scholarly journals Long-read isoform sequencing reveals tissue-specific isoform expression between active and hibernating brown bears (Ursus arctos)

2021 ◽  
Author(s):  
Elizabeth Tseng ◽  
Jason G Underwood ◽  
Brandon D Evans Hutzenbiler ◽  
Shawn Trojahn ◽  
Brewster Kingham ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Ursus Arctos ◽  
Differentially Expressed ◽  
Human Diseases ◽  
Sequencing Data ◽  
Mrna Isoforms ◽  
Brown Bears ◽  
Active Season ◽  
Urine Production ◽  
Isoform Expression

Abstract Understanding hibernation in brown bears (Ursus arctos) can provide insight into some human diseases. During hibernation, brown bears experience periods of insulin resistance, physical inactivity, extreme bradycardia, obesity, and the absence of urine production. These states closely mimic aspects of human diseases such as type 2 diabetes, muscle atrophy, as well as renal and heart failure. The reversibility of these states from hibernation to active season enables the identification of mediators with possible therapeutic value for humans. Recent studies have identified genes and pathways that are differentially expressed between active and hibernation seasons. However, little is known about the role of differential expression of gene isoforms on hibernation physiology. To identify both distinct and novel mRNA isoforms, full-length RNA-sequencing (Iso-Seq) was performed on adipose, skeletal muscle, and liver from three individuals sampled during both active and hibernation seasons. The existing reference annotation was improved by combining it with the Iso-Seq data. Short-read RNA-sequencing data from six individuals was mapped to the new reference annotation to quantify differential isoform usage between tissues and seasons. We identified differentially expressed isoforms in all three tissues, to varying degrees. Adipose had a high level of differential isoform usage with isoform switching, regardless of whether the genes were differentially expressed. Our analyses revealed that differential isoform usage, even in the absence of differential gene expression, is an important mechanism for modulating genes during hibernation. These findings demonstrate the value of isoform expression studies and will serve as the basis for deeper exploration into hibernation biology.

scholarly journals Long-read isoform sequencing reveals tissue-specific isoform expression between active and hibernating brown bears (Ursus arctos)

2021 ◽  
Author(s):  
Elizabeth Tseng ◽  
Jason G. Underwood ◽  
Brandon D. Evans Hutzenbiler ◽  
Shawn Trojahn ◽  
Brewster Kingham ◽  
...  
Keyword(s):  
Ursus Arctos ◽  
Comprehensive Evaluation ◽  
Differentially Expressed ◽  
Human Diseases ◽  
Mrna Isoforms ◽  
Brown Bears ◽  
Active Season ◽  
Urine Production ◽  
Long Read ◽  
Isoform Expression

Understanding hibernation in brown bears (Ursus arctos) can provide insight into many human diseases. During hibernation, brown bears experience states of insulin resistance, physical inactivity, extreme bradycardia, obesity, and the absence of urine production. These states closely mimic human diseases such as type 2 diabetes, muscle atrophy, renal and heart failure, cachexia, and obesity. The reversibility of these states from hibernation to active season allows for the identification of novel mediators with possible therapeutic value for humans. Recent studies have identified genes and pathways that are differentially expressed between active and hibernation seasons. However, little is known about the role of differential expression of gene isoforms on hibernation physiology. To identify both distinct and novel mRNA isoforms, we performed full-length RNA-sequencing (Iso-Seq) on three tissue types from three individuals sampled during both active and hibernation seasons. We combined the long-read data with the reference annotation for an improved transcriptome and mapped RNA-seq data from six individuals to the improved transcriptome to quantify differential isoform usage between tissues and seasons. We identified differentially expressed isoforms in all study tissues and showed that adipose has a high level of differential isoform usage with isoform switching, regardless of whether the genes were differentially expressed. Our analyses provide a comprehensive evaluation of isoform usage between active and hibernation states, revealing that differential isoform usage, even in the absence of differential gene expression, is an important mechanism for modulating genes during hibernation. These findings demonstrate the value of isoform expression studies and will serve as the basis for deeper exploration into hibernation biology.

Identification of Differentially Expressed and Spliced Genes with RNA Sequencing Analysis of CLL Specimens

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 4582-4582
Author(s):  
Wei Liao ◽  
Gwen Jordaan ◽  
Artur Jaroszewicz ◽  
Matteo Pellegrini ◽  
Sanjai Sharma
Keyword(s):  
B Cells ◽  
Rna Sequencing ◽  
Differentially Expressed Genes ◽  
Fold Change ◽  
Differentially Expressed ◽  
Pcr Analysis ◽  
Sequencing Analysis ◽  
Rna Seq ◽  
Mrna Isoforms ◽  
Core Set

Abstract Abstract 4582 High throughput sequencing of cellular mRNA provides a comprehensive analysis of the transcriptome. Besides identifying differentially expressed genes in different cell types, it also provides information of mRNA isoforms and splicing alterations. We have analyzed two CLL specimens and a normal peripheral blood B cells mRNA by this approach and performed data analysis to identify differentially expressed and spliced genes. The result showed CLLs specimens express approximately 40% more transcripts compared to normal B cells. The FPKM data (fragment per kilobase of exon per million) revealed a higher transcript expression on chromosome 12 in CLL#1 indicating the presence of trisomy 12, which was confirmed by fluorescent in-situ hybridization assay. With a two-fold change in FPKM as a cutoff and a p value cutoff of 0.05 as compared to the normal B cell control, 415 genes and 174 genes in CLL#1 and 676 and 235 genes in CLL#2 were up and downregulated or differentially expressed. In these two CLL specimens, 45% to 75% of differentially expressed genes are common to both the CLL specimens indicating that genetically disparate CLL specimens have a high percentage of a core set of genes that are potentially important for CLL biology. Selected differentially expressed genes with increased expression (selectin P ligand, SELPLG, and adhesion molecule interacts with CXADR antigen 1, AMICA) and decreased (Fos, Jun, CD69 and Rhob) expression based on the FPKM from RNA-sequencing data were also analyzed in additional CLL specimens by real time PCR analysis. The expression data from RNA-seq closely matches the fold-change in expression as measured by RT-PCR analysis and confirms the validity of the RNA-seq analysis. Interestingly, Fos was identified as one of the most downregulated gene in CLL. Using the Cufflinks and Cuffdiff software, the splicing patterns of genes in CLL specimens and normal B cells were analyzed. Approximately, 1100 to 1250 genes in the two CLL specimens were significantly differentially spliced as compared to normal B cells. In this analysis as well, there is a core set of 800 common genes which are differentially spliced in the two CLL specimens. The RNA-sequencing analysis accurately identifies differentially expressed novel genes and splicing variations that will help us understand the biology of CLL. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Functional module detection through integration of single-cell RNA sequencing data with protein–protein interaction networks

2019 ◽  
Author(s):  
Florian Klimm ◽  
Enrique M. Toledo ◽  
Thomas Monfeuga ◽  
Fang Zhang ◽  
Charlotte M. Deane ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Protein Interaction ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Differentially Expressed ◽  
Sequencing Data ◽  
Protein Protein Interaction ◽  
Single Cell Rna Sequencing ◽  
Protein Protein Interaction Networks

AbstractRecent advances in single-cell RNA sequencing (scRNA-seq) have allowed researchers to explore transcriptional function at a cellular level. In this study, we present scPPIN, a method for integrating single-cell RNA sequencing data with protein–protein interaction networks (PPINs) that detects active modules in cells of different transcriptional states. We achieve this by clustering RNA-sequencing data, identifying differentially expressed genes, constructing node-weighted PPINs, and finding the maximum-weight connected subgraphs with an exact Steiner-tree approach. As a case study, we investigate RNA-sequencing data from human liver spheroids but the techniques described here are applicable to other organisms and tissues. scPPIN allows us to expand the output of differential expressed genes analysis with information from protein interactions. We find that different transcriptional states have different subnetworks of the PPIN significantly enriched which represent biological pathways. In these pathways, scPPIN also identifies proteins that are not differentially expressed but have a crucial biological function (e.g., as receptors) and therefore reveals biology beyond a standard differentially expressed gene analysis.

scholarly journals Integrated Analysis of Dysregulated microRNA and mRNA Expression in Intestinal Epithelial Cells following Ethanol Intoxication and Burn Injury

2021 ◽  
Author(s):  
Caroline Herrnreiter ◽  
Xiaoling Li ◽  
Marisa Luck ◽  
Michael Zilliox ◽  
Mashkoor Choudhry
Keyword(s):  
Epithelial Cells ◽  
Rna Sequencing ◽  
Burn Injury ◽  
Intestinal Epithelial Cells ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Intestinal Epithelial ◽  
Sequencing Data ◽  
Gut Barrier ◽  
Gut Barrier Function

Abstract Gut barrier dysfunction is often implicated in pathology following alcohol intoxication and burn injury. MicroRNAs (miRNAs) are negative regulators of gene expression that play a central role in gut homeostasis, although their role after alcohol and burn injury is poorly understood. We performed an integrated analysis of miRNA and RNA sequencing data to identify a network of interactions within small intestinal epithelial cells (IECs) which could promote gut barrier disruption. Mice were gavaged with ~ 2.9 g/Kg ethanol and four hours later given a ~ 12.5% TBSA full thickness scald injury. One day later, IECs were harvested and total RNA extracted for RNA-seq and miRNA-sEq. RNA sequencing showed 712 differentially expressed genes (DEGs) (padj < 0.05) in IECs following alcohol and burn injury. Furthermore, miRNA sequencing revealed 17 differentially expressed miRNAs (DEMs) (padj < 0.1). Utilizing the miRNet, miRDB and TargetScan databases, we identified both validated and predicted miRNA gene targets. Integration of small RNA sequencing data with mRNA sequencing results identified correlated changes in miRNA and target expression. Overall, these findings suggest that alcohol and burn injury significantly alters the mRNA and miRNA expression profile of IECs and reveals numerous miRNA-mRNA interactions that regulate critical pathways for gut barrier function after alcohol and burn injury.

scholarly journals Hibernation induces widespread transcriptional remodeling in metabolic tissues of the grizzly bear

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Heiko T. Jansen ◽  
Shawn Trojahn ◽  
Michael W. Saxton ◽  
Corey R. Quackenbush ◽  
Brandon D. Evans Hutzenbiler ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Ursus Arctos ◽  
Muscle Protein ◽  
Animal Health ◽  
Gene Families ◽  
Differentially Expressed ◽  
Grizzly Bear ◽  
Active Season ◽  
Expression Of Genes ◽  
Transcriptional Changes

AbstractRevealing the mechanisms underlying the reversible physiology of hibernation could have applications to both human and animal health as hibernation is often associated with disease-like states. The present study uses RNA-sequencing to reveal the tissue and seasonal transcriptional changes occurring in grizzly bears (Ursus arctos horribilis). Comparing hibernation to other seasons, bear adipose has a greater number of differentially expressed genes than liver and skeletal muscle. During hyperphagia, adipose has more than 900 differentially expressed genes compared to active season. Hibernation is characterized by reduced expression of genes associated with insulin signaling, muscle protein degradation, and urea production, and increased expression within muscle protein anabolic pathways. Across all three tissues we find a subset of shared differentially expressed genes, some of which are uncharacterized, that together may reflect a common regulatory mechanism. The identified gene families could be useful for developing novel therapeutics to treat human and animal diseases.

scholarly journals Functional module detection through integration of single-cell RNA sequencing data with protein–protein interaction networks

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Florian Klimm ◽  
Enrique M. Toledo ◽  
Thomas Monfeuga ◽  
Fang Zhang ◽  
Charlotte M. Deane ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Protein Interaction ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Differentially Expressed ◽  
Sequencing Data ◽  
Protein Protein Interaction ◽  
Single Cell Rna Sequencing ◽  
Protein Protein Interaction Networks

Abstract Background Recent advances in single-cell RNA sequencing have allowed researchers to explore transcriptional function at a cellular level. In particular, single-cell RNA sequencing reveals that there exist clusters of cells with similar gene expression profiles, representing different transcriptional states. Results In this study, we present scPPIN, a method for integrating single-cell RNA sequencing data with protein–protein interaction networks that detects active modules in cells of different transcriptional states. We achieve this by clustering RNA-sequencing data, identifying differentially expressed genes, constructing node-weighted protein–protein interaction networks, and finding the maximum-weight connected subgraphs with an exact Steiner-tree approach. As case studies, we investigate two RNA-sequencing data sets from human liver spheroids and human adipose tissue, respectively. With scPPIN we expand the output of differential expressed genes analysis with information from protein interactions. We find that different transcriptional states have different subnetworks of the protein–protein interaction networks significantly enriched which represent biological pathways. In these pathways, scPPIN identifies proteins that are not differentially expressed but have a crucial biological function (e.g., as receptors) and therefore reveals biology beyond a standard differential expressed gene analysis. Conclusions The introduced scPPIN method can be used to systematically analyse differentially expressed genes in single-cell RNA sequencing data by integrating it with protein interaction data. The detected modules that characterise each cluster help to identify and hypothesise a biological function associated to those cells. Our analysis suggests the participation of unexpected proteins in these pathways that are undetectable from the single-cell RNA sequencing data alone. The techniques described here are applicable to other organisms and tissues.

Age-related differences in gene expression in colorectal cancer (CRC).

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 654-654
Author(s):  
Raphael M Byrne ◽  
Rebecca Ruhl ◽  
Christian Lanciault ◽  
Sudarshan Anand ◽  
Abhinav Nellore ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Rna Sequencing ◽  
Young Patients ◽  
Young Group ◽  
Fold Change ◽  
Differentially Expressed ◽  
Mouse Tumor ◽  
Sequencing Data ◽  
Old Patients

654 Background: Colorectal cancer (CRC) in young patients is increasing in incidence and is associated with worse outcomes than CRC in older patients. While distinct molecular subtypes of CRC have been recently characterized, it is unclear whether there are molecular differences between the tumors of young and old patients. We sought to identify differences in gene expression of CRC between these two groups. Our discovery analysis identified a gene signature of several differentially expressed RNAs, from which we validated PEG10. The PEG10 gene on chromosome 7q21.3 has been implicated in liver, gallbladder, thyroid, and blood cancers, and is thought to play a role in cancer cell survival and regulation of apoptosis. In hepatocellular carcinoma, increased PEG10 expression has been associated with younger patient age. Methods: RNA sequencing data was obtained from The Cancer Genome Atlas (TCGA) and analyzed for differences in gene expression between patients ≤ 45 years old and those ≥ 65 years old. The identified differentially expressed genes were then validated with qPCR using human CRC tissue from patients ≤ 45 years old and those ≥ 65 years old. Results: RNA sequencing data from patients ≤ 45 years old (n = 29) and patients ≥ 65 years old (n = 299) identified seven genes with increased expression in younger patients: ZNF334 (log2 [fold change] = 2.30), DSC3 (1.78), PEG10 (1.67), CACNA1I (1.54), PKIA (1.33), MAP9 (1.27), and EPHX3 (1.17) (p < 0.07). Validation with qPCR for PEG10 was most promising, and was performed on both young (n = 10, mean age = 39) and old patient samples ( n= 8, mean age = 72). Two cancers (20%) in the young group received radiation treatment and five (50%) received chemotherapy. One cancer (12.5%) in the old group received radiation and two (25%) received chemotherapy. PEG10 had increased expression in the young group with log2 [fold change] = 3.16 (p < 0.02). Conclusions: We have identified a potentially unique gene expression signature for CRC in young patients, which includes PEG10. Functional analysis of PEG10 and other genes is underway using in vitro cell culture, archived human tumor tissue, and mouse tumor models.

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