Functional Dissection of the Chickpea (Cicer arietinum L.) Stay-Green Phenotype Associated with Molecular Variation at an Ortholog of Mendel's I Gene for Cotyledon Color: Implications for Crop Production and Carotenoid Biofortification

Seed-Coat Pigmentation Plays a Crucial Role in Partner Selection and N2 Fixation in Legume-Root-Microbe Associations in African Soils

Legume-rhizobia symbiosis is the most important plant-microbe interaction in sustainable agriculture due to its ability to provide much needed N in cropping systems. This interaction is mediated by the mutual recognition of signaling molecules from the two partners, namely legumes and rhizobia. In legumes, these molecules are in the form of flavonoids and anthocyanins, which are responsible for the pigmentation of plant organs, such as seeds, flowers, fruits, and even leaves. Seed-coat pigmentation in legumes is a dominant factor influencing gene expression relating to N2 fixation and may be responsible for the different N2-fixing abilities observed among legume genotypes under field conditions in African soils. Common bean, cowpea, Kersting's groundnut, and Bambara groundnut landraces with black seed-coat color are reported to release higher concentrations of nod-gene-inducing flavonoids and anthocyanins compared with the Red and Cream landraces. Black seed-coat pigmentation is considered a biomarker for enhanced nodulation and N2 fixation in legumes. Cowpea, Bambara groundnut, and Kersting's bean with differing seed-coat colors are known to attract different soil rhizobia based on PCR-RFLP analysis of bacterial DNA. Even when seeds of the same legume with diverse seed-coat colors were planted together in one hole, the nodulating bradyrhizobia clustered differently in the PCR-RFLP dendrogram. Kersting's groundnut, Bambara groundnut, and cowpea with differing seed-coat colors were selectively nodulated by different bradyrhizobial species. The 16S rRNA amplicon sequencing also found significant selective influences of seed-coat pigmentation on microbial community structure in the rhizosphere of five Kersting's groundnut landraces. Seed-coat color therefore plays a dominant role in the selection of the bacterial partner in the legume-rhizobia symbiosis.

Dissecting the genetic basis of drought responses in common bean using natural variation

The common bean (Phaseolus vulgaris L) is the most important legume for human consumption, contributing 30% of the total daily protein intake in developing countries. A major limitation for its cultivation is drought, which causes more than 60% of the annual losses. Among physiological adaptations to drought, delaying senescence and extending the photosynthetic capacity can improve crop productivity. This strategy is known as functional "stay-green" (SG) and has been discussed as a goal in plant breeding to alleviate the loss of yield under water scarcity conditions. The genetic components behind SG traits have been explored specially in cereals, but they are to date poorly studied in the common bean. For this, we screened 71 common bean cultivars belonging to the three most important gene-pools, Mesoamerica, Andes and Europe, selected to cover the natural variation of the species. Phenotyping experiments under terminal drought during long-days in greenhouse conditions, identified six photoperiod insensitive cultivars of European origin with a clear SG phenotype. Using SNP data produced from whole genome re-sequencing data, we obtained 10 variants significantly associated to the SG phenotype on chromosomes 1, 3, 7, 8, 9 and 10 that are in close proximity to gene models with functional annotations related to hormone signaling and anti-oxidant production. Calculating pairwise FST between subgroups of cultivars divided according to their drought response (susceptibility, escape, recovery or SG), we identified up to 29 genomic windows accounting for 1,45Mb that differentiate SG cultivars; these signals were especially strong on chromosomes 1, 5 and 10. Within these windows, we found genes directly involved in photosynthetic processes and trehalose synthesis. Altogether, these signals represent good targets for further characterization and highlight the multigenic nature of the SG response in legumes.

Safflower (Carthamus tinctorius L.) crop adaptation to residual moisture stress: conserved water use and canopy temperature modulation are better adaptive mechanisms

Oilseeds with high productivity and tolerance to various environmental stresses are in high demand in the food and industrial sectors. Safflower, grown under residual moisture in the semi-arid tropics, is adapted to moisture stress at certain levels. However, a substantial reduction in soil moisture has a significant impact on its productivity. Therefore, assessing genetic variation for water use efficiency traits like transpiration efficiency (TE), water uptake, and canopy temperature depression (CTD) is essential for enhancing crop adaptation to drought. The response of safflower genotypes (n = 12) to progressive soil moisture depletion was studied in terms of water uptake, TE, and CTD under a series of pot and field experiments. The normalised transpiration rate (NTR) in relation to the fraction of transpirable soil water (FTSW) varied significantly among genotypes. The genotypes A-1, Bhima, GMU-2347, and CO-1 had higher NTR-FTSW threshold values of 0.79 (R2 = 0.92), 0.74 (R2 = 0.96), 0.71 (R2 = 0.96), and 0.71 (R2 = 0.91), respectively, whereas GMU-2644 had the lowest 0.38 (R2 = 0.93). TE was high in genotype GMU-2347, indicating that it could produce maximum biomass per unit of water transpired. At both the vegetative and reproductive stages, significant positive relationships between TE, SPAD chlorophyll metre reading (SCMR) (p < 0.01) and CTD (p < 0.01) were observed under field conditions by linear regression. The genotypes with high FTSW-NTR thresholds, high SCMR, and low CTD may be useful clues in identifying a genotype's ability to adapt to moisture stress. The findings showed that the safflower genotypes A-1, Bhima, GMU-2347, and CO-1 exhibited an early decline and regulated water uptake by conserving it for later growth stages under progressive soil water depletion.

Homolog of Pea SGR Controls Stay-Green in Faba Bean (Vicia faba L.)

Faba bean is an important legume crop consumed as a vegetable or snack food, and its green cotyledons could present an attractive color for consumers. A mutation in SGR causes stay-green in plants. In this study, vfsgr was identified from a green-cotyledon-mutant faba bean, SNB7, by homologous blast between the SGR of pea and the transcriptome of faba bean. Sequence analysis revealed that a SNP at position 513 of the CDS of VfSGR caused a pre-stop codon, resulting in a shorter protein in the green-cotyledon faba bean SNB7. A dCaps marker was developed according to the SNP that caused the pre-stop, and this marker was completely associated with the color of the cotyledon of faba bean. SNB7 stayed green during dark treatment, while the expression level of VfSGR increased during dark-induced senescence in the yellow-cotyledon faba bean HST. Transient expression of VfSGR in Nicotiana. benthamiana leaves resulted in chlorophyll degradation. These results indicate that vfsgr is the gene responsible for the stay-green of faba bean, and the dCaps marker developed in this study provides a molecular tool for the breeding of green-cotyledon faba beans.

The Key to the Future Lies in the Past: Insights from Grain Legume Domestication and Improvement Should Inform Future Breeding Strategies

Crop domestication is a co-evolutionary process that has rendered plants and animals significantly dependent on human interventions for survival and propagation. Grain legumes have played an important role in the development of Neolithic agriculture some 12,000 years ago. Despite being early companions of cereals in the origin and evolution of agriculture, the understanding of grain legume domestication has lagged behind that of cereals. Adapting plants for human use has resulted in distinct morpho-physiological changes between the wild ancestors and domesticates, and this distinction has been the focus of several studies aimed at understanding the domestication process and the genetic diversity bottlenecks created. Growing evidence from research on archeological remains, combined with genetic analysis and the geographical distribution of wild forms, has improved the resolution of the process of domestication, diversification and crop improvement. In this review, we summarize the significance of legume wild relatives as reservoirs of novel genetic variation for crop breeding programs. We describe key legume features, which evolved in response to anthropogenic activities. Here, we highlight how whole genome sequencing and incorporation of omics-level data have expanded our capacity to monitor the genetic changes accompanying these processes. Finally, we present our perspective on alternative routes centered on de novo domestication and re-domestication to impart significant agronomic advances of novel crops over existing commodities. A finely resolved domestication history of grain legumes will uncover future breeding targets to develop modern cultivars enriched with alleles that improve yield, quality and stress tolerance.

Genome-wide association analysis to delineate high-quality SNPs for seed micronutrient density in chickpea (Cicer arietinum L.)

Chickpea is the most important nutrient-rich grain legume crop in the world. A diverse core set of 147 chickpea genotypes was genotyped with a Axiom(®)50K CicerSNP array and trait phenotyped in two different environments for four seed micronutrients (Zn, Cu, Fe and Mn). The trait data and high-throughput 50K SNP genotypic data were used for the genome-wide association study (GWAS). The study led to the discovery of genes/QTLs for seed Zn, Cu, Fe and Mn, concentrations in chickpea. The analysis of seed micronutrient data revealed significant differences for all four micronutrient concentrations (P ≤ 0.05). The mean concentrations of seed Zn, Cu, Fe and Mn pooled over the 2 years were 45.9 ppm, 63.8 ppm 146.1 ppm, and 27.0 ppm, respectively. The analysis of results led to the identification of 35 SNPs significantly associated with seed Zn, Cu, Fe and Mn concentrations. Among these 35 marker-trait associations (MTAs), 5 were stable (consistently identified in different environments), 6 were major (explaining more than 15% of the phenotypic variation for an individual trait) and 3 were both major and stable MTAs. A set of 6 MTAs, MTAs (3 for Mn, 2 for Fe, and 1 for Cu) reported by us during the present study have been also reported in the same/almost same genomic regions in earlier studies and therefore declared as validated MTAs. The stable, major and validated MTAs identified during the present study will prove useful in future chickpea molecular breeding programs aimed at enhancing the seed nutrient density of chickpea.

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.

Machine Learning-Based Plant Detection Algorithms to Automate Counting Tasks Using 3D Canopy Scans

This study tested whether machine learning (ML) methods can effectively separate individual plants from complex 3D canopy laser scans as a prerequisite to analyzing particular plant features. For this, we scanned mung bean and chickpea crops with PlantEye (R) laser scanners. Firstly, we segmented the crop canopies from the background in 3D space using the Region Growing Segmentation algorithm. Then, Convolutional Neural Network (CNN) based ML algorithms were fine-tuned for plant counting. Application of the CNN-based (Convolutional Neural Network) processing architecture was possible only after we reduced the dimensionality of the data to 2D. This allowed for the identification of individual plants and their counting with an accuracy of 93.18% and 92.87% for mung bean and chickpea plants, respectively. These steps were connected to the phenotyping pipeline, which can now replace manual counting operations that are inefficient, costly, and error-prone. The use of CNN in this study was innovatively solved with dimensionality reduction, addition of height information as color, and consequent application of a 2D CNN-based approach. We found there to be a wide gap in the use of ML on 3D information. This gap will have to be addressed, especially for more complex plant feature extractions, which we intend to implement through further research.

Legume Genetics and Biology: From Mendel's Pea to Legume Genomics

Legumes have played an important part in cropping systems since the dawn of agriculture, both as human food and as animal feed. The legume family is arguably one of the most abundantly domesticated crop plant families. Their ability to symbiotically fix nitrogen and improve soil fertility has been rewarded since antiquity and makes them a key protein source. The pea was the original model organism used in Mendel’s discovery of the laws of inheritance, making it the foundation of modern plant genetics. This Special Issue provides up-to-date information on legume biology, genetic advances, and the legacy of Mendel.