scholarly journals RcTGA1 and glucosinolate biosynthesis pathway involvement in the defence of rose against the necrotrophic fungus Botrytis cinerea

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Penghua Gao ◽  
Hao Zhang ◽  
Huijun Yan ◽  
Qigang Wang ◽  
Bo Yan ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Gene Annotation ◽  
Infected Plant ◽  
Grey Mould ◽  
Cascade Reactions ◽  
Postharvest Quality ◽  
Rna Seq ◽  
Protein Activity ◽  
Phenylpropanoid Biosynthesis ◽  
And Cluster Analysis

Abstract Background Rose is an important economic crop in horticulture. However, its field growth and postharvest quality are negatively affected by grey mould disease caused by Botrytis c. However, it is unclear how rose plants defend themselves against this fungal pathogen. Here, we used transcriptomic, metabolomic and VIGS analyses to explore the mechanism of resistance to Botrytis c. Result In this study, a protein activity analysis revealed a significant increase in defence enzyme activities in infected plants. RNA-Seq of plants infected for 0 h, 36 h, 60 h and 72 h produced a total of 54 GB of clean reads. Among these reads, 3990, 5995 and 8683 differentially expressed genes (DEGs) were found in CK vs. T36, CK vs. T60 and CK vs. T72, respectively. Gene annotation and cluster analysis of the DEGs revealed a variety of defence responses to Botrytis c. infection, including resistance (R) proteins, MAPK cascade reactions, plant hormone signal transduction pathways, plant-pathogen interaction pathways, Ca2+ and disease resistance-related genes. qPCR verification showed the reliability of the transcriptome data. The PTRV2-RcTGA1-infected plant material showed improved susceptibility of rose to Botrytis c. A total of 635 metabolites were detected in all samples, which could be divided into 29 groups. Metabonomic data showed that a total of 59, 78 and 74 DEMs were obtained for T36, T60 and T72 (T36: Botrytis c. inoculated rose flowers at 36 h; T60: Botrytis c. inoculated rose flowers at 60 h; T72: Botrytis c. inoculated rose flowers at 72 h) compared to CK, respectively. A variety of secondary metabolites are related to biological disease resistance, including tannins, amino acids and derivatives, and alkaloids, among others; they were significantly increased and enriched in phenylpropanoid biosynthesis, glucosinolates and other disease resistance pathways. This study provides a theoretical basis for breeding new cultivars that are resistant to Botrytis c. Conclusion Fifty-four GB of clean reads were generated through RNA-Seq. R proteins, ROS signalling, Ca2+ signalling, MAPK signalling, and SA signalling were activated in the Old Blush response to Botrytis c. RcTGA1 positively regulates rose resistance to Botrytis c. A total of 635 metabolites were detected in all samples. DEMs were enriched in phenylpropanoid biosynthesis, glucosinolates and other disease resistance pathways.

scholarly journals Transcriptome Analysis of Apple Leaves in Response to Powdery Mildew (Podosphaera leucotricha) Infection

2019 ◽  
Vol 20 (9) ◽  
pp. 2326 ◽  
Author(s):  
Xiaomin Tian ◽  
Li Zhang ◽  
Shuaishuai Feng ◽  
Zhengyang Zhao ◽  
Xiping Wang ◽  
...  
Keyword(s):  
Powdery Mildew ◽  
Gene Annotation ◽  
Transcriptional Profiling ◽  
Molecular Genetic ◽  
Rna Seq ◽  
Podosphaera Leucotricha ◽  
Phenylpropanoid Biosynthesis ◽  
High Quality Sequence ◽  
Important Time ◽  
Plant Pathogen Interactions

Apple (Malus × domestica Borkh.) is one of the most important cultivated tree fruit crops worldwide. However, sustainable apple production is threatened by powdery mildew (PM) disease, which is caused by the obligate biotrophic fungus Podosphaera leucotricha. To gain insight into the molecular basis of the PM infection and disease progression, RNA-based transcriptional profiling (RNA-seq) was used to identify differentially expressed genes (DEGs) in apples following inoculation with P. leucotricha. Four RNA-seq libraries were constructed comprising a total of 214 Gb of high-quality sequence. 1177 DEGs (661 upregulated and 629 downregulated) have been identified according to the criteria of a ratio of infection/control fold change > 2, and a false discovery rate (FDR) < 0.001. The majority of DEGs (815) were detected 12 h after inoculation, suggesting that this is an important time point in the response of the PM infection. Gene annotation analysis revealed that DEGs were predominately associated with biological processes, phenylpropanoid biosynthesis, hormone signal transduction and plant-pathogen interactions. Genes activated by infection corresponded to transcription factors (e.g., AP2/ERF, MYB, WRKY and NAC) and synthesis of defense-related metabolites, including pathogenesis-related genes, glucosidase and dehydrin. Overall, the information obtained in this study enriches the resources available for research into the molecular-genetic mechanisms of the apple/powdery mildew interactions, and provides a theoretical basis for the development of new apple varieties with resistance to PM.

Comprehensive Analysis of Transcriptomics and Metabolomics between the Heads and Tails of Angelica Sinensis: Genes Related to Phenylpropanoid Biosynthesis Pathway

2020 ◽  
Vol 23 ◽  
Author(s):  
Jie Yang ◽  
Chi Zhang ◽  
Wei-Hong Li ◽  
Tian-Er Zhang ◽  
Guang-Zhong Fan ◽  
...  
Keyword(s):  
Ferulic Acid ◽  
Metabolic Regulation ◽  
Comprehensive Analysis ◽  
Angelica Sinensis ◽  
Rna Seq ◽  
Targeted Metabolomics ◽  
Kegg Pathways ◽  
Qrt Pcr ◽  
Phenylpropanoid Biosynthesis ◽  
Combined Strategy

Background:: In Traditional Chinese Medicine (TCM), the heads and tails of Angelica sinensis (Oliv.) Diels (AS) is used in treating different diseases due to their different pharmaceutical efficacies. The underline mechanisms, however, have not been fully explored. Objective:: Novel mechanisms responsible for the discrepant activities between AS heads and tails were explored by a combined strategy of transcriptomes and metabolomics. Method:: Six pairs of the heads and tails of AS roots were collected in Min County, China. Total RNA and metabolites, which were used for RNA-seq and untargeted metabolomics analysis, were respectively isolated from each AS sample (0.1 g) by Trizol and methanol reagent. Subsequently, differentially expressed genes (DEGs) and discrepant pharmaceutical metabolites were identified for comparing AS heads and tails. Key DEGs and metabolites were quantified by qRT-PCR and targeted metabolomics experiment. Results:: Comprehensive analysis of transcriptomes and metabolomics results suggested that five KEGG pathways with significant differences included 57 DEGs. Especially, fourteen DEGs and six key metabolites were relation to the metabolic regulation of Phenylpropanoid biosynthesis (PB) pathway. Results of qRT-PCR and targeted metabolomics indicated that higher levels of expression of crucial genes in PB pathway, such as PAL, CAD, COMT and peroxidase in the tail of AS were positively correlated with levels of ferulic acid-related metabolites. The average content of ferulic acid in tails (569.58162.39 nmol/g) was higher than those in the heads (168.73  67.30 nmol/g) (P˂0.01); Caffeic acid in tails (3.82  0.88 nmol/g) vs heads (1.37  0.41 nmol/g) (P˂0.01), and Cinnamic acid in tails (0.24  0.09 nmol/g) vs heads (0.14  0.02 nmol/g) (P˂0.05). Conclusion:: Our work demonstrated that overexpressed genes and accumulated metabolites derived from PB pathway might be responsible for the discrepant pharmaceutical efficacies between AS heads and tails.

scholarly journals Advancing clinical genomics and precision medicine with GVViZ: FAIR bioinformatics platform for variable gene-disease annotation, visualization, and expression analysis

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Zeeshan Ahmed ◽  
Eduard Gibert Renart ◽  
Saman Zeeshan ◽  
XinQi Dong
Keyword(s):  
Data Analysis ◽  
Patient Care ◽  
Expression Analysis ◽  
High Throughput ◽  
Gene Annotation ◽  
Next Generation Sequencing Data ◽  
Rna Seq ◽  
Sequencing Data ◽  
Complex Disorders ◽  
Transcriptomics Data

Abstract Background Genetic disposition is considered critical for identifying subjects at high risk for disease development. Investigating disease-causing and high and low expressed genes can support finding the root causes of uncertainties in patient care. However, independent and timely high-throughput next-generation sequencing data analysis is still a challenge for non-computational biologists and geneticists. Results In this manuscript, we present a findable, accessible, interactive, and reusable (FAIR) bioinformatics platform, i.e., GVViZ (visualizing genes with disease-causing variants). GVViZ is a user-friendly, cross-platform, and database application for RNA-seq-driven variable and complex gene-disease data annotation and expression analysis with a dynamic heat map visualization. GVViZ has the potential to find patterns across millions of features and extract actionable information, which can support the early detection of complex disorders and the development of new therapies for personalized patient care. The execution of GVViZ is based on a set of simple instructions that users without a computational background can follow to design and perform customized data analysis. It can assimilate patients’ transcriptomics data with the public, proprietary, and our in-house developed gene-disease databases to query, easily explore, and access information on gene annotation and classified disease phenotypes with greater visibility and customization. To test its performance and understand the clinical and scientific impact of GVViZ, we present GVViZ analysis for different chronic diseases and conditions, including Alzheimer’s disease, arthritis, asthma, diabetes mellitus, heart failure, hypertension, obesity, osteoporosis, and multiple cancer disorders. The results are visualized using GVViZ and can be exported as image (PNF/TIFF) and text (CSV) files that include gene names, Ensembl (ENSG) IDs, quantified abundances, expressed transcript lengths, and annotated oncology and non-oncology diseases. Conclusions We emphasize that automated and interactive visualization should be an indispensable component of modern RNA-seq analysis, which is currently not the case. However, experts in clinics and researchers in life sciences can use GVViZ to visualize and interpret the transcriptomics data, making it a powerful tool to study the dynamics of gene expression and regulation. Furthermore, with successful deployment in clinical settings, GVViZ has the potential to enable high-throughput correlations between patient diagnoses based on clinical and transcriptomics data.

scholarly journals A mutation in LacDWARF1 results in a GA-deficient dwarf phenotype in sponge gourd (Luffa acutangula)

2021 ◽  
Author(s):  
Gangjun Zhao ◽  
Caixia Luo ◽  
Jianning Luo ◽  
Junxing Li ◽  
Hao Gong ◽  
...  
Keyword(s):  
Gene Annotation ◽  
Recessive Gene ◽  
Genomic Region ◽  
Dwarf Mutant ◽  
Rna Seq ◽  
Dwarf Phenotype ◽  
Sponge Gourd ◽  
Response To Stress ◽  
Luffa Acutangula ◽  
Generation Sequencing

Abstract Key message A dwarfism gene LacDWARF1 was mapped by combined BSA-Seq and comparative genomics analyses to a 65.4 kb physical genomic region on chromosome 05. Abstract Dwarf architecture is one of the most important traits utilized in Cucurbitaceae breeding because it saves labor and increases the harvest index. To our knowledge, there has been no prior research about dwarfism in the sponge gourd. This study reports the first dwarf mutant WJ209 with a decrease in cell size and internodes. A genetic analysis revealed that the mutant phenotype was controlled by a single recessive gene, which is designated Lacdwarf1 (Lacd1). Combined with bulked segregate analysis and next-generation sequencing, we quickly mapped a 65.4 kb region on chromosome 5 using F2 segregation population with InDel and SNP polymorphism markers. Gene annotation revealed that Lac05g019500 encodes a gibberellin 3β-hydroxylase (GA3ox) that functions as the most likely candidate gene for Lacd1. DNA sequence analysis showed that there is an approximately 4 kb insertion in the first intron of Lac05g019500 in WJ209. Lac05g019500 is transcribed incorrectly in the dwarf mutant owing to the presence of the insertion. Moreover, the bioactive GAs decreased significantly in WJ209, and the dwarf phenotype could be restored by exogenous GA3 treatment, indicating that WJ209 is a GA-deficient mutant. All these results support the conclusion that Lac05g019500 is the Lacd1 gene. In addition, RNA-Seq revealed that many genes, including those related to plant hormones, cellular process, cell wall, membrane and response to stress, were significantly altered in WJ209 compared with the wild type. This study will aid in the use of molecular marker-assisted breeding in the dwarf sponge gourd.

scholarly journals Bioinformatic-Based Approaches for Disease-Resistance Gene Discovery in Plants

Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2259
Author(s):  
Andrea Fernandez-Gutierrez ◽  
Juan J. Gutierrez-Gonzalez
Keyword(s):  
Disease Resistance ◽  
Resistance Genes ◽  
Gene Annotation ◽  
Pathogen Resistance ◽  
Limiting Factors ◽  
Disease Resistance Gene ◽  
R Genes ◽  
Nucleotide Binding Sites ◽  
Bioinformatic Tools ◽  
Computer Based

Pathogens are among the most limiting factors for crop success and expansion. Thus, finding the underlying genetic cause of pathogen resistance is the main goal for plant geneticists. The activation of a plant’s immune system is mediated by the presence of specific receptors known as disease-resistance genes (R genes). Typical R genes encode functional immune receptors with nucleotide-binding sites (NBS) and leucine-rich repeat (LRR) domains, making the NBS-LRRs the largest family of plant resistance genes. Establishing host resistance is crucial for plant growth and crop yield but also for reducing pesticide use. In this regard, pyramiding R genes is thought to be the most ecologically friendly way to enhance the durability of resistance. To accomplish this, researchers must first identify the related genes, or linked markers, within the genomes. However, the duplicated nature, with the presence of frequent paralogues, and clustered characteristic of NLRs make them difficult to predict with the classic automatic gene annotation pipelines. In the last several years, efforts have been made to develop new methods leading to a proliferation of reports on cloned genes. Herein, we review the bioinformatic tools to assist the discovery of R genes in plants, focusing on well-established pipelines with an important computer-based component.

scholarly journals Maximizing prediction of orphan genes in assembled genomes

2019 ◽  
Author(s):  
Arun Seetharam ◽  
Urminder Singh ◽  
Jing Li ◽  
Priyanka Bhandary ◽  
Zeb Arendsee ◽  
...  
Keyword(s):  
Sequence Homology ◽  
Evolutionary History ◽  
Direct Evidence ◽  
Gene Annotation ◽  
Rna Seq ◽  
Orphan Genes ◽  
Orphan Gene ◽  
New Genes ◽  
Conserved Genes ◽  
Rapid Emergence

ABSTRACTThe evolutionary rapid emergence of new genes gives rise to “orphan genes” that share no sequence homology to genes in closely related genomes. These genes provide organisms with a reservoir of genetic elements to quickly respond to changing selection pressures. Gene annotation pipelines that combine ab initio machine-learning with sequence homology-based searches are efficient in identifying basal genes with a long evolutionary history. However, their ability to identify orphan genes and other young genes has not been systematically evaluated. Here, we classify the phylostrata of curated Arabidopsis thaliana genes and use these to assess the ability of two of the most prevalent annotation pipelines, MAKER and BRAKER, to predict orphans and other young genes. MAKER predictions are highly dependent on the RNA-Seq evidence, predicting between 11% and 60% of the orphan-genes and 95% to 98% of basal-genes in the annotated genome of Arabidopsis. In contrast, BRAKER consistently predicts 33% of orphan-genes and 98% of basal-genes. A less used method to identify genes is by directly aligning RNA-Seq data to the genome sequence. We present a Findable, Accessible, Interoperable and Reusable (FAIR) approach, called BIND, that mitigates the under-prediction of orphan genes. BIND combines BRAKER predictions with direct evidence-based inference of transcripts based on RNA-Seq alignments to the genome. BIND increases the number and accuracy of orphan gene predictions, identifying 68% of Araport11-annotated orphan genes and 99% of the conserved genes.

scholarly journals TrancriptomeReconstructoR, A Data-Driven Annotation of Complex Transcriptomes

2020 ◽  
Author(s):  
Maxim Ivanov ◽  
Albin Sandelin ◽  
Sebastian Marquardt
Keyword(s):  
De Novo ◽  
Gene Annotation ◽  
R Package ◽  
Sequence Information ◽  
Rna Seq ◽  
Sequencing Data ◽  
Gene Model ◽  
Preparation Methods ◽  
Downstream Analysis

Abstract Background: The quality of gene annotation determines the interpretation of results obtained in transcriptomic studies. The growing number of genome sequence information calls for experimental and computational pipelines for de novo transcriptome annotation. Ideally, gene and transcript models should be called from a limited set of key experimental data. Results: We developed TranscriptomeReconstructoR, an R package which implements a pipeline for automated transcriptome annotation. It relies on integrating features from independent and complementary datasets: i) full-length RNA-seq for detection of splicing patterns and ii) high-throughput 5' and 3' tag sequencing data for accurate definition of gene borders. The pipeline can also take a nascent RNA-seq dataset to supplement the called gene model with transient transcripts.We reconstructed de novo the transcriptional landscape of wild type Arabidopsis thaliana seedlings as a proof-of-principle. A comparison to the existing transcriptome annotations revealed that our gene model is more accurate and comprehensive than the two most commonly used community gene models, TAIR10 and Araport11. In particular, we identify thousands of transient transcripts missing from the existing annotations. Our new annotation promises to improve the quality of A.thaliana genome research.Conclusions: Our proof-of-concept data suggest a cost-efficient strategy for rapid and accurate annotation of complex eukaryotic transcriptomes. We combine the choice of library preparation methods and sequencing platforms with the dedicated computational pipeline implemented in the TranscriptomeReconstructoR package. The pipeline only requires prior knowledge on the reference genomic DNA sequence, but not the transcriptome. The package seamlessly integrates with Bioconductor packages for downstream analysis.

scholarly journals Transcriptome Analysis of Rice Roots in Response to Root-Knot Nematode Infection

2020 ◽  
Vol 21 (3) ◽  
pp. 848
Author(s):  
Yuan Zhou ◽  
Di Zhao ◽  
Li Shuang ◽  
Dongxue Xiao ◽  
Yuanhu Xuan ◽  
...  
Keyword(s):  
Transcriptome Analysis ◽  
Gene Annotation ◽  
Oryza Sativa L ◽  
Development Stage ◽  
Post Inoculation ◽  
Rna Seq ◽  
Wild Type ◽  
Root Knot Nematode ◽  
Rice Roots ◽  
Invasion Stage

Meloidogyne incognita and Meloidogyne graminicola are root-knot nematodes (RKNs) infecting rice (Oryza sativa L.) roots and severely decreasing yield, whose mechanisms of action remain unclear. We investigated RKN invasion and development in rice roots through RNA-seq transcriptome analysis. The results showed that 952 and 647 genes were differently expressed after 6 (invasion stage) and 18 (development stage) days post inoculation, respectively. Gene annotation showed that the differentially expressed genes were classified into diverse metabolic and stress response categories. Furthermore, phytohormone, transcription factor, redox signaling, and defense response pathways were enriched upon RKN infection. RNA-seq validation using qRT-PCR confirmed that CBL-interacting protein kinase (CIPK) genes (CIPK5, 8, 9, 11, 14, 23, 24, and 31) as well as brassinosteroid (BR)-related genes (OsBAK1, OsBRI1, D2, and D11) were altered by RKN infection. Analysis of the CIPK9 mutant and overexpressor indicated that the RKN populations were smaller in cipk9 and larger in CIPK9 OX, while more galls were produced in CIPK9 OX plant roots than the in wild-type roots. Significantly fewer numbers of second-stage infective juveniles (J2s) were observed in the plants expressing the BR biosynthesis gene D2 mutant and the BR receptor BRI1 activation-tagged mutant (bri1-D), and fewer galls were observed in bri1-D roots than in wild-type roots. The roots of plants expressing the regulator of ethylene signaling ERS1 (ethylene response sensor 1) mutant contained higher numbers of J2s and developed more galls compared with wild-type roots, suggesting that these signals function in RKN invasion or development. Our findings broaden our understanding of rice responses to RKN invasion and provide useful information for further research on RKN defense mechanisms.

scholarly journals Identification and characterization of genes frequently responsive to Xanthomonas oryzae pv. oryzae and Magnaporthe oryzae infections in rice

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Weiwen Kong ◽  
Li Ding ◽  
Xue Xia
Keyword(s):  
Disease Resistance ◽  
Magnaporthe Oryzae ◽  
Enrichment Analysis ◽  
Defense Responses ◽  
Resistance Mechanisms ◽  
Xanthomonas Oryzae ◽  
Transcriptional Reprogramming ◽  
Go Enrichment ◽  
Phenylpropanoid Biosynthesis ◽  
Rice Disease

Abstract Background Disease resistance is an important factor that impacts rice production. However, the mechanisms underlying rice disease resistance remain to be elucidated. Results Here, we show that a robust set of genes has been defined in rice response to the infections of Xanthomonas oryzae pv. oryzae (Xoo) and Magnaporthe oryzae (Mor). We conducted a comprehensive analysis of the available microarray data from a variety of rice samples with inoculation of Xoo and Mor. A set of 12,932 genes was identified to be regulated by Xoo and another set of 2709 Mor-regulated genes was determined. GO enrichment analysis of the regulated genes by Xoo or Mor suggested mitochondrion may be an arena for the up-regulated genes and chloroplast be another for the down-regulated genes by Xoo or Mor. Cytokinin-related processes were most frequently repressed by Xoo, while processes relevant to jasmonic acid and abscisic acid were most frequently activated by Xoo and Mor. Among genes responsive to Xoo and Mor, defense responses and diverse signaling pathways were the most frequently enriched resistance mechanisms. InterPro annotation showed the zinc finger domain family, WRKY proteins, and Myb domain proteins were the most significant transcription factors regulated by Xoo and Mor. KEGG analysis demonstrated pathways including ‘phenylpropanoid biosynthesis’, ‘biosynthesis of antibiotics’, ‘phenylalanine metabolism’, and ‘biosynthesis of secondary metabolites’ were most frequently triggered by Xoo and Mor, whereas ‘circadian rhythm-plant’ was the most frequent pathway repressed by Xoo and Mor. Conclusions The genes identified here represent a robust set of genes responsive to the infections of Xoo and Mor, which provides an overview of transcriptional reprogramming during rice defense against Xoo and Mor infections. Our study would be helpful in understanding the mechanisms of rice disease resistance.

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