Leveraging the mouse genome for gene prediction in human: from whole-genome shotgun reads to a global synteny map.
The availability of draft sequences for both the mouse and human genomes makes it possible, for the first time, to annotate whole mammalian genomes using comparative methods. TWINSCAN is a gene-prediction system that combines the methods of single-genome predictors like GENSCAN with information derived from genome comparison, thereby improving accuracy. Because TWINSCAN uses genomic sequence only, it is less biased toward highly and/or ubiquitously expressed genes than GENEWISE, GENOMESCAN, and other methods based on evidence derived from transcripts. We show that TWINSCAN improves gene prediction in human using intermediate products from various stages of the sequencing and analysis of the mouse genome, from low-redundancy, whole-genome shotgun reads to the draft assembly and the synteny map. TWINSCAN improves on the prior state of the art even when alignments from only 1X coverage of the mouse genome are available. Gene prediction accuracy improves steadily from 1X through 3X, more slowly from 3X to 4X, and relatively little thereafter. The assembly and the synteny map greatly speed the computations, however. Our human annotation using the mouse assembly is conservative, predicting only 25,622 genes, and appears to be one of the best de novo annotations of the human genome to date.
Flicek
Paul
P
Department of Computer Science and Engineering, Washington University, St. Louis, Missouri 63130, USA.
Keibler
Evan
E
Hu
Ping
P
Korf
Ian
I
Brent
Michael R
MR
D000818:Animals; D001482:Base Composition / Q000235:genetics; D002874:Chromosome Mapping / Q000379:methods*; D019295:Computational Biology / Q000379:methods / Q000592:standards; D005091:Exons / Q000235:genetics; D005544:Forecasting / Q000379:methods*; D020862:GC Rich Sequence / Q000235:genetics; D005796:Genes / Q000235:genetics*; D016678:Genome; D015894:Genome, Human; D006801:Humans; D051379:Mice; D011237:Predictive Value of Tests; D026801:Synteny / Q000235:genetics*