scholarly journals The Regulatory Network of CMPG1-V in Wheat–Blumeria graminis f. sp. tritici Interaction Revealed by Temporal Profiling Using RNA-Seq

2020 ◽  
Vol 21 (17) ◽  
pp. 5967 ◽  
Author(s):  
Jia Liu ◽  
Li Sun ◽  
Yiming Chen ◽  
Luyang Wei ◽  
Yongli Hao ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Blumeria Graminis ◽  
Sucrose Metabolism ◽  
Aba Signaling ◽  
Rna Seq ◽  
Haynaldia Villosa ◽  
Breeding Programs ◽  
Kegg Analysis ◽  
Broad Spectrum Resistance ◽  
Study Gene Expression

Wheat powdery mildew (Pm), caused by Blumeria graminis f. sp. tritici (Bgt), is a prevalent fungal disease. The diploid wheat relative Haynaldia villosa (H. villosa) showed broad-spectrum resistance (BSR) to Pm. A previous study reported an E3 ligase gene, CMPG1-V from H. villosa, showing BSR to Pm. To elucidate the regulatory network mediated by CMPG1-V, in this study, gene expression profiling of CMPG1-V transgenic plant (CMPG1-VOE) and its receptor Yangmai 158 was analyzed and compared after Bgt inoculation at four infection stages. GO and KEGG analysis revealed obvious reprogramming of SA and ABA signaling, starch/sucrose metabolism, and photosynthesis in CMPG1-VOE, compared with those in Yangmai 158. Transcripts of SA synthesis genes SARD1 and UGT, signaling factors TGA and PRs, and SnRKs in ABA signaling were specifically upregulated in CMPG1-VOE rather than Yangmai 158. Transcripts of LHCII in photosynthesis, GLUC and TPP in starch/sucrose metabolism were also induced distinctly in CMPG1-VOE. WGCNA analysis showed crucial regulatory candidates of CMPG1-V, involving serine/threonine-protein kinase in phosphorylation, glucosyltransferase in flavonoid biosynthesis, defense factor WRKYs, and peroxidase in oxidative stress. Our results facilitate the deciphering of the resistant regulatory network of CMPG1-V and the identification of key candidates which might be employed in breeding programs.

scholarly journals NKL Homeobox Gene VENTX Is Part of a Regulatory Network in Human Conventional Dendritic Cells

2021 ◽  
Vol 22 (11) ◽  
pp. 5902
Author(s):  
Stefan Nagel ◽  
Claudia Pommerenke ◽  
Corinna Meyer ◽  
Hans G. Drexler
Keyword(s):  
Dendritic Cells ◽  
Transcription Factors ◽  
Cell Lines ◽  
Expression Profiling ◽  
Regulatory Network ◽  
Homeobox Gene ◽  
Leukemia Cell Line ◽  
Specific Gene ◽  
Rna Seq ◽  
And Function

Recently, we documented a hematopoietic NKL-code mapping physiological expression patterns of NKL homeobox genes in human myelopoiesis including monocytes and their derived dendritic cells (DCs). Here, we enlarge this map to include normal NKL homeobox gene expressions in progenitor-derived DCs. Analysis of public gene expression profiling and RNA-seq datasets containing plasmacytoid and conventional dendritic cells (pDC and cDC) demonstrated HHEX activity in both entities while cDCs additionally expressed VENTX. The consequent aim of our study was to examine regulation and function of VENTX in DCs. We compared profiling data of VENTX-positive cDC and monocytes with VENTX-negative pDC and common myeloid progenitor entities and revealed several differentially expressed genes encoding transcription factors and pathway components, representing potential VENTX regulators. Screening of RNA-seq data for 100 leukemia/lymphoma cell lines identified prominent VENTX expression in an acute myelomonocytic leukemia cell line, MUTZ-3 containing inv(3)(q21q26) and t(12;22)(p13;q11) and representing a model for DC differentiation studies. Furthermore, extended gene analyses indicated that MUTZ-3 is associated with the subtype cDC2. In addition to analysis of public chromatin immune-precipitation data, subsequent knockdown experiments and modulations of signaling pathways in MUTZ-3 and control cell lines confirmed identified candidate transcription factors CEBPB, ETV6, EVI1, GATA2, IRF2, MN1, SPIB, and SPI1 and the CSF-, NOTCH-, and TNFa-pathways as VENTX regulators. Live-cell imaging analyses of MUTZ-3 cells treated for VENTX knockdown excluded impacts on apoptosis or induced alteration of differentiation-associated cell morphology. In contrast, target gene analysis performed by expression profiling of knockdown-treated MUTZ-3 cells revealed VENTX-mediated activation of several cDC-specific genes including CSFR1, EGR2, and MIR10A and inhibition of pDC-specific genes like RUNX2. Taken together, we added NKL homeobox gene activities for progenitor-derived DCs to the NKL-code, showing that VENTX is expressed in cDCs but not in pDCs and forms part of a cDC-specific gene regulatory network operating in DC differentiation and function.

Construction of an lncRNA–mRNA Co-Expression Regulatory Network Mediating Inflammation and Regeneration Following Acute Pancreatitis Injury

2021 ◽  
Author(s):  
Jing Wang ◽  
Tianjie Chen ◽  
Xiaohua Zhang ◽  
Shulei Zhao
Keyword(s):  
Acute Pancreatitis ◽  
Mrna Expression ◽  
Regulatory Network ◽  
Noncoding Rnas ◽  
Pancreatic Injury ◽  
Control Group ◽  
Rna Seq ◽  
Damage Repair ◽  
Injury And Repair ◽  
And Function

Abstract Long noncoding RNAs (lncRNAs) play important roles in the occurrence and development of many diseases and can be used as targets for diagnosis and treatment. However, the expression and function of lncRNAs in the injury and repair of acute pancreatitis (AP) are unclear. To decipher lncRNAs’ regulatory roles in AP, we reanalyzed an RNA-seq dataset of 24 pancreatic tissues, including those of normal control mice (BL), those 7 days after mild AP (D7), and those 14 days after mild AP (D14). The results showed significant differences in lncRNA and mRNA expression of D7/D14 groups compared with the control group. Co-expression analysis showed that differentially expressed (DE) lncRNAs were closely related to immunity- and inflammation-related pathways by trans-regulating mRNA expression. The lncRNA–mRNA network showed that the lncRNAs Dancer, Gmm20488, Terc, Snhg3, and Snhg20 were significantly correlated with AP pathogenesis. WGCNA and cis regulation analysis also showed that AP repair-associated lncRNAs were correlated with extracellular and inflammation-related genes, which affect the repair and regeneration of pancreatic injury after AP. In conclusion, the systemic dysregulation of lncRNAs is strongly involved in remodeling AP’s gene expression regulatory network, and the lncRNA–mRNA expression network could identify targets for AP treatment and damage repair.

scholarly journals Pathogenic Variation of Colletotrichum lindemuthianum causing Anthracnose of Beans (Phaseolus vulgaris) in Uganda

2017 ◽  
Vol 5 (3) ◽  
pp. 89-98
Author(s):  
Moses J. Kiryowa ◽  
Aston Ebinu ◽  
Vincent Kyaligonza ◽  
Stanley T. Nkalubo ◽  
Pamela Paparu ◽  
...  
Keyword(s):  
Broad Spectrum ◽  
Single Gene ◽  
Colletotrichum Lindemuthianum ◽  
Breeding Programs ◽  
Pathogenic Variation ◽  
Broad Spectrum Resistance ◽  
Differential Cultivars ◽  
Differential Cultivar ◽  
Bean Anthracnose ◽  
Pathogenic Variability

Colletotrichum lindemuthianum is a highly variable pathogen of common beans that easily overcomes resistance in cultivars bred with single-gene resistance. To determine pathogenic variability of the pathogen in Uganda, samples of common bean tissues with anthracnose symptoms were collected in eight districts of Uganda, namely Kabarole, Sironko, Mbale, Oyam, Lira, Kapchorwa, Maracha and Kisoro. 51 isolates sporulated successfully on Potato Dextrose Agar and Mathur’s media and were used to inoculate 12 differential cultivars under controlled conditions. Five plants per cultivar were inoculated with each isolate and then evaluated for their reaction using the 1 – 9 severity scale. Races were classified using the binary nomenclature system proposed by Pastor Corrales (1991). Variation due to cultivar and isolate effects was significant (P≤0.001) for severity. The 51 isolates from eight districts grouped into 27 different races. Sironko district had the highest number of races followed by Mbale and Kabarole. Races 2047 and 4095 were the most frequently found, each with 10 isolates grouped under them. Race 4095 was the most virulent since it caused a susceptible (S) reaction on all 12 differential cultivars and the susceptible check. This was followed by races 2479, 2047 and 2045 respectively. Two races, 4094 and 2479, caused a susceptible reaction on the differential cultivar G2333, which nevertheless, showed the most broad spectrum resistance followed by cultivars Cornell 49-242, TU, and AB136 respectively. These cultivars are recommended for use in breeding programs aiming at breeding for broad spectrum resistance to bean anthracnose in Uganda.

scholarly journals Differential regulatory network-based quantification and prioritization of key genes underlying cancer drug resistance based on time-course RNA-seq data

2019 ◽  
Vol 15 (11) ◽  
pp. e1007435 ◽  
Author(s):  
Jiajun Zhang ◽  
Wenbo Zhu ◽  
Qianliang Wang ◽  
Jiayu Gu ◽  
L. Frank Huang ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Regulatory Network ◽  
Time Course ◽  
Cancer Drug ◽  
Rna Seq ◽  
Cancer Drug Resistance ◽  
Key Genes

scholarly journals Differential Expression Profiles of the Transcriptome and miRNA Interactome in Synovial Fibroblasts of Rheumatoid Arthritis Revealed by Next Generation Sequencing

Diagnostics ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 98
Author(s):  
Chia-Chun Tseng ◽  
Ling-Yu Wu ◽  
Wen-Chan Tsai ◽  
Tsan-Teng Ou ◽  
Cheng-Chin Wu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Differential Expression ◽  
Regulatory Network ◽  
Functional Annotation ◽  
Interaction Analysis ◽  
Expression Profiles ◽  
Synovial Fibroblasts ◽  
Rna Seq ◽  
Network Mapping ◽  
Generation Sequencing

Using next-generation sequencing to decipher the molecular mechanisms underlying aberrant rheumatoid arthritis synovial fibroblasts (RASF) activation, we performed transcriptome-wide RNA-seq and small RNA-seq on synovial fibroblasts from rheumatoid arthritis (RA) subject and normal donor. Differential expression of mRNA and miRNA was integrated with interaction analysis, functional annotation, regulatory network mapping and experimentally verified miRNA–target interaction data, further validated with microarray expression profiles. In this study, 3049 upregulated mRNA and 3552 downregulated mRNA, together with 50 upregulated miRNA and 35 downregulated miRNA in RASF were identified. Interaction analysis highlighted contribution of miRNA to altered transcriptome. Functional annotation revealed metabolic deregulation and oncogenic signatures of RASF. Regulatory network mapping identified downregulated FOXO1 as master transcription factor resulting in altered transcriptome of RASF. Differential expression in three miRNA and corresponding targets (hsa-miR-31-5p:WASF3, hsa-miR-132-3p:RB1, hsa-miR-29c-3p:COL1A1) were also validated. The interactions of these three miRNA–target genes were experimentally validated with past literature. Our transcriptomic and miRNA interactomic investigation identified gene signatures associated with RASF and revealed the involvement of transcription factors and miRNA in an altered transcriptome. These findings help facilitate our understanding of RA with the hope of serving as a springboard for further discoveries relating to the disease.

No counts, no variance: allowing for loss of degrees of freedom when assessing biological variability from RNA-seq data

2017 ◽  
Vol 16 (2) ◽  
Author(s):  
Aaron T. L. Lun ◽  
Gordon K. Smyth
Keyword(s):  
Software Package ◽  
Error Control ◽  
Degrees Of Freedom ◽  
Linear Models ◽  
Type I Error ◽  
Real Data ◽  
Type I ◽  
Rna Seq ◽  
Study Gene Expression ◽  
Complex Models

AbstractRNA sequencing (RNA-seq) is widely used to study gene expression changes associated with treatments or biological conditions. Many popular methods for detecting differential expression (DE) from RNA-seq data use generalized linear models (GLMs) fitted to the read counts across independent replicate samples for each gene. This article shows that the standard formula for the residual degrees of freedom (d.f.) in a linear model is overstated when the model contains fitted values that are exactly zero. Such fitted values occur whenever all the counts in a treatment group are zero as well as in more complex models such as those involving paired comparisons. This misspecification results in underestimation of the genewise variances and loss of type I error control. This article proposes a formula for the reduced residual d.f. that restores error control in simulated RNA-seq data and improves detection of DE genes in a real data analysis. The new approach is implemented in the quasi-likelihood framework of the edgeR software package. The results of this article also apply to RNA-seq analyses that apply linear models to log-transformed counts, such as those in the limma software package, and more generally to any count-based GLM where exactly zero fitted values are possible.

scholarly journals Comparative RNA-Seq Analysis Reveals That Regulatory Network of Maize Root Development Controls the Expression of Genes in Response to N Stress

PLoS ONE ◽  
2016 ◽  
Vol 11 (3) ◽  
pp. e0151697 ◽  
Author(s):  
Xiujing He ◽  
Haixia Ma ◽  
Xiongwei Zhao ◽  
Shujun Nie ◽  
Yuhua Li ◽  
...  
Keyword(s):  
Root Development ◽  
Regulatory Network ◽  
Maize Root ◽  
Rna Seq ◽  
Expression Of Genes
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