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      Species in the faeces: DNA metabarcoding as a method to determine the diet of the endangered yellow-eyed penguin

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          Abstract

          Abstract Context. Diet variability is a significant driver of seabird decline; however, data on seabird diet composition and trends have been affected by changes in precision and resolution owing to the evolution of different sampling methods over time. We investigated the effectiveness of applying a passive molecular diet method using faeces obtained from the endangered yellow-eyed penguin. Aims. To assess the feasibility of applying DNA metabarcoding methods to yellow-eyed penguin faeces to evaluate diet, and to compare the reliability of diet results derived from adults and chicks, and from latrine versus fresh faecal samples. Methods. We collected 313 faecal samples from yellow-eyed penguins resident on the Otago coast of New Zealand from October 2016 to August 2017. We used polymerase chain reaction (PCR) with mitochondrial 16S cephalopod and chordate primers to amplify prey DNA present in the faecal samples, and tested the completeness of our assembled reference databases based on previous diet research. Amplified prey DNA sequences were then assigned to taxa from our reference databases by using QIIME2. Key results. Mitochondrial 16S chordate PCR primers were effective at identifying 29 fish taxa, with 98.3% of amplified sequences being identified to species or genus level in 193 samples (61.7% collected). There was no significant difference in the number, occurrence or proportion of ray-finned fish prey DNA sequences derived from fresh samples or latrines. Mitochondrial 16S cephalopod PCR primers classified 1.98% of amplified DNA sequences as targets, with 96.5% of these target sequences being identified to species or genus level in 48 samples (15.3% collected), and five taxa identified. Conclusions. We recommend the collection of latrine samples to enable long-term monitoring of the diet of yellow-eyed penguins, which will optimise the trade-off between wildlife disturbance and dietary resolution. Further refinement is needed to identify cephalopod dietary components for yellow-eyed penguins, because our cephalopod primers were not as specific as those used for ray-finned fishes, amplifying a large number (>98%) of non-cephalopod species. Implications. DNA metabarcoding offers a robust and comprehensive alternative to other, more intrusive, seabird diet-assessment methods, but still requires parallel studies to provide critical information on prey size, true diet composition and diet quality.

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          GenBank

          GenBank® is a comprehensive database that contains publicly available DNA sequences for more than 165 000 named organisms, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the web-based BankIt or standalone Sequin programs and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the EMBL Data Library in the UK and the DNA Data Bank of Japan helps to ensure worldwide coverage. GenBank is accessible through NCBI's retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, go to the NCBI Homepage at http://www.ncbi.nlm.nih.gov.
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            Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data?

            Abstract Advances in DNA sequencing technology have revolutionized the field of molecular analysis of trophic interactions, and it is now possible to recover counts of food DNA sequences from a wide range of dietary samples. But what do these counts mean? To obtain an accurate estimate of a consumer's diet should we work strictly with data sets summarizing frequency of occurrence of different food taxa, or is it possible to use relative number of sequences? Both approaches are applied to obtain semi‐quantitative diet summaries, but occurrence data are often promoted as a more conservative and reliable option due to taxa‐specific biases in recovery of sequences. We explore representative dietary metabarcoding data sets and point out that diet summaries based on occurrence data often overestimate the importance of food consumed in small quantities (potentially including low‐level contaminants) and are sensitive to the count threshold used to define an occurrence. Our simulations indicate that using relative read abundance (RRA) information often provides a more accurate view of population‐level diet even with moderate recovery biases incorporated; however, RRA summaries are sensitive to recovery biases impacting common diet taxa. Both approaches are more accurate when the mean number of food taxa in samples is small. The ideas presented here highlight the need to consider all sources of bias and to justify the methods used to interpret count data in dietary metabarcoding studies. We encourage researchers to continue addressing methodological challenges and acknowledge unanswered questions to help spur future investigations in this rapidly developing area of research.
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              Scrutinizing key steps for reliable metabarcoding of environmental samples

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                Author and article information

                Contributors
                (View ORCID Profile)
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                Journal
                Wildlife Research
                Wildl. Res.
                CSIRO Publishing
                1035-3712
                2020
                2020
                : 47
                : 6
                : 509
                Article
                10.1071/WR19246
                e6ad8fe2-88a5-4155-9369-4c6f6b1e1bf6
                © 2020
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