Nineteen additional unpredicted transcripts from human chromosome 21

Alexandre Reymond, Anamaria A. Camargo, Samuel Deutsch, Brian J. Stevenson, Raphael B. Parmigiani, Catherine Ucla, Fabiana Bettoni, Colette Rossier, Robert Lyle, Michel Guipponi, Sandro De Souza, Christian Iseli, C. Victor Jongeneel, Philipp Bucher, Andrew J.G. Simpson, Stylianos E. Antonarakis

Research output: Contribution to journalArticlepeer-review

Abstract

The identification of all human chromosome 21 (HC21) genes is a necessary step in understanding the molecular pathogenesis of trisomy 21 (Down syndrome). The first analysis of the sequence of 21q included 127 previously characterized genes and predicted an additional 98 novel anonymous genes. Recently we evaluated the quality of this annotation by characterizing a set of HC21 open reading frames (C21orfs) identified by mapping spliced expressed sequence tags (ESTs) and predicted genes (PREDs), identified only in silico. This study underscored the limitations of in silico-only gene prediction, as many PREDs were incorrectly predicted. To refine the HC21 annotation, we have developed a reliable algorithm to extract and stringently map sequences that contain bona fide 3′ transcript ends to the genome. We then created a specific 21q graphical display allowing an integrated view of the data that incorporates new ESTs as well as features such as CpG islands, repeats, and gene predictions. Using these tools we identified 27 new putative genes. To validate these, we sequenced previously cloned cDNAs and carried out RT-PCR, 5′- and 3′-RACE procedures, and comparative mapping. These approaches substantiated 19 new transcripts, thus increasing the HC21 gene count by 9.5%. These transcripts were likely not previously identified because they are small and encode small proteins. We also identified four transcriptional units that are spliced but contain no obvious open reading frame. The HC21 data presented here further emphasize that current gene prediction algorithms miss a substantial number of transcripts that nevertheless can be identified using a combination of experimental approaches and multiple refined algorithms.

Original languageEnglish (US)
Pages (from-to)824-832
Number of pages9
JournalGenomics
Volume79
Issue number6
DOIs
StatePublished - 2002
Externally publishedYes

Keywords

  • Acedb
  • Down syndrome
  • Expression pattern
  • Gene prediction
  • Genomic sequences annotation
  • Human chromosome 21
  • Transcription map
  • Trisomy 21

ASJC Scopus subject areas

  • Genetics

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