DOI: 10.5061/dryad.ht76hdrph
title: Reversing the decline of threatened koala (Phascolarctos cinereus) populations in New South Wales: Using genomics to enhance conservation outcomes

description: Genetic management is a critical component of threatened species
 conservation. Understanding spatial patterns of genetic diversity is
 essential for evaluating the resilience of fragmented populations to
 accelerating anthropogenic threats. Nowhere is this more relevant than on
 the Australian continent, which is experiencing an ongoing loss of
 biodiversity that exceeds any other developed nation. Using a proprietary
 genome complexity reduction-based method (DArTSeq), we generated a data
 set of 3,239 high quality Single Nucleotide Polymorphisms (SNPs) to
 investigate spatial patterns and indices of genetic diversity in the koala
 (Phascolarctos cinereus), a highly specialised folivorous marsupial that
 is experiencing rapid and widespread population declines across much of
 its former range. Our findings demonstrate that current management
 divisions across the state of New South Wales (NSW) do not fully represent
 the distribution of genetic diversity among extant koala populations, and
 that care must be taken to ensure that translocation paradigms based on
 these frameworks do not inadvertently restrict gene flow between
 populations and regions that were historically interconnected. We also
 recommend that koala populations should be prioritised for conservation
 action based on the scale and severity of the threatening processes that
 they are currently faced with, rather than placing too much emphasis on
 their perceived value (e.g., as reservoirs of potentially adaptive
 alleles), as our data indicate that existing genetic variation in koalas
 is primarily partitioned amongst individual animals. As such, the
 extirpation of koalas from any part of their range represents a
 potentially critical reduction of genetic diversity for this iconic
 Australian species.
description: Genomic DNA was extracted from 314 koala samples using either the
 Bioline Isolate II Genomic DNA Kit (Bioline, Eveleigh, Australia)
 following the manufacturer’s protocols, or a standard high-salt
 precipitation procedure (Sunnucks and Hales, 1996). Genotyping was
 performed using the Diversity Arrays Technology platform (DArTseq™). DNA
 was processed as per Kilian et al. (2012), using paired adaptors which
 corresponded to two different restriction enzyme overhangs: PstI and SphI.
 The PstI-compatible adapter included an Illumina flow cell attachment
 sequence, a sequencing primer binding site, and a varying length barcode
 region. The reverse adapter contained a SphI-compatible overhang sequence
 and a flow cell attachment region. A digestion–ligation reaction was
 performed at 37 °C for 2 h with ~100–200 ng of gDNA per sample. The DNA
 fragments that were successfully cut by both PstI and SphI were then
 amplified by 30 cycles of polymerase chain reaction (PCR), and the PCR
 products were sequenced as 77‐bp or 138-bp single‐end reads on the HiSeq
 2500 and Novaseq 6000 platforms, respectively (Illumina, San Diego, USA).
 The resulting short-read sequence data were processed using a variety of
 software packages and scripts which have been included with the Dryad
 package.
description: 1\) DArTSeq Fastq files * Demultiplexed DArTSeq fastq sequencing files for
 314 koala specimens and 60 technical replicates. 2\) Sequence processing
 & SNP calling * This folder contains the scripts and files required to
 process the fastq sequencing files and identify SNPs. Stacks v2.64 was
 used to process the demultiplexed and adapter trimmed short‐read sequence
 data supplied by DArT. The reads were truncated to 69bp in length and
 low-quality data (based on the PHRED scores provided in the FASTQ files)
 were identified and discarded using the process_radtags program.
 Burrows-Wheeler aligner (BWA) v0.7.15 was then used to align the read data
 from the previous step to the koala reference genome
 (GCA_002099425.1_phaCin_unsw_v4.1). The alignments were subsequently
 converted to BAM format using SAMtools v1.6. Finally, the
 reference-aligned data were used to assemble the sequences into loci and
 identify SNPs using the ref_map.pl pipeline in Stacks. A single SNP was
 extracted from each locus for downstream processing and analysis using the
 populations program, also implemented in Stacks. 3\) R software scripts
 for analysing the SNP data * The R software scripts for identifiyng
 candidate outlier SNPs that might represent loci under selection
 (PCAdapt), assessing population structure (DAPC), detecting departure from
 Hardy–Weinberg equilibrium (HWE), identifying "genetically diagnostic
 units" in koalas by fixed difference analysis, calculating pairwise
 FST indices, testing for hierarchical partitioning of genetic variation
 (AMOVA), examining the relationship between geographical and genetic
 distances (Mantel test), calculating individual-based measures of genetic
 variation (homozygosity by locus), and investigating the relationship
 between genetic diversity in koalas and several key aspects of their
 environment using a multilevel mixed-effects linear model have all been
 collated here.