scholarly journals Performance of a scalable RNA extraction-free transcriptome profiling method for adherent cultured human cells

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shreya Ghimire ◽  
Carley G. Stewart ◽  
Andrew L. Thurman ◽  
Alejandro A. Pezzulo
Keyword(s):  
Small Molecule ◽  
Cultured Cells ◽  
Low Cost ◽  
Expression Patterns ◽  
Rna Extraction ◽  
Differentially Expressed Gene ◽  
Dermal Fibroblasts ◽  
Quality Data ◽  
Rna Seq ◽  
Cdna Synthesis

AbstractRNA sequencing enables high-content/high-complexity measurements in small molecule screens. Whereas the costs of DNA sequencing and RNA-seq library preparation have decreased consistently, RNA extraction remains a significant bottleneck to scalability. We evaluate the performance of a bulk RNA-seq library prep protocol optimized for analysis of many samples of adherent cultured cells in parallel. We combined a low-cost direct lysis buffer compatible with cDNA synthesis (in-lysate cDNA synthesis) with Smart-3SEQ and examine the effects of calmidazolium and fludrocortisone-induced perturbation of primary human dermal fibroblasts. We compared this method to normalized purified RNA inputs from matching samples followed by Smart-3SEQ or Illumina TruSeq library prep. Our results show the minimal effect of RNA loading normalization on data quality, measurement of gene expression patterns, and generation of differentially expressed gene lists. We found that in-lysate cDNA synthesis combined with Smart-3SEQ RNA-seq library prep generated high-quality data with similar ranked DEG lists when compared to library prep with extracted RNA or with Illumina TruSeq. Our data show that small molecule screens or experiments based on many perturbations quantified with RNA-seq are feasible at low reagent and time costs.

scholarly journals Performance of a scalable extraction-free RNA-seq method

2021 ◽  
Author(s):  
Shreya Ghimire ◽  
Carley G. Stewart ◽  
Andrew L. Thurman ◽  
Alejandro A. Pezzulo
Keyword(s):  
Small Molecule ◽  
Cultured Cells ◽  
Low Cost ◽  
Expression Patterns ◽  
Rna Extraction ◽  
Differentially Expressed Gene ◽  
Dermal Fibroblasts ◽  
Quality Data ◽  
Rna Seq ◽  
Cdna Synthesis

AbstractRNA sequencing enables high-contents/high-complexity measurements in small molecule screens performed on biological samples. Whereas the costs of DNA sequencing and the complexity of RNA-seq library preparation and analysis have decreased consistently, RNA extraction remains a significant bottleneck for RNA-seq of hundreds of samples in parallel. Direct use of cell lysate for RNA-seq library prep is common in single cell RNA-seq but not in bulk RNA-seq protocols. Recently published protocols suggest that direct lysis is compatible with simplified RNA-seq library prep. Here, we evaluate the performance of a bulk RNA-seq library prep protocol optimized for analysis of many samples of adherent cultured cells in parallel. We combine a low-cost direct lysis buffer compatible with cDNA synthesis (“in-lysate cDNA synthesis”) with Smart-3SEQ and examine the effects of calmidazolium and fludrocortisone-induced perturbation of primary human dermal fibroblasts. We compared this method to normalized purified RNA inputs from matching samples followed by Smart-3SEQ or Illumina TruSeq library prep. Our results show that whereas variable RNA inputs for each sample in the in-lysate cDNA synthesis protocol result in variable sequencing depth, this had minimal effect on data quality, measurement of gene expression patterns, or generation of differentially expressed gene lists. We found that in-lysate cDNA synthesis combined with Smart-3SEQ RNA-seq library prep allows generation of high-quality data when compared to library prep with extracted RNA, or when compared to Illumina TruSeq. Our data show that small molecule screens using RNA-seq are feasible at low reagent and time costs.

scholarly journals xMD-miRNA-seq to generate near in vivo miRNA expression estimates in colon epithelial cells

2018 ◽  
Author(s):  
Avi Z. Rosenberg ◽  
Carrie Wright ◽  
Karen Fox-Talbot ◽  
Anandita Rajpurohit ◽  
Courtney Williams ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Small Rna ◽  
Mirna Expression ◽  
Low Cost ◽  
Expression Patterns ◽  
Small Rna Sequencing ◽  
Rna Seq ◽  
Cell Type

AbstractAccurate, RNA-seq based, microRNA (miRNA) expression estimates from primary cells have recently been described. However, this in vitro data is mainly obtained from cell culture, which is known to alter cell maturity/differentiation status, significantly changing miRNA levels. What is needed is a robust method to obtain in vivo miRNA expression values directly from cells. We introduce expression microdissection miRNA small RNA sequencing (xMD-miRNA-seq), a method to isolate cells directly from formalin fixed paraffin-embedded (FFPE) tissues. xMD-miRNA-seq is a low-cost, high-throughput, immunohistochemistry-based method to capture any cell type of interest. As a proof-of-concept, we isolated colon epithelial cells from two specimens and performed low-input small RNA-seq. We generated up to 600,000 miRNA reads from the samples. Isolated epithelial cells, had abundant epithelial-enriched miRNA expression (miR-192; miR-194; miR-200b; miR-200c; miR-215; miR-375) and overall similar miRNA expression patterns to other epithelial cell populations (colonic enteroids and flow-isolated colon epithelium). xMD-derived epithelial cells were generally not contaminated by other adjacent cells of the colon as noted by t-SNE analysis. xMD-miRNA-seq allows for simple, economical, and efficient identification of cell-specific miRNA expression estimates. Further development will enhance rapid identification of cell-specific miRNA expression estimates in health and disease for nearly any cell type using archival FFPE material.

scholarly journals MSF: Modulated Sub-graph Finder

F1000Research ◽  
2019 ◽  
Vol 7 ◽  
pp. 1346
Author(s):  
Mariam R. Farman ◽  
Ivo L. Hofacker ◽  
Fabian Amman
Keyword(s):  
Expression Patterns ◽  
Differentially Expressed Gene ◽  
Data Interpretation ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Novel Approach ◽  
Differential Gene ◽  
External Stimuli ◽  
Flow Of Information

High throughput techniques such as RNA-seq or microarray analysis have proven to be invaluable for the characterizing of global transcriptional gene activity changes due to external stimuli or diseases. Differential gene expression analysis (DGEA) is the first step in the course of data interpretation, typically producing lists of dozens to thousands of differentially expressed genes. To further guide the interpretation of these lists, different pathway analysis approaches have been developed. These tools typically rely on the classification of genes into sets of genes, such as pathways, based on the interactions between the genes and their function in a common biological process. Regardless of technical differences, these methods do not properly account for cross talk between different pathways and most of the methods rely on binary separation into differentially expressed gene and unaffected genes based on an arbitrarily set p-value cut-off. To overcome this limitation, we developed a novel approach to identify concertedly modulated sub-graphs in the global cell signaling network, based on the DGEA results of all genes tested. To this end, expression patterns of genes are integrated according to the topology of their interactions and allow potentially to read the flow of information and identify the effectors. The described software, named Modulated Sub-graph Finder (MSF) is freely available at https://github.com/Modulated-Subgraph-Finder/MSF.

scholarly journals An optimized method to obtain high-quality RNA from different tissues in Lilium davidii var. unicolor

2021 ◽  
Author(s):  
Chunlei Wang ◽  
Xuemei Hou ◽  
Nana Qi ◽  
Changxia Li ◽  
Yanyan Luo ◽  
...  
Keyword(s):  
Low Cost ◽  
Rna Extraction ◽  
Rna Isolation ◽  
Extraction Methods ◽  
High Yield ◽  
Rna Seq ◽  
High Quality ◽  
Ctab Method ◽  
Different Tissues ◽  
Lilium Davidii

Abstract Background: The high quality, high yield and purity RNA samples are essential for subsequent molecular experiments such as RT-PCR, qPCR and RNA-seq. However, harvest high quality RNA samples from different tissues in Lilium davidii var. unicolor is a great challenge due to its polysaccharides, polyphenols and other secondary metabolites. In this study, three RNA extraction methods, namely modified TRIzol method, Kit and CTAB methods were reported to obtain the total RNA from Lilium davidii var. unicolor, and the efficient RNA extraction protocol (modified TRIzol method) was described. Results: A Nano drop spectrophotometer and 1% gel electrophoresis were used to detect the RNA quality and integrity. Compared with Kit and CTAB methods, the higher RNA concentrations from different tissues were obtained and the A260/280 ratios of RNA samples were ranged from1.97 to 2.27 when using the modified TRIzol method. None of intact RNA bands were gained from the modified CTAB method, indicating that the RNA samples isolation were degraded. As a result of the modified TRIzol method, the RNA samples in the different tissues from Lilium presented clear 28S and 18S bands.Conclusions: Here, modified TRIzol method is an easy, efficient, and low-cost method for RNA isolation from Lilium davidii var. unicolor. Thus, modified TRIzol method is sufficient to gain eligible RNA to support further molecular experiments in Lilium davidii var. unicolor.

scholarly journals RNA-seq analysis of workers' brain reveals that queen and brood affect bumble bee worker reproduction via similar genetic pathways

2021 ◽  
Author(s):  
Priscila Santos ◽  
David Galbraith ◽  
Jesse Starkey ◽  
Etya Amsalem
Keyword(s):  
Gene Expression ◽  
Fat Body ◽  
Expression Patterns ◽  
Differentially Expressed Gene ◽  
Worker Reproduction ◽  
Differentially Expressed ◽  
Bumble Bee ◽  
Rna Seq ◽  
Evolution Of Sociality ◽  
Worker Sterility

Worker reproduction in social insects is often regulated by the queen’s presence but can be regulated by other colony members, such as the brood and nestmates. Adults and brood may induce the same outcomes in subordinates but may use different mechanisms. Here, we compared gene expression patterns in bumble bee workers (Bombus impatiens) in response to the queen, the brood, both or none. RNA‐seq analysis of workers’ brain identified 27 differentially expressed genes regulated by the queen and the brood. Expression levels of 8 candidate genes were re-tested using qRT-PCR in worker brain and fat body. Our results show that the brood’s effect on gene expression is substantially weaker than the queen, and a greater impact on gene expression was caused by the combined presence of the queen and the brood. All the genes that were explained by the brood presence were also regulated by the queen presence. A significant amount of the variation in gene expression was explained by the queen, that regulated the expression of key regulators of reproduction and brood care across insects, such as neuroparsin and vitellogenin. A comparison of the data with similar datasets in the honeybee and the raider ant revealed that neuroparsin is the only differentially expressed gene shared by all species. These data highlight the need to consider components other than the queen when examining mechanisms regulating worker sterility and provide information on key genes regulating reproduction that are likely to play an important role in the evolution of sociality.

scholarly journals Integration of transcriptomic data identifies key hallmark genes in hypertrophic cardiomyopathy

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jing Xu ◽  
Xiangdong Liu ◽  
Qiming Dai
Keyword(s):  
Machine Learning ◽  
Hypertrophic Cardiomyopathy ◽  
Heart Diseases ◽  
Expression Patterns ◽  
Support Vector ◽  
Rna Seq ◽  
Ppi Network ◽  
Learning Methods ◽  
Transcriptomic Data ◽  
Machine Learning Methods

Abstract Background Hypertrophic cardiomyopathy (HCM) represents one of the most common inherited heart diseases. To identify key molecules involved in the development of HCM, gene expression patterns of the heart tissue samples in HCM patients from multiple microarray and RNA-seq platforms were investigated. Methods The significant genes were obtained through the intersection of two gene sets, corresponding to the identified differentially expressed genes (DEGs) within the microarray data and within the RNA-Seq data. Those genes were further ranked using minimum-Redundancy Maximum-Relevance feature selection algorithm. Moreover, the genes were assessed by three different machine learning methods for classification, including support vector machines, random forest and k-Nearest Neighbor. Results Outstanding results were achieved by taking exclusively the top eight genes of the ranking into consideration. Since the eight genes were identified as candidate HCM hallmark genes, the interactions between them and known HCM disease genes were explored through the protein–protein interaction (PPI) network. Most candidate HCM hallmark genes were found to have direct or indirect interactions with known HCM diseases genes in the PPI network, particularly the hub genes JAK2 and GADD45A. Conclusions This study highlights the transcriptomic data integration, in combination with machine learning methods, in providing insight into the key hallmark genes in the genetic etiology of HCM.

scholarly journals Advanced mycelium materials as potential self-growing biomedical scaffolds

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maria Elena Antinori ◽  
Marco Contardi ◽  
Giulia Suarato ◽  
Andrea Armirotti ◽  
Rosalia Bertorelli ◽  
...  
Keyword(s):  
Tissue Engineering ◽  
Low Cost ◽  
Direct Interaction ◽  
Dermal Fibroblasts ◽  
Engineering Systems ◽  
Edible Fungi ◽  
Avant Garde ◽  
Fibrous Network ◽  
Body Tissues ◽  
Wide Range

AbstractMycelia, the vegetative part of fungi, are emerging as the avant-garde generation of natural, sustainable, and biodegradable materials for a wide range of applications. They are constituted of a self-growing and interconnected fibrous network of elongated cells, and their chemical and physical properties can be adjusted depending on the conditions of growth and the substrate they are fed upon. So far, only extracts and derivatives from mycelia have been evaluated and tested for biomedical applications. In this study, the entire fibrous structures of mycelia of the edible fungi Pleurotus ostreatus and Ganoderma lucidum are presented as self-growing bio-composites that mimic the extracellular matrix of human body tissues, ideal as tissue engineering bio-scaffolds. To this purpose, the two mycelial strains are inactivated by autoclaving after growth, and their morphology, cell wall chemical composition, and hydrodynamical and mechanical features are studied. Finally, their biocompatibility and direct interaction with primary human dermal fibroblasts are investigated. The findings demonstrate the potentiality of mycelia as all-natural and low-cost bio-scaffolds, alternative to the tissue engineering systems currently in place.

scholarly journals The assembled and annotated genome of the pigeon louse Columbicola columbae, a model ectoparasite

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
James G Baldwin-Brown ◽  
Scott M Villa ◽  
Anna I Vickrey ◽  
Kevin P Johnson ◽  
Sarah E Bush ◽  
...  
Keyword(s):  
Low Cost ◽  
Single Copy ◽  
Odorant Receptors ◽  
Rna Seq ◽  
Pediculus Humanus ◽  
Final Assembly ◽  
Oxford Nanopore ◽  
Genes Encoding ◽  
Host Parasite ◽  
G Protein Coupled

Abstract The pigeon louse Columbicola columbae is a longstanding and important model for studies of ectoparasitism and host-parasite coevolution. However, a deeper understanding of its evolution and capacity for rapid adaptation is limited by a lack of genomic resources. Here, we present a high-quality draft assembly of the C. columbae genome, produced using a combination of Oxford Nanopore, Illumina, and Hi-C technologies. The final assembly is 208 Mb in length, with 12 chromosome-size scaffolds representing 98.1% of the assembly. For gene model prediction, we used a novel clustering method (wavy_choose) for Oxford Nanopore RNA-seq reads to feed into the MAKER annotation pipeline. High recovery of conserved single-copy orthologs (BUSCOs) suggests that our assembly and annotation are both highly complete and highly accurate. Consistent with the results of the only other assembled louse genome, Pediculus humanus, we find that C. columbae has a relatively low density of repetitive elements, the majority of which are DNA transposons. Also similar to P. humanus, we find a reduced number of genes encoding opsins, G protein-coupled receptors, odorant receptors, insulin signaling pathway components, and detoxification proteins in the C. columbae genome, relative to other insects. We propose that such losses might characterize the genomes of obligate, permanent ectoparasites with predictable habitats, limited foraging complexity, and simple dietary regimes. The sequencing and analysis for this genome were relatively low cost, and took advantage of a new clustering technique for Oxford Nanopore RNAseq reads that will be useful to future genome projects.

scholarly journals Clustering Single-Cell RNA-Seq Data with Regularized Gaussian Graphical Model

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 311
Author(s):  
Zhenqiu Liu
Keyword(s):  
Single Cell ◽  
Free Parameter ◽  
Graphical Model ◽  
Expression Patterns ◽  
Information Criterion ◽  
Log P ◽  
Rna Seq ◽  
Clustering Methods ◽  
Wide Range ◽  
Free Parameters

Single-cell RNA-seq (scRNA-seq) is a powerful tool to measure the expression patterns of individual cells and discover heterogeneity and functional diversity among cell populations. Due to variability, it is challenging to analyze such data efficiently. Many clustering methods have been developed using at least one free parameter. Different choices for free parameters may lead to substantially different visualizations and clusters. Tuning free parameters is also time consuming. Thus there is need for a simple, robust, and efficient clustering method. In this paper, we propose a new regularized Gaussian graphical clustering (RGGC) method for scRNA-seq data. RGGC is based on high-order (partial) correlations and subspace learning, and is robust over a wide-range of a regularized parameter λ. Therefore, we can simply set λ=2 or λ=log(p) for AIC (Akaike information criterion) or BIC (Bayesian information criterion) without cross-validation. Cell subpopulations are discovered by the Louvain community detection algorithm that determines the number of clusters automatically. There is no free parameter to be tuned with RGGC. When evaluated with simulated and benchmark scRNA-seq data sets against widely used methods, RGGC is computationally efficient and one of the top performers. It can detect inter-sample cell heterogeneity, when applied to glioblastoma scRNA-seq data.

scholarly journals Transcriptome Analysis Reveals HgCl2 Induces Apoptotic Cell Death in Human Lung Carcinoma H1299 Cells through Caspase-3-Independent Pathway

2021 ◽  
Vol 22 (4) ◽  
pp. 2006
Author(s):  
Mi Jin Kim ◽  
Jinhong Park ◽  
Jinho Kim ◽  
Ji-Young Kim ◽  
Mi-Jin An ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Cell Death ◽  
Transcriptome Analysis ◽  
Caspase 3 ◽  
Apoptotic Cell ◽  
Expression Patterns ◽  
Nitrogen Compound ◽  
Apoptotic Cell Death ◽  
Mercury Chloride ◽  
Rna Seq

Mercury is one of the detrimental toxicants that can be found in the environment and exists naturally in different forms; inorganic and organic. Human exposure to inorganic mercury, such as mercury chloride, occurs through air pollution, absorption of food or water, and personal care products. This study aimed to investigate the effect of HgCl2 on cell viability, cell cycle, apoptotic pathway, and alters of the transcriptome profiles in human non-small cell lung cancer cells, H1299. Our data show that HgCl2 treatment causes inhibition of cell growth via cell cycle arrest at G0/G1- and S-phase. In addition, HgCl2 induces apoptotic cell death through the caspase-3-independent pathway. Comprehensive transcriptome analysis using RNA-seq indicated that cellular nitrogen compound metabolic process, cellular metabolism, and translation for biological processes-related gene sets were significantly up- and downregulated by HgCl2 treatment. Interestingly, comparative gene expression patterns by RNA-seq indicated that mitochondrial ribosomal proteins were markedly altered by low-dose of HgCl2 treatment. Altogether, these data show that HgCl2 induces apoptotic cell death through the dysfunction of mitochondria.

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