CoChat
Sign Up
Cited by 9Genetic diversity and population structureBat Biology and Ecology StudiesWildlife Ecology and Conservation

Species-specific SNP arrays for non-invasive genetic monitoring of a vulnerable bat

Open access
Thavornkanlapachai, Rujiporn, Armstrong, Kyle N., Knuckey, Chris, Huntley, Bart, Hanrahan, Nicola, Ottewell, Kym·2024·Scientific Reports
DOI 10.1038/s41598-024-51461-5PMC PMC10803360
Open this paper in CoChat — free accountOpen PDF

Abstract

Genetic tagging from scats is one of the minimally invasive sampling (MIS) monitoring approaches commonly used to guide management decisions and evaluate conservation efforts. Microsatellite markers have traditionally been used but are prone to genotyping errors. Here, we present a novel method for individual identification in the Threatened ghost bat Macroderma gigas using custom-designed Single Nucleotide Polymorphism (SNP) arrays on the MassARRAY system. We identified 611 informative SNPs from DArTseq data from which three SNP panels (44–50 SNPs per panel) were designed. We applied SNP genotyping and molecular sexing to 209 M. gigas scats collected from seven caves in the Pilbara, Western Australia, employing a two-step genotyping protocol and identifying unique genotypes using a custom-made R package, ScatMatch. Following data cleaning, the average amplification rate was 0.90 ± 0.01 and SNP genotyping errors were low (allelic dropout 0.003 ± 0.000) allowing clustering of scats based on one or fewer allelic mismatches. We identified 19 unique bats (9 confirmed/likely males and 10 confirmed/likely females) from a maternity and multiple transitory roosts, with two male bats detected using roosts, 9 km and 47 m apart. The accuracy of our SNP panels enabled a high level of confidence in the identification of individual bats. Targeted SNP genotyping is a valuable tool for monitoring and tracking of non-model species through a minimally invasive sampling approach.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41598-024-51461-5

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Species-specific or custom-designed STR and SNP arrays to identify different breeds are becoming more common.

    “For non-human models, species-specific or custom-designed STR and SNP arrays to identify different breeds are becoming more common [62,63,64].”

    From Genetic Insights into the Economic Toll of Cell Line Misidentification: A Comprehensive Review (2026) · cites this paper as [63]

    The Introduction says SNP markers are being used more widely in wildlife studies, and the Results (SNP selection) describe custom SNP panels for identifying individual bats. The paper discusses microsatellite (STR) markers, but does not establish that custom STR arrays are becoming more common or that either type of array is used to identify different breeds. Page numbers are not available in our copy. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 57

  1. [2]Zemanova MA Towards more compassionate wildlife research through the 3Rs principles: Moving from invasive to non-invasive methods Wildl. Biol. 2020 2020 1 14 10.2981/wlb.00607 · DOI
  2. [3]Carroll EL Genetic and genomic monitoring with minimally invasive sampling methods Evol. Appl. 2018 11 1094 1119 10.1111/eva.12600 30026800 PMC6050181 · DOI
  3. [4]Carpenter FM Dziminski MA Breaking down scats: Degradation of DNA from greater bilby (Macrotis lagotis) faecal pellets Austr. Mammal. 2017 39 197 204 10.1071/AM16030 · DOI
  4. [5]Piggott MP Effect of sample age and season of collection on the reliability of microsatellite genotyping of faecal DNA Wildl. Res. 2004 31 485 493 10.1071/WR03096 · DOI
  5. [6]Lamb CT Genetic tagging in the Anthropocene: Scaling ecology from alleles to ecosystems Ecol. Appl. 2019 29 e01876 10.1002/eap.1876 30913353 · DOI
  6. [7]Mengüllüoğlu D Fickel J Hofer H Förster DW Non-invasive faecal sampling reveals spatial organization and improves measures of genetic diversity for the conservation assessment of territorial species: Caucasian lynx as a case species PLoS One 2019 14 e0216549 10.1371/journal.pone.0216549 31075125 PMC6510455 · DOI
  7. [8]Nussberger B Wandeler P Weber D Keller L Monitoring introgression in European wildcats in the Swiss Jura Conserv. Genet. 2014 15 1219 1230 10.1007/s10592-014-0613-0 · DOI
  8. [9]Norman AJ Spong G Single nucleotide polymorphism-based dispersal estimates using noninvasive sampling Ecol. Evol. 2015 5 3056 3065 10.1002/ece3.1588 26357536 PMC4559049 · DOI
  9. [10]Ford MJ Inferred paternity and male reproductive success in a killer whale (Orcinus orca) population J. Hered. 2011 102 537 553 10.1093/jhered/esr067 21757487 · DOI
  10. [11]Ruegg KC Mapping migration in a songbird using high-resolution genetic markers Mol. Ecol. 2014 23 5726 5739 10.1111/mec.12977 25346105 · DOI
  11. [12]Claramunt AMA Determination of the diet of the ghost bat (Macroderma gigas) in the Pilbara region of Western Australia from dried prey remains and DNA metabarcoding Aust. J. Zool. 2018 66 195 200 10.1071/ZO18040 · DOI
  12. [13]Panasci M Evaluation of fecal DNA preservation techniques and effects of sample age and diet on genotyping success J. Wildl. Manag. 2011 75 1616 1624 10.1002/jwmg.221 · DOI
  13. [15]Berry O Sarre SD Farrington L Aitken N Faecal DNA detection of invasive species: The case of feral foxes in Tasmania Wildl. Res. 2007 34 1 7 10.1071/WR06082 · DOI
  14. [16]Sittenthaler M Factors influencing genotyping success and genotyping error rate of Eurasian otter (Lutra lutra) faeces collected in temperate Central Europe Eur. J. Wildl. Res. 2020 67 2 10.1007/s10344-020-01444-4 · DOI
  15. [17]Nsubuga AM Factors affecting the amount of genomic DNA extracted from ape faeces and the identification of an improved sample storage method Mol. Ecol. 2004 13 2089 2094 10.1111/j.1365-294X.2004.02207.x 15189228 · DOI
  16. [18]von Thaden A Assessing SNP genotyping of noninvasively collected wildlife samples using microfluidic arrays Sci. Rep. 2017 7 10768 10.1038/s41598-017-10647-w 28883428 PMC5589735 · DOI
  17. [20]Taberlet P Reliable genotyping of samples with very low DNA quantities using PCR Nucleic Acids Res. 1996 24 3189 3194 10.1093/nar/24.16.3189 8774899 PMC146079 · DOI · Paper page
  18. [21]Glaubitz JC Rhodes OE Jr Dewoody JA Prospects for inferring pairwise relationships with single nucleotide polymorphisms Mol. Ecol. 2003 12 1039 1047 10.1046/j.1365-294X.2003.01790.x 12753222 · DOI · Paper page
  19. [22]Ekblom R Sample identification and pedigree reconstruction in Wolverine (Gulo gulo) using SNP genotyping of non-invasive samples Conserv. Genet. Resour. 2021 13 261 274 10.1007/s12686-021-01208-5 · DOI
  20. [25]Hoyle SD Pople AR Toop GJ Mark–recapture may reveal more about ecology than about population trends: Demography of a threatened ghost bat (Macroderma gigas) population Austral Ecol. 2001 26 80 92 10.1111/j.1442-9993.2001.01092.pp.x · DOI
  21. [27]Churchill SK Helman PM Distribution of the Ghost Bat, Macroderma gigas, (Chiroptera: Megadermatidae) in central and South Australia Aust. Mammal. 1990 13 149 156 10.1071/AM90015 · DOI
  22. [29]Cramer VA Research priorities for the ghost bat (Macroderma gigas) in the Pilbara region of Western Australia Aust. Mammal. 2022 45 1 12 10.1071/AM21042 · DOI
  23. [30]Worthington Wilmer J Moritz C Hall L Toop J Pettigrew JD Extreme population structuring in the threatened ghost bat, Macroderma gigas: Evidence from mitochondrial DNA Proc. R. Soc. Lond. Ser. B Biol. Sci. 1994 257 193 198 10.1098/rspb.1994.0115 7972165 · DOI
  24. [31]Armstrong KN Anstee SD The ghost bat in the Pilbara: 100 years on Aust. Mammal. 2000 22 93 101 10.1071/AM00093 · DOI
  25. [33]Hanrahan N Turbill C Armstrong KN Dalziell AH Welbergen JA Ghost bats exhibit informative daily and seasonal temporal patterns in the production of social vocalisations Aust. J. Zool. 2019 67 305 315 10.1071/ZO20055 · DOI
  26. [34]Worthington Wilmer J Hall L Barratt E Moritz C Genetic structure and male-mediated gene flow in the Ghost Bat (Macroderma gigas) Evolution 1999 53 1582 1591 10.2307/2640903 28565551 · DOI
  27. [36]Kunz T Fenton MB Bat Ecology 2005 University of Chicago Press
  28. [37]Augusteyn J Hughes J Armstrong G Real K Pacioni C Tracking and tracing central Queensland’s Macroderma—Determining the size of the Mount Etna ghost bat population and potential threats Aust. Mammal. 2018 40 243 253 10.1071/AM16010 · DOI
  29. [38]Ottewell K Development and optimisation of molecular assays for microsatellite genotyping and molecular sexing of non-invasive samples of the ghost bat, Macroderma gigas Mol. Biol. Rep. 2020 47 5635 5641 10.1007/s11033-020-05544-x 32577991 · DOI
  30. [41]Zheng X A High-performance computing toolset for relatedness and principal component analysis of SNP data Bioinformatics 2012 28 3326 3328 10.1093/bioinformatics/bts606 23060615 PMC3519454 · DOI
  31. [43]Peakall R Smouse PE GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research—An update Bioinformatics 2012 28 2537 2539 10.1093/bioinformatics/bts460 22820204 PMC3463245 · DOI
  32. [44]Waits LP Luikart G Taberlet P Estimating the probability of identity among genotypes in natural populations: Cautions and guidelines Mol. Ecol. 2001 10 249 256 10.1046/j.1365-294X.2001.01185.x 11251803 · DOI · Paper page
  33. [46]Do C NeEstimator v2: Re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data Mol. Ecol. Resour. 2014 14 209 214 10.1111/1755-0998.12157 23992227 · DOI
  34. [47]Waples RS A bias correction for estimates of effective population size based on linkage disequilibrium at unlinked gene loci Conserv. Genet. 2016 7 167 184 10.1007/s10592-005-9100-y · DOI
  35. [48]Jones A Ovenden J Wang J Improved confidence intervals for the linkage disequilibrium method for estimating effective population size Heredity 2016 7 167 184 PMC5026751 27005004
  36. [49]Lynch M Ritland K Estimation of pairwise relatedness with molecular markers Genetics 1999 152 1753 1766 10.1093/genetics/152.4.1753 10430599 PMC1460714 · DOI
  37. [50]Attard CRM Beheregaray LB Möller LM Genotyping-by-sequencing for estimating relatedness in nonmodel organisms: Avoiding the trap of precise bias Mol. Ecol. Resour. 2018 18 381 390 10.1111/1755-0998.12739 29160928 · DOI
  38. [51]Ritland K Estimators for pairwise relatedness and individual inbreeding coefficients Genet. Res. 1996 67 175 185 10.1017/S0016672300033620 · DOI
  39. [52]von Thaden A Applying genomic data in wildlife monitoring: Development guidelines for genotyping degraded samples with reduced single nucleotide polymorphism panels Mol. Ecol. Resour. 2020 20 662 680 10.1111/1755-0998.13136 PMC7199164 31925943 · DOI
  40. [53]Lukacs PM Burnham KP Review of capture–recapture methods applicable to noninvasive genetic sampling Mol. Ecol. 2005 14 3909 3919 10.1111/j.1365-294X.2005.02717.x 16262847 · DOI
  41. [54]Goossens B Habitat fragmentation and genetic diversity in natural populations of the Bornean elephant: Implications for conservation Biol. Conserv. 2016 196 80 92 10.1016/j.biocon.2016.02.008 · DOI
  42. [55]Fitak RR Naidu A Thompson RW Culver M A new panel of SNP markers for the individual identification of North American Pumas J. Fish Wildl. Manag. 2015 7 13 27 10.3996/112014-JFWM-080 · DOI
  43. [56]Lampa S Henle K Klenke R Hoehn M Gruber B How to overcome genotyping errors in non-invasive genetic mark-recapture population size estimation—A review of available methods illustrated by a case study J. Wildl. Manag. 2013 77 1490 1511 10.1002/jwmg.604 · DOI
  44. [57]Lampa S Mihoub J-B Gruber B Klenke R Henle K Non-invasive genetic Mark-Recapture as a means to study population sizes and marking behaviour of the elusive Eurasian otter (Lutra lutra) PLoS One 2015 10 e0125684 10.1371/journal.pone.0125684 25973884 PMC4431875 · DOI
  45. [58]Pompanon F Bonin A Bellemain E Taberlet P Genotyping errors: Causes, consequences and solutions Nat. Rev. Genet. 2005 6 847 859 10.1038/nrg1707 16304600 · DOI
  46. [59]Marandel F Estimating effective population size using RADseq: Effects of SNP selection and sample size Ecol. Evol. 2020 10 1929 1937 10.1002/ece3.6016 32128126 PMC7042749 · DOI
  47. [61]Tidemann CR Priddel DM Nelson JE Pettigrew JD Foraging behaviour of the Australian Ghost Bat, Macroderma gigas (Microchiroptera: Megadermatidae) Aust. J. Zool. 1985 33 705 713 10.1071/ZO9850705 · DOI
  48. [65]Oyler-McCance SJ Genetic mark–recapture improves estimates of maternity colony size for Indiana bats J. Fish Wildl. Manag. 2018 9 25 35 10.3996/122016-JFWM-093 · DOI
  49. [66]Puechmaille SJ Petit EJ Empirical evaluation of non-invasive capture–mark–recapture estimation of population size based on a single sampling session J. Appl. Ecol. 2007 44 843 852 10.1111/j.1365-2664.2007.01321.x · DOI
  50. [67]Lachance J Tishkoff S SNP ascertainment bias in population genetic analyses: Why it is important, and how to correct it Bioessays 2013 35 780 786 10.1002/bies.201300014 23836388 PMC3849385 · DOI
  51. [68]Malomane DK Efficiency of different strategies to mitigate ascertainment bias when using SNP panels in diversity studies BMC Genomics 2018 19 22 10.1186/s12864-017-4416-9 29304727 PMC5756397 · DOI
  52. [70]Jansson L Individual shedder status and the origin of touch DNA Forensic Sci. Int. Genet. 2022 56 102626 10.1016/j.fsigen.2021.102626 34781198 · DOI
  53. [71]Lukacs PM Burnham KP Estimating population size from DNA-based closed Capture-Recapture data incorporating genotyping error J. Wildl. Manag. 2005 69 396 403 10.2193/0022-541X(2005)069<0396:EPSFDC>2.0.CO;2 · DOI
  54. [72]White GC Burnham KP Program MARK: Survival estimation from populations of marked animals Bird Study 1999 46 120 139 10.1080/00063659909477239 · DOI
  55. [73]De Paoli-Iseppi R Measuring animal age with DNA methylation: From humans to wild animals Front. Genet. 2017 8 1 8 10.3389/fgene.2017.00106 28878806 PMC5572392 · DOI
  56. [74]Polanowski AM Robbins J Chandler D Jarman SN Epigenetic estimation of age in humpback whales Mol. Ecol. Resour. 2014 14 976 987 10.1111/1755-0998.12247 24606053 PMC4314680 · DOI
  57. [75]Wright PGR Application of a novel molecular method to age free-living wild Bechstein’s bats Mol. Ecol. Resour. 2018 18 1374 1380 10.1111/1755-0998.12925 29981199 · DOI

Cited by

Sorted by citations

Authors
Thavornkanlapachai, R., Armstrong, K. N., Knuckey, C., Huntley, B., Hanrahan, N., & Ottewell, K.
Affiliations
  • Department of Biodiversity, Conservation and Attractions (AU)
  • South Australian Museum (AU)
  • Charles Darwin University (AU)
Corresponding author
Thavornkanlapachai, Rujiporn
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2024-01-22
Volume
14
Issue
1
Pages
1847-1847
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-024-51461-5
PMC
PMC10803360
OpenAlex
W4391108557
Cited by
9
References
2
Citations by year
2026: 4 · 2025: 5
FWCI
2.39
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Specialised Zoological
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
  • Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Bat Biology and Ecology Studies
  • Physical Sciences › Environmental Science › Ecology › Wildlife Ecology and Conservation
Keywords
Macroderma gigas, ghost bat, single nucleotide polymorphism array, SNP genotyping, individual identification, scat sampling, molecular sexing, DArTseq, allele dropout, maternity roosts, cave-dwelling bats, conservation genetics, vulnerable species
MeSH terms
Alleles, Animals, Chiroptera, Culture, Erythrocyte Membrane, Female, Humans, Male, Pregnancy, Cluster Analysis

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review