scholarly journals Fitnome Catalog: a resource for physical exercise genetics data mining

2021 ◽  
Vol 1 (3) ◽  
pp. 81-86
Author(s):  
Christina Pacheco Santos Martin ◽  
Stela Mirla Silva Felipe ◽  
Juliana Osório Alves ◽  
Raquel Martins de Freitas ◽  
Luis Henrique Pontes dos Santos ◽  
...  
Keyword(s):  
Gene Expression ◽  
Experimental Design ◽  
Physical Exercise ◽  
Molecular Mechanisms ◽  
Exercise Physiology ◽  
Good Health ◽  
Rna Seq ◽  
Rt Pcr ◽  
Data Points ◽  
Number Of Individuals

Physical exercise (PE) in regularity is a well-characterized non-pharmaceutical intervention for good health and welfare. Molecular mechanisms regulated in response to PE can be scrutinized, with molecular biology, genomics, transcriptomics, and bioinformatics being inserted into exercise physiology studies. From a biotechnological perspective, omic datasets about physical exercise gene expression help identify phenotypic, genetic variance for different physical training phenotypes. Extensive lists of genes regulated by PE were dispersed within the literature, and the Fitnome Catalog (FitC) was created to reach some systematization of this information. Manual and online text-mining tools generated this dataset in PE human gene expression articles (2003-2014) with microarray, RNA-Seq, RT-PCR, and genotyping methods. Spreadsheets were developed with information on exercise protocol, experimental design, gender, age, number of individuals, analytical approach, gene ID, fold change and statistical data, and genetic architecture, encompassing 21 columns. The produced dataset (with 5,147 genes and 101,343 data points) provides experimental design, gene expression information, gene attributes, and references. Functional categorization of the FitC dataset and standardized information on PE-expressed genes were presented.

scholarly journals Comparative RNA-Seq Analyses of Solenopsis japonica (Hymenoptera: Formicidae) Reveal Gene in Response to Cold Stress

Genes ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1610
Author(s):  
Mohammad Vatanparast ◽  
Youngjin Park
Keyword(s):  
Gene Expression ◽  
Cold Stress ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Predatory Behavior ◽  
P Value ◽  
Molecular Response ◽  
Rna Seq ◽  
Protein Database ◽  
Brood Chamber

Solenopsis japonica, as a fire ant species, shows some predatory behavior towards earthworms and woodlice, and preys on the larvae of other ant species by tunneling into a neighboring colony’s brood chamber. This study focused on the molecular response process and gene expression profiles of S. japonica to low (9 °C)-temperature stress in comparison with normal temperature (25 °C) conditions. A total of 89,657 unigenes (the clustered non-redundant transcripts that are filtered from the longest assembled contigs) were obtained, of which 32,782 were annotated in the NR (nonredundant protein) database with gene ontology (GO) terms, gene descriptions, and metabolic pathways. The results were 81 GO subgroups and 18 EggNOG (evolutionary genealogy of genes: Non-supervised Orthologous Groups) keywords. Differentially expressed genes (DEGs) with log2fold change (FC) > 1 and log2FC < −1 with p-value ≤ 0.05 were screened for cold stress temperature. We found 215 unigenes up-regulated and 115 unigenes down-regulated. Comparing transcriptome profiles for differential gene expression resulted in various DE proteins and genes, including fatty acid synthases and lipid metabolism, which have previously been reported to be involved in cold resistance. We verified the RNA-seq data by qPCR on 20 up- and down-regulated DEGs. These findings facilitate the basis for the future understanding of the adaptation mechanisms of S. japonica and the molecular mechanisms underlying the response to low temperatures.

scholarly journals Integrated genomic and transcriptomic analysis revealed mutation patterns of de-differentiated liposarcoma and leiomyosarcoma

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Wenshuai Liu ◽  
Hanxing Tong ◽  
Chenlu Zhang ◽  
Rongyuan Zhuang ◽  
He Guo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Sanger Sequencing ◽  
Immune Cell ◽  
Gene Copy Number ◽  
Gene Copy ◽  
Rna Seq ◽  
Loss Of Function ◽  
Rt Pcr ◽  
The Difference ◽  
Histologic Types

Abstract Background Treating patients with advanced sarcomas is challenging due to great histologic diversity among its subtypes. Leiomyosarcoma (LMS) and de-differentiated liposarcoma (DDLPS) are two common and aggressive subtypes of soft tissue sarcoma (STS). They differ significantly in histology and clinical behaviors. However, the molecular driving force behind the difference is unclear. Methods We collected 20 LMS and 12 DDLPS samples and performed whole exome sequencing (WES) to obtain their somatic mutation profiles. We also performed RNA-Seq to analyze the transcriptomes of 8 each of the LMS and DDLPS samples and obtained information about differential gene expression, pathway enrichment, immune cell infiltration in tumor microenvironment, and chromosomal rearrangement including gene fusions. Selected gene fusion events from the RNA-seq prediction were checked by RT-PCR in tandem with Sanger sequencing. Results We detected loss of function mutation and deletion of tumor suppressors mostly in LMS, and oncogene amplification mostly in DDLPS. A focal amplification affecting chromosome 12q13–15 region which encodes MDM2, CDK4 and HMGA2 is notable in DDLPS. Mutations in TP53, ATRX, PTEN, and RB1 are identified in LMS but not DDLPS, while mutation of HERC2 is only identified in DDLPS but not LMS. RNA-seq revealed overexpression of MDM2, CDK4 and HMGA2 in DDLPS and down-regulation of TP53 and RB1 in LMS. It also detected more fusion events in DDLPS than LMS (4.5 vs. 1, p = 0.0195), and the ones involving chromosome 12 in DDLPS stand out. RT-PCR and Sanger sequencing verified the majority of the fusion events in DDLPS but only one event in LMS selected to be tested. The tumor microenvironmental signatures are highly correlated with histologic types. DDLPS has more endothelial cells and fibroblasts content than LMS. Conclusions Our analysis revealed different recurrent genetic variations in LMS and DDLPS including simultaneous upregulation of gene expression and gene copy number amplification of MDM2 and CDK4. Up-regulation of tumor related genes is favored in DDLPS, while loss of suppressor function is favored in LMS. DDLPS harbors more frequent fusion events which can generate neoepitopes and potentially targeted by personalized immune treatment.

scholarly journals BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Paulo Rapazote-Flores ◽  
Micha Bayer ◽  
Linda Milne ◽  
Claus-Dieter Mayer ◽  
John Fuller ◽  
...  
Keyword(s):  
Gene Expression ◽  
Splice Junction ◽  
Rna Seq ◽  
Rt Pcr ◽  
High Quality ◽  
Transcript Quantification ◽  
Reference Transcript ◽  
Alternatively Spliced ◽  
Time Required ◽  
Comprehensive Reference

Abstract Background The time required to analyse RNA-seq data varies considerably, due to discrete steps for computational assembly, quantification of gene expression and splicing analysis. Recent fast non-alignment tools such as Kallisto and Salmon overcome these problems, but these tools require a high quality, comprehensive reference transcripts dataset (RTD), which are rarely available in plants. Results A high-quality, non-redundant barley gene RTD and database (Barley Reference Transcripts – BaRTv1.0) has been generated. BaRTv1.0, was constructed from a range of tissues, cultivars and abiotic treatments and transcripts assembled and aligned to the barley cv. Morex reference genome (Mascher et al. Nature; 544: 427–433, 2017). Full-length cDNAs from the barley variety Haruna nijo (Matsumoto et al. Plant Physiol; 156: 20–28, 2011) determined transcript coverage, and high-resolution RT-PCR validated alternatively spliced (AS) transcripts of 86 genes in five different organs and tissue. These methods were used as benchmarks to select an optimal barley RTD. BaRTv1.0-Quantification of Alternatively Spliced Isoforms (QUASI) was also made to overcome inaccurate quantification due to variation in 5′ and 3′ UTR ends of transcripts. BaRTv1.0-QUASI was used for accurate transcript quantification of RNA-seq data of five barley organs/tissues. This analysis identified 20,972 significant differentially expressed genes, 2791 differentially alternatively spliced genes and 2768 transcripts with differential transcript usage. Conclusion A high confidence barley reference transcript dataset consisting of 60,444 genes with 177,240 transcripts has been generated. Compared to current barley transcripts, BaRTv1.0 transcripts are generally longer, have less fragmentation and improved gene models that are well supported by splice junction reads. Precise transcript quantification using BaRTv1.0 allows routine analysis of gene expression and AS.

scholarly journals An animal model study on the gene expression profile of meniscal degeneration

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yehan Fang ◽  
Hui Huang ◽  
Gang Zhou ◽  
Qinghua Wang ◽  
Feng Gao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pathway Analysis ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Control Group ◽  
Ion Binding ◽  
Endoplasmic Reticulum Membrane ◽  
Rt Pcr ◽  
Go Analysis ◽  
Meniscal Degeneration

AbstractMeniscal degeneration is a very common condition in elderly individuals, but the underlying mechanisms of its occurrence are not completely clear. This study examines the molecular mechanisms of meniscal degeneration. The anterior cruciate ligament (ACL) and lateral collateral ligament (LCL) of the right rear limbs of seven Wuzhishan mini-pigs were resected (meniscal degeneration group), and the left rear legs were sham-operated (control group). After 6 months, samples were taken for gene chip analysis, including differentially expressed gene (DEG) analysis, gene ontology (GO) analysis, clustering analysis, and pathway analysis. The selected 12 DEGs were validated by real time reverse transcription-polymerase chain reaction (RT-PCR). The two groups showed specific and highly clustered DEGs. A total of 893 DEGs were found, in which 537 are upregulated, and 356 are downregulated. The GO analysis showed that the significantly affected biological processes include nitric oxide metabolic process, male sex differentiation, and mesenchymal morphogenesis, the significantly affected cellular components include the endoplasmic reticulum membrane, and the significantly affected molecular functions include transition metal ion binding and iron ion binding. The pathway analysis showed that the significantly affected pathways include type II diabetes mellitus, inflammatory mediator regulation of TRP channels, and AMPK signaling pathway. The results of RT-PCR indicate that the microarray data accurately reflects the gene expression patterns. These findings indicate that several molecular mechanisms are involved in the development of meniscal degeneration, thus improving our understanding of meniscal degeneration and provide molecular therapeutic targets in the future.

130 A CATALOG OF REFERENCE GENES WITH HIGH, MEDIUM, AND LOW LEVELS OF EXPRESSION DURING BOVINE IN VIVO PRE-IMPLANTATION DEVELOPMENT

2017 ◽  
Vol 29 (1) ◽  
pp. 173
Author(s):  
Z. Jiang ◽  
J. Sun ◽  
S. Marjani ◽  
H. Dong ◽  
X. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Genes ◽  
Target Genes ◽  
Stable Expression ◽  
Bovine Embryo ◽  
Rna Seq ◽  
Rt Pcr ◽  
Data Set ◽  
Low Expression

Appropriate reference genes for accurate normalization in RT-PCR are essential for the study of gene expression. Ideal reference genes should not only have stable expression across stages of embryo development, but also be expressed at comparable levels to the target genes. Using RNA-seq data from in vivo-produced bovine oocytes and embryos from the 2-cell to blastocyst stage (Jiang et al., 2014 BMC Genomics 15, 756), we tried to establish a catalogue of all reference genes for RT-PCR analysis. One-way ANOVA generated 4055 genes that did not differ across stages. To reduce this list, we used the entire RNA-seq data set and first removed genes with a FPKM (fragments per kilobase of transcript per million mapped reads) of <1, and then rescaled each gene’s expression values within a range of 0 to 1. We subsequently calculated the expression variance for each gene across all stages. By assuming that the calculated variances follow a Gaussian distribution and that the majority of the genes do not have a stable expression level, a gene was classified as a reference if its variance significantly deviated (P < 0.05) from these assumptions. We identified 346 potential reference genes, all of which were among the candidates from the ANOVA analysis. We arbitrarily assigned genes in this list to high (FPKM ≥ 100), medium (10 < FPKM < 100), and low expression levels (FPKM ≤ 10), and 37, 154, and 155 genes, respectively, fell into these groups. Surprisingly, none of the commonly used reference genes, such as GAPDH, PPIA, ACTB, PRL15, GUSB, and H3F2A, were identified as being stably expressed across in vivo development. This is consistent with findings of prior RT-PCR studies (Robert et al. 2002 Biol. Reprod. 67, 1465–1472; Ross et al. 2010 Cell Reprogram. 12, 709–717). The following gene ontology terms were significantly enriched for the 346 genes: cell cycle, translation, transport, chromatin, cell division, and metabolic process, indicating that the early embryos maintained constant levels of genes involved in fundamental biological functions. Finally, we performed RT-PCR to validate the RNA-seq results using different bovine in vivo-derived oocytes and embryos (n = 3/stage). We successfully validated 10 selected genes, including those in the high (CS, PGD, and ACTR3), medium (CCT5, MRPL47, COG2, CRT9, and HELLS), and low expression groups (CDC23 and TTF1). In conclusion, we recommend the use of reference genes that are expressed at comparable levels to target genes. This study offers a useful resource to aid in the appropriate selection of reference genes, which will improve the accuracy of quantitative gene expression analyses across bovine embryo pre-implantation development.

scholarly journals Transcriptome Analysis Reveals the Molecular Mechanisms Underlying Adenosine Biosynthesis in Anamorph Strain of Caterpillar Fungus

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Shan Lin ◽  
Zhicheng Zou ◽  
Cuibing Zhou ◽  
Hancheng Zhang ◽  
Zhiming Cai
Keyword(s):  
Gene Expression ◽  
Transcriptome Analysis ◽  
Molecular Mechanisms ◽  
Purine Metabolism ◽  
Expression Data ◽  
Rna Seq ◽  
Metabolism Pathway ◽  
Caterpillar Fungus ◽  
Regulated Gene Expression ◽  
Late Stages

Caterpillar fungus is a well-known fungal Chinese medicine. To reveal molecular changes during early and late stages of adenosine biosynthesis, transcriptome analysis was performed with the anamorph strain of caterpillar fungus. A total of 2,764 differentially expressed genes (DEGs) were identified (p≤0.05, |log2 Ratio| ≥ 1), of which 1,737 were up-regulated and 1,027 were down-regulated. Gene expression profiling on 4–10 d revealed a distinct shift in expression of the purine metabolism pathway. Differential expression of 17 selected DEGs which involved in purine metabolism (map00230) were validated by qPCR, and the expression trends were consistent with the RNA-Seq results. Subsequently, the predicted adenosine biosynthesis pathway combined with qPCR and gene expression data of RNA-Seq indicated that the increased adenosine accumulation is a result of down-regulation of ndk, ADK, and APRT genes combined with up-regulation of AK gene. This study will be valuable for understanding the molecular mechanisms of the adenosine biosynthesis in caterpillar fungus.

scholarly journals Epstein-Barr Virus-Induced Changes in B-Lymphocyte Gene Expression

2002 ◽  
Vol 76 (20) ◽  
pp. 10427-10436 ◽  
Author(s):  
Kara L. Carter ◽  
Ellen Cahir-McFarland ◽  
Elliott Kieff
Keyword(s):  
Gene Expression ◽  
Real Time ◽  
B Lymphocytes ◽  
Epstein Barr Virus ◽  
Molecular Mechanisms ◽  
B Lymphocyte ◽  
Protein Biosynthesis ◽  
Rt Pcr ◽  
Barr Virus ◽  
Epstein Barr

ABSTRACT To elucidate the mechanisms by which Epstein-Barr virus (EBV) latency III gene expression transforms primary B lymphocytes to lymphoblastoid cell lines (LCLs), the associated alterations in cell gene expression were assessed by using 4,146 cellular cDNAs arrayed on nitrocellulose filters and real-time reverse transcription-PCR (RT-PCR). A total of 1,405 of the 4,146 cDNAs were detected using cDNA probes from poly(A)+ RNA of IB4 LCLs, a non-EBV-infected Burkitt's lymphoma (BL) cell line, BL41, or EBV latency III-converted BL41 cells (BL41EBV). Thirty-eight RNAs were consistently twofold more abundant in the IB4 LCL and BL41EBV than in BL41 by microarray analysis. Ten of these are known to be EBV induced. A total of 23 of 28 newly identified EBV-induced genes were confirmed by real-time RT-PCR. In addition, nine newly identified genes and CD10 were EBV repressed. These EBV-regulated genes encode proteins involved in signal transduction, transcription, protein biosynthesis and degradation, and cell motility, shape, or adhesion. Seven of seven newly identified EBV-induced RNAs were more abundant in newly established LCLs than in resting B lymphocytes. Surveys of eight promoters of newly identified genes implicate NF-κB or PU.1 as potentially important mediators of EBV-induced effects through LMP1 or EBNA2, respectively. Thus, examination of the transcriptional effects of EBV infection can elucidate the molecular mechanisms by which EBV latency III alters B lymphocytes.

scholarly journals Transcriptome analysis of sevoflurane exposure effects at the different brain regions

2020 ◽  
Author(s):  
Hiroto Yamamoto ◽  
Yutaro Uchida ◽  
Tomoki Chiba ◽  
Ryota Kurimoto ◽  
Takahide Matsushima ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
Neural Development ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Transcriptional Analysis ◽  
Rna Seq ◽  
Ontology Term ◽  
Whole Brain ◽  
Differently Expressed Genes

AbstractBackgroundsSevoflurane is a most frequently used volatile anaesthetics, but its molecular mechanisms of action remain unclear. We hypothesized that specific genes play regulatory roles in whole brain exposed to sevoflurane. Thus, we aimed to evaluate the effects of sevoflurane inhalation and identify potential regulatory genes by RNA-seq analysis.MethodsEight-week old mice were exposed to sevoflurane. RNA from four medial prefrontal cortex, striatum, hypothalamus, and hippocampus were analysed using RNA-seq. Differently expressed genes were extracted. Their gene ontology terms and the transcriptome array data of the cerebral cortex of sleeping mice were analysed using Metascape, and the gene expression patterns were compared. Finally, the activities of transcription factors were evaluated using a weighted parametric gene set analysis (wPGSA). JASPAR was used to confirm the existence of binding motifs in the upstream sequences of the differently expressed genes.ResultsThe gene ontology term enrichment analysis result suggests that sevoflurane inhalation upregulated angiogenesis and downregulated neural differentiation in the whole brain. The comparison with the brains of sleeping mice showed that the gene expression changes were specific to anaesthetized mice. Sevoflurane induced Klf4 upregulation in the whole brain. The transcriptional analysis result suggests that KLF4 is a potential transcriptional regulator of angiogenesis and neural development.ConclusionsKlf4 was upregulated by sevoflurane inhalation in whole brain. KLF4 might promote angiogenesis and cause the appearance of undifferentiated neural cells by transcriptional regulation. The roles of KLF4 might be key to elucidating the mechanisms of sevoflurane induced functional modification in the brain.

scholarly journals Full Length Transcriptome Highlights the Coordination of Plastid Transcript Processing

2021 ◽  
Author(s):  
Marine Guilcher ◽  
Arnaud Liehrmann ◽  
Chloé Seyman ◽  
Thomas Blein ◽  
Guillem Rigaill ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Full Length ◽  
Nanopore Sequencing ◽  
Rna Seq ◽  
Plastid Gene ◽  
Plastid Gene Expression ◽  
Short Read ◽  
Transcript Processing

Plastid gene expression involves many post-transcriptional maturation steps resulting in a complex transcriptome composed of multiple isoforms. Although short read RNA-seq has considerably improved our understanding of the molecular mechanisms controlling these processes, it is unable to sequence full-length transcripts. This information is however crucial when it comes to understand the interplay between the various steps of plastid gene expression. Here, the study of the Arabidopsis leaf plastid transcriptome using Nanopore sequencing showed that many splicing and editing events were not independent but co-occurring. For a given transcript, maturation events also appeared to be chronologically ordered with splicing happening after most sites are edited.

scholarly journals Chromatin-enriched RNAs mark active and repressive cis-regulation: an analysis of nuclear RNA-seq

2019 ◽  
Author(s):  
Xiangying Sun ◽  
Zhezhen Wang ◽  
Carlos Perez-Cervantes ◽  
Alex Ruthenburg ◽  
Ivan Moskowitz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Noncoding Rna ◽  
Molecular Mechanisms ◽  
Specific Gene ◽  
Rna Seq ◽  
Cell Type ◽  
Neighboring Gene ◽  
Cis Regulation ◽  
Nuclear Rna ◽  
Cell Type Specific

AbstractLong noncoding RNAs (lncRNAs) localize in the cell nucleus and influence gene expression through a variety of molecular mechanisms. RNA sequencing of two biochemical fractions of nuclei reveals a unique class of lncRNAs, termed chromatin-enriched nuclear RNAs (cheRNAs) that are tightly bound to chromatin and putatively function to cis-activate gene expression. Until now, a rigorous analytic pipeline for nuclear RNA-seq has been lacking. In this study, we survey four computational strategies for nuclear RNA-seq data analysis and show that a new pipeline, Tuxedo, outperforms other approaches. Tuxedo not only assembles a more complete transcriptome, but also identifies cheRNA with higher accuracy. We have used Tuxedo to analyze gold-standard K562 cell datasets and further characterize the genomic features of intergenic cheRNA (icheRNA) and their similarity to those of enhancer RNA (eRNA). Moreover, we quantify the transcriptional correlation of icheRNA and adjacent genes, and suggest that icheRNA may be the cis-acting transcriptional regulator that is more positively associated with neighboring gene expression than eRNA predicted by state-of-art method or CAGE signal. We also explore two novel genomic associations, suggesting cheRNA may have diverse functions. A possible new role of H3K9me3 modification coincident with icheRNA may be associated with active enhancer derived from ancient mobile elements, while a potential cis-repressive function of antisense cheRNA (as-cheRNA) is likely to be involved in transiently modulating cell type-specific cis-regulation.Author SummaryChromatin-enriched nuclear RNA (cheRNA) is a class of gene regulatory non-coding RNAs. CheRNA provides a powerful way to profile the nuclear transcriptional landscape, especially to profile the noncoding transcriptome. The computational framework presented here provides a reliable approach to identifying cheRNA, and for studying cell-type specific gene regulation. We found that intergenic cheRNA, including intergenic cheRNA with high levels of H3K9me3 (a mark associated with closed/repressed chromatin), may act as a transcriptional activator. In contrast, antisense cheRNA, which originates from the complementary strand of the protein-coding gene, may interact with diverse chromatin modulators to repress local transcription. With our new pipeline, one future challenge will be refining the functional mechanisms of these noncoding RNA classes through exploring their regulatory roles, which are involved in diverse molecular and cellular processes in human and other organisms.

Sign in / Sign up

Export Citation Format

Share Document