Accurately identifying orthologs among species is key to solving their evolutionary relationships (see box) – an exercise that proves even more challenging for species not closely related to model species, and for which prior information is scarce. A tool, derived from the SIB Resource OMA developed by the team of SIB Group Leader Christophe Dessimoz at the University of Lausanne, allows scientists to analyze their own custom genomes or transcriptomes in combination with publicly available data. “OMA standalone” is described in a paper published in Genome Research.

Of the importance of orthology

Understanding how species are related to one another, which is the goal of phylogenetic trees, relies on the correct inference of sequences which have descended from a single common gene in their last common ancestor. These are called orthologous sequences.

With new genomes and transcriptomes becoming available every day, another key role of orthologs is to enable scientists to characterize newly sequenced genes from existing knowledge on related ones.

A customizable local version of OMA

“In studies seeking to resolve difficult phylogenies, the impact of orthology accuracy is too often overlooked,” explains SIB Group Leader Christophe Dessimoz. “Our study demonstrates that the choice of orthology method can have a large impact on phylogenetic reconstruction. With OMA standalone, researchers can use a cutting-edge orthology inference algorithm on their custom genomic data.”

Indeed, while orthology databases such as the SIB Resource OMA already elucidate orthologous relationships among publicly available genomes, identifying orthologs on user-generated data had been a more involved endeavour. With OMA standalone it now becomes possible to easily and comprehensively analyse entire genome or transcriptome and compare them with publicly available data. “Considering the recent announcement of the Earth BioGenome initiative, which aims at sequencing over 1.5 million species within the coming decade, the need for methods for orthology inference on non-model species will only increase.” says Dessimoz.

Solving trees of life – and more

The Lophotrochozoa is a particularly deep lineage of animals – encompassing the cuttlefish and the earthworm. Resolving speciation events that happened 700 million years ago is a particularly complex task: so what best example to test and compare OMA standalone to other pipelines? The authors showed that the OMA standalone consistently led to the most accurate Lophotrochozoa trees as compared with those obtained with other pipelines. “Our study also shed new light on some of the unresolved parts of the tree—for instance, we found annelids (which include the earthworm) to be sister to molluscs and ribbon worms, with high statistical support” adds Dessimoz.

Prior to this publication, OMA standalone has already been used in several high-profile studies, from centipedes to scorpions, and to identify gene families related to the emergence and loss of echolocation in bats. But the applications of a reliable orthology tool extend beyond phylogenies: for instance, new potential drug targets could also be identified in a human parasite such has the tape worm, by allowing researchers to identify and ‘sieve out’ well-conserved proteins between human and nematodes.

Reference:
Altenhoff A M. OMA standalone: orthology inference among publicand custom genomes and transcriptomes. Genome Research 2019. doi: 10.1101/gr.243212.118

Talk at ISMB 2018 on OMA standalone