scholarly journals Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling

2011 ◽  
Vol 27 (13) ◽  
pp. i383-i391 ◽  
Author(s):  
Paweł P. Łabaj ◽  
Germán G. Leparc ◽  
Bryan E. Linggi ◽  
Lye Meng Markillie ◽  
H. Steven Wiley ◽  
...  
Keyword(s):  
Expression Profiling ◽  
Transcript Expression ◽  
Rna Seq

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.

scholarly journals Differential modulation of heat inducible genes across diverse genotypes and molecular cloning of a sHSP from Pearl millet [Pennisetum glaucum (L.) R. Br.]

2020 ◽  
Author(s):  
S MukeshSankar ◽  
C. Tara Satyavathi ◽  
Sharmistha Barthakur ◽  
S.P Singh ◽  
Roshan Kumar ◽  
...  
Keyword(s):  
Heat Stress ◽  
High Temperature ◽  
Pearl Millet ◽  
Temperature Stress ◽  
Expression Profiling ◽  
Stability Index ◽  
High Temperature Stress ◽  
Seedling Stage ◽  
Transcript Expression ◽  
Membrane Stability Index

AbstractEnvironmental stresses negatively influence survival, biomass and grain yield of most crops. Towards functionally clarifying the role of heat responsive genes in Pearl millet under high temperature stress, the present study were carried out using semi quantitative RT- PCR for transcript expression profiling of hsf and hsps in 8 different inbred lines at seedling stage, which was earlier identified as thermo tolerant/susceptible lines through initial screening for thermo tolerance using membrane stability index among 38 elite genotypes. Transcript expression pattern suggested existence of differential response among different genotypes in response to heat stress in the form of accumulation of heat shock responsive gene transcripts. Genotypes WGI 126, TT-1 and MS 841B responded positively towards high temperature stress for transcript accumulation for both Pgcp 70 and Pghsf and also had better growth under heat stress, whereas PPMI 69 showed the least responsiveness to transcript induction supporting the membrane stability index data for scoring thermotolerance, suggesting the efficacy of transcript expression profiling as a molecular based screening technique for identification of thermotolerant genes and genotypes at particular crop growth stages. As to demonstrate this, a full length cDNA of Pghsp 16.97 was cloned from the thermotolerant cultivar, WGI 126 and characterized for thermotolerance. The results of demonstration set forth the transcript profiling for heat tolerant genes can be a very useful technique for high throughput screening of tolerant genotypes at molecular level from large cultivar collections at seedling stage.

scholarly journals A novel min-cost flow method for estimating transcript expression with RNA-Seq

2013 ◽  
Vol 14 (S5) ◽  
Author(s):  
Alexandru I Tomescu ◽  
Anna Kuosmanen ◽  
Romeo Rizzi ◽  
Veli Mäkinen
Keyword(s):  
Transcript Expression ◽  
Rna Seq ◽  
Flow Method ◽  
Cost Flow ◽  
Min Cost Flow

scholarly journals RNA-Seq investigations of human post-mortem trigeminal ganglia

Cephalalgia ◽  
2017 ◽  
Vol 38 (5) ◽  
pp. 912-932 ◽  
Author(s):  
Danielle M LaPaglia ◽  
Matthew R Sapio ◽  
Peter D Burbelo ◽  
Jean Thierry-Mieg ◽  
Danielle Thierry-Mieg ◽  
...  
Keyword(s):  
Genetic Association ◽  
Expression Profiling ◽  
Association Studies ◽  
Susceptibility Genes ◽  
Blood Levels ◽  
Trigeminal Ganglia ◽  
Molecular Heterogeneity ◽  
Post Mortem ◽  
Rna Seq ◽  
Hsv 1

Background The trigeminal ganglion contains neurons that relay sensations of pain, touch, pressure, and many other somatosensory modalities to the central nervous system. The ganglion is also a reservoir for latent herpes virus 1 infection. To gain a better understanding of molecular factors contributing to migraine and headache, transcriptome analyses were performed on postmortem human trigeminal ganglia. Methods RNA-Seq measurements of gene expression were conducted on small sub-regions of 16 human trigeminal ganglia. The samples were also characterized for transcripts derived from viral and microbial genomes. Herpes simplex virus 1 (HSV-1) antibodies in blood were measured using the luciferase immunoprecipitation assay. Results Observed molecular heterogeneity could be explained by sampling of anatomically distinct sub-regions of the excised ganglia consistent with neurally-enriched and non-neural, i.e. Schwann cell, enriched subregions. The levels of HSV-1 transcripts detected in trigeminal ganglia correlated with blood levels of HSV-1 antibodies. Multiple migraine susceptibility genes were strongly expressed in neurally-enriched trigeminal samples, while others were expressed in blood vessels. Conclusions These data provide a comprehensive human trigeminal transcriptome and a framework for evaluation of inhomogeneous post-mortem tissues through extensive quality control and refined downstream analyses for RNA-Seq methodologies. Expression profiling of migraine susceptibility genes identified by genetic association appears to emphasize the blood vessel component of the trigeminovascular system. Other genes displayed enriched expression in the trigeminal compared to dorsal root ganglion, and in-depth transcriptomic analysis of the KCNK18 gene underlying familial migraine shows selective neural expression within two specific populations of ganglionic neurons. These data suggest that expression profiling of migraine-associated genes can extend and amplify the underlying neurobiological insights obtained from genetic association studies.

scholarly journals Fast and accurate approximate inference of transcript expression from RNA-seq data

2015 ◽  
pp. btv483 ◽  
Author(s):  
James Hensman ◽  
Panagiotis Papastamoulis ◽  
Peter Glaus ◽  
Antti Honkela ◽  
Magnus Rattray
Keyword(s):  
Approximate Inference ◽  
Transcript Expression ◽  
Rna Seq
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