DOI: 10.5061/dryad.r2280gbn5
title: Data from: Genetic evidence of killer whale predation on white sharks in Australia

description: Killer whales (Orcinus orca) have been documented to prey on white sharks
 (Carcharodon carcharias), in some cases causing localised shark
 displacement and triggering ecological cascades. Notably, a series of such
 predation events have been reported from South Africa over the last
 decade, with killer whales specifically targeting shark’s liver. However,
 observations of these interactions are rare and knowledge of their
 frequency across the world’s oceans remain limited. In October 2023, a 4.7
 m (total length) white shark carcass washed ashore in south-eastern
 Australia, coinciding with reports from citizen scientists of killer
 whales hunting a large, unidentified prey item in the area. Visual
 inspection of the carcass revealed that the liver, digestive, and
 reproductive organs were missing, and the presence of four distinctive
 bite wounds, one of which was characteristic of killer whale liver
 extraction as seen in South Africa. Genomic analyses performed on swabs
 taken from the bite wounds confirmed the presence of killer whale DNA in
 the major bite area, while the other bites were embedded with genetic
 material from the scavenging broadnose sevengill shark (Notorynchus
 cepedianus). These results provide confirmed evidence of killer whale
 predation on white sharks in Australia, and the likely selective
 consumption of the liver, suggesting predations of this nature are more
 globally prevalent than currently assumed.
description: We collected genetic material from bite wounds on a white shark
 carcass by swabbing internal and external wound surfaces with a flocked
 cotton swab and preserving each in ATL buffer (QIAGEN). We collected a
 total of 15 swabs four distinct bite wounds, with each swab taken from a
 different area of each wound site. Samples were subsequently transported
 to the laboratory on ice and stored at 4oC for 24 h prior to genetic
 analysis. Total genomic DNA was extracted from the swabs using a QIAGEN
 DNeasy Blood and Tissue Kit, following the manufacturer's protocol
 with minor modifications as specified by Clark et al. (2023). We performed
 four negative extraction controls in parallel (all extraction steps
 performed but without a swab sample) to control for potential cross-sample
 contamination. Polymerase chain reaction (PCR)
 targeting the mitochondrial 12S rRNA gene (106bp) was performed using a
 universal vertebrate PCR assay (Riaz et al., 2011; Table 1) following the
 laboratory workflow outlined by Clark et al. (2023). Briefly, PCR primer
 combinations were modified to include Illumina adapter tails at their 5′
 ends (‘TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG’ and ‘GTC TCG TGG GCT CGG
 AGA TGT GTA TAA GAG ACA G’ for forward and reverse primers, respectively)
 to enable the addition of Illumina dual-index barcodes. Additionally,
 blocking primers were used to suppress human and white shark DNA
 amplification.  We performed all PCR reactions in duplicate for each
 sample with PCR reaction matrices and thermal cycling conditions being
 consistent with those described by Clark et al. (2023). A total of eight
 negative template PCR controls (no DNA extract added) and four negative
 DNA controls (extract from negative DNA extractions) were included in each
 step of the metabarcoding process through to sequencing to control for
 laboratory contamination. Index PCR reaction matrices
 and thermal cycling conditions were again performed following Clark et al.
 (2023). Forward and reverse index primers provided dual indices in unique
 combinations, allowing demultiplexing of pooled products and Illumina
 sequencing adapters. PCR products were purified using 0.8× volume of
 AmpureBead XP (Beckman Coulter) and quantified using a Qubit dsDNA BR
 Assay Kit (Invitrogen). Indexed PCR products were subsequently normalised
 and pooled to create a single pooled library for sequencing. The resulting
 library was finally denatured and sequenced on the Illumina iSeq® platform
 using the iSeq® Version 2 kit (300 bp paired end), allowing for average
 read depth of 5 × 104 DNA sequence reads per sample.
description: # Data from: Genetic evidence of killer whale predation on white sharks in
 Australia
 [https://doi.org/10.5061/dryad.r2280gbn5](https://doi.org/10.5061/dryad.r2280gbn5) ## Description of the data and file structure ### Files and variables #### File: Shark_and_Killer_ASVs.xlsx **Description:** Mitochondrial DNA haplotype sequences isolated from the bite wounds on the white shark carcass. These sequences were BLASTed against vertebrate haplotype sequences on the NCBI sequence archives to determine the taxonomic identity. #### File: Metadata.csv **Description:** Information on sample IDs, corresponding bit wounds and swab samples, and corresponding sample codes for which fastq sequence data is provided. #### File: Sequence_data_Fastq.zip **Description:** All sequence data for each biological sample taken from each bite wound on the white shark carcass ## Code/software We performed bioinformatic analyses of the resulting DNA sequences from each bite wound following the analytical pipeline of Clark et al. (2023). In summary, this involved the alignment of filtered DNA sequences against a reference library consisting of 12S rRNA haplotype sequences representing more than 25,000 vertebrate species, including reference haplotype sequences for all marine mammal and elasmobranch species found on Genbank ([www.ncbi.nlm.nih.gov/genbank/](http://www.ncbi.nlm.nih.gov/genbank/)) and known to be present in south-eastern Australian waters. Bioinformatic analyses were performed with a custom analysis pipeline that incorporated the software  programs VSEARCH v2.9.0 (Rognes, Flouri, Nichols, Quince, & Mahé, 2016) and cutadapt (Martin, 2011). Following preliminary bioinformatic processing and quality filtering, sequencing reads were dereplicated and those with an abundance of less than 10 were excluded from further analyses. Sequences were clustered into OTUs using a pairwise identity of 100% (vsearch --id 1.0). Although using a threshold of 100% at this stage could be considered conservative, this approach was adopted because it allowed for greater transparency in the pipeline (taxonomic assignment for any individual sequence could be traced more easily compared to the scenario where sequences with &gt;100% identity were grouped into the same cluster). Furthermore, a conservative approach was deemed preferable to avoid misassignments or over-assignments in the downstream analysis given the relatively short marker lengths used in this study. All code used for data processing has been made available here in the Software Related works link.