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arxiv: q-bio/0611084 · v3 · submitted 2006-11-25 · 🧬 q-bio.PE · math.ST· q-bio.QM· stat.TH

A Novel Test for Host-Symbiont Codivergence Indicates Ancient Origin of Fungal Endophytes in Grasses

classification 🧬 q-bio.PE math.STq-bio.QMstat.TH
keywords codivergencemethodrandomtesttreeagesanalysisapplied
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Significant phylogenetic codivergence between plant or animal hosts ($H$) and their symbionts or parasites ($P$) indicate the importance of their interactions on evolutionary time scales. However, valid and realistic methods to test for codivergence are not fully developed. One of the systems where possible codivergence has been of interest involves the large subfamily of temperate grasses (Pooideae) and their endophytic fungi (epichloae). These widespread symbioses often help protect host plants from herbivory and stresses, and affect species diversity and food web structures. Here we introduce the MRCALink (most-recent-common-ancestor link) method and use it to investigate the possibility of grass-epichlo\"e codivergence. MRCALink applied to ultrametric $H$ and $P$ trees identifies all corresponding nodes for pairwise comparisons of MRCA ages. The result is compared to the space of random $H$ and $P$ tree pairs estimated by a Monte Carlo method. Compared to tree reconciliation the method is less dependent on tree topologies (which often can be misleading), and it crucially improves on phylogeny-independent methods such as {\tt ParaFit} or the Mantel test by eliminating an extreme (but previously unrecognized) distortion of node-pair sampling. Analysis of 26 grass species-epichlo\"e species symbioses did not reject random association of $H$ and $P$ MRCA ages. However, when five obvious host jumps were removed the analysis significantly rejected random association and supported grass-endophyte codivergence. Interestingly, early cladogenesis events in the Pooideae corresponded to early cladogenesis events in epichloae, suggesting concomitant origins of this grass subfamily and its remarkable group of symbionts. We also applied our method to the well-known gopher-louse data set.

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