Community-level data, the type generated by an increasing number of metabarcoding studies, is often graphed as stacked bar charts or pie graphs that use color to represent taxa. These graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. As an alternative, we developed metacoder, an R package for easily parsing, manipulating, and graphing publication-ready plots of hierarchical data. Metacoder includes a dynamic and flexible function that can parse most text-based formats that contain taxonomic classifications, taxon names, taxon identifiers, or sequence identifiers. Metacoder can then subset, sample, and order this parsed data using a set of intuitive functions that take into account the hierarchical nature of the data. Finally, an extremely flexible plotting function enables quantitative representation of up to 4 arbitrary statistics simultaneously in a tree format by mapping statistics to the color and size of tree nodes and edges. Metacoder also allows exploration of barcode primer bias by integrating functions to run digital PCR. Although it has been designed for data from metabarcoding research, metacoder can easily be applied to any data that has a hierarchical component such as gene ontology or geographic location data. Our package complements currently available tools for community analysis and is provided open source with an extensive online user manual.

BackgroundMilkweeds (Asclepias L.) have been extensively investigated in diverse areas of evolutionary biology and ecology; however, there are few genetic resources available to facilitate and compliment these studies. This study explored how low coverage genome sequencing of the common milkweed (Asclepias syriaca L.) could be useful in characterizing the genome of a plant without prior genomic information and for development of genomic resources as a step toward further developing A. syriaca as a model in ecology and evolution.ResultsA 0.5× genome of A. syriaca was produced using Illumina sequencing. A virtually complete chloroplast genome of 158,598 bp was assembled, revealing few repeats and loss of three genes: accD, clpP, and ycf1. A nearly complete rDNA cistron (18S-5.8S-26S; 7,541 bp) and 5S rDNA (120 bp) sequence were obtained. Assessment of polymorphism revealed that the rDNA cistron and 5S rDNA had 0.3% and 26.7% polymorphic sites, respectively. A partial mitochondrial genome sequence (130,764 bp), with identical gene content to tobacco, was also assembled. An initial characterization of repeat content indicated that Ty1/copia-like retroelements are the most common repeat type in the milkweed genome. At least one A. syriaca microread hit 88% of Catharanthus roseus (Apocynaceae) unigenes (median coverage of 0.29×) and 66% of single copy orthologs (COSII) in asterids (median coverage of 0.14×). From this partial characterization of the A. syriaca genome, markers for population genetics (microsatellites) and phylogenetics (low-copy nuclear genes) studies were developed.ConclusionsThe results highlight the promise of next generation sequencing for development of genomic resources for any organism. Low coverage genome sequencing allows characterization of the high copy fraction of the genome and exploration of the low copy fraction of the genome, which facilitate the development of molecular tools for further study of a target species and its relatives. This study represents a first step in the development of a community resource for further study of plant-insect co-evolution, anti-herbivore defense, floral developmental genetics, reproductive biology, chemical evolution, population genetics, and comparative genomics using milkweeds, and A. syriaca in particular, as ecological and evolutionary models.

Community-level data, the type generated by an increasing number of metabarcoding studies, is often graphed as stacked bar charts or pie graphs that use color to represent taxa. These graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. As an alternative, we developed metacoder, an R package for easily parsing, manipulating, and graphing publication-ready plots of hierarchical data. Metacoder includes a dynamic and flexible function that can parse most textbased formats that contain taxonomic classifications, taxon names, taxon identifiers, or sequence identifiers. Metacoder can then subset, sample, and order this parsed data using a set of intuitive functions that take into account the hierarchical nature of the data. Finally, an extremely flexible plotting function enables quantitative representation of up to 4 arbitrary statistics simultaneously in a tree format by mapping statistics to the color and size of tree nodes and edges. Metacoder also allows exploration of barcode primer bias by integrating functions to run digital PCR. Although it has been designed for data from metabarcoding research, metacoder can easily be applied to any data that has a hierarchical component such as gene ontology or geographic location data. Our package complements currently available tools for community analysis and is provided open source with an extensive online user manual. This is a PLOS Computational Biology

The taxa R package provides a set of tools for defining and manipulating taxonomic data. The recent and widespread application of DNA sequencing to community composition studies is making large data sets with taxonomic information commonplace. However, compared to typical tabular data, this information is encoded in many different ways and the hierarchical nature of taxonomic classifications makes it difficult to work with. There are many R packages that use taxonomic data to varying degrees but there is currently no cross-package standard for how this information is encoded and manipulated. We developed the R package taxa to provide a robust and flexible solution to storing and manipulating taxonomic data in R and any application-specific information associated with it. Taxa provides parsers that can read common sources of taxonomic information (taxon IDs, sequence IDs, taxon names, and classifications) from nearly any format while preserving associated data. Once parsed, the taxonomic data and any associated data can be manipulated using a cohesive set of functions modeled after the popular R package dplyr. These functions take into account the hierarchical nature of taxa and can modify the taxonomy or associated data in such a way that both are kept in sync. Taxa is currently being used by the metacoder and taxize packages, which provide broadly useful functionality that we hope will speed adoption by users and developers.

Oomycetes are a group of eukaryotes related to brown algae and diatoms, many of which cause plant and animal diseases. Improved methods are needed for rapid and accurate characterization of oomycete communities using DNA metabarcoding. We have identified the mitochondrial 40S ribosomal protein S10 gene (rps10) as a locus for oomycete metabarcoding and provide primers predicted to amplify all oomycetes based on a wide range of available reference sequences. We evaluated its utility relative to the internal transcribed spacer 1 (ITS1), by sequencing environmental samples and a mock community using Illumina MiSeq. Amplified sequence variants (ASVs) and operational taxonomic units (OTUs) were identified per community. Observed sequences and predicted taxonomy of ASVs and OTUs were compared to the known composition of the mock community. Both rps10 and ITS yielded ASVs with sequences matching 21 of the 24 species in the mock community and matching all 24 when allowing for a 1 bp difference. Taxonomic classifications of ASVs included 23 members of the mock community for rps10 and 17 for ITS1. Sequencing results for the environmental samples suggest that the rps10 locus results in substantially less amplification of non-target organisms than the ITS1 method. The amplified rps10 region also has higher taxonomic resolution than ITS1, allowing for greater discrimination of closely related species. We present a new website with a searchable rps10 reference database for species identification and all protocols needed for oomycete metabarcoding. The rps10 barcode and methods described herein provide an effective tool for metabarcoding oomycetes using short-read sequencing.