DOI: 10.5061/dryad.37pvmcvsj
title: Evolution of bioluminescence in Anthozoa with emphasis on Octocorallia

description: Bioluminescence is a widespread phenomenon that has evolved multiple times
 across the tree of life, converging among diverse fauna and habitat types.
 The ubiquity of bioluminescence, particularly in marine environments where
 it is commonly used for communication and defense, highlights the adaptive
 value of this trait, though the evolutionary origins and timing of
 emergence remain elusive for a majority of luminous organisms. Anthozoan
 cnidarians are a diverse group of animals with numerous bioluminescent
 species found throughout the world’s oceans, from shallow waters to the
 light-limited deep sea where bioluminescence is particularly prominent.
 This study documents the presence of bioluminescent Anthozoa across depth
 and explores the diversity and evolutionary origins of bioluminescence
 among the Octocorallia – a major anthozoan group of marine luminous
 organisms. Using a phylogenomic approach and ancestral state
 reconstruction, we provide evidence for a single origin of bioluminescence
 in Octocorallia and infer the age of occurrence to around the Cambrian
 era, approximately 540 million years ago- setting a new record for the
 earliest timing of emergence of bioluminescence in the marine environment.
 Our results further suggest this trait was largely maintained in
 descendants of a deep-water ancestor and bioluminescent capabilities may
 have facilitated anthozoan diversification in the deep sea.
description: The recently published fossil-calibrated phylogeny (Quattrini et
 al. 2020) (1,729 loci) was used to map bioluminescent traits and depth
 categories across Anthozoa.  For the phylogenomic
 analyses, new fully-resolved phylogeny for Octocorallia reconstructed
 using target-capture sequence data (from 739 loci from 185 octocoral taxa)
 (McFadden et al. 2022), was used to investigate the evolution of
 bioluminescence in octocorals. The tree was constructed using maximum
 likelihood in IQTree v2.1 using the best model (GTR+F+R10).
 Divergence-dating of this recently revised octocoral tree was conducted
 using BEAST v 2.6 as outlined in Quattrini et al. (2020). First, a
 time-calibrated starting tree of the phylogeny in McFadden et al. 2022 was
 generated using penalized likelihood method
 (<em>chronopl</em>, based on 26) in the R package
 <em>ape</em>. The calibration points included the minimum ages
 of two fossils and a minimum age at the crown Octocorallia and at the root
 of the tree, obtained from Quattrini et al. (2020). We then selected a
 25-locus alignment to input into the BEAST v.2.6 analysis. In the BEAST
 analysis, loci were partitioned so that a GTRGAMMA model (initial 1.0, 0
 to infinity bounds) was applied to each locus. Exponential priors were
 used for fossil calibration points and a normal prior was applied to the
 crown Octocorallia and root of the tree, based on Quattrini et al. (2020).
 Two separate runs of 200M generations were conducted. Log and tree files
 from each run were combined in LogCombiner, with a 10% burnin. The
 combined log file was assessed for convergence of parameter values and age
 estimates by inspecting traces and effective sample sizes in Tracer v.1.7.
 Trees were combined from both runs, and resampled by selecting one out of
 every 10K trees, resulting in 75K trees. TreeAnnotator was then used to
 produce a maximum clade credibility tree based on mean ages. 
 We expanded the highly-supported tree generated using
 ultraconserved elements (UCE tree) by McFadden et al. 2022, by combining
 mitochondrial data, mutS-like DNA repair gene (mtMutS), for an additional
 107 octocoral taxa (McFadden et al. 2022) to produce a hybrid (UCE/MutS)
 phylogeny. Phylogenomic analyses were conducted using maximum likelihood
 and a partitioned analysis for multi-gene alignments with IQTree v2.1
 using both the concatenated UCE alignment (739 loci) and the alignment for
 mtMutS (McFadden et al. 2022). ModelFinder was used to find the best
 substitution model for each partition (UCE/mtMutS). The partition model
 was given discrete substitution models for each gene/character set and
 each partition was allowed to have its own evolution rate. Ultrafast
 bootstrapping (-bb 2000) and the Sh-like approximate likelihood ratio test
 (-alrt 1000) were conducted. The reconstructed tree was pruned using the
 phytools (v1.2-4) package in R (v3.5.0) to remove four aberrantly placed
 taxa with poorly supported nodes, based on the recently published
 phylogeny (McFadden et al. 2022). The final hybrid (UCE/MutS) octocoral
 tree consisted of 270 operational taxonomic units (or OTUs). The
 Scleralcyonacea clade was rooted to the Malacalcyonacea clade for
 downstream analysis uin R based on the findings of McFadden et al.
 (2022). For Ancestral State Reconstruction (ASR), trait
 tables were generated for octocoral taxa represented in both the
 time-calibrated UCE tree (185 OTUs) and the UCE/MutS hybrid tree (270
 OTUs) based on a scale of 0-1 (0: <em>Non-bioluminescent or
 unlikely</em>; 1: <em>Likely bioluminescent or
 confirmed</em>; NA or 0.5: <em>unknown</em>). Ancestral
 states of bioluminescence were calculated using stochastic character
 mapping, sampling ancestral states from posterior probability
 distributions generated from 100 stochastic character maps for the
 bioluminescence trait using the <em>make.simmap</em> function
 (nsim=100) in the R package phytools. The best fit model was determined by
 fitting and comparing the extended Mk models (<em>fitMk</em>)
 for discrete character evolution. Akaike information criterion (AIC)
 values for the fitted models were then compared to determine the model
 with the lowest AIC score. This was determined to be the ARD model
 assuming different rates of trait gain/loss, which was utilized for
 downstream analysis. Phytools was then used to plot one stochastic
 character map for the bioluminescence trait on both the time-calibrated
 phylogeny for Octocorallia (UCE tree) and the more inclusive hybrid tree,
 along with the posterior probabilities (pie charts) at each
 node. To estimate the ancestral depth ranges, a
 Bayesian dispersal-extirpation-cladogenesis (DEC) model implemented in
 RevBayes was conducted on the dated, maximum clade credibility tree.
 Ancestral ranges of shallow (&lt; 200 m) and deep-sea (&gt; 200 m)
 depths were estimated following the guidelines in the online tutorial on
 simple analysis of historical biogeography (https://revbayes.github.io/tutorials/biogeo/biogeo_simple.html). Current depth ranges were coded as binary values (0,1) whether a species was recorded from deep, shallow, or both depth ranges. Depths were obtained from obis.org and supplemented with recent museum (NMNH) and geome (geome-db.org) records and the literature. For species identified to a rank above genus, the depth of collection was used. In RevBayes, the number of generations (MCMC) was set to 5000. The R package <em>RevGadgets </em>was then used to plot the probability of ancestral states (as pie charts) at the nodes.
description: # Evolution of bioluminescence in Anthozoa with emphasis on Octocorallia
 Access this dataset on Dryad:
 Bioluminescence is a
 widespread phenomenon. Anthozoan cnidarians are a diverse group of animals
 with numerous bioluminescent species found throughout the world’s oceans,
 from shallow waters to the light-limited deep sea where bioluminescence is
 particularly prominent. This study documents the presence of
 bioluminescent Anthozoa across depth and summarizes those findings here.
 Further, it explores the diversity and evolutionary origins of
 bioluminescence among Octocorallia – a major anthozoan group of marine
 luminous organisms. Using phylogenomic analyses, including the production
 of a fossil-calibrated phylogeny for Octocorallia, and ancestral state
 reconstruction (ASR) for bioluminescent traits and ocean depth habitats,
 we provide evidence for a single origin of bioluminescence in Octocorallia
 and infer the age of occurrence to around the Cambrian era, approximately
 540 million years ago. The findings set a new record for the earliest
 timing of emergence of bioluminescence in the marine environment and
 suggest this trait was largely maintained in descendants of a deep-water
 ancestor. ## Description of the data and file structure ### Supplementary
 files from the manuscript, including compiled metadata for the main
 figures (Zenodo): ##### DeLeo\_TableS1\_Fig1\_metadata.csv Metadata for
 the Anthozoa phylogeny (Figure 1), including (columns): species name,
 depth code (deep, shallow, shallow/deep), and bioluminescent trait coding
 (Biolum: 0=unlikely or non-bioluminescent; 1=likely or confirmed
 bioluminescent; NA is unknown). Depth code was based on known genus-level
 depth ranges (shallow &lt; 200 m; deep &gt; 200 m; shallow/deep range
 spans both). Bioluminescent traits were defined as bioluminescent (species
 or genus-level record), non-bioluminescent (negative record at species or
 genus level), or unknown (no record). #####
 DeLeo\_TableS3\_Fig3\_metadata.csv Metadata for the
 fossil-calibrated/dated Octocorallia phylogeny (Figure 3), including
 (columns): sample ID, species name, depth code, and bioluminescent trait
 coding. These depth categories and trait codes were used to run Ancestral
 State Reconstructions with R using the code and files below. #####
 DeLeo\_TableS4\_UCEmutStree\_metadata.csv Trait coding for hybrid UCE/mutS
 Octocorallia phylogeny (Figure S4). Includes (columns): sample ID, species
 name, bioluminescent category (B) (0=unlikely or non-bioluminescent;
 1=likely or confirmed bioluminescent; NA is unknown). #####
 DeLeo\_TableS5\_BioluminescentAnthozoaSummary.xlsx Compiled summary list
 of luminous anthozoans from this and previous studies, including
 references and field notes to facilitate future work. ### beast\_final.zip
 Files associated with the BEAST analysis and fossil-calibrating the
 Octocorallia tree: Contents of zip folder include: #### Files 1.
 25loci_v3_nov22_oct.xml is an xml file created in BEAUTI and modified in a
 text editor according to the BEAST2 tutorial. This file is used as an
 input in BEAST analyses 2. 25loci.comb.loci.final.log is the combined log
 file generated from combing log files from the two different runs
 (newrun3, newrun4). This file was created with LogCombiner. 3.
 DeLeo_octo.mcc.mean.tree is the maximum clade credibility tree based on
 mean ages. This treefile was produced by TreeAnnotator, after combining
 treefiles from the two different runs (newrun3, new run4). #### Results
 directories In each result directory include files produced by BEAST (log
 gile, state file, .trees file) as well as the job file used to start the
 BEAST run on Smithsonian’s High Performance Computing System, Hydra. 1.
 newrun3_results is a results folder containing the results from a single
 BEAST run (250M generations) using the supplied xml file as input. 2.
 newrun4_results is a results folder containing the results from a single
 BEAST run (250M generations) using the supplied xml file as input. ###
 Code for Ancestral State Reconstruction analyses (.R), and the final dated
 Octocorallia tree (.tree) and trait table (.csv) used to run the ASR:
 ##### DeLeo\_ASRcode\_octoUCEdatedtree.R (Zenodo) Code used to run the ASR
 analyses on the dated Octocorallia tree produced from BEAST, and plot
 those reconstructions onto the tree. #####
 datedtree\_biolumtraits\_new05\_jan24.csv Trait file used to run the ASR
 for bioluminescence. Columns include 1) species name (must match exact
 names in BEAST tree, below) and 2) bioluminescent trait category (B:
 0=unlikely or non-bioluminescent; 1=likely or confirmed bioluminescent;
 0.5 = NA or unknown). ##### DeLeo\_octo.mcc.mean\_labeled.tree Dated tree
 file produced from BEAST that was read into R and used for the ASR
 analyses using the above code. #####
 datedtree\_biolumtraits\_new05\_jan24\_TEST.csv The modified trait table
 used to run the test ASR analysis - labeling all unknowns as
 "non-bioluminescent" or "0," instead of
 "unknown" or "0.5," using same ASR code above. ###
 Code and files to conduct depth range analyses in RevBayes followed by
 plotting in R. Code also followed in Revbayes online tutorials
 : #####
 DeLeo\_RevBayesDepthRangeCode.txt (Zenodo) Contains code adapted from the
 Revbayes tutorial (above) to conduct the ancestral depth range analyses on
 the BEAST tree (DeLeo_octo.mcc.mean_labeled.tree) using the depth
 categories listed in DeLeo_TableS3_Fig3_metadata.csv. Additional code then
 plots those reconstructions onto the tree in R. ### Alignment (.phy) and
 partition (.nex) files (including run log) to assemble the hybrid UCE/MutS
 tree with IQTree: ##### partitions\_tested.nex.log,
 alltaxa\_mutS\_ucenames\_final.phy, and partitions\_combined.nex The final
 concatenated alignment file (.phy) for the UCE/MutS hybrid tree after
 partition testing with ModelFinder (.nex), including the log file for this
 partition testing and alignment conducted in IQTree (.log) #####
 octo.comb.prune.6oct22.withlabs.final.r.tree Final curated and labeled
 hybrid UCE/MutS tree produced from IQTree and used to run the ASR analysis
 in R, with metadata associated with the tree species found in
 DeLeo_TableS4_UCEmutStree_metadata.csv. #### Data file that can be used to
 make the histograms and evaluate depth distributions #####
 GenusBinDepthBiolum.tsv Tab-separated file that was used to generate
 Figure 2 and Figure S2, showing octocoral abundance across depth. The
 depth distributions of octocorals were observed during ROV dives offshore
 of Monterey Bay, California. Species were categorized based on the trait
 table as likely to be bioluminescent (species or genus level observation)
 or undefined (no record). File contains (columns) information on: genus,
 depth in meters (BinDepth) and bioluminescent category (Biolum). ##
 Sharing/Access information Links to other publicly accessible locations of
 the BEAST and R code used to process these data: *
 *
 Data was derived
 from the following sources: *
 *