title: Detecting novel genes with sparse arrays.
abstract: Species-specific genes play an important role in defining the phenotype of an organism. However, current gene prediction methods can only efficiently find genes that share features such as sequence similarity or general sequence characteristics with previously known genes. Novel sequencing methods and tiling arrays can be used to find genes without prior information and they have demonstrated that novel genes can still be found from extensively studied model organisms. Unfortunately, these methods are expensive and thus are not easily applicable, e.g., to finding genes that are expressed only in very specific conditions. We demonstrate a method for finding novel genes with sparse arrays, applying it on the 33.9 Mb genome of the filamentous fungus Trichoderma reesei. Our computational method does not require normalisations between arrays and it takes into account the multiple-testing problem typical for analysis of microarray data. In contrast to tiling arrays, that use overlapping probes, only one 25 mer microarray oligonucleotide probe was used for every 100b. Thus, only relatively little space on a microarray slide was required to cover the intergenic regions of a genome. The analysis was done as a by-product of a conventional microarray experiment with no additional costs. We found at least 23 good candidates for novel transcripts that could code for proteins and all of which were expressed at high levels. Candidate genes were found to neighbour ire1 and cre1 and many other regulatory genes. Our simple, low-cost method can easily be applied to finding novel species-specific genes without prior knowledge of their sequence properties.
authors.affiliation: VTT Technical Research Centre of Finland, Tietotie 2, PO Box FI-1000, 02044 VTT, Espoo, Finland. mikko.arvas@vtt.fi
authors.forename: Mikko
authors.initials: M
authors.lastname: Arvas
authors.forename: Niina
authors.initials: N
authors.lastname: Haiminen
authors.forename: Bart
authors.initials: B
authors.lastname: Smit
authors.forename: Jari
authors.initials: J
authors.lastname: Rautio
authors.forename: Marika
authors.initials: M
authors.lastname: Vitikainen
authors.forename: Marilyn
authors.initials: M
authors.lastname: Wiebe
authors.forename: Diego
authors.initials: D
authors.lastname: Martinez
authors.forename: Christine
authors.initials: C
authors.lastname: Chee
authors.forename: Joe
authors.initials: J
authors.lastname: Kunkel
authors.forename: Charles
authors.initials: C
authors.lastname: Sanchez
authors.forename: Mary Anne
authors.initials: MA
authors.lastname: Nelson
authors.forename: Tiina
authors.initials: T
authors.lastname: Pakula
authors.forename: Markku
authors.initials: M
authors.lastname: Saloheimo
authors.forename: Merja
authors.initials: M
authors.lastname: Penttilä
authors.forename: Teemu
authors.initials: T
authors.lastname: Kivioja
mesh_terms: D019295:Computational Biology / Q000379:methods; D015870:Gene Expression; D005786:Gene Expression Regulation; D005800:Genes, Fungal; D016681:Genome, Fungal; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012333:RNA, Messenger / Q000032:analysis; D013045:Species Specificity; D014242:Trichoderma / Q000235:genetics*
chemical_list: D012333:RNA, Messenger