Genome-wide Association Studies in Maize: Praise and Stargaze

Prioritizing Maize Metabolic Gene Regulators through Multi-Omic Network Integration

Elucidating gene regulatory networks is a major area of study within plant systems biology. Phenotypic traits are intricately linked to specific gene expression profiles. These expression patterns arise primarily from regulatory connections between sets of transcription factors (TFs) and their target genes. Here, we integrated 46 co-expression networks, 283 protein-DNA interaction (PDI) assays, and 16 million SNPs used to identify expression quantitative trait loci (eQTL) to construct TF-target networks. In total, we analyzed ∼4.6M interactions to generate four distinct types of TF-target networks: co-expression, PDI, trans -eQTL, and cis -eQTL combined with PDIs. To functionally annotate TFs based on their target genes, we implemented three different network integration strategies. We evaluated the effectiveness of each strategy through TF loss-of function mutant inspection and random network analyses. The multi-network integration allowed us to identify transcriptional regulators of several biological processes. Using the topological properties of the fully integrated network, we identified potential functionally redundant TF paralogs. Our findings retrieved functions previously documented for numerous TFs and revealed novel functions that are crucial for informing the design of future experiments. The approach here-described lays the foundation for the integration of multi-omic datasets in maize and other plant systems.

GRAPHICAL ABSTRACT

Leveraging Multiomics Insights and Exploiting Wild Relatives' Potential for Drought and Heat Tolerance in Maize

Climate change, particularly drought and heat stress, may slash agricultural productivity by 25.7% by 2080, with maize being the hardest hit. Therefore, unraveling the molecular nature of plant responses to these stressors is vital for the development of climate-smart maize. This manuscript's primary objective was to examine how maize plants respond to these stresses, both individually and in combination. Additionally, the paper delved into harnessing the potential of maize wild relatives as a valuable genetic resource and leveraging AI-based technologies to boost maize resilience. The role of multiomics approaches particularly genomics and transcriptomics in dissecting the genetic basis of stress tolerance was also highlighted. The way forward was proposed to utilize a bunch of information obtained through omics technologies by an interdisciplinary state-of-the-art forward-looking big-data, cyberagriculture system, and AI-based approach to orchestrate the development of climate resilient maize genotypes.

Understanding grain development in the Poaceae family by comparing conserved and distinctive pathways through omics studies in wheat and maize

The Poaceae family, commonly known as the grass family, encompasses a diverse group of crops that play an essential role in providing food, fodder, biofuels, environmental conservation, and cultural value for both human and environmental well-being. Crops in Poaceae family are deeply intertwined with human societies, economies, and ecosystems, making it one of the most significant plant families in the world. As the major reservoirs of essential nutrients, seed grain of these crops has garnered substantial attention from researchers. Understanding the molecular and genetic processes that controls seed formation, development and maturation can provide insights for improving crop yield, nutritional quality, and stress tolerance. The diversity in photosynthetic pathways between C3 and C4 plants introduces intriguing variations in their physiological and biochemical processes, potentially affecting seed development. In this review, we explore recent studies performed with omics technologies, such as genomics, transcriptomics, proteomics and metabolomics that shed light on the mechanisms underlying seed development in wheat and maize, as representatives of C3 and C4 plants respectively, providing insights into their unique adaptations and strategies for reproductive success.

Doubled haploid technology and synthetic apomixis: Recent advances and applications in future crop breeding

Doubled haploid (DH) technology and synthetic apomixis approaches can considerably shorten breeding cycles and enhance breeding efficiency. Compared with traditional breeding methods, DH technology offers the advantage of rapidly generating inbred lines, while synthetic apomixis can effectively fix hybrid vigor. In this review, we focus on (i) recent advances in identifying and characterizing genes responsible for haploid induction (HI), (ii) the molecular mechanisms of HI, (iii) spontaneous haploid genome doubling, and (iv) crop synthetic apomixis. We also discuss the challenges and potential solutions for future crop breeding programs utilizing DH technology and synthetic apomixis. Finally, we provide our perspectives about how to integrate DH and synthetic apomixis for precision breeding and de novo domestication.

Identification of anther thermotolerance genes by the integration of linkage and association analysis in maize

Maize is one of the world's most important staple crops, yet its production is increasingly threatened by the rising frequency of high-temperature stress (HTS). To investigate the genetic basis of anther thermotolerance under field conditions, we performed linkage and association analysis to identify HTS response quantitative trait loci (QTL) using three recombinant inbred line (RIL) populations and an association panel containing 375 diverse maize inbred lines. These analyses resulted in the identification of 16 co-located large QTL intervals. Among the 37 candidate genes identified in these QTL intervals, five have rice or Arabidopsis homologs known to influence pollen and filament development. Notably, one of the candidate genes, ZmDUP707, has been subject to selection pressure during breeding. Its expression is suppressed by HTS, leading to pollen abortion and barren seeds. We also identified several additional candidate genes potentially underly QTL previously reported by other researchers. Taken together, our results provide a pool of valuable candidate genes that could be employed by future breeding programs aiming at enhancing maize HTS tolerance.

Genome-wide association studies dissect low-phosphorus stress response genes underling field and seedling traits in maize

Phosphorus (P) is an essential element for plant growth, and its deficiency can cause decreased crop yield. This study systematically evaluated the low-phosphate (Pi) response traits in a large population at maturity and seedling stages, and explored candidate genes and their interrelationships with specific traits. The results revealed a greater sensitivity of seedling maize to low-Pi stress compared to that at maturity stage. The phenotypic response patterns to low-Pi stress at different stages were independent. Chlorophyll content was found to be a potential indicator for screening low-Pi-tolerant materials in the field. A total of 2900 and 1446 significantly associated genes at the maturity and seedling stages were identified, respectively. Among these genes, 972 were uniquely associated with maturity traits, while 330 were specifically detected at the seedling stage under low-Pi stress. Moreover, 768 and 733 genes were specifically associated with index values (low-Pi trait/normal-Pi trait) at maturity and seedling stage, respectively. Genetic network diagrams showed that the low-Pi response gene Zm00001d022226 was specifically associated with multiple primary P-related traits under low-Pi conditions. A total of 963 out of 2966 genes specifically associated with traits under low-Pi conditions or index values were found to be induced by low-Pi stress. Notably, ZmSPX4.1 and ZmSPX2 were sharply up-regulated in response to low-Pi stress across different lines or tissues. These findings advance our understanding of maize's response to low-Pi stress at different developmental stages, shedding light on the genes and pathways implicated in this response.

Integrated Assays of Genome-Wide Association Study, Multi-Omics Co-Localization, and Machine Learning Associated Calcium Signaling Genes with Oilseed Rape Resistance to Sclerotinia sclerotiorum

Sclerotinia sclerotiorum (Ss) is one of the most devastating fungal pathogens, causing huge yield loss in multiple economically important crops including oilseed rape. Plant resistance to Ss pertains to quantitative disease resistance (QDR) controlled by multiple minor genes. Genome-wide identification of genes involved in QDR to Ss is yet to be conducted. In this study, we integrated several assays including genome-wide association study (GWAS), multi-omics co-localization, and machine learning prediction to identify, on a genome-wide scale, genes involved in the oilseed rape QDR to Ss. Employing GWAS and multi-omics co-localization, we identified seven resistance-associated loci (RALs) associated with oilseed rape resistance to Ss. Furthermore, we developed a machine learning algorithm and named it Integrative Multi-Omics Analysis and Machine Learning for Target Gene Prediction (iMAP), which integrates multi-omics data to rapidly predict disease resistance-related genes within a broad chromosomal region. Through iMAP based on the identified RALs, we revealed multiple calcium signaling genes related to the QDR to Ss. Population-level analysis of selective sweeps and haplotypes of variants confirmed the positive selection of the predicted calcium signaling genes during evolution. Overall, this study has developed an algorithm that integrates multi-omics data and machine learning methods, providing a powerful tool for predicting target genes associated with specific traits. Furthermore, it makes a basis for further understanding the role and mechanisms of calcium signaling genes in the QDR to Ss.

Modern Breeding Strategies and Tools for Durable Late Blight Resistance in Potato

Cultivated potato (Solanum tuberosum) is a major crop worldwide. It occupies the second place after cereals (corn, rice, and wheat). This important crop is threatened by the Oomycete Phytophthora infestans, the agent of late blight disease. This pathogen was first encountered during the Irish famine during the 1840s and is a reemerging threat to potatoes. It is mainly controlled chemically by using fungicides, but due to health and environmental concerns, the best alternative is resistance. When there is no disease, no treatment is required. In this study, we present a summary of the ongoing efforts concerning resistance breeding of potato against this devastating pathogen, P. infestans. This work begins with the search for and selection of resistance genes, whether they are from within or from outside the species. The genetic methods developed to date for gene mining, such as effectoromics and GWAS, provide researchers with the ability to identify genes of interest more efficiently. Once identified, these genes are cloned using molecular markers (MAS or QRL) and can then be introduced into different cultivars using somatic hybridization or recombinant DNA technology. More innovative technologies have been developed lately, such as gene editing using the CRISPR system or gene silencing, by exploiting iRNA strategies that have emerged as promising tools for managing Phytophthora infestans, which can be employed. Also, gene pyramiding or gene stacking, which involves the accumulation of two or more R genes on the same individual plant, is an innovative method that has yielded many promising results. All these advances related to the development of molecular techniques for obtaining new potato cultivars resistant to P. infestans can contribute not only to reducing losses in agriculture but especially to ensuring food security and safety.

Metabolite-based genome-wide association studies enable the dissection of the genetic bases of flavonoids, betaine and spermidine in wolfberry (Lycium)

Wolfberry is a plant with medicinal and food values. However, its bioactive ingredients and the corresponding genetic bases have not been determined. Here, we de novo generated a chromosome-level genome assembly for wolfberry, yielding a genome sequence of ~1.77 Gb with contig N50 of 50.55 Mb and 39 224 predicted gene models. A variation map, using 307 re-sequenced accessions, was called based on this genome assembly. Furthermore, the fruit metabolome of these accessions was profiled using 563 annotated metabolites, which separated Lycium barbarum L. and non-L. barbarum L. The flavonoids, coumarins, alkaloids and nicotinic acid contents were higher in the former than in the latter. A metabolite-based genome-wide association study mapped 156 164 significant single nucleotide polymorphisms corresponding to 340 metabolites. This included 19 219 unique lead single nucleotide polymorphisms in 1517 significant association loci, of which three metabolites, flavonoids, betaine and spermidine, were highlighted. Two candidate genes, LbUGT (evm.TU.chr07.2692) and LbCHS (evm.TU.chr07.2738), with non-synonymous mutations, were associated with the flavonoids content. LbCHS is a structural gene that interacts with a nearby MYB transcription factor (evm.TU.chr07.2726) both in L. barbarum and L. ruthenicum. Thus, these three genes might be involved in the biosynthesis/metabolism of flavonoids. LbSSADH (evm.TU.chr09.627) was identified as possibly participating in betaine biosynthesis/metabolism. Four lycibarbarspermidines (E-G and O) were identified, and only the lycibarbarspermidines O content was higher in L. barbarum varieties than in non-L. barbarum varieties. The evm.TU.chr07.2680 gene associated with lycibarbarspermidines O was annotated as an acetyl-CoA-benzylalcohol acetyltransferase, suggesting that it is a candidate gene for spermidine biosynthesis. These results provide novel insights into the specific metabolite profile of non-L. barbarum L. and the genetic bases of flavonoids, betaine and spermidine biosynthesis/metabolism.

Crop root system architecture in drought response

Drought is a natural disaster that profoundly impacts on global agricultural production, significantly reduces crop yields, and thereby poses a severe threat to worldwide food security. Addressing the challenge of effectively improving crop drought resistance (DR) to mitigate yield loss under drought conditions is a global issue. An optimal root system architecture (RSA) plays a pivotal role in enhancing crops' capacity to efficiently uptake water and nutrients, which consequently strengthens their resilience against environmental stresses. In this review, we discuss the compositions and roles of crop RSA and summarize the most recent developments in augmenting drought tolerance in crops by manipulating RSA-related genes. Based on the current research, we propose the potential optimal RSA configuration that could be helpful in enhancing crop DR. Lastly, we discussed the existing challenges and future directions for breeding crops with enhanced DR capabilities through genetic improvements targeting RSA.

Transcriptome-wide association mapping provides insights into the genetic basis and candidate genes governing flowering, maturity and seed weight in rice bean (Vigna umbellata)

BACKGROUND

Rice bean (Vigna umbellata), an underrated legume, adapts to diverse climatic conditions with the potential to support food and nutritional security worldwide. It is used as a vegetable, minor food crop and a fodder crop, being a rich source of proteins, minerals, and essential fatty acids. However, little effort has been made to decipher the genetic and molecular basis of various useful traits in this crop. Therefore, we considered three economically important traits i.e., flowering, maturity and seed weight of rice bean and identified the associated candidate genes employing an associative transcriptomics approach on 100 diverse genotypes out of 1800 evaluated rice bean accessions from the Indian National Genebank.

RESULTS

The transcriptomics-based genotyping of one-hundred diverse rice bean cultivars followed by pre-processing of genotypic data resulted in 49,271 filtered markers. The STRUCTURE, PCA and Neighbor-Joining clustering of 100 genotypes revealed three putative sub-populations. The marker-trait association analysis involving various genome-wide association study (GWAS) models revealed significant association of 82 markers on 48 transcripts for flowering, 26 markers on 22 transcripts for maturity and 22 markers on 21 transcripts for seed weight. The transcript annotation provided information on the putative candidate genes for the considered traits. The candidate genes identified for flowering include HSC80, P-II PsbX, phospholipid-transporting-ATPase-9, pectin-acetylesterase-8 and E3-ubiquitin-protein-ligase-RHG1A. Further, the WRKY1 and DEAD-box-RH27 were found to be associated with seed weight. Furthermore, the associations of PIF3 and pentatricopeptide-repeat-containing-gene with maturity and seed weight, and aldo-keto-reductase with flowering and maturity were revealed.

CONCLUSION

This study offers insights into the genetic basis of key agronomic traits in rice bean, including flowering, maturity, and seed weight. The identified markers and associated candidate genes provide valuable resources for future exploration and targeted breeding, aiming to enhance the agronomic performance of rice bean cultivars. Notably, this research represents the first transcriptome-wide association study in pulse crop, uncovering the candidate genes for agronomically useful traits.

Genome-wide identification and analyses of ZmAPY genes reveal their roles involved in maize development and abiotic stress responses

Apyrase is a class of enzyme that catalyzes the hydrolysis of nucleoside triphosphates/diphosphates (NTP/NDP), which widely involved in regulation of plant growth and stress responses. However, apyrase family genes in maize have not been identified, and their characteristics and functions are largely unknown. In this study, we identified 16 apyrases (named as ZmAPY1-ZmAPY16) in maize genome, and analyzed their phylogenetic relationships, gene structures, chromosomal distribution, upstream regulatory transcription factors and expression patterns. Analysis of the transcriptome database unveiled tissue-specific and abiotic stress-responsive expression of ZmAPY genes in maize. qPCR analysis further confirmed their responsiveness to drought, heat, and cold stresses. Association analyses indicated that variations of ZmAPY5 and ZmAPY16 may regulate maize agronomic traits and drought responses. Our findings shed light on the molecular characteristics and evolutionary history of maize apyrase genes, highlighting their roles in various biological processes and stress responses. This study forms a basis for further exploration of apyrase functions in maize.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-024-01474-9.

A genome-wide association study identifies genes associated with cuticular wax metabolism in maize

The plant cuticle is essential in plant defense against biotic and abiotic stresses. To systematically elucidate the genetic architecture of maize (Zea mays L.) cuticular wax metabolism, 2 cuticular wax-related traits, the chlorophyll extraction rate (CER) and water loss rate (WLR) of 389 maize inbred lines, were investigated and a genome-wide association study (GWAS) was performed using 1.25 million single nucleotide polymorphisms (SNPs). In total, 57 nonredundant quantitative trait loci (QTL) explaining 5.57% to 15.07% of the phenotypic variation for each QTL were identified. These QTLs contained 183 genes, among which 21 strong candidates were identified based on functional annotations and previous publications. Remarkably, 3 candidate genes that express differentially during cuticle development encode β-ketoacyl-CoA synthase (KCS). While ZmKCS19 was known to be involved in cuticle wax metabolism, ZmKCS12 and ZmKCS3 functions were not reported. The association between ZmKCS12 and WLR was confirmed by resequencing 106 inbred lines, and the variation of WLR was significant between different haplotypes of ZmKCS12. In this study, the loss-of-function mutant of ZmKCS12 exhibited wrinkled leaf morphology, altered wax crystal morphology, and decreased C32 wax monomer levels, causing an increased WLR and sensitivity to drought. These results confirm that ZmKCS12 plays a vital role in maize C32 wax monomer synthesis and is critical for drought tolerance. In sum, through GWAS of 2 cuticular wax-associated traits, this study reveals comprehensively the genetic architecture in maize cuticular wax metabolism and provides a valuable reference for the genetic improvement of stress tolerance in maize.

Dissection of quantitative trait nucleotides and candidate genes associated with agronomic and yield-related traits under drought stress in rapeseed varieties: integration of genome-wide association study and transcriptomic analysis

Introduction

An important strategy to combat yield loss challenge is the development of varieties with increased tolerance to drought to maintain production. Improvement of crop yield under drought stress is critical to global food security.

Methods

In this study, we performed multiomics analysis in a collection of 119 diverse rapeseed (Brassica napus L.) varieties to dissect the genetic control of agronomic traits in two watering regimes [well-watered (WW) and drought stress (DS)] for 3 years. In the DS treatment, irrigation continued till the 50% pod development stage, whereas in the WW condition, it was performed throughout the whole growing season.

Results

The results of the genome-wide association study (GWAS) using 52,157 single-nucleotide polymorphisms (SNPs) revealed 1,281 SNPs associated with traits. Six stable SNPs showed sequence variation for flowering time between the two irrigation conditions across years. Three novel SNPs on chromosome C04 for plant weight were located within drought tolerance-related gene ABCG16, and their pleiotropically effects on seed weight per plant and seed yield were characterized. We identified the C02 peak as a novel signal for flowering time, harboring 52.77% of the associated SNPs. The 288-kbps LD decay distance analysis revealed 2,232 candidate genes (CGs) associated with traits. The CGs BIG1-D, CAND1, DRG3, PUP10, and PUP21 were involved in phytohormone signaling and pollen development with significant effects on seed number, seed weight, and grain yield in drought conditions. By integrating GWAS and RNA-seq, 215 promising CGs were associated with developmental process, reproductive processes, cell wall organization, and response to stress. GWAS and differentially expressed genes (DEGs) of leaf and seed in the yield contrasting accessions identified BIG1-D, CAND1, and DRG3 genes for yield variation.

Discussion

The results of our study provide insights into the genetic control of drought tolerance and the improvement of marker-assisted selection (MAS) for breeding high-yield and drought-tolerant varieties.

Natural variation in Brachypodium distachyon responses to combined abiotic stresses

The demand for agricultural production is becoming more challenging as climate change increases global temperature and the frequency of extreme weather events. This study examines the phenotypic variation of 149 accessions of Brachypodium distachyon under drought, heat, and the combination of stresses. Heat alone causes the largest amounts of tissue damage while the combination of stresses causes the largest decrease in biomass compared to other treatments. Notably, Bd21-0, the reference line for B. distachyon, did not have robust growth under stress conditions, especially the heat and combined drought and heat treatments. The climate of origin was significantly associated with B. distachyon responses to the assessed stress conditions. Additionally, a GWAS found loci associated with changes in plant height and the amount of damaged tissue under stress. Some of these SNPs were closely located to genes known to be involved in responses to abiotic stresses and point to potential causative loci in plant stress response. However, SNPs found to be significantly associated with a response to heat or drought individually are not also significantly associated with the combination of stresses. This, with the phenotypic data, suggests that the effects of these abiotic stresses are not simply additive, and the responses to the combined stresses differ from drought and heat alone.

Genetic basis of maize stalk strength decoded via linkage and association mapping

Stalk lodging is a severe problem that limits maize production worldwide, although little attention has been given to its genetic basis. Here we measured rind penetrometer resistance (RPR), an effective index for stalk lodging, in a multi-parent population of 1948 recombinant inbred lines (RILs) and an association population of 508 inbred lines (AMP508). Linkage and association mapping identified 53 and 29 single quantitative trait loci (QTLs) and 50 and 19 pairs of epistatic interactions for RPR in the multi-parent population and AMP508 population, respectively. Phenotypic variation explained by all identified epistatic QTLs (up to ~5%) was much less than that explained by all single additive QTLs (up to ~33% in the multi-parent population and ~ 60% in the AMP508 population). Among all detected QTLs, only eight single QTLs explained >10% of phenotypic variation in single RIL populations. Alleles that increased RPR were enriched in tropical/subtropical (TST) groups from the AMP508 population. Based on genome-wide association studies in both populations, we identified 137 candidate genes affecting RPR, which were assigned to multiple biological processes, such as the biosynthesis of cell wall components. Sixty-six candidate genes were cross-validated by multiple methods or populations. Most importantly, 23 candidate genes were upregulated or downregulated in high-RPR lines relative to low-RPR lines, supporting the associations between candidate genes and RPR. These findings reveal the complex nature of the genetic basis underlying RPR and provide loci or candidate genes for developing elite varieties that are resistant to stalk lodging via molecular breeding.

Identification of Novel QTL for Mercury Accumulation in Maize Using an Enlarged SNP Panel

Mercury (Hg) pollution not only poses a threat to the environment but also adversely affects the growth and development of plants, with potential repercussions for animals and humans through bioaccumulation in the food chain. Maize, a crucial source of food, industrial materials, and livestock feed, requires special attention in understanding the genetic factors influencing mercury accumulation. Developing maize varieties with low mercury accumulation is vital for both maize production and human health. In this study, a comprehensive genome-wide association study (GWAS) was conducted using an enlarged SNP panel comprising 1.25 million single nucleotide polymorphisms (SNPs) in 230 maize inbred lines across three environments. The analysis identified 111 significant SNPs within 78 quantitative trait loci (QTL), involving 169 candidate genes under the Q model. Compared to the previous study, the increased marker density and optimized statistical model led to the discovery of 74 additional QTL, demonstrating improved statistical power. Gene ontology (GO) enrichment analysis revealed that most genes participate in arsenate reduction and stress responses. Notably, GRMZM2G440968, which has been reported in previous studies, is associated with the significant SNP chr6.S_155668107 in axis tissue. It encodes a cysteine proteinase inhibitor, implying its potential role in mitigating mercury toxicity by inhibiting cysteine. Haplotype analyses provided further insights, indicating that lines carrying hap3 exhibited the lowest mercury content compared to other haplotypes. In summary, our study significantly enhances the statistical power of GWAS, identifying additional genes related to mercury accumulation and metabolism. These findings offer valuable insights into unraveling the genetic basis of mercury content in maize and contribute to the development of maize varieties with low mercury accumulation.

Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.

From concept to reality: Transforming agriculture through innovative rhizosphere engineering for plant health and productivity

The plant rhizosphere is regarded as a microbial hotspot due to a wide array of root exudates. These root exudates comprise diverse organic compounds such as phenolic, polysaccharides, flavonoids, fatty acids, and amino acids that showed chemotactic responses towards microbial communities and mediate significant roles in root colonization. The rhizospheric microbiome is a crucial driver of plant growth and productivity, contributing directly or indirectly by facilitating nutrient acquisition, phytohormone modulation, and phosphate solubilization under normal and stressful conditions. Moreover, these microbial candidates protect plants from pathogen invasion by secreting antimicrobial and volatile organic compounds. To enhance plant fitness and yield, rhizospheric microbes are frequently employed as microbial inoculants. However, recent developments have shifted towards targeted rhizosphere engineering or microbial recruitments as a practical approach to constructing desired plant rhizospheres for specific outcomes. The rhizosphere, composed of plants, microbes, and soil, can be modified in several ways to improve inoculant efficiency. Rhizosphere engineering is achieved through three essential mechanisms: a) plant-mediated modifications involving genetic engineering, transgenics, and gene editing of plants; b) microbe-mediated modifications involving genetic alterations of microbes through upstream or downstream methodologies; and c) soil amendments. These mechanisms shape the rhizospheric microbiome, making plants more productive and resilient under different stress conditions. This review paper comprehensively summarizes the various aspects of rhizosphere engineering and their potential applications in maintaining plant health and achieving optimum agricultural productivity.

Multi-omics-driven advances in the understanding of triacylglycerol biosynthesis in oil seeds

Vegetable oils are rich sources of polyunsaturated fatty acids and energy as well as valuable sources of human food, animal feed, and bioenergy. Triacylglycerols, which are comprised of three fatty acids attached to a glycerol backbone, are the main component of vegetable oils. Here, we review the development and application of multiple-level omics in major oilseeds and emphasize the progress in the analysis of the biological roles of key genes underlying seed oil content and quality in major oilseeds. Finally, we discuss future research directions in functional genomics research based on current omics and oil metabolic engineering strategies that aim to enhance seed oil content and quality, and specific fatty acids components according to either human health needs or industrial requirements.

Physiological Mechanisms Underlying Tassel Symptom Formation in Maize Infected with Sporisorium reilianum

Head smut is a soil-borne fungal disease caused by Sporisorium reilianum that infects maize tassels and ears. This disease poses a tremendous threat to global maize production. A previous study found markedly different and stably heritable tassel symptoms in some maize inbred lines with Sipingtou blood after infection with S. reilianum. In the present study, 55 maize inbred lines with Sipingtou blood were inoculated with S. reilianum and classified into three tassel symptom types (A, B, and C). Three maize inbred lines representing these classes (Huangzao4, Jing7, and Chang7-2, respectively) were used as test materials to investigate the physiological mechanisms of tassel formation in infected plants. Changes in enzyme activity, hormone content, and protein expression were analyzed in all three lines after infection and in control plants. The activities of peroxidase (POD), superoxide dismutase (SOD), and phenylalanine-ammonia-lyase (PAL) were increased in the three typical inbred lines after inoculation. POD and SOD activities showed similar trends between lines, with the increase percentage peaking at the V12 stage (POD: 57.06%, 63.19%, and 70.28% increases in Huangzao4, Jing7, and Chang7-2, respectively; SOD: 27.01%, 29.62%, and 47.07% in Huangzao4, Jing7, and Chang7-2, respectively. These were all higher than in the disease-resistant inbred line Mo17 at the same growth stage); this stage was found to be key in tassel symptom formation. Levels of gibberellic acid (GA3), indole-3-acetic acid (IAA), and abscisic acid (ABA) were also altered in the three typical maize inbred lines after inoculation, with changes in GA3 and IAA contents tightly correlated with tassel symptoms after S. reilianum infection. The differentially expressed proteins A5H8G4, P09233, and Q8VXG7 were associated with changes in enzyme activity, whereas P49353, P13689, and P10979 were associated with changes in hormone contents. Fungal infection caused reactive oxygen species (ROS) and nitric oxide (NO) bursts in the three typical inbred lines. This ROS accumulation caused biofilm disruption and altered host signaling pathways, whereas NO signaling triggered strong secondary metabolic responses in the host and altered the activities of defense-related enzymes. These factors together resulted in the formation of varying tassel symptoms. Thus, interactions between S. reilianum and susceptible maize materials were influenced by a variety of signals, enzymes, hormones, and metabolic cycles, encompassing a very complex regulatory network. This study preliminarily identified the physiological mechanisms leading to differences in tassel symptoms, deepening our understanding of S. reilianum-maize interactions.

Integration of genome-wide association study, linkage analysis, and population transcriptome analysis to reveal the TaFMO1-5B modulating seminal root growth in bread wheat

Bread wheat, one of the keystone crops for global food security, is challenged by climate change and resource shortage. The root system plays a vital role in water and nutrient absorption, making it essential for meeting the growing global demand. Here, using an association-mapping population composed of 406 accessions, we identified QTrl.Rs-5B modulating seminal root development with a genome-wide association study and validated its genetic effects with two F5 segregation populations. Transcriptome-wide association study prioritized TaFMO1-5B, a gene encoding the flavin-containing monooxygenases, as the causal gene for QTrl.Rs-5B, whose expression levels correlate negatively with the phenotyping variations among our population. The lines silenced for TaFMO1-5B consistently showed significantly larger seminal roots in different genetic backgrounds. Additionally, the agriculture traits measured in multiple environments showed that QTrl.Rs-5B also affects yield component traits and plant architecture-related traits, and its favorable haplotype modulates these traits toward that of modern cultivars, suggesting the application potential of QTrl.Rs-5B for wheat breeding. Consistently, the frequency of the favorable haplotype of QTrl.Rs-5B increased with habitat expansion and breeding improvement of bread wheat. In conclusion, our findings identified and demonstrated the effects of QTrl.Rs-5B on seminal root development and illustrated that it is a valuable genetic locus for wheat root improvement.

OPEN leaf: an open-source cloud-based phenotyping system for tracking dynamic changes at leaf-specific resolution in Arabidopsis

The first draft of the Arabidopsis genome was released more than 20 years ago and despite intensive molecular research, more than 30% of Arabidopsis genes remained uncharacterized or without an assigned function. This is in part due to gene redundancy within gene families or the essential nature of genes, where their deletion results in lethality (i.e., the dark genome). High-throughput plant phenotyping (HTPP) offers an automated and unbiased approach to characterize subtle or transient phenotypes resulting from gene redundancy or inducible gene silencing; however, access to commercial HTPP platforms remains limited. Here we describe the design and implementation of OPEN leaf, an open-source phenotyping system with cloud connectivity and remote bilateral communication to facilitate data collection, sharing and processing. OPEN leaf, coupled with our SMART imaging processing pipeline was able to consistently document and quantify dynamic changes at the whole rosette level and leaf-specific resolution when plants experienced changes in nutrient availability. Our data also demonstrate that VIS sensors remain underutilized and can be used in high-throughput screens to identify and characterize previously unidentified phenotypes in a leaf-specific time-dependent manner. Moreover, the modular and open-source design of OPEN leaf allows seamless integration of additional sensors based on users and experimental needs.

Identification of Multiple Genetic Loci Related to Low-Temperature Tolerance during Germination in Maize (Zea maize L.) through a Genome-Wide Association Study

Low-temperature stress during the germination stage is an important abiotic stress that affects the growth and development of northern spring maize and seriously restricts maize yield and quality. Although some quantitative trait locis (QTLs) related to low-temperature tolerance in maize have been detected, only a few can be commonly detected, and the QTL intervals are large, indicating that low-temperature tolerance is a complex trait that requires more in-depth research. In this study, 296 excellent inbred lines from domestic and foreign origins (America and Europe) were used as the study materials, and a low-coverage resequencing method was employed for genome sequencing. Five phenotypic traits related to low-temperature tolerance were used to assess the genetic diversity of maize through a genome-wide association study (GWAS). A total of 14 SNPs significantly associated with low-temperature tolerance were detected (-log10(P) > 4), and an SNP consistently linked to low-temperature tolerance in the field and indoors during germination was utilized as a marker. This SNP, 14,070, was located on chromosome 5 at position 2,205,723, which explained 4.84-9.68% of the phenotypic variation. The aim of this study was to enrich the genetic theory of low-temperature tolerance in maize and provide support for the innovation of low-temperature tolerance resources and the breeding of new varieties.

GWAS and Meta-QTL Analysis of Yield-Related Ear Traits in Maize

Maize ear traits are an important component of yield, and the genetic basis of ear traits facilitates further yield improvement. In this study, a panel of 580 maize inbred lines were used as the study material, eight ear-related traits were measured through three years of planting, and whole genome sequencing was performed using the maize 40 K breeding chip based on genotyping by targeted sequencing (GBTS) technology. Five models were used to conduct a genome-wide association study (GWAS) on best linear unbiased estimate (BLUE) of ear traits to find the best model. The FarmCPU (Fixed and random model Circulating Probability Unification) model was the best model for this study; a total of 104 significant single nucleotide polymorphisms (SNPs) were detected, and 10 co-location SNPs were detected simultaneously in more than two environments. Through gene function annotation and prediction, a total of nine genes were identified as potentially associated with ear traits. Moreover, a total of 760 quantitative trait loci (QTL) associated with yield-related traits reported in 37 different articles were collected. Using the collected 760 QTL for meta-QTL analysis, a total of 41 MQTL (meta-QTL) associated with yield-related traits were identified, and 19 MQTL detected yield-related ear trait functional genes and candidate genes that have been reported in maize. Five significant SNPs detected by GWAS were located within these MQTL intervals, and another three significant SNPs were close to MQTL (less than 1 Mb). The results provide a theoretical reference for the analysis of the genetic basis of ear-related traits and the improvement of maize yield.

Combination of linkage and association mapping with genomic prediction to infer QTL regions associated with gray leaf spot and northern corn leaf blight resistance in tropical maize

Among the diseases threatening maize production in Africa are gray leaf spot (GLS) caused by Cercospora zeina and northern corn leaf blight (NCLB) caused by Exserohilum turcicum. The two pathogens, which have high genetic diversity, reduce the photosynthesizing ability of susceptible genotypes and, hence, reduce the grain yield. To identify population-based quantitative trait loci (QTLs) for GLS and NCLB resistance, a biparental population of 230 lines derived from the tropical maize parents CML511 and CML546 and an association mapping panel of 239 tropical and sub-tropical inbred lines were phenotyped across multi-environments in western Kenya. Based on 1,264 high-quality polymorphic single-nucleotide polymorphisms (SNPs) in the biparental population, we identified 10 and 18 QTLs, which explained 64.2% and 64.9% of the total phenotypic variance for GLS and NCLB resistance, respectively. A major QTL for GLS, qGLS1_186 accounted for 15.2% of the phenotypic variance, while qNCLB3_50 explained the most phenotypic variance at 8.8% for NCLB resistance. Association mapping with 230,743 markers revealed 11 and 16 SNPs significantly associated with GLS and NCLB resistance, respectively. Several of the SNPs detected in the association panel were co-localized with QTLs identified in the biparental population, suggesting some consistent genomic regions across genetic backgrounds. These would be more relevant to use in field breeding to improve resistance to both diseases. Genomic prediction models trained on the biparental population data yielded average prediction accuracies of 0.66-0.75 for the disease traits when validated in the same population. Applying these prediction models to the association panel produced accuracies of 0.49 and 0.75 for GLS and NCLB, respectively. This research conducted in maize fields relevant to farmers in western Kenya has combined linkage and association mapping to identify new QTLs and confirm previous QTLs for GLS and NCLB resistance. Overall, our findings imply that genetic gain can be improved in maize breeding for resistance to multiple diseases including GLS and NCLB by using genomic selection.

Genome-Wide Association Studies of Biluochun Tea Plant Populations in Dongting Mountain and Comprehensive Identification of Candidate Genes Associated with Core Agronomic Traits by Four Analysis Models

The elite germplasm resources are key to the beautiful appearance and pleasant flavor of Biluochun tea. We collected and measured the agronomic traits of 95 tea plants to reveal the trait diversity and breeding value of Biluochun tea plant populations. The results revealed that the agronomic traits of Biluochun tea plant populations were diverse and had high breeding value. Additionally, we resequenced these tea plant populations to reveal genetic diversity, population structure, and selection pressure. The Biluochun tea plant populations contained two groups and were least affected by natural selection based on the results of population structure and selection pressure. More importantly, four non-synonymous single nucleotide polymorphisms (nsSNPs) and candidate genes associated with (-)-gallocatechin gallate (GCG), (-)-gallocatechin (GC), and caffeine (CAF) were detected using at least two GWAS models. The results will promote the development and application of molecular markers and the utilization of elite germplasm from Biluochun populations.

Identifying QTLs involved in hybrid performance and heterotic group complementarity: new GWAS models applied to factorial and admixed diallel maize hybrid panels

KEY MESSAGE

An original GWAS model integrating the ancestry of alleles was proposed and allowed the detection of background specific additive and dominance QTLs involved in heterotic group complementarity and hybrid performance. Maize genetic diversity is structured into genetic groups selected and improved relative to each other. This process increases group complementarity and differentiation over time and ensures that the hybrids produced from inter-group crosses exhibit high performances and heterosis. To identify loci involved in hybrid performance and heterotic group complementarity, we introduced an original association study model that disentangles allelic effects from the heterotic group origin of the alleles and compared it with a conventional additive/dominance model. This new model was applied on a factorial between Dent and Flint lines and a diallel between Dent-Flint admixed lines with two different layers of analysis: within each environment and in a multiple-environment context. We identified several strong additive QTLs for all traits, including some well-known additive QTLs for flowering time (in the region of Vgt1/2 on chromosome 8). Yield trait displayed significant non-additive effects in the diallel panel. Most of the detected Yield QTLs exhibited overdominance or, more likely, pseudo-overdominance effects. Apparent overdominance at these QTLs contributed to a part of the genetic group complementarity. The comparison between environments revealed a higher stability of additive QTL effects than non-additive ones. Several QTLs showed variations of effects according to the local heterotic group origin. We also revealed large chromosomic regions that display genetic group origin effects. Altogether, our results illustrate how admixed panels combined with dedicated GWAS modeling allow the identification of new QTLs that could not be revealed by a classical hybrid panel analyzed with traditional modeling.

Genomic selection to improve husk tightness based on genomic molecular markers in maize

Introduction

The husk tightness (HTI) in maize plays a crucial role in regulating the water content of ears during the maturity stage, thereby influencing the quality of mechanical grain harvesting in China. Genomic selection (GS), which employs molecular markers, offers a promising approach for identifying and selecting inbred lines with the desired HTI trait in maize breeding. However, the effectiveness of GS is contingent upon various factors, including the genetic architecture of breeding populations, sequencing platforms, and statistical models.

Methods

An association panel of maize inbred lines was grown across three sites over two years, divided into four subgroups. GS analysis for HTI prediction was performed using marker data from three sequencing platforms and six marker densities with six statistical methods.

Results

The findings indicate that a loosely attached husk can aid in the dissipation of water from kernels in temperate maize germplasms across most environments but not nessarily for tropical-origin maize. Considering the balance between GS prediction accuracy and breeding cost, the optimal prediction strategy is the rrBLUP model, the 50K sequencing platform, a 30% proportion of the test population, and a marker density of r2=0.1. Additionally, selecting a specific SS subgroup for sampling the testing set significantly enhances the predictive capacity for husk tightness.

Discussion

The determination of the optimal GS prediction strategy for HTI provides an economically feasible reference for the practice of molecular breeding. It also serves as a reference method for GS breeding of other agronomic traits.

Identification of southern corn rust resistance QTNs in Chinese summer maize germplasm via multi-locus GWAS and post-GWAS analysis

Southern corn rust (SCR) caused by Puccinia polysora Underw is a major disease leading to severe yield losses in China Summer Corn Belt. Using six multi-locus GWAS methods, we identified a set of SCR resistance QTNs from a diversity panel of 140 inbred lines collected from China Summer Corn Belt. Thirteen QTNs on chromosomes 1, 2, 4, 5, 6, and 8 were grouped into three types of allele effects and their associations with SCR phenotypes were verified by post-GWAS case-control sampling, allele/haplotype effect analysis. Relative resistance (RRR) and relative susceptibility (RRs) catering to its inbred carrier were estimated from single QTN and QTN-QTN combos and epistatitic effects were estimated for QTN-QTN combos. By transcriptomic annotation, a set of candidate genes were predicted to be involved in transcriptional regulation (S5_145, Zm00001d01613, transcription factor GTE4), phosphorylation (S8_123, Zm00001d010672, Pgk2- phosphoglycerate kinase 2), and temperature stress response (S6_164a/S6_164b, Zm00001d038806, hsp101, and S5_211, Zm00001d017978, cellulase25). The breeding implications of the above findings were discussed.

Association analysis of agronomic traits and construction of genetic networks by resequencing of 306 sugar beet (Beta vulgaris L.) lines

Due to the relatively brief domestication history of sugar beet (Beta vulgaris ssp. vulgaris), our understanding of the genomic diversity and functional genes in its cultivars is limited, resulting in slow breeding progress. To address this issue, a total of 306 germplasm materials of major cultivars and breeding lines from China, the USA, and Europe were selected for genome resequencing. We investigated population structure and genetic diversity and performed selective scanning of genomic regions, identifying six novel genes associated with important agronomic traits: the candidate genes DFAX2 and P5CS for skin roughness; the candidate genes FRO5, GL24, and PPR91 for root yield and sugar yield, and the pleiotropic candidate gene POLX for flourishing growth vigour, plant height, crown size, flesh coarseness, and sugar yield. In addition, we constructed a protein-protein interaction network map and a phenotype-gene network map, which provide valuable information for identifying and characterizing functional genes affecting agronomic traits in sugar beet. Overall, our study sheds light on the future improvement of sugar beet agronomic traits at the molecular level.

Genome-wide association studies: an intuitive solution for SNP identification and gene mapping in trees

Analysis of natural diversity in wild/cultivated plants can be used to understand the genetic basis for plant breeding programs. Recent advancements in DNA sequencing have expanded the possibilities for genetically altering essential features. There have been several recently disclosed statistical genetic methods for discovering the genes impacting target qualities. One of these useful methods is the genome-wide association study (GWAS), which effectively identifies candidate genes for a variety of plant properties by examining the relationship between a molecular marker (such as SNP) and a target trait. Conventional QTL mapping with highly structured populations has major limitations. The limited number of recombination events results in poor resolution for quantitative traits. Only two alleles at any given locus can be studied simultaneously. Conventional mapping approach fails to work in perennial plants and vegetatively propagated crops. These limitations are sidestepped by association mapping or GWAS. The flexibility of GWAS comes from the fact that the individuals being examined need not be linked to one another, allowing for the use of all meiotic and recombination events to increase resolution. Phenotyping, genotyping, population structure analysis, kinship analysis, and marker-trait association analysis are the fundamental phases of GWAS. With the rapid development of sequencing technologies and computational methods, GWAS is becoming a potent tool for identifying the natural variations that underlie complex characteristics in crops. The use of high-throughput sequencing technologies along with genotyping approaches like genotyping-by-sequencing (GBS) and restriction site associated DNA (RAD) sequencing may be highly useful in fast-forward mapping approach like GWAS. Breeders may use GWAS to quickly unravel the genomes through QTL and association mapping by taking advantage of natural variances. The drawbacks of conventional linkage mapping can be successfully overcome with the use of high-resolution mapping and the inclusion of multiple alleles in GWAS.

Resequencing of global Lotus corniculatus accessions reveals population distribution and genetic loci, associated with cyanogenic glycosides accumulation and growth traits

BACKGROUND

Lotus corniculatus is a widely distributed perennial legume whose great adaptability to different environments and resistance to barrenness make it an excellent forage and ecological restoration plant. However, its molecular genetics and genomic relationships among populations are yet to be uncovered.

RESULT

Here we report on a genomic variation map from worldwide 272 L. corniculatus accessions by genome resequencing. Our analysis suggests that L. corniculatus accessions have high genetic diversity and could be further divided into three subgroups, with the genetic diversity centers were located in Transcaucasia. Several candidate genes and SNP site associated with CNglcs content and growth traits were identified by genome-wide associated study (GWAS). A non-synonymous in LjMTR was responsible for the decreased expression of CNglcs synthesis genes and LjZCD was verified to positively regulate CNglcs synthesis gene CYP79D3. The LjZCB and an SNP in LjZCA promoter were confirmed to be involved in plant growth.

CONCLUSION

This study provided a large number of genomic resources and described genetic relationship and population structure among different accessions. Moreover, we attempt to provide insights into the molecular studies and breeding of CNglcs and growth traits in L. corniculatus.

Genetic variation among elite inbred lines suggests potential to breed for BNI-capacity in maize

Biological nitrification inhibition (BNI) is a plant function where root systems release antibiotic compounds (BNIs) specifically aimed at suppressing nitrifiers to limit soil-nitrate formation in the root zone. Little is known about BNI-activity in maize (Zea mays L.), the most important food, feed, and energy crop. Two categories of BNIs are released from maize roots; hydrophobic and hydrophilic BNIs, that determine BNI-capacity in root systems. Zeanone is a recently discovered hydrophobic compound with BNI-activity, released from maize roots. The objectives of this study were to understand/quantify the relationship between zeanone activity and hydrophobic BNI-capacity. We assessed genetic variability among 250 CIMMYT maize lines (CMLs) characterized for hydrophobic BNI-capacity and zeanone activity, towards developing genetic markers linked to this trait in maize. CMLs with high BNI-capacity and ability to release zeanone from roots were identified. GWAS was performed using 27,085 SNPs (with unique positions on the B73v.4 reference genome, and false discovery rate = 10), and phenotypic information for BNI-capacity and zeanone production from root systems. Eighteen significant markers were identified; three associated with specific BNI-activity (SBNI), four with BNI-activity per plant (BNIPP), another ten were common between SBNI and BNIPP, and one with zeanone release. Further, 30 annotated genes were associated with the significant SNPs; most of these genes are involved in pathways of "biological process", and one (AMT5) in ammonium regulation in maize roots. Although the inbred lines in this study were not developed for BNI-traits, the identification of markers associated with BNI-capacity suggests the possibility of using these genomic tools in marker-assisted selection to improve hydrophobic BNI-capacity in maize.

Genome-wide association study reveals candidate genes controlling root system architecture under low phosphorus supply at seedling stage in Brassica napus

Optimal root system architecture (RSA) is essential for vigorous growth and yield in crops. Plants have evolved adaptive mechanisms in response to low phosphorus (LP) stress, and one of those is changes in RSA. Here, more than five million single-nucleotide polymorphisms (SNPs) obtained from whole-genome re-sequencing data (WGR) of an association panel of 370 oilseed rape (Brassica napus L.) were used to conduct a genome-wide association study (GWAS) of RSA traits of the panel at LP in "pouch and wick" system. Fifty-two SNPs were forcefully associated with lateral root length (LRL), total root length (TRL), lateral root density (LRD), lateral root number (LRN), mean lateral root length (MLRL), and root dry weight (RDW) at LP. There were significant correlations between phenotypic variation and the number of favorable alleles of the associated loci on chromosomes A06 (chrA06_20030601), C03 (chrC03_3535483), and C07 (chrC07_42348561), respectively. Three candidate genes (BnaA06g29270D, BnaC03g07130D, and BnaC07g43230D) were detected by combining transcriptome, candidate gene association analysis, and haplotype analysis. Cultivar carrying "CCGC" at BnaA06g29270DHap1, "CAAT" at BnaC03g07130DHap1, and "ATC" at BnaC07g43230DHap1 had greater LRL, LRN, and RDW than lines carrying other haplotypes at LP supply. The RSA of a cultivar harboring the three favorable haplotypes was further confirmed by solution culture experiments. These findings define exquisite insights into genetic architectures underlying B. napus RSA at LP and provide valuable gene resources for root breeding.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01411-2.

The Genetic Structures and Molecular Mechanisms Underlying Ear Traits in Maize (Zea mays L.)

Maize (Zea mays L.) is one of the world's staple food crops. In order to feed the growing world population, improving maize yield is a top priority for breeding programs. Ear traits are important determinants of maize yield, and are mostly quantitatively inherited. To date, many studies relating to the genetic and molecular dissection of ear traits have been performed; therefore, we explored the genetic loci of the ear traits that were previously discovered in the genome-wide association study (GWAS) and quantitative trait locus (QTL) mapping studies, and refined 153 QTL and 85 quantitative trait nucleotide (QTN) clusters. Next, we shortlisted 19 common intervals (CIs) that can be detected simultaneously by both QTL mapping and GWAS, and 40 CIs that have pleiotropic effects on ear traits. Further, we predicted the best possible candidate genes from 71 QTL and 25 QTN clusters that could be valuable for maize yield improvement.

Identification of Candidate QTLs and Genes for Ear Diameter by Multi-Parent Population in Maize

Ear diameter (ED) is a critical component of grain yield (GY) in maize (Zea mays L.). Studying the genetic basis of ED in maize is of great significance in enhancing maize GY. Against this backdrop, this study was framed to (1) map the ED-related quantitative trait locus (QTL) and SNPs associated with ED; and (2) identify putative functional genes that may affect ED in maize. To accomplish this, an elite maize inbred line, Ye107, which belongs to the Reid heterotic group, was used as a common parent and crossed with seven elite inbred lines from three different heterotic groups (Suwan1, Reid, and nonReid) that exhibited abundant genetic variation in ED. This led to the construction of a multi-parent population consisting of 1215 F₇ recombinant inbred lines (F₇RILs). A genome-wide association study (GWAS) and linkage analysis were then conducted for the multi-parent population using 264,694 high-quality SNPs generated via the genotyping-by-sequencing method. Our study identified a total of 11 SNPs that were significantly associated with ED through the GWAS, and three QTLs were revealed by the linkage analysis for ED. The major QTL on chromosome 1 was co-identified in the region by the GWAS at SNP_143985532. SNP_143985532, located upstream of the Zm00001d030559 gene, encodes a callose synthase that is expressed in various tissues, with the highest expression level in the maize ear primordium. Haplotype analysis indicated that the haplotype B (allele AA) of Zm00001d030559 was positively correlated with ED. The candidate genes and SNPs identified in this study provide crucial insights for future studies on the genetic mechanism of maize ED formation, cloning of ED-related genes, and genetic improvement of ED. These results may help develop important genetic resources for enhancing maize yield through marker-assisted breeding.

The Microbial Connection to Sustainable Agriculture

Microorganisms are an important element in modeling sustainable agriculture. Their role in soil fertility and health is crucial in maintaining plants' growth, development, and yield. Further, microorganisms impact agriculture negatively through disease and emerging diseases. Deciphering the extensive functionality and structural diversity within the plant-soil microbiome is necessary to effectively deploy these organisms in sustainable agriculture. Although both the plant and soil microbiome have been studied over the decades, the efficiency of translating the laboratory and greenhouse findings to the field is largely dependent on the ability of the inoculants or beneficial microorganisms to colonize the soil and maintain stability in the ecosystem. Further, the plant and its environment are two variables that influence the plant and soil microbiome's diversity and structure. Thus, in recent years, researchers have looked into microbiome engineering that would enable them to modify the microbial communities in order to increase the efficiency and effectiveness of the inoculants. The engineering of environments is believed to support resistance to biotic and abiotic stressors, plant fitness, and productivity. Population characterization is crucial in microbiome manipulation, as well as in the identification of potential biofertilizers and biocontrol agents. Next-generation sequencing approaches that identify both culturable and non-culturable microbes associated with the soil and plant microbiome have expanded our knowledge in this area. Additionally, genome editing and multidisciplinary omics methods have provided scientists with a framework to engineer dependable and sustainable microbial communities that support high yield, disease resistance, nutrient cycling, and management of stressors. In this review, we present an overview of the role of beneficial microbes in sustainable agriculture, microbiome engineering, translation of this technology to the field, and the main approaches used by laboratories worldwide to study the plant-soil microbiome. These initiatives are important to the advancement of green technologies in agriculture.

Genes and genetic mechanisms contributing to fall armyworm resistance in maize

Maize (Zea mays L.) is a crop of major economic and food security importance globally. The fall armyworm (FAW), Spodoptera frugiperda, can devastate entire maize crops, especially in countries or markets that do not allow the use of transgenic crops. Host-plant insect resistance is an economical and environmentally benign way to control FAW, and this study sought to identify maize lines, genes, and pathways that contribute to resistance to FAW. Of the 289 maize lines phenotyped for FAW damage in artificially infested, replicated field trials over 3 years, 31 were identified with good levels of resistance that could donate FAW resistance into elite but susceptible hybrid parents. The 289 lines were genotyped by sequencing to provide single nucleotide polymorphism (SNP) markers for a genome-wide association study (GWAS), followed by a metabolic pathway analysis using the Pathway Association Study Tool (PAST). GWAS identified 15 SNPs linked to 7 genes, and PAST identified multiple pathways, associated with FAW damage. Top pathways, and thus useful resistance mechanisms for further study, include hormone signaling pathways and the biosynthesis of carotenoids (particularly zeaxanthin), chlorophyll compounds, cuticular wax, known antibiosis agents, and 1,4-dihydroxy-2-naphthoate. Targeted metabolite analysis confirmed that maize genotypes with lower levels of FAW damage tend to have higher levels of chlorophyll a than genotypes with high FAW damage, which tend to have lower levels of pheophytin, lutein, chlorophyll b and β-carotene. The list of resistant genotypes, and the results from the genetic, pathway, and metabolic study, can all contribute to efficient creation of FAW resistant cultivars.

Genomic insight into changes of root architecture under drought stress in maize

Drought stress is a central environmental factor that severely limits maize production worldwide. Root architecture plays an important role in drought tolerance and can be targeted in breeding programmes. Here, we conducted phenotyping of root architecture under different water treatments for 373 maize inbred lines, representative germplasm from both China and the United States in different breeding eras. We found that seminal root length in response to drought stress experienced convergent increase during breeding in both countries. Using a genome-wide association study, we identified a total of 221 associated loci underlying 13 root traits under well-watered and water-stressed conditions. These loci harboured many reported root- and abiotic stress-related genes. Furthermore, a total of 75 strong candidate genes were prioritised by integrating candidate genes associated with seminal root length and differentially expressed genes in seminal root. One of high-confidence candidate genes, ZmCIPK3 was functionally characterised and probably plays a role in enhancing drought tolerance through regulating seminal root growth. This study provides valuable information for genetic improvement of root architecture and drought tolerance in maize.

Genome-wide association study of ear tip barrenness in waxy maize

Ear tip-barrenness (ETB), which results from aborted kernels or infertile florets at the ear tip, is an undesirable factor affecting the yield and quality of waxy maize. To uncover the genetic basis of ETB, a genome-wide association study (GWAS) was conducted using the genotype with 27,354 SNPs and phenotype with three environments. Five SNPs that distributed on chromosomes 1, 3 and 6, were identified to be significantly associated with ETB based on the threshold of false discovery rate (FDR) at 0.05. Among these significant loci, three SNPs were clustered together and colocalized with genomic regions previously reported. The average length of ETB decreased almost linearly from the inbred lines containing no favorable alleles across the three loci (1.75 cm) to those with one (1.18 cm), two (0.94 cm) and three (0.65 cm) favorable alleles. Moreover, three important genes, Zm00001d030028, Zm00001d041510 and Zm00001d038676 were predicted for three significant QTLs, respectively. These results promote the understanding genetic basis for ETB and will be useful for breeding waxy maize varieties with high-quality and high-yield.

Opportunity and challenges of phenotyping plant salt tolerance

Salinity is a key factor limiting agricultural production worldwide. Recent advances in field phenotyping have enabled the recording of the environmental history and dynamic response of plants by considering both genotype × environment (G×E) interactions and envirotyping. However, only a few studies have focused on plant salt tolerance phenotyping. Therefore, we analyzed the potential opportunities and major challenges in improving plant salt tolerance using advanced field phenotyping technologies. RGB imaging and spectral and thermal sensors are the most useful and important sensing techniques for assessing key morphological and physiological traits of plant salt tolerance. However, field phenotyping faces challenges owing to its practical applications and high costs, limiting its use in early generation breeding and in developing countries.

Rapid identification of a major locus qPRL-C06 affecting primary root length in Brassica napus by QTL-seq

BACKGROUND AND AIMS

Brassica napus is one of the most important oilseed crops worldwide. Seed yield of B. napus significantly correlates with the primary root length (PRL). The aims of this study were to identify quantitative trait loci (QTLs) for PRL in B. napus.

METHODS

QTL-seq and conventional QTL mapping were jointly used to detect QTLs associated with PRL in a B. napus double haploid (DH) population derived from a cross between 'Tapidor' and 'Ningyou 7'. The identified major locus was confirmed and resolved by an association panel of B. napus and an advanced backcross population. RNA-seq analysis of two long-PRL lines (Tapidor and TN20) and two short-PRL lines (Ningyou 7 and TN77) was performed to identify differentially expressed genes in the primary root underlying the target QTLs.

KEY RESULTS

A total of 20 QTLs impacting PRL in B. napus grown at a low phosphorus (P) supply were found by QTL-seq. Eight out of ten QTLs affecting PRL at a low P supply discovered by conventional QTL mapping could be detected by QTL-seq. The locus qPRL-C06 identified by QTL-seq was repeatedly detected at both an optimal P supply and a low P supply by conventional QTL mapping. This major constitutive QTL was further confirmed by regional association mapping. qPRL-C06 was delimited to a 0.77 Mb genomic region on chromosome C06 using an advanced backcross population. A total of 36 candidate genes within qPRL-C06 were identified that showed variations in coding sequences and/or exhibited significant differences in mRNA abundances in primary root between the long-PRL and short-PRL lines, including five genes involved in phytohormone biosynthesis and signaling.

CONCLUSIONS

These results both demonstrate the power of the QTL-seq in rapid QTL detection for root traits and will contribute to marker-assisted selective breeding of B. napus cultivars with increased PRL.

GWAS across multiple environments and WGCNA suggest the involvement of ZmARF23 in embryonic callus induction from immature maize embryos

Combined GWAS, WGCNA, and gene-based association studies identified the co-expression network and hub genes for maize EC induction. ZmARF23 bound to ZmSAUR15 promoter and regulated its expression, affecting EC induction. Embryonic callus (EC) induction in immature maize embryos shows high genotype dependence, which limits the application of genetic transformation in transgenic breeding and gene function elucidation in maize. Herein, we conducted a genome-wide association mapping (GWAS) for four EC induction-related traits, namely rate of embryonic callus induction (REC), increased callus diameter (ICD), ratio of shoot formation (RSF), and length of shoot (LS) across different environments. A total of 77 SNPs were significantly associated these traits under three environments and using the averages (across environments). Among these significant SNPs, five were simultaneously detected under multiple environments and 11 had respective phenotypic variation explained > 10%. A total of 257 genes were located in the linkage disequilibrium decay of these REC- and ICD-associated SNPs, of which 178 were responsive to EC induction. According to the expression values of the 178 genes, we performed a weighted gene co-expression network analysis (WGCNA) and revealed an EC induction-associated module and five hub genes. Hub gene-based association studies uncovered that the intragenic variations in GRMZM2G105473 and ZmARF23 influenced EC induction efficiency among different maize lines. Dual-luciferase reporter assay indicated that ZmARF23 bound to the promoter of a known causal gene (ZmSAUR15) for EC induction and positively regulated its expression on the transcription level. Our study will deepen the understanding of genetic and molecular mechanisms underlying EC induction and contribute to the use of genetic transformation in maize.

Genomic insights into the genetic basis of cotton breeding in China

The excellent Upland cotton (Gossypium hirsutum) cultivars developed since 1949 have made a huge contribution to cotton production in China, the world's largest producer and consumer of cotton. However, the genetic and genomic basis for the improvements of these cotton cultivars remains largely unclear. In this study, we selected 16 Upland cotton cultivars with important historical status in Chinese cotton breeding and constructed a multiparent, advanced generation, intercross (MAGIC) population comprising 920 recombinant inbred lines. A genome-wide association study using the MAGIC population identified 54 genomic loci associated with lint yield and fiber quality. Of them, 25 (46.30%) pleiotropic genomic loci cause simultaneous changes of lint yield and/or fiber quality traits, revealing complex trade-offs and linkage drags in Upland cotton agronomic traits. Deep sequencing data of 11 introduced ancestor cultivars and publicly available resequencing datasets of 839 cultivars developed in China during the past 70 years were integrated to explore the historical distribution and origin of the elite or selected alleles. Interestingly, 85% of these elite alleles were selected and fixed from different American ancestors, consistent with cotton breeding practices in China. However, seven elite alleles of native origin that are responsible for Fusarium wilt resistance, early maturing, good-quality fiber, and other characteristics were not found in American ancestors but have greatly contributed to Chinese cotton breeding and wide cultivation. Taken together, these results provide a genetic basis for further improving cotton cultivars and reveal that the genetic composition of Chinese cotton cultivars is narrow and mainly derived from early introduced American varieties.

A Genome-Wide Association Study to Identify Novel Candidate Genes Related to Low-Nitrogen Tolerance in Cucumber (Cucumis sativus L.)

Cucumber is one of the most important vegetables, and nitrogen is essential for the growth and fruit production of cucumbers. It is crucial to develop cultivars with nitrogen limitation tolerance or high nitrogen efficiency for green and efficient development in cucumber industry. To reveal the genetic basis of cucumber response to nitrogen starvation, a genome-wide association study (GWAS) was conducted on a collection of a genetically diverse population of cucumber (Cucumis sativus L.) comprising 88 inbred and DH accessions including the North China type, the Eurasian type, the Japanese and South China type mixed subtype, and the South China type subtype. Phenotypic evaluation of six traits under control (14 mM) and treatment (3.5 mM) N conditions depicted the presence of broad natural variation in the studied population. The GWAS results showed that there were significant differences in the population for nitrogen limitation treatment. Nine significant loci were identified corresponding to six LD blocks, three of which overlapped. Sixteen genes were selected by GO annotation associated with nitrogen. Five low-nitrogen stress tolerance genes were finally identified by gene haplotype analysis: CsaV3_3G003630 (CsNRPD1), CsaV3_3G002970 (CsNRT1.1), CsaV3_4G030260 (CsSnRK2.5), CsaV3_4G026940, and CsaV3_3G011820 (CsNPF5.2). Taken together, the experimental data and identification of candidate genes presented in this study offer valuable insights and serve as a useful reference for the genetic enhancement of nitrogen limitation tolerance in cucumbers.

Genetic basis of resistance to southern corn leaf blight in the maize multi-parent population and diversity panel

Southern corn leaf blight (SLB), caused by the necrotrophic pathogen Cochliobolus heterostrophus, is one of the maize foliar diseases and poses a great threat to corn production around the world. Identification of genetic variations underlying resistance to SLB is of paramount importance to maize yield and quality. Here, we used a random-open-parent association mapping population containing eight recombinant inbred line populations and one association mapping panel consisting of 513 diversity maize inbred lines with high-density genetic markers to dissect the genetic basis of SLB resistance. Overall, 109 quantitative trait loci (QTLs) with predominantly small or moderate additive effects, and little epistatic effects were identified. We found 35 (32.1%) novel loci in comparison with the reported QTLs. We revealed that resistant alleles were significantly enriched in tropical accessions and the frequency of about half of resistant alleles decreased during the adaptation process owing to the selection of agronomic traits. A large number of annotated genes located in the SLB-resistant QTLs were shown to be involved in plant defence pathways. Integrating genome-wide association study, transcriptomic profiling, resequencing and gene editing, we identified ZmFUT1 and MYBR92 as the putative genes responsible for the major QTLs for resistance to C. heterostrophus. Our results present a comprehensive insight into the genetic basis of SLB resistance and provide resistant loci or genes as direct targets for crop genetic improvement.

Genome-wide association study identifies GhSAL1 affects cold tolerance at the seedling emergence stage in upland cotton (Gossypium hirsutum L.)

Genomic analysis of upland cotton revealed that cold tolerance was associated with ecological distribution. GhSAL1 on chromosome D09 negatively regulated cold tolerance of upland cotton. Cotton can undergo low-temperature stress at the seedling emergence stage, which adversely affects growth and yield; however, the regulatory mechanism underlying cold tolerance remains nebulous. Here, we analyze the phenotypic and physiological parameters in 200 accessions from 5 ecological distributions under constant chilling (CC) and diurnal variation of chilling (DVC) stresses at the seedling emergence stage. All accessions were clustered into four groups, of which Group IV, with most germplasms from the northwest inland region (NIR), had better phenotypes than Groups I-III under the two kinds of chilling stresses. A total of 575 significantly associated single-nucleotide polymorphism (SNP) were identified, and 35 stable genetic quantitative trait loci (QTL) were obtained, of which 5 were associated with traits under CC and DVC stress, respectively, while the remaining 25 were co-associated. The accumulation of dry weight (DW) of seedling was associated with the flavonoid biosynthesis process regulated by Gh_A10G0500. The emergence rate (ER), DW, and total length of seedling (TL) under CC stress were associated with the SNPs variation of Gh_D09G0189 (GhSAL1). GhSAL1^HapB was the elite haplotype, which increased ER, DW, and TL by 19.04%, 11.26%, and 7.69%, respectively, compared with that of GhSAL1^HapA. The results of virus-induced gene silencing (VIGS) experiment and determination of metabolic substrate content preliminarily illustrated that GhSAL1 negatively regulated cotton cold tolerance through IP₃-Ca²⁺ signaling pathway. The elite haplotypes and candidate genes identified in this study could be used to improve cold tolerance at the seedling emergence stage in future upland cotton breeding.

Integration of high-throughput phenotyping, GWAS, and predictive models reveals the genetic architecture of plant height in maize

Plant height (PH) is an essential trait in maize (Zea mays) that is tightly associated with planting density, biomass, lodging resistance, and grain yield in the field. Dissecting the dynamics of maize plant architecture will be beneficial for ideotype-based maize breeding and prediction, as the genetic basis controlling PH in maize remains largely unknown. In this study, we developed an automated high-throughput phenotyping platform (HTP) to systematically and noninvasively quantify 77 image-based traits (i-traits) and 20 field traits (f-traits) for 228 maize inbred lines across all developmental stages. Time-resolved i-traits with novel digital phenotypes and complex correlations with agronomic traits were characterized to reveal the dynamics of maize growth. An i-trait-based genome-wide association study identified 4945 trait-associated SNPs, 2603 genetic loci, and 1974 corresponding candidate genes. We found that rapid growth of maize plants occurs mainly at two developmental stages, stage 2 (S2) to S3 and S5 to S6, accounting for the final PH indicators. By integrating the PH-association network with the transcriptome profiles of specific internodes, we revealed 13 hub genes that may play vital roles during rapid growth. The candidate genes and novel i-traits identified at multiple growth stages may be used as potential indicators for final PH in maize. One candidate gene, ZmVATE, was functionally validated and shown to regulate PH-related traits in maize using genetic mutation. Furthermore, machine learning was used to build predictive models for final PH based on i-traits, and their performance was assessed across developmental stages. Moderate, strong, and very strong correlations between predictions and experimental datasets were achieved from the early S4 (tenth-leaf) stage. Colletively, our study provides a valuable tool for dissecting the spatiotemporal formation of specific internodes and the genetic architecture of PH, as well as resources and predictive models that are useful for molecular design breeding and predicting maize varieties with ideal plant architectures.

Pleiotropy Structures Plant Height and Seed Weight Scaling in Barley despite Long History of Domestication and Breeding Selection

Size scaling describes the relative growth rates of different body parts of an organism following a positive correlation. Domestication and crop breeding often target the scaling traits in the opposite directions. The genetic mechanism of the size scaling influencing the pattern of size scaling remains unexplored. Here, we revisited a diverse barley (Hordeum vulgare L.) panel with genome-wide single-nucleotide polymorphisms (SNPs) profile and the measurement of their plant height and seed weight to explore the possible genetic mechanisms that may lead to a correlation of the two traits and the influence of domestication and breeding selection on the size scaling. Plant height and seed weight are heritable and remain positively correlated in domesticated barley regardless of growth type and habit. Genomic structural equation modeling systematically evaluated the pleiotropic effect of individual SNP on the plant height and seed weight within a trait correlation network. We discovered seventeen novel SNPs (quantitative trait locus) conferring pleiotropic effect on plant height and seed weight, involving genes with function in diverse traits related to plant growth and development. Linkage disequilibrium decay analysis revealed that a considerable proportion of genetic markers associated with either plant height or seed weight are closely linked in the chromosome. We conclude that pleiotropy and genetic linkage likely form the genetic bases of plant height and seed weight scaling in barley. Our findings contribute to understanding the heritability and genetic basis of size scaling and open a new venue for seeking the underlying mechanism of allometric scaling in plants.