scholarly journals The Cotton Lignin Biosynthetic Gene Gh4CL30 Regulates Lignification and Phenolic Content and Contributes to Verticillium Wilt Resistance

2021 ◽  
pp. MPMI-03-20-0071
Author(s):  
Xian-Peng Xiong ◽  
Shi-Chao Sun ◽  
Qian-Hao Zhu ◽  
Xin-Yu Zhang ◽  
Yan-Jun Li ◽  
...  
Keyword(s):  
Verticillium Wilt ◽  
Expression Profiles ◽  
Lignin Biosynthesis ◽  
Biosynthesis Pathway ◽  
Virus Induced Gene Silencing ◽  
Cotton Production ◽  
Hub Genes ◽  
Time Points ◽  
Before And After ◽  
Open Access Article

Verticillium wilt is a vascular disease causing tremendous damage to cotton production worldwide. However, our knowledge of the mechanisms of cotton resistance or susceptibility to this disease is very limited. In this study, we compared the defense transcriptomes of cotton (Gossypium hirsutum) cultivars Shidalukang 1 (Verticillium dahliae resistant, HR) and Junmian 1 (V. dahliae susceptible, HS) before and after V. dahliae infection, identified hub genes of the network associated with responses to V. dahliae infection, and functionally characterized one of the hub genes involved in biosynthesis of lignin and phenolics. We identified 6,831 differentially expressed genes (DEGs) between the basal transcriptomes of HR and HS; 3,685 and 3,239 of these DEGs were induced in HR and HS, respectively, at different time points after V. dahliae infection. KEGG pathway analysis indicated that DEGs were enriched for genes involved in lignin biosynthesis. In all, 23 hub genes were identified based on a weighted gene coexpression network analysis of the 6,831 DEGs and their expression profiles at different time points after V. dahliae infection. Knockdown of Gh4CL30, one of the hub genes related to the lignin biosynthesis pathway, by virus-induced gene silencing, led to a decreased content of flavonoids, lignin, and S monomer but an increased content of G monomer, G/S lignin monomer, caffeic acid, and ferulic acid, and enhanced cotton resistance to V. dahliae. These results suggest that Gh4CL30 is a key gene modulating the outputs of different branches of the lignin biosynthesis pathway, and provide new insights into cotton resistance to V. dahliae. [Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

scholarly journals Rapid Mining of Candidate Genes for Verticillium Wilt Resistance in Cotton Based on BSA-Seq Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Yanli Cui ◽  
Qun Ge ◽  
Pei Zhao ◽  
Wei Chen ◽  
Xiaohui Sang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Verticillium Wilt ◽  
Molecular Breeding ◽  
Fiber Quality ◽  
Transcriptome Data ◽  
Virus Induced Gene Silencing ◽  
Cotton Production ◽  
Genomic Information ◽  
Important Cash Crop ◽  
Candidate Loci

Cotton is a globally important cash crop. Verticillium wilt (VW) is commonly known as “cancer” of cotton and causes serious loss of yield and fiber quality in cotton production around the world. Here, we performed a BSA-seq analysis using an F2:3 segregation population to identify the candidate loci involved in VW resistance. Two QTLs (qvw-D05-1 and qvw-D05-2) related to VW resistance in cotton were identified using two resistant/susceptible bulks from the F2 segregation population constructed by crossing the resistant cultivar ZZM2 with the susceptible cultivar J11. A total of 30stop-lost SNPs and 42 stop-gained SNPs, which included 17 genes, were screened in the qvw-D05-2 region by SnpEff analysis. Further analysis of the transcriptome data and qRT-PCR revealed that the expression level of Ghir_D05G037630 (designated as GhDRP) varied significantly at certain time points after infection with V. dahliae. The virus-induced gene silencing of GhDRP resulted in higher susceptibility of the plants to V. dahliae than the control, suggesting that GhDRP is involved in the resistance to V. dahlia infection. This study provides a method for rapid mining of quantitative trait loci and screening of candidate genes, as well as enriches the genomic information and gene resources for the molecular breeding of disease resistance in cotton.

scholarly journals Comparative RNA-Sequence Transcriptome Analysis of Phenolic Acid Metabolism in Salvia miltiorrhiza, a Traditional Chinese Medicine Model Plant

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Zhenqiao Song ◽  
Linlin Guo ◽  
Tian Liu ◽  
Caicai Lin ◽  
Jianhua Wang ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Phenolic Acid ◽  
Expression Profiles ◽  
Salvia Miltiorrhiza ◽  
Lignin Biosynthesis ◽  
Biosynthesis Pathway ◽  
Acid Biosynthesis ◽  
The Core ◽  
Phenylpropanoid Biosynthesis

Salvia miltiorrhiza Bunge is an important traditional Chinese medicine (TCM). In this study, two S. miltiorrhiza genotypes (BH18 and ZH23) with different phenolic acid concentrations were used for de novo RNA sequencing (RNA-seq). A total of 170,787 transcripts and 56,216 unigenes were obtained. There were 670 differentially expressed genes (DEGs) identified between BH18 and ZH23, 250 of which were upregulated in ZH23, with genes involved in the phenylpropanoid biosynthesis pathway being the most upregulated genes. Nine genes involved in the lignin biosynthesis pathway were upregulated in BH18 and thus result in higher lignin content in BH18. However, expression profiles of most genes involved in the core common upstream phenylpropanoid biosynthesis pathway were higher in ZH23 than that in BH18. These results indicated that genes involved in the core common upstream phenylpropanoid biosynthesis pathway might play an important role in downstream secondary metabolism and demonstrated that lignin biosynthesis was a putative partially competing pathway with phenolic acid biosynthesis. The results of this study expanded our understanding of the regulation of phenolic acid biosynthesis in S. miltiorrhiza.

scholarly journals Transcriptome Analysis and RNA Interference Reveal GhGDH2 Regulating Cotton Resistance to Verticillium Wilt by JA and SA Signaling Pathways

2021 ◽  
Vol 12 ◽  
Author(s):  
Xian-Peng Xiong ◽  
Shi-Chao Sun ◽  
Qian-Hao Zhu ◽  
Xin-Yu Zhang ◽  
Feng Liu ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Verticillium Wilt ◽  
Molecular Mechanisms ◽  
Functional Characterization ◽  
Lignin Biosynthesis ◽  
Differentially Expressed ◽  
Multiple Time ◽  
Virus Induced Gene Silencing ◽  
Network Modules ◽  
Multiple Time Points

Verticillium wilt, caused by Verticillium dahliae, is one of the most damaging and widespread soil-borne cotton diseases. The molecular mechanisms underlying the cotton defense against V. dahliae remain largely elusive. Here, we compared the transcriptional differences between Upland cotton cultivars: one highly resistant (HR; Shidalukang 1) and one highly susceptible (HS; Junmian 1). This was done at multiple time points after V. dahliae inoculation, which identified 2010 and 1275 differentially expressed genes (DEGs) in HR and HS, respectively. Plant hormone signal transduction-related genes were enriched in HR, whereas genes related to lignin biosynthesis were enriched in both HR and HS. Weighted gene co-expression network analysis (WGCNA) using the 2868 non-redundant genes differentially expressed between the V. dahliae infected and uninfected samples in HR or HS identified 10 different gene network modules and 22 hub genes with a potential role in regulating cotton defense against V. dahliae infection. GhGDH2, encoding glutamate dehydrogenase (GDH), was selected for functional characterization. Suppressing the expression level of GhGDH2 by virus-induced gene silencing (VIGS) in HS led to inhibition of the salicylic acid (SA) biosynthesis/signaling pathways and activation of the jasmonic acid (JA) biosynthesis/signaling pathways, which resulted in an increase of 42.1% JA content and a reduction of 78.9% SA content in cotton roots, and consequently enhanced V. dahliae resistance. Our finding provides new insights on the molecular mechanisms of cotton resistance to V. dahliae infection and candidate genes for breeding V. dahliae resistance cotton cultivars by genetic modification.

scholarly journals The SlHB8 Acts as a Negative Regulator in Stem Development and Lignin Biosynthesis

2021 ◽  
Vol 22 (24) ◽  
pp. 13343
Author(s):  
Xiaojuan Liu ◽  
Caiyu Wu ◽  
Deding Su ◽  
Yang Yang ◽  
Zhiqiang Xian ◽  
...  
Keyword(s):  
Leucine Zipper ◽  
Expression Profiles ◽  
Lignin Biosynthesis ◽  
Stem Diameter ◽  
Negative Regulator ◽  
Biosynthesis Pathway ◽  
Loss Of Function ◽  
Class Iii ◽  
Cell Layers ◽  
Stem Development

The stem is an important organ in supporting plant body, transporting nutrients and communicating signals for plant growing. However, studies on the regulation of stem development in tomato are rather limited. In our study, we demonstrated that SlHB8 negatively regulated tomato stem development. SlHB8 belongs to homeo domain-leucine zipper Class III gene family transcription factors and expressed in all the organs examined including root, stem, leaves, flower, and fruit. Among these tissues, SlHB8 showed stable high expression level during tomato stem development. Overexpression of SlHB8 gene decreased stem diameter with inhibited xylem width and xylem cell layers, while loss of function of SlHB8gene increased the stem diameter and xylem width. The contents of lignin were decreased both in leaves and stems of SlHB8 overexpression plants. RNA-seq analysis on the stems of wild type and SlHB8 transgenic plants showed that the 116 DEGs (differential expressed genes) with reversible expression profiles in SlHB8-ox and SlHB8-cr plants were significantly enriched in the phenylpropanoid biosynthesis pathway and plant-pathogen pathway which were related to lignin biosynthesis and disease resistance. Meanwhile, the key genes involved in the lignin biosynthesis pathway such as SlCCR (cinnamoyl-CoA reductase), SlCYP73A14/C4H (cinnamate 4-hydroxylase), SlC3H (coumarate 3-hydroxylase) and SlCAD (cinnamoyl alcohol dehydrogenase) were down-regulated in both stem and leaves of SlHB8 overexpression plants, indicating a negative regulatory role of SlHB8 in the lignin biosynthesis and stem development.

Predicting Hub Genes of Glioblastomas Based on Support Vector Machine Combined with CFS algorithms

2020 ◽  
Vol 15 ◽  
Author(s):  
Chun Qiu ◽  
Sai Li ◽  
Shenghui Yang ◽  
Lin Wang ◽  
Aihui Zeng ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Expression Profiles ◽  
Independent Set ◽  
Classification Model ◽  
Support Vector ◽  
Feature Subset ◽  
Hub Genes ◽  
Effective Prevention ◽  
Key Genes ◽  
Control Samples

Aim: To search the genes related to the mechanisms of the occurrence of glioma and to try to build a prediction model for glioblastomas. Background: The morbidity and mortality of glioblastomas are very high, which seriously endangers human health. At present, the goals of many investigations on gliomas are mainly to understand the cause and mechanism of these tumors at the molecular level and to explore clinical diagnosis and treatment methods. However, there is no effective early diagnosis method for this disease, and there are no effective prevention, diagnosis or treatment measures. Methods: First, the gene expression profiles derived from GEO were downloaded. Then, differentially expressed genes (DEGs) in the disease samples and the control samples were identified. After that, GO and KEGG enrichment analyses of DEGs were performed by DAVID. Furthermore, the correlation-based feature subset (CFS) method was applied to the selection of key DEGs. In addition, the classification model between the glioblastoma samples and the controls was built by an Support Vector Machine (SVM) based on selected key genes. Results and Discussion: Thirty-six DEGs, including 17 upregulated and 19 downregulated genes, were selected as the feature genes to build the classification model between the glioma samples and the control samples by the CFS method. The accuracy of the classification model by using a 10-fold cross-validation test and independent set test was 76.25% and 70.3%, respectively. In addition, PPP2R2B and CYBB can also be found in the top 5 hub genes screened by the protein– protein interaction (PPI) network. Conclusions: This study indicated that the CFS method is a useful tool to identify key genes in glioblastomas. In addition, we also predicted that genes such as PPP2R2B and CYBB might be potential biomarkers for the diagnosis of glioblastomas.

scholarly journals Transcriptomal dissection of soybean circadian rhythmicity in two geographically, phenotypically and genetically distinct cultivars

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanlei Yue ◽  
Ze Jiang ◽  
Enoch Sapey ◽  
Tingting Wu ◽  
Shi Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Circadian Clock ◽  
Chromosome Structure ◽  
Clock Genes ◽  
Expression Profiles ◽  
Circadian Rhythmicity ◽  
Rna Seq ◽  
Night Time ◽  
Time Points ◽  
Circadian Clock Genes

Abstract Background In soybean, some circadian clock genes have been identified as loci for maturity traits. However, the effects of these genes on soybean circadian rhythmicity and their impacts on maturity are unclear. Results We used two geographically, phenotypically and genetically distinct cultivars, conventional juvenile Zhonghuang 24 (with functional J/GmELF3a, a homolog of the circadian clock indispensable component EARLY FLOWERING 3) and long juvenile Huaxia 3 (with dysfunctional j/Gmelf3a) to dissect the soybean circadian clock with time-series transcriptomal RNA-Seq analysis of unifoliate leaves on a day scale. The results showed that several known circadian clock components, including RVE1, GI, LUX and TOC1, phase differently in soybean than in Arabidopsis, demonstrating that the soybean circadian clock is obviously different from the canonical model in Arabidopsis. In contrast to the observation that ELF3 dysfunction results in clock arrhythmia in Arabidopsis, the circadian clock is conserved in soybean regardless of the functional status of J/GmELF3a. Soybean exhibits a circadian rhythmicity in both gene expression and alternative splicing. Genes can be grouped into six clusters, C1-C6, with different expression profiles. Many more genes are grouped into the night clusters (C4-C6) than in the day cluster (C2), showing that night is essential for gene expression and regulation. Moreover, soybean chromosomes are activated with a circadian rhythmicity, indicating that high-order chromosome structure might impact circadian rhythmicity. Interestingly, night time points were clustered in one group, while day time points were separated into two groups, morning and afternoon, demonstrating that morning and afternoon are representative of different environments for soybean growth and development. However, no genes were consistently differentially expressed over different time-points, indicating that it is necessary to perform a circadian rhythmicity analysis to more thoroughly dissect the function of a gene. Moreover, the analysis of the circadian rhythmicity of the GmFT family showed that GmELF3a might phase- and amplitude-modulate the GmFT family to regulate the juvenility and maturity traits of soybean. Conclusions These results and the resultant RNA-seq data should be helpful in understanding the soybean circadian clock and elucidating the connection between the circadian clock and soybean maturity.

scholarly journals The landscape of gene co-expression modules correlating with prognostic genetic abnormalities in AML

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Chao Guo ◽  
Ya-yue Gao ◽  
Qian-qian Ju ◽  
Chun-xia Zhang ◽  
Ming Gong ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Prediction Model ◽  
Hox Genes ◽  
Expression Profiles ◽  
Penalized Regression ◽  
Diagnostic Utility ◽  
Lasso Regression ◽  
Hub Genes ◽  
Npm1 Mutation ◽  
Genetic Abnormalities

Abstract Background The heterogenous cytogenetic and molecular variations were harbored by AML patients, some of which are related with AML pathogenesis and clinical outcomes. We aimed to uncover the intrinsic expression profiles correlating with prognostic genetic abnormalities by WGCNA. Methods We downloaded the clinical and expression dataset from BeatAML, TCGA and GEO database. Using R (version 4.0.2) and ‘WGCNA’ package, the co-expression modules correlating with the ELN2017 prognostic markers were identified (R2 ≥ 0.4, p < 0.01). ORA detected the enriched pathways for the key co-expression modules. The patients in TCGA cohort were randomly assigned into the training set (50%) and testing set (50%). The LASSO penalized regression analysis was employed to build the prediction model, fitting OS to the expression level of hub genes by ‘glmnet’ package. Then the testing and 2 independent validation sets (GSE12417 and GSE37642) were used to validate the diagnostic utility and accuracy of the model. Results A total of 37 gene co-expression modules and 973 hub genes were identified for the BeatAML cohort. We found that 3 modules were significantly correlated with genetic markers (the ‘lightyellow’ module for NPM1 mutation, the ‘saddlebrown’ module for RUNX1 mutation, the ‘lightgreen’ module for TP53 mutation). ORA revealed that the ‘lightyellow’ module was mainly enriched in DNA-binding transcription factor activity and activation of HOX genes. The ‘saddlebrown’ module was enriched in immune response process. And the ‘lightgreen’ module was predominantly enriched in mitosis cell cycle process. The LASSO- regression analysis identified 6 genes (NFKB2, NEK9, HOXA7, APRC5L, FAM30A and LOC105371592) with non-zero coefficients. The risk score generated from the 6-gene model, was associated with ELN2017 risk stratification, relapsed disease, and prior MDS history. The 5-year AUC for the model was 0.822 and 0.824 in the training and testing sets, respectively. Moreover, the diagnostic utility of the model was robust when it was employed in 2 validation sets (5-year AUC 0.743–0.79). Conclusions We established the co-expression network signature correlated with the ELN2017 recommended prognostic genetic abnormalities in AML. The 6-gene prediction model for AML survival was developed and validated by multiple datasets.

scholarly journals Dynamic characteristics and functional analysis provide new insights into long non-coding RNA responsive to Verticillium dahliae infection in Gossypium hirsutum

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guoning Wang ◽  
Xingfen Wang ◽  
Yan Zhang ◽  
Jun Yang ◽  
Zhikun Li ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Verticillium Wilt ◽  
Dynamic Characteristics ◽  
Target Genes ◽  
Acid Metabolism ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Alpha Linolenic Acid ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Abstract Background Verticillium wilt is a widespread and destructive disease, which causes serious loss of cotton yield and quality. Long non-coding RNA (lncRNA) is involved in many biological processes, such as plant disease resistance response, through a variety of regulatory mechanisms, but their possible roles in cotton against Verticillium dahliae infection remain largely unclear. Results Here, we measured the transcriptome of resistant G. hirsutum following infection by V. dahliae and 4277 differentially expressed lncRNAs (delncRNAs) were identified. Localization and abundance analysis revealed that delncRNAs were biased distribution on chromosomes. We explored the dynamic characteristics of disease resistance related lncRNAs in chromosome distribution, induced expression profiles, biological function, and these lncRNAs were divided into three categories according to their induced expression profiles. For the delncRNAs, 687 cis-acting pairs and 14,600 trans-acting pairs of lncRNA-mRNA were identified, which indicated that trans-acting was the main way of Verticillium wilt resistance-associated lncRNAs regulating target mRNAs in cotton. Analyzing the regulation pattern of delncRNAs revealed that cis-acting and trans-acting lncRNAs had different ways to influence target genes. Gene Ontology (GO) enrichment analysis revealed that the regulatory function of delncRNAs participated significantly in stimulus response process, kinase activity and plasma membrane components. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that delncRNAs participated in some important disease resistance pathways, such as plant-pathogen interaction, alpha-linolenic acid metabolism and plant hormone signal transduction. Additionally, 21 delncRNAs and 10 target genes were identified as being involved in alpha-linolenic acid metabolism associated with the biosynthesis of jasmonic acid (JA). Subsequently, we found that GhlncLOX3 might regulate resistance to V. dahliae through modulating the expression of GhLOX3 implicated in JA biosynthesis. Further functional analysis showed that GhlncLOX3-silenced seedlings displayed a reduced resistance to V. dahliae, with down-regulated expression of GhLOX3 and decreased content of JA. Conclusion This study shows the dynamic characteristics of delncRNAs in multiaspect, and suggests that GhlncLOX3-GhLOX3-JA network participates in response to V. dahliae invasion. Our results provide novel insights for genetic improvement of Verticillium wilt resistance in cotton using lncRNAs.

scholarly journals Bayesian approach for predicting responses to therapy from high-dimensional time-course gene expression profiles

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Arika Fukushima ◽  
Masahiro Sugimoto ◽  
Satoru Hiwa ◽  
Tomoyuki Hiroyasu
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Response To Therapy ◽  
Hcv Infection ◽  
Entire Treatment Period ◽  
Time Points ◽  
Time Course Data ◽  
Conventional Methods

Abstract Background Historical and updated information provided by time-course data collected during an entire treatment period proves to be more useful than information provided by single-point data. Accurate predictions made using time-course data on multiple biomarkers that indicate a patient’s response to therapy contribute positively to the decision-making process associated with designing effective treatment programs for various diseases. Therefore, the development of prediction methods incorporating time-course data on multiple markers is necessary. Results We proposed new methods that may be used for prediction and gene selection via time-course gene expression profiles. Our prediction method consolidated multiple probabilities calculated using gene expression profiles collected over a series of time points to predict therapy response. Using two data sets collected from patients with hepatitis C virus (HCV) infection and multiple sclerosis (MS), we performed numerical experiments that predicted response to therapy and evaluated their accuracies. Our methods were more accurate than conventional methods and successfully selected genes, the functions of which were associated with the pathology of HCV infection and MS. Conclusions The proposed method accurately predicted response to therapy using data at multiple time points. It showed higher accuracies at early time points compared to those of conventional methods. Furthermore, this method successfully selected genes that were directly associated with diseases.

scholarly journals Genome-Wide Analysis and Characterization of the Aux/IAA Family Genes Related to Floral Scent Formation in Hedychium coronarium

2019 ◽  
Vol 20 (13) ◽  
pp. 3235 ◽  
Author(s):  
Yanguo Ke ◽  
Farhat Abbas ◽  
Yiwei Zhou ◽  
Rangcai Yu ◽  
Yuechong Yue ◽  
...  
Keyword(s):  
Gene Family ◽  
Developmental Stages ◽  
Floral Scent ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Regulatory Elements ◽  
Virus Induced Gene Silencing ◽  
Cut Flowers ◽  
Flower Opening ◽  
Hedychium Coronarium

Auxin plays a key role in different plant growth and development processes, including flower opening and development. The perception and signaling of auxin depend on the cooperative action of various components, among which auxin/indole-3-acetic acid (Aux/IAA) proteins play an imperative role. In a recent study, the entire Aux/IAA gene family was identified and comprehensively analyzed in Hedychium coronarium, a scented species used as an ornamental plant for cut flowers. Phylogenetic analysis showed that the Aux/IAA gene family in H. coronarium is slightly contracted compared to Arabidopsis, with low levels of non-canonical proteins. Sequence analysis of promoters showed numerous cis-regulatory elements related to various phytohormones. HcIAA genes showed distinct expression patterns in different tissues and flower developmental stages, and some HcIAA genes showed significant responses to auxin and ethylene, indicating that Aux/IAAs may play an important role in linking hormone signaling pathways. Based on the expression profiles, HcIAA2, HcIAA4, HcIAA6 and HcIAA12, were selected as candidate genes and HcIAA2 and HcIAA4 were screened for further characterization. Downregulation of HcIAA2 and HcIAA4 by virus-induced gene silencing in H. coronarium flowers modified the total volatile compound content, suggesting that HcIAA2 and HcIAA4 play important roles in H. coronarium floral scent formation. The results presented here will provide insights into the putative roles of HcIAA genes and will assist the elucidation of their precise roles during floral scent formation.

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