DOI: 10.5061/dryad.v15dv4274
title: 3RAD datasets used for phylogenomic, species delimitation, biogeography, and introgression analyses on Dugesia from Corsica and Sardinia

description: Speciation is a complex process where many evolutionary forces interplay.
 The Mediterranean is acknowledged as one of the most relevant biodiverse
 areas in the Palearctic region and researchers have long studied the
 species inhabiting it to pursue the goals of evolutionary biology. Here,
 we study a complex of freshwater flatworm species of the genus Dugesia
 from Corsica and Sardinia using restriction site-associated DNA sequencing
 (specifically, 3RAD) data to unravel their evolutionary history and tackle
 the processes driving it. We assess the phylogenetic relationships and
 population structure within the group and evaluate new species boundaries
 using multispecies coalescent approaches. Furthermore, we offer insights
 into the environmental niche model of the group and use said model to
 guide our sampling efforts and collect and present molecular evidence for
 the first time of Dugesia leporii specimens, endemic from Sardinia last
 spotted in 1999. Our results indicate that paleoclimatic conditions rather
 than microplate tectonic dynamics were likely an important driver of
 diversification for the Corso-Sardinian group. Furthermore, our results
 warrant the taxonomic re-evaluation of the group as eight primary species
 candidates are established based on molecular data. Our study also reveals
 the first case of interspecific natural hybridization reported in
 Dugesiidae and, to our knowledge, in Tricladida. Finally, we discuss how
 this hybridization might constitute a new form of hybrid speciation.
description: # Dols-Serrate\_et\_al\_2025\_3RAD\_Dugesia
 [https://doi.org/10.5061/dryad.v15dv4274](https://doi.org/10.5061/dryad.v15dv4274) ## Description of the data and file structure Demultiplexed data and datasets used for phylogenomic, biogeography, and introgression analyses on *Dugesia* species from Corsica and Sardinia. ### Files and variables #### File: `Dols-Serrate_et_al_MPE_2025.tar.gz` **Description:** These data were generated using the 3RAD sequencing protocol (details in Supplementary Materials and Methods) and processed with the Stacks v2.52 de novo pipeline (available at: [https://catchenlab.life.illinois.edu/stacks/manual/](https://catchenlab.life.illinois.edu/stacks/manual/)). The dataset includes demultiplexed sequencing data for all 90 samples, representing multiple *Dugesia* species from Corsica and Sardinia. Files contained within `Dols-Serrate_et_al_MPE_2025.tar.gz` : 1\) `Demultiplexed_data_90sample.tar.gz` A compressed file containing all **demultiplexed RAD pair-end** **reads** of all 90 sequenced samples for this study. Samples were processed with *process_radtags*, a program provided within the modular pipeline of Stacks. The following files are present for each processed sample: * `SAMPLE_ID.1.fq.gz` - file containing all first reads of pair-end sequencing. * `SAMPLE_ID.2.fq.gz` - file containing all second reads of pair-end sequencing. * `SAMPLE_ID.rem.1.fq.gz` - file containing discarded first reads due to low quality or missing restriction enzyme cut site. * `SAMPLE_ID.rem.2.fq.gz` - file containing discarded second reads due to low quality or missing restriction enzyme cut site. 2\) `popmap_10x_63.tsv` Popmap file containing the **63 samples that were used for subsequent downstream analyses** and their affiliation to a population. Sample IDs and population affiliation are written down in two tab-separed columns as follows: ``` SAMPLE_ID1POPULATION_ACRONYM1 SAMPLE_ID2POPULATION_ACRONYM1 SAMPLE_ID3POPULATION_ACRONYM2 [...] [...] ``` This is an example of the first five lines of the popmap_10x_63.tsv document: ``` MR1286_20 UC MR1286_25 UC MR1286_28 UC MR1286_29 UC MR1287_16 AI ``` The abovementioned `POPULATION_ACRONYM` variable within the popmap file describes the sample locality from which the samples were collected. Downstream analyses often require data filtering based, for the most part, on two capital parameters from the `populations` program (integrated within the modular pipeline of Stacks), namely `-r` and `-p`. * `-r` - controls the minimum percentage of individuals in a population required to process a locus for that population. * `-p` - controls the minimum number of populations a locus must be present in to process a locus. Thus, it is important to ensure that the popmap file has no typos or mispecified populations. In total, there are 17 population acronyms plus the acronym for the outgroup (*Dugesia hepta*, `HEP`), whose samples were treated as a unified population. The following list showcases the established acronyms and the population they refer to: ``` [Locality name, Island] [Population acronym] [Coordinates] Bunnari, Sardinia BU 40°42'05"N, 8°35'30"E Mascari, Sardinia MA 40°41'60"N, 8°35'23"E Mulinu, Sardinia MU 40°24'25"N, 8°37'35"E Monte Cidro, Sardinia MC 39°27'03.5"N, 8°28'27.3"E Fluminimaggiore, Sardinia FL 39°26'11.4"N, 8°30'35.1"E Sa Carcaredda, Sardinia SC 40°00'04.4"N, 9°25'16.0"E Monte Albo, Sardinia MT 40°34'30"N, 9°40'31"E Silis, Sardinia SI 40°45'24.0"N 8°43'28.0"E U Crocolli, Corsica UC 42°03'31.9"N, 8°57'54.5"E Aiaccio, Corsica AI 41°58'25.0"N, 8°49'53.4"E Corte, Corsica CT 42°18'18.3"N, 9°09'55.9"E Camping Campita, Corsica CC 42°23'34.2"N, 9°10'34.8"E Setti Polli, Corsica SP 41°55'43.9"N, 8°52'15.6"E Calvi, Corsica CA 42°29'10.8"N, 8°48'09.2"E Montegrosso, Corsica MG 42°32'17.4"N, 8°50'38.5"E Barchetta, Corsica BA 42°30'24.2"N, 9°22'27.3"E Turghja, Corsica TG 41°51'09.1"N, 8°58'00.1"E #############################[Outgroup]################################## Dugesia_hepta HEP Collected across BU, MA & SI ``` As an **important note**, the readership will notice that when performing phylogenetic tree inference analyses Stacks has a particular way of conducting things. If one wishes to obtain a tree wherein all samples are represented, the popmap file will require minor modifications. Namely, each sample should constitute its very own 'population', just as showcased in the example below: ``` MR1286_20 UC1286_20 MR1286_25 UC1286_25 MR1286_28 UC1286_28 MR1286_29 UC1286_29 MR1287_16 AI1287_16 ``` But then, what about `-r` and `-p` if each sample consitutes a population? Fear not, **the solution is simple.** The readership should first filter the loci using the regular `popmap_10x_63.tsv` file. After that, using the following UNIX command they will built a whitelist by processing one of the output files from `populations`: ``` grep -v "^#" populations.sumstats.tsv | cut -f 1 | sort | uniq &gt; whitelist.tsv ``` All filtered loci tags will be stored in the `whitelist.tsv` file. Then, the readership will have to run `populations` anew but this time with the modified popmap file while indicating the program to use the whitelist that we just created using the flag `-W` (path to a file containing whitelisted loci to include in the export), and specifying the desired output format. In our particular case for a phylogenetic tree, usually using the flag `--phylip-var-all`. Be sure to check all possible output formats of `populations` at [https://catchenlab.life.illinois.edu/stacks/comp/populations.php](https://catchenlab.life.illinois.edu/stacks/comp/populations.php) 3\) Folders `/Dryad_OP`, `/Dryad_DF` and, `/Dryad_OVM` . Each folder contains all intermediate datasets and loci catalogs produced from running the `denovo_map.pl` wrapper provided with the modular pipeline of Stacks, along with their corresponding blacklisted loci, which are used to filter loci and SNPs for downstream analyses. Assembly parameters need to be specified when using the de novo pipeline. There are three basic assembly parameters that the readership will care about: * `m` - minimum number of identical reads to establish a stack (an equivalent to an allele). * `M` - number of mismatches allowed between stacks **within** individuals to identify individual loci. * `n` - number of mismatches allowed between stacks **between** individuals to identify population or metapopulation loci. Each of the dataset folders herein provided comprise: * The `/Dryad_OP` folder includes loci assembled using the de novo RAD loci assembly parameters `m2 M1 n2` and all associated output files. * The `/Dryad_DF` folder contains loci assembled with the parameters `m3 M2 n1` and all their associated output files. * The `/Dryad_OVM` folder contains loci assembled with the parameters `m3 M5 n6` and all their associated output files. **Blacklists** were generated by filtering the `catalog.fa.gz` file from each RAD loci dataset (OP, DF, and OVM) to remove contaminants (see Materials and Methods and Supplementary Materials and Methods). These blacklists are labeled as `blacklist_*.tsv`. To reproduce any desired analysis, it is important to ensure that all Stacks output files provided within a given dataset folder are not modified or stored in different subfolders. Each sample within each data folder presents the following datasets: * `SAMPLE_ID.tags.tsv.gz` - assembled loci for a given sample. * `SAMPLE_ID.snps.tsv.gz` - model calls from each locus within a given sample. * `SAMPLE_ID.alleles.tsv.gz` - haplotypes/alleles recorded from each locus within a given sample. * `SAMPLE_ID.matches.tsv.gz` - matches of loci from a given sample to the loci catalog created from all processed samples. * `SAMPLE_ID.matches.bam` - sorted and collated matches to the catalog. Concurrently, within each folder there are the following datasets as well: * `catalog.fa.gz` - consensus catalog loci containing the consensus sequence for each locus produced by each processed sample. * `catalog.calls` - file containing the output of the SNP (single nucleotide polymorphism) calling model for each nucleotide in the analysis. * `catalog.snps.tsv.gz` - model calls from each locus in the analysis. * `catalog.tags.tsv.gz` - assembled loci in the analysis. * `catalog.alleles.tsv.gz` - haplotypes/alleles recorded in the analysis. Detailed instructions on the obtention of these datasets can be found in the Materials and Methods and Supplementary Materials and Methods sections of the manuscript ***Mixed, not stirred: Genomic data confirm the first case of interspecific hybridization in planarian triclads (Platyhelminthes: Tricladida) and raise questions about a possibly novel form of hybrid speciation*** (Dols-Serrate et al., 2025). Therein, the readership will find all indications and filtering steps necessary to reproduce the analyses performed with these data. A more thorough explanation of all Stacks output files contained within each data folder (OP, DF, and OVM) can be found at [https://catchenlab.life.illinois.edu/stacks/manual/#sfiles ](https://catchenlab.life.illinois.edu/stacks/manual/#sfiles)as well. #### Usage notes The following is a list of all different data types sorted by file suffix included in this repository along with brief descriptions on how to work with them. However, it is advisable not to meddle with any file, specially if it starts with `catalog*`, to avoid problems with file interpretation in downstream analyses. Descriptions of FASTA, and FASTQ file formats can be found in the SAMtools [file-format specifications page.](https://samtools.github.io/hts-specs/) **.bam:** Compressed binary sequence alignment/mapping format. Can be visualized with [SAMtools](https://github.com/samtools/samtools). **.tsv or .tsv.gz:** tab-delimited plain text files. These files can be viewed or manipulated with any plain text editor (e.g. `less` or `zless` UNIX command, Nano, Vim, etc.). **.fa.gz:** Compressed plain text DNA sequence information in FASTA format. **.fq.gz:** Compressed plain text DNA sequence information in FASTQ format. **.tar.gz:** Compressed archive file format obtained using the command `tar -czfv`. Can be decompressed using the UNIX command `tar -xvcf`.