scholarly journals Comparative Transcriptome Analyses of Gene Response to Different Light Conditions of Camellia oleifera Leaf Using Illumina and Single-Molecule Real-Time-Based RNA-Sequencing

Forests ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 91
Author(s):  
Qianqian Song ◽  
Shipin Chen ◽  
Yuefeng Wu ◽  
Yifan He ◽  
Jinling Feng ◽  
...  
Keyword(s):  
Real Time ◽  
Rna Sequencing ◽  
Blue Light ◽  
Differentially Expressed Genes ◽  
Single Molecule ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Phenotypic Traits ◽  
Camellia Oleifera ◽  
Light Conditions

Camellia oleifera Abel. is a critical oil tree species. Camellia oil, which is extracted from the seeds, is widely regarded as a premium cooking oil, with the content of oleic acid being over 80%. Light is thought to be one of the largest essential natural components in the regulation of plant developmental processes, and different light qualities can considerably influence plant physiological and phenotypic traits. In this research, we examined the growth and physiological responses of C. oleifera “MIN 43” cultivar plantlets to three different wavelengths of light, containing white, red, and blue light, and we utilized the combination of the PacBio single-molecule real-time (SMRT) and Illumina HiSeq RNA sequencing to obtain the mRNA expression profiles. The results showed that plantlets growing under blue light conditions displayed superior growth performance, including stimulated enhancement of the leaf area, increased leaf number, increased chlorophyll synthesis, and improved photosynthesis. Furthermore, SMAT sequencing created 429,955 reads of inserts, where 406,722 of them were full-length non-chimeric reads, and 131,357 non-redundant isoforms were produced. Abundant differentially expressed genes were found in leaves under different light qualities by RNA-sequencing. Gene expression profiles of actin, dynein, tubulin, defectively organized tributaries 3 (DOT3), and ADP ribosylation factor 5 (ARF5) were associated with the greatest leaf performance occurring under blue light conditions. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis identified hundreds of pathways involved in different light conditions. The pathways of the plant circadian rhythm and hormone signal transduction were associated with different light quality responses in C. oleifera. Phytochrome B (PHYB), constitutively photomorphogenic 1 (COP1), long hypocotyl 5 (HY5), auxin/indole-3-acetic acid (AUX/IAA), Gretchen Hagen 3 (GH3), and small auxin-up RNA (SAUR), which were differentially expressed genes involved in these two pathways, play a vital role in responses to different wavelengths of light in C. oleifera. In addition, blue light significantly promotes flavonoid biosynthesis via changing expression of related genes.

4 Molecularly guided multiplexed digital spatial analysis reveals differential gene expression profiles in the WNT-β-catenin pathway between melanoma and prostate tumors

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A4-A4
Author(s):  
Anushka Dikshit ◽  
Dan Zollinger ◽  
Karen Nguyen ◽  
Jill McKay-Fleisch ◽  
Kit Fuhrman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Molecule ◽  
Spatial Information ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Fluorescence Assay ◽  
Differentially Expressed ◽  
Tumor Type ◽  
Prostate Tumors

BackgroundThe canonical WNT-β-catenin signaling pathway is vital for development and tissue homeostasis but becomes strongly tumorigenic when dysregulated. and alter the transcriptional signature of a cell to promote malignant transformation. However, thorough characterization of these transcriptomic signatures has been challenging because traditional methods lack either spatial information, multiplexing, or sensitivity/specificity. To overcome these challenges, we developed a novel workflow combining the single molecule and single cell visualization capabilities of the RNAscope in situ hybridization (ISH) assay with the highly multiplexed spatial profiling capabilities of the GeoMx™ Digital Spatial Profiler (DSP) RNA assays. Using these methods, we sought to spatially profile and compare gene expression signatures of tumor niches with high and low CTNNB1 expression.MethodsAfter screening 120 tumor cores from multiple tumors for CTNNB1 expression by the RNAscope assay, we identified melanoma as the tumor type with the highest CTNNB1 expression while prostate tumors had the lowest expression. Using the RNAscope Multiplex Fluorescence assay we selected regions of high CTNNB1 expression within 3 melanoma tumors as well as regions with low CTNNB1 expression within 3 prostate tumors. These selected regions of interest (ROIs) were then transcriptionally profiled using the GeoMx DSP RNA assay for a set of 78 genes relevant in immuno-oncology. Target genes that were differentially expressed were further visualized and spatially assessed using the RNAscope Multiplex Fluorescence assay to confirm GeoMx DSP data with single cell resolution.ResultsThe GeoMx DSP analysis comparing the melanoma and prostate tumors revealed that they had significantly different gene expression profiles and many of these genes showed concordance with CTNNB1 expression. Furthermore, immunoregulatory targets such as ICOSLG, CTLA4, PDCD1 and ARG1, also demonstrated significant correlation with CTNNB1 expression. On validating selected targets using the RNAscope assay, we could distinctly visualize that they were not only highly expressed in melanoma compared to the prostate tumor, but their expression levels changed proportionally to that of CTNNB1 within the same tumors suggesting that these differentially expressed genes may be regulated by the WNT-β-catenin pathway.ConclusionsIn summary, by combining the RNAscope ISH assay and the GeoMx DSP RNA assay into one joint workflow we transcriptionally profiled regions of high and low CTNNB1 expression within melanoma and prostate tumors and identified genes potentially regulated by the WNT- β-catenin pathway. This novel workflow can be fully automated and is well suited for interrogating the tumor and stroma and their interactions.GeoMx Assays are for RESEARCH ONLY, not for diagnostics.

scholarly journals Identifying Candidate Genes for Hypoxia Adaptation of Tibet Chicken Embryos by Selection Signature Analyses and RNA Sequencing

Genes ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 823
Author(s):  
Xiayi Liu ◽  
Xiaochen Wang ◽  
Jing Liu ◽  
Xiangyu Wang ◽  
Haigang Bao
Keyword(s):  
Candidate Genes ◽  
Rna Sequencing ◽  
Differentially Expressed Genes ◽  
Gallus Gallus ◽  
Differentially Expressed ◽  
Tibet Plateau ◽  
Embryonic Liver ◽  
Selection Signature ◽  
Chicken Embryos ◽  
Hypoxia Adaptation

The Tibet chicken (Gallus gallus) lives on the Qinghai–Tibet Plateau and adapts to the hypoxic environment very well. The objectives of this study was to obtain candidate genes associated with hypoxia adaptation in the Tibet chicken embryos. In the present study, we used the fixation index (Fst) and cross population extended haplotype homozygosity (XPEHH) statistical methods to detect signatures of positive selection of the Tibet chicken, and analyzed the RNA sequencing data from the embryonic liver and heart with HISAT, StringTie and Ballgown for differentially expressed genes between the Tibet chicken and White leghorn (Gallus gallus, a kind of lowland chicken) embryos hatched under hypoxia condition. Genes which were screened out by both selection signature analysis and RNA sequencing analysis could be regarded as candidate genes for hypoxia adaptation of chicken embryos. We screened out 1772 genes by XPEHH and 601 genes by Fst, and obtained 384 and 353 differentially expressed genes in embryonic liver and heart, respectively. Among these genes, 89 genes were considered as candidate genes for hypoxia adaptation in chicken embryos. ARNT, AHR, GSTK1 and FGFR1 could be considered the most important candidate genes. Our findings provide references to elucidate the molecular mechanism of hypoxia adaptation in Tibet chicken embryos.

scholarly journals HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Differentially Expressed Genes ◽  
Cd4 T Cells ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Infected Cells ◽  
Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

scholarly journals Expression profiles of differentially expressed genes affecting fecundity in goat ovarian tissues

2015 ◽  
Vol 14 (4) ◽  
pp. 18743-18752 ◽  
Author(s):  
Y.H. Ling ◽  
Q. Quan ◽  
H. Xiang ◽  
L. Zhu ◽  
M.X. Chu ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Differentially Expressed

scholarly journals Genomic Expression Profiling of Colorectal Cancer in Silico

2021 ◽  
Author(s):  
Feifei Liu ◽  
Yu Wang ◽  
Wenxue Li ◽  
Diancheng Li ◽  
Yuwei Xin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Survival Analysis ◽  
Mrna Expression ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Analysis Tool ◽  
Hub Genes ◽  
Normal Tissues

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.

scholarly journals Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

2021 ◽  
Author(s):  
Li Guoquan ◽  
Du Junwei ◽  
He Qi ◽  
Fu Xinghao ◽  
Ji Feihong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Inflammatory Responses ◽  
Expression Profiles ◽  
Treatment Options ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Chronic Lymphocytic Thyroiditis ◽  
Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

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