Phylogenetic profiles reveal evolutionary relationships within the "twilight zone" of sequence similarity

Su Chang Gue, Yoojin Hong, Dae Ko Kyung, Gaurav Bhardwaj, Edward C. Holmes, Randen L. Patterson, Damian B. Van Rossum

Research output: Contribution to journalArticlepeer-review

35 Scopus citations


Inferring evolutionary relationships among highly divergent protein sequences is a daunting task. In particular, when pairwise sequence alignments between protein sequences fall <25% identity, the phylogenetic relationships among sequences cannot be estimated with statistical certainty. Here, we show that phylogenetic profiles generated with the Gestalt Domain Detection Algorithm-Basic Local Alignment Tool (GDDA-BLAST) are capable of deriving, ab initio, phylogenetic relationships for highly divergent proteins in a quantifiable and robust manner. Notably, the results from our computational case study of the highly divergent family of retroelements accord with previous estimates of their evolutionary relationships. Taken together, these data demonstrate that GDDA-BLAST provides an independent and powerful measure of evolutionary relationships that does not rely on potentially subjective sequence alignment. We demonstrate that evolutionary relationships can be measured with phylogenetic profiles, and therefore propose that these measurements can provide key insights into relationships among distantly related and/or rapidly evolving proteins.

Original languageEnglish (US)
Pages (from-to)13474-13479
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number36
StatePublished - Sep 9 2008

All Science Journal Classification (ASJC) codes

  • General


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