Genetic-based dissection of arsenic accumulation in maize using a genome-wide association analysis method

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.

The TabHLH094-TaMYC8 complex mediates the cadmium response in wheat

In wheat, TaMYC8 is a negative regulator of cadmium (Cd)-responsive ethylene signaling. In this study, we functionally characterized TabHLH094, a basic helix-loop-helix (bHLH) transcription factor (TF) that inhibits the transcriptional activity of TaMYC8. The TabHLH094 protein was found in the nucleus of tobacco epidermal cells and exhibited transcriptional activation activity. Real-time quantitative PCR (RT-qPCR) indicated that TabHLH094 exhibited root-specific, Cd-responsive expression in wheat seedlings. Overexpression of TabHLH094 enhanced the tolerance of wheat seedlings to Cd exposure. The protein-protein interaction between TabHLH094 and TaMYC8 was verified by glutathione S-transferase (GST) pulldown, coimmunoprecipitation (Co-IP), yeast two-hybrid (Y2H), and bimolecular fluorescence complementation (BiFC) analyses. TabHLH094 was found to reduce the ability of TaMYC8 to bind to the TaERF6 promoter. Furthermore, TabHLH094 could also reduce aminocyclopropanecarboxylate oxidase (ACO) and ACC synthase (ACS) activities, both of which are necessary for ethylene biosynthesis. Taken together, these results indicate that TabHLH094 mediates Cd tolerance by regulating the transcriptional activity of TaMYC8 and decreasing ethylene production.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01404-1.

State-of-the-art OMICS strategies against toxic effects of heavy metals in plants: A review

Environmental pollution of heavy metals (HMs), mainly due to anthropogenic activities, has received growing attention in recent decades. HMs, especially the non-essential carcinogenic ones, including chromium (Cr), cadmium (Cd), mercury (Hg), aluminum (Al), lead (Pb), and arsenic (As), have appeared as the most significant air, water, and soil pollutants, which adversely affect the quantity, quality, and security of plant-based food all over the world. Plants exposed to HMs could experience significant decline in growth and yield. To avoid or tolerate the toxic effects of HMs, plants have developed complicated defense mechanisms, including absorption and accumulation of HMs in cell organelles, immobilization by forming complexes with organic chelates, extraction by using numerous transporters, ion channels, signalling cascades, and transcription elements, among others. OMICS strategies have developed significantly to understand the mechanisms of plant transcriptomics, genomics, proteomics, metabolomics, and ionomics to counter HM-mediated stress stimuli. These strategies have been considered to be reliable and feasible for investigating the roles of genomics (genomes), transcriptomic (coding), mRNA transcripts (non-coding), metabolomics (metabolites), and ionomics (metal ions) to enhance stress resistance or tolerance in plants. The recent developments in the mechanistic understandings of the HMs-plant interaction in terms of their absorption, translocation, and toxicity invasions at the molecular and cellular levels, as well as plants' response and adaptation strategies against these stressors, are summarized in the present review. Transcriptomics, genomics, metabolomics, proteomics, and ionomics for plants against HMs toxicities are reviewed, while challenges and future recommendations are also discussed.

Genome-Wide Association Studies of Maize Seedling Root Traits under Different Nitrogen Levels

Nitrogen (N) is one of the important factors affecting maize root morphological construction and growth development. An association panel of 124 maize inbred lines was evaluated for root and shoot growth at seedling stage under normal N (CK) and low N (LN) treatments, using the paper culture method. Twenty traits were measured, including three shoot traits and seventeen root traits, a genome-wide association study (GWAS) was performed using the Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) methods. The results showed that LN condition promoted the growth of the maize roots, and normal N promoted the growth of the shoots. A total of 185 significant SNPs were identified, including 27 SNPs for shoot traits and 158 SNPs for root traits. Four important candidate genes were identified. Under LN conditions, the candidate gene Zm00001d004123 was significantly correlated with the number of crown roots, Zm00001d025554 was correlated with plant height. Under CK conditions, the candidate gene Zm00001d051083 was correlated with the length and area of seminal roots, Zm00001d050798 was correlated with the total root length. The four candidate genes all responded to the LN treatment. The research results provide genetic resources for the genetic improvement of maize root traits.

Advances in "Omics" Approaches for Improving Toxic Metals/Metalloids Tolerance in Plants

Food safety has emerged as a high-urgency matter for sustainable agricultural production. Toxic metal contamination of soil and water significantly affects agricultural productivity, which is further aggravated by extreme anthropogenic activities and modern agricultural practices, leaving food safety and human health at risk. In addition to reducing crop production, increased metals/metalloids toxicity also disturbs plants' demand and supply equilibrium. Counterbalancing toxic metals/metalloids toxicity demands a better understanding of the complex mechanisms at physiological, biochemical, molecular, cellular, and plant level that may result in increased crop productivity. Consequently, plants have established different internal defense mechanisms to cope with the adverse effects of toxic metals/metalloids. Nevertheless, these internal defense mechanisms are not adequate to overwhelm the metals/metalloids toxicity. Plants produce several secondary messengers to trigger cell signaling, activating the numerous transcriptional responses correlated with plant defense. Therefore, the recent advances in omics approaches such as genomics, transcriptomics, proteomics, metabolomics, ionomics, miRNAomics, and phenomics have enabled the characterization of molecular regulators associated with toxic metal tolerance, which can be deployed for developing toxic metal tolerant plants. This review highlights various response strategies adopted by plants to tolerate toxic metals/metalloids toxicity, including physiological, biochemical, and molecular responses. A seven-(omics)-based design is summarized with scientific clues to reveal the stress-responsive genes, proteins, metabolites, miRNAs, trace elements, stress-inducible phenotypes, and metabolic pathways that could potentially help plants to cope up with metals/metalloids toxicity in the face of fluctuating environmental conditions. Finally, some bottlenecks and future directions have also been highlighted, which could enable sustainable agricultural production.

Molecular dissection of maize seedling salt tolerance using a genome-wide association analysis method

Salt stress is a major devastating abiotic factor that affects the yield and quality of maize. However, knowledge of the molecular mechanisms of the responses to salt stress in maize is limited. To elucidate the genetic basis of salt tolerance traits, a genome-wide association study was performed on 348 maize inbred lines under normal and salt stress conditions using 557 894 single nucleotide polymorphisms (SNPs). The phenotypic data for 27 traits revealed coefficients of variation of >25%. In total, 149 significant SNPs explaining 6.6%-11.2% of the phenotypic variation for each SNP were identified. Of the 104 identified quantitative trait loci (QTLs), 83 were related to salt tolerance and 21 to normal traits. Additionally, 13 QTLs were associated with two to five traits. Eleven and six QTLs controlling salt tolerance traits and normal root growth, respectively, co-localized with QTL intervals reported previously. Based on functional annotations, 13 candidate genes were predicted. Expression levels analysis of 12 candidate genes revealed that they were all responsive to salt stress. The CRISPR/Cas9 technology targeting three sites was applied in maize, and its editing efficiency reached 70%. By comparing the biomass of three CRISPR/Cas9 mutants of ZmCLCg and one zmpmp3 EMS mutant with their wild-type plants under salt stress, the salt tolerance function of candidate genes ZmCLCg and ZmPMP3 were confirmed. Chloride content analysis revealed that ZmCLCg regulated chloride transport under sodium chloride stress. These results help to explain genetic variations in salt tolerance and provide novel loci for generating salt-tolerant maize lines.

Natural variations in the P-type ATPase heavy metal transporter gene ZmHMA3 control cadmium accumulation in maize grains

Cadmium (Cd) accumulation in maize grains is detrimental to human health. Developing maize varieties with low Cd content is important for safe consumption of maize grains. However, the key genes controlling maize grain Cd accumulation have not been cloned. Here, we identified one major locus for maize grain Cd accumulation (qCd1) using a genome-wide association study (GWAS) and bulked segregant RNA-seq analysis with a biparental segregating population of Jing724 (low-Cd line) and Mo17 (high-Cd line). The candidate gene ZmHMA3 was identified by fine mapping and encodes a tonoplast-localized heavy metal P-type ATPase transporter. An ethyl methane sulfonate mutant analysis and an allelism test confirmed that ZmHMA3 influences maize grain Cd accumulation. A transposon in intron 1 of ZmHMA3 is responsible for the abnormal amino acid sequence in Mo17. Based on the natural sequence variations in the ZmHMA3 gene of diverse maize lines, four PCR-based molecular markers were developed, and these were successfully used to distinguish five haplotypes with different grain Cd contents in the GWAS panel and to predict grain Cd contents of widely used maize inbred lines and hybrids. These molecular markers can be used to breed elite maize varieties with low grain Cd contents.

Integrating a genome-wide association study with transcriptomic data to predict candidate genes and favourable haplotypes influencing Brassica napus seed phytate

Phytate is the storage form of phosphorus in angiosperm seeds and plays vitally important roles during seed development. However, in crop plants phytate decreases bioavailability of seed-sourced mineral elements for humans, livestock and poultry, and contributes to phosphate-related water pollution. However, there is little knowledge about this trait in oilseed rape (Brassica napus). Here, a panel of 505 diverse B. napus accessions was screened in a genome-wide association study (GWAS) using 3.28 × 10⁶ single-nucleotide polymorphisms (SNPs). This identified 119 SNPs significantly associated with phytate concentration (PA_Conc) and phytate content (PA_Cont) and six candidate genes were identified. Of these, BnaA9.MRP5 represented the candidate gene for the significant SNP chrA09_5198034 (27 kb) for both PA_Cont and PA_Conc. Transcription of BnaA9.MRP5 in a low-phytate variety (LPA20) was significantly elevated compared with a high-phytate variety (HPA972). Association and haplotype analysis indicated that inbred lines carrying specific SNP haplotypes within BnaA9.MRP5 were associated with high- and low-phytate phenotypes. No significant differences in seed germination and seed yield were detected between low and high phytate cultivars examined. Candidate genes, favourable haplotypes and the low phytate varieties identified in this study will be useful for low-phytate breeding of B. napus.

Genetic dissection of maize seedling traits in an IBM Syn10 DH population under the combined stress of lead and cadmium

The heavy metals lead and cadmium have become important pollutants in the environment, which exert negative effects on plant morphology, growth and photosynthesis. It is particularly significant to uncover the genetic loci and the causal genes for lead and cadmium tolerance in plants. This study used an IBM Syn10 DH population to identify the quantitative trait loci (QTL) controlling maize seedling tolerance to lead and cadmium by linkage mapping. The broad-sense heritability of these seedling traits ranged from 65.8-97.3% and 32.0-98.8% under control (CK) and treatment (T) conditions, respectively. A total of 53 and 64 QTL were detected under CK and T conditions, respectively. Moreover, 42 QTL were identified using lead and cadmium tolerance coefficient (LCTC). Among these QTL, five and two major QTL that explained > 10% of phenotypic variation were identified under T condition and using LCTC, respectively. Furthermore, eight QTL were simultaneously identified by T and LCTC, explaining 5.23% to 9.21% of the phenotypic variations. Within these major and common QTL responsible for the combined heavy metal tolerance, four candidate genes (Zm00001d048759, Zm00001d004689, Zm00001d004843, Zm00001d033527) were previously reported to correlate with heavy metal transport and tolerance. These findings will contribute to functional gene identification and molecular marker-assisted breeding for improving heavy metal tolerance in maize.

A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments

Using GWAS and QTL mapping identified 100 QTL and 138 SNPs, which control yield-related traits in maize. The candidate gene GRMZM2G098557 was further validated to regulate ear row number by using a segregation population. Understanding the genetic basis of yield-related traits contributes to the improvement of grain yield in maize. This study used an inter-mated B73 × Mo17 (IBM) Syn10 doubled-haploid (DH) population and an association panel to identify the genetic loci responsible for nine yield-related traits in maize. Using quantitative trait loci (QTL) mapping, 100 QTL influencing these traits were detected across different environments in the IBM Syn10 DH population, with 25 co-detected in multiple environments. Using a genome-wide association study (GWAS), 138 single-nucleotide polymorphisms (SNPs) were identified as correlated with these traits (P < 2.04E-06) in the association panel. Twenty-one pleiotropic QTL/SNPs were identified to control different traits in both populations. A combination of QTL mapping and GWAS uncovered eight significant SNPs (PZE-101097575, PZE-103169263, ZM011204-0763, PZE-104044017, PZE-104123110, SYN8062, PZE-108060911, and PZE-102043341) that were co-located within seven QTL confidence intervals. According to the eight co-localized SNPs by the two populations, 52 candidate genes were identified, among which the ear row number (ERN)-associated SNP SYN8062 was closely linked to SBP-transcription factor 7 (GRMZM2G098557). Several SBP-transcription factors were previously demonstrated to modulate maize ERN. We then validated the phenotypic effects of SYN8062 in the IBM Syn10 DH population, indicating that the ERN of the lines with the A-allele in SYN8062 was significantly (P < 0.05) larger than that of the lines with the G-allele in SYN8062 in each environment. These findings provide valuable information for understanding the genetic mechanisms of maize grain yield formation and for improving molecular marker-assisted selection for the high-yield breeding of maize.

Dissection of the genetic variation and candidate genes of lint percentage by a genome-wide association study in upland cotton

A genome-wide associated study identified six novel QTLs for lint percentage. Two candidate genes underlying this trait were also detected. Increasing lint percentage (LP) is a core goal of cotton breeding. To better understand the genetic basis of LP, a genome-wide association study (GWAS) was conducted using 276 upland cotton accessions planted in multiple environments and genotyped with a CottonSNP63K array. After filtering, 10,660 high-quality single-nucleotide polymorphisms (SNPs) were retained. Population structure, principal component and neighbor-joining phylogenetic tree analyses divided the accessions into two subpopulations. These results along with linkage disequilibrium decay indicated accessions were not highly structured and exhibited weak relatedness. GWAS uncovered 23 polymorphic SNPs and 15 QTLs significantly associated with LP, with six new QTLs identified. Two candidate genes, Gh_D05G0313 and Gh_D05G1124, both contained one significant SNP, highly expressed during ovule and fiber development stages, implying that the two genes may act as the most promising regulators of LP. Furthermore, the phenotypic value of LP was found to be positively correlated with the number of favorable SNP alleles. These favorable alleles for LP identified in the study may be useful for improving lint yield.