scholarly journals Expression analysis of genes related to cold tolerance in Dendroctonus valens

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10864
Author(s):  
Dongfang Zhao ◽  
Chunchun Zheng ◽  
Fengming Shi ◽  
Yabei Xu ◽  
Shixiang Zong ◽  
...  
Keyword(s):  
Cold Tolerance ◽  
Expression Analysis ◽  
Molecular Mechanisms ◽  
Differential Expression Analysis ◽  
The United States ◽  
Model Organisms ◽  
Large Area ◽  
Illumina Hiseq ◽  
Dendroctonus Valens ◽  
Genes Encoding

Pine beetles are well known in North America for their widespread devastation of pine forests. However, Dendroctonus valens LeConte is an important invasive forest pest in China also. Adults and larvae of this bark beetle mainly winter at the trunks and roots of Pinus tabuliformis and Pinus sylvestris; larvae, in particular, result in pine weakness or even death. Since the species was introduced from the United States to Shanxi in 1998, its distribution has spread northward. In 2017, it invaded a large area at the junction of Liaoning, Inner Mongolia and Hebei provinces, showing strong cold tolerance. To identify genes relevant to cold tolerance and the process of overwintering, we sequenced the transcriptomes of wintering and non-wintering adult and larval D. valens using the Illumina HiSeq platform. Differential expression analysis methods for other non-model organisms were used to compare transcript abundances in adults and larvae at two time periods, followed by the identification of functions and metabolic pathways related to genes associated with cold tolerance. We detected 4,387 and 6,091 differentially expressed genes (DEGs) between sampling dates in larvae and adults, respectively, and 1,140 common DEGs, including genes encoding protein phosphatase, very long-chain fatty acids protein, cytochrome P450, and putative leucine-rich repeat-containing proteins. In a Gene Ontology (GO) enrichment analysis, 1,140 genes were assigned to 44 terms, with significant enrichment for cellulase activity, hydrolase activity, and carbohydrate metabolism. Kyoto Encyclopedia of Genes and Genomes (KEGG) classification and enrichment analyses showed that the lysosomal and purine metabolism pathways involved the most DEGs, the highly enriched terms included autophagy—animal, pentose and glucuronate interconversions and lysosomal processes. We identified 140 candidate genes associated with cold tolerance, including genes with established roles in this trait (e.g., genes encoding trehalose transporter, fructose-1,6-bisphosphatase, and trehalase). Our comparative transcriptome analysis of adult and larval D. valens in different conditions provides basic data for the discovery of key genes and molecular mechanisms underlying cold tolerance.

scholarly journals Genome-wide Identification, characterization and expression analysis of the effector-triggered immunity (ETI) pathway-mediated defense responsive genes in grapes against powdery and downy mildew infections

2020 ◽  
Author(s):  
Neetu Goyal ◽  
Garima Bhatia ◽  
Naina Garewal ◽  
Anuradha Upadhyay ◽  
Kashmir Singh
Keyword(s):  
Expression Analysis ◽  
Molecular Mechanisms ◽  
Differential Expression Analysis ◽  
Differentially Expressed ◽  
Fungal Resistance ◽  
Biotic Stresses ◽  
Sequence Of Events ◽  
Genome Wide ◽  
Effector Triggered Immunity ◽  
Grape Varieties

Abstract Grapevine productivity is severely affected by fungal diseases worldwide and for the diseases control in eco-friendly way, it is essential to understand the molecular mechanisms of fungal resistance in grapes. Therefore, we performed genome-wide identification of various Resistance (R) genes expressed during PM and DM infection in grapevine. Consequently, we identified 6, 21, 2, 5, 3 and 48 EDS1, NDR1, PAD4, NPR, RAR and PR genes respectively in the grapevine genome. Further, differential expression analysis resulted in identification of 2, 4, 7, 2, 4, 1 and 7 differentially expressed PM-responsive Resistance (R) genes (NBS-LRR, EDS1, NDR1, PAD4, NPR, RAR1 and PR) and 28, 2, 5, 4, 1 and 19 differentially expressed DM-responsive Resistance (R) genes (NBS-LRR, EDS1, NDR1, NPR, RAR1 and PR) in V. vinifera. These genes are involved in salicylic acid mediated Effector-triggered immunity (ETI) pathway, therefore, we examined their co-expression to determine the sequence of events that occurs during a signaling cascade in order to respond against PM and DM-infection. Altogether, the PM and DM responsive R genes of ETI pathway found in this study can be used in future to produce new and improved grape varieties that are immune to biotic stresses.

scholarly journals Transcriptome Sequencing and Differential Expression Analysis Reveal Molecular Mechanisms for Seed Starch Accumulation in Chinese Chestnut Metaxenia

2020 ◽  
Author(s):  
Shengxing Li ◽  
Zhuogong Shi ◽  
Zhiheng Zhao ◽  
Qiurong Zhu ◽  
Liang Tao ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Soluble Sugars ◽  
Differential Expression Analysis ◽  
Female Parent ◽  
Sucrose Metabolism ◽  
Starch Accumulation ◽  
Seed Kernel ◽  
Nutrient Contents ◽  
Genes Encoding ◽  
Lim Proteins

Abstract Background: Chestnut is an important kind of edible nut rich in starch and protein. The characteristics and nutrient contents of chestnut have been found to show obvious metaxenia effects in previous studies. To improve the understanding of the metaxenia effect on chestnut starch and sucrose metabolism, this study used three varieties of chestnut, ‘Yongfeng 1’, ‘Yong Renzao’ and ‘Yimeng 1’, as male parents to pollinate ‘Yongfeng 1’, as the female parent, and studied the mechanisms of starch and sucrose metabolism in three starch accumulation stages (70 (S1), 82 (S2), and 94 (S3) days after pollination , DAP) in the chestnut seed kernel.Result: Most carbohydrate metabolism genes were highly expressed in YFF in stage S2 and in YFR and YFM in stage S3. In stage S3, hub genes encoding HSF_DNA-binding, ACT, Pkinase, and LIM proteins and four transcription factors were highly expressed, with YFF showing the higest expression, followed by YFR and, finally, YFM. In addition, transcriptome analysis of the kernels at 70, 82 and 94 DAP showed that the starch granule-bound starch synthase (EC 2.4.1.242) and ADP-glucose pyrophosphorylase (EC 2.7 .7.27) genes were actively expressed at 94 DAF. Chestnut seeds regulate the accumulation of soluble sugars, reducing sugars and starch by controlling glycosyl transferase and hydrolysis activity during development.Conclusion: These studies and resources have important guiding significance for further research on starch and sucrose metabolism and other types of metabolism related to chestnut metaxenia.

Identification of Critical Functional Modules and Signaling Pathways in Osteoporosis

2020 ◽  
Vol 15 ◽  
Author(s):  
Xiaowei Jiang ◽  
Pu Ying ◽  
Yingchao Shen ◽  
Yiming Miu ◽  
Wenbin Kong ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Differential Expression ◽  
Expression Analysis ◽  
Network Topology ◽  
Molecular Mechanisms ◽  
Differential Expression Analysis ◽  
Osteoclast Differentiation ◽  
Enrichment Analysis ◽  
Osteoclast Formation ◽  
Functional Modules

Background: Osteoporosis is the most common bone metabolic disease. Abnormal osteoclast formation and resorption play a fundamental role in osteoporosis pathogenesis. Recent researches have greatly broadened our understanding of molecular mechanisms of osteoporosis. However, the molecular mechanisms leading to osteoporosis are still not entirely clear. Objective: The purpose of this work is to study the critical regulatory genes, functional modules, and signaling pathways. Methods: Differential expression analysis, network topology-based analysis, and overrepresentation enrichment analysis (ORA) were used to identify differentially expressed genes (DEGs), gene subnetworks, and signaling pathways related to osteoporosis, respectively. Results: Differential expression analysis identified DEGs, such as POGLUT1, DAPK3 and NFKBIA, associated with osteoclastogenesis, which highlighted Notch, apoptosis and NF-kB signaling pathways. Network topology-based analysis identified the upregulated subnetwork characterized by EXOSC8 and DIS3L from the RNA exosome complex, and the downregulated subnetwork composed of histone deacetylases and the cofactors, MORF4L1 and JDP2. Furthermore, the overrepresentation enrichment analysis highlighted that corticotrophin-releasing hormone signaling pathway may affect osteoclastogenesis through its component NR4A1, and suppressing osteoclast differentiation and osteoclast bone resorption with urocortin (UCN). Conclusion: Our systematic analysis not only discovered novel molecular mechanisms, but also proposed potential drug targets for osteoporosis.

scholarly journals Assembly-free rapid differential gene expression analysis in non-model organisms using DNA-protein alignment

2021 ◽  
Author(s):  
Anish M.S. Shrestha ◽  
Joyce Emlyn B. Guiao ◽  
Kyle Christian R. Santiago
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Expression Analysis ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Differential Expression Analysis ◽  
Homology Search ◽  
Model Organisms ◽  
Rna Seq ◽  
Protein Database

AbstractRNA-seq is being increasingly adopted for gene expression studies in a panoply of non-model organisms, with applications spanning the fields of agriculture, aquaculture, ecology, and environment. Conventional differential expression analysis for organisms without reference sequences requires performing computationally expensive and error-prone de-novo transcriptome assembly, followed by homology search against a high-confidence protein database for functional annotation. We propose a shortcut, where we obtain counts for differential expression analysis by directly aligning RNA-seq reads to the protein database. Through experiments on simulated and real data, we show drastic reductions in run-time and memory usage, with no loss in accuracy. A Snakemake implementation of our workflow is available at:https://bitbucket.org/project_samar/samar

scholarly journals A Computational Framework to Identify Transcriptional and Network Differences between Hepatocellular Carcinoma and Normal Liver Tissue and Their Applications in Repositioning Drugs

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Aimin Hu ◽  
Zheng Wei ◽  
Zuxiang Zheng ◽  
Bichao Luo ◽  
Jieming Yi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Differentially Expressed Genes ◽  
Expression Analysis ◽  
Molecular Mechanisms ◽  
Drug Repositioning ◽  
Differential Expression Analysis ◽  
Differentially Expressed ◽  
Computational Framework ◽  
Normal Tissues

Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies worldwide. Although there have been extensive studies on the molecular mechanisms of its carcinogenesis, FDA-approved drugs for HCC are rare. Side effects, development time, and cost of these drugs are the major bottlenecks, which can be partially overcome by drug repositioning. In this study, we developed a computational framework to study the mechanisms of HCC carcinogenesis, in which drug perturbation-induced gene expression signatures were utilized for repositioning of potential drugs. Specifically, we first performed differential expression analysis and coexpression network module analysis on the HCC dataset from The Cancer Genome Atlas database. Differential gene expression analysis identified 1,337 differentially expressed genes between HCC and adjacent normal tissues, which were significantly enriched in functions related to various pathways, including α-adrenergic receptor activity pathway and epinephrine binding pathway. Weighted gene correlation network analysis (WGCNA) suggested that the number of coexpression modules was higher in HCC tissues than in normal tissues. Finally, by correlating differentially expressed genes with drug perturbation-related signatures, we prioritized a few potential drugs, including nutlin and eribulin, for the treatment of hepatocellular carcinoma. The drugs have been reported by a few experimental studies to be effective in killing cancer cells.

Circular RNA expression profiling in dorsal root ganglion of rats with peripheral nerve injury-induced neuropathic pain

2020 ◽  
Author(s):  
Wanxia Xiong ◽  
Fan Liu ◽  
jie wang ◽  
zhiyao wang
Keyword(s):  
Neuropathic Pain ◽  
Differential Expression ◽  
Expression Analysis ◽  
Functional Annotation ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
Differential Expression Analysis ◽  
Mapk Signaling ◽  
Circular Rnas ◽  
Next Generation Sequencing Technology

Abstract Background : Circular RNAs (circRNAs) comprise a class of endogenous species of RNA consisting of a covalently closed loop structure that is crucial for genetic and epigenetic regulation. The significance of circRNA in neuropathic pain remains to be investigated. Methods : The sciatic nerve chronic constriction injury (CCI) model was established to induce neuropathic pain. We performed genome-wide circRNA analysis of 4 paired DRG sample from CCI and NC rats via next generation sequencing technology. The differentially expressed circRNAs (DEcircRNAs) were identified by differential expression analysis and the expression profile of circRNAs was validated by quantitative real-time PCR (qPCR). Functional annotation analysis was performed to predict the function of DEcircRNAs. Results : A total of 374 DEcirRNAs were identified between CCI and NC rats using circRNA High-throughput sequencing (HTS). Expression levels of 9 DEcircRNAs were validated by qPCR. Functional annotation analysis showed that DEcircRNAs were mainly enriched in pathways and functions such as ‘dopaminergic synapse’, ‘renin secretion’, ‘MAPK signaling pathway’ and ‘neurogenesis’. Competing endogenous RNAs analysis showed that top 50 circRNAs exhibited interactions with four pain related miRNAs. Circ:chr2:33950934-33955969 is the largest node in the circRNA-miRNA interaction network. Conclusion : DEcircRNAs may advance our understanding of the molecular mechanisms underlying neuropathic pain. Key words : neuropathic pain, circRNA, CCI, differential expression analysis

scholarly journals THE EFFECTS OF AGE AND SIZE ON THE COMPANION DOG METABOLOME: ROLES OF TRYPTOPHAN AND FATTY ACID METABOLISM

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S424-S425
Author(s):  
Jessica M Hoffman ◽  
Steven Austad
Keyword(s):  
Molecular Mechanisms ◽  
Acid Metabolism ◽  
Geographic Location ◽  
The United States ◽  
Tryptophan Metabolism ◽  
Model Organisms ◽  
Interesting Phenomenon ◽  
Companion Dogs ◽  
Metabolomics Study

Abstract Recently, the companion dog has been promoted as an ideal animal model for human aging. Dogs show an interesting phenomenon where smaller individuals are longer lived than their larger counterparts. However, many of the underlying molecular mechanisms that influence aging and longevity in the dog are unknown. To begin to uncover these physiological changes, we completed the largest metabolomics study to date in the companion dog. Here, we collected blood plasma samples from companion dogs in three in the United States for metabolomics analysis. We then looked at the effects of age and size on the metabolome to develop new hypotheses about healthy canine aging. Our most striking differences were found with regards to geographic location in the canine metabolome, in which metabolic profiles were more similar between dogs in the same city than across cities. After controlling for this location effect, we found a strong signal of amino acid metabolism, specifically tryptophan metabolism, associated with weight in the dog where metabolites in the tryptophan metabolism pathway were always higher in small, long-lived dogs. Future studies will directly investigate the role of tryptophan metabolism in model organisms.

scholarly journals RNfuzzyApp: an R shiny RNA-seq data analysis app for visualisation, differential expression analysis, time-series clustering and enrichment analysis

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 654
Author(s):  
Margaux Haering ◽  
Bianca H Habermann
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Model Organisms ◽  
Rna Seq ◽  
Series Analysis ◽  
Shiny App ◽  
R Shiny

RNA sequencing (RNA-seq) is a widely adopted affordable method for large scale gene expression profiling. However, user-friendly and versatile tools for wet-lab biologists to analyse RNA-seq data beyond standard analyses such as differential expression, are rare. Especially, the analysis of time-series data is difficult for wet-lab biologists lacking advanced computational training. Furthermore, most meta-analysis tools are tailored for model organisms and not easily adaptable to other species. With RNfuzzyApp, we provide a user-friendly, web-based R shiny app for differential expression analysis, as well as time-series analysis of RNA-seq data. RNfuzzyApp offers several methods for normalization and differential expression analysis of RNA-seq data, providing easy-to-use toolboxes, interactive plots and downloadable results. For time-series analysis, RNfuzzyApp presents the first web-based, fully automated pipeline for soft clustering with the Mfuzz R package, including methods to aid in cluster number selection, cluster overlap analysis, Mfuzz loop computations, as well as cluster enrichments. RNfuzzyApp is an intuitive, easy to use and interactive R shiny app for RNA-seq differential expression and time-series analysis, offering a rich selection of interactive plots, providing a quick overview of raw data and generating rapid analysis results. Furthermore, its orthology assignment, enrichment analysis, as well as ID conversion functions are accessible to non-model organisms.

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