scholarly journals Transcriptome analysis reveals mechanism of early ripening in Kyoho grape with hydrogen peroxide treatment

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Da-Long Guo ◽  
Zhen-Guang Wang ◽  
Mao-Song Pei ◽  
Li-Li Guo ◽  
Yi-He Yu
Keyword(s):  
Cell Wall ◽  
Rna Sequencing ◽  
Time Course ◽  
Developmental Stages ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
Sequencing Analysis ◽  
Physiological Level ◽  
Early Ripening ◽  
And Control

Abstract Background In a previous study, the early ripening of Kyoho grape following H2O2 treatment was explored at the physiological level, but the mechanism by which H2O2 promotes ripening at the molecular level is unclear. To reveal the molecular mechanism, RNA-sequencing analysis was conducted on the different developmental stages of Kyoho berry treated with H2O2. Results In the comparison of treatment and control groups, 406 genes were up-regulated and 683 were down-regulated. Time course sequencing (TCseq) analysis showed that the expression patterns of most of the genes were similar between the treatment and control, except for some genes related to chlorophyll binding and photosynthesis. Differential expression analysis and the weighted gene co-expression network were used to screen significantly differentially expressed genes and hub genes associated with oxidative stress (heat shock protein, HSP), cell wall deacetylation (GDSL esterase/lipase, GDSL), cell wall degradation (xyloglucan endotransglucosylase/ hydrolase, XTH), and photosynthesis (chlorophyll a-b binding protein, CAB1). Gene expression was verified with RT-qPCR, and the results were largely consistent with those of RNA sequencing. Conclusions The RNA-sequencing analysis indicated that H2O2 treatment promoted the early ripening of Kyoho berry by affecting the expression levels of HSP, GDSL, XTH, and CAB1 and- photosynthesis- pathways.

Abstract W P73: Feasibility and Preliminary Results of Whole Blood RNA-Sequencing Analysis in Patients With Intracranial Aneurysms

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
Blake Haas ◽  
Nestor R Gonzalez ◽  
Elina Nikkola ◽  
Mark Connolly ◽  
William Hsu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Rna Sequencing ◽  
Whole Blood ◽  
Intracranial Aneurysms ◽  
Small Sample Size ◽  
Expression Patterns ◽  
Small Sample ◽  
Cellular Respiration ◽  
Sequencing Analysis

Introduction: Intracranial aneurysms (IA) growth and rupture have been associated with chronic remodeling of the arterial wall. However, the pathobiology of this process remains poorly understood. The objective of the present study was to evaluate the feasibility of analyzing gene expression patterns in peripheral blood of patients with ruptured and unruptured saccular IAs. Materials and Methods: We analyzed human whole blood transcriptomes by performing paired-end, 100 bp RNA-sequencing (RNAseq) using the Illumina platform. We used STAR to align reads to the genome, HTSeq to count reads, and DESeq to normalize counts across samples. Self-reported patient information was used to correct expression values for ancestry, age, and sex. We utilized weighted gene co-expression network analysis (WGCNA) to identify gene expression network modules associated with IA size and rupture. The DAVID tool was employed to search for Gene Ontology enrichment in relevant modules. Results: Samples from 12 patients (9 females, age 57.6 +/-12) with IAs were analyzed. Four had ruptured aneurysms. RNA isolation and application of the methodology described above was successful in all samples. Although the small sample size prevents us from drawing definite conclusions, we observed promising novel co-expression networks for IAs: WCGNA analysis showed down-regulation of two transcript modules associated with ruptured IA status (r=-0.78, p=0.008 and r=-0.77, p=0.009), and up-regulation of two modules associated with aneurysm size (r=0.86, p=0.002 and r=0.9, p=4e-04), respectively. DAVID analyses showed that genes upregulated in an IA size-associated module were enriched with genes involved in cellular respiration and translation, while genes involved in transcription were down-regulated in a module associated with ruptured IAs. Conclusions: Whole blood RNAseq analysis is a feasible tool to capture transcriptome dynamics and achieve a better understanding of the pathophysiology of IAs. Further longitudinal studies of patients with IAs using network analysis are justified.

scholarly journals Differential Expression Analysis Using A Model-Based Gene Clustering Algorithm for RNA-Seq Data

2020 ◽  
Author(s):  
Takayuki Osabe ◽  
Kentaro Shimizu ◽  
Koji Kadota
Keyword(s):  
Differential Expression ◽  
Time Course ◽  
Clustering Algorithm ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
Real Data ◽  
Gene Clustering ◽  
Rna Seq ◽  
Model Based ◽  
Group Data

Abstract Background RNA-seq is a tool for measuring gene expression and is commonly used to identify differentially expressed genes (DEGs). Gene clustering is used to classify DEGs with similar expression patterns for the subsequent analyses of data from experiments such as time-courses or multi-group comparisons. However, gene clustering has rarely been used for analyzing simple two-group data or differential expression (DE). In this study, we report a model-based clustering algorithm, MBCluster.Seq, that can be implemented using an R package for DE analysis.Results The input data originally used by MBCluster.Seq is DEGs, and the proposed method (called MBCdeg) uses all genes for the analysis. The method uses posterior probabilities of genes assigned to a cluster displaying non-DEG pattern for overall gene ranking. We compared the performance of MBCdeg with conventional R packages such as edgeR, DESeq2, and TCC that are specialized for DE analysis using simulated and real data. Our results showed that MBCdeg outperformed other methods when the proportion of DEG was less than 50%. However, the DEG identification using MBCdeg was less consistent than with conventional methods. We compared the effects of different normalization algorithms using MBCdeg, and performed an analysis using MBCdeg in combination with a robust normalization algorithm (called DEGES) that was not implemented in MBCluster.Seq. The new analysis method showed greater stability than using the original MBCdeg with the default normalization algorithm.Conclusions MBCdeg with DEGES normalization can be used in the identification of DEGs when the PDEG is relatively low. As the method is based on gene clustering, the DE result includes information on which expression pattern the gene belongs to. The new method may be useful for the analysis of time-course and multi-group data, where the classification of expression patterns is often required.

scholarly journals A relative comparison between Hidden Markov- and Log-Linear-based models for differential expression analysis in a real time course RNA sequencing data

2018 ◽  
Author(s):  
Fatemeh Gholizadeh ◽  
Zahra Salehi ◽  
Ali Mohammad banaei-Moghaddam ◽  
Abbas Rahimi Foroushani ◽  
Kaveh kavousi
Keyword(s):  
Real Time ◽  
Differential Expression ◽  
Rna Sequencing ◽  
Time Course ◽  
Hidden Markov ◽  
Differential Expression Analysis ◽  
Rna Seq ◽  
Sequencing Data ◽  
Normalization Methods ◽  
Log Linear

AbstractWith the advent of the Next Generation Sequencing technologies, RNA-seq has become known as an optimal approach for studying gene expression profiling. Particularly, time course RNA-seq differential expression analysis has been used in many studies to identify candidate genes. However, applying a statistical method to efficiently identify differentially expressed genes (DEGs) in time course studies is challenging due to inherent characteristics of such data including correlation and dependencies over time. Here we aim to relatively compare EBSeq-HMM, a Hidden Markov-based model, with multiDE, a Log-Linear-based model, in a real time course RNA sequencing data. In order to conduct the comparison, common DEGs detected by edgeR, DESeq2 and Voom (referred to as Benchmark DEGs) were utilized as a measure. Each of the two models were compared using different normalization methods. The findings revealed that multiDE identified more Benchmark DEGs and showed a higher agreement with them than EBSeq-HMM. Furthermore, multiDE and EBSeq-HMM displayed their best performance using TMM and Upper-Quartile normalization methods, respectively.

scholarly journals Genome-Wide Association Study and Transcriptome Differential Expression Analysis of the Feather Rate in Shouguang Chickens

2020 ◽  
Vol 11 ◽  
Author(s):  
Xiayi Liu ◽  
Zhou Wu ◽  
Junying Li ◽  
Haigang Bao ◽  
Changxin Wu
Keyword(s):  
Differential Expression ◽  
Candidate Genes ◽  
Rna Sequencing ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Serine Phosphorylation ◽  
Differentially Expressed ◽  
Genome Wide Association ◽  
Sequencing Analysis ◽  
Genome Wide

The feather rate phenotype in chicks, including early-feathering and late-feathering phenotypes, are widely used as a sexing system in the poultry industry. The objective of this study was to obtain candidate genes associated with the feather rate in Shouguang chickens. In the present study, we collected 56 blood samples and 12 hair follicle samples of flight feathers from female Shouguang chickens. Then we identified the chromosome region associated with the feather rate by genome-wide association analysis (GWAS). We also performed RNA sequencing and analyzed differentially expressed genes between the early-feathering and late-feathering phenotypes using HISAT2, StringTie, and DESeq2. We identified a genomic region of 10.0–13.0 Mb of chromosome Z, which is statistically associated with the feather rate of Shouguang chickens at one-day old. After RNA sequencing analysis, 342 differentially expressed known genes between the early-feathering (EF) and late-feathering (LF) phenotypes were screened out, which were involved in epithelial cell differentiation, intermediate filament organization, protein serine kinase activity, peptidyl-serine phosphorylation, retinoic acid binding, and so on. The sperm flagellar 2 gene (SPEF2) and prolactin receptor (PRLR) gene were the only two overlapping genes between the results of GWAS and differential expression analysis, which implies that SPEF2 and PRLR are possible candidate genes for the formation of the chicken feathering phenotype in the present study. Our findings help to elucidate the molecular mechanism of the feather rate in chicks.

scholarly journals Identification of the regulatory networks and hub genes controlling alfalfa floral pigmentation variation using RNA-sequencing analysis

2020 ◽  
Author(s):  
Hui-Rong Duan ◽  
Li-Rong Wang ◽  
Guang-Xin Cui ◽  
Xue-Hui Zhou ◽  
Xiao-Rong Duan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Regulatory Networks ◽  
Developmental Stages ◽  
Flower Color ◽  
Molecular Networks ◽  
Sequencing Analysis ◽  
Hub Genes ◽  
Color Formation ◽  
Network Analyses

Abstract Background: To understand the gene expression networks controlling flower color formation in alfalfa, flowers anthocyanins were identified using two materials with contrasting flower colors, namely Defu and Zhongtian No. 3, and transcriptome analyses of PacBio full-length sequencing combined with RNA sequencing were performed, across four flower developmental stages. Results: Malvidin and petunidin glycoside derivatives were the major anthocyanins in the flowers of Defu, which were lacking in the flowers of Zhongtian No. 3. The two transcriptomic datasets provided a comprehensive and systems-level view on the dynamic gene expression networks underpinning alfalfa flower color formation. By weighted gene coexpression network analyses, we identified candidate genes and hub genes from the modules closely related to floral developmental stages. PAL , 4CL , CHS , CHR , F3’H , DFR , and UFGT were enriched in the important modules. Additionally, PAL6 , PAL9 , 4CL18 , CHS2 , 4 and 8 were identified as hub genes. Thus, a hypothesis explaining the lack of purple color in the flower of Zhongtian No. 3 was proposed. Conclusions: These analyses identified a large number of potential key regulators controlling flower color pigmentation, thereby providing new insights into the molecular networks underlying alfalfa flower development.

scholarly journals Transcriptional Analysis of the Early Ripening of ‘Kyoho’ Grape in Response to the Treatment of Riboflavin

Genes ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 514 ◽  
Author(s):  
Zhen-Guang Wang ◽  
Li-Li Guo ◽  
Xiao-Ru Ji ◽  
Yi-He Yu ◽  
Guo-Hai Zhang ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Developmental Stages ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Grape Berry ◽  
Differentially Expressed ◽  
Transcriptional Analysis ◽  
Regulation Mechanism ◽  
Chlorophyll Metabolism ◽  
Early Ripening

Previous study has demonstrated that the riboflavin treatment promoted the early ripening of the ‘Kyoho’ grape berry. However, the molecular mechanism causing this was unclear. In order to reveal the regulation mechanism of riboflavin treatment on grape berry development and ripening, the different berry developmental stages of the ‘Kyoho’ berry treated with 0.5 mmol/L of riboflavin was sampled for transcriptome profiling. RNA-seq revealed that 1526 and 430 genes were up-regulated and down-regulated, respectively, for the comparisons of the treatment to the control. TCseq analysis showed that the expression patterns of most of the genes were similar between the treatment and the control, except for some genes that were related to the chlorophyll metabolism, photosynthesis–antenna proteins, and photosynthesis, which were revealed by the enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The differentially expressed genes and weighted gene co-expression network analysis (WGCNA) analysis identified some significantly differentially expressed genes and some hub genes, including up-regulation of the photosynthesis-related ELIP1 and growth and development-related GDSL; and down-regulation of the oxidative stress-related ATHSP22 and berry softening-related XTH32 and GH9B15. The results suggested that the riboflavin treatment resulted in the variations of the expression levels of these genes, and then led to the early ripening of the ‘Kyoho’ berry.

scholarly journals Aberrant regulation of retinoic acid signaling genes in cerebral arterio venous malformation nidus and neighboring astrocytes

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Jaya Mary Thomas ◽  
Dhakshmi Sasankan ◽  
Sumi Surendran ◽  
Mathew Abraham ◽  
Arumugam Rajavelu ◽  
...  
Keyword(s):  
Retinoic Acid ◽  
Rna Sequencing ◽  
Expression Pattern ◽  
Molecular Mechanisms ◽  
Venous Malformation ◽  
Immunofluorescence Staining ◽  
Sequencing Analysis ◽  
Retinoic Acid Signaling ◽  
Permanent Disability ◽  
And Control

Abstract Background Cerebral arterio venous malformations (AVM) are a major causal factor for intracranial hemorrhage, which result in permanent disability or death. The molecular mechanisms of AVM are complex, and their pathogenesis remains an enigma. Current research on cerebral AVM is focused on characterizing the molecular features of AVM nidus to elucidate the aberrant signaling pathways. The initial stimuli that lead to the development of AVM nidus structures between a dilated artery and a vein are however not known. Methods In order to understand the molecular basis of development of cerebral AVM, we used in-depth RNA sequencing with the total RNA isolated from cerebral AVM nidus. Immunoblot and qRT-PCR assays were used to study the differential gene expression in AVM nidus, and immunofluorescence staining was used to study the expression pattern of aberrant proteins in AVM nidus and control tissues. Immunohistochemistry was used to study the expression pattern of aberrant proteins in AVM nidus and control tissues. Results The transcriptome study has identified 38 differentially expressed genes in cerebral AVM nidus, of which 35 genes were upregulated and 3 genes were downregulated. A final modular analysis identified an upregulation of ALDH1A2, a key rate-limiting enzyme of retinoic acid signaling pathway. Further analysis revealed that CYR61, a regulator of angiogenesis, and the target gene for retinoic acid signaling is upregulated in AVM nidus. We observed that astrocytes associated with AVM nidus are abnormal with increased expression of GFAP and Vimentin. Triple immunofluorescence staining of the AVM nidus revealed that CYR61 was also overexpressed in the abnormal astrocytes associated with AVM tissue. Conclusion Using high-throughput RNA sequencing analysis and immunostaining, we report deregulated expression of retinoic acid signaling genes in AVM nidus and its associated astrocytes and speculate that this might trigger the abnormal angiogenesis and the development of cerebral AVM in humans.

scholarly journals Identification of Long Non-Coding RNAs Associated with Tomato Fruit Expansion and Ripening by Strand-Specific Paired-End RNA Sequencing

Horticulturae ◽  
2021 ◽  
Vol 7 (12) ◽  
pp. 522
Author(s):  
Jinyu Wang ◽  
Yan Feng ◽  
Xiaotao Ding ◽  
Jingtian Huo ◽  
Wen-Feng Nie
Keyword(s):  
Rna Sequencing ◽  
Fruits And Vegetables ◽  
Developmental Stages ◽  
Tomato Fruit ◽  
Expression Patterns ◽  
Fleshy Fruit ◽  
Tomato Fruits ◽  
Tomato Plants ◽  
Horticultural Crops ◽  
Non Coding Rnas

As emerging essential regulators in plant development, long non-coding RNAs (lncRNAs) have been extensively investigated in multiple horticultural crops, as well as in different tissues of plants. Tomato fruits are an indispensable part of people’s diet and are consumed as fruits and vegetables. Meanwhile, tomato is widely used as a model to study the ripening mechanism in fleshy fruit. Although increasing evidence shows that lncRNAs are involved in lots of biological processes in tomato plants, the comprehensive identification of lncRNAs in tomato fruit during its expansion and ripening and their functions are partially known. Here, we performed strand-specific paired-end RNA sequencing (ssRNA-seq) of tomato Heinz1706 fruits at five different developmental stages, as well as flowers and leaves. We identified 17,674 putative lncRNAs by referencing the recently released SL4.0 and annotation ITAG4.0 in tomato plants. Many lncRNAs show different expression patterns in fleshy fruit at different developmental stages compared with leaves or flowers. Our results indicate that lncRNAs play an important role in the regulation of tomato fruit expansion and ripening, providing informative lncRNA candidates for further studies in tomato fruits. In addition, we also summarize the recent advanced progress in lncRNAs mediated regulation on horticultural fruits. Hence, our study updates the understanding of lncRNAs in horticultural plants and provides resources for future studies relating to the expansion and ripening of tomato fruits.

scholarly journals Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kapil Gupta ◽  
Shubhra Gupta ◽  
Adi Faigenboim-Doron ◽  
Abhinandan Surgonda Patil ◽  
Yael Levy ◽  
...  
Keyword(s):  
Cell Wall ◽  
Transcription Factors ◽  
Dry Matter ◽  
Developmental Stages ◽  
Expression Patterns ◽  
Cellulose Synthase ◽  
Pathogen Resistance ◽  
Cell Wall Biosynthesis ◽  
Peanut Shell ◽  
Pod Development

Abstract Background Peanut (Arachis hypogaea L.) belongs to an exceptional group of legume plants, wherein the flowers are produced aerially, but the pods develop under the ground. In such a unique environment, the pod’s outer shell plays a vital role as a barrier against mechanical damage and soilborne pathogens. Recent studies have reported the uniqueness and importance of gene expression patterns that accompany peanut pods’ biogenesis. These studies focused on biogenesis and pod development during the early stages, but the late developmental stages and disease resistance aspects still have gaps. To extend this information, we analyzed the transcriptome generated from four pod developmental stages of two genotypes, Hanoch (Virginia-type) and IGC53 (Peruvian-type), which differs significantly in their pod shell characteristics and pathogen resistance. Results The transcriptome study revealed a significant reprogramming of the number and nature of differentially expressed (DE) genes during shell development. Generally, the numbers of DE genes were higher in IGC53 than in Hanoch, and the R5-R6 transition was the most dynamic in terms of transcriptomic changes. Genes related to cell wall biosynthesis, modification and transcription factors (TFs) dominated these changes therefore, we focused on their differential, temporal and spatial expression patterns. Analysis of the cellulose synthase superfamily identified specific Cellulose synthase (CesAs) and Cellulose synthase-like (Csl) genes and their coordinated interplay with other cell wall-related genes during the peanut shell development was demonstrated. TFs were also identified as being involved in the shell development process, and their pattern of expression differed in the two peanut genotypes. The shell component analysis showed that overall crude fiber, cellulose, lignin, hemicelluloses and dry matter increased with shell development, whereas K, N, protein, and ash content decreased. Genotype IGC53 contained a higher level of crude fiber, cellulose, NDF, ADF, K, ash, and dry matter percentage, while Hanoch had higher protein and nitrogen content. Conclusions The comparative transcriptome analysis identified differentially expressed genes, enriched processes, and molecular processes like cell wall biosynthesis/modifications, carbohydrate metabolic process, signaling, transcription factors, transport, stress, and lignin biosynthesis during the peanut shell development between two contrasting genotypes. TFs and other genes like chitinases were also enriched in peanut shells known for pathogen resistance against soilborne major pathogens causing pod wart disease and pod damages. This study will shed new light on the biological processes involved with underground pod development in an important legume crop.

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