Matches in SemOpenAlex for { <https://semopenalex.org/work/W4284697966> ?p ?o ?g. }
- W4284697966 endingPage "1603" @default.
- W4284697966 startingPage "1584" @default.
- W4284697966 abstract "Abstract Monitoring fish is necessary for understanding population dynamics, tracking distribution patterns and evaluating conservation efforts. Molecular techniques targeting environmental DNA (eDNA) are now considered effective methods for detecting specific species or characterising fish communities. The analysis of DNA from lake‐surface sediments (sedDNA) can provide a time‐integrated sampling approach which reduces the variability sometimes observed in water samples. However, studies of sedDNA have had varying success in detecting fish. The present study aimed to determine the most effective extraction method for recovering fish DNA from lake‐surface sediments. A literature review was undertaken to identify DNA extraction methods used previously on aquatic sediments targeting aquatic and terrestrial animals. Five methods with various modifications were tested to establish their ability to desorb extracellular DNA. Based on these results, two methods were selected and optimised, and the recovery of fish sedDNA characterised using droplet digital PCR assays targeting eel and perch ( Anguilla australis , Anguilla dieffenbachii , Perca fluviatilis ). A range of sediment masses (0.25–20 g) were assessed to establish the optimal amount required to accurately assess fish sedDNA. The DNA extraction methods found to be most effective at recovering extracellular DNA spiked into small sediment masses (0.25 g) were the DNeasy PowerSoil DNA Isolation Kit (QIAGEN), and the ABPS protocol which involved an initial alkaline buffer extraction followed by the PowerSoil extraction kit. For larger sediment masses (>0.25 g) the ABPS protocol or the DNeasy PowerMax Soil Kit (QIAGEN) with an additional ethanol DNA concentration step (PMET protocol) yielded the highest concentrations of target genes across a range of lake sediments. Larger sediment masses (≤20 g was tested) increased the likelihood of detection of fish in sedDNA. Optimisation of the ABPS protocol was required (65°C incubation temperature, pooling of multiple PowerSoil extractions) to overcome technical challenges related to co‐precipitation of organic content in lake‐surface sediments. This optimised ABPS protocol was called the “Lakes ABPS protocol”. We recommend the use of the Lakes ABPS protocol as it is cheaper than the PMET protocol. Additionally, after the first extraction step, the process can be automated on a DNA extraction robot, allowing for higher sample throughput. A mass of 10 g is suggested, although higher detection is achieved with more sediment, a suite of challenges, such as co‐precipitation of organic content, are encountered when the amount is increased. This study highlights the complexity of the extraction and detection of fish sedDNA from lake sediment, especially when it has a high organic content. We have optimised a DNA extraction method to overcome some of these complexities that can be applied to a wide range of lake sediments." @default.
- W4284697966 created "2022-07-08" @default.
- W4284697966 creator A5011466414 @default.
- W4284697966 creator A5018524429 @default.
- W4284697966 creator A5019713432 @default.
- W4284697966 creator A5024676279 @default.
- W4284697966 date "2022-07-05" @default.
- W4284697966 modified "2023-10-09" @default.
- W4284697966 title "Optimised protocol for the extraction of fish <scp>DNA</scp> from freshwater sediments" @default.
- W4284697966 cites W1018973490 @default.
- W4284697966 cites W1545479461 @default.
- W4284697966 cites W1820401862 @default.
- W4284697966 cites W1969254808 @default.
- W4284697966 cites W1969511463 @default.
- W4284697966 cites W1986729715 @default.
- W4284697966 cites W1987416145 @default.
- W4284697966 cites W1998161466 @default.
- W4284697966 cites W2006242401 @default.
- W4284697966 cites W2012313205 @default.
- W4284697966 cites W2017354194 @default.
- W4284697966 cites W2025322446 @default.
- W4284697966 cites W2026764344 @default.
- W4284697966 cites W2036390749 @default.
- W4284697966 cites W2045328330 @default.
- W4284697966 cites W2047462181 @default.
- W4284697966 cites W2056531209 @default.
- W4284697966 cites W2057790241 @default.
- W4284697966 cites W2060649143 @default.
- W4284697966 cites W2063726689 @default.
- W4284697966 cites W2084787000 @default.
- W4284697966 cites W2087462595 @default.
- W4284697966 cites W2112907615 @default.
- W4284697966 cites W2120991087 @default.
- W4284697966 cites W2123506747 @default.
- W4284697966 cites W2145539051 @default.
- W4284697966 cites W2171100005 @default.
- W4284697966 cites W2189909264 @default.
- W4284697966 cites W2206920360 @default.
- W4284697966 cites W2301825788 @default.
- W4284697966 cites W2337259322 @default.
- W4284697966 cites W2337792354 @default.
- W4284697966 cites W2341066319 @default.
- W4284697966 cites W2559866823 @default.
- W4284697966 cites W2588813229 @default.
- W4284697966 cites W2590338609 @default.
- W4284697966 cites W2622101866 @default.
- W4284697966 cites W2626376206 @default.
- W4284697966 cites W2733591563 @default.
- W4284697966 cites W2782609842 @default.
- W4284697966 cites W2794495228 @default.
- W4284697966 cites W2800289038 @default.
- W4284697966 cites W2911813797 @default.
- W4284697966 cites W2913078818 @default.
- W4284697966 cites W2917409942 @default.
- W4284697966 cites W2947929494 @default.
- W4284697966 cites W2951122641 @default.
- W4284697966 cites W2951879240 @default.
- W4284697966 cites W2951968263 @default.
- W4284697966 cites W2952837685 @default.
- W4284697966 cites W2955680102 @default.
- W4284697966 cites W2981061272 @default.
- W4284697966 cites W3008679654 @default.
- W4284697966 cites W3015287852 @default.
- W4284697966 cites W3028008639 @default.
- W4284697966 cites W3039671998 @default.
- W4284697966 cites W3044332703 @default.
- W4284697966 cites W3082796241 @default.
- W4284697966 cites W3087942109 @default.
- W4284697966 cites W3133246116 @default.
- W4284697966 cites W3153963581 @default.
- W4284697966 cites W3159262590 @default.
- W4284697966 cites W3166875446 @default.
- W4284697966 cites W3182762480 @default.
- W4284697966 cites W3203942894 @default.
- W4284697966 cites W4254687493 @default.
- W4284697966 doi "https://doi.org/10.1111/fwb.13962" @default.
- W4284697966 hasPublicationYear "2022" @default.
- W4284697966 type Work @default.
- W4284697966 citedByCount "6" @default.
- W4284697966 countsByYear W42846979662023 @default.
- W4284697966 crossrefType "journal-article" @default.
- W4284697966 hasAuthorship W4284697966A5011466414 @default.
- W4284697966 hasAuthorship W4284697966A5018524429 @default.
- W4284697966 hasAuthorship W4284697966A5019713432 @default.
- W4284697966 hasAuthorship W4284697966A5024676279 @default.
- W4284697966 hasBestOaLocation W42846979661 @default.
- W4284697966 hasConcept C104317684 @default.
- W4284697966 hasConcept C107872376 @default.
- W4284697966 hasConcept C130217890 @default.
- W4284697966 hasConcept C144024400 @default.
- W4284697966 hasConcept C149923435 @default.
- W4284697966 hasConcept C151730666 @default.
- W4284697966 hasConcept C175327387 @default.
- W4284697966 hasConcept C185592680 @default.
- W4284697966 hasConcept C18903297 @default.
- W4284697966 hasConcept C2776654248 @default.
- W4284697966 hasConcept C2777798493 @default.
- W4284697966 hasConcept C2779969263 @default.