June 2020
Volume 61, Issue 7
ARVO Annual Meeting Abstract  |   June 2020
Characterization of long noncoding RNAs in lens development
Author Affiliations & Notes
  • Deepti Anand
    Biological Sciences, University of Delaware, Newark, Delaware, United States
  • Mona Batish
    Medical & Molecular Sciences, University of Delaware, Newark, Delaware, United States
  • Salil A. Lachke
    Biological Sciences, University of Delaware, Newark, Delaware, United States
    Center for Bioinformatics and Computational Biology, University of Delware, Newark, Delaware, United States
  • Footnotes
    Commercial Relationships   Deepti Anand, None; Mona Batish, None; Salil Lachke, None
  • Footnotes
    Support  R01 EY021505
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 2867. doi:
  • Views
  • Share
  • Tools
    • Alerts
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Deepti Anand, Mona Batish, Salil A. Lachke; Characterization of long noncoding RNAs in lens development. Invest. Ophthalmol. Vis. Sci. 2020;61(7):2867.

      Download citation file:

      © ARVO (1962-2015); The Authors (2016-present)

  • Supplements

Purpose : In recent years, function of noncoding RNAs in the control of gene expression has been well established. In particular, long noncoding RNA (lncRNA)–defined as transcripts longer than 200 nucleotides (nt) that do not encode proteins–are involved in regulating the cellular proteome by controlling gene expression by both transcriptional and post-transcriptional mechanisms. However, lncRNA function in the lens is not well understood. Therefore, we performed bioinformatics analyses to identify lncRNAs expressed in mouse embryonic and postnatal lens development and applied single-molecule RNA imaging to characterize their expression in lens cells.

Methods : Previously generated RNA-sequencing (RNA-seq) datasets from wild-type mouse lens tissue at embryonic (E10.5, E12.5, E14.5, E15.0, E16.5, E18.0) and post-natal (P0, P3, P6 and P9) stages were analyzed using in-house RNA-seq pipeline that implemented coding potential assessment tools to identify potential lens expressed lncRNAs. Single-molecule RNA imaging was used to examine lncRNA expression in mammalian lens epithelial cell lines.

Results : In total, 36,453 high-confidence transcripts, comprising of 31,457 coding transcripts and 4,996 noncoding transcripts were identified as expressed at 1 FPKM (Fragments Per Kilobase of transcript per Million mapped reads) in at least two lens stages. Noncoding transcripts and protein-coding transcripts differed in transcript size and exon number with the former being 905 nt with an average of 3.2 exons and the latter being 3175 nt with an average of 11.5 exons. Clustering analysis identified lncRNAs that were preferentially expressed in embryonic and post-natal lens. These clusters revealed high expression of long intervening noncoding RNAs (lincRNAs) (Gas5, Gm26847, Malat1, Rmst, Snhg6, Snhg8), antisense lncRNAs (Gm12744, Gm15655, Prox1os) and others such as Igf2, Mt1 and Tma7. Single-molecule RNA imaging validated expression of candidate lncRNAs such as Malat1 in lens epithelial cell lines.

Conclusions : This study reports a comprehensive bioinformatics-based analyses of lens RNA-seq data to identify lncRNAs expressed in various embryonic and postnatal stages of mouse lens development. It also demonstrates the use of single-molecular RNA imaging assay to visualize and validate expression of lncRNAs in lens cells.

This is a 2020 ARVO Annual Meeting abstract.


This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.