Skip Header

You are using a version of browser that may not display all the features of this website. Please consider upgrading your browser.

Nineteen additional unpredicted transcripts from human chromosome 21.

Reymond A., Camargo A.A., Deutsch S., Stevenson B.J., Parmigiani R.B., Ucla C., Bettoni F., Rossier C., Lyle R., Guipponi M., de Souza S., Iseli C., Jongeneel C.V., Bucher P., Simpson A.J.G., Antonarakis S.E.

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.

Genomics 79:824-832(2002) [PubMed] [Europe PMC]

We'd like to inform you that we have updated our Privacy Notice to comply with Europe’s new General Data Protection Regulation (GDPR) that applies since 25 May 2018.

Do not show this banner again
UniProt is an ELIXIR core data resource
Main funding by: National Institutes of Health