scholarly journals Characterization of the rat developmental liver transcriptome

2013 ◽  
Vol 45 (8) ◽  
pp. 301-311 ◽  
Author(s):  
Richard H. Chapple ◽  
Polyana C. Tizioto ◽  
Kevin D. Wells ◽  
Scott A. Givan ◽  
JaeWoo Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput Sequencing ◽  
Mitochondrial Gene ◽  
Probe Design ◽  
Rna Seq ◽  
Illumina Hiseq ◽  
Biologically Relevant ◽  
Gradual Process ◽  
Intergenic Regions ◽  
Sequencing Platforms

Gene regulation and transcriptome studies have been enabled by the development of RNA-Seq applications for high-throughput sequencing platforms. Next generation sequencing is remarkably efficient and avoids many issues inherent in hybridization-based microarray methodologies including the exon-specific dependence of probe design. Biologically relevant transcripts including messenger and regulatory RNAs may now be quantified and annotated regardless of whether they have previously been observed. We used RNA-Seq to investigate global patterns of gene expression in early developing rat liver. Liver samples from timed-pregnant Lewis rats were collected at six fetal and neonatal stages [embryonic day (E)14, E16, E18, E20, postnatal day (P)1, P7], transcripts were sequenced using an Illumina HiSeq 2000, and data analysis was performed with the Tuxedo software suite. Genes and isoforms differing in abundance were queried for enrichment within functionally related gene groups using the Functional Annotation Tool of the DAVID Bioinformatics Database. While hematopoietic gene expression is initiated by E14, hepatocyte maturation is a gradual process involving clusters of genes responsible for response to nutrients and enzymes responsible for glycolysis and fatty acid catabolism. Following birth, a large cluster of differentially abundant genes was enriched for mitochondrial gene expression and cholesterol synthesis indicating that by 1 wk of age, the liver is engaged in lipid sensing and bile production. Clustering results for differentially abundant genes and isoforms were similar with the greatest difference for the E14/E16 comparison. Finally, a bioinformatic approach was used to annotate 1,307 novel liver transcripts assembled from sequences that aligned to intergenic regions of the rat genome.

Comparative analysis of sequencing technologies platforms for single-cell transcriptomics

2018 ◽  
Author(s):  
Kedar Nath Natarajan ◽  
Zhichao Miao ◽  
Miaomiao Jiang ◽  
Xiaoyun Huang ◽  
Hongpo Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Cells ◽  
K562 Cells ◽  
Library Preparation ◽  
Rna Seq ◽  
Illumina Hiseq ◽  
Technical Variability ◽  
Sequencing Technologies ◽  
Sequencing Platforms

AbstractAll single-cell RNA-seq protocols and technologies require library preparation prior to sequencing on a platform such as Illumina. Here, we present the first report to utilize the BGISEQ-500 platform for scRNA-seq, and compare the sensitivity and accuracy to Illumina sequencing. We generate a scRNA-seq resource of 468 unique single-cells and 1,297 matched single cDNA samples, performing SMARTer and Smart-seq2 protocols on mESCs and K562 cells with RNA spike-ins. We sequence these libraries on both BGISEQ-500 and Illumina HiSeq platforms using single- and paired-end reads. The two platforms have comparable sensitivity and accuracy in terms of quantification of gene expression, and low technical variability. Our study provides a standardised scRNA-seq resource to benchmark new scRNA-seq library preparation protocols and sequencing platforms.

scholarly journals Ancient RNA from Late Pleistocene permafrost and historical canids shows tissue-specific transcriptome survival

2019 ◽  
Author(s):  
Oliver Smith ◽  
Glenn Dunshea ◽  
Mikkel-Holger S. Sinding ◽  
Sergey Fedorov ◽  
Mietje Germonpre ◽  
...  
Keyword(s):  
Ribosomal Rna ◽  
High Throughput Sequencing ◽  
Rna Seq ◽  
Biologically Relevant ◽  
Archaeological Material ◽  
Tissue Identification ◽  
Mammalian Tissues ◽  
Sequencing Platforms ◽  
Genome Activity

AbstractWhile sequencing ancient DNA from archaeological material is now commonplace, very few attempts to sequence ancient transcriptomes have been made, even from typically stable deposition environments such as permafrost. This is presumably due to assumptions that RNA completely degrades relatively quickly, particularly when dealing with autolytic, nuclease-rich mammalian tissues. However, given the recent successes in sequencing ancient RNA (aRNA) from various sources including plants and animals, we suspect that these assumptions may be incorrect or exaggerated. To challenge the underlying dogma, we generated shotgun RNA data from sources that might normally be dismissed for such study. Here we present aRNA data generated from two historical wolf skins, and permafrost-preserved liver tissue of a 14,300-year-old Pleistocene canid. Not only is the latter the oldest RNA ever to be sequenced, but also shows evidence of biologically relevant tissue-specificity and close similarity to equivalent data derived from modern-day control tissue. Other hallmarks of RNA-seq data such as exon-exon junction presence and high endogenous ribosomal RNA content confirms our data’s authenticity. By performing independent technical replicates using two high-throughput sequencing platforms, we show not only that aRNA can survive for extended periods in mammalian tissues, but also that it has potential for tissue identification, and possibly further uses such as in vivo genome activity and adaptation, when sequenced using this technology.

scholarly journals Mitochondrial Mistranslation in Brain Provokes a Metabolic Response Which Mitigates the Age-Associated Decline in Mitochondrial Gene Expression

2021 ◽  
Vol 22 (5) ◽  
pp. 2746
Author(s):  
Dimitri Shcherbakov ◽  
Reda Juskeviciene ◽  
Adrián Cortés Sanchón ◽  
Margarita Brilkova ◽  
Hubert Rehrauer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Metabolic Response ◽  
Mitochondrial Gene ◽  
Tca Cycle ◽  
Brain Mitochondria ◽  
Mitochondrial Gene Expression ◽  
Rna Seq ◽  
The Tca Cycle ◽  
Neurological Phenotype

Mitochondrial misreading, conferred by mutation V338Y in mitoribosomal protein Mrps5, in-vivo is associated with a subtle neurological phenotype. Brain mitochondria of homozygous knock-in mutant Mrps5V338Y/V338Y mice show decreased oxygen consumption and reduced ATP levels. Using a combination of unbiased RNA-Seq with untargeted metabolomics, we here demonstrate a concerted response, which alleviates the impaired functionality of OXPHOS complexes in Mrps5 mutant mice. This concerted response mitigates the age-associated decline in mitochondrial gene expression and compensates for impaired respiration by transcriptional upregulation of OXPHOS components together with anaplerotic replenishment of the TCA cycle (pyruvate, 2-ketoglutarate).

scholarly journals RNA-Seq-Based Analysis of Cortisol-Induced Differential Gene Expression Associated with Piscirickettsia salmonis Infection in Rainbow Trout (Oncorhynchus mykiss) Myotubes

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2399
Author(s):  
Rodrigo Zuloaga ◽  
Phillip Dettleff ◽  
Macarena Bastias-Molina ◽  
Claudio Meneses ◽  
Claudia Altamirano ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Proliferation ◽  
Rainbow Trout ◽  
Enrichment Analysis ◽  
Rna Seq ◽  
Illumina Hiseq ◽  
Transcriptomic Response ◽  
Bacterial Gene ◽  
Intensive Farming ◽  
Piscirickettsia Salmonis

Salmonid rickettsial septicemia (SRS) is the major infectious disease of the Chilean salmonid aquaculture industry caused by Piscirickettsia salmonis. Intensive farming conditions generate stress and increased susceptibility to diseases, being skeletal muscle mainly affected. However, the interplay between pathogen infection and stress in muscle is poorly understood. In this study, we perform an RNA-seq analysis on rainbow trout myotubes that are pretreated for 3 h with cortisol (100 ng/mL) and then infected with P. salmonis strain LF-89 for 8 h (MOI 50). Twelve libraries are constructed from RNA samples (n = 3 per group) and sequenced on Illumina HiSeq 4000. A total of 704,979,454 high-quality reads are obtained, with 70.25% mapped against the reference genome. In silico DETs include 175 total genes—124 are upregulated and 51 are downregulated. GO enrichment analysis reveals highly impacted biological processes related to apoptosis, negative regulation of cell proliferation, and innate immune response. These results are validated by RT-qPCR of nine candidate transcripts. Furthermore, cortisol pretreatment significantly stimulated bacterial gene expression of ahpC and 23s compared to infection. In conclusion, for the first time, we describe a transcriptomic response of trout myotubes infected with P. salmonis by inducing apoptosis, downregulating cell proliferation, and intrinsic immune-like response that is differentially regulated by cortisol.

scholarly journals Transcriptome-based Selection and Validation of Optimal House-keeping Genes for Skin Research in Goats (Capra hircus)

2020 ◽  
Author(s):  
Jipan Zhang ◽  
Chengchen Deng ◽  
Jialu Li ◽  
Yong-Ju Zhao
Keyword(s):  
Gene Expression ◽  
Target Gene ◽  
High Throughput Sequencing ◽  
Comprehensive Analysis ◽  
Skin Tissue ◽  
Capra Hircus ◽  
Meat Industry ◽  
Rna Seq ◽  
Tissue Samples ◽  
Target Gene Expression

Abstract Background : In quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression results are dependent on optimal amplification of house-keeping genes (HKGs). RNA-seq technology offers a novel approach to detect new HKGs with improved stability. Goat ( Capra hircus ) is an economically important livestock species and plays an indispensable role in the world animal fiber and meat industry. Unfortunately, uniform and reliable HKGs for skin research have not been identified in goat. Therefore, this study seeks to identify a set of stable HKGs for the skin tissue of C. hircus using high-throughput sequencing technology. Results: Based on the transcriptome dataset of 39 goat skin tissue samples, 8 genes ( SRP68 , NCBP3 , RRAGA , EIF4H , CTBP2 , PTPRA , CNBP , and EEF2 ) with relatively stable expression levels were identified and selected as new candidate HKGs. Commonly used HKGs including SDHA and YWHAZ from a previous study, and 2 conventional genes ( ACTB and GAPDH ) were also examined. Four different experimental variables: (1) different development stages, (2) hair follicle cycle stages, (3) breeds, and (4) sampling sites were used for determination and validation. Four algorithms (geNorm, NormFinder, BestKeeper, and ΔCt method) and a comprehensive algorithm (ComprFinder, developed in-house) were used to assess the stability of each HKG. It was shown that NCBP3+SDHA+PTPRA were more stably expressed than previously used genes in all conditions analysis, and that this combination was effective at normalizing target gene expression. Moreover, a new algorithm for comprehensive analysis, ComprFinder, was developed and released. Conclusion: This study presents the first list of candidate HKGs for C. hircus skin tissues based on an RNA-seq dataset. We propose that the NCBP3+SDHA+PTPRA combination could be regarded as a triplet set of HKGs in skin molecular biology experiments in C. hircus and other closely related species. In addition, we also encourage researchers who perform candidate HKG evaluations and who require comprehensive analysis to adopt our new algorithm, ComprFinder.

scholarly journals Cobolt: integrative analysis of multimodal single-cell sequencing data

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Boying Gong ◽  
Yun Zhou ◽  
Elizabeth Purdom
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Chromatin Accessibility ◽  
Integrative Analysis ◽  
Rna Seq ◽  
Sequencing Data ◽  
Single Cell Sequencing ◽  
Multiple Datasets ◽  
Novel Method ◽  
Sequencing Platforms

AbstractA growing number of single-cell sequencing platforms enable joint profiling of multiple omics from the same cells. We present , a novel method that not only allows for analyzing the data from joint-modality platforms, but provides a coherent framework for the integration of multiple datasets measured on different modalities. We demonstrate its performance on multi-modality data of gene expression and chromatin accessibility and illustrate the integration abilities of by jointly analyzing this multi-modality data with single-cell RNA-seq and ATAC-seq datasets.

scholarly journals Sexual dimorphism of the pulmonary transcriptome in neonatal hyperoxic lung injury: identification of angiogenesis as a key pathway

2017 ◽  
Vol 313 (6) ◽  
pp. L991-L1005 ◽  
Author(s):  
Cristian Coarfa ◽  
Yuhao Zhang ◽  
Suman Maity ◽  
Dimuthu N. Perera ◽  
Weiwu Jiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Injury ◽  
Mrna Level ◽  
Sexually Dimorphic ◽  
Rna Seq ◽  
Illumina Hiseq ◽  
Data Set ◽  
Vascular Growth ◽  
Hyperoxic Lung Injury ◽  
High Concentrations

Bronchopulmonary dysplasia (BPD) is characterized by impaired alveolar secondary septation and vascular growth. Exposure to high concentrations of oxygen (hyperoxia) contributes to the development of BPD. The male sex is considered an independent risk factor for the development of BPD. The reasons underlying sexually dimorphic outcomes in premature neonates are not known. We hypothesized that sex-specific modulation of biological processes in the lung under hyperoxic conditions contributes to sex-based differences. Neonatal male and female mice (C57BL/6) were exposed to hyperoxia [95% [Formula: see text], postnatal day (PND) 1–5: saccular stage of lung development] and euthanized on PND 7 or 21. Pulmonary gene expression was studied using RNA-Seq on the Illumina HiSeq 2500 platform. Analysis of the pulmonary transcriptome revealed differential sex-specific modulation of crucial pathways such as angiogenesis, response to hypoxia, inflammatory response, and p53 pathway. Candidate genes from these pathways were validated at the mRNA level by qPCR. Analysis also revealed sex-specific differences in the modulation of crucial transcription factors. Focusing on the differential modulation of the angiogenesis pathway, we also showed sex-specific differential activation of Hif-1α-regulated genes using ChIP-qPCR and differences in expression of crucial genes ( Vegf, VegfR2, and Phd2) modulating angiogenesis. We demonstrate the translational relevance of our findings by showing that our murine sex-specific differences in gene expression correlate with those from a preexisting human BPD data set. In conclusion, we provide novel molecular insights into differential sex-specific modulation of the pulmonary transcriptome in neonatal hyperoxic lung injury and highlight angiogenesis as one of the crucial differentially modulated pathways.

ISOFORM ABUNDANCE INFERENCE PROVIDES A MORE ACCURATE ESTIMATION OF GENE EXPRESSION LEVELS IN RNA-SEQ

2010 ◽  
Vol 08 (supp01) ◽  
pp. 177-192 ◽  
Author(s):  
XI WANG ◽  
ZHENGPENG WU ◽  
XUEGONG ZHANG
Keyword(s):  
Gene Expression ◽  
High Throughput Sequencing ◽  
Transcript Abundance ◽  
Accurate Estimation ◽  
Rna Seq ◽  
Estimation Errors ◽  
Expression Levels ◽  
Or Gene ◽  
Read Distribution ◽  
Gene Expression Levels

Due to its unprecedented high-resolution and detailed information, RNA-seq technology based on next-generation high-throughput sequencing significantly boosts the ability to study transcriptomes. The estimation of genes' transcript abundance levels or gene expression levels has always been an important question in research on the transcriptional regulation and gene functions. On the basis of the concept of Reads Per Kilo-base per Million reads (RPKM), taking the union-intersection genes (UI-based) and summing up inferred isoform abundance (isoform-based) are the two current strategies to estimate gene expression levels, but produce different estimations. In this paper, we made the first attempt to compare the two strategies' performances through a series of simulation studies. Our results showed that the isoform-based method gives not only more accurate estimation but also has less uncertainty than the UI-based strategy. If taking into account the non-uniformity of read distribution, the isoform-based method can further reduce estimation errors. We applied both strategies to real RNA-seq datasets of technical replicates, and found that the isoform-based strategy also displays a better performance. For a more accurate estimation of gene expression levels from RNA-seq data, even if the abundance levels of isoforms are not of interest, it is still better to first infer the isoform abundance and sum them up to get the expression level of a gene as a whole.

scholarly journals intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data

BMC Genomics ◽  
2020 ◽  
Vol 21 (S11) ◽  
Author(s):  
Yingying Cao ◽  
Simo Kitanovski ◽  
Daniel Hoffmann
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
High Throughput Sequencing ◽  
Differential Expression Analysis ◽  
Cell Types ◽  
R Package ◽  
Integrative Approach ◽  
Integrated Analysis ◽  
Data Sets ◽  
Rna Seq

Abstract Background RNA-Seq, the high-throughput sequencing (HT-Seq) of mRNAs, has become an essential tool for characterizing gene expression differences between different cell types and conditions. Gene expression is regulated by several mechanisms, including epigenetically by post-translational histone modifications which can be assessed by ChIP-Seq (Chromatin Immuno-Precipitation Sequencing). As more and more biological samples are analyzed by the combination of ChIP-Seq and RNA-Seq, the integrated analysis of the corresponding data sets becomes, theoretically, a unique option to study gene regulation. However, technically such analyses are still in their infancy. Results Here we introduce intePareto, a computational tool for the integrative analysis of RNA-Seq and ChIP-Seq data. With intePareto we match RNA-Seq and ChIP-Seq data at the level of genes, perform differential expression analysis between biological conditions, and prioritize genes with consistent changes in RNA-Seq and ChIP-Seq data using Pareto optimization. Conclusion intePareto facilitates comprehensive understanding of high dimensional transcriptomic and epigenomic data. Its superiority to a naive differential gene expression analysis with RNA-Seq and available integrative approach is demonstrated by analyzing a public dataset.

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