Genome annotation past, present, and future: how to define an ORF at each locus.
Driven by competition, automation, and technology, the genomics community has far exceeded its ambition to sequence the human genome by 2005. By analyzing mammalian genomes, we have shed light on the history of our DNA sequence, determined that alternatively spliced RNAs and retroposed pseudogenes are incredibly abundant, and glimpsed the apparently huge number of non-coding RNAs that play significant roles in gene regulation. Ultimately, genome science is likely to provide comprehensive catalogs of these elements. However, the methods we have been using for most of the last 10 years will not yield even one complete open reading frame (ORF) for every gene--the first plateau on the long climb toward a comprehensive catalog. These strategies--sequencing randomly selected cDNA clones, aligning protein sequences identified in other organisms, sequencing more genomes, and manual curation--will have to be supplemented by large-scale amplification and sequencing of specific predicted mRNAs. The steady improvements in gene prediction that have occurred over the last 10 years have increased the efficacy of this approach and decreased its cost. In this Perspective, I review the state of gene prediction roughly 10 years ago, summarize the progress that has been made since, argue that the primary ORF identification methods we have relied on so far are inadequate, and recommend a path toward completing the Catalog of Protein Coding Genes, Version 1.0.
Brent
Michael R
MR
Laboratory for Computational Genomics and Department of Computer Science, Washington University, St. Louis, Missouri 63130, USA. brent@cse.wustl.edu
D000818:Animals; D019295:Computational Biology / Q000379:methods* / Q000639:trends; D030561:Databases, Nucleic Acid / Q000592:standards*; D005544:Forecasting; D016678:Genome; D015894:Genome, Human; D023281:Genomics / Q000379:methods / Q000639:trends; D006801:Humans; D016366:Open Reading Frames / Q000235:genetics