High-performance computing in the search for the Tree of Life

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Phylogeny, in the upper limit the entire Tree of Life, is a source of fascination in itself. Ever since we have known species share common ancestors, we have sought to discover the pattern of relationships among species. The pattern of relationships is typically represented as a bifurcating tree, whose tips represent extant species and internal nodes represent hypothetical ancestors. Until the late 20th Century, phylogenetic research was speculative, due to the limited quantity of data morphology can provide and problems of interpretation. Two technological developments in the 20th Century revolutionised the field. One was the availability of computers, allowing the replacement of subjective reasoning in phylogeny reconstruction with algorithmic and statistical approaches. The other was the availability of DNA sequence, allowing a step-change in the quality and quantity of data upon which to base phylogeny reconstruction.Computers and DNA sequence have had a transformative effect on phylogeny reconstruction. However, after decades of stability, in the 21st century DNA sequencing technology is changing. This Big Data is placing a strain on computational phylogeny. In the 1990s, a PhD student might sequence a single gene from each of 20 species, and the insights would be novel and astounding. Now, the student might sequence the entire genome of these same species, with enormously greater opportunities for discovery and certainty. With continuing developments in DNA sequencing technology, within a decade such a student will be able to sequence the entire genome of several thousands of species. Finally, after almost two centuries of intellectual contributions on the tree of life, the tree in its entirety is almost within our grasp - with respect to input data at least.The bottleneck has shifted from DNA sequence availability, to algorithms and software able to extract phylogenetic relationships from these data.To find the optimal phylogeny based on DNA sequences, ideally one would evaluate all possible tree topologies. However, the number of topologies increases factorially with the number of extant species, and for 54 species there are more possible unrooted bifurcating topologies than atoms in the universe. The only way forward is a combined high performance computing (HPC) and advanced algorithmic approach. This will search the range of solutions in an effective and rapid manner, and will maximise the potential of increasingly available large computing resources.LVB is a piece of software for phylogeny reconstruction, using the advanced simulated annealing heuristic. This allows a good (realistic) result to be obtained, by looking at only a small fraction of possible tree topologies. We seek to:- implement LVB on parallel computer systems, including all current desktop computers and larger HPC systems, typically found in research institutes, universities and industry;- integrate LVB with other phylogeny reconstruction software, so that initial results obtained rapidly by LVB may be further refined by a range of plausible criteria;- make LVB available to run through a Web server, which will record aspects of the user's input as well as the quality of results, so that in future the software can adapt in light of this knowledge to be even better;- apply LVB to a published, challenging data set of 73,060 eukaryotic species, to obtain comparative performance data and the best possible phylogeny for this major branch of the Tree of Life.