Validation and identification of promising gene specific markers governing foliar disease resistance in groundnut (Arachis hypogaea L.).

BACKGROUND: Groundnut is vulnerable to the major foliar fungal disease viz., late leaf spot (LLS) and rust in kharif season, which results in severe yield losses. Until now, LLS and rust resistance linked markers were developed based on GPBD 4 as a major donor source and were validated in its derivatives only, which restricted their use in marker assisted selection (MAS) involving other donors. METHODS AND RESULTS: The current study focused to validate LLS and rust resistance linked markers employing advanced breeding lines of F6 generation, derived from nine different crosses involving nine diverse parents, to identify potential markers for marker-assisted breeding of LLS and rust resistance in groundnut. Out of 28-trait linked markers used for validation, 8 were polymorphic (28.57%). Marker-trait association (MTA) and Single Marker Analysis (SMA) revealed that the SSR marker pPGPseq5D05 is significantly associated with both LLS (15.8% PVE) and rust (17.5% PVE) resistance, whereas, the marker IPAHM103 is tightly linked with rust resistance (26.8% PVE) alone. In silico analysis revealed that the marker gene for IPAHM103 is a zinc finger protein and the marker gene for pPGPseq5D05 is an ADP-ribosylation factor GTPase-activating protein. Both these protein products impart resistance or tolerance to biotic stress in crop plants. Two other markers namely, GMLQ975 and pPGPseq13A10 were also found to be associated with LLS resistance explaining MTA up to 60%. CONCLUSION: These gene specific markers will enable us to screen more number of germplasm lines or newly developed lines in MAS schemes for LLS and rust resistance using a wide range of resistant sources.

High-yield hybrid breeding of Camellia oleifolia based on ISSR molecular markers.

BACKGROUND: C. Oleifera is among the world's largest four woody plants known for their edible oil production, yet the contribution rate of improved varieties is less than 20%. The species traditional breeding is lengthy cycle (20-30 years), occupation of land resources, high labor cost, and low accuracy and efficiency, which can be enhanced by molecular marker-assisted selection. However, the lack of high-quality molecular markers hinders the species genetic analysis and molecular breeding. RESULTS: Through quantitative traits characterization, genetic diversity assessment, and association studies, we generated a selection population with wide genetic diversity, and identified five excellent high-yield parental combinations associated with four reliable high-yield ISSR markers. Early selection criteria were determined based on kernel fresh weight and cultivated 1-year seedling height, aided by the identification of these 4 ISSR markers. Specific assignment of selected individuals as paternal and maternal parents was made to capitalize on their unique attributes. CONCLUSIONS: Our results indicated that molecular markers-assisted breeding can effectively shorten, enhance selection accuracy and efficiency and facilitate the development of a new breeding system for C. oleifera.

Enhancing grain shape, thermotolerance, and alkaline tolerance via Gγ protein manipulation in rice.

KEY MESSAGE: Our findings highlight a valuable breeding resource, demonstrating the potential to concurrently enhance grain shape, thermotolerance, and alkaline tolerance by manipulating Gγ protein in rice. Temperate Geng/Japonica (GJ) rice yields have improved significantly, bolstering global food security. However, GJ rice breeding faces challenges, including enhancing grain quality, ensuring stable yields at warmer temperatures, and utilizing alkaline land. In this study, we employed CRISPR/Cas9 gene-editing technology to knock out the GS3 locus in seven elite GJ varieties with superior yield performance. Yield component measurements revealed that GS3 knockout mutants consistently enhanced grain length and reduced plant height in diverse genetic backgrounds. The impact of GS3 on the grain number per panicle and setting rate depended on the genetic background. GS3 knockout did not affect milling quality and minimally altered protein and amylose content but notably influenced chalkiness-related traits. GS3 knockout indiscriminately improved heat and alkali stress tolerance in the GJ varieties studied. Transcriptome analysis indicated differential gene expression between the GS3 mutants and their wild-type counterparts, enriched in biological processes related to photosynthesis, photosystem II stabilization, and pathways associated with photosynthesis and cutin, suberine, and wax biosynthesis. Our findings highlight GS3 as a breeding resource for concurrently improving grain shape, thermotolerance, and alkaline tolerance through Gγ protein manipulation in rice.

Pm57 from Aegilops searsii encodes a tandem kinase protein and confers wheat powdery mildew resistance.

Powdery mildew is a devastating disease that affects wheat yield and quality. Wheat wild relatives represent valuable sources of disease resistance genes. Cloning and characterization of these genes will facilitate their incorporation into wheat breeding programs. Here, we report the cloning of Pm57, a wheat powdery mildew resistance gene from Aegilops searsii. It encodes a tandem kinase protein with putative kinase-pseudokinase domains followed by a von Willebrand factor A domain (WTK-vWA), being ortholog of Lr9 that mediates wheat leaf rust resistance. The resistance function of Pm57 is validated via independent mutants, gene silencing, and transgenic assays. Stable Pm57 transgenic wheat lines and introgression lines exhibit high levels of all-stage resistance to diverse isolates of the Bgt fungus, and no negative impacts on agronomic parameters are observed in our experimental set-up. Our findings highlight the emerging role of kinase fusion proteins in plant disease resistance and provide a valuable gene for wheat breeding.

Microsatellite marker-assisted backcross breeding for improvement of wheat salt tolerance using Kharchia 65.

BACKGROUND: Salinity is a significant abiotic stress that affects plants from germination through all growth stages. This study was aimed to determine the morpho-physiological and genetic variations in BC1F2, BC2F1 and F3 generations resulting from the cross combination WH1105 × Kharchia 65. RESULTS: A significant reduction in germination percentage was observed under salt stress in BC1F2 and F3 seeds. Correlation, heritability in the broad sense, phenotypic coefficient of variability (PCV) and genotypic coefficient of variability (GCV) were measured for all traits. The presence of both Nax1 and Nax2 loci was confirmed in twenty-nine plants using the marker-assisted selection technique. Genetic relationships among the populations were assessed using twenty-four polymorphic SSR markers. CONCLUSION: Cluster analysis along with two and three-dimensional PCA scaling (Principal Component Analysis) revealed the distinct nature of WH 1105 and Kharchia 65. Six plants closer to the recurrent parent (WH1105) selected through this study can serve as valuable genetic material for salt-tolerant wheat improvement programs.

Pyramiding of bacterial blight resistance genes into promising restorer BRRI31R line through marker-assisted backcross breeding and evaluation of agro-morphological and physiochemical characteristics of developed resistant restorer lines.

BRRI31R is one of the Bangladesh's most promising restorer lines due to its abundant pollen producing capacity, strong restoring ability, good combining ability, high outcrossing rate and genetically diverse from cytoplasmic male sterile (CMS) line. But the drawback of this line is that it is highly susceptible to bacterial blight (BB) disease of rice caused by Xanthomonas oryzae pv. oryzae. The present study highlighted the pyramiding of effective BB resistance genes (xa5, xa13 and Xa21) into the background of BRRI31R, through marker-assisted backcrossing (MABC). Backcross progenies were confirmed and advanced based on the foreground selection of target genes. Pyramided lines were used for pathogenicity test against five Bangladeshi Xanthomonas oryzae (BXo) races (BXo93, BXo220, BXo822, BXo826, BXo887) and confirmed the dominant fertility restore genes, Rf3 and Rf4 and further validated against SNP markers for more confirmation of target resistance genes. All pyramided restorer lines consisted of Xa4 (in built), xa5, xa13, Xa21, and Chalk5 with two fertility restorer genes, Rf3, Rf4. and these restorer lines showed intermediate amylose content (<25%). Restorer lines BRRI31R-MASP3 and BRRI31R-MASP4 showed high levels of resistance against five virulent BXo races and SNP genotyping revealed that these lines also contained a blast resistance gene Pita races. Gene pyramided restorer lines, BRRI31R-MASP3 and BRRI31R-MASP4 can directly be used as a male parent for the development of new BB resistant hybrid rice variety or could be used as a replacement of restorer line of BRRI hybrid dhan5 and 7 to enhance the quality of hybrid seeds as well as rice production in Bangladesh.

TaeC: A manually annotated text dataset for trait and phenotype extraction and entity linking in wheat breeding literature.

Wheat varieties show a large diversity of traits and phenotypes. Linking them to genetic variability is essential for shorter and more efficient wheat breeding programs. A growing number of plant molecular information networks provide interlinked interoperable data to support the discovery of gene-phenotype interactions. A large body of scientific literature and observational data obtained in-field and under controlled conditions document wheat breeding experiments. The cross-referencing of this complementary information is essential. Text from databases and scientific publications has been identified early on as a relevant source of information. However, the wide variety of terms used to refer to traits and phenotype values makes it difficult to find and cross-reference the textual information, e.g. simple dictionary lookup methods miss relevant terms. Corpora with manually annotated examples are thus needed to evaluate and train textual information extraction methods. While several corpora contain annotations of human and animal phenotypes, no corpus is available for plant traits. This hinders the evaluation of text mining-based crop knowledge graphs (e.g. AgroLD, KnetMiner, WheatIS-FAIDARE) and limits the ability to train machine learning methods and improve the quality of information. The Triticum aestivum trait Corpus is a new gold standard for traits and phenotypes of wheat. It consists of 528 PubMed references that are fully annotated by trait, phenotype, and species. We address the interoperability challenge of crossing sparse assay data and publications by using the Wheat Trait and Phenotype Ontology to normalize trait mentions and the species taxonomy of the National Center for Biotechnology Information to normalize species. The paper describes the construction of the corpus. A study of the performance of state-of-the-art language models for both named entity recognition and linking tasks trained on the corpus shows that it is suitable for training and evaluation. This corpus is currently the most comprehensive manually annotated corpus for natural language processing studies on crop phenotype information from the literature.

Diversity in bread and durum wheat stigma morphology and linkage of increased stigma length to dwarfing gene Rht14.

KEY MESSAGE: The dwarfing allele Rht14 of durum wheat associates with greater stigma length, an important trait for hybrid breeding, whilst major dwarfing alleles Rht-B1b and Rht-D1b showed little to no effect. Although much understudied in wheat, the stigma is a crucial component for attaining grain set, the fundamental basis for yield, particularly in hybrid production systems where successful grain set relies on wind-driven pollen dispersal by the male parent and effective pollen capture by the female parent. Females with long stigma that exsert early are thought to be advantageous. Using glasshouse-grown lines, we examined variation in Total Stigma Length (TSL) across diverse panels comprising 27 durum and 116 bread wheat genotypes. Contrasting genotypes were selected for population development and genetic analysis. Quantitative trait loci (QTL) analysis was performed on a durum F2 population and a bread wheat recombinant inbred line (RIL) population. Contrasting with studies of anther length, we found no large effect on TSL of the GA-insensitive semi-dwarfing genes Rht-B1 and Rht-D1 in either durum or bread wheat. However, in durum cultivar Italo, we identified a region on chromosome 6A which is robustly associated with larger TSL and contains the Rht14 allele for reduced plant height, a trait that is favourable for female line development in hybrid systems. This dual effect locus explained 25.2 and 19.2% of TSL phenotypic variation in experiments across two growing seasons, with preliminary results suggesting this locus may increase TSL when transferred to bread wheat. In a bread wheat, RIL population minor QTL on 1A and 2A was indicated, but the strongest association was with Ppd-B1. Methods developed here, and the identification of a TSL-enhancing locus provides advances and further opportunities in the study of wheat stigma.

Identification and validation of two major QTL for grain number per spike on chromosomes 2B and 2D in bread wheat (Triticum aestivum L.).

KEY MESSAGE: Major QTL for grain number per spike were identified on chromosomes 2B and 2D. Haplotypes and candidate genes of QGns.cib-2B.1 were analyzed. Grain number per spike (GNS) is one of the main components of wheat yield. Genetic dissection of their regulatory factors is essential to improve the yield potential. In present study, a recombinant inbred line population comprising 180 lines developed from the cross between a high GNS line W7268 and a cultivar Chuanyu12 was employed to identify quantitative trait loci (QTL) associated with GNS across six environments. Two major QTL, QGns.cib-2B.1 and QGns.cib-2D.1, were detected in at least four environments with the phenotypic variations of 12.99-27.07% and 8.50-13.79%, respectively. And significant interactions were observed between the two major QTL. In addition, QGns.cib-2B.1 is a QTL cluster for GNS, grain number per spikelet and fertile tiller number, and they were validated in different genetic backgrounds using Kompetitive Allele Specific PCR (KASP) markers. QGns.cib-2B.1 showed pleotropic effects on other yield-related traits including plant height, spike length, and spikelet number per spike, but did not significantly affect thousand grain weight which suggested that it might be potentially applicable in breeding program. Comparison analysis suggested that QGns.cib-2B.1 might be a novel QTL. Furthermore, haplotype analysis of QGns.cib-2B.1 indicated that it is a hot spot of artificial selection during wheat improvement. Based on the expression patterns, gene annotation, orthologs analysis and sequence variations, the candidate genes of QGns.cib-2B.1 were predicted. Collectively, the major QTL and KASP markers reported here provided a wealth of information for the genetic basis of GNS and grain yield improvement.

Multi-trait index: selection and recommendation of superior black bean genotypes as new improved varieties.

Common bean provides diet rich in vitamins, fiber, minerals, and protein, which could contribute into food security of needy populations in many countries. Developing genotypes that associate favorable agronomic and grain quality traits in the common bean crop could increase the chances of adopting new cultivars black bean. In this context, the present study aimed at selection of superior black bean lines using multi-variate indexes, Smith-Hazel-index, and genotype by yield*trait biplot analysis. These trials were conducted in Campos dos Goytacazes - RJ, in 2020 and 2021. The experimental design used was randomized blocks, with 28 treatments and three replications. The experimental unit consisted of four rows 4.0 m long, spaced at 0.50 m apart, with a sowing density of 15 seeds per meter. The two central rows were used for the evaluations. The selection of superior genotypes was conducted using the multiple trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), multi-trait index based on factor analysis and genotype-ideotype distance (FAI-BLUP), Smith-Hazel index, and Genotype by Yield*Trait Biplot (GYT). The multivariate indexes efficiently selected the best black bean genotypes, presenting desirable selection gains for most traits. The use of multivariate indexes and GYT enable the selection of early genotypes with higher grain yields. These lines G9, G13, G17, G23, and G27 were selected based on their performance for multiple traits closest to the ideotype and could be recommended as new varieties.

Genome-wide association study revealed significant SNPs for anthracnose resistance, seed alkaloids and protein content in white lupin.

White lupin (Lupinus albus L.) is a high-protein grain legume alternative to soybean in Central Europe, but its cultivation is risky due to the fungal disease anthracnose that can cause severe yield damage. In addition, management of seed alkaloids is critical for human nutrition and animal feed. We report on a white lupin collection of genebank accessions, advanced breeding lines and cultivars that was genotyped and phenotypically characterized for anthracnose resistance and seed alkaloids and protein levels. Using genotyping by sequencing (GBS), SeqSNP-targeted GBS, BiomarkX genotyping and Sanger sequencing, a genetic resource of genome-wide SNPs for white lupin was established. We determined anthracnose resistance in two years field trials at four locations with infection rows and measured seed alkaloids and protein levels by near-infrared spectroscopy (NIRS). Few white lupin breeding lines showed anthracnose resistance comparable or better than Celina and Frieda, currently the best commercial cultivars in Germany. NIRS estimates for seed alkaloids and protein levels revealed variation in the white lupin collection. Using genome-wide association studies (GWAS), we identified SNPs significantly associated with anthracnose resistance in the field representing known and new genomic regions. We confirmed the pauper locus and detected new SNP markers significantly associated with seed alkaloids. For the first time, we present loci associated with total grain protein content. Finally, we tested the potential of genomic prediction (GP) in predicting the phenotype of these three quantitative traits. Application of results and resources are discussed in the context of fostering breeding programs for white lupin.

Genomic and phenomic predictions help capture low-effect alleles promoting seed germination in oilseed rape in addition to QTL analyses.

KEY MESSAGE: Phenomic prediction implemented on a large diversity set can efficiently predict seed germination, capture low-effect favorable alleles that are not revealed by GWAS and identify promising genetic resources. Oilseed rape faces many challenges, especially at the beginning of its developmental cycle. Achieving rapid and uniform seed germination could help to ensure a successful establishment and therefore enabling the crop to compete with weeds and tolerate stresses during the earliest developmental stages. The polygenic nature of seed germination was highlighted in several studies, and more knowledge is needed about low- to moderate-effect underlying loci in order to enhance seed germination effectively by improving the genetic background and incorporating favorable alleles. A total of 17 QTL were detected for seed germination-related traits, for which the favorable alleles often corresponded to the most frequent alleles in the panel. Genomic and phenomic predictions methods provided moderate-to-high predictive abilities, demonstrating the ability to capture small additive and non-additive effects for seed germination. This study also showed that phenomic prediction estimated phenotypic values closer to phenotypic values than GEBV. Finally, as the predictive ability of phenomic prediction was less influenced by the genetic structure of the panel, it is worth using this prediction method to characterize genetic resources, particularly with a view to design prebreeding populations.

Selection of rice breeding lines for resistance to biotic and abiotic stresses.

Rice (Oryza sativa L.) grown in many countries around the world with different climatic conditions and a huge number of environmental stresses, both biotic (fungi, bacteria, viruses, insects) and abiotic (cold, drought, salinity) limit rice productivity. In this regard, breeders and scientists are trying to create rice lines that are resistant to multiple stresses. The aim of this work was to screen and select cold and blast resistant rice breeding lines (RBLs) using molecular markers. Molecular screening of RBLs and parental varieties to cold tolerance was carried out using markers RM24545, RM1377, RM231 and RM569 associated with QTLs (qPSST-3, qPSST-7, qPSST-9). It was discovered that the presence of three QTLs characterizes the cold resistance of studied genotypes, and the absence of one of them leads to cold sensitivity. As a result, 21 cold-resistant out of the 28 studied RBLs were identified. These cold resistant 21 RBLs were further tested to blast resistance using markers Pi-ta, Pita3, Z56592, 195R-1, NMSMPi9-1, TRS26, Pikh MAS, MSM6, 9871.T7E2b, RM224 and RM1233. It was revealed that 16 RBLs from 21 studied lines contain 5-6 blast resistance genes. In accordance with the blast resistance strategy, the presence of 5 or more genes ensures the formation of stable resistance to Magnaporthe oryzae. Thus, 16 lines resistant to multiple stresses, such as cold and blast disease were developed. It should be noted that 6 of these selected lines are high-yielding, which is very important in rice breeding program. These RBLs can be used in breeding process as starting lines, germplasm exchange as a source of resistant genes for the development of new rice varieties resistant to multiple stress factors.

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.

Brown-top millet: an overview of breeding, genetic, and genomic resources development for crop improvement.

MAIN CONCLUSION: Brown-top millet is a lesser-known millet with a high grain nutrient value, early maturation, and drought tolerance that needs basic research to understand and conserve food security. Brown-top millet [Urochloa ramosa (L.)] is currently cultivated in some developing countries (especially in India) for food and fodder, although it is less known among the small millets. Like other millets, it contains macro- and micronutrients, vitamins, minerals, proteins, and fiber, all of which have rich health benefits. The nutritional importance and health benefits of brown-top millet are still unknown to many people due to a lack of awareness, wide cultivation, and research. Hence, this millet is currently overshadowed by other major cereals. This review article aims to present the nutritional, breeding, genetic, and genomic resources of brown-top millet to inform millet and other plant researchers. It is important to note that genetic and genomic resources have not yet been created for this millet. To date, there are no genomic and transcriptomic resources for brown-top millet to develop single nucleotide polymorphisms (SNP) and insertion/Deletions (InDels) for breeding studies. Furthermore, studies regarding nutritional significance and health benefits are required to investigate the exact nutritional contents and health benefits of the brown-top millet. The present review delves into the nutritional value and health advantages of brown-top millet, as supported by the available literature. The limitations of producing brown-top millet have been enumerated. We also cover the status of marker-assisted breeding and functional genomics research on closely related species. Lastly, we draw insights for further research such as developing omics resources and applying genome editing to study and improve brown-top millet. This review will help to start breeding and other molecular studies to increase the growth and development of this cereal.

Genome-wide association analysis uncovers rice blast resistance alleles of Ptr and Pia.

A critical step to maximize the usefulness of genome-wide association studies (GWAS) in plant breeding is the identification and validation of candidate genes underlying genetic associations. This is of particular importance in disease resistance breeding where allelic variants of resistance genes often confer resistance to distinct populations, or races, of a pathogen. Here, we perform a genome-wide association analysis of rice blast resistance in 500 genetically diverse rice accessions. To facilitate candidate gene identification, we produce de-novo genome assemblies of ten rice accessions with various rice blast resistance associations. These genome assemblies facilitate the identification and functional validation of novel alleles of the rice blast resistance genes Ptr and Pia. We uncover an allelic series for the unusual Ptr rice blast resistance gene, and additional alleles of the Pia resistance genes RGA4 and RGA5. By linking these associations to three thousand rice genomes we provide a useful tool to inform future rice blast breeding efforts. Our work shows that GWAS in combination with whole-genome sequencing is a powerful tool for gene cloning and to facilitate selection of specific resistance alleles for plant breeding.

Opportunities, Challenges, and Scientific Progress in Hemp Crops.

The resurgence of cannabis (Cannabis sativa L.) has been propelled by changes in the legal framework governing its cultivation and use, increased demand for hemp-derived products, and studies recognizing the industrial and health benefits of hemp. This has led to the creation of novel high-cannabidiol, low-Δ9-tetrahydrocannabinol varieties, enabling hemp crop expansion worldwide. This review elucidates the recent implications for hemp cultivation in Europe, with a focus on the legislative impacts on the cultivation practices, prospective breeding efforts, and dynamic scientific landscape surrounding this crop. We also review the current cultivars' cannabinoid composition of the European hemp market and its major differences with that of the United States.

Enhancing winter wheat prediction with genomics, phenomics and environmental data.

In the realm of multi-environment prediction, when the goal is to predict a complete environment using the others as a training set, the efficiency of genomic selection (GS) falls short of expectations. Genotype by environment interaction poses a challenge in achieving high prediction accuracies. Consequently, current efforts are focused on enhancing efficiency by integrating various types of inputs, such as phenomics data, environmental information, and other omics data. In this study, we sought to evaluate the impact of incorporating environmental information into the modeling process, in addition to genomic and phenomics information. Our evaluation encompassed five data sets of soft white winter wheat, and the results revealed a significant improvement in prediction accuracy, as measured by the normalized root mean square error (NRMSE), through the integration of environmental information. Notably, there was an average gain in prediction accuracy of 49.19% in terms of NRMSE across the data sets. Moreover, the observed prediction accuracy ranged from 5.68% (data set 3) to 60.36% (data set 4), underscoring the substantial effect of integrating environmental information. By including genomic, phenomic, and environmental data in prediction models, plant breeding programs can improve selection efficiency across locations.

The role of phenomics and genomics in delineating the genetic basis of complex traits in millets.

Millets, comprising a diverse group of small-seeded grains, have emerged as vital crops with immense nutritional, environmental, and economic significance. The comprehension of complex traits in millets, influenced by multifaceted genetic determinants, presents a compelling challenge and opportunity in agricultural research. This review delves into the transformative roles of phenomics and genomics in deciphering these intricate genetic architectures. On the phenomics front, high-throughput platforms generate rich datasets on plant morphology, physiology, and performance in diverse environments. This data, coupled with field trials and controlled conditions, helps to interpret how the environment interacts with genetics. Genomics provides the underlying blueprint for these complex traits. Genome sequencing and genotyping technologies have illuminated the millet genome landscape, revealing diverse gene pools and evolutionary relationships. Additionally, different omics approaches unveil the intricate information of gene expression, protein function, and metabolite accumulation driving phenotypic expression. This multi-omics approach is crucial for identifying candidate genes and unfolding the intricate pathways governing complex traits. The review highlights the synergy between phenomics and genomics. Genomically informed phenotyping targets specific traits, reducing the breeding size and cost. Conversely, phenomics identifies promising germplasm for genomic analysis, prioritizing variants with superior performance. This dynamic interplay accelerates breeding programs and facilitates the development of climate-smart, nutrient-rich millet varieties and hybrids. In conclusion, this review emphasizes the crucial roles of phenomics and genomics in unlocking the genetic enigma of millets.

Unlocking the potential of Kodo millet: reviving an indigenous super grain for tomorrow's nutrition.

Kodo millet (Paspalum scrobiculatum L.) is an underutilized crop that encompasses nutritional benefits and climate resilience, making it a viable option for future crop development with nutraceutical properties. The cultivation of this crop has ancient roots, where it was revered for its ability to thrive in times of famine and was a vital companion crop to rice. Dishes made with Kodo millet are highly palatable and can be easily integrated into mainstream rice-based dishes. Among all cereals, Kodo millet is distinguished by its gluten-free composition, high phosphorus content, and significant antioxidant potential, which contributes to a diet that may reduce cardiovascular disease risk. Often grown in rainfed zones by marginal farmers, Kodo millet is valued for its grain and fodder. This less demanding crop can tolerate both biotic and abiotic stress, allowing it to thrive in soils with low organic matter and with minimal inputs, making it an ideal dual-purpose crop for rainfed areas. Despite its nutritional and agricultural benefits, Kodo millet's popularity is hindered by challenges such as low yield, market demand, lodging at harvest, and poor dehulling recovery, which necessitate the development of high-yielding varieties through the latest breeding advancements. Systematic investment and concerted breeding efforts are essential to harness the full potential of this nutrient-dense crop. The absence of whole genome sequence for Kodo millet poses a barrier to uncovering novel genetic traits. Consequently, there is an imperative to establish a millet-based value chain that elevates these underutilized crops, shaping smart cropping patterns and enhancing nutritional profiles for sustainable diets. Accordingly, this review highlights the significance of Kodo millet and the impact of breeding to establish it as a smart food choice for the future.