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Fig. 10 in Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing

Fig. 10. Phylogenetic analysis of the isolated bacteria/viruses. Reference oligonucleotide sequences were selected by BLAST searches of the NCBI nt database. (A) Subtrees of the experimental sequences from the Borrelia burgdorferi 16S rRNA gene. (B) Subtrees of the experimental sequences from the Coxiella burnetii 16S rRNA gene. (C) Subtrees of the experimental sequences from the Anaplasma phagocytophilum MSP4 gene. (D) Subtrees of the experimental sequences from the Simian foamy virus pathogen. (E) Subtrees of the experimental sequences from the Crimean-Congo haemorrhagic fever orthonairovirus segment-S gene.

Fig. 7 in Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing

Fig. 7. Population distribution of micropathogens in different samples. Note: "%" represents the proportion of micropathogen in the total community from each sample.

Fig. 3 in Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing

Fig. 3. Venn diagram based on the eggNOG database. Note: The corresponding functional categories and non-supervised orthologous group (NOG) numbers were obtained from the eggNOG database.

Fig. 5 in Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing

Fig. 5. Heat maps of community composition based on genera. Note: X-axis, template name; Y-axis, genus. The darker the blue colour is, the higher the enrichment of the genus in the sample.

Fig. 2 in Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing

Fig. 2. Summary of the tag length distribution following the sequencing of genes from the four samples.

Fig. 9 in Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing

Fig. 9. Pie chart of the distribution of viral abundances in different samples. Note: "%" represents the proportion of the virus in the total community from each sample, and the different colours represent different viruses. A: The primary micropathogens analysed in G1. B: The primary micropathogens analysed in G2. C: The main micropathogens analysed in G3. D: The main micropathogens analysed in G4.

Fig. 4 in Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing

Fig. 4. Venn diagram based on the KEGG Orthology database. Note: DIAMOND was used to compare gene sequences with the KEGG database, and the corresponding metabolic pathway information and KEGG orthology results of the genes were obtained from the KEGG database.

Fig. 1 in Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing

Fig. 1. The genomic DNA library was generated according to the PacBio Sequel sample preparation instructions.

opencc-zeroDec 2019View details →

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Molecular sequencing and morphological identification reveal similar patterns in native bee communities across private and public grasslands of eastern North Dakota

Bees play a key role in the functioning of human-modified and natural ecosystems by pollinating agricultural crops and wild plant communities. Global pollinator conservation efforts need large-scale and long-term monitoring to detect changes in species' demographic patterns and shifts in bee community structure. The objective of this project was to test a molecular sequencing pipeline that would utilize a commonly used locus, produce accurate and precise identifications consistent with morphological identifications, and generate data that are both qualitative and quantitative. We applied this amplicon sequencing pipeline to native bee communities sampled across Conservation Reserve Program (CRP) lands and native grasslands in eastern North Dakota. We found the 28S LSU locus to be more capable of discriminating between species than the 18S SSU rRNA locus, and in some cases even resolved instances of cryptic species or morphologically ambiguous species complexes. Overall, we found the amplicon sequencing method to be a qualitatively accurate representation of the sampled bee community richness and species identity, especially when a well-curated database of known 28S LSU sequences is available. Both morphological identification and molecular sequencing revealed similar patterns in native bee community structure across CRP lands and native prairie. Additionally, a genetic algorithm approach to compute taxon-specific correction factors using a small subset of the most concordant samples demonstrated that a high level of quantitative accuracy could be possible if the specimens are fresh and processed soon after collection. Here we provide a first step to a molecular pipeline for identifying insect pollinator communities. This tool should prove useful for future national monitoring efforts as use of molecular tools becomes more affordable and as numbers of 28S LSU sequences for pollinator species increase in publicly-available databases.

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Fig. 6 in Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing

Fig. 6. Bar chart of the relative abundances of genera.

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Fig. 8 in Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing

Fig. 8. Bar chart of the relative abundances of bacteria.

publicJan 2020View details →

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Molecular sequencing and morphological identification reveal similar patterns in native bee communities across public and private grasslands of eastern North Dakota

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Efficacy of metabarcoding for identification of fish eggs evaluated with mock communities

There is urgent need for effective and efficient monitoring of marine fish populations. Monitoring eggs and larval fish may be more informative that traditional fish surveys since ichthyoplankton surveys reveal the reproductive activities of fish populations, which directly impact their population trajectories. Ichthyoplankton surveys have turned to molecular methods (DNA barcoding & metabarcoding) for identification of eggs and larval fish due to challenges of morphological identification. In this study we examine the effectiveness of using metabarcoding methods on mock communities of known fish egg DNA. We constructed six mock communities with known ratios of species. In addition we analyzed two samples from a large field collection of fish eggs and compared metabarcoding results with traditional DNA barcoding results. We examine the ability of our metabarcoding methods to detect species and relative proportion of species identified in each mock community. We found that our metabarcoding methods were able to detect species at very low input proportions, however levels of successful detection depended on the markers used in amplification, suggesting that the use of multiple markers is desirable. Variability in our quantitative results may result from amplification bias as well as interspecific variation in mitochondrial DNA copy number. Our results demonstrate that there remain significant challenges to using metabarcoding for estimating proportional species composition; however the results provide important insights into understanding how to interpret metabarcoding data. This study will aid in the continuing development of efficient molecular methods of biological monitoring for fisheries management.

opencc-zeroFeb 2021View details →

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Data from: Identification of migratory bird flyways in North America using community detection on biological networks

Migratory behavior of waterfowl populations in North America has traditionally been broadly characterized by four north-south flyways, and these flyways have been central to the management of waterfowl populations for more than 80 years. However, previous flyway characterizations are not easily updated with current bird movement data and fail to provide assessments of the importance of specific geographical regions to the identification of flyways. Here, we developed a network model of migratory movement for four waterfowl species —mallard (Anas platyrhnchos), northern pintail (A. acuta), American green-winged teal (A. carolinensis), and Canada goose (Branta canadensis) — in North America using bird band and recovery data. We then identified migratory flyways using a community detection algorithm and characterize the importance of smaller geographic regions in identifying flyways using a novel metric, the consolidation factor. We identified four main flyways for mallards, northern pintails, and American green-winged teal with the flyway identification in Canada geese exhibiting higher complexity. For mallards, flyways were relatively consistent through time. However, consolidation factors revealed that for mallards and green-winged teal the presumptive Mississippi flyway was potentially a zone of high mixing between other flyways. Our results demonstrate that the network approach provides a robust method for flyway identification that is widely applicable given the relatively minimal data requirements and is easily updated with future movement data to reflect changes in flyway definitions and management goals.

opencc-zeroDec 2014View details →

FIGURE 18 in The diversity of a snake community in a karst forest ecosystem in the central Truong Son, Vietnam, with an identification key

FIGURE 18. Map showing the location of Phong Nha - Ke Bang National Park (1) within Quang Binh Province, central Vietnam, and Tam Dao National Park (2) in the North of Vietnam.

FIGURE 15 in The diversity of a snake community in a karst forest ecosystem in the central Truong Son, Vietnam, with an identification key

FIGURE 15. Spotted slug snake (Pareas macularius) in its habitat in Phong Nha - Ke Bang (ZFMK 86446). Photo: Thomas Ziegler

FIGURE 12 in The diversity of a snake community in a karst forest ecosystem in the central Truong Son, Vietnam, with an identification key

FIGURE 12. Portrait of the preserved specimen of Lycodon cf. ruhstrati from Phong Nha - Ke Bang (ZFMK 86451). Photo: Thomas Ziegler

FIGURE 10 in The diversity of a snake community in a karst forest ecosystem in the central Truong Son, Vietnam, with an identification key

FIGURE 10. Green bush ratsnake (Gonyosoma prasinum) while passing a forest road in Phong Nha - Ke Bang (ZFMK 86443). Photo: Astrid Heidrich

FIGURE 8 in The diversity of a snake community in a karst forest ecosystem in the central Truong Son, Vietnam, with an identification key

FIGURE 8. Portrait of the preserved male Calamaria thanhi from Phong Nha - Ke Bang (SRC PNKB III '06-1). Photo: Thomas Ziegler