Fast Nano-IR Hyperspectral Imaging Empowered by Large-Dataset-Free Miniaturized Spatial-Spectral Network.

The emerging field of nanoscale infrared (nano-IR) offers label-free molecular contrast, yet its imaging speed is limited by point-by-point traverse acquisition of a three-dimensional (3D) data cube. Here, we develop a spatial-spectral network (SS-Net), a miniaturized deep-learning model, together with compressive sampling to accelerate the nano-IR imaging. The compressive sampling is performed in both the spatial and spectral domains to accelerate the imaging process. The SS-Net is trained to learn the mapping from small nano-IR image patches to the corresponding spectra. With this elaborated mapping strategy, the training can be finished quickly within several minutes using the subsampled data, eliminating the need for a large-labeled dataset of common deep learning methods. We also designed an efficient loss function, which incorporates the image and spectral similarity to enhance the training. We first validate the SS-Net on an open stimulated Raman-scattering dataset; the results exhibit the potential of 10-fold imaging speed improvement with state-of-the-art performance. We then demonstrate the versatility of this approach on atomic force microscopy infrared (AFM-IR) microscopy with 7-fold imaging speed improvement, even on nanoscale Fourier transform infrared (nano-FTIR) microscopy with up to 261.6 folds faster imaging speed. We further showcase the generalization of this method on AFM-force volume-based multiparametric nanoimaging. This method establishes a paradigm for rapid nano-IR imaging, opening new possibilities for cutting-edge research in materials, photonics, and beyond.

Rapid theoretical method for inverse design on a tip-enhanced Raman spectroscopy (TERS) probe.

Tip-enhanced Raman spectroscopy (TERS) can provide correlated topographic and chemical information at the nanoscale, with great sensitivity and spatial resolution depending on the configuration of the TERS probe. The sensitivity of the TERS probe is largely determined by two effects: the lightning-rod effect and local surface plasmon resonance (LSPR). While 3D numerical simulations have traditionally been used to optimize the TERS probe structure by sweeping two or more parameters, this method is extremely resource-intensive, with computation times growing exponentially as the number of parameters increases. In this work, we propose an alternative rapid theoretical method that reduces computational loading while still achieving effective TERS probe optimization through the inverse design method. By applying this method to optimize a TERS probe with four free-structural parameters, we observed a nearly 1 order of magnitude improvement in enhancement factor (|E/E0|2), in contrast to a parameter sweeping 3D simulation that would take ∼7000 hours of computation. Our method, therefore, shows great promise as a useful tool for designing not only TERS probes but also other near-field optical probes and optical antennas.

Mechanism of Cations Suppressing Proton Diffusion Kinetics for Electrocatalysis.

Proton transfer is crucial for electrocatalysis. Accumulating cations at electrochemical interfaces can alter the proton transfer rate and then tune electrocatalytic performance. However, the mechanism for regulating proton transfer remains ambiguous. Here, we quantify the cation effect on proton diffusion in solution by hydrogen evolution on microelectrodes, revealing the rate can be suppressed by more than 10 times. Different from the prevalent opinions that proton transport is slowed down by modified electric field, we found water structure imposes a more evident effect on kinetics. FTIR test and path integral molecular dynamics simulation indicate that proton prefers to wander within the hydration shell of cations rather than to hop rapidly along water wires. Low connectivity of water networks disrupted by cations corrupts the fast-moving path in bulk water. This study highlights the promising way for regulating proton kinetics via a modified water structure.

Functional analysis revealed the involvement of ZmABCB15 in resistance to rice black-streaked dwarf virus infection.

BACKGROUND: Maize rough dwarf disease (MRDD), caused by rice black-streaked dwarf virus (RBSDV) belonging to the Fijivirus genus, seriously threatens maize production worldwide. Three susceptible varieties (Ye478, Zheng 58, and Zhengdan 958) and two resistant varieties (P138 and Chang7-2) were used in our study. RESULTS: A set of ATP-binding cassette subfamily B (ABCB) transporter genes were screened to evaluate their possible involvements in RBSDV resistance. In the present study, ZmABCB15, an ABCB transporter family member, was cloned and functionally identified. Expression analysis showed that ZmABCB15 was significantly induced in the resistant varieties, not in the susceptible varieties, suggesting its involvement in resistance to the RBSDV infection. ZmABCB15 gene encodes a putative polar auxin transporter containing two trans-membrane domains and two P-loop nucleotide-binding domains. Transient expression analysis indicated that ZmABCB15 is a cell membrance localized protein. Over-expression of ZmABCB15 enhanced the resistance by repressing the RBSDV replication ratio. ZmABCB15 might participate in the RBSDV resistance by affecting the homeostasis of active and inactive auxins in RBSDV infected seedlings. CONCLUSIONS: Polar auxin transport might participate in the RBSDV resistance by affecting the distribution of endogenous auxin among tissues. Our data showed the involvement of polar auxin transport in RBSDV resistance and provided novel mechanism underlying the auxin-mediated disease control technology.

Genome wide association analysis for yield related traits in maize.

BACKGROUND: Understanding the genetic basis of yield related traits contributes to the improvement of grain yield in maize. RESULTS: Using 291 excellent maize inbred lines as materials, six yield related traits of maize, including grain yield per plant (GYP), grain length (GL), grain width (GW), kernel number per row (KNR), 100 kernel weight (HKW) and tassel branch number (TBN) were investigated in Jinan, in 2017, 2018 and 2019. The average values of three environments were taken as the phenotypic data of yield related traits, and they were statistically analyzed. Based on 38,683 high-quality SNP markers in the whole genome of the association panel, the MLM with PCA model was used for genome-wide association analysis (GWAS) to obtain 59 significantly associated SNP sites. Moreover, 59 significantly associated SNPs (P < 0.0001) referring to GYP, GL, GW, KNR, HKW and TBN, of which 14 SNPs located in yield related QTLs/QTNs previously reported. A total of 66 candidate genes were identified based on the 59 significantly associated SNPs, of which 58 had functional annotation. CONCLUSIONS: Using genome-wide association analysis strategy to identify genetic loci related to maize yield, a total of 59 significantly associated SNP were detected. Those results aid in our understanding of the genetic architecture of maize yield and provide useful SNPs for genetic improvement of maize.

An Efficient Interfacial Synthesis of Two-Dimensional Metal-Organic Framework Nanosheets for Electrochemical Hydrogen Peroxide Production.

Two-dimensional (2D) metal-organic framework nanosheets (MOF NSs) play a vital role in catalysis, but the most preparation is ultrasonication or solvothermal. Herein, a liquid-liquid interfacial synthesis method has been developed for the efficient fabrication of a series of 2D Ni MOF NSs. The active sites could be modulated by readily tuning the ratios of metal precursors and organic linkers (RM/L ). The Ni MOF NSs display highly RM/L dependent activities towards 2e oxygen reduction reaction (ORR) to hydrogen peroxide (H2 O2 ), where the Ni MOF NSs with the RM/L of 6 exhibit the optimal near-zero overpotential, ca. 98 % H2 O2 selectivity and production rate of ca. 80 mmol gcat -1 h-1 in 0.1 M KOH. As evidenced by X-ray absorption fine structure spectroscopy, the coordination environment of active sites changed from saturation to unsaturation, and the partially unsaturated metal atoms are crucial to create optimal sites for enhancing the electrocatalysis.

Genome-wide selection and genetic improvement during modern maize breeding.

Since the development of single-hybrid maize breeding programs in the first half of the twentieth century1, maize yields have increased over sevenfold, and much of that increase can be attributed to tolerance of increased planting density2-4. To explore the genomic basis underlying the dramatic yield increase in maize, we conducted a comprehensive analysis of the genomic and phenotypic changes associated with modern maize breeding through chronological sampling of 350 elite inbred lines representing multiple eras of germplasm from both China and the United States. We document several convergent phenotypic changes in both countries. Using genome-wide association and selection scan methods, we identify 160 loci underlying adaptive agronomic phenotypes and more than 1,800 genomic regions representing the targets of selection during modern breeding. This work demonstrates the use of the breeding-era approach for identifying breeding signatures and lays the foundation for future genomics-enabled maize breeding.

Genomic selection on shelling percentage and other traits for maize.

Genomic selection (GS) is the one of the new method for molecular marker-assisted selection (MAS) that can improve selection efficiency and thereby accelerate selective breeding progress. In the present study, we used the exotic germplasm LK1 to improve the shelling percentage of Qi319 by GS. Genome-wide marker effects for each trait were estimated based on the performance of the testcross and SNP data for F2 progenies in the training population. The accuracy of genomic predictions was estimated as the correlation between marker-predicted genotypic values and phenotypic values of the testcrosses for each trait in the validation population. Our study result indicated that selection response for shell percentage was 33.7%, which is greater than those for grain yield, kernel number per ear, or grain moisture at harvest. Selection response for tassel branch number and weight per 100 kernels was greater than 60%. The Higher trait heritability resulted in better prediction efficiency; Prediction accuracy increased with the training population size; Prediction efficiency did not differ significantly between SNP densities of 1000 bp and 55,000 bp. The results of the present research project will provide a basis for genome-wide selection technology in maize breeding, and lay the groundwork for the application of GS to germplasms that are useful in China.

Combined small RNA and gene expression analysis revealed roles of miRNAs in maize response to rice black-streaked dwarf virus infection.

Maize rough dwarf disease, caused by rice black-streaked dwarf virus (RBSDV), is a devastating disease in maize (Zea mays L.). MicroRNAs (miRNAs) are known to play critical roles in regulation of plant growth, development, and adaptation to abiotic and biotic stresses. To elucidate the roles of miRNAs in the regulation of maize in response to RBSDV, we employed high-throughput sequencing technology to analyze the miRNAome and transcriptome following RBSDV infection. A total of 76 known miRNAs, 226 potential novel miRNAs and 351 target genes were identified. Our dataset showed that the expression patterns of 81 miRNAs changed dramatically in response to RBSDV infection. Transcriptome analysis showed that 453 genes were differentially expressed after RBSDV infection. GO, COG and KEGG analysis results demonstrated that genes involved with photosynthesis and metabolism were significantly enriched. In addition, twelve miRNA-mRNA interaction pairs were identified, and six of them were likely to play significant roles in maize response to RBSDV. This study provided valuable information for understanding the molecular mechanism of maize disease resistance, and could be useful in method development to protect maize against RBSDV.

Expression analysis of genes encoding double B-box zinc finger proteins in maize.

The B-box proteins play key roles in plant development. The double B-box (DBB) family is one of the subfamily of the B-box family, with two B-box domains and without a CCT domain. In this study, 12 maize double B-box genes (ZmDBBs) were identified through a genome-wide survey. Phylogenetic analysis of DBB proteins from maize, rice, Sorghum bicolor, Arabidopsis, and poplar classified them into five major clades. Gene duplication analysis indicated that segmental duplications made a large contribution to the expansion of ZmDBBs. Furthermore, a large number of cis-acting regulatory elements related to plant development, response to light and phytohormone were identified in the promoter regions of the ZmDBB genes. The expression patterns of the ZmDBB genes in various tissues and different developmental stages demonstrated that ZmDBBs might play essential roles in plant development, and some ZmDBB genes might have unique function in specific developmental stages. In addition, several ZmDBB genes showed diurnal expression pattern. The expression levels of some ZmDBB genes changed significantly under light/dark treatment conditions and phytohormone treatments, implying that they might participate in light signaling pathway and hormone signaling. Our results will provide new information to better understand the complexity of the DBB gene family in maize.

Inventory and general analysis of the ATP-binding cassette (ABC) gene superfamily in maize (Zea mays L.).

The metabolic functions of ATP-binding cassette (or ABC) proteins, one of the largest families of proteins presented in all organisms, have been investigated in many protozoan, animal and plant species. To facilitate more systematic and complicated studies on maize ABC proteins in the future, we present the first complete inventory of these proteins, including 130 open reading frames (ORFs), and provide general descriptions of their classifications, basic structures, typical functions, evolution track analysis and expression profiles. The 130 ORFs were assigned to eight subfamilies based on their structures and homological features. Five of these subfamilies consist of 109 proteins, containing transmembrane domains (TM) performing as transporters. The rest three subfamilies contain 21 soluble proteins involved in various functions other than molecular transport. A comparison of ABC proteins among nine selected species revealed either convergence or divergence in each of the ABC subfamilies. Generally, plant genomes contain far more ABC genes than animal genomes. The expression profiles and evolution track of each maize ABC gene were further investigated, the results of which could provide clues for analyzing their functions. Quantitative real-time polymerase chain reaction experiments (PCR) were conducted to detect induced expression in select ABC genes under several common stresses. This investigation provides valuable information for future research on stress tolerance in plants and potential strategies for enhancing maize production under stressful conditions.

Genome-wide analysis and environmental response profiling of the FK506-binding protein gene family in maize (Zea mays L.).

The FK506-binding proteins (FKBPs) belong to the peptidyl-prolyl cis/trans isomerase (PPIase) superfamily, and have been implicated in a wide spectrum of biological processes, including protein folding, hormone signaling, plant growth, and stress responses. Genome-wide structural and evolutionary analyses of the entire FKBP gene family have been conducted in Arabidopsis and rice. In the present study, a genome-wide analysis was performed to identify all maize FKBP genes. The availability of complete maize genome sequences allowed for the identification of 24 FKBP genes. Chromosomal locations in the maize genome were determined and the protein domain and motif organization of ZmFKBPs analyzed. The phylogenetic relationships between maize FKBPs were also assessed. The expression profiles of ZmFKBP genes were measured under different environmental conditions and revealed distinct ZmFKBP gene expression patterns under heat, cold, salt, and drought stress. These data not only contribute to a better understanding of the complex regulation of the maize FKBP gene family, but also provide evidence supporting the role of FKBPs in multiple signaling pathways involved in stress responses. This investigation may provide valuable information for further research on stress tolerance in plants and potential strategies for enhancing maize survival under stressful conditions.

PwHAP5, a CCAAT-binding transcription factor, interacts with PwFKBP12 and plays a role in pollen tube growth orientation in Picea wilsonii.

The HAP complex occurs in many eukaryotic organisms and is involved in multiple physiological processes. Here it was found that in Picea wilsonii, HAP5 (PwHAP5), a putative CCAAT-binding transcription factor gene, is involved in pollen tube development and control of tube orientation. Quantitative real-time reverse transcription-PCR showed that PwHAP5 transcripts were expressed strongly in germinating pollen and could be induced by Ca(2+). Overexpression of PwHAP5 in pollen altered pollen tube orientation, whereas the tube with PwHAP5RNAi showed normal growth without diminishing pollen tube growth. Furthermore, PwFKBP12, which encodes an FK506-binding protein (FKBP) was screened and a bimolecular fluorescence complementation assay performed to confirm the interaction of PwHAP5 and PwFKBP12 in vivo. Transient expression of PwFKBP12 in pollen showed normal pollen tube growth, whereas the tube with PwFKBP12RNAi bent. The phenotype of overexpression of HAP5 on pollen tube was restored by FKBP12. Altogether, our study supported the role of HAP5 in pollen tube development and orientation regulation and identified FKBP12 as a novel partner to interact with HAP5 involved in the process.