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Fig. 5 in A retrospective epidemiological study of sarcoptic mange in koalas (Phascolarctos cinereus) using wildlife carer admission records

Fig. 5. Frequency of sarcoptic mange infestation by body region recorded from 12 koalas that were reported with mange between September 2019 to March 2020. A) Total records. Sex specific features (pouch, testicles) were included as the stomach region. B) Male records (n = 10), C) Female records (n = 2).

Fig. 4 in A retrospective epidemiological study of sarcoptic mange in koalas (Phascolarctos cinereus) using wildlife carer admission records

Fig. 4. Koala sarcoptic mange admissions: a) Number of cases of koalas per month from 75 koala admission records affected by sarcoptic mange from January 2018 and December 2021. b) Number of koala sarcoptic mange admissions per season (n = 75). c) Rate of koala sarcoptic mange admissions per month for each koala breeding season (n = 82).

Fig. 3 in A retrospective epidemiological study of sarcoptic mange in koalas (Phascolarctos cinereus) using wildlife carer admission records

Fig. 3. Conscious state of koalas when located by wildlife carers from 12 admission records of sarcoptic mange affected individuals from Dutch Thunder Wildlife Shelter between September 2019 to March 2020. Percentages and sample sizes are provided for each category.

Fig. 2 in A retrospective epidemiological study of sarcoptic mange in koalas (Phascolarctos cinereus) using wildlife carer admission records

Fig. 2. Outcome of 82 records of koala admissions with sarcoptic mange into Dutch Thunder Wildlife Shelter between October 2017 to May 2022.

opencc-zeroJul 2024View details →

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Reversing the decline of threatened koala (Phascolarctos cinereus) populations in New South Wales: Using genomics to enhance conservation outcomes

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.

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Fig. 1 in A retrospective epidemiological study of sarcoptic mange in koalas (Phascolarctos cinereus) using wildlife carer admission records

Fig. 1. Map of locations of koalas (Phascolarctos cinereus) admitted with sarcoptic mange.

publicJul 2024View details →

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Reversing the decline of threatened koala (Phascolarctos cinereus) populations in New South Wales: Using genomics to enhance conservation outcomes

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opencc-zeroDec 2012View details →

Data from: Reliable genotyping of the koala (Phascolarctos cinereus) using DNA isolated from a single faecal pellet

The koala, an Australian icon, has been added to the threatened species list. Rationale for the listing includes proposed declines in population size, threats to populations (e.g. disease) and loss and fragmentation of habitat. There is now an urgent need to obtain accurate data to assess the status of koala populations in Australia, to ensure the long-term viability of this species. Advances in genetic techniques have enabled DNA analysis to study and inform the management of wild populations; however, sampling of individual koalas is difficult in tall, often remote, eucalypt forest. The collection of faecal pellets (scats) from the forest floor presents an opportunistic sampling strategy, where DNA can be collected without capturing or even sighting an individual. Obtaining DNA via noninvasive sampling can be used to rapidly sample a large proportion of a population; however, DNA from noninvasively collected samples is often degraded. Factors influencing DNA quality and quantity include environmental exposure, diet and methods of sample collection, storage and DNA isolation. Reduced DNA quality and quantity can introduce genotyping errors and provide inaccurate DNA profiles, reducing confidence in the ability of such data to inform management/conservation strategies. Here, we present a protocol that produces a reliable individual koala genotype from a single faecal pellet and highlight the importance of optimizing DNA isolation and analysis for the species of interest. This method could readily be adapted for genetic studies of mammals other than koalas, particularly those whose diet contains high proportions of volatile materials that are likely to induce DNA damage.

opencc-zeroDec 2014View details →

Data from: Immunomics of the koala (Phascolarctos cinereus )

The study of the koala transcriptome has the potential to advance our understanding of its immunome—immunological reaction of a given host to foreign antigens—and to help combat infectious diseases (e.g., chlamydiosis) that impede ongoing conservation efforts. We used Illumina sequencing of cDNA to characterize genes expressed in two different koala tissues of immunological importance, blood and spleen. We generated nearly 600 million raw sequence reads, and about 285 million of these were subsequently assembled and condensed into ~70,000 subcomponents that represent putative transcripts. We annotated ~16 % of these subcomponents and identified those related to infection and the immune response, including Toll-like receptors (TLRs), RIG-I-like receptors (RLRs), major histocompatibility complex (MHC) genes, and koala retrovirus (KoRV). Using phylogenetic analyses, we identified 29 koala genes in these target categories and report their concordance with currently accepted gene groups. By mapping multiple sequencing reads to transcripts, we identified 56 putative SNPs in genes of interest. The distribution of these SNPs indicates that MHC genes (34 SNPs) are more diverse than KoRV (12 SNPs), TLRs (8 SNPs), or RLRs (2 SNPs). Our sequence data also indicate that KoRV sequences are highly expressed in the transcriptome. Our efforts have produced full-length sequences for potentially important immune genes in koala, which should serve as targets for future investigations that aim to conserve koala populations.

opencc-zeroDec 2017View details →

Data from: Genomic comparisons reveal biogeographic and anthropogenic impacts in the koala (Phascolarctos cinereus); a dietary-specialist species distributed across heterogeneous environments

The Australian koala is an iconic marsupial with specific dietary requirements distributed across heterogeneous environments, over a large geographic range. The distribution and genetic structure of koala populations has been heavily influenced by human actions, specifically habitat modification, hunting and translocation of koalas. There is currently limited information on population diversity and gene-flow at a species-wide scale, or with consideration to the potential impacts of local adaptation. Using species-wide sampling across heterogeneous environments, and high-density genome-wide markers (SNPs and PAVs), we show that most koala populations display levels of diversity comparable to other outbred species, except for those populations impacted by population reductions. Genetic clustering analysis and phylogenetic reconstruction reveals a lack of support for taxonomic classification of three koala sub-species, with only a single evolutionary significant unit supported. Furthermore, ~70% of genetic variance is accounted for at the individual level. The Sydney Basin region is highlighted as a unique reservoir of genetic diversity, having higher diversity levels (ie. Blue Mountains region; AvHecorr=0.20, PL%=68.6). Broad-scale population differentiation is primarily driven by an Isolation by Distance genetic structure model (49% of genetic variance), with clinal local adaptation corresponding to habitat bioregions. Signatures of selection were detected between bioregions, with no single region returning evidence of strong selection. The results of this study show that although the koala is widely considered to be a dietary-specialist species, this apparent specialisation has not limited the koala's ability to maintain gene-flow and adapt across divergent environments as long as the required food source is available.

opencc-zeroDec 2013View details →

Data from: MHC class II diversity of koala (Phascolarctos cinereus) populations across their range

Major histocompatibility complex class II (MHCII) genes code for proteins that bind and present antigenic peptides and trigger the adaptive immune response. We present a broad geographical study of MHCII DA β1 (DAB) and DB β1 (DBB) variants of the koala (Phascolarctos cinereus; n=191) from 12 populations across eastern Australia, with a total of 13 DAB and 7 DBB variants found. We identified greater MHCII variation and, possibly, additional gene copies in koala populations in the north (Queensland and New South Wales) relative to the south (Victoria), confirmed by STRUCTURE analyses and genetic differentiation using analysis of molecular variance. The higher MHCII diversity in the north relative to south could potentially be attributed to (i) significant founder effect in Victorian populations linked to historical translocation of bottlenecked koala populations and (ii) increased pathogen-driven balancing selection and/or local genetic drift in the north. Low MHCII genetic diversity in koalas from the south could reduce their potential response to disease, although the three DAB variants found in the south had substantial sequence divergence between variants. This study assessing MHCII diversity in the koala with historical translocations in some populations contributes to understanding the effects of population translocations on functional genetic diversity.

opencc-zeroDec 2017View details →

Data from: Demographic, environmental and genetic determinants of mating success in captive koalas (Phascolarctos cinereus)

Many factors have been shown to affect mating behavior. For instance, genes of the major histocompatibility complex (MHC) are known to influence mate choice in a wide variety of vertebrate species. The genetic management of captive populations can be confounded if intrinsic mate choice reduces or eliminates reproductive success between carefully chosen breeding pairs. For example, the San Diego Zoo koala colony only has a 45% copulation rate for matched individuals. Herein, we investigated determinants of koala mating success using breeding records (1984-2010) and genotypes for 52 individuals at four MHC markers. We quantified MHC diversity according to functional amino acids, heterozygosity, and the probability of producing a heterozygous offspring. We then used categorical analysis and logistic regression to investigate both copulation and parturition success. In addition, we also examined age, day length, and average pairwise kinship. Our post-hoc power analysis indicates that at a power level of 1 – β = 0.8, we should have been able to detect strong MHC preferences. However, we did not find a significant MHC effect on either copulation or parturition success with one exception: pairs with lower or no production of a joey had significantly lower MHC functional amino acid diversity in the categorical analysis. In contrast, day length and dam age (or age difference of the pair) consistently had an effect on mating success. These findings may be leveraged to improve the success of attempted pairs, conserve resources, and facilitate genetic management.

Figure 8 in Hanging on and digging deep: comparative forelimb myology of the koala (Phascolarctos cinereus) and common wombat (Vombatus ursinus)

Figure 8. Architectural parameters of muscle groups crossing the shoulder, elbow, and wrist in the koala (K) and the common wombat (W). The less y axis relates to stacked bars and shows (A) summed PCSA and (B) mean fascicle length (normalized by body mass). The right y axis relates to circle (koala) and square (wombat) points, and shows the ratio between these PCSA and FL values for each antagonistic muscle group, as a measure of relative emphasis placed by these species on opposing actions at each of the forelimb joints. Muscles assigned to each functional group are detailed in Table 5.

Figure 4 in Hanging on and digging deep: comparative forelimb myology of the koala (Phascolarctos cinereus) and common wombat (Vombatus ursinus)

Figure 4. Muscle aưachment sites on the right humerus of the koala (A) and common wombat (B) in lateral, cranial, medial, and caudal views. For abbreviations see Table 2. Articulated versions of these muscle maps are available in the Supporting Information, Model S2.

Figure 7 in Hanging on and digging deep: comparative forelimb myology of the koala (Phascolarctos cinereus) and common wombat (Vombatus ursinus)

Figure 7. Functional morphospace showing PCSA and fascicle length values for muscles of the forelimb in the (A) koala and the (B) common wombat. Values have been normalized by individual body mass. For abbreviations see Table 2.

Figure 1 in Hanging on and digging deep: comparative forelimb myology of the koala (Phascolarctos cinereus) and common wombat (Vombatus ursinus)

Figure 1. Muscle topology of the right forelimb of the (A) koala and the (B) common wombat in lateral view at sequential depths of dissection from superficial (top) to deep (boưom). For abbreviations see Table 2. An interactive version of this figure is available in the Supporting Information, Model S1.

Figure 3 in Hanging on and digging deep: comparative forelimb myology of the koala (Phascolarctos cinereus) and common wombat (Vombatus ursinus)

Figure 3. Muscle aưachment sites on the right scapula of the koala (A) and common wombat (B) in lateral, medial, distal, and inferior views. For abbreviations see Table 2. Articulated versions of these muscle maps are available in the Supporting Information, Model S2.

Figure 2 in Hanging on and digging deep: comparative forelimb myology of the koala (Phascolarctos cinereus) and common wombat (Vombatus ursinus)

Figure 2. Muscle topology of the right forelimb of the (A) koala and the (B) common wombat in medial view at sequential depths of dissection from superficial (top) to deep (boưom). For abbreviations see Table 2. An interactive version of this figure is available in the Supporting Information, Model S1.

Figure 6 in Hanging on and digging deep: comparative forelimb myology of the koala (Phascolarctos cinereus) and common wombat (Vombatus ursinus)

Figure 6. Muscle aưachment sites on the right manus of the koala (A) and common wombat (B) in ulnar, dorsal, radial, and palmar views. For abbreviations see Table 2. Articulated versions of these muscle maps are available in the Supporting Information, Model S2.

Figure 5 in Hanging on and digging deep: comparative forelimb myology of the koala (Phascolarctos cinereus) and common wombat (Vombatus ursinus)

Figure 5. Muscle aưachment sites on the right radius and ulna of the koala (A) and the common wombat (B) in lateral, cranial, medial, and caudal views. For abbreviations see Table 2. Articulated versions of these muscle maps are available in the Supporting Information, Model S2.