Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases.

Background: Surprisingly little is known about the organization and distribution of tRNA genes and tRNA-related sequences on a genome-wide scale. While tRNA gene complements are usually reported in passing as part of genome annotation efforts, and peculiar features such as the tandem arrangements of tRNA gene in Entamoeba histolytica have been described in some detail, systematic comparative studies are rare and mostly restricted to bacteria. We therefore set out to survey the genomic arrangement of tRNA genes and pseudogenes in a wide range of eukaryotes to identify common patterns and taxon-specific peculiarities. Results: In line with previous reports, we find that tRNA complements evolve rapidly and tRNA gene and pseudogene locations are subject to rapid turnover. At phylum level, the distributions of the number of tRNA genes and pseudogenes numbers are very broad, with standard deviations on the order of the mean. Even among closely related species we observe dramatic changes in local organization. For instance, 65% and 87% of the tRNA genes and pseudogenes are located in genomic clusters in zebrafish and stickleback, resp., while such arrangements are relatively rare in the other three sequenced teleost fish genomes. Among basal metazoa, Trichoplax adhaerens has hardly any duplicated tRNA gene, while the sea anemone Nematostella vectensis boasts more than 17000 tRNA genes and pseudogenes. Dramatic variations are observed even within the eutherian mammals. Higher primates, for instance, have 616 ± 120 tRNA genes and pseudogenes of which 17% to 36% are arranged in clusters, while the genome of the bushbaby Otolemur garnetti has 45225 tRNA genes and pseudogenes of which only 5.6% appear in clusters. In contrast, the distribution is surprisingly uniform across plant genomes. Consistent with this variability, syntenic conservation of tRNA genes and pseudogenes is also poor in general, with turn-over rates comparable to those of unconstrained sequence elements. Despite this large variation in abundance in Eukarya we observe a significant correlation between the number of tRNA genes, tRNA pseudogenes, and genome size. Conclusions: The genomic organization of tRNA genes and pseudogenes shows complex lineage-specific patterns characterized by an extensive variability that is in striking contrast to the extreme levels of sequence-conservation of the tRNAs themselves. The comprehensive analysis of the genomic organization of tRNA genes and pseudogenes in Eukarya provides a basis for further studies into the interplay of tRNA gene arrangements and genome organization in general.

Background: Kiwi, comprising five species from the genus Apteryx, are endangered, ground-dwelling bird species endemic to New Zealand. They are the smallest and only nocturnal representatives of the ratites. The timing of kiwi adaptation to a nocturnal niche and the genomic innovations, which shaped sensory systems and morphology to allow this adaptation, are not yet fully understood. Results: We sequenced and assembled the brown kiwi genome to 150-fold coverage and annotated the genome using kiwi transcript data and non-redundant protein information from multiple bird species. We identified evolutionary sequence changes that underlie adaptation to nocturnality and estimated the onset time of these adaptations. Several opsin genes involved in color vision are inactivated in the kiwi. We date this inactivation to the Oligocene epoch, likely after the arrival of the ancestor of modern kiwi in New Zealand. Genome comparisons between kiwi and representatives of ratites, Galloanserae, and Neoaves, including nocturnal and song birds, show diversification of kiwi’s odorant receptors repertoire, which may reflect an increased reliance on olfaction rather than sight during foraging. Further, there is an enrichment of genes influencing mitochondrial function and energy expenditure among genes that are rapidly evolving specifically on the kiwi branch, which may also be linked to its nocturnal lifestyle. Conclusions: The genomic changes in kiwi vision and olfaction are consistent with changes that are hypothesized to occur during adaptation to nocturnal lifestyle in mammals. The kiwi genome provides a valuable genomic resource for future genome-wide comparative analyses to other extinct and extant diurnal ratites.

Automated software tools for multiple alignment often fail to produce biologically meaningful results. In such situations, expert knowledge can help to improve the quality of alignments. Herein, we describe a semi-automatic version of the alignment program DIALIGN that can take pre-defined constraints into account. It is possible for the user to specify parts of the sequences that are assumed to be homologous and should therefore be aligned to each other. Our software program can use these sites as anchor points by creating a multiple alignment respecting these constraints. This way, our alignment method can produce alignments that are biologically more meaningful than alignments produced by fully automated procedures. As a demonstration of how our method works, we apply our approach to genomic sequences around the Hox gene cluster and to a set of DNA-binding proteins. As a by-product, we obtain insights about the performance of the greedy algorithm that our program uses for multiple alignment and about the underlying objective function. This information will be useful for the further development of DIALIGN. The described alignment approach has been integrated into the TRACKER software system.