Maize smart-canopy architecture enhances yield at high densities.

Increasing planting density is a key strategy for enhancing maize yields1-3. An ideotype for dense planting requires a 'smart canopy' with leaf angles at different canopy layers differentially optimized to maximize light interception and photosynthesis4-6, among other features. Here we identified leaf angle architecture of smart canopy 1 (lac1), a natural mutant with upright upper leaves, less erect middle leaves and relatively flat lower leaves. lac1 has improved photosynthetic capacity and attenuated responses to shade under dense planting. lac1 encodes a brassinosteroid C-22 hydroxylase that predominantly regulates upper leaf angle. Phytochrome A photoreceptors accumulate in shade and interact with the transcription factor RAVL1 to promote its degradation via the 26S proteasome, thereby inhibiting activation of lac1 by RAVL1 and decreasing brassinosteroid levels. This ultimately decreases upper leaf angle in dense fields. Large-scale field trials demonstrate that lac1 boosts maize yields under high planting densities. To quickly introduce lac1 into breeding germplasm, we transformed a haploid inducer and recovered homozygous lac1 edits from 20 diverse inbred lines. The tested doubled haploids uniformly acquired smart-canopy-like plant architecture. We provide an important target and an accelerated strategy for developing high-density-tolerant cultivars, with lac1 serving as a genetic chassis for further engineering of a smart canopy in maize.

The transcription factor bZIP68 negatively regulates cold tolerance in maize.

Maize (Zea mays) originated in tropical areas and is thus susceptible to low temperatures, which pose a major threat to maize production. Our understanding of the molecular basis of cold tolerance in maize is limited. Here, we identified bZIP68, a basic leucine zipper (bZIP) transcription factor, as a negative regulator of cold tolerance in maize. Transcriptome analysis revealed that bZIP68 represses the cold-induced expression of DREB1 transcription factor genes. The stability and transcriptional activity of bZIP68 are controlled by its phosphorylation at the conserved Ser250 residue under cold stress. Furthermore, we demonstrated that the bZIP68 locus was a target of selection during early domestication. A 358-bp insertion/deletion (Indel-972) polymorphism in the bZIP68 promoter has a significant effect on the differential expression of bZIP68 between maize and its wild ancestor teosinte. This study thus uncovers an evolutionary cis-regulatory variant that could be used to improve cold tolerance in maize.

Genome-Wide Association Analyses Reveal the Importance of Alternative Splicing in Diversifying Gene Function and Regulating Phenotypic Variation in Maize.

Alternative splicing (AS) enhances transcriptome diversity and plays important roles in regulating plant processes. Although widespread natural variation in AS has been observed in plants, how AS is regulated and contribute to phenotypic variation is poorly understood. Here, we report a population-level transcriptome assembly and genome-wide association study to identify splicing quantitative trait loci (sQTLs) in developing maize (Zea mays) kernels from 368 inbred lines. We detected 19,554 unique sQTLs for 6570 genes. Most sQTLs showed small isoform usage changes without involving major isoform switching between genotypes. The sQTL-affected isoforms tend to display distinct protein functions. We demonstrate that nonsense-mediated mRNA decay, microRNA-mediated regulation, and small interfering peptide-mediated peptide interference are frequently involved in sQTL regulation. The natural variation in AS and overall mRNA level appears to be independently regulated with different cis-sequences preferentially used. We identified 214 putative trans-acting splicing regulators, among which ZmGRP1, encoding an hnRNP-like glycine-rich RNA binding protein, regulates the largest trans-cluster. Knockout of ZmGRP1 by CRISPR/Cas9 altered splicing of numerous downstream genes. We found that 739 sQTLs colocalized with previous marker-trait associations, most of which occurred without changes in overall mRNA level. Our findings uncover the importance of AS in diversifying gene function and regulating phenotypic variation.

ZmCCT9 enhances maize adaptation to higher latitudes.

From its tropical origin in southwestern Mexico, maize spread over a wide latitudinal cline in the Americas. This feat defies the rule that crops are inhibited from spreading easily across latitudes. How the widespread latitudinal adaptation of maize was accomplished is largely unknown. Through positional cloning and association mapping, we resolved a flowering-time quantitative trait locus to a Harbinger-like transposable element positioned 57 kb upstream of a CCT transcription factor (ZmCCT9). The Harbinger-like element acts in cis to repress ZmCCT9 expression to promote flowering under long days. Knockout of ZmCCT9 by CRISPR/Cas9 causes early flowering under long days. ZmCCT9 is diurnally regulated and negatively regulates the expression of the florigen ZCN8, thereby resulting in late flowering under long days. Population genetics analyses revealed that the Harbinger-like transposon insertion at ZmCCT9 and the CACTA-like transposon insertion at another CCT paralog, ZmCCT10, arose sequentially following domestication and were targeted by selection for maize adaptation to higher latitudes. Our findings help explain how the dynamic maize genome with abundant transposon activity enabled maize to adapt over 90° of latitude during the pre-Columbian era.

An improved deep learning approach and its applications on colonic polyp images detection.

BACKGROUND: Colonic polyps are more likely to be cancerous, especially those with large diameter, large number and atypical hyperplasia. If colonic polyps cannot be treated in early stage, they are likely to develop into colon cancer. Colonoscopy is easily limited by the operator's experience, and factors such as inexperience and visual fatigue will directly affect the accuracy of diagnosis. Cooperating with Hunan children's hospital, we proposed and improved a deep learning approach with global average pooling (GAP) in colonoscopy for assisted diagnosis. Our approach for assisted diagnosis in colonoscopy can prompt endoscopists to pay attention to polyps that may be ignored in real time, improve the detection rate, reduce missed diagnosis, and improve the efficiency of medical diagnosis. METHODS: We selected colonoscopy images from the gastrointestinal endoscopy room of Hunan children's hospital to form the colonic polyp datasets. And we applied the image classification method based on Deep Learning to the classification of Colonic Polyps. The classic networks we used are VGGNets and ResNets. By using global average pooling, we proposed the improved approaches: VGGNets-GAP and ResNets-GAP. RESULTS: The accuracies of all models in datasets exceed 98%. The TPR and TNR are above 96 and 98% respectively. In addition, VGGNets-GAP networks not only have high classification accuracies, but also have much fewer parameters than those of VGGNets. CONCLUSIONS: The experimental results show that the proposed approach has good effect on the automatic detection of colonic polyps. The innovations of our method are in two aspects: (1) the detection accuracy of colonic polyps has been improved. (2) our approach reduces the memory consumption and makes the model lightweight. Compared with the original VGG networks, the parameters of our VGG19-GAP networks are greatly reduced.

Complex genetic architecture underlies maize tassel domestication.

Maize (Zea mays) tassels underwent profound morphological changes during maize domestication and improvement. Although a number of genes affecting maize inflorescence development have been identified, the genetic basis of the morphological changes in maize tassels since domestication is not well understood. Here, using a large population of 866 maize-teosinte BC2 S3 recombinant inbred lines genotyped using 19 838 single nucleotide polymorphism (SNP) markers, we performed high-resolution quantitative trait locus (QTL) mapping for five tassel morphological traits. We showed that the five tassel traits were associated with different genetic architecture features. Known genes for maize inflorescence development identified by mutagenesis were significantly enriched in the tassel trait QTLs, and many of these genes, including ramosa1 (ra1), barren inflorescence2 (bif2), unbranched2 (ub2), zea floricaula leafy2 (zfl2) and barren stalk fastigiate1 (baf1), showed evidence of selection. An in-depth nucleotide diversity analysis at the bif2 locus identified strong selection signatures in the 5'-regulatory region. We also found that several known flowering time genes co-localized with tassel trait QTLs. A further association analysis indicated that the maize photoperiod gene ZmCCT was significantly associated with tassel size variation. Using near-isogenic lines, we narrowed down a major-effect QTL for tassel length, qTL9-1, to a 513-kb physical region. These results provide important insights into the genetic architecture that controls maize tassel evolution.

The genetic architecture of leaf number and its genetic relationship to flowering time in maize.

The number of leaves and their distributions on plants are critical factors determining plant architecture in maize (Zea mays), and leaf number is frequently used as a measure of flowering time, a trait that is key to local environmental adaptation. Here, using a large set of 866 maize-teosinte BC2 S3 recombinant inbred lines genotyped by using 19,838 single nucleotide polymorphism markers, we conducted a comprehensive genetic dissection to assess the genetic architecture of leaf number and its genetic relationship to flowering time. We demonstrated that the two components of total leaf number, the number of leaves above (LA) and below (LB) the primary ear, were under relatively independent genetic control and might be subject to differential directional selection during maize domestication and improvement. Furthermore, we revealed that flowering time and leaf number are commonly regulated at a moderate level. The pleiotropy of the genes ZCN8, dlf1 and ZmCCT on leaf number and flowering time were validated by near-isogenic line analysis. Through fine mapping, qLA1-1, a major-effect locus that specifically affects LA, was delimited to a region with severe recombination suppression derived from teosinte. This study provides important insights into the genetic basis of traits affecting plant architecture and adaptation. The genetic independence of LA from LB enables the optimization of leaf number for ideal plant architecture breeding in maize.

Identification and fine mapping of quantitative trait loci for the number of vascular bundle in maize stem.

Studies that investigated the genetic basis of source and sink related traits have been widely conducted. However, the vascular system that links source and sink received much less attention. When maize was domesticated from its wild ancestor, teosinte, the external morphology has changed dramatically; however, less is known for the internal anatomy changes. In this study, using a large maize-teosinte experimental population, we performed a high-resolution quantitative trait locus (QTL) mapping for the number of vascular bundle in the uppermost internode of maize stem. The results showed that vascular bundle number is dominated by a large number of small-effect QTLs, in which a total of 16 QTLs that jointly accounts for 52.2% of phenotypic variation were detected, with no single QTL explaining more than 6% of variation. Different from QTLs for typical domestication traits, QTLs for vascular bundle number might not be under directional selection following domestication. Using Near Isogenic Lines (NILs) developed from heterogeneous inbred family (HIF), we further validated the effect of one QTL qVb9-2 on chromosome 9 and fine mapped the QTL to a 1.8-Mb physical region. This study provides important insights for the genetic architecture of vascular bundle number in maize stem and sets basis for cloning of qVb9-2.

A SAR Image Target Recognition Approach via Novel SSF-Net Models.

With the wide application of high-resolution radar, the application of Radar Automatic Target Recognition (RATR) is increasingly focused on how to quickly and accurately distinguish high-resolution radar targets. Therefore, Synthetic Aperture Radar (SAR) image recognition technology has become one of the research hotspots in this field. Based on the characteristics of SAR images, a Sparse Data Feature Extraction module (SDFE) has been designed, and a new convolutional neural network SSF-Net has been further proposed based on the SDFE module. Meanwhile, in order to improve processing efficiency, the network adopts three methods to classify targets: three Fully Connected (FC) layers, one Fully Connected (FC) layer, and Global Average Pooling (GAP). Among them, the latter two methods have less parameters and computational cost, and they have better real-time performance. The methods were tested on public datasets SAR-SOC and SAR-EOC-1. The experimental results show that the SSF-Net has relatively better robustness and achieves the highest recognition accuracy of 99.55% and 99.50% on SAR-SOC and SAR-EOC-1, respectively, which is 1% higher than the comparison methods on SAR-EOC-1.