FuzzyID2: A software package for large data set species identification via barcoding and metabarcoding using hidden Markov models and fuzzy set methods

Method for quick DNA barcode reference library construction

DNA barcoding has become one of the most important techniques in plant species identification. Successful application of this technology is dependent on the availability of reference database of high species coverage. Unfortunately, there are experimental and data processing challenges to construct such a library within a short time. Here, we present our solutions to these challenges. We sequenced six conventional DNA barcode fragments (ITS1, ITS2, matK1, matK2, rbcL1, and rbcL2) of 380 flowering plants on next-generation sequencing (NGS) platforms (Illumina Hiseq 2500 and Ion Torrent S5) and the Sanger sequencing platform. After comparing the sequencing depths, read lengths, base qualities, and base accuracies, we conclude that Illumina Hiseq2500 PE250 run is suitable for conventional DNA barcoding. We developed a new "Cotu" method to create consensus sequences from NGS reads for longer output sequences and more reliable bases than the other three methods. Step-by-step instructions to our method are provided. By using high-throughput machines (PCR and NGS), labeling PCR, and the Cotu method, it is possible to significantly reduce the cost and labor investments for DNA barcoding. A regional or even global DNA barcoding reference library with high species coverage is likely to be constructed in a few years.

Debar: A sequence-by-sequence denoiser for COI-5P DNA barcode data

DNA barcoding and metabarcoding are now widely used to advance species discovery and biodiversity assessments. High-throughput sequencing (HTS) has expanded the volume and scope of these analyses, but elevated error rates introduce noise into sequence records that can inflate estimates of biodiversity. Denoising -the separation of biological signal from instrument (technical) noise-of barcode and metabarcode data currently employs abundance-based methods which do not capitalize on the highly conserved structure of the cytochrome c oxidase subunit I (COI) region employed as the animal barcode. This manuscript introduces debar, an R package that utilizes a profile hidden Markov model to denoise indel errors in COI sequences introduced by instrument error. In silico studies demonstrated that debar recognized 95% of artificially introduced indels in COI sequences. When applied to real-world data, debar reduced indel errors in circular consensus sequences obtained with the Sequel platform by 75%, and those generated on the Ion Torrent S5 by 94%. The false correction rate was less than 0.1%, indicating that debar is receptive to the majority of true COI variation in the animal kingdom. In conclusion, the debar package improves DNA barcode and metabarcode workflows by aiding the generation of more accurate sequences aiding the characterization of species diversity.

Regional assemblages shaped by historical and contemporary factors: Evidence from a species-rich insect group

Understanding diversity patterns requires accounting for the roles of both historical and contemporary factors in the assembly of communities. Here, we compared diversity patterns of two moth assemblages sampled from Taihang and Yanshan mountains in Northern China and performed ancestral range reconstructions using the Multi-State Speciation and Extinction model, to track the origins of these patterns. Further, we estimated diversification rates of the two moth assemblages and explored the effects of contemporary ecological factors. From 7,788 specimens we identified 835 species belonging to 23 families, using both DNA barcode analysis and morphology. Moths in Yanshan mountains showed higher species diversity than in Taihang mountains. Ancestral range analysis indicated Yanshan as the origin, with significant historical dispersals from Yanshan to Taihang. Asymmetrical diversification, population expansion, along with frequent and considerable gene flow were detected between communities. Moreover, dispersal limitation or the joint effect of environment filtering and dispersal limitation were inferred as main driving forces shaping current diversity patterns. In summary, we demonstrate that a multiscale (community, population and species level) analysis incorporating both historical and contemporary factors can be useful in delineating factors contributing to community assembly and patterning in diversity.

A two-step DNA barcoding approach for delimiting moth species: moths of Dongling Mountain (Beijing, China) as a case study

DNA barcoding, based on a fragment of cytochrome c oxidase I (COI) mtDNA, is as an effective molecular tool for identification, discovery, and biodiversity assessment for most animals. However, multiple gene markers coupled with more sophisticated analytical approaches may be necessary to clarify species boundaries in cases of cryptic diversity or morphological plasticity. Using 339 moths collected from mountains surrounding Beijing, China, we tested a pipeline consisting of two steps: (1) rapid morphospecies sorting and screening of the investigated fauna with standard COI barcoding approaches; (2) additional analyses with multiple molecular markers for those specimens whose morphospecies and COI barcode grouping were incongruent. In step 1, 124 morphospecies were delimited into 116 barcode units, with 90% of the conflicts being associated with specimens identified to the genus Hypena. In step 2, 55 individuals representing all 12 Hypena morphospecies were analysed using COI, COII, 28S, EF-1a, Wgl sequences or their combinations with the BPP (Bayesian Phylogenetics and Phylogeography) multigene species delimitation method. The multigene analyses supported the delimitation of 5 species, consistent with the COI analysis. We conclude that a two-step barcoding analysis pipeline is able to rapidly characterize insect biodiversity and help to elucidate species boundaries for taxonomic complexes without jeopardizing overall project efficiency by substantially increasing analytical costs.

Automated high throughput animal CO1 metabarcode classification

We introduce a method for assigning names to CO1 metabarcode sequences with confidence scores in a rapid, high-throughput manner. We compiled nearly 1 million CO1 barcode sequences appropriate for classifying arthropods and chordates. Compared to our previous Insecta classifier, the current classifier has more than three times the taxonomic coverage, including outgroups, and is based on almost five times as many reference sequences. Unlike other popular rDNA metabarcoding markers, we show that classification performance is similar across the length of the CO1 barcoding region. We show that the RDP classifier can make taxonomic assignments about 19 times faster than the popular top BLAST hit method and reduce the false positive rate from nearly 100% to 34%. This is especially important in large-scale biodiversity and biomonitoring studies where datasets can become very large and the taxonomic assignment problem is not trivial. We also show that reference databases are becoming more representative of current species diversity but that gaps still exist. We suggest that it would benefit the field as a whole if all investigators involved in metabarocoding studies, through collaborations with taxonomic experts, also planned to barcode representatives of their local biota as a part of their projects.

Scaling up: A guide to high-throughput genomic approaches for biodiversity analysis

The purpose of this review is to present the most common and emerging DNA-based methods used to generate data for biodiversity and biomonitoring studies. As environmental assessment and monitoring programmes may require biodiversity information at multiple levels, we pay particular attention to the DNA metabarcoding method and discuss a number of bioinformatic tools and considerations for producing DNA-based indicators using operational taxonomic units (OTUs), taxa at a variety of ranks and community composition. By developing the capacity to harness the advantages provided by the newest technologies, investigators can "scale up" by increasing the number of samples and replicates processed, the frequency of sampling over time and space, and even the depth of sampling such as by sequencing more reads per sample or more markers per sample. The ability to scale up is made possible by the reduced hands-on time and cost per sample provided by the newest kits, platforms and software tools. Results gleaned from broad-scale monitoring will provide opportunities to address key scientific questions linked to biodiversity and its dynamics across time and space as well as being more relevant for policymakers, enabling science-based decision-making, and provide a greater socio-economic impact. As genomic approaches are continually evolving, we provide this guide to methods used in biodiversity genomics.