scholarly journals Manganese Treatment Alleviates Zinc Deficiency Symptoms in Arabidopsis Seedlings

2020 ◽  
Vol 61 (10) ◽  
pp. 1711-1723
Author(s):  
Sayuri Nakayama ◽  
Shigeo S Sugano ◽  
Haruna Hirokawa ◽  
Izumi C Mori ◽  
Hiroyuki Daimon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Basal Medium ◽  
Principal Component ◽  
Growth Conditions ◽  
Zn Deficiency ◽  
Rna Seq ◽  
Short Term ◽  
Chlorophyll Contents ◽  
Deficient Medium

Abstract Plant phenotypes caused by mineral deficiencies differ depending on growth conditions. We recently reported that the growth of Arabidopsis thaliana was severely inhibited on MGRL-based zinc (Zn)-deficient medium but not on Murashige–Skoog-based Zn-deficient medium. Here, we explored the underlying reason for the phenotypic differences in Arabidopsis grown on the different media. The root growth and chlorophyll contents reduced by Zn deficiency were rescued by the addition of extra manganese (Mn) during short-term growth (10 or 14 d). However, this treatment did not affect the growth recovery after long-term growth (38 d). To investigate the reason for plant recovery from Zn deficiency, we performed the RNA-seq analysis of the roots grown on the Zn-basal medium and the Zn-depleted medium with/without additional Mn. Principal component analysis of the RNA-seq data showed that the gene expression patterns of plants on the Zn-basal medium were similar to those on the Zn-depleted medium with Mn, whereas those on the Zn-depleted medium without Mn were different from the others. The expression of several transcription factors and reactive oxygen species (ROS)-related genes was upregulated in only plants on the Zn-depleted medium without Mn. Consistent with the gene expression data, ROS accumulation in the roots grown on this medium was higher than those grown in other conditions. These results suggest that plants accumulate ROS and reduce their biomass under undesirable growth conditions, such as Zn depletion. Taken together, this study shows that the addition of extra Mn to the Zn-depleted medium induces transcriptional changes in ROS-related genes, thereby alleviating short-term growth inhibition due to Zn deficiency.

scholarly journals In Silico Analysis and Characterization of Differentially Expressed Genes to Distinguish Glioma Stem Cells from Normal Neural Stem Cells

2021 ◽  
Author(s):  
Urja Parekh ◽  
Mohit Mazumder ◽  
Harpreet Kaur ◽  
Elia Brodsky
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Neural Stem Cells ◽  
Differentially Expressed Genes ◽  
Expression Patterns ◽  
Principal Component ◽  
Differentially Expressed ◽  
Glioma Stem Cells ◽  
Rna Seq ◽  
Bioinformatics Analyses

AbstractGlioblastoma multiforme (GBM) is a heterogeneous, invasive primary brain tumor that develops chemoresistance post therapy. Theories regarding the aetiology of GBM focus on transformation of normal neural stem cells (NSCs) to a cancerous phenotype or tumorigenesis driven via glioma stem cells (GSCs). Comparative RNA-Seq analysis of GSCs and NSCs can provide a better understanding of the origin of GBM. Thus, in the current study, we performed various bioinformatics analyses on transcriptional profiles of a total 40 RNA-seq samples including 20 NSC and 20 GSC, that were obtained from the NCBI-SRA (SRP200400). First, differential gene expression (DGE) analysis using DESeq2 revealed 358 significantly differentially expressed genes between GSCs and NSCs (padj. value <0.05, log2fold change ±3) with 192 upregulated and 156 downregulated genes in GSCs in comparison to NSCs. Subsequently, exploratory data analysis using the principal component analysis (PCA) based on key significant genes depicted the clear separation between both the groups. Further, the Hierarchical clustering confirmed the distinct clusters of GSC and NSC samples. Eventually, the biological enrichment analysis of the significant genes showed their enrichment in tumorigenesis pathways such as Wnt-signalling, VEGF- signalling and TGF-β-signalling pathways. Conclusively, our study depicted significant differences in the gene expression patterns between NSCs and GSCs. Besides, we also identified novel genes and genes previously unassociated with gliomagenesis that may prove to be valuable in establishing diagnostic, prognostic biomarkers and therapeutic targets for GBM.

scholarly journals Comprehensive Comparison of Amnion Stromal Cells and Chorion Stromal Cells by RNA-Seq

2021 ◽  
Vol 22 (4) ◽  
pp. 1901
Author(s):  
Brielle Jones ◽  
Chaoyang Li ◽  
Min Sung Park ◽  
Anne Lerch ◽  
Vimal Jacob ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stromal Cells ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Principal Component ◽  
Differentially Expressed ◽  
Inflammatory Factor ◽  
Next Generation Sequencing Technology ◽  
Angiogenic Potential ◽  
Anti Inflammatory

Mesenchymal stromal cells derived from the fetal placenta, composed of an amnion membrane, chorion membrane, and umbilical cord, have emerged as promising sources for regenerative medicine. Here, we used next-generation sequencing technology to comprehensively compare amniotic stromal cells (ASCs) with chorionic stromal cells (CSCs) at the molecular and signaling levels. Principal component analysis showed a clear dichotomy of gene expression profiles between ASCs and CSCs. Unsupervised hierarchical clustering confirmed that the biological repeats of ASCs and CSCs were able to respectively group together. Supervised analysis identified differentially expressed genes, such as LMO3, HOXA11, and HOXA13, and differentially expressed isoforms, such as CXCL6 and HGF. Gene Ontology (GO) analysis showed that the GO terms of the extracellular matrix, angiogenesis, and cell adhesion were significantly enriched in CSCs. We further explored the factors associated with inflammation and angiogenesis using a multiplex assay. In comparison with ASCs, CSCs secreted higher levels of angiogenic factors, including angiogenin, VEGFA, HGF, and bFGF. The results of a tube formation assay proved that CSCs exhibited a strong angiogenic function. However, ASCs secreted two-fold more of an anti-inflammatory factor, TSG-6, than CSCs. In conclusion, our study demonstrated the differential gene expression patterns between ASCs and CSCs. CSCs have superior angiogenic potential, whereas ASCs exhibit increased anti-inflammatory properties.

scholarly journals Combined Metabolome and Transcriptome Profiling Reveal Optimal Harvest Strategy Model Based on Different Production Purposes in Olive

Foods ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 360
Author(s):  
Guodong Rao ◽  
Jianguo Zhang ◽  
Xiaoxia Liu ◽  
Xue Li ◽  
Chenhe Wang
Keyword(s):  
Gene Expression ◽  
Olive Oil ◽  
Expression Patterns ◽  
Transcriptome Profiling ◽  
Minor Components ◽  
Harvest Time ◽  
Rna Seq ◽  
Optimal Harvest ◽  
Harvest Strategy ◽  
Different Color

Olive oil has been favored as high-quality edible oil because it contains balanced fatty acids (FAs) and high levels of minor components. The contents of FAs and minor components are variable in olive fruits of different color at harvest time, which render it difficult to determine the optimal harvest strategy for olive oil producing. Here, we combined metabolome, Pacbio Iso-seq, and Illumina RNA-seq transcriptome to investigate the association between metabolites and gene expression of olive fruits at harvest time. A total of 34 FAs, 12 minor components, and 181 other metabolites (including organic acids, polyols, amino acids, and sugars) were identified in this study. Moreover, we proposed optimal olive harvesting strategy models based on different production purposes. In addition, we used the combined Pacbio Iso-seq and Illumina RNA-seq gene expression data to identify genes related to the biosynthetic pathways of hydroxytyrosol and oleuropein. These data lay the foundation for future investigations of olive fruit metabolism and gene expression patterns, and provide a method to obtain olive harvesting strategies for different production purposes.

scholarly journals Bayesian Framework for Detecting Gene Expression Outliers in Individual Samples

2020 ◽  
pp. 160-170
Author(s):  
John Vivian ◽  
Jordan M. Eizenga ◽  
Holly C. Beale ◽  
Olena M. Vaske ◽  
Benedict Paten
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Rna Seq ◽  
Single Patient ◽  
Tissue Samples ◽  
Composite Tissue ◽  
Patient Sample ◽  
Statistical Framework ◽  
Therapeutic Leads ◽  
Upregulated Genes

PURPOSE Many antineoplastics are designed to target upregulated genes, but quantifying upregulation in a single patient sample requires an appropriate set of samples for comparison. In cancer, the most natural comparison set is unaffected samples from the matching tissue, but there are often too few available unaffected samples to overcome high intersample variance. Moreover, some cancer samples have misidentified tissues of origin or even composite-tissue phenotypes. Even if an appropriate comparison set can be identified, most differential expression tools are not designed to accommodate comparisons to a single patient sample. METHODS We propose a Bayesian statistical framework for gene expression outlier detection in single samples. Our method uses all available data to produce a consensus background distribution for each gene of interest without requiring the researcher to manually select a comparison set. The consensus distribution can then be used to quantify over- and underexpression. RESULTS We demonstrate this method on both simulated and real gene expression data. We show that it can robustly quantify overexpression, even when the set of comparison samples lacks ideally matched tissue samples. Furthermore, our results show that the method can identify appropriate comparison sets from samples of mixed lineage and rediscover numerous known gene-cancer expression patterns. CONCLUSION This exploratory method is suitable for identifying expression outliers from comparative RNA sequencing (RNA-seq) analysis for individual samples, and Treehouse, a pediatric precision medicine group that leverages RNA-seq to identify potential therapeutic leads for patients, plans to explore this method for processing its pediatric cohort.

scholarly journals RNA-seq: primary cells, cell lines and heat stress

2015 ◽  
Author(s):  
Carl J Schmdt ◽  
Elizabeth M Pritchett ◽  
Liang Sun ◽  
Richard V.N. Davis ◽  
Allen Hubbard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heat Stress ◽  
Sequence Data ◽  
Expression Patterns ◽  
Effective Means ◽  
Cost Effective ◽  
Rna Seq ◽  
Individual Gene ◽  
Examine Gene Expression ◽  
A Cell

Transcriptome analysis by RNA-seq has emerged as a high-throughput, cost-effective means to evaluate the expression pattern of genes in organisms. Unlike other methods, such as microarrays or quantitative PCR, RNA-seq is a target free method that permits analysis of essentially any RNA that can be amplified from a cell or tissue. At its most basic, RNA-seq can determine individual gene expression levels by counting the number of times a particular transcript was found in the sequence data. Transcript levels can be compared across multiple samples to identify differentially expressed genes and infer differences in biological states between the samples. We have used this approach to examine gene expression patterns in chicken and human cells, with particular interest in determining response to heat stress.

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 Interferon-regulated genetic programs and JAK/STAT pathway activate the intronic promoter of the short ACE2 isoform in renal proximal tubules

2021 ◽  
Author(s):  
Jakub Jankowski ◽  
Hye Kyung Lee ◽  
Julia Wilflingseder ◽  
Lothar Hennighausen
Keyword(s):  
Gene Expression ◽  
Proximal Tubule ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Regulatory Elements ◽  
Rna Seq ◽  
Angiotensin Converting Enzyme 2 ◽  
Genome Wide ◽  
Cytokine Stimulation

SummaryRecently, a short, interferon-inducible isoform of Angiotensin-Converting Enzyme 2 (ACE2), dACE2 was identified. ACE2 is a SARS-Cov-2 receptor and changes in its renal expression have been linked to several human nephropathies. These changes were never analyzed in context of dACE2, as its expression was not investigated in the kidney. We used Human Primary Proximal Tubule (HPPT) cells to show genome-wide gene expression patterns after cytokine stimulation, with emphasis on the ACE2/dACE2 locus. Putative regulatory elements controlling dACE2 expression were identified using ChIP-seq and RNA-seq. qRT-PCR differentiating between ACE2 and dACE2 revealed 300- and 600-fold upregulation of dACE2 by IFNα and IFNβ, respectively, while full length ACE2 expression was almost unchanged. JAK inhibitor ruxolitinib ablated STAT1 and dACE2 expression after interferon treatment. Finally, with RNA-seq, we identified a set of genes, largely immune-related, induced by cytokine treatment. These gene expression profiles provide new insights into cytokine response of proximal tubule cells.

scholarly journals Identifying core biological processes distinguishing human eye tissues with precise systems-level gene expression analyses and weighted correlation networks

2017 ◽  
Author(s):  
John M Bryan ◽  
Temesgen D Fufa ◽  
Kapil Bharti ◽  
Brian P Brooks ◽  
Robert B Hufnagel ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Mouse Retina ◽  
Human Tissues ◽  
Biological Processes ◽  
Rna Seq ◽  
Human Eye ◽  
Correlation Networks ◽  
Eye Tissues ◽  
Study Gene Expression

AbstractThe human eye is built from several specialized tissues which direct, capture, and pre-process information to provide vision. The gene expression of the different eye tissues has been extensively profiled with RNA-seq across numerous studies. Large consortium projects have also used RNA-seq to study gene expression patterning across many different human tissues, minus the eye. There has not been an integrated study of expression patterns from multiple eye tissues compared to other human body tissues. We have collated all publicly available healthy human eye RNA-seq datasets as well as dozens of other tissues. We use this fully integrated dataset to probe the biological processes and pan expression relationships between the cornea, retina, RPE-choroid complex, and the rest of the human tissues with differential expression, clustering, and GO term enrichment tools. We also leverage our large collection of retina and RPE-choroid tissues to build the first human weighted gene correlation networks and use them to highlight known biological pathways and eye gene disease enrichment. We also have integrated publicly available single cell RNA-seq data from mouse retina into our framework for validation and discovery. Finally, we make all these data, analyses, and visualizations available via a powerful interactive web application (https://eyeintegration.nei.nih.gov/).

scholarly journals RNA-Sequencing of Cytogenetically Normal Acute Myeloid Leukemia to Extend Routine Molecular Diagnostics

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4969-4969
Author(s):  
Laura Laine Herborg ◽  
Marcus Celik Hansen ◽  
Maria Hansen ◽  
Anne Stidsholt Roug ◽  
Peter Hokland
Keyword(s):  
Gene Expression ◽  
Microarray Data ◽  
Myeloid Leukemia ◽  
Residual Disease ◽  
Expression Patterns ◽  
Rna Seq ◽  
Mutational Status ◽  
The Individual ◽  
Minimal Residual ◽  
Acute Myeloid

Abstract Introduction Despite the discovery of new genetic alterations the cytogenetically normal acute myeloid leukemia (CN-AML) subset is still insufficiently characterized. As mRNA-sequencing (RNA-seq) is becoming more accessible, sequencing of the transcriptome could reveal not only information regarding deregulated expression patterns in leukemias, but also enable mutational evaluation of expressed alleles. To address this issue we performed RNA-seq of 5 AML patients from diagnostic bone marrow aspirates to assess the validity of the following: 1) remission samples can be used as control, 2) concordance between standard clinical laboratory analysis and RNA-seq data, and 3) implementation of existing microarray data repository to infer expected mutational status of the sequenced samples based on expression patterns. Methods Diagnostic samples were selected among patients with high leukemic blast fraction (mean of 75%) and paired remission samples with very low, or no detectable, molecular minimal residual disease. A panel of recurrent somatic mutations was assessed by means of quantitative PCR (qPCR) and fragment analysis for sequencing comparisons. Sequencing was performed on single HiSeq lane aimed at minimum 66 million reads per sample (AROS Applied Biotechnology, Aarhus, Denmark). Biomedical Genomics Workbench 2 was employed for alignment, mutation calling and analysis of differential expression (Robinson-Smyth exact test, Bonferroni corrected). R and Mathematica were used for comparison of expression patterns from the individual samples in conjunction with CN-AML (251) and control bone marrow (73) data from microarray repositories (Gene Expression Omnibus, GSE15434 and GSE13159). Results 259 genes were differentially expressed as defined by the following thresholds: normalized fold-change > 2, expression range values > 10 RPKM and p<0.05. Of these, 41 genes were upregulated in AML samples (p<0.01 subset heatmap is shown in fig. 1A). Supervised clustering of the samples on the basis of differential expression patterns efficiently divided the data into 2 groups according to diagnosis and remission status (fig. 1A, dendrogram). A median of 61 mutations per sample was observed (35 to 675). Thirty-four mutations occurred twice or more (fig. 1B, size reflects transcript fraction of mutated allele). A close correlation between routine molecular diagnostics and sequencing data was found. As expected, routine minimal residual disease marker WT1 was in agreement and found to be clearly expressed at diagnosis, but not at time of remission. By comparing patient expression patterns with NPM1, FLT3 or CEPBA mutation specific microarray expression signatures we were largely able to deduce expected mutational status for each patient (fig. 1C, showing the individual matching fraction of mutation specific gene expression signature in terms of upregulated or downregulated) in favor of qPCR analysis shown in table 1. Table 1. Comparison of mutational status from qPCR/RNA-seq FLT3 mut NPM1 mut IDH1 mut WT1 mut CEBPA mut KIT mut #1 +/+ +/+ +/+ -/- -/- -/- #2 +/+ +/+ -/- -/- -/- -/- #3 +/+ +/- -/- -/- -/- -/- #4 -/- +/- +/+ +/- -/- -/- #5 +/+ -/- -/- -/- -/- -/- Conclusions This approach serves as a proof of the concept that RNA-sequencing can be directly implemented in the routine laboratory. Moreover, transcriptome data such as these can extend the molecular survey in a dynamic manner by aiding in therapy-related decision-making for the application of targeted therapy and for delineating the reasons for treatment. While publicly available repositories of RNA-seq data are being generated for referencing, it is possible to include microarray data to support molecular classification of the individual patients, as is shown here. Figure 1. Figure 1. Disclosures No relevant conflicts of interest to declare.

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