scholarly journals High-quality genome assembly of the soybean fungal pathogen Cercospora kikuchii

2021 ◽  
Author(s):  
Takeshi Kashiwa ◽  
Tomohiro Suzuki
Keyword(s):  
Genome Assembly ◽  
Gene Prediction ◽  
Genomic Analysis ◽  
Agricultural Practices ◽  
Gene Clusters ◽  
Plant Diseases ◽  
Evolutionary Genomic ◽  
Soybean Leaf ◽  
Solid Foundation ◽  
Soybean Diseases

Abstract Plant diseases caused by the Cercospora genus of ascomycete fungi are a major concern for commercial agricultural practices. Several Cercospora species can affect soybeans, such as C. kikuchii which causes soybean leaf blight. Speciation in Cercospora on soybean has not been adequately studied. Some cryptic groups of Cercospora also cause diseases on soybean. Moreover, it has been known C. kikuchii population genetic structure is different between countries. Consequently, further genomic information could help to elucidate the covert differentiation of Cercospora diseases in soybean. Here, we report for the first time, a chromosome-level genome assembly for C. kikuchii. The genome assembly of 9 contigs was 34.44 Mb and the N50 was 4.19 Mb. Based on ab-initio gene prediction, several pathogenicity-related genes, including 242 genes for effector candidates, 55 secondary metabolite gene clusters, and 399 carbohydrate-active enzyme genes were identified. The genome sequence and the features described in this study provide a solid foundation for comparative and evolutionary genomic analysis for Cercospora species that cause soybean diseases worldwide.

SOYBEAN LEAF DISEASES DETECTION AND CLASSIFICATION USING RECENT IMAGE PROCESSING TECHNIQUES

2020 ◽  
Vol 8 (3) ◽  
pp. 01-08
Author(s):  
Arpan Singh Rajput ◽  
Shailja Shukla ◽  
S. S. Thakur
Keyword(s):  
Image Processing ◽  
Early Stage ◽  
Weather Condition ◽  
Plant Diseases ◽  
Soybean Plant ◽  
Plant Leaf ◽  
Image Processing Techniques ◽  
Soybean Leaf ◽  
Processing Techniques ◽  
Soybean Diseases

Purpose: India is an agricultural country and soybean production is one of the major sources of earning. Due to the major factors like diseases, pest attacks, and sudden changes in the weather condition, the productivity of the soybean crop decreases. Automatic detection of soybean plant diseases is essential to detect the symptoms of soybean diseases as early as they appear on the growing stage. This paper proposed a methodology for the analysis and detection of soybean plant leaf diseases using recent digital image processing techniques. In this paper, experimental results demonstrate that the proposed method can successfully detect and classify the major soybean diseases. Methodology: MatLab 18a is used for the simulation for the result and machine learning-based recent image processing techniques for the detection of the soybean leaf disease. Main Findings: The main finding of this work is to create the soybean leaf database which includes healthy and unhealthy leaves and achieved 96 percent accuracy in this work using the proposed methodology. Applications of this study: To detect soybean plant leaf diseases in the early stage in Agricultural. The novelty of this study: Self-prepared database of healthy and unhealthy images of soybean leaf with the proposed algorithm.

scholarly journals Whole-Genome Sequencing of Corallococcus sp. Strain EGB Reveals the Genetic Determinants Linking Taxonomy and Predatory Behavior

Genes ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1421
Author(s):  
Yuqiang Zhao ◽  
Yanxin Wang ◽  
Chengyao Xia ◽  
Xu Li ◽  
Xianfeng Ye ◽  
...  
Keyword(s):  
Extracellular Enzymes ◽  
Genomic Analysis ◽  
Gene Clusters ◽  
Predatory Behavior ◽  
Phytopathogenic Fungi ◽  
Plant Diseases ◽  
Comparative Genomic ◽  
Comprehensive Overview ◽  
Circular Chromosome ◽  
Pan Genome

Corallococcus sp. strain EGB is a Gram-negative myxobacteria isolated from saline soil, and has considerable potential for the biocontrol of phytopathogenic fungi. However, the detailed mechanisms related to development and predatory behavior are unclear. To obtain a comprehensive overview of genetic features, the genome of strain EGB was sequenced, annotated, and compared with 10 other Corallococcus species. The strain EGB genome was assembled as a single circular chromosome of 9.4 Mb with 7916 coding genes. Phylogenomics analysis showed that strain EGB was most closely related to Corallococcus interemptor AB047A, and it was inferred to be a novel species within the Corallococcus genus. Comparative genomic analysis revealed that the pan-genome of Corallococcus genus was large and open. Only a small proportion of genes were specific to strain EGB, and most of them were annotated as hypothetical proteins. Subsequent analyses showed that strain EGB produced abundant extracellular enzymes such as chitinases and β-(1,3)-glucanases, and proteases to degrade the cell-wall components of phytopathogenic fungi. In addition, 35 biosynthetic gene clusters potentially coding for antimicrobial compounds were identified in the strain EGB, and the majority of them were present in the dispensable pan-genome with unexplored metabolites. Other genes related to secretion and regulation were also explored for strain EGB. This study opens new perspectives in the greater understanding of the predatory behavior of strain EGB, and facilitates a potential application in the biocontrol of fungal plant diseases in the future.

scholarly journals Microbial Biocontrol as an Alternative to Synthetic Fungicides: Boundaries between Pre- and Postharvest Applications on Vegetables and Fruits

Fermentation ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 60
Author(s):  
Vincenzo Michele Sellitto ◽  
Severino Zara ◽  
Fabio Fracchetti ◽  
Vittorio Capozzi ◽  
Tiziana Nardi
Keyword(s):  
Crop Production ◽  
Fruits And Vegetables ◽  
Control Plant ◽  
Agricultural Practices ◽  
Plant Diseases ◽  
Postharvest Quality ◽  
Crucial Point ◽  
Production Chain ◽  
Vegetables And Fruits ◽  
And Storage

From a ‘farm to fork’ perspective, there are several phases in the production chain of fruits and vegetables in which undesired microbial contaminations can attack foodstuff. In managing these diseases, harvest is a crucial point for shifting the intervention criteria. While in preharvest, pest management consists of tailored agricultural practices, in postharvest, the contaminations are treated using specific (bio)technological approaches (physical, chemical, biological). Some issues connect the ‘pre’ and ‘post’, aligning some problems and possible solution. The colonisation of undesired microorganisms in preharvest can affect the postharvest quality, influencing crop production, yield and storage. Postharvest practices can ‘amplify’ the contamination, favouring microbial spread and provoking injures of the product, which can sustain microbial growth. In this context, microbial biocontrol is a biological strategy receiving increasing interest as sustainable innovation. Microbial-based biotools can find application both to control plant diseases and to reduce contaminations on the product, and therefore, can be considered biocontrol solutions in preharvest or in postharvest. Numerous microbial antagonists (fungi, yeasts and bacteria) can be used in the field and during storage, as reported by laboratory and industrial-scale studies. This review aims to examine the main microbial-based tools potentially representing sustainable bioprotective biotechnologies, focusing on the biotools that overtake the boundaries between pre- and postharvest applications protecting quality against microbial decay.

scholarly journals Genome Reduction and Secondary Metabolism of the Marine Sponge-Associated Cyanobacterium Leptothoe

Marine Drugs ◽  
2021 ◽  
Vol 19 (6) ◽  
pp. 298
Author(s):  
Despoina Konstantinou ◽  
Rafael V. Popin ◽  
David P. Fewer ◽  
Kaarina Sivonen ◽  
Spyros Gkelis
Keyword(s):  
Natural Products ◽  
Microbial Communities ◽  
Genomic Analysis ◽  
Gene Clusters ◽  
Marine Sponges ◽  
Genome Reduction ◽  
Extracellular Polysaccharides ◽  
Comparative Genomic ◽  
Symbiotic Relationships ◽  
Genes Encoding

Sponges form symbiotic relationships with diverse and abundant microbial communities. Cyanobacteria are among the most important members of the microbial communities that are associated with sponges. Here, we performed a genus-wide comparative genomic analysis of the newly described marine benthic cyanobacterial genus Leptothoe (Synechococcales). We obtained draft genomes from Le. kymatousa TAU-MAC 1615 and Le. spongobia TAU-MAC 1115, isolated from marine sponges. We identified five additional Leptothoe genomes, host-associated or free-living, using a phylogenomic approach, and the comparison of all genomes showed that the sponge-associated strains display features of a symbiotic lifestyle. Le. kymatousa and Le. spongobia have undergone genome reduction; they harbored considerably fewer genes encoding for (i) cofactors, vitamins, prosthetic groups, pigments, proteins, and amino acid biosynthesis; (ii) DNA repair; (iii) antioxidant enzymes; and (iv) biosynthesis of capsular and extracellular polysaccharides. They have also lost several genes related to chemotaxis and motility. Eukaryotic-like proteins, such as ankyrin repeats, playing important roles in sponge-symbiont interactions, were identified in sponge-associated Leptothoe genomes. The sponge-associated Leptothoe stains harbored biosynthetic gene clusters encoding novel natural products despite genome reduction. Comparisons of the biosynthetic capacities of Leptothoe with chemically rich cyanobacteria revealed that Leptothoe is another promising marine cyanobacterium for the biosynthesis of novel natural products.

scholarly journals A High-Quality Grapevine Downy Mildew Genome Assembly Reveals Rapidly Evolving and Lineage-Specific Putative Host Adaptation Genes

2019 ◽  
Vol 11 (3) ◽  
pp. 954-969 ◽  
Author(s):  
Yann Dussert ◽  
Isabelle D Mazet ◽  
Carole Couture ◽  
Jérôme Gouzy ◽  
Marie-Christine Piron ◽  
...  
Keyword(s):  
Downy Mildew ◽  
Genome Assembly ◽  
Population Genomics ◽  
Plasmopara Viticola ◽  
Plant Diseases ◽  
Host Specialization ◽  
Grapevine Downy Mildew ◽  
Downy Mildews ◽  
Genes Encoding ◽  
High Level

Abstract Downy mildews are obligate biotrophic oomycete pathogens that cause devastating plant diseases on economically important crops. Plasmopara viticola is the causal agent of grapevine downy mildew, a major disease in vineyards worldwide. We sequenced the genome of Pl. viticola with PacBio long reads and obtained a new 92.94 Mb assembly with high contiguity (359 scaffolds for a N50 of 706.5 kb) due to a better resolution of repeat regions. This assembly presented a high level of gene completeness, recovering 1,592 genes encoding secreted proteins involved in plant–pathogen interactions. Plasmopara viticola had a two-speed genome architecture, with secreted protein-encoding genes preferentially located in gene-sparse, repeat-rich regions and evolving rapidly, as indicated by pairwise dN/dS values. We also used short reads to assemble the genome of Plasmopara muralis, a closely related species infecting grape ivy (Parthenocissus tricuspidata). The lineage-specific proteins identified by comparative genomics analysis included a large proportion of RxLR cytoplasmic effectors and, more generally, genes with high dN/dS values. We identified 270 candidate genes under positive selection, including several genes encoding transporters and components of the RNA machinery potentially involved in host specialization. Finally, the Pl. viticola genome assembly generated here will allow the development of robust population genomics approaches for investigating the mechanisms involved in adaptation to biotic and abiotic selective pressures in this species.

scholarly journals Integrated Genomic Analysis of Sézary Syndrome

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Xin Mao ◽  
Tracy Chaplin ◽  
Bryan D. Young
Keyword(s):  
Copy Number ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Genomic Analysis ◽  
Gene Clusters ◽  
Sézary Syndrome ◽  
Sezary Syndrome ◽  
Snp Microarray ◽  
The Impact ◽  
Chromosome Regions

Sézary syndrome (SS) is a rare variant of primary cutaneous T-cell lymphoma. Little is known about the underlying pathogenesis of S. To address this issue, we used Affymetrix 10K SNP microarray to analyse 13 DNA samples isolated from 8 SS patients and qPCR with ABI TaqMan SNP genotyping assays for the validation of the SNP microarray results. In addition, we tested the impact of SNP loss of heterozygosity (LOH) identified in SS cases on the gene expression profiles of SS cases detected with Affymetrix GeneChip U133A. The results showed: (1) frequent SNP copy number change and LOH involving 1, 2p, 3, 4q, 5q, 6, 7p, 8, 9, 10, 11, 12q, 13, 14, 16q, 17, and 20, (2) reduced SNP copy number at FAT gene (4q35) in 75% of SS cases, and (3) the separation of all SS cases from normal control samples by SNP LOH gene clusters at chromosome regions of 9q31q34, 10p11q26, and 13q11q12. These findings provide some intriguing information for our current understanding of the molecular pathogenesis of this tumour and suggest the possibility of presence of functional SNP LOH in SS tumour cells.

scholarly journals Convolutional Neural Networks for Leaf Image-Based Plant Disease Classification

2019 ◽  
Vol 8 (4) ◽  
pp. 328
Author(s):  
Sachin B. Jadhav
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Convolutional Neural Network ◽  
Convolutional Neural Networks ◽  
Plant Diseases ◽  
Experimental Results ◽  
Disease Classification ◽  
Soybean Leaves ◽  
Soybean Diseases ◽  
Validation Strategy

<span lang="EN-US">Plant pathologists desire soft computing technology for accurate and reliable diagnosis of plant diseases. In this study, we propose an efficient soybean disease identification method based on a transfer learning approach by using a pre-trained convolutional neural network (CNN’s) such as AlexNet, GoogleNet, VGG16, ResNet101, and DensNet201. The proposed convolutional neural networks were trained using 1200 plant village image dataset of diseased and healthy soybean leaves, to identify three soybean diseases out of healthy leaves. Pre-trained CNN used to enable a fast and easy system implementation in practice. We used the five-fold cross-validation strategy to analyze the performance of networks. In this study, we used a pre-trained convolutional neural network as feature extractors and classifiers. The experimental results based on the proposed approach using pre-trained AlexNet, GoogleNet, VGG16, ResNet101, and DensNet201 networks achieve an accuracy of 95%, 96.4 %, 96.4 %, 92.1%, 93.6% respectively. The experimental results for the identification of soybean diseases indicated that the proposed networks model achieves the highest accuracy</span>

scholarly journals Chromosome-level de novo assembly of Coprinopsis cinerea A43mut B43mut pab1-1 #326 and genetic variant identification of mutants using Nanopore MinION sequencing

2020 ◽  
Author(s):  
Yichun Xie ◽  
Yiyi Zhong ◽  
Jinhui Chang ◽  
Hoi Shan Kwan
Keyword(s):  
Genome Assembly ◽  
Dna Isolation ◽  
Variant Calling ◽  
Genomic Analysis ◽  
Single Nucleotide ◽  
Sequencing Platform ◽  
Genomic Dna Isolation ◽  
Long Reads ◽  
Dna Isolation Protocol ◽  
Chromosome Level

AbstractThe homokaryotic Coprinopsis cinerea strain A43mut B43mut pab1-1 #326 is a widely used experimental model for developmental studies in mushroom-forming fungi. It can grow on defined artificial media and complete the whole lifecycle within two weeks. The mutations in mating type factors A and B result in the special feature of clamp formation and fruiting without mating. This feature allows investigations and manipulations with a homokaryotic genetic background. Current genome assembly of strain #326 was based on short-read sequencing data and was highly fragmented, leading to the bias in gene annotation and downstream analyses. Here, we report a chromosome-level genome assembly of strain #326. Oxford Nanopore Technology (ONT) MinION sequencing was used to get long reads. Illumina short reads was used to polish the sequences. A combined assembly yield 13 chromosomes and a mitochondrial genome as individual scaffolds. The assembly has 15,250 annotated genes with a high synteny with the C. cinerea strain Okayama-7 #130. This assembly has great improvement on contiguity and annotations. It is a suitable reference for further genomic studies, especially for the genetic, genomic and transcriptomic analyses in ONT long reads. Single nucleotide variants and structural variants in six mutagenized and cisplatin-screened mutants could be identified and validated. A 66 bp deletion in Ras GTPase-activating protein (RasGAP) was found in all mutants. To make a better use of ONT sequencing platform, we modified a high-molecular-weight genomic DNA isolation protocol based on magnetic beads for filamentous fungi. This study showed the use of MinION to construct a fungal reference genome and to perform downstream studies in an individual laboratory. An experimental workflow was proposed, from DNA isolation and whole genome sequencing, to genome assembly and variant calling. Our results provided solutions and parameters for fungal genomic analysis on MinION sequencing platform.HighlightA chromosome-level genome assembly of C. cinerea #326A fast and efficient high-molecular-weight fungal genomic DNA isolation protocolStructural variant and single nucleotide variant calling using Nanopore readsA series of solutions and reference parameters for fungal genomic analysis on MinION

scholarly journals Genome assembly of the JD17 soybean provides a new reference genome for Comparative genomics

2021 ◽  
Author(s):  
Xinxin Yi ◽  
Jing Liu ◽  
Shengcai Chen ◽  
Hao Wu ◽  
Min Liu ◽  
...  
Keyword(s):  
Nitrogen Fixation ◽  
Genome Assembly ◽  
Reference Genome ◽  
De Novo ◽  
Genomic Analysis ◽  
Comparative Genomic ◽  
High Quality ◽  
Genome Wide ◽  
A Genome ◽  
Cultivated Soybean

Cultivated soybean (Glycine max) is an important source for protein and oil. Many elite cultivars with different traits have been developed for different conditions. Each soybean strain has its own genetic diversity, and the availability of more high-quality soybean genomes can enhance comparative genomic analysis for identifying genetic underpinnings for its unique traits. In this study, we constructed a high-quality de novo assembly of an elite soybean cultivar Jidou 17 (JD17) with chromsome contiguity and high accuracy. We annotated 52,840 gene models and reconstructed 74,054 high-quality full-length transcripts. We performed a genome-wide comparative analysis based on the reference genome of JD17 with three published soybeans (WM82, ZH13 and W05) , which identified five large inversions and two large translocations specific to JD17, 20,984 - 46,912 PAVs spanning 13.1 - 46.9 Mb in size, and 5 - 53 large PAV clusters larger than 500kb. 1,695,741 - 3,664,629 SNPs and 446,689 - 800,489 Indels were identified and annotated between JD17 and them. Symbiotic nitrogen fixation (SNF) genes were identified and the effects from these variants were further evaluated. It was found that the coding sequences of 9 nitrogen fixation-related genes were greatly affected. The high-quality genome assembly of JD17 can serve as a valuable reference for soybean functional genomics research.

scholarly journals Draft Genome Sequence of Mesosutterella multiformis JCM 32464T, a Member of the Family Sutterellaceae, Isolated from Human Feces

2019 ◽  
Vol 8 (24) ◽  
Author(s):  
Nao Ikeyama ◽  
Moriya Ohkuma ◽  
Mitsuo Sakamoto
Keyword(s):  
Genome Sequence ◽  
Genome Assembly ◽  
Draft Genome ◽  
Genomic Analysis ◽  
Draft Genome Sequence ◽  
Human Feces ◽  
The Family ◽  
Metabolic Activities

Here, we report the draft genome sequence of Mesosutterella multiformis JCM 32464T, a new member of the family Sutterellaceae that was isolated from human feces. The genome assembly comprised 2,621,983 bp, with a G+C content of 56.9%. This genomic analysis will be useful for understanding the metabolic activities of this asaccharolytic bacterium.

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