DOI: 10.5061/dryad.hqbzkh1nb
title: Files for phylogenetic analyses and molecular diagnosis between Diplomystidae catfish species

description: Diplomystidae is an early-diverged family of freshwater catfish endemic to
 southern South America. We have recently collected five juvenile specimens
 belonging to this family from the Bueno River Basin, a basin which the
 only previous record was a single juvenile specimen collected in 1996.
 This finding confirms the distribution of the family further South in
 northern Patagonia, but poses new questions about the origin of this
 population in an area with a strong glacial history. We used phylogenetic
 analyses to evaluate three different hypotheses that could explain the
 origin of this population in the basin. First, the population could have
 originated in Atlantic basins (East of the Andes) and dispersed to the
 Bueno Basin after the Last Glacial Maximum (LGM) via river reversals, as
 it has been proposed for other population of Diplomystes as well as for
 other freshwater species from Patagonia. Second, the population could have
 originated in the geographically close Valdivia Basin (West of the Andes)
 and dispersed south to its current location in the Bueno Basin. Third,
 regardless of its geographic origin (West or East of the Andes), the Bueno
 Basin population could have a longer history in the basin, surviving in
 situ through the LGM. In addition, we conducted species delimitation
 analyses using a recently developed method that uses a protracted model of
 speciation. Our goal was to test the species status of the Bueno Basin
 population along with another controversial population in Central Chile
 (Biobío Basin), which appeared highly divergent in previous studies with
 mtDNA. The phylogenetic analyses showed that the population from the Bueno
 Basin is more related to Atlantic than to Pacific lineages, although with
 a deep divergence that predated the LGM, supporting in situ survival
 rather than postglacial dispersal. In addition, these analyses also showed
 that the species D. nahuelbutaensis is polyphyletic, supporting the need
 for a taxonomic reevaluation. The species delimitation analyses supported
 two new species which are described using molecular diagnostic characters:
 Diplomystes arratiae sp. nov. from the Biobío, Carampangue, and Laraquete
 basins, maintaining D. nahuelbutaensis valid only for the Imperial Basin,
 and Diplomystes habitae sp. nov. from the Bueno Basin. This study greatly
 increases the number of species within both the family Diplomystidae and
 Patagonia, and contributes substantially to the knowledge of the evolution
 of southern South American freshwater biodiversity during its glacial
 history. Given the important contribution to the phylogenetic diversity of
 the family, we recommend a high conservation priority for both new
 species. Finally, this study highlights an exemplary scenario where
 species descriptions based only on DNA data are particularly valuable,
 bringing additional elements to the ongoing debate on DNAbased taxonomy.
description: 2. MATERIAL AND METHODS 2.1<em>
 Sampling</em> A total of eight individuals from
 the Bueno Basin were collected during the summer 2019 (n= 3) and 2021 (n=
 5) from two different sections of the Bueno River (-40,2528 -72,6178 and
 -40.2561 -72.5942, respectively) near the outlet of Ranco Lake (figure 1).
 Specimens from 2019 were released alive after collecting a small piece of
 the adipose fin by clipping. Specimens from 2021 were kept as vouchers.
 All the vouchers show a long and continuous lateral line typical of the
 genus <em>Diplomystes</em>, so they were assigned to this
 genus following Arratia & Quezada-Romegialli (2017). Additionally,
 three individuals from the coastal basins Laraquete and Carampangue
 (Muñoz-Ramírez et al., 2020), genetically close to populations from the
 Biobío Basin, were included to increase data from the Biobío lineage for
 the species delimitation analysis and were considered for all purposes as
 part of the Biobío Basin, due to their close geographical and genetic
 proximity.  2.2 <em>Lab protocols and molecular
 data</em> A small tissue sample from the adipose
 fin or muscle from each specimen was used for DNA extraction, which was
 conducted using the DNeasy Tissue Kit (QIAGEN Inc., Chatsworth CA)
 following de manufacturer’s protocol. All individuals were amplified for
 two mitochondrial DNA regions, the Cytochrome B (cytB) and the control
 region (CR), and portions of two nuclear genes, the GH (growth hormone,
 exons three through ﬁve and introns three and four), and the S7 (intron
 one) following Muñoz-Ramírez et al., (2014). These newly generated data
 were complemented with published data from Muñoz-Ramírez et al. (2014,
 2020) to conduct all analyses (see Supplementary Material Table S1 for
 additional details and GenBank accession numbers). 2.3
 <em>Phylogenetic estimation</em> The
 phylogenetic position of the Bueno population was estimated in two ways.
 First, a Maximum Likelihood genealogy was estimated using RAxML-NG v. 1.1.0 (Kozlov, 2019)
 with mtDNA regions cytB and CR concatenated. Each mtDNA region was treated
 as a separate partition with its own model of molecular evolution.
 Best-fit models of molecular evolution were chosen by Modeltest-NG
 (Darriba et al. 2020) using the Bayesian information criterion (BIC). The
 RAxML analysis was estimated with 1000 nonparametric bootstrap replicates
 , followed by a search for the best-scoring ML tree. 
 Second, we estimated a population tree using the coalescent
 method StarBeast3 (Douglas, Jiménez-Silva, & Bouckaert, 2022)
 implemented as part of the software BEAST2 v2.6.6.0 (Bouckaert et al.,
 2014) using both the mtDNA and nuclear data (three independent loci). The
 cytB and CR gene regions were linked as one single locus (mtDNA), but
 analyzed as two separate partitions for the site model estimations. Each
 nuclear locus, GH and S7, was analyzed as a separate locus. A total of 22
 individuals were assigned into populations represented by Andean Basins,
 with the sole exception of the Rapel and Mataquito basins which were
 merged as one single population given recent evidence of panmixia
 (Muñoz-Ramírez, Victoriano, & Habit, 2015). The analysis was run
 specifying models of molecular evolution based on results from
 Modeltest-NG (Darriba et al., 2020). The strict clock model was selected
 over the relaxed clock model via the Bayes Factor method (Kass &
 Raftery, 1995) after obtaining the marginal likelihoods by the Path
 Sampling method (Baele, Li, Drummond, Suchard, & Lemey, 2012). A
 Yule prior was used for the species tree. To estimate dates for each node
 we used a calibration point for the divergence between the Chubut and the
 Baker populations based on geological evidence for the reversal of the
 Chubut Basin after ice-dam collapse between 12.6–11.7 ka (Benito &
 Thorndycraft, 2020). A normal distribution with mean 0.01215 ka and a
 standard deviation of 2.5E-4 ka, with fixed monophyly for the Chubut-Baker
 clade, was used as prior. The MCMC chains were run for 500 million
 generations, sampling every 50,000 generations to produce 10,000 sampling
 values. Parameter estimates were checked for convergence in Tracer v1.4
 (Rambaut and Drummond, 2007), discarding the ﬁrst 20% of the samplings as
 burn-in. The species tree was finally obtained by summarizing the sampled
 trees in the TreeAnnotator application removing the first 20 % of trees as
 burn-in. 2.4 Species Delimitation and DNA
 diagnosis To test whether the Bueno Basin and the
 Biobío Basin represent parts of known species or new species, we use a
 recently developed speciation-based approach called Delineate (Sukumaran,
 Holder, & Knowles, 2021). Classical approaches to species
 delimitation based on the Multispecies Coalescent (MSC) identify
 disruptions in Wright-Fisher panmixia due to gene flow barriers, and
 assume that these disruptions are explained by species boundaries (Yang
 & Rannala 2010). As has been noted (Sukumaran & Knowles
 2017), however, if there is within-species lineage structuring, then, as
 long as there is sufficient power available with the data sampled, these
 approaches will result in conflation of population units with species
 units, resulting in spurious species boundaries as distinct populations
 are mis-characterized as distinct species. In contrast, while DELINEATE
 relies on the Multispecies Coalescent (MSC) as well, it only uses it to
 first diagnose population units. It then infers the actual species
 boundaries using an explicit probabilistic speciation process model that
 organizes these population units into higher-level species units. The
 DELINEATE approach accounts for the possibility that some structure does
 not involve speciation events by modeling the formation of population
 lineages and their subsequent development into independent species as
 separate processes. DELINEATE uses information about the current taxonomy
 of the taxa as understood by the investigator to calibrate the model.
 Specifically, the investigator provides species identities for a subset of
 the population lineages being considered. These “known” species identities
 for this subset of population are used to infer a tempo of speciation,
 i.e., the rate at which an independent population lineage evolves into
 distinct species, for the entire system. With this, the probabilities of
 different species delimitation configurations can be calculated and
 ranked, with the species delimitation of the highest probability
 constituting the maximum likelihood estimate species delimitation. This
 estimate of course includes the species assignments for the subset of
 population lineages as provided by the investigator, but it will also
 include species assignments for the remaining lineages, i.e., the
 population lineages of uncertain, unknown, or undetermined species
 affinities. Each of these population lineages of unknown species
 affinities will be assigned a species identity. Each of the populations of
 unknown species affinities may end up being categorized as a population of
 a species previously identified by the investigator or, alternatively, as
 a population of “new” unnamed species, previously undisclosed or
 undeclared by the investigator. We use the tree
 inferred by StarBeast3 as the input tree of population lineages required
 for DELINEATE. For the taxonomic information required, we considered two
 different schemes. One scheme considered the currently accepted taxonomic
 view of the family, with three extant species for the Pacific basins and
 three species for the Atlantic basins (hereafter the Azpelicueta scheme;
 Azpelicueta, 1994). The second scheme reflects a more conservative
 taxonomic view that considers all species from Atlantic basins as a single
 one (hereafter the Arratia scheme; Arratia, 1987). Although the latter is
 not the prevailing view for the Atlantic taxonomic diversity, we used it
 to test the robustness of results under a more conservative scenario that
 would make splitting more difficult (i.e. by decreasing the speciation
 rate parameter). Given the uncertainty about the
 taxonomic status of the Biobío population (Muñoz-Ramírez et al., 2014),
 only the population from the Imperial Basin was assigned to
 <em>Diplomystes nahuelbutaensis </em>because the Holotype of
 this species is from the Imperial Basin, whereas the status of the Biobío
 population was left to be tested by the analysis. The Baker Basin
 population is included as part of the Chubut basin, and therefore under
 the same taxonomic status of Chubut, after Muñoz-Ramírez et al.,
 (2014). Once the results of the species delimitation
 analyses were available, molecular diagnostic characters were obtained for
 DNA diagnosis using the nucDIAG function from the R-package SPIDER (Brown
 et al. 2012). All gene regions were used, including the cytB and CR
 sequence alignments and the nuclear gene alignments, although for the CR,
 a portion of 90 bp (positions 33-122) was not considered because it
 contained large portions of gaps in most individuals. 
 2.5 <em>Estimating Conservation value using phylogenetic
 diversity</em> The conservation value of each
 basin was measured regarding the contribution of the lineage or species
 present at a given basin to the overall phylogenetic diversity (PD) of the
 entire family. This was obtained by calculating the proportion of PD that
 is lost when a given basin population is removed, repeating this procedure
 for each basin. PD and complementary calculations were conducted using the
 caper R-package (Orme et al. 2013) on the population tree obtained with
 StarBeast3. Coastal basins were not included given their comparatively
 small size and because the two coastal basins harboring Diplomystids are
 historically part of the larger Andean Biobío basin. 
description: These data contain different types of files: 
 Sequence alignments for molecular diagnosis
 script with functions to conduct phylogenetic diversity
 analysis XML files to run starBeast
 analysis Here is a brief description of
 each file included in this data:
 cr_cb_gh_s7_monophyly_prior.xml: <br>Input file to run
 beast, using the starBEAST3 package to estimate a dated species tree. The
 file is set to force the monophyly of a pair of populations (Baker and
 Chubut) (monophyly prior).
 cr_cb_gh_s7_no_monophyly_prior.xml: <br>Input file to run
 beast, using the starBEAST3 package to estimate a dated species tree. The
 monophyly of a pair of populations (Baker and Chubut) is not constrained
 (no monophyly prior).
 211_Diplos_RC.fas: <br>Alignment file with 211 sequences of
 a portion of the mitochondrial control region representing individuals of
 the catfish family Diplomystidae from 15 river basins. This file is used
 for the molecular diagnosis analysis, called from the R script file
 Diagnostic_nucleotides.R.
 212_Diplos_CytB.fas: <br>Alignment file with 212 sequences
 of a portion of the mitochondrial cytochrome b gene representing
 individuals of the catfish family Diplomystidae from 15 river basins. This
 file is used in the molecular diagnosis analysis, called from the R script
 file Diagnostic_nucleotides.R.
 S723.fas: <br>Alignment file with 23 sequences of a portion
 of the nuclear S7 gene (intron 1) representing individuals of the catfish
 family Diplomystidae from 15 river basins. This file is used in the
 molecular diagnosis analysis, called from the R script file
 Diagnostic_nucleotides.R. GH23.fas: <br>Alignment
 file with 23 sequences of portions of the nuclear growth hormone (GH) gene
 representing individuals of the catfish family Diplomystidae from 15 river
 basins. This file is used in the molecular diagnosis analysis, called from
 the R script file Diagnostic_nucleotides.R.
 Diagnostic_nucleotides.R: <br>R script file with commands
 used to run the molecular diagnostic analyses. 
 vouchers_for_DiagNuc_CR.csv: <br>Data frame containing
 grouping factors for the control region sequence alignments needed to run
 the DNA diagnostic analyses in the R script
 Diagnostic_nucleotides.R
 vouchers_for_DiagNuc_cytb.csv: <br>Data frame containing
 grouping factors for the cytochrome b sequence alignment needed to run the
 DNA diagnostic analyses in the R script Diagnostic_nucleotides.R
 nucleares_vouchers.csv: <br>Data frame containing grouping
 factors for the nuclear sequence alignment needed to run the DNA
 diagnostic analyses in the R script Diagnostic_nucleotides.R
description: # Files for phylogenetics analyses and molecular diagnosis between
 Diplomystidae catfish species This data contain files to conduct species
 tree analyses with starBEAST, a prerequisite for the DELINEATE analyses
 and to conduct the molecular diagnostic analyses. The results of these
 analyses are presented in figures and tables in a manuscript ##
 Description of the data and file structure These are several files used to
 conduct different types of analyses. cr_cb_gh_s7_monophyly_prior.xml:
 Input file to run beast, using the starBEAST3 package to estimate a dated
 species tree. The file is set to force the monophyly of a pair of
 populations (Baker and Chubut) (monophyly prior).
 cr_cb_gh_s7_no_monophyly_prior.xml: Input file to run beast, using the
 starBEAST3 package to estimate a dated species tree. The monophyly of a
 pair of populations (Baker and Chubut) is not constrained (no monophyly
 prior). 211_Diplos_RC.fas: Alignment file with 211 sequences of a portion
 of the mitochondrial control region representing individuals of the
 catfish family Diplomystidae from 15 river basins. This file is used for
 the molecular diagnosis analysis, called from the R script file
 Diagnostic_nucleotides.R. 212_Diplos_CytB.fas: Alignment file with 212
 sequences of a portion of the mitochondrial cytochrome b gene representing
 individuals of the catfish family Diplomystidae from 15 river basins. This
 file is used in the molecular diagnosis analysis, called from the R script
 file Diagnostic_nucleotides.R. S723.fas: Alignment file with 23 sequences
 of a portion of the nuclear S7 gene (intron 1) representing individuals of
 the catfish family Diplomystidae from 15 river basins. This file is used
 in the molecular diagnosis analysis, called from the R script file
 Diagnostic_nucleotides.R. GH23.fas: Alignment file with 23 sequences of
 portions of the nuclear growth hormone (GH) gene representing individuals
 of the catfish family Diplomystidae from 15 river basins. This file is
 used in the molecular diagnosis analysis, called from the R script file
 Diagnostic_nucleotides.R. Diagnostic_nucleotides.R: R script file with
 commands used to run the molecular diagnostic analyses.
 vouchers_for_DiagNuc_CR.csv: Data frame containing grouping factors for
 the control region sequence alignments needed to run the DNA diagnostic
 analyses in the R script Diagnostic_nucleotides.R
 vouchers_for_DiagNuc_cytb.csv: Data frame containing grouping factors for
 the cytochrome b sequence alignment needed to run the DNA diagnostic
 analyses in the R script Diagnostic_nucleotides.R nucleares_vouchers.csv:
 Data frame containing grouping factors for the nuclear sequence alignment
 needed to run the DNA diagnostic analyses in the R script
 Diagnostic_nucleotides.R ## Sharing/Access information Sequence data can
 be accessed from GenBank accession numbers: ## Code/Software Commands,
 functions, and packages used in the R environment are described in detail
 in the file Diagnostic_nucleotides.R.