated with DPPH and FRAP activity at high confidence [-log (p) > 3.0-7.4]. Furthermore, flanking regions of significantly associated SNPs were explored for candidate gene harvesting. This identified 18 candidate genes related to antioxidant pathway genes (flavanone 7-O-beta-glycosyltransferase, GDSL esterase/lipase, glutathione S-transferase) residing within or near the association signal that can be selected for further functional characterization. Patterns of genetic variability and the associated genes reported in this study are useful findings, which would need further validation before their utilization in molecular breeding for high antioxidant-containing pearl millet cultivars.

Genome-wide association study identifies QTL for thousand grain weight in winter wheat under normal- and late-sown stressed environments

GWAS identified stable loci for TGW and stress tolerance in winter wheat based on two sowing conditions, which will provide opportunities for developing new cultivars with high yield and yield stability. Wheat is an important food crop widely cultivated in the world. Breeding new varieties with high yields and superior adaptability is the main goal of modern wheat breeding program. In order to determine the marker-trait associations (MATs), a set of 688 diverse winter wheat accessions were subjected to genome-wide association study (GWAS) using the wheat 90K array. Field trials under normal-sown (NS) and late-sown (LS) conditions were conducted for thousand grain weight (TGW) and stress susceptibility index (SSI) at three different sites across two consecutive years. A total of 179 (NS) and 158 (LS) MATs corresponded with TGW; of these, 16 and 6 stable MATs for TGW_NS and TGW_LS were identified on chromosomes 1B, 2B, 3A, 3B, 5A, 5B, 5D, 6B, and 7D across at least three environments. Notably, a QTL hot spot controlling TGW under NS and LS conditions was found on chromosome 5A (140-142 cM). Moreover, 8 of 228 stable MATs on chromosomes 4B, 5A, and 5D for SSI were detected. A haplotype block associated with TGW and SSI was located on chromosome 5A at 91 cM, nearby the vernalization gene VRN-A1. Additionally, analysis of wheat varieties from the different eras revealed that the grain weight and stress tolerance are not improved concurrently. Overall, our results provide promising alleles controlling grain weight and stress tolerance (particularly for thermotolerance) for wheat breeders, which can be used in marker-assisted selection for improving grain yield and yield stability in wheat.

Genomic diversity in pearl millet inbred lines derived from landraces and improved varieties

BACKGROUND

Genetic improvement of pearl millet is lagging behind most of the major crops. Development of genomic resources is expected to expedite breeding for improved agronomic traits, stress tolerance, yield, and nutritional quality. Genotyping a breeding population with high throughput markers enables exploration of genetic diversity, population structure, and linkage disequilibrium (LD) which are important preludes for marker-trait association studies and application of genomic-assisted breeding.

RESULTS

Genotyping-by-sequencing (GBS) libraries of 309 inbred lines derived from landraces and improved varieties from Africa and India generated 54,770 high quality single nucleotide polymorphism (SNP) markers. On average one SNP per 29 Kb was mapped in the reference genome, with the telomeric regions more densely mapped than the pericentromeric regions of the chromosomes. Population structure analysis using 30,208 SNPs evenly distributed in the genome divided 309 accessions into five subpopulations with different levels of admixture. Pairwise genetic distance (GD) between accessions varied from 0.09 to 0.33 with the average distance of 0.28. Rapid LD decay implied low tendency of markers inherited together. Genetic differentiation estimates were the highest between subgroups 4 and 5, and the lowest between subgroups 1 and 2.

CONCLUSIONS

Population genomic analysis of pearl millet inbred lines derived from diverse geographic and agroecological features identified five subgroups mostly following pedigree differences with different levels of admixture. It also revealed the prevalence of high genetic diversity in pearl millet, which is very useful in defining heterotic groups for hybrid breeding, trait mapping, and holds promise for improving pearl millet for yield and nutritional quality. The short LD decay observed suggests an absence of persistent haplotype blocks in pearl millet. The diverse genetic background of these lines and their low LD make this set of germplasm useful for traits mapping.

Genomics-Integrated Breeding for Carotenoids and Folates in Staple Cereal Grains to Reduce Malnutrition

Globally, two billion people suffer from micronutrient deficiencies. Cereal grains provide more than 50% of the daily requirement of calories in human diets, but they often fail to provide adequate essential minerals and vitamins. Cereal crop production in developing countries achieved remarkable yield gains through the efforts of the Green Revolution (117% in rice, 30% in wheat, 530% in maize, and 188% in pearl millet). However, modern varieties are often deficient in essential micronutrients compared to traditional varieties and land races. Breeding for nutritional quality in staple cereals is a challenging task; however, biofortification initiatives combined with genomic tools increase the feasibility. Current biofortification breeding activities include improving rice (for zinc), wheat (for zinc), maize (for provitamin A), and pearl millet (for iron and zinc). Biofortification is a sustainable approach to enrich staple cereals with provitamin A, carotenoids, and folates. Significant genetic variation has been found for provitamin A (96-850 μg and 12-1780 μg in 100 g in wheat and maize, respectively), carotenoids (558-6730 μg in maize), and folates in rice (11-51 μg) and wheat (32.3-89.1 μg) in 100 g. This indicates the prospects for biofortification breeding. Several QTLs associated with carotenoids and folates have been identified in major cereals, and the most promising of these are presented here. Breeding for essential nutrition should be a core objective of next-generation crop breeding. This review synthesizes the available literature on folates, provitamin A, and carotenoids in rice, wheat, maize, and pearl millet, including genetic variation, trait discovery, QTL identification, gene introgressions, and the strategy of genomics-assisted biofortification for these traits. Recent evidence shows that genomics-assisted breeding for grain nutrition in rice, wheat, maize, and pearl millet crops have good potential to aid in the alleviation of micronutrient malnutrition in many developing countries.

Genome-Wide Association Studies and Genomic Selection in Pearl Millet: Advances and Prospects

Pearl millet is a climate-resilient, drought-tolerant crop capable of growing in marginal environments of arid and semi-arid regions globally. Pearl millet is a staple food for more than 90 million people living in poverty and can address the triple burden of malnutrition substantially. It remained a neglected crop until the turn of the 21st century, and much emphasis has been placed since then on the development of various genetic and genomic resources for whole-genome scan studies, such as the genome-wide association studies (GWAS) and genomic selection (GS). This was facilitated by the advent of sequencing-based genotyping, such as genotyping-by-sequencing (GBS), RAD-sequencing, and whole-genome re-sequencing (WGRS) in pearl millet. To carry out GWAS and GS, a world association mapping panel called the Pearl Millet inbred Germplasm Association Panel (PMiGAP) was developed at ICRISAT in partnership with Aberystwyth University. This panel consisted of germplasm lines, landraces, and breeding lines from 27 countries and was re-sequenced using the WGRS approach. It has a repository of circa 29 million genome-wide SNPs. PMiGAP has been used to map traits related to drought tolerance, grain Fe and Zn content, nitrogen use efficiency, components of endosperm starch, grain yield, etc. Genomic selection in pearl millet was jump-started recently by WGRS, RAD, and tGBS (tunable genotyping-by-sequencing) approaches for the PMiGAP and hybrid parental lines. Using multi-environment phenotyping of various training populations, initial attempts have been made to develop genomic selection models. This mini review discusses advances and prospects in GWAS and GS for pearl millet.

Assessment of Water and Nitrogen Use Efficiencies Through UAV-Based Multispectral Phenotyping in Winter Wheat

Unmanned aerial vehicle (UAV) based remote sensing is a promising approach for non-destructive and high-throughput assessment of crop water and nitrogen (N) efficiencies. In this study, UAV was used to evaluate two field trials using four water (T0 = 0 mm, T1 = 80 mm, T2 = 120 mm, and T3 = 160 mm), and four N (T0 = 0, T1 = 120 kg ha^-1, T2 = 180 kg ha^-1, and T3 = 240 kg ha^-1) treatments, respectively, conducted on three wheat genotypes at two locations. Ground-based destructive data of water and N indictors such as biomass and N contents were also measured to validate the aerial surveillance results. Multispectral traits including red normalized difference vegetation index (RNDVI), green normalized difference vegetation index (GNDVI), normalized difference red-edge index (NDRE), red-edge chlorophyll index (RECI) and normalized green red difference index (NGRDI) were recorded using UAV as reliable replacement of destructive measurements by showing high r values up to 0.90. NGRDI was identified as the most efficient non-destructive indicator through strong prediction values ranged from R ² = 0.69 to 0.89 for water use efficiencies (WUE) calculated from biomass (WUE.BM), and R ² = 0.80 to 0.86 from grain yield (WUE.GY). RNDVI was better in predicting the phenotypic variations for N use efficiency calculated from nitrogen contents of plant samples (NUE.NC) with high R ² values ranging from 0.72 to 0.94, while NDRE was consistent in predicting both NUE.NC and NUE.GY by 0.73 to 0.84 with low root mean square errors. UAV-based remote sensing demonstrates that treatment T2 in both water 120 mm and N 180 kg ha^-1 supply trials was most appropriate dosages for optimum uptake of water and N with high GY. Among three cultivars, Zhongmai 895 was highly efficient in WUE and NUE across the water and N treatments. Conclusively, UAV can be used to predict time-series WUE and NUE across the season for selection of elite genotypes, and to monitor crop efficiency under varying N and water dosages.

Physiological and Proteomic Signatures Reveal Mechanisms of Superior Drought Resilience in Pearl Millet Compared to Wheat

Presently, pearl millet and wheat are belonging to highly important cereal crops. Pearl millet, however, is an under-utilized crop, despite its superior resilience to drought and heat stress in contrast to wheat. To investigate this in more detail, we performed comparative physiological screening and large scale proteomics of drought stress responses in drought-tolerant and susceptible genotypes of pearl millet and wheat. These chosen genotypes are widely used in breeding and farming practices. The physiological responses demonstrated large differences in the regulation of root morphology and photosynthetic machinery, revealing a stay-green phenotype in pearl millet. Subsequent tissue-specific proteome analysis of leaves, roots and seeds led to the identification of 12,558 proteins in pearl millet and wheat under well-watered and stress conditions. To allow for this comparative proteome analysis and to provide a platform for future functional proteomics studies we performed a systematic phylogenetic analysis of all orthologues in pearl millet, wheat, foxtail millet, sorghum, barley, brachypodium, rice, maize, Arabidopsis, and soybean. In summary, we define (i) a stay-green proteome signature in the drought-tolerant pearl millet phenotype and (ii) differential senescence proteome signatures in contrasting wheat phenotypes not capable of coping with similar drought stress. These different responses have a significant effect on yield and grain filling processes reflected by the harvest index. Proteome signatures related to root morphology and seed yield demonstrated the unexpected intra- and interspecies-specific biochemical plasticity for stress adaptation for both pearl millet and wheat genotypes. These quantitative reference data provide tissue- and phenotype-specific marker proteins of stress defense mechanisms which are not predictable from the genome sequence itself and have potential value for marker-assisted breeding beyond genome assisted breeding.

Genome-Wide Population Structure Analyses of Three Minor Millets: Kodo Millet, Little Millet, and Proso Millet

Developed genome-wide SNP marker data for kodo, proso, and little millet Marker data used to analyze genetic diversity Heritability results of various traits used to validate genetic data Millets are a diverse group of small-seeded grains that are rich in nutrients but have received relatively little advanced plant breeding research. Millets are important to smallholder farmers in Africa and Asia because of their short growing season, good stress tolerance, and high nutritional content. To advance the study and use of these species, we present genome-wide marker datasets and population structure analyses for three minor millets: kodo millet (Paspalum scrobiculatum L.), little millet (Panicum sumatrense Roth), and proso millet (Panicum miliaceum L.).We generated genome-wide marker data sets for 190 accessions of each species with genotyping-by-sequencing (GBS). After filtering, we retained between 161 and 165 accessions of each species, with 3461, 2245, and 1882 single-nucleotide polymorphisms (SNPs) for kodo, little, and proso millet, respectively. Population genetic analysis revealed seven putative subpopulations of kodo millet and eight each of proso millet and little millet. To confirm the accuracy of this genetic data, we used public phenotype data on a subset of these accessions to estimate the heritability of various agronomically relevant phenotypes. Heritability values largely agree with the prior expectation for each phenotype, indicating that these SNPs provide an accurate genome-wide sample of genetic variation. These data represent one of first genome-wide population genetics analyses-and the most extensive-in these species and the first genomic analyses of any sort for little millet and kodo millet. These data will be a valuable resource for researchers and breeders trying to improve these crops for smallholder farmers.

Genetic Diversity, Population Structure, and Linkage Disequilibrium of Pearl Millet

Mapping of GBS reads of 398 accessions to the draft genome sequence identified 82,112 SNPs Model-based clustering analysis revealed a hierarchical genetic structure of six subgroups Greater LD decay in the west-African subpopulation is likely due to long history of recombination Genetic differentiation analysis among subpopulations revealed variation in selection signatures Pearl millet [Cenchrus americanus (L.) Morrone syn. Pennisetum glaucum (L.) R. Br.] is one of the most extensively cultivated cereals in the world, after wheat (Triticum aestivum L.), maize (Zea mays L.), rice (Oryza sativa L.), barley (Hordeum vulgare L.), and sorghum [Sorghum bicolor (L.) Moench]. It is the main component of traditional farming systems and a staple food in the arid and semiarid regions of Africa and southern Asia. However, its genetic improvement is lagging behind other major cereals and the yield is still low. Genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) markers were screened on a total of 398 accessions from different geographic regions to assess genetic diversity, population structure, and linkage disequilibrium (LD). By mapping the GBS reads to the reference genome sequence, 82,112 genome-wide SNPs were discovered. The telomeric regions of the chromosomes have the higher SNP density than in pericentromeric regions. Model-based clustering analysis of the population revealed a hierarchical genetic structure of six subgroups that mostly overlap with the geographic origins or sources of the genotypes but with differing levels of admixtures. A neighbor-joining phylogeny analysis revealed that germplasm from western Africa rooted the dendrogram with much diversity within each subgroup. Greater LD decay was observed in the west-African subpopulation than in the other subpopulations, indicating a long history of recombination among landraces. Also, genome scan of genetic differentiatation detected different selection histories among subpopulations. These results have potential application in the development of genomic-assisted breeding in pearl millet and heterotic grouping of the lines for improved hybrid performance.

Selection Criteria for Drought-Tolerant Bread Wheat Genotypes at Seedling Stage

Diminishing water resources as a result of excessive use of water for irrigation and climate change posture a severe global threat to food security. Herein, an experiment was conducted to determine the selection criteria for drought-tolerant bread wheat genotypes at the seedling stage using morphological and photosynthetic pigmentation-related traits. A panel of 105 wheat landraces, historical Pakistani varieties, and advance breeding lines were evaluated under normal and drought stress using factorial completely randomized design. The root length, fresh weight, dry weight, cell membrane thermo-stability, and chlorophyll b were positively correlated among themselves under both normal and stress conditions. Hence, selection of any one of these traits enhances the performance of other traits. The shoot length was non-significant and negatively associated with all other studied characters except relative water content. The results suggested that selection for shoot length could not improve genetic gain for drought tolerance. Out of 10 principal components (PCs), the first three PCs were showed significant genetic variation under both conditions. The first three PCs showed 74.6% and 76% cumulative genetic variation under normal and drought conditions, respectively. Based on PCA, 10 drought-tolerant and five drought-susceptible genotypes were identified. Overall results suggested that selection for root length, fresh weight, dry weight, cell membrane thermo-stability, and chlorophyll b at the seedling stage would improve genetic gain for drought tolerance. The outperforming genotypes under drought stress conditions can be useful in future wheat breeding programs, and early selection for the traits recommended in this study will be effective for developing high-yielding and drought-tolerant wheat varieties.

Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat

BACKGROUND

Plant height is an important selection target since it is associated with yield potential, stability and particularly with lodging resistance in various environments. Rapid and cost-effective estimation of plant height from airborne devices using a digital surface model can be integrated with academic research and practical wheat breeding programs. A bi-parental wheat population consisting of 198 doubled haploid lines was used for time-series assessments of progress in reaching final plant height and its accuracy was assessed by quantitative genomic analysis. UAV-based data were collected at the booting and mid-grain fill stages from two experimental sites and compared with conventional measurements to identify quantitative trait loci (QTL) underlying plant height.

RESULTS

A significantly high correlation of R 2 = 0.96 with a 5.75 cm root mean square error was obtained between UAV-based plant height estimates and ground truth observations at mid-grain fill across both sites. Correlations for UAV and ground-based plant height data were also very high (R 2 = 0.84-0.85, and 0.80-0.83) between plant height at the booting and mid-grain fill stages, respectively. Broad sense heritabilities were 0.92 at booting and 0.90-0.91 at mid-grain fill across sites for both data sets. Two major QTL corresponding to Rht-B1 on chromosome 4B and Rht-D1 on chromosome 4D explained 61.3% and 64.5% of the total phenotypic variations for UAV and ground truth data, respectively. Two new and stable QTL on chromosome 6D seemingly associated with accelerated plant growth was identified at the booting stage using UAV-based data. Genomic prediction accuracy for UAV and ground-based data sets was significantly high, ranging from r = 0.47-0.55 using genome-wide and QTL markers for plant height. However, prediction accuracy declined to r = 0.20-0.31 after excluding markers linked to plant height QTL.

CONCLUSION

This study provides a fast way to obtain time-series estimates of plant height in understanding growth dynamics in bread wheat. UAV-enabled phenotyping is an effective, high-throughput and cost-effective approach to understand the genetic basis of plant height in genetic studies and practical breeding.

Genome-Wide Association Study of Major Agronomic Traits in Foxtail Millet (Setaria italica L.) Using ddRAD Sequencing

Foxtail millet (Setaria italica), the second largest cultivated millet crop after pearl millet, is utilized for food and forage globally. Further, it is also considered as a model crop for studying agronomic, nutritional and biofuel traits. In the present study, a genome-wide association study (GWAS) was performed for ten important agronomic traits in 142 foxtail millet core eco-geographically diverse genotypes using 10 K SNPs developed through GBS-ddRAD approach. Number of SNPs on individual chromosome ranged from 844 (chromosome 5) to 2153 (chromosome 8) with an average SNP frequency of 25.9 per Mb. The pairwise linkage disequilibrium (LD) estimated using the squared-allele frequency correlations was found to decay rapidly with the genetic distance of 177 Kb. However, for individual chromosome, LD decay distance ranged from 76 Kb (chromosome 6) to 357 Kb (chromosome 4). GWAS identified 81 MTAs (marker-trait associations) for ten traits across the genome. High confidence MTAs for three important agronomic traits including FLW (flag leaf width), GY (grain yield) and TGW (thousand-grain weight) were identified. Significant pyramiding effect of identified MTAs further supplemented its importance in breeding programs. Desirable alleles and superior genotypes identified in the present study may prove valuable for foxtail millet improvement through marker-assisted selection.

UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought

Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F2 partially inbred population (termed here 'POP6'), whose F1 was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature (Tc) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype variability under drought stress conditions. Tc derived from aerial thermal imagery presented a good correlation with ground-truth stomatal conductance (gs) in both segmentation techniques. Interestingly, the HTFP approach was instrumental to detect drought-tolerant response in 25% of the population. This study shows the potential of UAV-based thermal imaging for field phenomics of poplar and other tree species. This is anticipated to have tremendous implications for accelerating forest tree genetic improvement against abiotic stress.

Pearl millet genome sequence provides a resource to improve agronomic traits in arid environments

Draft genome, 994 re-sequenced lines and GWAS for yield-traits provide a resource of genetics and genomics tools for pearl millet researchers and breeders.

Pearl millet [Cenchrus americanus (L.) Morrone] is a staple food for more than 90 million farmers in arid and semi-arid regions of sub-Saharan Africa, India and South Asia. We report the ∼1.79 Gb draft whole genome sequence of reference genotype Tift 23D₂B₁-P1-P5, which contains an estimated 38,579 genes. We highlight the substantial enrichment for wax biosynthesis genes, which may contribute to heat and drought tolerance in this crop. We resequenced and analyzed 994 pearl millet lines, enabling insights into population structure, genetic diversity and domestication. We use these resequencing data to establish marker trait associations for genomic selection, to define heterotic pools, and to predict hybrid performance. We believe that these resources should empower researchers and breeders to improve this important staple crop.

Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes

There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses.

Identification of putative QTLs for seedling stage phosphorus starvation response in finger millet (Eleusine coracana L. Gaertn.) by association mapping and cross species synteny analysis

A germplasm assembly of 128 finger millet genotypes from 18 countries was evaluated for seedling-stage phosphorus (P) responses by growing them in P sufficient (Psuf) and P deficient (Pdef) treatments. Majority of the genotypes showed adaptive responses to low P condition. Based on phenotype behaviour using the best linear unbiased predictors for each trait, genotypes were classified into, P responsive, low P tolerant and P non-responsive types. Based on the overall phenotype performance under Pdef, 10 genotypes were identified as low P tolerants. The low P tolerant genotypes were characterised by increased shoot and root length and increased root hair induction with longer root hairs under Pdef, than under Psuf. Association mapping of P response traits using mixed linear models revealed four quantitative trait loci (QTLs). Two QTLs (qLRDW.1 and qLRDW.2) for low P response affecting root dry weight explained over 10% phenotypic variation. In silico synteny analysis across grass genomes for these QTLs identified putative candidate genes such as Ser-Thr kinase and transcription factors such as WRKY and basic helix-loop-helix (bHLH). The QTLs for response under Psuf were mapped for traits such as shoot dry weight (qHSDW.1) and root length (qHRL.1). Putative associations of these QTLs over the syntenous regions on the grass genomes revealed proximity to cytochrome P450, phosphate transporter and pectin methylesterase inhibitor (PMEI) genes. This is the first report of the extent of phenotypic variability for P response in finger millet genotypes during seedling-stage, along with the QTLs and putative candidate genes associated with P starvation tolerance.

Genome-wide association mapping of latex yield and girth in Amazonian accessions of Hevea brasiliensis grown in a suboptimal climate zone

Latex yield and growth are the key complex traits in commercial rubber production. The present study is the first to report genome-wide association mapping of latex yield and girth, for 170 Amazonian accessions grown in a suboptimal area characterized by limited rainfall and a lengthy dry season. Targeted sequence enrichment to capture gene transcripts generated 14,155 high quality filtered single nucleotide polymorphisms (SNPs) of which 94.3% resided in coding regions. The rapid decay of linkage disequilibrium over physical and genetic distance found in the accessions was comparable to those previously reported for several outcrossing species. A mixed linear model detected three significant SNPs in three candidate genes involved in plant adaptation to drought stress, individually explaining 12.7-15.7% of the phenotypic variance. The SNPs identified in the study will help to extend understanding, and to support genetic improvement of rubber trees grown in drought-affected regions.

Identification of genomic regions for grain yield and yield stability and their epistatic interactions

The task of identifying genomic regions conferring yield stability is challenging in any crop and requires large experimental data sets in conjunction with complex analytical approaches. We report findings of a first attempt to identify genomic regions with stable expression and their individual epistatic interactions for grain yield and yield stability in a large elite panel of wheat under multiple environments via a genome wide association mapping (GWAM) approach. Seven hundred and twenty lines were genotyped using genotyping-by-sequencing technology and phenotyped for grain yield and phenological traits. High gene diversity (0.250) and a moderate genetic structure (five groups) in the panel provided an excellent base for GWAM. The mixed linear model and multi-locus mixed model analyses identified key genomic regions on chromosomes 2B, 3A, 4A, 5B, 7A and 7B. Further, significant epistatic interactions were observed among loci with and without main effects that contributed to additional variation of up to 10%. Simple stepwise regression provided the most significant main effect and epistatic markers resulting in up to 20% variation for yield stability and up to 17% gain in yield with the best allelic combination.

Unexpected pattern of pearl millet genetic diversity among ethno-linguistic groups in the Lake Chad Basin

Despite of a growing interest in considering the role of sociological factors in seed exchanges and their consequences on the evolutionary dynamics of agro-biodiversity, very few studies assessed the link between ethno-linguistic diversity and genetic diversity patterns in small-holder farming systems. This is key for optimal improvement and conservation of crop genetic resources. Here, we investigated genetic diversity at 17 SSR markers of pearl millet landraces (varieties named by farmers) in the Lake Chad Basin. 69 pearl millet populations, representing 27 landraces collected in eight ethno-linguistic farmer groups, were analyzed. We found that the farmers' local taxonomy was not a good proxy for population's genetic differentiation as previously shown at smaller scales. Our results show the existence of a genetic structure of pearl millet mainly associated with ethno-linguistic diversity in the western side of the lake Chad. It suggests there is a limit to gene flow between landraces grown by different ethno-linguistic groups. This result was rather unexpected, because of the highly outcrossing mating system of pearl millet, the high density of pearl millet fields all along the green belt of this Sahelian area and the fact that seed exchanges among ethno-linguistic groups are known to occur. In the eastern side of the Lake, the pattern of genetic diversity suggests a larger efficient circulation of pearl millet genes between ethno-linguistic groups that are less numerous, spatially intermixed and, for some of them, more prone to exogamy. Finally, other historical and environmental factors which may contribute to the observed diversity patterns are discussed.

Exploration of Genetic and Genomic Resources for Abiotic and Biotic Stress Tolerance in Pearl Millet

Pearl millet is one of the most important small-grained C4 Panicoid crops with a large genome size (∼2352 Mb), short life cycle and outbreeding nature. It is highly resilient to areas with scanty rain and high temperature. Pearl millet is a nutritionally superior staple crop for people inhabiting hot, drought-prone arid and semi-arid regions of South Asia and Africa where it is widely grown and used for food, hay, silage, bird feed, building material, and fuel. Having excellent nutrient composition and exceptional buffering capacity against variable climatic conditions and pathogen attack makes pearl millet a wonderful model crop for stress tolerance studies. Pearl millet germplasm show a large range of genotypic and phenotypic variations including tolerance to abiotic and biotic stresses. Conventional breeding for enhancing abiotic and biotic stress resistance in pearl millet have met with considerable success, however, in last few years various novel approaches including functional genomics and molecular breeding have been attempted in this crop for augmenting yield under adverse environmental conditions, and there is still a lot of scope for further improvement using genomic tools. Discovery and use of various DNA-based markers such as EST-SSRs, DArT, CISP, and SSCP-SNP in pearl millet not only help in determining population structure and genetic diversity but also prove to be important for developing strategies for crop improvement at a faster rate and greater precision. Molecular marker-based genetic linkage maps and identification of genomic regions determining yield under abiotic stresses particularly terminal drought have paved way for marker-assisted selection and breeding of pearl millet cultivars. Reference collections and marker-assisted backcrossing have also been used to improve biotic stress resistance in pearl millet specifically to downy mildew. Whole genome sequencing of pearl millet genome will give new insights for processing of functional genes and assist in crop improvement programs through molecular breeding approaches. This review thus summarizes the exploration of pearl millet genetic and genomic resources for improving abiotic and biotic stress resistance and development of cultivars superior in stress tolerance.

UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought

Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F₂ partially inbred population (termed here 'POP6'), whose F₁ was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature (T_c) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype variability under drought stress conditions. T_c derived from aerial thermal imagery presented a good correlation with ground-truth stomatal conductance (g_s) in both segmentation techniques. Interestingly, the HTFP approach was instrumental to detect drought-tolerant response in 25% of the population. This study shows the potential of UAV-based thermal imaging for field phenomics of poplar and other tree species. This is anticipated to have tremendous implications for accelerating forest tree genetic improvement against abiotic stress.

Deciphering Genomic Regions for High Grain Iron and Zinc Content Using Association Mapping in Pearl Millet

Micronutrient malnutrition, especially deficiency of two mineral elements, iron [Fe] and zinc [Zn] in the developing world needs urgent attention. Pearl millet is one of the best crops with many nutritional properties and is accessible to the poor. We report findings of the first attempt to mine favorable alleles for grain iron and zinc content through association mapping in pearl millet. An association mapping panel of 130 diverse lines was evaluated at Delhi, Jodhpur and Dharwad, representing all the three pearl millet growing agro-climatic zones of India, during 2014 and 2015. Wide range of variation was observed for grain iron (32.3-111.9 ppm) and zinc (26.6-73.7 ppm) content. Genotyping with 114 representative polymorphic SSRs revealed 0.35 mean gene diversity. STRUCTURE analysis revealed presence of three sub-populations which was further supported by Neighbor-Joining method of clustering and principal coordinate analysis (PCoA). Marker-trait associations (MTAs) were analyzed with 267 markers (250 SSRs and 17 genic markers) in both general linear model (GLM) and mixed linear model (MLM), however, MTAs resulting from MLM were considered for more robustness of the associations. After appropriate Bonferroni correction, Xpsmp 2261 (13.34% R²-value), Xipes 0180 (R²-value of 11.40%) and Xipes 0096 (R²-value of 11.38%) were consistently associated with grain iron and zinc content for all the three locations. Favorable alleles and promising lines were identified for across and specific environments. PPMI 1102 had highest number (7) of favorable alleles, followed by four each for PPMFeZMP 199 and PPMI 708 for across the environment performance for both grain Fe and Zn content, while PPMI 1104 had alleles specific to Dharwad for grain Fe and Zn content. When compared with the reference genome Tift 23D₂B₁-P1-P5, Xpsmp 2261 amplicon was identified in intergenic region on pseudomolecule 5, while the other marker, Xipes 0810 was observed to be overlapping with aspartic proteinase (Asp) gene on pseudomolecule 3. Thus, this study can help in breeding new lines with enhanced micronutrient content using marker-assisted selection (MAS) in pearl millet leading to improved well-being especially for women and children.