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Applications in omics research, such as comparative transcriptomics and proteomics, require the knowledge of the species-specific gene sequence and benefit from a comprehensive high-quality annotation of the coding genes to achieve high coverage. While protein-coding genes can in simple cases be detected by scanning the genome for open reading frames, in more complex genomes exonic sequences are separated by introns. Despite advances in sequencing technologies that allow for ever-growing numbers of genomes, the quality of many of the provided genome assemblies do not reach reference quality. These non-contiguous assemblies with gaps and the necessity to predict splice sites limit accurate gene annotation from solely genomic data. In contrast, the transcriptome only contains transcribed gene regions, is devoid of introns and thus provides the optimal basis for the identification of open reading frames. The additional integration of proteomics data to validate predicted protein-coding genes further enriches for accurate gene models. This review outlines the principles of the proteotranscriptomics approach, discusses common challenges and suggests methods for improvement.