Quartet Sampling distinguishes lack of support from conflicting support 1 in the plant tree of life 1 2 3

14 Premise of the Study— Phylogenetic support has been difficult to evaluate within the plant 15 tree of life partly due to the inability of standard methods to distinguish conflicted versus poorly 16 informed branches. As phylogenomic and broad-scale datasets continue to grow, support 17 measures are needed that are more efficient and informative. 18 Methods— We describe the Quartet Sampling (QS) method that synthesizes several 19 phylogenetic and genomic analytical approaches into a quartet-based evaluation system. QS 20 rapidly characterizes discordance in large-sparse and genome-wide datasets, overcoming issues of 21 sparse alignment and distinguishing strong conflict from weak support. We test this method with 22 simulations and recent plant phylogenies inferred from variously sized datasets. 23 Key Results— QS scores decrease in variance with increasing replicates and are not strongly 24 affected by branch depth. Patterns of QS support from different phylogenies leads to a coherent 25 understanding of ancestral branches defining key disagreements, including Ginkgo+cycad, 26 magnoliids+eudicots (excluding monocots), and mosses+liverworts. The relationships of ANA 27 grade angiosperms, major monocot groups, and bryophytes and fern families are found to likely 28 be the result of discordant evolutionary histories, rather than poor information. Also, analyses of 29 phylogenomic data show QS can detect discordance due to introgression. 30 Conclusions— The QS method represents an efficient and effective synthesis of phylogenetic 31 tests that offer more comprehensive and specific information on branch support than conventional 32 measures. The QS method corroborates growing evidence that phylogenomic investigations that 33 2 . CC-BY-NC 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/148536 doi: bioRxiv preprint first posted online Jun. 10, 2017;