Abstract: With the new sequencing technologies, the number of novel genome sequences has exploded. At the same time the genome projects are hampered by the lack of homologies to the novel genome, making it difficult both to properly train genome analysis tools and to assess the results. Moreover, the faster and cheaper sequencing methods come with the cost of data quality, and sequencing and annotation errors that make it into the genome databases are propagated to new genomes, making annotation an even bigger challenge. Methods that can improve the data quality is desperately needed.
Here we propose a novel use of comparative gene finding to improve the annotation in organisms with high nucleotide diversity. Comparative gene finding methods utilizes the contrast in sequence similarity between functional and non-functional regions of evolutionary related species. We show how this can be applied to chromosome pair sequences in diploid sequence data. We demonstrate the approach on the highly diverse sea orchid Balanus improvisus using SLAM, a cross-species gene finder that simultaneously annotates and aligns two homologous sequences using Generalized Pair Hidden Markov Models.