DOI: 10.5061/dryad.tx95x69zc
title: Data from: Lineage diversity within a widespread endemic Australian skink to better inform conservation in response to regional-scale disturbance

description: This dataset was used to examine the phylogeographic genetic structure of
 Eastern three lined skink Bassiana duperreyi. It comprises  SNP
 data used for population genetics and phylogenetic reconstruction. The
 data were used to provide foundational work for the detailed taxonomic
 re-evaluation of this species complex and to reinforce the need for
 biodiversity assessment to include an examination of cryptic species
 and/or cryptic diversity below the level of species. Such information on
 lineage diversity within species and its distribution in the context of
 disturbance at a regional scale can be factored into conservation planning
 regardless of whether a decision is made to formally diagnose new species
 taxonomically and nomenclaturally.
description: Briefly, samples of tissue were collected from across the range
 of the species, <em>Bassiana duperreyi,</em> including from
 Australian Museums, DNA was extracted, double digested and genotyped for
 SNP markers using the technology of Diversity Arrays Technology (DArT,
 Canberra). The data were analysed in the software package dartR available
 on the CRAN repository, as per the script provided. Structure across the
 landscape was used to inform assessment of the impact of regional scale
 disturbance. Skin tissues and extracted DNA were
 provided to DArT for processing, sequencing and informative SNP marker
 identification using DArTseqTM (Kilian et al., 2012). DArT performed a
 genome complexity reduction technique using double digestion of genomic
 DNA with two restriction endonucleases PstI (5′- CTGCA|G- 3′) and SphI
 (5′- GCATG|C- 3′), fragment-size selection and next-generation sequencing
 on an Illumina HiSeq2500 (CA, USA). Sequences were processed using
 proprietary DArT analytical pipelines (for full details refer to Georges
 et al. (2018). Initial filtering was based primarily on average and
 variance of sequencing depth, average allele counts and call rate across
 samples. Approximately one-third of samples were sequenced twice as
 technical replicates, with scoring consistency identifying high quality
 SNP markers with low error rates. We applied further quality control
 filtering using the R package dartR 2.7.2 (Gruber et al., 2018; Mijangos
 et al., 2022).  These filters were for reproducibility across technical
 replicates (&lt; 99%), call rate removing both loci and individuals
 with &gt; 5% missing data, read depth (&lt; 8x and above &gt;
 50x) to remove low coverage SNPs and potential paralogs and by removing
 all but one of multiple SNPs per locus.
description: The script necessary to undertake the SNP analyses depends on the
 R software package dartR.base available on the Comprehensive R Archive Network (CRAN). dartR.base works with adegenet genlight objects such as those in the file list provided. Software for undertaking phylogenetic analysis on the SNPs include SVDQuartets (Singular Value Decomposition Quartets, Chifman & Kubatko, 2014) available through Paup (Swofford, 2003).
description: # Data from: Lineage diversity within a widespread endemic Australian
 skink to better inform conservation in response to regional-scale
 disturbance This Dryad
 entry contains the datafiles and associated R script to prepare the data
 in a form conducive to analysis, including the analyses presented in the
 companion article. They include SNP datasets for the Eastern three-lined
 skink *Bassiana duperreyi*. ## Description of the data and file structure
 The SNP data comprises a matrix of entities (individuals) versus
 attributes (loci) taking on the states 0 for homozygous reference allele,
 2 for homozygous alternate allele and 1 for the heterozygous state. As
 such, the data have no units of measurement but do when summed,
 conveniently, represent the frequency of the alternate allele. The data
 are stored in compressed form as an adegenet genlight object with
 associated locus metadata (e.g. callrate, reproducibility) and individual
 metadata (e.g. latitude, longitude, population). The SNP scores can be
 examined in R with as.matrix(gl); the names of the locus metadata can be
 obtained with names(gl@other$loc.metrics); the names of the individual
 metadata can be obtained with names(gl@other$ind.metrics). Locus metadata
 are: | AlleleID | Unique identifier for the sequence in which the SNP
 marker occurs | | :-------------- |
 :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | AlleleSequence | In 1 row format: the sequence of the Reference allele. In 2 rows format: the sequence of the Reference allele is in the Ref row, the sequence of the SNP allele in the SNP row | | AvgCountRef | The sum of the tag read counts for all samples, divided by the number of samples with non-zero tag read counts, for the Reference allele row | | AvgCountSnp | The sum of the tag read counts for all samples, divided by the number of samples with non-zero tag read counts, for the SNP allele row | | AvgPIC | The average of the polymorphism information content (PIC) of the Reference and SNP allele rows | | CallRate | The proportion of samples for which the genotype call is either "1" or "0", rather than "-"  | | CloneID | Unique identifier for the sequence in which the SNP marker occurs | | FreqHets | The proportion of samples which score as heterozygous | | FreqHomRef | The proportion of samples which score as homozygous for the Reference allele | | FreqHomSnp | The proportion of samples which score as homozygous for the SNP allele | | OneRatioRef | The proportion of samples for which the genotype score is "1", in the Reference allele row | | OneRatioSnp | The proportion of samples for which the genotype score is "1", in the SNP allele row | | PICRef | The polymorphism information content (PIC) for the Reference allele row | | PICSnp | The polymorphism information content (PIC) for the SNP allele row | | RepAvg | The proportion of technical replicate assay pairs for which the marker score is consistent | | SNP | In 2 rows format: this column is blank in the Reference row, and contains the base position and base variant details in the SNP row. In 1 row format: contains the base position and base variant details | | SnpPosition | The position (zero indexed) in the sequence tag at which the defined SNP variant base occurs | | TrimmedSequence | Same as the full sequence, but with removed adapters in short marker tags | Individual metadata are: | no | Specimen identifier | | :-------- | :------------------------------------------- | | id | Sample identifier | | pop | Population code | | popname | Population name | | legend | Location label useful for figure legends | | bioregion | Bioregion from which the animal was captured | | species | Species of lizard | | elevation | Elevation above sea level | | age | Age category, e.g. adult, neonate | | lat | Latitude of location of capture | | lon | Longitude of location of capture | Missing data are scored as NA. Missing data arise both because the target sequence tag is present in the genome but missed by chance because of finite read depth or because the sequence tag is not amplified because of a mutation at one or both of the restriction enzyme sites (null allele). **1.       Report_DSk20-4927_1_moreOrders_SNP_2.csv** Raw data as provided by Diversity Arrays Technology in 2-row format. Refer to for details of this format, and to Georges et al. (2018) for an overview of how the data were generated. **2.       Report_DSk20-4927_1_moreOrders_SNP_3.csv** Raw data as provided by Diversity Arrays Technology in 2-row format. Refer to for details of this format, and to Georges et al. (2018) for an overview of how the data were generated. \**3.       metadata_raw.csv        ** Metadata associated with each individual, including population assignments, sex, stage of maturity and location of capture. **4.       bassiana_raw.Rdata** Contains the raw data, as per **Report_DSk20-4927_1_moreOrders_SNP_2.csv **and** Report_DSk20-4927_1_moreOrders_SNP_3.csv **in binary format. Can be read in to dartR using gl &lt;- readRDS(file="bassiana_raw.Rdata") **5.       bassiana_full.Rdata** Contains the data post filtering (see **R_code_final_Dryad.r) **for all individuals in the study. Can be read in to dartR using gl &lt;- readRDS(file="bassiana_full.Rdata") **6.       bassiana_ingroup.Rdata** Contains the data post filtering (see **R_code_final_Dryad.r) **for the ingroup taxon *Bassiana duperreyi* only. Can be read in to dartR using gl &lt;- readRDS(file="bassiana_ingroup.Rdata") **7.       R_code_final_Dryad.r**    R code used to generate the results. Point of entry is indicated, and begins by reading in the data from one of bassiana_raw.Rdata, bassiana_full.Rdata or bassiana_ingroup.Rdata using the function readRDS().To access the datasets (those with .Rdata extension), use my.genlight.object &lt;- readRDS("path/filename") or dartR.base::gl.load(("path/filename"). To interrogate the datasets after loading, use the accessors provided in the R package {adegenet}. Refer to the accompanying ms_initial_read.R. ## Code/Software The script necessary to undertake the SNP analyses depends on the R software package dartR.base available on the [Comprehensive R Archive Network (](https://www.google.com.au/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjDscuY5ZWDAxWDrVYBHU41D_0QFnoECBUQAQ&url=https%3A%2F%2Fcran.r-project.org%2F&usg=AOvVaw0pGNScRjIdSkNXK6Ky1j_m&opi=89978449)CRAN). dartR.base works with adegenet genlight objects such as those listed above. Software for undertaking phylogenetic analysis on the SNPs include SVDQuartets (Singular Value Decomposition Quartets, Chifman & Kubatko, 2014) available through Paup (Swofford, 2003). ## Data availability These data are freely available unconditionally for download and use. Although some of the data were generated using a commercial service, the intellectual property associated with the data reside entirely with the authors, and their are no restrictions on use arising. ## References Chifman, J., & Kubatko, L. (2014). Quartet inference from SNP data under the coalescent model. *Bioinformatics*, *30*, 3317–3324. Georges, A., Gruber, B., Pauly, G., Adams, M., White, D., Young, M., Kilian, A., Zhang, X., Shaffer, H. B., & Unmack, P. J. (2018). Genome-wide SNP markers breathe new life into phylogeography and species delimitation for the problematic short-necked turtles (Chelidae: Emydura) of eastern Australia. *Molecular Ecology*, *27*, 5195–5213. Gruber, B., Unmack, P. J., Berry, O. F., & Georges, A. (2018). dartr: An r package to facilitate analysis of SNP data generated from reduced representation genome sequencing. *Molecular Ecology Resources*, *18*(3), 691–699. Kilian, A., Wenzl, P., Huttner, E., Carling, J., Xia, L., Blois, H., Caig, V., Heller-Uszynska, K., Jaccoud, D., Hopper, C., Aschenbrenner-Kilian, M., Evers, M., Peng, K., Cayla, C., Hok, P., & Uszynski, G. (2012). Diversity Arrays Technology: a generic genome profiling technology on open platforms. In F. Pompanon & A. Bonin (Eds.), *Data Production and Analysis in Population Genomics: Methods and Protocols* (pp. 67–89). Humana Press. Mijangos, J., Gruber, B., Berry, O., Pacioni, C., & Georges, A. (2022). dartR v2: an accessible genetic analysis platform for conservation, ecology, and agriculture. *Methods in Ecology and Evolution*, *3*, 2150–2158. Swofford, D. L. (2003). Phylogenetic Analysis Using Parsimony * (and other methods). Version 4. In *PAUP*. Phylogenetic Analysis Using Parsimony (*and Other Methods). Version 4.* Sinauer Associates.