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Long Non-Coding RNAs pp 53–74Cite as

Long Non-coding RNA Expression Profiling Using Arraystar LncRNA Microarrays

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 2372))

Abstract

Arraystar LncRNA microarrays are designed for transcriptome-wide gene expression profiling of both lncRNAs and mRNAs on the same array. The array contents feature comprehensive collections of lncRNAs and include all canonical known coding mRNAs . Each lncRNA transcript is detected by a splice junction specific probe or a unique exon sequence , such that the alternatively spliced transcript isoforms or variants are reliably and accurately detected. The highly optimized experimental protocols and efficient workflow ensure sensitive, robust, and accurate microarray data generation. Standard data analyses are provided for microarray raw data processing, data quality control, gene expression clustering heat map visualization, differentially expressed lncRNAs and mRNAs , lncRNA subcategories, regulatory relationships of lncRNAs with the target mRNAs , gene ontology and pathway analyses. The LncRNA microarrays are a powerful tool for studying lncRNAs in biology and disease, with broad applications in gene expression profiling, gene regulatory mechanism research, lncRNA functional discovery, and biomarker development.

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Author information

Authors and Affiliations

  1. Arraystar Inc., Rockville, MD, USA

    Yanggu Shi & Jindong Shang

Authors
  1. Yanggu Shi
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  2. Jindong Shang
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Corresponding author

Correspondence to Yanggu Shi .

Editor information

Editors and Affiliations

  1. Department of Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, PA, USA

    Lin Zhang

  2. Department of Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, PA, USA

    Xiaowen Hu

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Shi, Y., Shang, J. (2021). Long Non-coding RNA Expression Profiling Using Arraystar LncRNA Microarrays. In: Zhang, L., Hu, X. (eds) Long Non-Coding RNAs. Methods in Molecular Biology, vol 2372. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1697-0_7

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  • DOI: https://doi.org/10.1007/978-1-0716-1697-0_7

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1696-3

  • Online ISBN: 978-1-0716-1697-0

  • eBook Packages: Springer Protocols

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