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1,076 results for “Metabarcoding”
Ecological specialization and niche overlap of subterranean rodents inferred from DNA metabarcoding diet analysis
<p>Knowledge of how animal species use food resources available in the environment increases our understanding of ecological processes. However, obtaining this information using traditional methods is a hard task for species feeding on a large variety of food items in highly diverse environments. We amplified the DNA of plants for 306 scat and 40 soil samples, and applied an eDNA metabarcoding approach to investigate food preferences, degree of diet specialization and diet overlap of seven herbivore rodent species of the <i>Ctenomys</i> genus distributed in southern and midwestern Brazil.<b> </b>The metabarcoding approach revealed that species consume more than 60% of the plant families recovered in soil samples, indicating generalist feeding habits of ctenomyids. The Poaceae family was the most common food resource retrieved in scats of all species as well in soil samples. Niche overlap analysis indicated high overlap in the plant families and Molecular Operational Taxonomic Units consumed, mainly among the southern species.<b> </b>Interspecific difference in diet composition was influenced, among other factors, by the availability of resources in the environment. In addition, our results provide support for the hypothesis that the allopatric distributions of ctenomyids allow them to exploit the same range of resources when available, possibly because of the absence of interspecific competition.</p>
Supplementary material 1 from: Duarte S, Vieira PE, Costa FO (2020) Assessment of species gaps in DNA barcode libraries of non-indigenous species (NIS) occurring in European coastal regions. Metabarcoding and Metagenomics 4: e55162. https://doi.org/10.3897/mbmg.4.55162
Supplementary figures and tables used to analyse the data
Multi-species models reveal that eDNA metabarcoding is more sensitive than backpack electrofishing for conducting fish surveys in freshwater streams
Environmental DNA (eDNA) sampling can provide accurate, cost-effective, landscape-level data on species distributions. Previous studies have compared the sensitivity of eDNA sampling to traditional sampling methods for single species, but similar comparative studies on multi-species eDNA metabarcoding are rare. Using hierarchical species occupancy-detection models, we examined whether key choices associated with eDNA metabarcoding (primer selection, low-abundance read filtering, and the number of positive water samples used to classify a species as present at a site) affect the sensitivity of metabarcoding, relative to backpack electrofishing for fish in freshwater streams. Under all scenarios (teleostei and vertebrate primers; 0%, 0.1% and 1% read filtering thresholds; 1 or 2 positive samples required to classify species as present), we found that eDNA metabarcoding is, on average, more sensitive than electrofishing. Combining vertebrate and teleostei markers resulted in higher detection probabilities relative to the use of either marker in isolation. Increasing the threshold used to filter low abundance reads decreased species detection probabilities but did not change our overall finding that eDNA metabarcoding was more sensitive than electrofishing. Using a threshold of two positive water samples (out of 5) to classify a species as present typically had negligible effects on detection probabilities compared to using one positive water sample. Our findings demonstrate that eDNA metabarcoding is generally more sensitive than electrofishing for conducting fish surveys in freshwater streams, and that this outcome is not sensitive to methodological decisions associated with metabarcoding.
The limited spatial scale of dispersal in soil arthropods revealed with whole-community haplotype-level metabarcoding
<p>Soil mesofauna communities are hyperdiverse and critical for ecosystem functioning. However, our knowledge on spatial structure and underlying processes of community assembly for soil arthropods is scarce, hampered by limited empirical data on species diversity and turnover. We implement a high-throughput-sequencing approach to generate comparative data for thousands of arthropods at three hierarchical levels: genetic, species and supra-specific lineages. A joint analysis of the spatial arrangement across these levels can reveal the predominant processes driving the variation in biological assemblages at the local scale. This multi-hierarchical approach was performed using <span>haplotype-level-COI metabarcoding</span> of entire communities of mites, springtails and beetles from three Iberian mountain regions. Tens of thousands of specimens were extracted from deep and superficial soil layers and produced comparative phylogeographic data for >1000 co-distributed species and nearly 3000 haplotypes. Local assemblages were highly distinctive between grasslands and forests, and within each of them showed strong spatial structures and high endemicity at the scale of a few kilometres or less. The local distance-decay patterns were self-similar for the haplotypes and higher hierarchical entities, and this fractal structure was very similar in all three regions, pointing to a significant role of dispersal limitation driving the local-scale community assembly. Our results from whole-community metabarcoding provide insight into how dispersal limitations constrain mesofauna community structure within local spatial settings over evolutionary timescales. If generalized across wider areas, the high turnover and endemicity in the soil locally may indicate extremely high richness globally, challenging our current estimations of total arthropod-diversity on Earth.</p>
Supplementary material 1 from: Snyder MR, Stepien CA (2020) Increasing confidence for discerning species and population compositions from metabarcoding assays of environmental samples: case studies of fishes in the Laurentian Great Lakes and Wabash River. Metabarcoding and Metagenomics 4: e53455. https://doi.org/10.3897/mbmg.4.53455
Supplementary material: Additional methods, results, figures, and tables
Supplementary material 2 from: Laini A, Beermann AJ, Bolpagni R, Burgazzi G, Elbrecht V, Zizka VMA, Leese F, Viaroli P (2020) Exploring the potential of metabarcoding to disentangle macroinvertebrate community dynamics in intermittent streams. Metabarcoding and Metagenomics 4: e51433. https://doi.org/10.3897/mbmg.4.51433
Table S1, Figures S1–S5
Supplementary material 1 from: Laini A, Beermann AJ, Bolpagni R, Burgazzi G, Elbrecht V, Zizka VMA, Leese F, Viaroli P (2020) Exploring the potential of metabarcoding to disentangle macroinvertebrate community dynamics in intermittent streams. Metabarcoding and Metagenomics 4: e51433. https://doi.org/10.3897/mbmg.4.51433
Raw data
Supplementary material 1 from: Nugent CM, Adamowicz SJ (2020) Alignment-free classification of COI DNA barcode data with the Python package Alfie. Metabarcoding and Metagenomics 4: e55815. https://doi.org/10.3897/mbmg.4.55815
File S1 – Training, test, and validation data sets used in model training and analysis
Supplementary material 1 from: Macher J-N, Drakou K, Papatheodoulou A, Hoorn B, Vasquez M (2020) The mitochondrial genomes of 11 aquatic macroinvertebrate species from Cyprus. Metabarcoding and Metagenomics 4: e58259. https://doi.org/10.3897/mbmg.4.58259
Scripts used for Megahit and Spades assemly of mitochornial genomes and nuclear 18S and 28S rRNAs
Supplementary material 1 from: Di Muri C, Lawson Handley L, Bean CW, Li J, Peirson G, Sellers GS, Walsh K, Watson HV, Winfield IJ, Hänfling B (2020) Read counts from environmental DNA (eDNA) metabarcoding reflect fish abundance and biomass in drained ponds. Metabarcoding and Metagenomics 4: e56959. https://doi.org/10.3897/mbmg.4.56959
Table S1 and Figure S1
Supplementary material 2 from: Di Muri C, Lawson Handley L, Bean CW, Li J, Peirson G, Sellers GS, Walsh K, Watson HV, Winfield IJ, Hänfling B (2020) Read counts from environmental DNA (eDNA) metabarcoding reflect fish abundance and biomass in drained ponds. Metabarcoding and Metagenomics 4: e56959. https://doi.org/10.3897/mbmg.4.56959
Table S2. Fish taxonomic assignment metaBEAT
Supplementary material 3 from: Di Muri C, Lawson Handley L, Bean CW, Li J, Peirson G, Sellers GS, Walsh K, Watson HV, Winfield IJ, Hänfling B (2020) Read counts from environmental DNA (eDNA) metabarcoding reflect fish abundance and biomass in drained ponds. Metabarcoding and Metagenomics 4: e56959. https://doi.org/10.3897/mbmg.4.56959
Table S3. Unassigned blast 1.0
Data from: eDNA metabarcoding reveals a core and secondary diets of the greater horseshoe bat with strong spatio-temporal plasticity
<p><strong>ABSTRACT</strong></p> <p>Dietary plasticity is an important issue for conservation biology as it may be essential for species to cope with environmental changes. However, it still remains scarcely addressed in the literature, potentially because diet studies have long been constrained by methodological limits. The advent of molecular approaches now makes it possible to get a precise picture of diet and its plasticity, even for endangered and elusive species. Here we focused on the greater horseshoe bat (<em>Rhinolophus ferrumequinum</em>) in Western France, where this insectivorous species has been classified as ‘Vulnerable’ on the Regional Red List (2016). We applied an eDNA metabarcoding approach on 1986 fecal samples collected in six maternity colonies at three sampling dates. We described its diet and investigated whether the landscape surrounding colonies and the different phases of the maternity cycle influenced the diversity and the composition of this diet. We showed that <em>R. ferrumequinum</em> feed on a highly more diverse spectrum of prey than expected from previous studies, therefore highlighting how eDNA metabarcoding can help improving diet knowledge of a flying elusive endangered species. Our approach also revealed that <em>R. ferrumequinum</em> diet is composed of two distinct features: the core diet consisting in a few preferred taxa shared by all the colonies (25% of the occurrences) and the secondary diet consisting in numerous rare prey that were highly different between colonies and sampling dates (75% of the occurrences). Energetic needs and constraints associated with the greater horseshoe bat life-cycle, as well as insect phenology and landscape features, strongly influenced the diversity and composition of both the whole and core diets. Further research should now explore the relationships between <em>R. ferrumequinum</em> dietary plasticity and fitness, to better assess the impact of core prey decline on <em>R. ferrumequinum</em> populations viability.</p> <p> </p> <p><strong>FILE DESCRIPTION</strong></p> <p><strong>Information concerning the samples and the positive and negative controls multiplexed in the MiSeq Runs 5 to 9</strong></p> <p>This XLSX file contains the sample IDs, the sample types, the PCR IDs, the PCR replicate numbers, the locality names, the predator species and the fastq file names for each PCR products multiplexed in the five different Illumina MiSeq runs.</p> <p>File name: Sample_informations.xlsx</p> <p> </p> <p><strong>MiSeq raw sequences of the COI minibarcode from the faecal pellets of bats (Run5)</strong></p> <p>This ZIP file contains the Run5 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each faecal pellet in triplicate using the MiSeq platform. The 1271 multiplexed PCR products were indexed using both forward and reverse indices. The list of the 475 multiplexed samples and the 8 positive and 94 negative controls are provided in the following XLSX file titled: Sample_Information.xlsx.</p> <p>Note: the 186 PCR3 replicates from the localities BEA and SGE are available in the ZIP file MiSeq_Reads_COI_Bat_faecal_pellets_Run9.zip</p> <p>File name: MiSeq_Reads_COI_Bat_faecal_pellets_Run5.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the COI minibarcode from the faecal pellets of bats (Run6)</strong></p> <p>This ZIP file contains the Run6 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each faecal pellet in triplicate using the MiSeq platform. The 1440 multiplexed PCR products were indexed using both forward and reverse indices. The list of the 466 multiplexed samples and the 8 positive and 130 negative controls are provided in the following XLSX file titled: Sample_Information.xlsx.</p> <p>File name: MiSeq_Reads_COI_Bat_faecal_pellets_Run6.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the COI minibarcode from the faecal pellets of bats (Run7)</strong></p> <p>This ZIP file contains the Run7 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each faecal pellet in triplicate using the MiSeq platform. The 1464 multiplexed PCR products were indexed using both forward and reverse indices. The list of the 475 multiplexed samples and the 8 positive and 103 negative controls are provided in the following XLSX file titled: Sample_Information.xlsx.</p> <p>File name: MiSeq_Reads_COI_Bat_faecal_pellets_Run7.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the COI minibarcode from the faecal pellets of bats (Run8)</strong></p> <p>This ZIP file contains the Run8 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each faecal pellet in triplicate using the MiSeq platform. The 1464 multiplexed PCR products were indexed using both forward and reverse indices. The list of the 475 multiplexed samples and the 8 positive and 103 negative controls are provided in the following XLSX file titled: Sample_Information.xlsx.</p> <p>File name: MiSeq_Reads_COI_Bat_faecal_pellets_Run8.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the COI minibarcode from the faecal pellets of bats (Run9)</strong></p> <p>This ZIP file contains the Run9 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each faecal pellet in triplicate using the MiSeq platform. The 499 multiplexed PCR products were indexed using both forward and reverse indices. The list of the 281 multiplexed samples (including 29 samples from another project) and the 11 positive and 172 negative controls are provided in the following XLSX file titled: Sample_Information.xlsx.</p> <p>Note: the 372 PCR1 & PCR2 replicates from the localities BEA and SGE are available in the ZIP file MiSeq_Reads_COI_Bat_faecal_pellets_Run5.zip</p> <p>File name: MiSeq_Reads_COI_Bat_faecal_pellets_Run9.zip</p> <p> </p> <p><strong>Raw abundance tables of the COI minibarcode from the faecal pellets of bats before data filtering (Run5 to 9)</strong></p> <p>This ZIP file contains five TXT files showing the number of reads for each of the 17,998 distinct variants (OTUs) and each of the 6138 PCR products of the samples (<em>n</em>=2015) and controls sequenced in the MiSeq Runs 5 to 9 before the data filtering.</p> <p>File name: Raw_COI_Bat_Faecal_Pellets_abundance_Runs5to9_before_filtering.zip</p> <p> </p> <p><strong>Abundance table of the COI minibarcode from the faecal pellets of bats after data filtering (Run5 to 9)</strong></p> <p>This XLSX file contains the number of reads for each of the 7206 distinct variants (OTUs) and each of sample (<em>n</em>=2014) after the data filtering using (1) the thresholds based on the negative and positive controls (Tcc & Tfa) and (2) the validation using the three technical replicates.</p> <p>File name: COI_Bat_Faecal_Pellets_abundance_Runs5to9_after_filtering.xlsx</p> <p> </p> <p><strong>Final abundance table of the COI minibarcode for the prey of <em>Rhinolophus ferrumequinum</em> only (Run5 to 9)</strong></p> <p>This XLSX file contains the number of reads for each <em>Rhinolophus ferrumequinum</em> samples (<em>n</em>=1034) and each of the 679 validated prey taxa (OTUs) after taxonomic affiliations check and redundancy removals.</p> <p>File name: Final_COI_Rhino_Prey_abundance_Run5to9.xlsx</p> <p> </p> <p><strong>Landscape data table used to build the PCA</strong></p> <p>File name: Landscape_variables.xlsx</p>
Supplementary material 1 from: Clasen LA, Detheridge AP, Scullion J, Griffith GW (2020) Soil stabilisation for DNA metabarcoding of plants and fungi. Implications for sampling at remote locations or via third-parties. Metabarcoding and Metagenomics 4: e58365. https://doi.org/10.3897/mbmg.4.58365
Combined Supplemntary Data Files 1–8
Supplementary material 9 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Figure S3
Supplementary material 10 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Figure S4
Supplementary material 11 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Figure S5
Supplementary material 8 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Figure S2
Supplementary material 12 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Figure S6
Supplementary material 7 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Figure S1
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