Genome-wide computational identification and manual annotation of human long noncoding RNA genes

  1. Leonard Lipovich1
  1. 1Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48202, USA
  2. 2Lee and Roland Witte Natural Sciences Division, Hillsdale College, Hillsdale, Michigan 49242, USA
  3. 3Stem Cell and Developmental Biology Group, Genome Institute of Singapore, 138672 Singapore
  • 4 Present address: Center for Genomic Regulation, Barcelona, Spain.

Abstract

Experimental evidence suggests that half or more of the mammalian transcriptome consists of noncoding RNA. Noncoding RNAs are divided into short noncoding RNAs (including microRNAs) and long noncoding RNAs (lncRNAs). We defined complementary DNAs (cDNAs) lacking any positive-strand open reading frames (ORFs) longer than 30 amino acids, as well as cDNAs lacking any evidence of interspecies conservation of their longer-than-30-amino acid ORFs, as noncoding. We have identified 5446 lncRNA genes in the human genome from ∼24,000 full-length cDNAs, using our new ORF-prediction pipeline. We combined them nonredundantly with lncRNAs from four published sources to derive 6736 lncRNA genes. In an effort to distinguish standalone and antisense lncRNA genes from database artifacts, we stratified our catalog of lncRNAs according to the distance between each lncRNA gene candidate and its nearest known protein-coding gene. We concurrently examined the protein-coding capacity of known genes overlapping with lncRNAs. Remarkably, 62% of known genes with “hypothetical protein” names actually lacked protein-coding capacity. This study has greatly expanded the known human lncRNA catalog, increased its accuracy through manual annotation of cDNA-to-genome alignments, and revealed that a large set of hypothetical-protein genes in GenBank lacks protein-coding capacity. In addition, we have developed, independently of existing NCBI tools, command-line programs with high-throughput ORF-finding and BLASTP-parsing functionality, suitable for future automated assessments of protein-coding capacity of novel transcripts.

Keywords

Footnotes

  • Reprint requests to: Leonard Lipovich, Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI 48202, USA; e-mail: LLipovich{at}med.wayne.edu; fax: (313) 577-5218.

  • Article published online ahead of print. Article and publication date are at http://www.rnajournal.org/cgi/doi/10.1261/rna.1951310.

  • Received October 8, 2009.
  • Accepted May 14, 2010.
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