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Human 1.0 st array

Manufactured by Thermo Fisher Scientific

The Human 1.0 ST Array is a high-density gene expression microarray designed for comprehensive analysis of the human transcriptome. The array contains probes targeting over 25,000 well-annotated human genes, providing a thorough assessment of gene expression levels across the genome.

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4 protocols using human 1.0 st array

1

Genome-Wide Gene Expression Analysis of Fetal Lung Tissue

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Human fetal lung tissue samples were acquired through the tissue retrieval program sponsored by the National Institute of Child Health and Development, the University of Maryland Brain and Tissue Bank for Developmental Disorders (Baltimore, MD, USA), and the Center for Birth Defects Research (University of Washington, Seattle, WA, USA) [13 (link)]. Gene expression profiles were generated using the Affymetrix Human 1.0 ST Array. All human and animal studies were approved by the Brigham and Women’s Hospital Institutional Review Board.
RNA was extracted from fetal tissue whole lung homogenate and RNA sample quality was assessed using the Agilent 2100 Bioanalyzer (Agilent Technologies, Inc.,Santa Clara, CA, USA). Genome-wide gene expression profiles were generated using the Affymetrix Human 1.0 ST Array. The pre-processing of the gene expression data was performed including background correction and quantile normalization prior to analysis. The probe with the highest variance for each miRNA was used as the representation of each miRNA. In total, ~200 of the known miRNAs were interrogated on this Affymetrix platform.
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2

Integrative Analysis of mRNA, lncRNA, and miRNA Interactions in Lung Adenocarcinoma

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The mRNA and lncRNA expression data of LAD were recruited from the research of Xi et al. (10 (link)) by repurposing the exon-array data on the Affymetrix Human 1.0 ST array from the ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/), which was accessible through E-GEOD-12236. There were 40 samples in E-GEOD-12236, including 20 normal samples and 20 LAD samples. In detail, the probe sets were re-annotated to the human gene symbols, and 17,681 genes were identified. Then, the 17,681 genes were mapped to the miRNA-mRNA interactions and lncRNA-miRNA interactions. Ultimately, expression profiles of 10,485 mRNAs and 57 lncRNAs were identified. Afterwards, we, respectively, extracted the interactions containing any genes of 10,485 mRNAs and 57 lncRNAs from the miRNA-mRNA interactions and lncRNA-miRNA interactions. Totally, 334,014 miRNA-mRNA interactions and 695 lncRNA-miRNA interactions were identified.
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3

Unveiling lncRNA-mRNA Interactions in GBM

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The specific steps of our study were divided into the following procedures: Firstly, mRNA as well as lncRNA expression data of GBM were obtained from the GEO database (http://www.ncbi.nlm.nih.gov/geo/) based on the platform of exon-array data on the Affymetrix Human 1.0 ST Array. Simultaneously, miRNA-target interactions were downloaded from starBase v2.0 (25 (link)). Then, a hypergeometric test was applied to identify the competing lncRNA-mRNA interactions, following by co-expression analysis to extract the co-expressed lncRNA-mRNA pairs to further establish the LMCN. Functional analyses for the mRNAs in the LMCN to reveal the biological roles of lncRNAs.
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4

Profiling LncRNA Expression in LSCC

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The lncRNA expression dataset was derived from the study of Du et al (29 (link)), repurposing the probes from an Affymetrix Human Exon 1.0 ST microarray. In brief, the probes of the Affymetrix Human 1.0 ST array were uniquely mapped to lncRNA using the latest annotations of lncRNA with a computational pipeline. A total of 10,207 lncRNA-encoding genes with at least 4 probes were obtained for further analysis. The expression value of lncRNA was obtained by summarizing the background-corrected intensity of all probes corresponding to this lncRNA and was standardized using the quantile-normalized method and an empirical Bayes method.
Expression profiles of lncRNAs between LSCC patients at early stages and those with late-stage disease were compared and the differentially expressed lncRNAs were identified using the significance analysis of microarrays method. Those lncRNAs with a P-value of <0.01 and a fold change of >1.5 or <0.67 were considered as differentially expressed lncRNAs. Unsupervised hierarchical clustering of LSCC patients and lncRNAs was performed with the R platform (version 3.2.5; https://www.r-project.org) using the euclidean distance and complete linkage method.
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