Research ArticleEVOLUTIONARY BIOLOGY

Multiple origins of green blood in New Guinea lizards

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Science Advances  16 May 2018:
Vol. 4, no. 5, eaao5017
DOI: 10.1126/sciadv.aao5017
  • Fig. 1 Ancestral reconstruction indicates four origins of green blood.

    (A) Transitions between red blood and green blood in Australasian lizards were summarized from 1000 stochastic character simulations on a fixed species topology. The phylogeny was estimated from a 70% complete sequence matrix from our ONE data set using an unpartitioned concatenated analysis in RAxML. Bootstrap values for all nodes are 100. Branches are colored continuously according to posterior probability (PP) support for red (PP = 1.0) or green (PP = 0.0) blood under our “mixed” model. Pie charts indicate proportion of character histories that reconstructed red or green blood as the ancestral state for the most recent common ancestor of all Prasinohaema species under each transition rate model: all rates different (ARD), equal rates (ER), irreversible (IR), or mixed. Values for the character rate matrix were either fixed at their maximum likelihood estimates (MLE) or sampled from a posterior distribution of rate matrices (MCMC). Pictures show the following green-blooded species: (B) Prasinohaema flavipes, (C) P. prehensicauda, (D) Prasinohaema semoni, (E) Prasinohaema sp. nov., and (F) Prasinohaema virens.

  • Table 1 Summary of UCE alignments.

    Ten samples with fewer than 499 (10%) UCE loci or missing voucher information were removed from our “ALL” data set. Our 1K data set removed all individuals with fewer than 1000 UCE loci, the TWO data set trimmed sampling to no more than two individuals per species, and the ONE data set removed all but one individual per species.

    Data setTaxaTotal length (bp)No. UCE loci in % taxa
    50%60%70%80%
    ALL1091,545,997408833311931542
    1K981,641,1064354395231951624
    TWO631,748,7744333394631371606
    ONE431,838,5404368398632201910
  • Table 2 Integrating over multiple models for stochastic character mapping.

    Three transition rate models (ARD, ER, and IR) and one mixed model were considered for stochastic character mapping. The number of simulations (Nsim) for each model was normalized using Akaike information criterion weights (wAIC) for that model and the mixed model sampled character histories from all three models. The transition rate matrix for a given model was either fixed at its empirical MLE or sampled using MCMC from its posterior distribution (MCMC). Rates (q), AIC scores, Likelihood (LnL), mean number of forward and reverse transitions, and PP of red blood reconstructed for the most recent common ancestor (MRCA) for all Prasinohaema are shown for the ONE-p70 tree. Models are described in the main text.

    Transition rate matrixModelModel summaryMean no. of changesPP of red-blooded MRCA
    qRGqGRAICwAICln (L)NsimRed→GreenRed←Green
    MLE (fixed)ARD11.7137.232.20.386−14.13864.09.027.1
    ER11.811.832.50.332−15.33324.20.599.9
    IR10.60.032.80.282−15.42824.00.0100
    Mixed10003.92.281.4
    MCMCARD3.51.036.30.156−16.11563.90.1100
    ER3.83.833.50.622−15.76223.90.1100
    IR3.90.035.50.222−16.72224.00.0100
    Mixed10003.90.1100

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/4/5/eaao5017/DC1

    fig. S1. ML tree for ONE-i100.

    fig. S2. Species tree for ONE-i100.

    fig. S3. ML tree for ONE-p70.

    fig. S4. Species tree for ONE-p70.

    fig. S5. ML tree for TWO-i100.

    fig. S6. Species tree for TWO-i100.

    fig. S7. Species tree for TWO-p70 data set.

    table S1. Sampling information and data processing results.

    table S2. SH test results from the SH tests for monophyly of Prasinohaema.

    table S3. Partial and full monophyly of Prasinohaema.

    table S4. Model test results for the ONE-p70 and TWO-p70 data sets.

    table S5. Results from marginal ancestral state reconstructions and stochastic character mapping using the ONE and TWO data set as input.

    table S6. Results from stochastic mapping across gene trees and posterior trees.

  • Supplementary Materials

    This PDF file includes:

    • fig. S1. ML tree for ONE-i100.
    • fig. S2. Species tree for ONE-i100.
    • fig. S3. ML tree for ONE-p70.
    • fig. S4. Species tree for ONE-p70.
    • fig. S5. ML tree for TWO-i100.
    • fig. S6. Species tree for TWO-i100.
    • fig. S7. Species tree for TWO-p70 data set.
    • table S1. Sampling information and data processing results.
    • table S2. SH test results from the SH tests for monophyly of Prasinohaema.
    • table S3. Partial and full monophyly of Prasinohaema.
    • table S4. Model test results for the ONE-p70 and TWO-p70 data sets.
    • table S5. Results from marginal ancestral state reconstructions and stochastic character mapping using the ONE and TWO data set as input.
    • table S6. Results from stochastic mapping across gene trees and posterior trees.

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