scholarly journals A Comprehensive Coexpression Network Analysis in Vibrio cholerae

mSystems ◽  
2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Cory D. DuPai ◽  
Claus O. Wilke ◽  
Bryan W. Davies
Keyword(s):  
Network Analysis ◽  
Vibrio Cholerae ◽  
Rna Sequencing ◽  
High Throughput Sequencing ◽  
Model Organism ◽  
Coexpression Network ◽  
Sequencing Data ◽  
Content Type ◽  
The Impact ◽  
Coexpression Network Analysis

ABSTRACT Research into the evolution and pathogenesis of Vibrio cholerae has benefited greatly from the generation of high-throughput sequencing data to drive molecular analyses. The steady accumulation of these data sets now provides a unique opportunity for in silico hypothesis generation via coexpression analysis. Here, we leverage all published V. cholerae RNA sequencing data, in combination with select data from other platforms, to generate a gene coexpression network that validates known gene interactions and identifies novel genetic partners across the entire V. cholerae genome. This network provides direct insights into genes influencing pathogenicity, metabolism, and transcriptional regulation, further clarifies results from previous sequencing experiments in V. cholerae (e.g., transposon insertion sequencing [Tn-seq] and chromatin immunoprecipitation sequencing [ChIP-seq]), and expands upon microarray-based findings in related Gram-negative bacteria. IMPORTANCE Cholera is a devastating illness that kills tens of thousands of people annually. Vibrio cholerae, the causative agent of cholera, is an important model organism to investigate both bacterial pathogenesis and the impact of horizontal gene transfer on the emergence and dissemination of new virulent strains. Despite the importance of this pathogen, roughly one-third of V. cholerae genes are functionally unannotated, leaving large gaps in our understanding of this microbe. Through coexpression network analysis of existing RNA sequencing data, this work develops an approach to uncover novel gene-gene relationships and contextualize genes with no known function, which will advance our understanding of V. cholerae virulence and evolution.

scholarly journals A comprehensive co-expression network analysis in Vibrio cholerae

2020 ◽  
Author(s):  
Cory D. DuPai ◽  
Claus O. Wilke ◽  
Bryan W. Davies
Keyword(s):  
Network Analysis ◽  
Vibrio Cholerae ◽  
Rna Sequencing ◽  
High Throughput Sequencing ◽  
Model Organism ◽  
Sequencing Data ◽  
High Throughput Sequencing Data ◽  
Virulent Strains ◽  
Micro Array ◽  
The Impact

AbstractResearch into the evolution and pathogenesis of Vibrio cholerae has benefited greatly from the generation of high throughput sequencing data to drive molecular analyses. The steady accumulation of these datasets now provides a unique opportunity for in silico hypothesis generation via co-expression analysis. Here we leverage all published V. cholerae RNA-sequencing data, in combination with select data from other platforms, to generate a gene co-expression network that validates known gene interactions and identifies novel genetic partners across the entire V. cholerae genome. This network provides direct insights into genes influencing pathogenicity, metabolism, and transcriptional regulation, further clarifies results from previous sequencing experiments in V. cholerae (e.g. Tn-seq and ChIP-seq), and expands upon micro-array based findings in related gram-negative bacteria.ImportanceCholera is a devastating illness that kills tens of thousands of people annually. Vibrio cholerae, the causative agent of cholera, is an important model organism to investigate both bacterial pathogenesis and the impact of horizontal gene transfer on the emergence and dissemination of new virulent strains. Despite this importance, roughly one third of V. cholerae genes are functionally un-annotated, leaving large gaps in our understanding of this microbe. Through co-expression network analysis of existing RNA-sequencing data, this work develops an approach to uncover novel gene-gene relationships and contextualize genes with no known function, which will advance our understanding of V. cholerae virulence and evolution.

scholarly journals A meta-analysis reveals the environmental and host factors shaping the structure and function of the shrimp microbiota

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5382 ◽  
Author(s):  
Fernanda Cornejo-Granados ◽  
Luigui Gallardo-Becerra ◽  
Miriam Leonardo-Reza ◽  
Juan Pablo Ochoa-Romo ◽  
Adrian Ochoa-Leyva
Keyword(s):  
Developmental Stage ◽  
High Throughput Sequencing ◽  
Meta Analysis ◽  
Biological Factor ◽  
Rrna Gene ◽  
Wild Type ◽  
Biological Factors ◽  
Sequencing Data ◽  
Freshwater Environment ◽  
The Impact

The shrimp or prawn is the most valuable traded marine product in the world market today and its microbiota plays an essential role in its development, physiology, and health. The technological advances and dropping costs of high-throughput sequencing have increased the number of studies characterizing the shrimp microbiota. However, the application of different experimental and bioinformatics protocols makes it difficult to compare different studies to reach general conclusions about shrimp microbiota. To meet this necessity, we report the first meta-analysis of the microbiota from freshwater and marine shrimps using all publically available sequences of the 16S ribosomal gene (16S rRNA gene). We obtained data for 199 samples, in which 63.3% were from marine (Alvinocaris longirostris, Litopenaeus vannamei and Penaeus monodon), and 36.7% were from freshwater (Macrobrachium asperulum, Macrobrachium nipponense, Macrobranchium rosenbergii, Neocaridina denticulata) shrimps. Technical variations among studies, such as selected primers, hypervariable region, and sequencing platform showed a significant impact on the microbiota structure. Additionally, the ANOSIM and PERMANOVA analyses revealed that the most important biological factor in structuring the shrimp microbiota was the marine and freshwater environment (ANOSIM R = 0.54, P = 0.001; PERMANOVA pseudo-F = 21.8, P = 0.001), where freshwater showed higher bacterial diversity than marine shrimps. Then, for marine shrimps, the most relevant biological factors impacting the microbiota composition were lifestyle (ANOSIM R = 0.341, P = 0.001; PERMANOVA pseudo-F = 8.50, P = 0.0001), organ (ANOSIM R = 0.279, P = 0.001; PERMANOVA pseudo-F = 6.68, P = 0.001) and developmental stage (ANOSIM R = 0.240, P = 0.001; PERMANOVA pseudo-F = 5.05, P = 0.001). According to the lifestyle, organ, developmental stage, diet, and health status, the highest diversity were for wild-type, intestine, adult, wild-type diet, and healthy samples, respectively. Additionally, we used PICRUSt to predict the potential functions of the microbiota, and we found that the organ had more differentially enriched functions (93), followed by developmental stage (12) and lifestyle (9). Our analysis demonstrated that despite the impact of technical and bioinformatics factors, the biological factors were also statistically significant in shaping the microbiota. These results show that cross-study comparisons are a valuable resource for the improvement of the shrimp microbiota and microbiome fields. Thus, it is important that future studies make public their sequencing data, allowing other researchers to reach more powerful conclusions about the microbiota in this non-model organism. To our knowledge, this is the first meta-analysis that aims to define the shrimp microbiota.

scholarly journals Quality assessment of single-cell RNA sequencing data by coverage skewness analysis

2019 ◽  
Author(s):  
Imad Abugessaisa ◽  
Shuhei Noguchi ◽  
Melissa Cardon ◽  
Akira Hasegawa ◽  
Kazuhide Watanabe ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cells ◽  
Assessment Method ◽  
Poor Quality ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Gene Coverage ◽  
The Impact

AbstractAnalysis and interpretation of single-cell RNA-sequencing (scRNA-seq) experiments are compromised by the presence of poor quality cells. For meaningful analyses, such poor quality cells should be excluded to avoid biases and large variation. However, no clear guidelines exist. We introduce SkewC, a novel quality-assessment method to identify poor quality single-cells in scRNA-seq experiments. The method is based on the assessment of gene coverage for each single cell and its skewness as a quality measure. To validate the method, we investigated the impact of poor quality cells on downstream analyses and compared biological differences between typical and poor quality cells. Moreover, we measured the ratio of intergenic expression, suggesting genomic contamination, and foreign organism contamination of single-cell samples. SkewC is tested in 37,993 single-cells generated by 15 scRNA-seq protocols. We envision SkewC as an indispensable QC method to be incorporated into scRNA-seq experiment to preclude the possibility of scRNA-seq data misinterpretation.

scholarly journals Coexpression network analysis of neural tissue reveals perturbations in developmental processes in schizophrenia

2010 ◽  
Vol 20 (4) ◽  
pp. 403-412 ◽  
Author(s):  
A. Torkamani ◽  
B. Dean ◽  
N. J. Schork ◽  
E. A. Thomas
Keyword(s):  
Network Analysis ◽  
Neural Tissue ◽  
Coexpression Network ◽  
Developmental Processes ◽  
Coexpression Network Analysis

Review of Weighted Gene Coexpression Network Analysis

2011 ◽  
pp. 369-388 ◽  
Author(s):  
Tova Fuller ◽  
Peter Langfelder ◽  
Angela Presson ◽  
Steve Horvath
Keyword(s):  
Network Analysis ◽  
Coexpression Network ◽  
Gene Coexpression Network ◽  
Gene Coexpression ◽  
Coexpression Network Analysis

scholarly journals Evaluation of Whole-Genome Sequencing for Identification and Typing of Vibrio cholerae

2018 ◽  
Vol 56 (11) ◽  
Author(s):  
David R. Greig ◽  
Ulf Schaefer ◽  
Sophie Octavia ◽  
Ebony Hunter ◽  
Marie A. Chattaway ◽  
...  
Keyword(s):  
Public Health ◽  
Whole Genome Sequencing ◽  
Vibrio Cholerae ◽  
Species Identification ◽  
Genome Sequencing ◽  
National Level ◽  
Whole Genome ◽  
Content Type ◽  
El Tor ◽  
The Impact

ABSTRACT Epidemiological and microbiological data on Vibrio cholerae strains isolated between April 2004 and March 2018 (n = 836) and held at the Public Health England culture archive were reviewed. The traditional biochemical species identification and serological typing results were compared with the genome-derived species identification and serotype for a subset of isolates (n = 152). Of the 836 isolates, 750 (89.7%) were from a fecal specimen, 206 (24.6%) belonged to serogroup O1, and 7 (0.8%) were serogroup O139; 792 (94.7%) isolates were from patients reporting recent travel abroad, most commonly to India (n = 209) and Pakistan (n = 104). Of the 152 V. cholerae isolates identified by use of kmer, 149 (98.1%) were concordant with those identified using the traditional biochemical approach. Traditional serotyping results were 100% concordant with those of the whole-genome sequencing (WGS) analysis for the identification of serogroups O1 and O139 and classical and El Tor biotypes. ctxA was detected in all isolates of V. cholerae O1 El Tor and O139 belonging to sequence type 69 (ST69) and in V. cholerae O1 classical variants belonging to ST73. A phylogeny of isolates belonging to ST69 from U.K. travelers clustered geographically, with isolates from India and Pakistan located on separate branches. Moving forward, WGS data from U.K. travelers will contribute to global surveillance programs and the monitoring of emerging threats to public health and the global dissemination of pathogenic lineages. At the national level, these WGS data will inform the timely reinforcement of direct public health messaging to travelers and mitigate the impact of imported infections and the associated risks to public health.

scholarly journals Effects of CPAP on the transcriptional signatures in patients with obstructive sleep apnea via coexpression network analysis

2019 ◽  
Vol 120 (6) ◽  
pp. 9277-9290 ◽  
Author(s):  
Juxiang Peng ◽  
Jukun Song ◽  
Jing Zhou ◽  
Xinhai Yin ◽  
Jinlin Song
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Network Analysis ◽  
Coexpression Network ◽  
Obstructive Sleep ◽  
Coexpression Network Analysis

scholarly journals Weighted gene coexpression network analysis reveals hub genes involved in cholangiocarcinoma progression and prognosis

2019 ◽  
Vol 49 (10) ◽  
pp. 1195-1206 ◽  
Author(s):  
Aiping Tian ◽  
Ke Pu ◽  
Boxuan Li ◽  
Min Li ◽  
Xiaoguang Liu ◽  
...  
Keyword(s):  
Network Analysis ◽  
Coexpression Network ◽  
Gene Coexpression Network ◽  
Hub Genes ◽  
Gene Coexpression ◽  
Coexpression Network Analysis
Sign in / Sign up

Export Citation Format

Share Document