Phylogenetic profiles reveal evolutionary relationships within the "twilight zone" of sequence similarity.
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.
Chang
Gue Su
GS
Department of Biology, Pennsylvania State University, State College, PA 16802, USA.
Hong
Yoojin
Y
Ko
Kyung Dae
KD
Bhardwaj
Gaurav
G
Holmes
Edward C
EC
Patterson
Randen L
RL
van Rossum
Damian B
DB