Transcriptome and GWAS analyses reveal candidate gene for seminal root length of maize seedlings under drought stress

Identification of quantitative trait loci for abdominal muscle content in red swamp crayfish (Procambarus clarkii) and potential application in molecular breeding

Red swamp crayfish (Procambarus clarkii) is a prized aquatic product among consumers, abdominal muscle content being a crucial economic trait. Therefore, there is an urgent need to exploit the genetic basis of crayfish abdominal muscle content for breeding. In the present study, Quantitative Trait Locus (QTL) mapping was performed using 10 different populations (Pop1-Pop10), raised in water tanks, ponds, and rice-crayfish fields, using single- and multiple-culture models of full-sib families and natural populations, from 2020 to 2023. In total, 22 QTLs for abdominal muscle content were identified with population repetitions, explaining the phenotypic variation in the range of 2.7 %-21.3 %, six of which were heterosis sites. Additionally, nine of the 22 QTLs had the consistent genotype with phenotypic effect in eight natural populations (Pop3-Pop10), where the proportion of genotypes with phenotypic effect of the QTL for abdominal muscle weight / body weight (MW/BW) and chelae weight / body weight (CHW/BW) in the group including the top 10 % of the yield of abdominal muscle content individuals (High group) was significantly higher than that in the group including the bottom 10 % of the yield of abdominal muscle content individuals (Low group), respectively (P < 0.01). These results suggest that the QTLs identified repeatedly, especially the nine QTLs, are reliable candidate loci for abdominal muscle content, which is immensely important for the genetic analysis of abdominal muscle content in red swamp crayfish and molecular marker-assisted breeding.

GWAS and transcriptome analyses unravel ZmGRAS15 regulates drought tolerance and root elongation in maize

BACKGROUND

Drought is a major abiotic stress affecting maize development and growth. Unravelling the molecular mechanisms underlying maize drought tolerance and enhancing the drought tolerance of maize is of great importance. However, due to the complexity of the maize genome and the multiplicity of drought tolerance mechanisms, identifying the genetic effects of drought tolerance remains great challenging.

RESULTS

Using a mixed linear model (MLM) based on 362 maize inbred lines, we identified 40 associated loci and 150 candidate genes associated with survival rates. Concurrently, transcriptome analysis was conducted for five drought - tolerant and five drought - sensitive lines under Well-Watered (WW) and Water-Stressed (WS) conditions. Additionally, through co-expression network analysis (WGCNA), we identified five modules significantly associated with the leaf relative water content (RWC) under drought treatment. By integrating the results of GWAS, DEGs, and WGCNA, four candidate genes (Zm00001d006947, Zm00001d038753, Zm00001d003429 and Zm00001d003553) significantly associated with survival rate were successfully identified. Among them, ZmGRAS15 (Zm00001d003553), a GRAS transcription factor considered as a key hub gene, was selected for further functional validation. The overexpression of ZmGRAS15 in maize could significantly enhance drought tolerance through regulating primary root length at the seedling stage.

CONCLUSION

This study provides valuable information for understanding the genetic basis of drought tolerance and gene resources for maize drought tolerance breeding.

Overexpression of ZmEULD1b enhances maize seminal root elongation and drought tolerance

Drought stress damages the growth and development of maize, which results in the maize yield reduction. A strong root system improves the drought tolerance in maize. A previous genome-wide association study for the maize seminal root length under drought stress conditions identified a significant SNP, which was located in the ZmEULD1b gene. Here, we show that enhancing ZmEULD1b expression in transgenic maize increases seminal root length, as well as plant tolerance to water deficit. Meanwhile, ZmEULD1b overexpression influences the stomatal development and promotes water-use efficiency of maize. Further, transcriptome analysis of wild type and ZmEULD1b-OE plants show that several peroxidases and ABA-related pathway genes are upregulated in the ZmEULD1b-OE plants under drought stress conditions. Additionally, rhizosphere microbiota analyses of plant root confirm that overexpression of ZmEULD1b improves the abundance of growth-promoting microbes in the maize root system under drought stress conditions. Collectively, the data presented in this work suggest that ZmEULD1b could be a valuable gene resource or selection target for the drought-tolerant genetic improvement of maize.

Unraveling key genes and pathways involved in Verticillium wilt resistance by integrative GWAS and transcriptomic approaches in Upland cotton

Verticillium dahliae Kleb, the cause of Verticillium wilt, is a particularly destructive soil-borne vascular disease that affects cotton, resulting in serious decline in fiber quality and causing significant losses in cotton production worldwide. However, the progress in identification of wilt-resistance loci or genes in cotton has been limited, most probably due to the highly complex genetic nature of the trait. Nevertheless, the molecular mechanism behind the Verticillium wilt resistance remains poorly understood. In the present study, we investigated the phenotypic variations in Verticillium tolerance and conducted a genome wide association study (GWAS) among a natural population containing 383 accessions of upland cotton germplasm and performed transcriptomic analysis of cotton genotypes with differential responses to Verticillium wilt. GWAS detected 70 significant SNPs and 116 genes associated with resistance loci in two peak signals on D02 and D11 in E1. The transcriptome analysis identified a total of 2689 and 13289 differentially expressed genes (DEGs) among the Verticillium wilt-tolerant (J46) and wilt-susceptible (J11) genotypes, respectively. The DEGs were predominantly enriched in metabolism, plant hormone signal transduction, phenylpropanoid pathway, MAPK cascade pathway and plant-pathogen interaction pathway in GO and KEGG analyses. The identified DEGs were found to comprise several transcription factor (TF) gene families, primarily including AP2/ERF, ZF, WRKY, NAC and MYB, in addition to pentatricopeptide repeat (PPR) proteins and Resistance (R) genes. Finally, by integrating the two results, 34 candidate genes were found to overlap between GWAS and RNA-seq analyses, associated with Verticillium-wilt resistance, including WRKY, MYB, CYP and RGA. This work contributes to our knowledge of the molecular processes underlying cotton responses to Verticillium wilt, offering crucial insights for additional research into the genes and pathways implicated in these responses and paving the way for developing Verticillium wilt-resistant cotton varieties through accelerated breeding by providing a plethora of candidate genes.

Unveiling alfalfa root rot resistance genes through an integrative GWAS and transcriptome study

BACKGROUND

Root rot is a major disease affecting alfalfa (Medicago sativa L.), causing significant yield losses and economic damage. The primary pathogens include Fusarium spp., Rhizoctonia spp., Pythium spp., and Phytophthora spp., with Fusarium being particularly severe. Breeding disease-resistant varieties is crucial for mitigating these losses.

RESULTS

Under conditions of inoculation with Fusarium oxysporum, we conducted a statistical analysis of six phenotypic traits in alfalfa. Significant phenotypic variation was observed among different alfalfa varieties. Correlation analysis revealed significant relationships among traits such as relative yield, relative plant height (PH), and relative root number (NR), indicating potential synergistic roles of these traits in disease resistance. Through GWAS analysis, we identified 41 significant single nucleotide polymorphisms (SNP) associated with root rot resistance across eight chromosomes. The transcriptome analysis identified multiple differentially expressed genes (DEGs) associated with root rot stress, including transcription factors such as WRKY, NAC, AP2, GRAS, HLH, B3, MYB, and ARF. By integrating GWAS and transcriptome data, we identified four key DEGs significantly associated with root rot resistance, offering valuable insights for developing disease-resistant alfalfa varieties and enhancing overall crop resilience.

CONCLUSION

Our study identified significant phenotypic variation and key correlations among traits under root rot stress in alfalfa. We pinpointed 41 significant SNPs associated with root rot resistance across eight chromosomes and identified several key DEGs, including WRKY, NAC, and MYB transcription factors. The integration of GWAS and RNA-Seq data identified four key DEGs associated with root rot resistance, providing valuable insights for breeding disease-resistant alfalfa varieties and enhancing crop resilience.

A Critical Review of Recent Advances in Maize Stress Molecular Biology

With the intensification of global climate change and environmental stress, research on abiotic and biotic stress resistance in maize is particularly important. High temperatures and drought, low temperatures, heavy metals, salinization, and diseases are widespread stress factors that can reduce maize yields and are a focus of maize-breeding research. Molecular biology provides new opportunities for the study of maize and other plants. This article reviews the physiological and biochemical responses of maize to high temperatures and drought, low temperatures, heavy metals, salinization, and diseases, as well as the molecular mechanisms associated with them. Special attention is given to key transcription factors in signal transduction pathways and their roles in regulating maize stress adaptability. In addition, the application of transcriptomics, genome-wide association studies (GWAS), and QTL technology provides new strategies for the identification of molecular markers and genes for maize-stress-resistance traits. Crop genetic improvements through gene editing technologies such as the CRISPR/Cas system provide a new avenue for the development of new stress-resistant varieties. These studies not only help to understand the molecular basis of maize stress responses but also provide important scientific evidence for improving crop tolerance through molecular biological methods.

Phenotype identification and genome-wide association study of ear-internode vascular bundles in maize (Zea mays)

The vascular bundle in the ear-internode of maize is a key conduit for transporting photosynthetic materials between "source" and "sink", making it critically important to examine its micro-phenotypes and genetic architecture to identify advantageous characteristics and cultivate high-yielding and high-quality varieties. Unfortunately, the limited observation methods and scope of study precludes any comprehensive and systematic investigations into the microscopic phenotypes and genetic mechanisms of vascular bundle in maize ear-internode. In this study, 47 phenotypic traits were extracted in 495 maize inbred lines using micro computed tomography (Micro-CT) scanning technology and a deep learning-based phenotype acquisition method for stem vascular bundle, which included stem slice-related, epidermis zone-related, periphery zone-related, inner zone-related and vascular bundles-related traits. Phenotypic analysis indicated that there was extensive phenotypic variation of vascular bundle traits in ear-internode, especially that in the inner zone. Of these, 30 phenotypic traits with heritability greater than 0.70 were conducted for GWAS, and a total of 4,225 significant SNPs and 416 candidate genes with detailed functional annotations were identified. Furthermore, 20 genes were highly expressed in stem-related tissues, especially in maize internodes. Functional analysis of candidate genes indicated that the pathways obtained for candidate genes of different trait groups were distinct, mainly involved in vitamin synthesis and metabolism, transport of substances, carbohydrate derivative catabolic process, protein transport and localization, and anatomical structure development. The results of this study will help to further understand the phenotypic traits of stem vascular bundles and provide a reference for revealing the genetic mechanism of maize ear-internode vascular bundles.

Comparative transcriptome analysis highlights resistance regulatory networks of maize in response to Exserohilum turcicum infection at the early stage

Northern corn leaf blight, caused by Exserohilum turcicum (E. turcicum), is one of the most destructive diseases in maize, leading to serious yield losses. However, the underlying molecular mechanisms of E. turcicum infection response in maize remain unclear. In this study, we performed comparative transcriptome analysis in resistant maize inbred line J9D207 (R) and susceptible maize inbred line PH4CV (S) after infecting with E. turcicum at 0 h, 24 h and 72 h, respectively. Compared with 0 h, 9656 (24 h) and 8748 (72 h) differentially expressed genes (DEGs) were identified in J9D207, and 7915 (24 h) and 7865 (72 h) DEGs were identified in PH4CV. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that alpha-linolenic acid metabolism, benzoxazinoid biosynthesis, flavonoid biosynthesis and phenylpropanoid biosynthesis might be involved in maize defense reactions. Some DEGs coded for transcription factors, such as MYB-related, ERF, NAC, bZIP, bHLH and WRKY families, which indicated that they may participate in resistance against E. turcicum. In addition, DEGs involved in SA, JA, ABA and ET signaling pathways were revealed. Moreover, 75 SOD activity-related genes and 421 POD activity-related genes were identified through weighted gene co-expression network analysis (WGCNA), respectively. These results provide a novel insight into the resistance mechanism of maize in response to E. turcicum inoculation.

Association mapping unravels the genetic basis for drought related traits in different developmental stages of barley

Drought stress significantly reduces crop yields at all stages of plant development. Barley, known for its abiotic-stress adaptation among cereals was used to examine the genetic basis of drought tolerance. A population of 164 spring barley lines was subjected to polyethylene glycol (PEG) induced drought stress during germination and seedling development. Six traits were measured, including germination percentage and rate, seedling length and weight, and root-to-shoot ratios. Seedling area, volume, and root and shoot diameter was acquired with a flatbed scanner. This population was also subjected to short-term drought during the heading stage in the greenhouse. Root and shoot weight and grain yield data were collected from well watered and droughted plants. Significant variation within traits were observed and several of them exhibited strong correlations with each other. In this population, two genotypes had 100% germination under PEG-induced drought and drought tolerance throughout the heading stage of plant development. A genome-wide association scan (GWAS) revealed 64 significant marker-trait associations across all seven barley chromosomes. Candidate genes related to abiotic stress and germination were identified within a 0.5Mbp interval around these SNPs. In silico analysis indicated a high frequency of differential expression of the candidate genes in response to stress. This study enabled identification of barley lines useful for drought tolerance breeding and pinpointed candidate genes for enhancing drought resiliency in barley.

Genome-wide association study reveals genetic basis and candidate genes for chlorophyll content of leaves in maize (Zea mays L.)

The chlorophyll content (CC) directly affects photosynthesis, growth, and yield. However, the genetic basis of CC is still unclear in maize (Zea mays L.). Here, we conducted a genome-wide association study using mixed linear model for CC of the fifth leaves at seedling stage (CCFSS) and the ear leaves at filling stage (CCEFS) for 334 maize inbred lines. The heritability estimates for CCFSS and CCEFS, obtained via variance components analysis using the lme4 package in R, were 70.84% and 78.99%, respectively, indicating that the CC of leaves is primarily controlled by genetic factors. A total of 15 CC-related SNPs and 177 candidate genes were identified with a p-value < 4.49 × 10-5, which explained 4.98-7.59% of the phenotypic variation. Lines with more favorable gene variants showed higher CC. Meanwhile, Gene Ontology (GO) analysis implied that these candidate genes were probably related to chlorophyll biosynthesis. In addition, gene-based association analyses revealed that six variants in GRMZM2G037152, GRMZM5G816561, GRMZM2G324462, and GRMZM2G064657 genes were significantly (p-value < 0.01) correlated with CC, of which GRMZM2G064657 (encodes a phosphate transporter protein) and GRMZM5G816561 (encodes a cytochrome P450 protein) were specifically highly expressed in leaves tissues. Interestingly, these candidate genes were previously reported to involve in the regulation of the contents of chlorophyll in plants or Chlamydomonas. These results may contribute to the understanding of genetic basis and molecular mechanisms of maize CC and the selection of maize varieties with improved CC.

GWAS and Meta-QTL Analysis of Kernel Quality-Related Traits in Maize

The quality of corn kernels is crucial for their nutritional value, making the enhancement of kernel quality a primary objective of contemporary corn breeding efforts. This study utilized 260 corn inbred lines as research materials and assessed three traits associated with grain quality. A genome-wide association study (GWAS) was conducted using the best linear unbiased estimator (BLUE) for quality traits, resulting in the identification of 23 significant single nucleotide polymorphisms (SNPs). Additionally, nine genes associated with grain quality traits were identified through gene function annotation and prediction. Furthermore, a total of 697 quantitative trait loci (QTL) related to quality traits were compiled from 27 documents, followed by a meta-QTL analysis that revealed 40 meta-QTL associated with these traits. Among these, 19 functional genes and reported candidate genes related to quality traits were detected. Three significant SNPs identified by GWAS were located within the intervals of these QTL, while the remaining eight significant SNPs were situated within 2 Mb of the QTL. In summary, the findings of this study provide a theoretical framework for analyzing the genetic basis of corn grain quality-related traits and for enhancing corn quality.

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.

Natural variation in root traits identifies significant SNPs and candidate genes for phosphate deficiency tolerance in Zea mays L

Phosphorus (P) is a crucial macronutrient required for normal plant growth. Its effective uptake from the soil is a trait of agronomic importance. Natural variation in maize (339 accessions) root traits, namely root length and number of primary, seminal, and crown roots, root and shoot phosphate (Pi) contents, and root-to-shoot Pi translocation (root: shoot Pi) under normal (control, 40 ppm) and low phosphate (LP, 1 ppm) conditions, were used for genome-wide association studies (GWAS). The Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model of GWAS provided 23 single nucleotide polymorphisms (SNPs) and 12 relevant candidate genes putatively linked with root Pi, root: shoot Pi, and crown root number (CRN) under LP. The DNA-protein interaction analysis of Zm00001d002842, Zm00001d002837, Zm00001d002843 for root Pi, and Zm00001d044312, Zm00001d045550, Zm00001d025915, Zm00001d044313, Zm00001d051842 for root: shoot Pi, and Zm00001d031561, Zm00001d001803, and Zm00001d001804 for CRN showed the presence of potential binding sites of key transcription factors like MYB62, bZIP11, ARF4, ARF7, ARF10 and ARF16 known for induction/suppression of phosphate starvation response (PHR). The in-silico RNA-seq analysis revealed up or down-regulation of candidate genes along with key transcription factors of PHR, while Uniprot analysis provided genetic relatedness. Candidate genes that may play a role in P uptake and root-to-shoot Pi translocation under LP are proposed using common PHR signaling components like MYB62, ARF4, ARF7, ARF10, ARF16, and bZIP11 to induce changes in root growth in maize. Candidate genes may be used to improve low P tolerance in maize using the CRISPR strategy.

GWAS determined genetic loci associated with callus induction in oil palm tissue culture

KEY MESSAGE

GWAS identified six loci at 25 kb downstream of WAK2, a crucial gene for cell wall and callus formation, enabling development of a SNP marker for enhanced callus induction potential. Efficient callus induction is vital for successful oil palm tissue culture, yet identifying genomic loci and markers for early detection of genotypes with high potential of callus induction remains unclear. In this study, immature male inflorescences from 198 oil palm accessions (dura, tenera and pisifera) were used as explants for tissue culture. Callus induction rates were collected at one-, two- and three-months after inoculation (C1, C2 and C3) as phenotypes. Resequencing generated 11,475,258 high quality single nucleotide polymorphisms (SNPs) as genotypes. GWAS was then performed, and correlation analysis revealed a positive association of C1 with both C2 (R = 0.81) and C3 (R = 0.50), indicating that C1 could be used as the major phenotype for callus induction rate. Therefore, only significant SNPs (P ≤ 0.05) in C1 were identified to develop markers for screening individuals with high potential of callus induction. Among 21 significant SNPs in C1, LD block analysis revealed six SNPs on chromosome 12 (Chr12) potentially linked to callus formation. Subsequently, 13 SNP markers were identified from these loci and electrophoresis results showed that marker C-12 at locus Chr12_12704856 can be used effectively to distinguish the GG allele, which showed the highest probability (69%) of callus induction. Furthermore, a rapid SNP variant detection method without electrophoresis was established via qPCR-based melting curve analysis. Our findings facilitated marker-assisted selection for specific palms with high potential of callus induction using immature male inflorescence as explant, aiding ortet palm selection in oil palm tissue culture.

Root system architecture change in response to waterlogging stress in a 448 global collection of rapeseeds (Brassica napus L.)

MAIN CONCLUSIONS

A novel image-based screening method for precisely identifying genotypic variations in rapeseed RSA under waterlogging stress was developed. Five key root traits were confirmed as good indicators of waterlogging and might be employed in breeding, particularly when using the MFVW approach. Waterlogging is a vital environmental factor that has detrimental effects on the growth and development of rapeseed (Brassica napus L.). Plant roots suffer from hypoxia under waterlogging, which ultimately confers yield penalty. Therefore, it is crucially important to understand the genetic variation of root system architecture (RSA) in response to waterlogging stress to guide the selection of new tolerant cultivars with favorable roots. This research was conducted to investigate RSA traits using image-based screening techniques to better understand how RSA changes over time during waterlogging at the seedling stage. First, we performed a t-test by comparing the relative root trait value between four tolerant and four sensitive accessions. The most important root characteristics associated with waterlogging tolerance at 12 h are total root length (TRL), total root surface area (TRSA), total root volume (TRV), total number of tips (TNT), and total number of forks (TNF). The root structures of 448 rapeseed accessions with or without waterlogging showed notable genetic diversity, and all traits were generally restrained under waterlogging conditions, except for the total root average diameter. Additionally, according to the evaluation and integration analysis of 448 accessions, we identified that five traits, TRL, TRSA, TRV, TNT, and TNF, were the most reliable traits for screening waterlogging-tolerant accessions. Using analysis of the membership function value (MFVW) and D-value of the five selected traits, 25 extremely waterlogging-tolerant materials were screened out. Waterlogging significantly reduced RSA, inhibiting root growth compared to the control. Additionally, waterlogging increased lipid peroxidation, accompanied by a decrease in the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). This study effectively improves our understanding of the response of RSA to waterlogging. The image-based screening method developed in this study provides a new scientific guidance for quickly examining the basic RSA changes and precisely predicting waterlogging-tolerant rapeseed germplasms, thus expanding the genetic diversity of waterlogging-tolerant rapeseed germplasm available for breeding.

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.

The Genetic Dissection of Nitrogen Use-Related Traits in Flax (Linum usitatissimum L.) at the Seedling Stage through the Integration of Multi-Locus GWAS, RNA-seq and Genomic Selection

Nitrogen (N), the most important macro-nutrient for plant growth and development, is a key factor that determines crop yield. Yet its excessive applications pollute the environment and are expensive. Hence, studying nitrogen use efficiency (NUE) in crops is fundamental for sustainable agriculture. Here, an association panel consisting of 123 flax accessions was evaluated for 21 NUE-related traits at the seedling stage under optimum N (N+) and N deficiency (N-) treatments to dissect the genetic architecture of NUE-related traits using a multi-omics approach integrating genome-wide association studies (GWAS), transcriptome analysis and genomic selection (GS). Root traits exhibited significant and positive correlations with NUE under N- conditions (r = 0.33 to 0.43, p < 0.05). A total of 359 QTLs were identified, accounting for 0.11% to 23.1% of the phenotypic variation in NUE-related traits. Transcriptomic analysis identified 1034 differentially expressed genes (DEGs) under contrasting N conditions. DEGs involved in N metabolism, root development, amino acid transport and catabolism and others, were found near the QTLs. GS models to predict NUE stress tolerance index (NUE_STI) trait were tested using a random genome-wide SNP dataset and a GWAS-derived QTLs dataset. The latter produced superior prediction accuracy (r = 0.62 to 0.79) compared to the genome-wide SNP marker dataset (r = 0.11) for NUE_STI. Our results provide insights into the QTL architecture of NUE-related traits, identify candidate genes for further studies, and propose genomic breeding tools to achieve superior NUE in flax under low N input.

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.

Comprehensive transcriptome and WGCNA analysis reveals the potential function of anthocyanins in low-temperature resistance of a red flower mutant tobacco

The anthocyanin is a protective substance in various plants, and plays important roles in resisting to low-temperature. Here, we explored transcriptome analysis of pink flower (as CK) and the natural mutant red flower (as research objects) under low-temperature conditions, and aimed to reveal the potential functions of anthocyanins and anthocyanin-related regulatory factors in resistance to low-temperature. Our results showed that most of the differentially expressed genes (DEGs) encoding key enzymes in the late stage of anthocyanin metabolism in the mutant were significantly up-regulated. Meanwhile, several genes significantly differentially expressed in CK or mutant were obtained by classification and analysis of transcription factors (TFs), phytohormones and osmoregulators. Additionally, WGCNA was carried out to mine hub genes resistanted to low-temperature stress in flavonoid pathway. Finally, one UFGT family gene, three MYB and one bHLH were obtained as the future hub genes of this study. Combined with the above information, we concluded that the ability of the red flower mutant to grow and develop normally at low-temperatures was the result of a combination of flavonoids and cold resistance genes.

QTL mapping for flowering time in a maize-teosinte population under well-watered and water-stressed conditions

Maize grain yield can be greatly reduced when flowering time coincides with drought conditions, which delays silking and consequently increases the anthesis-silking interval. Although the genetic basis of delayed flowering time under water-stressed conditions has been elucidated in maize-maize populations, little is known in this regard about maize-teosinte populations. Here, 16 quantitative trait loci (QTL) for three flowering-time traits, namely days to anthesis, days to silk, and the anthesis-silking interval, were identified in a maize-teosinte introgression population under well-watered and water-stressed conditions; these QTL explained 3.98-32.61% of phenotypic variations. Six of these QTL were considered to be sensitive to drought stress, and the effect of any individual QTL was small, indicating the complex genetic nature of drought resistance in maize. To resolve which genes underlie the six QTL, 11 candidate genes were identified via colocalization analysis of known associations with flowering-time-related drought traits. Among the 11 candidate genes, five were found to be differentially expressed in response to drought stress or under selection during maize domestication, and thus represented the most likely candidates underlying the drought-sensitive QTL. The results lay a foundation for further studies of the genetic mechanisms of drought resistance and provide valuable information for improving drought resistance during maize breeding.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01413-0.

Hybrid performance evaluation and genome-wide association analysis of root system architecture in a maize association population

KEY MESSAGE

The genetic architecture of RSA traits was dissected by GWAS and coexpression networks analysis in a maize association population. Root system architecture (RSA) is a crucial determinant of water and nutrient uptake efficiency in crops. However, the maize genetic architecture of RSA is still poorly understood due to the challenges in quantifying root traits and the lack of dense molecular markers. Here, an association mapping panel including 356 inbred lines were crossed with a common tester, Zheng58, and the test crosses were phenotyped for 12 RSA traits in three locations. We observed a 1.3 ~ sixfold phenotypic variation for measured RSA in the association panel. The association panel consisted of four subpopulations, non-stiff stalk (NSS) lines, stiff stalk (SS), tropical/subtropical (TST), and mixed. Zheng58 × TST has a 2.1% higher crown root number (CRN) and 8.6% less brace root number (BRN) than Zheng58 × NSS and Zheng58 × SS, respectively. Using a genome-wide association study (GWAS) with 1.25 million SNPs and correction for population structure, 191 significant SNPs were identified for root traits. Ninety (47%) of the significant SNPs showed positive allelic effects, and 101 (53%) showed negative effects. Each locus could explain 0.39% to 11.8% of phenotypic variation. By integrating GWAS results and comparing coexpression networks, 26 high-priority candidate genes were identified. Gene GRMZM2G377215, which belongs to the COBRA-like gene family, affected root growth and development. Gene GRMZM2G468657 encodes the aspartic proteinase nepenthesin-1, related to root development and N-deficient response. Collectively, our research provides progress in the genetic dissection of root system architecture. These findings present the further possibility for the genetic improvement of root traits in maize.

Comprehensive Evaluation and Transcriptome Analysis Reveal the Salt Tolerance Mechanism in Semi-Wild Cotton (Gossypium purpurascens)

Elevated salinity significantly threatens cotton growth, particularly during the germination and seedling stages. The utilization of primitive species of Gossypium hirsutum, specifically Gossypium purpurascens, has the potential to facilitate the restoration of genetic diversity that has been depleted due to selective breeding in modern cultivars. This investigation evaluated 45 G. purpurascens varieties and a salt-tolerant cotton variety based on 34 morphological, physiological, and biochemical indicators and comprehensive salt tolerance index values. This study effectively identified a total of 19 salt-tolerant and two salt-resistant varieties. Furthermore, transcriptome sequencing of a salt-tolerant genotype (Nayanmian-2; NY2) and a salt-sensitive genotype (Sanshagaopao-2; GP2) revealed 2776, 6680, 4660, and 4174 differentially expressed genes (DEGs) under 0.5, 3, 12, and 24 h of salt stress. Gene ontology enrichment analysis indicated that the DEGs exhibited significant enrichment in biological processes like metabolic (GO:0008152) and cellular (GO:0009987) processes. MAPK signaling, plant-pathogen interaction, starch and sucrose metabolism, plant hormone signaling, photosynthesis, and fatty acid metabolism were identified as key KEGG pathways involved in salinity stress. Among the DEGs, including NAC, MYB, WRKY, ERF, bHLH, and bZIP, transcription factors, receptor-like kinases, and carbohydrate-active enzymes were crucial in salinity tolerance. Weighted gene co-expression network analysis (WGCNA) unveiled associations of salt-tolerant genotypes with flavonoid metabolism, carbon metabolism, and MAPK signaling pathways. Identifying nine hub genes (MYB4, MYB105, MYB36, bZIP19, bZIP43, FRS2 SMARCAL1, BBX21, F-box) across various intervals offered insights into the transcriptional regulation mechanism of salt tolerance in G. purpurascens. This study lays the groundwork for understanding the important pathways and gene networks in response to salt stress, thereby providing a foundation for enhancing salt tolerance in upland cotton.

Linking genetic and environmental factors through marker effect networks to understand trait plasticity

Understanding how plants adapt to specific environmental changes and identifying genetic markers associated with phenotypic plasticity can help breeders develop plant varieties adapted to a rapidly changing climate. Here, we propose the use of marker effect networks as a novel method to identify markers associated with environmental adaptability. These marker effect networks are built by adapting commonly used software for building gene coexpression networks with marker effects across growth environments as the input data into the networks. To demonstrate the utility of these networks, we built networks from the marker effects of ∼2,000 nonredundant markers from 400 maize hybrids across 9 environments. We demonstrate that networks can be generated using this approach, and that the markers that are covarying are rarely in linkage disequilibrium, thus representing higher biological relevance. Multiple covarying marker modules associated with different weather factors throughout the growing season were identified within the marker effect networks. Finally, a factorial test of analysis parameters demonstrated that marker effect networks are relatively robust to these options, with high overlap in modules associated with the same weather factors across analysis parameters. This novel application of network analysis provides unique insights into phenotypic plasticity and specific environmental factors that modulate the genome.

Transcriptome analysis reveals key regulatory genes for root growth related to potassium utilization efficiency in rapeseed (Brassica napus L.)

Root system architecture (RSA) is the primary predictor of nutrient intake and significantly influences potassium utilization efficiency (KUE). Uncertainty persists regarding the genetic factors governing root growth in rapeseed. The root transcriptome analysis reveals the genetic basis driving crop root growth. In this study, RNA-seq was used to profile the overall transcriptome in the root tissue of 20 Brassica napus accessions with high and low KUE. 71,437 genes in the roots displayed variable expression profiles between the two contrasting genotype groups. The 212 genes that had varied expression levels between the high and low KUE lines were found using a pairwise comparison approach. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional classification analysis revealed that the DEGs implicated in hormone and signaling pathways, as well as glucose, lipid, and amino acid metabolism, were all differently regulated in the rapeseed root system. Additionally, we discovered 33 transcription factors (TFs) that control root development were differentially expressed. By combining differential expression analysis, weighted gene co-expression network analysis (WGCNA), and recent genome-wide association study (GWAS) results, four candidate genes were identified as essential hub genes. These potential genes were located fewer than 100 kb from the peak SNPs of QTL clusters, and it was hypothesized that they regulated the formation of the root system. Three of the four hub genes' homologs-BnaC04G0560400ZS, BnaC04G0560400ZS, and BnaA03G0073500ZS-have been shown to control root development in earlier research. The information produced by our transcriptome profiling could be useful in revealing the molecular processes involved in the growth of rapeseed roots in response to KUE.

Identification and Functional Characterization of ZmSCYL2 Involved in Phytosterol Accumulation in Plants

Phytosterols are natural active substances widely found in plants and play an important role in hypolipidemia, antioxidants, antitumor, immunomodulation, plant growth, and development. In this study, phytosterols were extracted and identified from the seed embryos of 244 maize inbred lines. Based on this, a genome-wide association study (GWAS) was used to predict the possible candidate genes responsible for phytosterol content; 9 SNPs and 32 candidate genes were detected, and ZmSCYL2 was identified to be associated with phytosterol accumulation. We initially confirmed its functions in transgenic Arabidopsis and found that mutation of ZmSCYL2 resulted in slow plant growth and a significant reduction in sterol content, while overexpression of ZmSCYL2 accelerated plant growth and significantly increased sterol content. These results were further confirmed in transgenic tobacco and suggest that ZmSCYL2 was closely related to plant growth; overexpression of ZmSCYL2 not only facilitated plant growth and development but also promoted the accumulation of phytosterols.

Integration of GWAS and RNA-Seq Analysis to Identify SNPs and Candidate Genes Associated with Alkali Stress Tolerance at the Germination Stage in Mung Bean

Soil salt-alkalization seriously impacts crop growth and productivity worldwide. Breeding and applying tolerant varieties is the most economical and effective way to address soil alkalization. However, genetic resources for breeders to improve alkali tolerance are limited in mung bean. Here, a genome-wide association study (GWAS) was performed to detect alkali-tolerant genetic loci and candidate genes in 277 mung bean accessions during germination. Using the relative values of two germination traits, 19 QTLs containing 32 SNPs significantly associated with alkali tolerance on nine chromosomes were identified, and they explained 3.6 to 14.6% of the phenotypic variance. Moreover, 691 candidate genes were mined within the LD intervals containing significant trait-associated SNPs. Transcriptome sequencing of alkali-tolerant accession 132-346 under alkali and control conditions after 24 h of treatment was conducted, and 2565 DEGs were identified. An integrated analysis of the GWAS and DEGs revealed six hub genes involved in alkali tolerance responses. Moreover, the expression of hub genes was further validated by qRT-PCR. These findings improve our understanding of the molecular mechanism of alkali stress tolerance and provide potential resources (SNPs and genes) for the genetic improvement of alkali tolerance in mung bean.

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 presents insights into the genetic architecture of drought tolerance in maize seedlings under field water-deficit conditions

Introduction

Drought stress is one of the most serious abiotic stresses leading to crop yield reduction. Due to the wide range of planting areas, the production of maize is particularly affected by global drought stress. The cultivation of drought-resistant maize varieties can achieve relatively high, stable yield in arid and semi-arid zones and in the erratic rainfall or occasional drought areas. Therefore, to a great degree, the adverse impact of drought on maize yield can be mitigated by developing drought-resistant or -tolerant varieties. However, the efficacy of traditional breeding solely relying on phenotypic selection is not adequate for the need of maize drought-resistant varieties. Revealing the genetic basis enables to guide the genetic improvement of maize drought tolerance.

Methods

We utilized a maize association panel of 379 inbred lines with tropical, subtropical and temperate backgrounds to analyze the genetic structure of maize drought tolerance at seedling stage. We obtained the high quality 7837 SNPs from DArT's and 91,003 SNPs from GBS, and a resultant combination of 97,862 SNPs of GBS with DArT's. The maize population presented the lower her-itabilities of the seedling emergence rate (ER), seedling plant height (SPH) and grain yield (GY) under field drought conditions.

Results

GWAS analysis by MLM and BLINK models with the phenotypic data and 97862 SNPs revealed 15 variants that were significantly independent related to drought-resistant traits at the seedling stage above the threshold of P < 1.02 × 10-5. We found 15 candidate genes for drought resistance at the seedling stage that may involve in (1) metabolism (Zm00001d012176, Zm00001d012101, Zm00001d009488); (2) programmed cell death (Zm00001d053952); (3) transcriptional regulation (Zm00001d037771, Zm00001d053859, Zm00001d031861, Zm00001d038930, Zm00001d049400, Zm00001d045128 and Zm00001d043036); (4) autophagy (Zm00001d028417); and (5) cell growth and development (Zm00001d017495). The most of them in B73 maize line were shown to change the expression pattern in response to drought stress. These results provide useful information for understanding the genetic basis of drought stress tolerance of maize at seedling stage.

Combining GS-assisted GWAS and transcriptome analysis to mine candidate genes for nitrogen utilization efficiency in Populus cathayana

BACKGROUND

Forest trees such as poplar, shrub willow, et al. are essential natural resources for sustainable and renewable energy production, and their wood can reduce dependence on fossil fuels and reduce environmental pollution. However, the productivity of forest trees is often limited by the availability of nitrogen (N), improving nitrogen use efficiency (NUE) is an important way to address it. Currently, NUE genetic resources are scarce in forest tree research, and more genetic resources are urgently needed.

RESULTS

Here, we performed genome-wide association studies (GWAS) using the mixed linear model (MLM) to identify genetic loci regulating growth traits in Populus cathayana at two N levels, and attempted to enhance the signal strength of single nucleotide polymorphism (SNP) detection by performing genome selection (GS) assistance GWAS. The results of the two GWAS analyses identified 55 and 40 SNPs that were respectively associated with plant height (PH) and ground diameter (GD), and 92 and 69 candidate genes, including 30 overlapping genes. The prediction accuracy of the GS model (rrBLUP) for phenotype exceeds 0.9. Transcriptome analysis of 13 genotypes under two N levels showed that genes related to carbon and N metabolism, amino acid metabolism, energy metabolism, and signal transduction were differentially expressed in the xylem of P. cathayana under N treatment. Furthermore, we observed strong regional patterns in gene expression levels of P. cathayana, with significant differences between different regions. Among them, P. cathayana in Longquan region exhibited the highest response to N. Finally, through weighted gene co-expression network analysis (WGCNA), we identified a module closely related to the N metabolic process and eight hub genes.

CONCLUSIONS

Integrating the GWAS, RNA-seq and WGCNA data, we ultimately identified four key regulatory genes (PtrNAC123, PtrNAC025, Potri.002G233100, and Potri.006G236200) involved in the wood formation process, and they may affect P. cathayana growth and wood formation by regulating nitrogen metabolism. This study will provide strong evidence for N regulation mechanisms, and reliable genetic resources for growth and NUE genetic improvement in poplar.

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.

Insights into physiological and molecular mechanisms underlying efficient utilization of boron in different boron efficient Beta vulgaris L. varieties

Boron (B) deficiency and consequent limitation of plant yield and quality, particularly of sugar beet (Beta vulgaris L.) has emerged as a maior problem,which is exacerbating due to cultivar dependent variability in B deficiency tolerance. Pertinently, the current study was designed to elucidate the physiological and molecular mechanisms of B deficiency tolerance of sugar beet varieties KWS1197 (B-efficient variety) and KWS0143 (B-inefficient variety). A hydroponic experiment was conducted employing two B levels B0.1 (0.1 μM L^-1 H₃BO₃, deficiency) and B50 (50 μM L^-1 H₃BO₃, adequacy). Boron deficiency greatly inhibited root elongation and dry matter accumulation; however, formation of lateral roots stimulated and average root diameter was increased. Results exhibited that by up-regulating the expression of NIP5-1, NIP6-1, and BOR2, and suppressing the expression of BOR4, cultivar KWS1197, in contrast to KWS0143, managed to transfer sufficient amount of B to the aboveground plant parts, facilitating its effective absorption and utilization. Accumulation of malondialdehyde (MDA) and reactive oxygen species (ROS) was also mellowed in KWS1197, as well as the oxidative damage to root cells via preservation of the antioxidant enzyme system. Additionally, the expression of essential enzymes for biosynthesis of phytohormone (PYR/PYL) and lignin (COMT, POX, and CCoAOMT) were found to be highly up-regulated in KWS1197. Deductively, through effective B absorption and transportation, balanced nutrient accumulation, and an activated antioxidant enzyme system, B-efficient cultivars may cope with B deficiency while retaining a superior cellular structure to enable root development.

Morphology, photosynthetic physiology and biochemistry of nine herbaceous plants under water stress

Global climate warming and shifts in rainfall patterns are expected to trigger increases in the frequency and magnitude of drought and/or waterlogging stress in plants. To cope with water stress, plants develop diverse tactics. However, the adoption capability and mechanism vary depending upon the plant species identity as well as stress duration and intensity. The objectives of this study were to evaluate the species-dependent responses of alpine herbaceous species to water stress. Nine herbaceous species were subjected to different water stresses (including moderate drought and moderate waterlogging) in pot culture using a randomized complete block design with three replications for each treatment. We hypothesized that water stress would negatively impact plant growth and metabolism. We found considerable interspecies differences in morphological, physiological, and biochemical responses when plants were exposed to the same water regime. In addition, we observed pronounced interactive effects of water regime and plant species identity on plant height, root length, root/shoot ratio, biomass, and contents of chlorophyll a, chlorophyll b, chlorophyll (a+b), carotenoids, malondialdehyde, soluble sugar, betaine, soluble protein and proline, implying that plants respond to water regime differently. Our findings may cast new light on the ecological restoration of grasslands and wetlands in the Qinghai-Tibetan Plateau by helping to select stress-tolerant plant species.

Transcriptome and GWAS Analyses Reveal Candidate Gene for Root Traits of Alfalfa during Germination under Salt Stress

Alfalfa growth and production in China are negatively impacted by high salt concentrations in soils, especially in regions with limited water supplies. Few reliable genetic markers are currently available for salt tolerance selection. As a result, molecular breeding strategies targeting alfalfa are hindered. Therefore, with the continuous increase in soil salinity in agricultural lands, it is indispensable that a salt-tolerant variety of alfalfa is produced. We collected 220 alfalfa varieties around the world for resequencing and performed genome-wide association studies (GWASs). Alfalfa seeds were germinated in saline water with different concentrations of NaCl, and the phenotypic differences in several key root traits were recorded. In the phenotypic analysis, the breeding status and geographical origin strongly affected the salt tolerance of alfalfa. Forty-nine markers were significantly associated with salt tolerance, and 103 candidate genes were identified based on linkage disequilibrium. A total of 2712 differentially expressed genes were upregulated and 3570 were downregulated based on transcriptomic analyses. Some candidate genes that affected root development in the seed germination stage were identified through the combination of GWASs and transcriptome analyses. These genes could be used for molecular breeding strategies to increase alfalfa’s salt tolerance and for further research on salt tolerance in general.

Genome-Wide Meta-Analysis of QTLs Associated with Root Traits and Implications for Maize Breeding

Root system architecture (RSA), also known as root morphology, is critical in plant acquisition of soil resources, plant growth, and yield formation. Many QTLs associated with RSA or root traits in maize have been identified using several bi-parental populations, particularly in response to various environmental factors. In the present study, a meta-analysis of QTLs associated with root traits was performed in maize using 917 QTLs retrieved from 43 mapping studies published from 1998 to 2020. A total of 631 QTLs were projected onto a consensus map involving 19,714 markers, which led to the prediction of 68 meta-QTLs (MQTLs). Among these 68 MQTLs, 36 MQTLs were validated with the marker-trait associations available from previous genome-wide association studies for root traits. The use of comparative genomics approaches revealed several gene models conserved among the maize, sorghum, and rice genomes. Among the conserved genomic regions, the ortho-MQTL analysis uncovered 20 maize MQTLs syntenic to 27 rice MQTLs for root traits. Functional analysis of some high-confidence MQTL regions revealed 442 gene models, which were then subjected to in silico expression analysis, yielding 235 gene models with significant expression in various tissues. Furthermore, 16 known genes viz., DXS2, PHT, RTP1, TUA4, YUC3, YUC6, RTCS1, NSA1, EIN2, NHX1, CPPS4, BIGE1, RCP1, SKUS13, YUC5, and AW330564 associated with various root traits were present within or near the MQTL regions. These results could aid in QTL cloning and pyramiding in developing new maize varieties with specific root architecture for proper plant growth and development under optimum and abiotic stress conditions.

Chromosome groups 5, 6 and 7 harbor major quantitative trait loci controlling root traits in bread wheat (Triticum aestivum L.)

Identifying genomic regions for root traits in bread wheat can help breeders develop climate-resilient and high-yielding wheat varieties with desirable root traits. This study used the recombinant inbred line (RIL) population of Synthetic W7984 × Opata M85 to identify quantitative trait loci (QTL) for different root traits such as rooting depth (RD), root dry mass (RM), total root length (RL), root diameter (Rdia) and root surface areas (RSA1 for coarse roots and RSA2 for fine roots) under controlled conditions in a semi-hydroponic system. We detected 14 QTL for eight root traits on nine wheat chromosomes; we discovered three QTL each for RD and RSA1, two QTL each for RM and RSA2, and one QTL each for RL, Rdia, specific root length and nodal root number per plant. The detected QTL were concentrated on chromosome groups 5, 6 and 7. The QTL for shallow RD (Q.rd.uwa.7BL: Xbarc50) and high RM (Q.rm.uwa.6AS: Xgwm334) were validated in two independent F₂ populations of Synthetic W7984 × Chara and Opata M85 × Cascade, respectively. Genotypes containing negative alleles for Q.rd.uwa.7BL had 52% shallower RD than other Synthetic W7984 × Chara population lines. Genotypes with the positive alleles for Q.rm.uwa.6AS had 31.58% higher RM than other Opata M85 × Cascade population lines. Further, we identified 21 putative candidate genes for RD (Q.rd.uwa.7BL) and 13 for RM (Q.rm.uwa.6AS); TraesCS6A01G020400, TraesCS6A01G024400 and TraesCS6A01G021000 identified from Q.rm.uwa.6AS, and TraesCS7B01G404000, TraesCS7B01G254900 and TraesCS7B01G446200 identified from Q.rd.uwa.7BL encoded important proteins for root traits. We found germin-like protein encoding genes in both Q.rd.uwa.7BL and Q.rm.uwa.6AS regions. These genes may play an important role in RM and RD improvement. The identified QTL, especially the validated QTL and putative candidate genes are valuable genetic resources for future root trait improvement in wheat.

Developing drought-smart, ready-to-grow future crops

Breeding crop plants with increased yield potential and improved tolerance to stressful environments is critical for global food security. Drought stress (DS) adversely affects agricultural productivity worldwide and is expected to rise in the coming years. Therefore, it is vital to understand the physiological, biochemical, molecular, and ecological mechanisms associated with DS. This review examines recent advances in plant responses to DS to expand our understanding of DS-associated mechanisms. Suboptimal water sources adversely affect crop growth and yields through physical impairments, physiological disturbances, biochemical modifications, and molecular adjustments. To control the devastating effect of DS in crop plants, it is important to understand its consequences, mechanisms, and the agronomic and genetic basis of DS for sustainable production. In addition to plant responses, we highlight several mitigation options such as omics approaches, transgenics breeding, genome editing, and biochemical to mechanical methods (foliar treatments, seed priming, and conventional agronomic practices). Further, we have also presented the scope of conventional and speed breeding platforms in helping to develop the drought-smart future crops. In short, we recommend incorporating several approaches, such as multi-omics, genome editing, speed breeding, and traditional mechanical strategies, to develop drought-smart cultivars to achieve the 'zero hunger' goal.

Transcriptome analysis of drought-responsive and drought-tolerant mechanisms in maize leaves under drought stress

Maize is a major crop essential for food and feed, but its production is threatened by various biotic and abiotic stresses. Drought is one of the most common abiotic stresses, causing severe crop yield reduction. Although several studies have been devoted to selecting drought-tolerant maize lines and detecting the drought-responsive mechanism of maize, the transcriptomic differences between drought-tolerant and drought-susceptible maize lines are still largely unknown. In our study, RNA-seq was performed on leaves of the drought-tolerant line W9706 and the drought-susceptible line B73 after drought treatment. We identified 3147 differentially expressed genes (DEGs) between these two lines. The upregulated DEGs in W9706 were enriched in specific processes, including ABA signaling, wax biosynthesis, CHO metabolism, signal transduction and brassinosteroid biosynthesis-related processes, while the downregulated DEGs were enriched in specific processes, such as stomatal movement. Altogether, transcriptomic analysis suggests that the different drought resistances were correlated with the differential expression of genes, while the drought tolerance of W9706 is due to the more rapid response to stimulus, higher water retention capacity and stable cellular environment under water deficit conditions.

Identification of a new QTL underlying seminal root number in a maize-teosinte population

Seminal roots play an important role in acquisition of water and nutrients by maize seedlings. Compared with its teosinte ancestor, maize underwent a change in seminal root number (SRN). Although several key genes controlling SRN have been cloned, identification and utilization of new genes from teosinte would be useful for improving maize root architecture. In this study, a maize-teosinte BC₂F₆ population containing 206 individuals genotyped by resequencing was used to conduct high-resolution quantitative trait locus (QTL) mapping of SRN. A new major QTL on chromosome 7 (qSRN7) was identified. Differentially expressed genes (DEGs) based on RNA-Seq were identified between two inbred lines with no SRN and multiple SRN at two periods of seminal roots primordia formation. A total of 116 DEGs detected in at least one period were identified within the qSRN7 interval. Three DEGs (Zm00001d021572, Zm00001d021579 and Zm00001d021861) associated with SRN were identified through regional association mapping. When compared with reported domestication-related selective sweeps, Zm00001d021572 was selected during maize domestication. Our findings provide important insights into the genetic basis of SRN and identify a promising candidate gene for further studies on SRN.

QTL Mapping and a Transcriptome Integrative Analysis Uncover the Candidate Genes That Control the Cold Tolerance of Maize Introgression Lines at the Seedling Stage

Chilling injury owing to low temperatures severely affects the growth and development of maize (Zea mays.L) seedlings during the early and late spring seasons. The existing maize germplasm is deficient in the resources required to improve maize's ability to tolerate cold injury. Therefore, it is crucial to introduce and identify excellent gene/QTLs that confer cold tolerance to maize for sustainable crop production. Wild relatives of maize, such as Z. perennis and Tripsacum dactyloides, are strongly tolerant to cold and can be used to improve the cold tolerance of maize. In a previous study, a genetic bridge among maize that utilized Z. perennis and T. dactyloides was created and used to obtain a highly cold-tolerant maize introgression line (MIL)-IB030 by backcross breeding. In this study, two candidate genes that control relative electrical conductivity were located on MIL-IB030 by forward genetics combined with a weighted gene co-expression network analysis. The results of the phenotypic, genotypic, gene expression, and functional verification suggest that two candidate genes positively regulate cold tolerance in MIL-IB030 and could be used to improve the cold tolerance of cultivated maize. This study provides a workable route to introduce and mine excellent genes/QTLs to improve the cold tolerance of maize and also lays a theoretical and practical foundation to improve cultivated maize against low-temperature stress.

Co-expression pan-network reveals genes involved in complex traits within maize pan-genome

BACKGROUND

With the advances in the high throughput next generation sequencing technologies, genome-wide association studies (GWAS) have identified a large set of variants associated with complex phenotypic traits at a very fine scale. Despite the progress in GWAS, identification of genotype-phenotype relationship remains challenging in maize due to its nature with dozens of variants controlling the same trait. As the causal variations results in the change in expression, gene expression analyses carry a pivotal role in unraveling the transcriptional regulatory mechanisms behind the phenotypes.

RESULTS

To address these challenges, we incorporated the gene expression and GWAS-driven traits to extend the knowledge of genotype-phenotype relationships and transcriptional regulatory mechanisms behind the phenotypes. We constructed a large collection of gene co-expression networks and identified more than 2 million co-expressing gene pairs in the GWAS-driven pan-network which contains all the gene-pairs in individual genomes of the nested association mapping (NAM) population. We defined four sub-categories for the pan-network: (1) core-network contains the highest represented ~ 1% of the gene-pairs, (2) near-core network contains the next highest represented 1-5% of the gene-pairs, (3) private-network contains ~ 50% of the gene pairs that are unique to individual genomes, and (4) the dispensable-network contains the remaining 50-95% of the gene-pairs in the maize pan-genome. Strikingly, the private-network contained almost all the genes in the pan-network but lacked half of the interactions. We performed gene ontology (GO) enrichment analysis for the pan-, core-, and private- networks and compared the contributions of variants overlapping with genes and promoters to the GWAS-driven pan-network.

CONCLUSIONS

Gene co-expression networks revealed meaningful information about groups of co-regulated genes that play a central role in regulatory processes. Pan-network approach enabled us to visualize the global view of the gene regulatory network for the studied system that could not be well inferred by the core-network alone.

OMICS in Fodder Crops: Applications, Challenges, and Prospects

Biomass yield and quality are the primary targets in forage crop improvement programs worldwide. Low-quality fodder reduces the quality of dairy products and affects cattle's health. In multipurpose crops, such as maize, sorghum, cowpea, alfalfa, and oat, a plethora of morphological and biochemical/nutritional quality studies have been conducted. However, the overall growth in fodder quality improvement is not on par with cereals or major food crops. The use of advanced technologies, such as multi-omics, has increased crop improvement programs manyfold. Traits such as stay-green, the number of tillers per plant, total biomass, and tolerance to biotic and/or abiotic stresses can be targeted in fodder crop improvement programs. Omic technologies, namely genomics, transcriptomics, proteomics, metabolomics, and phenomics, provide an efficient way to develop better cultivars. There is an abundance of scope for fodder quality improvement by improving the forage nutrition quality, edible quality, and digestibility. The present review includes a brief description of the established omics technologies for five major fodder crops, i.e., sorghum, cowpea, maize, oats, and alfalfa. Additionally, current improvements and future perspectives have been highlighted.

Integrating advancements in root phenotyping and genome-wide association studies to open the root genetics gateway

Plant adaptation to challenging environmental conditions around the world has made root growth and development an important research area for plant breeders and scientists. Targeted manipulation of root system architecture (RSA) to increase water and nutrient use efficiency can minimize the adverse effects of climate change on crop production. However, phenotyping of RSA is a major bottleneck since the roots are hidden in the soil. Recently the development of 2- and 3D root imaging techniques combined with the genome-wide association studies (GWASs) have opened up new research tools to identify the genetic basis of RSA. These approaches provide a comprehensive understanding of the RSA, by accelerating the identification and characterization of genes involved in root growth and development. This review summarizes the latest developments in phenotyping techniques and GWAS for RSA, which are used to map important genes regulating various aspects of RSA under varying environmental conditions. Furthermore, we discussed about the state-of-the-art image analysis tools integrated with various phenotyping platforms for investigating and quantifying root traits with the highest phenotypic plasticity in both artificial and natural environments which were used for large scale association mapping studies, leading to the identification of RSA phenotypes and their underlying genetics with the greatest potential for RSA improvement. In addition, challenges in root phenotyping and GWAS are also highlighted, along with future research directions employing machine learning and pan-genomics approaches.

Paclobutrazol improves surface water use efficiency by regulating allometric trait behavior in maize

Paclobutrazol (PBZ) role in drought management of maize is least understood. In maize, root traits are linked with surface water management. Over three years, early and terminal deficit irrigation (EDI and TDI) with or without PBZ were imposed on DKC-9144 and PG-2475 maize varieties. Several allometric parameters viz. stem height, stem diameter, leaf area and root traits along with physiological processes were measured. Implication of these parameters in the management of soil surface irrigation in terms of water use efficiency (WUE) was demonstrated in maize. Increased number of lateral roots and root number density in DKC-9144 provided more surface area for water absorption for better management of EDI. Root growth rates showed a similar pattern with root length, root surface areas, and root numbers in EDI. Elevated expressions of ZmRTCL, ZmRTCS and ZmARF34 in EDI and EDI plus PBZ were associated with seminal roots and root laterals initiation. Under TDI alone or in combination with PBZ, root lengths (BRL, CRL, SRL) and root surface areas varied in DKC-9144 and PG-2475 over control. Furthermore, correlation analysis showed that decrease in WUE under TDI was significantly associated with a reduction in stem thickness and leaf surface area. For WUE_N in TDI and PBZ plus TDI, structural equation modelling proposed, brace root surface area (BRSA_N) as a positive contributor, while a negative contributor was seminal root surface area (SRSA_N). Present study explained the importance of specific root traits and their association with other allometric parameters for improving WUE in DKC-9144 variety of maize and the crop in general.

Mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus QTLs

Nutrient restrictions and large-scale emergence of diseases are threatening the maize production. Recent findings demonstrated that there is a certain synergistic interaction between nutrition and diseases pathways in model plants, however there are few studies on the synergistic genes of nutrients and diseases in maize. Thus, the transcriptome data of nitrogen (N) and phosphorus (P) nutrients and diseases treatments in maize, rice, wheat and Arabidopsis thaliana were collected in this study, and four and 22 weighted co-expression modules were obtained by using Weighted Gene Co-expression Network Analysis (WGCNA) in leaf and root tissues, respectively. With a total of 5252 genes, MFUZZ cluster analysis screened 26 clusters with the same expression trend under nutrition and disease treatments. In the meantime, 1427 genes and 22 specific consensus quantitative trait loci (scQTLs) loci were identified by meta-QTL analysis of nitrogen and phosphorus nutrition and disease stress in maize. Combined with the results of cluster analysis and scQTLs, a total of 195 consistent genes were screened, of which six genes were shown to synergistically respond to nutrition and disease both in roots and leaves. Moreover, the six candidate genes were found in scQTLs associated with gray leaf spot (GLS) and corn leaf blight (CLB). In addition, subcellular localization and bioinformatics analysis of the six candidate genes revealed that they were primarily expressed in endoplasmic reticulum, mitochondria, nucleus and plasma membrane, and were involved in defense and stress, MeJA and abscisic acid response pathways. The fluorescence quantitative PCR confirmed their responsiveness to nitrogen and phosphorus nutrition as well as GLS treatments. Taken together, findings of this study indicated that the nutrition and disease have a significant synergistic response in maize.

Mapping of Candidate Genes in Response to Low Nitrogen in Rice Seedlings

Nitrogen is not only a macronutrient essential for crop growth and development, but also one of the most critical nutrients in farmland ecosystem. Insufficient nitrogen supply will lead to crop yield reduction, while excessive application of nitrogen fertilizer will cause agricultural and eco-environment damage. Therefore, mining low-nitrogen tolerant rice genes and improving nitrogen use efficiency are of great significance to the sustainable development of agriculture. This study was conducted by Genome-wide association study on a basis of two root morphological traits (root length and root diameter) and 788,396 SNPs of a natural population of 295 rice varieties. The transcriptome of low-nitrogen tolerant variety (Longjing 31) and low-nitrogen sensitive variety (Songjing 10) were sequenced between low and high nitrogen treatments. A total of 35 QTLs containing 493 genes were mapped. 3085 differential expressed genes were identified. Among these 493 genes, 174 genes showed different haplotype patterns. There were significant phenotype differences among different haplotypes of 58 genes with haplotype differences. These 58 genes were hypothesized as candidate genes for low nitrogen tolerance related to root morphology. Finally, six genes (Os07g0471300, Os11g0230400, Os11g0229300, Os11g0229400, Os11g0618300 and Os11g0229333) which expressed differentially in Longjing 31 were defined as more valuable candidate genes for low-nitrogen tolerance. The results revealed the response characteristics of rice to low-nitrogen, and provided insights into regulatory mechanisms of rice to nitrogen deficiency.

Recent developments in multi-omics and breeding strategies for abiotic stress tolerance in maize (Zea mays L.)

High-throughput sequencing technologies (HSTs) have revolutionized crop breeding. The advent of these technologies has enabled the identification of beneficial quantitative trait loci (QTL), genes, and alleles for crop improvement. Climate change have made a significant effect on the global maize yield. To date, the well-known omic approaches such as genomics, transcriptomics, proteomics, and metabolomics are being incorporated in maize breeding studies. These approaches have identified novel biological markers that are being utilized for maize improvement against various abiotic stresses. This review discusses the current information on the morpho-physiological and molecular mechanism of abiotic stress tolerance in maize. The utilization of omics approaches to improve abiotic stress tolerance in maize is highlighted. As compared to single approach, the integration of multi-omics offers a great potential in addressing the challenges of abiotic stresses of maize productivity.

Transcriptomic and alternative splicing analyses provide insights into the roles of exogenous salicylic acid ameliorating waxy maize seedling growth under heat stress

BACKGROUND

Salicylic acid (SA) is a phytohormone which works to regulate the abiotic stress response of plants. However, the molecular mechanism by which SA mediates heat tolerance in waxy maize (Zea mays L. sinsensis Kulesh) remains unknown.

RESULTS

Two varieties of waxy maize seedlings, heat-tolerant 'Yunuo7' (Y7) and heat-sensitive 'Suyunuo5' (S5), were pretreated with SA prior to heat stress (HTS). After treatment, physiological and transcriptomic changes were analyzed. Compared with HTS, the exogenous application of SA enhanced the shoot dry weight, the activities of antioxidant enzymes (e.g., SOD, POD, CAT and APX), and the concentration of endogenous phytohormones (e.g., SA, ABA, IAA, GA3), while decreased the MDA content. Transcriptome analysis showed that the number of differentially expressed genes (DEGs) identified in the control (CK) vs HTS and HTS vs HTS + SA comparisons were more in S5 than in Y7. HTS induced the downregulation of genes involved in photosynthesis and the upregulation of genes encoding heat shock transcription factors (HSFs) and heat shock proteins (HSPs). Compared with HTS, SA pretreatment reversed the expression of 5 photosynthesis-related genes, 26 phytohormone-related genes, and all genes encoding HSFs and HSPs in S5. Furthermore, the number of alternative splicing (AS) events increased under HTS treatment for both varieties, while decreased under SA pretreatment of S5. Differentially spliced genes (DSGs) showed little overlap with DEGs, and DEGs and DSGs differed significantly in functional enrichment.

CONCLUSIONS

Physiological and transcriptional together indicated that HTS and SA pretreatment had a greater effect on S5 than Y7. Additionally, it appears that transcriptional regulation and AS work synergistically to enhance thermotolerance in heat-sensitive waxy maize. Our study revealed the regulatory effects and underlying molecular mechanisms of SA on waxy maize seedling under HTS.

GWAS and RNA-seq analysis uncover candidate genes associated with alkaline stress tolerance in maize (Zea mays L.) seedlings

Soil salt-alkalization is a common yet critical environmental stress factor for plant growth and development. Discovering and exploiting genes associated with alkaline tolerance in maize (Zea mays L.) is helpful for improving alkaline resistance. Here, an association panel consisting of 200 maize lines was used to identify the genetic loci responsible for alkaline tolerance-related traits in maize seedlings. A total of nine single-nucleotide polymorphisms (SNPs) and their associated candidate genes were found to be significantly associated with alkaline tolerance using a genome-wide association study (GWAS). An additional 200 genes were identified when the screen was extended to include a linkage disequilibrium (LD) decay distance of r2 ≥ 0.2 from the SNPs. RNA-sequencing (RNA-seq) analysis was then conducted to confirm the linkage between the candidate genes and alkali tolerance. From these data, a total of five differentially expressed genes (DEGs; |log2FC| ≥ 0.585, p < 0.05) were verified as the hub genes involved in alkaline tolerance. Subsequently, two candidate genes, Zm00001d038250 and Zm00001d001960, were verified to affect the alkaline tolerance of maize seedlings by qRT-PCR analysis. These genes were putatively involved protein binding and "flavonoid biosynthesis process," respectively, based on Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses. Gene promoter region contains elements related to stress and metabolism. The results of this study will help further elucidate the mechanisms of alkaline tolerance in maize, which will provide the groundwork for future breeding projects.

Contrasting Water Withholding Responses of Young Maize Plants Reveal Link Between Lipid Peroxidation and Osmotic Regulation Corroborated by Genetic Analysis

Linking biochemistry and genetics of tolerance to osmotic stress is of interest for understanding plant adaptations to unfavorable conditions. The aims of this study were to investigate the variability in responses of panel of elite maize inbred lines to water withholding for stress-related traits through association study and to identify pathways linked to detected associations for better understanding of maize stress responses. Densely genotyped public and expired Plant Variety Protection Certificate (ex-PVP) inbred lines were planted in controlled conditions (16-h/8-h day/night, 25°C, 50% RH) in control (CO) and exposed to 10-day water withholding (WW). Traits analyzed were guaiacol peroxidase activity (GPOD), total protein content (PROT), lipid peroxidation (TBARS), hydrogen peroxide accumulation (H₂O₂), proline accumulation (proline), and current water content (CWC). Proline accumulation was found to be influenced by H₂O₂ and TBARS signaling pathways acting as an accumulation-switching mechanism. Most of the associations detected were for proline (29.4%) and TBARS (44.1%). Gene ontology (GO) enrichment analysis showed significant enrichment in regulation of integral membrane parts and peroxisomes along with regulation of transcription and polysaccharide catabolism. Dynamic studies involving inbreds with extreme phenotypes are needed to elucidate the role of this signaling mechanism in regulation of response to water deficit.

Combined GWAS and Transcriptome Analyses Provide New Insights Into the Response Mechanisms of Sunflower Against Drought Stress

Sunflower is one of the most important oil crops in the world, and drought stress can severely limit its production and quality. To understand the underlying mechanism of drought tolerance, and identify candidate genes for drought tolerance breeding, we conducted a combined genome-wide association studies (GWAS) and RNA-seq analysis. A total of 226 sunflower inbred lines were collected from different regions of China and other countries. Eight phenotypic traits were evaluated under control and drought stress conditions. Genotyping was performed using a Specific-Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 934.08 M paired-end reads were generated, with an average Q30 of 91.97%. Based on the 243,291 polymorphic SLAF tags, a total of 94,162 high-quality SNPs were identified. Subsequent analysis of linkage disequilibrium (LD) and population structure in the 226 accessions was carried out based on the 94,162 high-quality SNPs. The average LD decay across the genome was 20 kb. Admixture analysis indicated that the entire population most likely originated from 11 ancestors. GWAS was performed using three methods (MLM, FarmCPU, and BLINK) simultaneously. A total of 80 SNPs showed significant associations with the 8 traits (p < 1.062 × 10-6). Next, a total of 118 candidate genes were found. To obtain more reliable candidate genes, RNA-seq analysis was subsequently performed. An inbred line with the highest drought tolerance was selected according to phenotypic traits. RNA was extracted from leaves at 0, 7, and 14 days of drought treatment. A total of 18,922 differentially expressed genes were obtained. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed up-regulated genes were mainly enriched in the branched-chain amino acid catabolic process, while the down-regulated genes were mainly enriched in the photosynthesis-related process. Six DEGs were randomly selected from all DEGs for validation; these genes showed similar patterns in RNA-seq and RT-qPCR analysis, with a correlation coefficient of 0.8167. Through the integration of the genome-wide association study and the RNA-sequencing, 14 candidate genes were identified. Four of them (LOC110885273, LOC110872899, LOC110891369, LOC110920644) were abscisic acid related protein kinases and transcription factors. These genes may play an important role in sunflower drought response and will be used for further study. Our findings provide new insights into the response mechanisms of sunflowers against drought stress and contribute to further genetic breeding.