Genome-wide analysis of the NAC transcription factor family in broomcorn millet (Panicum miliaceum L.) and expression analysis under drought stress.

BACKGROUND: Broomcorn millet is a drought-tolerant cereal that is widely cultivated in the semiarid regions of Asia, Europe, and other continents; however, the mechanisms underlying its drought-tolerance are poorly understood. The NAM, ATAF1/2, and CUC2 (NAC) transcription factors form a large plant-specific gene family that is involved in the regulation of tissue development and abiotic stress. To date, NAC transcription factors have not been systematically researched in broomcorn millet. RESULTS: In the present study, a total of 180 NAC (PmNAC) genes were identified from the broomcorn millet genome and named uniformly according to their chromosomal distribution. Phylogenetic analysis demonstrated that the PmNACs clustered into 12 subgroups, including the broomcorn millet-specific subgroup Pm_NAC. Gene structure and protein motif analyses indicated that closely clustered PmNAC genes were relatively conserved within each subgroup, while genome mapping analysis revealed that the PmNAC genes were unevenly distributed on broomcorn millet chromosomes. Transcriptome analysis revealed that the PmNAC genes differed greatly in expression in various tissues and under different drought stress durations. The expression of 10 selected genes under drought stress was analyzed using quantitative real-time PCR. CONCLUSION: In this study, 180 NAC genes were identified in broomcorn millet, and their phylogenetic relationships, gene structures, protein motifs, chromosomal distribution, duplication, expression patterns in different tissues, and responses to drought stress were studied. These results will be useful for the further study of the functional characteristics of PmNAC genes, particularly with regards to drought resistance.

Meta-analysis of the effects of overexpression of WRKY transcription factors on plant responses to drought stress.

BACKGROUND: The tryptophan-arginine-lysine-tyrosine (WRKY) transcription factors play important roles in plants, allowing them to adapt to environmental conditions that are not normally conducive to plant growth; in particular, drought. There has been extensive research on WRKY transcription factors and the effects of their overexpression in plants on resistance to drought stress. However, due to the materials (the type and species of donor and receptor, promoters) and treatments (the type and time of stress) used, different and often confounding results have been obtained between studies. Meta-analysis is a powerful statistical tool that can be used to summarize results from numerous independent experiments on the same research topic while accounting for variability across experiments. RESULTS: We carried out a meta-analysis of 16 measured parameters that affect drought resistance in plants overexpressing WRKY transcription factors and wild-type plants. We found that only one of these parameters was significantly different between transgenic and wild-type plants under drought and control conditions at a 95% confidence interval (p = 0.000, p = 0.009, respectively). Eleven of the sixteen parameters were obviously different in WRKY transgenic plants under drought and control conditions (SV, p = 0.023, SSC, p = 0.000, SOD, p = 0.012, SFW, p = 0.000, RL, p = 0.016, Pro, p = 0.000, POD, p = 0.027, MDA, p = 0.000, H2O2, p = 0.003, EL, p = 0.000, CHC, p = 0.000, respectively), seven of the eleven obviously different parameters showed positive effect (SSC, SOD, Pro, POD, MDA, H2O2, EL), four of them revealed negative effect (SV, SFW, RL, CHC). CONCLUSION: We have found that only one of these parameters was significantly different between transgenic and wild-type plants under drought and control conditions respectively, at a 95% confidence interval. And eleven of sixteen parameters showed obviously different of WRKY-overexpressed plants under different conditions (water-stressed and normal), suggesting that WRKY transcription factors play an important role in plant responses to drought stress. These findings also provide a theoretical basis for further study of the role of WRKY transcription factors in the regulation of plant responses to environmental stress.

Infection of Embryonic Callus with Agrobacterium Enables High-Speed Transformation of Maize.

Several approaches have recently been adopted to improve Agrobacterium-mediated transformation of maize; however, about eight months of in vitro culture are still required to isolate transgenic plants. Furthermore, genetic transformation of maize depends on immature embryos, which greatly increases costs. Here, we report a method that ensures the competency of an embryogenic callus secondary culture under laboratory conditions for Agrobacterium-mediated transformation. Moreover, pretreatment of the cell wall with a mixed lytic enzyme solution prior to Agrobacterium infection, significantly improved transformation efficiency and stability. Average stable transformation efficiency was approximately 30.39%, with peaks of 94.46%. Expression and phenotypic analysis of the Rsc reporter gene were tested in the T0 generation of transgenic plants. Using this system, we successfully regenerated transgenic maize plantlets within three months of the emergence of the embryogenic callus. Additionally, we reduced somaclonal variation accompanying prolonged culture of maize cells in the dedifferentiated state, thus facilitating the molecular breeding of maize.

Identification of minor effect QTLs for plant architecture related traits using super high density genotyping and large recombinant inbred population in maize (Zea mays).

BACKGROUND: Plant Architecture Related Traits (PATs) are of great importance for maize breeding, and mainly controlled by minor effect quantitative trait loci (QTLs). However, cloning or even fine-mapping of minor effect QTLs is very difficult in maize. Theoretically, large population and high density genetic map can be helpful for increasing QTL mapping resolution and accuracy, but such a possibility have not been actually tested. RESULTS: Here, we employed a genotyping-by-sequencing (GBS) strategy to construct a linkage map with 16,769 marker bins for 1021 recombinant inbred lines (RILs). Accurately mapping of well studied genes P1, pl1 and r1 underlying silk color demonstrated the map quality. After QTL analysis, a total of 51 loci were mapped for six PATs. Although all of them belong to minor effect alleles, the lengths of the QTL intervals, with a minimum and median of 1.03 and 3.40 Mb respectively, were remarkably reduced as compared with previous reports using smaller size of population or small number of markers. Several genes with known function in maize were shown to be overlapping with or close neighboring to these QTL peaks, including na1, td1, d3 for plant height, ra1 for tassel branch number, and zfl2 for tassel length. To further confirm our mapping results, a plant height QTL, qPH1a, was verified by an introgression lines (ILs). CONCLUSIONS: We demonstrated a method for high resolution mapping of minor effect QTLs in maize, and the resulted comprehensive QTLs for PATs are valuable for maize molecular breeding in the future.

Comparative mapping combined with homology-based cloning of the rice genome reveals candidate genes for grain zinc and iron concentration in maize.

BACKGROUND: Grain zinc and iron concentration is a complex trait that is controlled by quantitative trait loci (QTL) and is important for maintaining body health. Despite the substantial effort that has been put into identifying QTL for grain zinc and iron concentration, the integration of independent QTL is useful for understanding the genetic foundation of traits. The number of QTL for grain zinc and iron concentration is relatively low in a single species. Therefore, combined analysis of different genomes may help overcome this challenge. RESULTS: As a continuation of our work on maize, meta-analysis of QTL for grain zinc and iron concentration in rice was performed to identify meta-QTL (MQTL). Based on MQTL in rice and maize, comparative mapping combined with homology-based cloning was performed to identify candidate genes for grain zinc and iron concentration in maize. In total, 22 MQTL in rice, 4 syntenic MQTL-related regions, and 3 MQTL-containing candidate genes in maize (ortho-mMQTL) were detected. Two maize orthologs of rice, GRMZM2G366919 and GRMZM2G178190, were characterized as natural resistance-associated macrophage protein (NRAMP) genes and considered to be candidate genes. Phylogenetic analysis of NRAMP genes among maize, rice, and Arabidopsis thaliana further demonstrated that they are likely responsible for the natural variation of maize grain zinc and iron concentration. CONCLUSIONS: Syntenic MQTL-related regions and ortho-mMQTL are prime areas for future investigation as well as for marker-assisted selection breeding programs. Furthermore, the combined method using the rice genome that was used in this study can shed light on other species and help direct future quantitative trait research. In conclusion, these results help elucidate the molecular mechanism that underlies grain zinc and iron concentration in maize.

Gut microbiota and Tritrichomonas foetus infection: A study of prevalence and risk factors based on pet cats.

Tritrichomonas foetus (T. foetus) is a protozoal pathogen that infects cats and constitutes a significant cause of chronic colitis and diarrhea. Perturbations in the gut microbiota (GM) are affected by Trichomonas infection. Furthermore, dysregulation of the host GM enhances Trichomonas pathogenicity. However, it remains unclear whether the occurrence of diarrhea is associated with a dysregulation in GM following T. foetus infection in cats. Hence, the primary objective of this investigation was to explore the correlation between T. foetus infection and dysregulation in GM by analyzing fecal samples obtained from pet cats in Henan Province, central China. We randomly collected 898 fecal samples from pet cats living in 11 prefectural cities within Henan Province, and T. foetus was screened with polymerase chain reaction (PCR) amplification based on the 18 S rRNA gene. Subsequently, six T. foetus-positive and six T. foetus-negative samples underwent analysis through 16 S rRNA gene sequencing to evaluate the gut microbiota's composition. The overall prevalence of T. foetus infection among the collected samples was found to be 6.01% (54/898). Notably, a higher prevalence of infection was observed in young, undewormed, unimmunized, and diarrheic pet cats. T. foetus infection was found to significantly alter the composition of the pet cat fecal microbiota, leading to dysfunctions. Moreover, it resulted in a substantial increase in the abundance of Bacteroidetes, Proteobacteria, and Phascolarctobacterium spp., while decreasing the ratio of Firmicutes to Bacteroidetes (F/B) and the abundance of Actinobacteria, Clostridiaceae_Clostridium spp., Phascolarctobacterium spp., SMB53 spp., and Blautia spp. We constructed ROC curves to assess the diagnostic value of specific bacterial taxa in discriminating T. foetus infection. The analysis revealed that Proteobacteria and Clostridiaceae_Clostridium spp. were the most reliable single predictors for T. foetus infection. This finding suggests that alterations in the GM may be strongly associated with T. foetus infections.

Molecular characterization of Cryptosporidium spp. and Giardia duodenalis in pet cats in Henan Province, central China.

Cryptosporidium spp. and G. duodenalis often infect humans, cats, and other mammals, causing diarrhea and being responsible for numerous outbreaks of waterborne and foodborne infections worldwide. The rapid increase in the number of pet cats poses a substantial public health risk. However, there were few reports about the infection of Cryptosporidium spp. and G. duodenalis infections in pet cats in Henan Province, central China. Thus, to understand the prevalence and genetic distribution of Cryptosporidium spp. and G. duodenalis in pet cats, and to evaluate the zoonotic potential, possible transmission routes and public health implications of isolates, fecal samples (n = 898) were randomly collected from pet cats in 11 cities in Henan Province, central China. Nested PCR based on the SSU rRNA gene and bg gene was used to the prevalence of Cryptosporidium spp. and G. duodenalis, respectively. The prevalence was 0.8 % (7/898) and 2.0 % (18/898) for Cryptosporidium spp. and G. duodenalis respectively. Additionally, the Cryptosporidium spp. positive isolates were identified as C. parvum subtype IIdA19G1 by gp60 gene. In the present study, the IIdA19G1 subtype was discovered in pet cats for the first time in China, enriching the information on the host type and geographical distribution of Cryptosporidium spp. in China. For G. duodenalis, a total of 18 G. duodenalis positive samples were identified, belonging to four assemblages: a zoonotic assemblage A1 (4/898), three host-specific assemblages C (8/898), D (5/898), and F (1/898). Interestingly, we found that pet cats infected with Cryptosporidium spp. and G. duodenalis are more likely to experience emaciation symptoms compared to the negative group. More importantly, the prevalence of Cryptosporidium spp. and G. duodenalis detected in the present study were low, but the subtype IIdA19G1 of Cryptosporidium spp. and the assemblages A1, C, D, and F of G. duodenalis have the potential for zoonotic transmission. Thus, we should focus on preventing and controlling the risk of cross-species transmission that may occur in pet cats in Henan Province.

Identification and characterization of the zinc-regulated transporters, iron-regulated transporter-like protein (ZIP) gene family in maize.

BACKGROUND: Zinc (Zn) and iron (Fe) are essential micronutrients for plant growth and development, their deficiency or excess severely impaired physiological and biochemical reactions of plants. Therefore, a tightly controlled zinc and iron uptake and homeostasis network has been evolved in plants. The Zinc-regulated transporters, Iron-regulated transporter-like Proteins (ZIP) are capable of uptaking and transporting divalent metal ion and are suggested to play critical roles in balancing metal uptake and homeostasis, though a detailed analysis of ZIP gene family in maize is still lacking. RESULTS: Nine ZIP-coding genes were identified in maize genome. It was revealed that the ZmZIP proteins share a conserved transmembrane domain and a variable region between TM-3 and TM-4. Transiently expression in onion epidermal cells revealed that all ZmZIP proteins were localized to the endoplasmic reticulum and plasma membrane. The yeast complementation analysis was performed to test the Zn or Fe transporter activity of ZmZIP proteins. Expression analysis showed that the ZmIRT1 transcripts were dramatically induced in response to Zn- and Fe-deficiency, though the expression profiles of other ZmZIP changed variously. The expression patterns of ZmZIP genes were observed in different stages of embryo and endosperm development. The accumulations of ZmIRT1 and ZmZIP6 were increased in the late developmental stages of embryo, while ZmZIP4 was up-regulated during the early development of embryo. In addition, the expression of ZmZIP5 was dramatically induced associated with middle stage development of embryo and endosperm. CONCLUSIONS: These results suggest that ZmZIP genes encode functional Zn or Fe transporters that may be responsible for the uptake, translocation, detoxification and storage of divalent metal ion in plant cells. The various expression patterns of ZmZIP genes in embryo and endosperm indicates that they may be essential for ion translocation and storage during differential stages of embryo and endosperm development. The present study provides new insights into the evolutionary relationship and putative functional divergence of the ZmZIP gene family during the growth and development of maize.

ZmCOP1 Regulates Maize Mesocotyl Length and Plant Height through the Phytohormone Pathways.

The morphogenesis of crops is critical to their yield performance. COP1 (constitutively photomorphogenic1) is one of the core regulators in plant morphogenesis and has been deeply studied in Arabidopsis thaliana. However, the function of COP1 in maize is still unclear. Here, we found that the mesocotyl lengths of zmcop1 loss-of-function mutants were shorter than those of wild-type B73 in darkness, while the mesocotyl lengths of lines with ZmCOP1 overexpression were longer than those of wild-type B104. The plant height with zmcop1 was shorter than that of B73 in both short- and long-day photoperiods. Using transcriptome RNA sequencing technology, we identified 33 DEGs (differentially expressed genes) between B73's etiolated seedlings and those featuring zmcop1, both in darkness. The DEGs were mainly enriched in the plant phytohormone pathways. Our results provide direct evidence that ZmCOP1 functions in the elongation of etiolated seedlings in darkness and affects plant height in light. Our data can be applied in the improvement of maize plant architecture.

Automatic Localization of Seizure Onset Zone Based on Multi-Epileptogenic Biomarkers Analysis of Single-Contact from Interictal SEEG.

Successful surgery on drug-resistant epilepsy patients (DRE) needs precise localization of the seizure onset zone (SOZ). Previous studies analyzing this issue still face limitations, such as inadequate analysis of features, low sensitivity and limited generality. Our study proposed an innovative and effective SOZ localization method based on multiple epileptogenic biomarkers (spike and HFOs), and analysis of single-contact (MEBM-SC) to address the above problems. We extracted contacts epileptic features from signal distributions and signal energy based on machine learning and end-to-end deep learning. Among them, a normalized pathological ripple rate was designed to reduce the disturbance of physiological ripple and enhance the performance of SOZ localization. Then, a feature selection algorithm based on Shapley value and hypothetical testing (ShapHT+) was used to limit interference from irrelevant features. Moreover, an attention mechanism and a focal loss algorithm were used on the classifier to learn significant features and overcome the unbalance of SOZ/nSOZ contacts. Finally, we provided an SOZ prediction and visualization on magnetic resonance imaging (MRI). Ten patients with DRE were selected to verify our method. The experiment performed cross-validation and revealed that MEBM-SC obtains higher sensitivity. Additionally, the spike has better sensitivity while HFOs have better specificity, and the combination of these biomarkers can achieve the best performance. The study confirmed that MEBM-SC can increase the sensitivity and accuracy of SOZ localization and help clinicians to perform a precise and reliable preoperative evaluation based on interictal SEEG.

SEEG-Net: An explainable and deep learning-based cross-subject pathological activity detection method for drug-resistant epilepsy.

OBJECTIVE: Precise preoperative evaluation of drug-resistant epilepsy (DRE) requires accurate analysis of invasive stereoelectroencephalography (SEEG). With the tremendous breakthrough of Artificial intelligence (AI), previous studies can help clinical experts to identify pathological activities automatically. However, they still face limitations when applied in real-world clinical DRE scenarios, such as sample imbalance, cross-subject domain shift, and poor interpretability. Our objective is to propose a model that can address the above problems and realizes high-sensitivity SEEG pathological activity detection based on two real clinical datasets. METHODS: Our proposed innovative and effective SEEG-Net introduces a multiscale convolutional neural network (MSCNN) to increase the receptive field of the model, and to learn SEEG multiple frequency domain features, local and global features. Moreover, we designed a novel focal domain generalization loss (FDG-loss) function to enhance the target sample weight and to learn domain consistency features. Furthermore, to enhance the interpretability and flexibility of SEEG-Net, we explain SEEG-Net from multiple perspectives, such as significantly different features, interpretable models, and model learning process interpretation by Grad-CAM++. RESULTS: The performance of our proposed method is verified on a public benchmark multicenter SEEG dataset and a private clinical SEEG dataset for a robust comparison. The experimental results demonstrate that the SEEG-Net model achieves the highest sensitivity and is state-of-the-art on cross-subject (for different patients) evaluation, and well deal with the known problems. Besides, we provide an SEEG processing and database construction flow, by maintaining consistency with the real-world clinical scenarios. SIGNIFICANCE: According to the results, SEEG-Net is constructed to increase the sensitivity of SEEG pathological activity detection. Simultaneously, we settled certain problems about AI assistance in clinical DRE, built a bridge between AI algorithm application and clinical practice.

Identification of quantitative trait loci for related traits of stalk lodging resistance using genome-wide association studies in maize (Zea mays L.).

BACKGROUND: Stalk lodging is one of the main factors affecting maize (Zea mays L.) yield and limiting mechanized harvesting. Developing maize varieties with high stalk lodging resistance requires exploring the genetic basis of lodging resistance-associated agronomic traits. Stalk strength is an important indicator to evaluate maize lodging and can be evaluated by measuring stalk rind penetrometer resistance (RPR) and stalk buckling strength (SBS). Along with morphological traits of the stalk for the third internodes length (TIL), fourth internode length (FIL), third internode diameter (TID), and the fourth internode diameter (FID) traits are associated with stalk lodging resistance. RESULTS: In this study, a natural population containing 248 diverse maize inbred lines genotyped with 83,057 single nucleotide polymorphism (SNP) markers was used for genome-wide association study (GWAS) for six stalk lodging resistance-related traits. The heritability of all traits ranged from 0.59 to 0.72 in the association mapping panel. A total of 85 significant SNPs were identified for the association mapping panel using best linear unbiased prediction (BLUP) values of all traits. Additionally, five candidate genes were associated with stalk strength traits, which were either directly or indirectly associated with cell wall components. CONCLUSIONS: These findings contribute to our understanding of the genetic basis of maize stalk lodging and provide valuable theoretical guidance for lodging resistance in maize breeding in the future.

Genome-wide association studies of grain quality traits in maize.

High quality is the main goal of today's maize breeding and the investigation of grain quality traits would help to breed high-quality varieties in maize. In this study, genome-wide association studies in a set of 248 diverse inbred lines were performed with 83,057 single nucleotide polymorphisms (SNPs), and five grain quality traits were investigated in diverse environments for two years. The results showed that maize inbred lines showed substantial natural variations of grain quality and these traits showed high broad-sense heritability. A total of 49 SNPs were found to be significantly associated with grain quality traits. Among these SNPs, four co-localized sites were commonly detected by multiple traits. The candidate genes which were searched for can be classified into 11 biological processes, 13 cellular components, and 6 molecular functions. Finally, we found 29 grain quality-related genes. These genes and the SNPs identified in the study would offer essential information for high-quality varieties breeding programs in maize.

Computer-Aided Intracranial EEG Signal Identification Method Based on a Multi-Branch Deep Learning Fusion Model and Clinical Validation.

Surgical intervention or the control of drug-refractory epilepsy requires accurate analysis of invasive inspection intracranial EEG (iEEG) data. A multi-branch deep learning fusion model is proposed to identify epileptogenic signals from the epileptogenic area of the brain. The classical approach extracts multi-domain signal wave features to construct a time-series feature sequence and then abstracts it through the bi-directional long short-term memory attention machine (Bi-LSTM-AM) classifier. The deep learning approach uses raw time-series signals to build a one-dimensional convolutional neural network (1D-CNN) to achieve end-to-end deep feature extraction and signal detection. These two branches are integrated to obtain deep fusion features and results. Resampling is employed to split the imbalanced epileptogenic and non-epileptogenic samples into balanced subsets for clinical validation. The model is validated over two publicly available benchmark iEEG databases to verify its effectiveness on a private, large-scale, clinical stereo EEG database. The model achieves high sensitivity (97.78%), accuracy (97.60%), and specificity (97.42%) on the Bern-Barcelona database, surpassing the performance of existing state-of-the-art techniques. It is then demonstrated on a clinical dataset with an average intra-subject accuracy of 92.53% and cross-subject accuracy of 88.03%. The results suggest that the proposed method is a valuable and extremely robust approach to help researchers and clinicians develop an automated method to identify the source of iEEG signals.

Association mapping for general combining ability with yield, plant height and ear height using F1 population in maize.

General combining ability (GCA) is an important index for inbred lines breeding of maize. To identify the genetic loci of GCA and associated agronomic traits, an association analysis with 195 SSRs was made in phenotypic traits of 240 F1 derived from 120 elite inbred lines containing current breeding resources of maize crossed with 2 testers (Zheng58 and Chang7-2) in two places in 2018. All of the 20 association loci detected for grain yield (GY), plant height (PH), ear height (EH) and GCA for the three traits in two places could explain a phenotypic variation range of 7.31%-9.29%. Among the 20 association loci, 9 (7.31%-9.04%) were associated with GY, 4 (7.22%-8.91%) were related to GCA of GY, 1 (7.56%) was associated with PH, and 3 (7.53%-8.96%) were related to EH. In addition, 3 loci (9.14%-9.29%) were associated with GCA of PH whereas no locus was identified for GCA of EH. In the comparison of the association loci detected in Baoding and Handan, interestingly, one locus (7.69% and 8.11%) was identified in both environments and one locus (7.52% and 7.82%) was identified for yield and GCA of yield. Therefore, the identification of GY-, PH-, EH- and GCA-related association loci could not only provide references for high yield breeding of maize, but also help us comprehend the relationships among GY, agricultural traits and GCA.

Genome-Wide Association Study of Vascular Bundle-Related Traits in Maize Stalk.

The vascular bundle plays an important role in nutrient transportation in plants and exerts great influence on crop yield. Maize is widely used for food, feed, and fuel, producing the largest yield in the world. However, genes and molecular mechanism controlling vascular bundle-related traits in maize have largely remained undiscovered. In this study, a natural population containing 248 diverse maize inbred lines genotyped with high-throughput SNP markers was used for genome-wide association study. The results showed that broad variations existed for the vascular bundle-related traits which are subject to genetic structure and it was suitable for association analysis. In this study, we identified 15, 13, 2, 1, and 5 SNPs significantly associated with number of small vascular bundle, number of large vascular bundle, average area of single small vascular bundle, average area of single large vascular bundle, and cross-sectional area, respectively. The 210 candidate genes in the confidence interval can be classified into ten biological processes, three cellular components, and eight molecular functions. As for the Kyoto Encyclopedia of Genes and Genomes analysis of the candidate genes, a total of six pathways were identified. Finally, we found five genes related to vascular development, three genes related to cell wall, and two genes related to the mechanical strength of the stalk. Our results provide the further understanding of the genetic foundation of vascular bundle-related traits in maize stalk.

Construction of Marker-Free Genetically Modified Maize Using a Heat-Inducible Auto-Excision Vector.

Gene modification is a promising tool for plant breeding, and gradual application from the laboratory to the field. Selectable marker genes (SMG) are required in the transformation process to simplify the identification of transgenic plants; however, it is more desirable to obtain transgenic plants without selection markers. Transgene integration mediated by site-specific recombination (SSR) systems into the dedicated genomic sites has been demonstrated in a few different plant species. Here, we present an auto-elimination vector system that uses a heat-inducible Cre to eliminate the selectable marker from transgenic maize, without the need for repeated transformation or sexual crossing. The vector combines an inducible site-specific recombinase (hsp70::Cre) that allows for the precise elimination of the selectable marker gene egfp upon heating. This marker gene is used for the initial positive selection of transgenic tissue. The egfp also functions as a visual marker to demonstrate the effectiveness of the heat-inducible Cre. A second marker gene for anthocyanin pigmentation (Rsc) is located outside of the region eliminated by Cre and is used for the identification of transgenic offspring in future generations. Using the heat-inducible auto-excision vector, marker-free transgenic maize plants were obtained in a precisely controlled genetic modification process. Genetic and molecular analyses indicated that the inducible auto-excision system was tightly controlled, with highly efficient DNA excision, and provided a highly reliable method to generate marker-free transgenic maize.

Identification and characterization of maize ACD6-like gene reveal ZmACD6 as the maize orthologue conferring resistance to Ustilago maydis.

Enhancing broad-spectrum resistance is a major goal of crop breeding. However, broad-spectrum resistance has not been thoroughly investigated, and its underlying molecular mechanisms remain elusive. In the model plant Arabidopsis (Arabidopsis thaliana), ACCELERATED CELL DEATH6 (ACD6) is a key component of broad-spectrum resistance that acts in a positive feedback loop with salicylic acid (SA) to regulate multiple pattern recognition receptors. However, the role of ACD6 in disease resistance in crop plants is unclear. Here, we show that the transcript of ANK23, one of the 15 ACD6-like genes in maize (Zea mays), is induced by SA and by infection with the pathogenic fungus Ustilago maydis. Heterologous expression of ANK23 restored disease resistance in the Arabidopsis mutant acd6-2. We show that ANK23 is a maize ortholog of ACD6 and therefore rename ANK23 as ZmACD6. Furthermore, using CRISPR/Cas9, we generated ZmACD6 knockout maize plants, which are more susceptible to U. maydis than wild-type plants. We also identified a maize line (SC-9) with relatively high ZmACD6 expression levels from a diverse natural maize population. SC-9 has increased disease resistance to U. maydis and defense activation, suggesting a practical approach to cultivate elite varieties with enhanced disease resistance.

Identification and Fine-Mapping of a Major Maize Leaf Width QTL in a Re-sequenced Large Recombinant Inbred Lines Population.

Leaf width (LW) influences canopy architecture of population-cultured maize and can thus contribute to density breeding. In previous studies, almost all maize LW-related mutants have extreme effect on leaf development or accompanied unfavorable phenotypes. In addition, the identification of quantitative trait loci (QTLs) has been resolution-limited, with cloning and fine-mapping rarely performed. Here, we constructed a bin map for 670 recombinant inbred lines (RILs) using ∼1.2 billion 100-bp re-sequencing reads. QTL analysis of the LW trait directly narrowed the major effect QTL, qLW4, to a ∼270-kb interval. A fine-mapping population and near-isogenic lines (NILs) were quickly constructed using a key RIL harboring heterozygous genotypes across the qLW4 region. A recombinant-derived progeny testing strategy was subsequently used to further fine-map qLW4 to a 55-kb interval. Examination of NILs revealed that qLW4 has a completely dominant effect on LW, with no additional effect on leaf length. Candidate gene analysis suggested that this locus may be a novel LW controlling allele in maize. Our findings demonstrate the advantage of large-population high-density bin mapping, and suggest a strategy for efficiently fine-mapping or even cloning of QTLs. These results should also be helpful for further dissection of the genetic mechanism of LW variation, and benefit maize density breeding.

Constitutive expression of the ZmZIP7 in Arabidopsis alters metal homeostasis and increases Fe and Zn content.

Iron (Fe) and zinc (Zn) are important micronutrients for plant growth and development. Zinc-regulated transporters and the iron-regulated transporter-like protein (ZIP) are necessary for the homeostatic regulation of these metal micronutrients. In this study, the physiological function of ZmZIP7 which encodes a ZIP family transporter was characterized. We detected the expression profiles of ZmZIP7 in maize, and found that the accumulation of ZmZIP7 in root, stem, leaf, and seed was relatively higher than tassel and young ear. ZmZIP7 overexpression transgenic Arabidopsis lines were generated and the metal contents in transgenic and wild-type (WT) plants were examined using inductively coupled plasma atomic emission spectroscopy (ICP-OES) and Zinpyr-1 staining. Fe and Zn concentrations were elevated in the roots and shoots of ZmZIP7-overexpressing plants, while only Fe content was elevated in the seeds. We also analyzed the expression profiles of endogenous genes associated with metal homeostasis. Both endogenic Fe-deficiency inducible genes and the genes responsible for Zn and Fe transport and storage were stimulated in ZmZIP7 transgenic plants. In conclusion, ZmZIP7 encodes a functional Zn and Fe transporter, and ectopic overexpression of ZmZIP7 in Arabidopsis stimulate endogenous Fe and Zn uptake mechanisms, thereby facilitating both metal uptake and homeostasis. Our results contribute to improved understanding of ZIP family transporter functions and suggest that ZmZIP7 could be used to enhance Fe levels in grains.