scholarly journals Transcriptomic Analysis of Rhodococcus opacus R7 Grown on o-Xylene by RNA-Seq

2020 ◽  
Vol 11 ◽  
Author(s):  
Jessica Zampolli ◽  
Alessandra Di Canito ◽  
Andrea Manconi ◽  
Luciano Milanesi ◽  
Patrizia Di Gennaro ◽  
...  
Keyword(s):  
Transcriptomic Analysis ◽  
Rhodococcus Opacus ◽  
Rna Seq

scholarly journals Transcriptomic analysis of Rhodococcus opacus R7 grown on polyethylene by RNA-seq

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jessica Zampolli ◽  
Alessandro Orro ◽  
Andrea Manconi ◽  
Diletta Ami ◽  
Antonino Natalello ◽  
...  
Keyword(s):  
Genetic System ◽  
Transcriptomic Analysis ◽  
Rhodococcus Opacus ◽  
Aliphatic Chain ◽  
Rna Seq ◽  
Gene Encoding ◽  
Enzymatic Assays ◽  
Cytochrome P450 Hydroxylase ◽  
Global Issue ◽  
Genes Encoding

AbstractPlastic waste management has become a global issue. Polyethylene (PE) is the most abundant synthetic plastic worldwide, and one of the most resistant to biodegradation. Indeed, few bacteria can degrade polyethylene. In this paper, the transcriptomic analysis unveiled for the first time Rhodococcus opacus R7 complex genetic system based on diverse oxidoreductases for polyethylene biodegradation. The RNA-seq allowed uncovering genes putatively involved in the first step of oxidation. In-depth investigations through preliminary bioinformatic analyses and enzymatic assays on the supernatant of R7 grown in the presence of PE confirmed the activation of genes encoding laccase-like enzymes. Moreover, the transcriptomic data allowed identifying candidate genes for the further steps of short aliphatic chain oxidation including alkB gene encoding an alkane monooxygenase, cyp450 gene encoding cytochrome P450 hydroxylase, and genes encoding membrane transporters. The PE biodegradative system was also validated by FTIR analysis on R7 cells grown on polyethylene.

scholarly journals The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read differential expression analysis tools

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Xueyi Dong ◽  
Luyi Tian ◽  
Quentin Gouil ◽  
Hasaru Kariyawasam ◽  
Shian Su ◽  
...  
Keyword(s):  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Transcriptomic Analysis ◽  
Statistical Testing ◽  
Rna Seq ◽  
Sequencing Data ◽  
Short Read ◽  
Sequencing Platform ◽  
Long Read

Abstract Application of Oxford Nanopore Technologies’ long-read sequencing platform to transcriptomic analysis is increasing in popularity. However, such analysis can be challenging due to the high sequence error and small library sizes, which decreases quantification accuracy and reduces power for statistical testing. Here, we report the analysis of two nanopore RNA-seq datasets with the goal of obtaining gene- and isoform-level differential expression information. A dataset of synthetic, spliced, spike-in RNAs (‘sequins’) as well as a mouse neural stem cell dataset from samples with a null mutation of the epigenetic regulator Smchd1 was analysed using a mix of long-read specific tools for preprocessing together with established short-read RNA-seq methods for downstream analysis. We used limma-voom to perform differential gene expression analysis, and the novel FLAMES pipeline to perform isoform identification and quantification, followed by DRIMSeq and limma-diffSplice (with stageR) to perform differential transcript usage analysis. We compared results from the sequins dataset to the ground truth, and results of the mouse dataset to a previous short-read study on equivalent samples. Overall, our work shows that transcriptomic analysis of long-read nanopore data using long-read specific preprocessing methods together with short-read differential expression methods and software that are already in wide use can yield meaningful results.

Transcriptomic analysis of Camellia oleifera in response to drought stress using high throughput RNA-seq

2017 ◽  
Vol 64 (5) ◽  
pp. 728-737 ◽  
Author(s):  
H. Yang ◽  
H. Y. Zhou ◽  
X. N. Yang ◽  
J. J. Zhan ◽  
H. Zhou ◽  
...  
Keyword(s):  
Drought Stress ◽  
High Throughput ◽  
Transcriptomic Analysis ◽  
Camellia Oleifera ◽  
Rna Seq

scholarly journals Mechanisms of colitis-accelerated colon carcinogenesis and its prevention with the combination of aspirin and curcumin: Transcriptomic analysis using RNA-seq

2017 ◽  
Vol 135 ◽  
pp. 22-34 ◽  
Author(s):  
Yue Guo ◽  
Zheng-Yuan Su ◽  
Chengyue Zhang ◽  
John M. Gaspar ◽  
Rui Wang ◽  
...  
Keyword(s):  
Colon Carcinogenesis ◽  
Transcriptomic Analysis ◽  
Rna Seq

RNA-Seq-mediated transcriptomic analysis of heat stress response in a polar Chlorella sp. (Trebouxiophyceae, Chlorophyta)

2018 ◽  
Vol 30 (6) ◽  
pp. 3103-3119 ◽  
Author(s):  
Sze-Wan Poong ◽  
Kok-Keong Lee ◽  
Phaik-Eem Lim ◽  
Tun-Wen Pai ◽  
Chiew-Yen Wong ◽  
...  
Keyword(s):  
Heat Stress ◽  
Stress Response ◽  
Transcriptomic Analysis ◽  
Rna Seq ◽  
Heat Stress Response ◽  
Chlorella Sp

scholarly journals Fast and accurate single-cell RNA-Seq analysis by clustering of transcript-compatibility counts

2016 ◽  
Author(s):  
Vasilis Ntranos ◽  
Govinda M. Kamath ◽  
Jesse Zhang ◽  
Lior Pachter ◽  
David N. Tse
Keyword(s):  
Single Cell ◽  
Transcriptomic Analysis ◽  
Rna Seq ◽  
Standard Analysis ◽  
Novel Method ◽  
Computationally Intensive ◽  
Or Gene ◽  
Specific Modeling

Current approaches to single-cell transcriptomic analysis are computationally intensive and require assay-specific modeling which limit their scope and generality. We propose a novel method that departs from standard analysis pipelines, comparing and clustering cells based not on their transcript or gene quantifications but on their transcript-compatibility read counts. In re-analysis of two landmark yet disparate single-cell RNA-Seq datasets, we show that our method is up to two orders of magnitude faster than previous approaches, provides accurate and in some cases improved results, and is directly applicable to data from a wide variety of assays.

Transcriptomic analysis by RNA-seq of Escherichia coli O157:H7 response to prolonged cold stress

LWT ◽  
2018 ◽  
Vol 97 ◽  
pp. 17-24 ◽  
Author(s):  
Yaru Li ◽  
Donggen Zhou ◽  
Shuangfang Hu ◽  
Xinglong Xiao ◽  
Yigang Yu ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Cold Stress ◽  
Transcriptomic Analysis ◽  
Escherichia Coli O157 ◽  
Rna Seq
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