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The grain moisture content of maize inbred lines at maturity is one of the most important indicators for mechanical harvesting of kernels. In this study, 116 maize inbred lines from a wide range of sources were used as research materials and 30 traits of grain moisture content were analyzed using multivariate statistical analysis. The results showed that all 30 traits had some correlations. Principal component analysis downscaled the 30 traits into 10 principal component factors, reflecting 77.674% of the information in the original traits. Cluster analysis categorized the 116 inbred lines into 5 major groups containing 26, 29, 31, 16 and 14 inbred lines. Based on the D value of the overall evaluation, discriminant analysis reclassified the maize inbred lines by principal component scores and 98 maize inbred lines were correctly discriminated with a probability of 84.48%, which can be regarded as a relatively reliable clustering result. The stepwise regression method was further used to screen seven traits: GMC2, GDR1, HMC3, NH, GDR2, CD and EL and to establish a comprehensive evaluation model for the grain moisture content of maize inbred lines. Among 116 maize inbred lines, 14, represented by H21 and MS71, had the lowest grain moisture content at maturity. [ABSTRACT FROM AUTHOR]

Maize Ustilago maydis is a disease that severely affects maize yield and quality. In this paper, we employed transcriptome sequencing and GWAS analysis to identify candidate genes and reveal disease-resistant germplasm resources, thereby laying the foundation for further analysis of the molecular mechanism of maize Ustilago maydis resistance and genetic improvement. The results of transcriptome sequencing revealed that a considerable number of receptor kinase genes, signal-transduction-related protein genes, redox-response-related genes, WRKYs, and P450s genes were significantly upregulated. There was a wide range of mutations of Ustilago maydis in maize inbred lines. Thirty-two high-resistance maize inbred lines were selected, and 16 SNPs were significantly associated with the disease index. By integrating the results of GWAS and RNA-seq, five genes related to disease resistance were identified, encoding the chitinase 1 protein, fatty acid elongase (FAE), IAA9, GATA TF8, and EREB94, respectively. It provides a certain reference for the cloning of maize anti-tumor smut genes and the breeding of new varieties. [ABSTRACT FROM AUTHOR]

Maize productivity in the central belt plays a significant role in the food security of China. With good adaptability and disease resistance, landrace germplasm is important for maize improvement. A total of 246 landrace accessions were collected from the maize belts in central China and genotyped with the SLAF-seq (Specific-Locus Amplified Fragment Sequencing) method, and 144,650 SNPs were obtained for each accession. The results showed that the landrace accessions could be divided into three major groups. In the cluster results, Group I included 64 accessions, which mainly belonged to the landrace of White horse teeth; Group II had 71 accessions, which mainly belonged to the lantern red landraces; the rest of the 116 accessions were clustered as Group III, including a variety of types landraces and seven indicator inbred lines. In the results of structure and multidimensional scaling, the accessions' attribution differed with the clusters, the main reason for which is the attribution change in intermediate germplasms. Linkage disequilibrium decay distance was 0.98 kb, which was much lower than that of temperate and tropical maize inbred lines, indicated the much higher genetic diversity of landrace germplasms. The results can help us select suitable landrace germplasms and speed up the process of inbred line development and maize improvement. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]