Short DNA Barcode Research Articles

Environmental niche models improve species identification in DNA barcoding

Abstract Recent advances in DNA barcoding have immeasurably advanced global biodiversity research in the last two decades. However, inherent limitations in barcode sequences, such as hybridization, introgression or incomplete lineage sorting can lead to misidentifications when relying solely on barcode sequences. Here, we propose a new Niche‐model‐Based Species Identification (NBSI) method based on the idea that species distribution information is a potential complement to DNA barcoding species identifications. NBSI performs species membership inference by incorporating niche modelling predictions and traditional DNA barcoding identifications. Systematic tests across diverse scenarios show significant improvements in species identification success rates under the newly proposed NBSI framework, where the largest increase is from 4.7% (95% CI: 3.51%–6.25%) to 94.8% (95% CI: 93.19%–96.06%). Additionally, obvious improvements were observed when using NBSI on potentially ambiguous sequences whose genetic nearest neighbours belongs to another species or more than two species, which occurs commonly with species represented by single or short DNA barcodes. These results support our assertion that environmental factors/variables are valuable complements to DNA sequence data for species identification by avoiding potential misidentifications inferred from genetic information alone. The NBSI framework is currently implemented as a new R package, ‘NicheBarcoding’, that is open source under GNU General Public Licence and freely available from https://CRAN.R‐project.org/package=NicheBarcoding.

VESPA: an optimized protocol for accurate metabarcoding-based characterization of vertebrate eukaryotic endosymbiont and parasite assemblages

Protocols for characterizing taxonomic assemblages by deep sequencing of short DNA barcode regions (metabarcoding) have revolutionized our understanding of microbial communities and are standardized for bacteria, archaea, and fungi. Unfortunately, comparable methods for host-associated eukaryotes have lagged due to technical challenges. Despite 54 published studies, issues remain with primer complementarity, off-target amplification, and lack of external validation. Here, we present VESPA (Vertebrate Eukaryotic endoSymbiont and Parasite Analysis) primers and optimized metabarcoding protocol for host-associated eukaryotic community analysis. Using in silico prediction, panel PCR, engineered mock community standards, and clinical samples, we demonstrate VESPA to be more effective at resolving host-associated eukaryotic assemblages than previously published methods and to minimize off-target amplification. When applied to human and non-human primate samples, VESPA enables reconstruction of host-associated eukaryotic endosymbiont communities more accurately and at finer taxonomic resolution than microscopy. VESPA has the potential to advance basic and translational science on vertebrate eukaryotic endosymbiont communities, similar to achievements made for bacterial, archaeal, and fungal microbiomes.

Phylogenetic Structure Revealed through Combining DNA Barcodes with Multi-Gene Data for Agrodiaetus Blue Butterflies (Lepidoptera, Lycaenidae).

The need for multi-gene analysis in evolutionary and taxonomic studies is generally accepted. However, the sequencing of multiple genes is not always possible. For various reasons, short mitochondrial DNA barcodes are the only source of molecular information for some species in many genera, although multi-locus data are available for other species of the same genera. In particular, such situation exists in the species-rich butterfly subgenus Polyommatus (Agrodiaetus). Here, we analyzed the partitioning of this subgenus into species groups by using three data sets. The first data set was represented by short mitochondrial DNA barcodes for all analyzed samples. The second and third data sets were represented by a combination of short mitochondrial DNA barcodes for part of the taxa with longer mitochondrial sequences COI + tRNA-Leu + COII (data set 2) and with longer mitochondrial COI + tRNA-Leu + COII and nuclear 5.8S rDNA + ITS2 + 28S rDNA sequences (data set 3) for the remaining species. We showed that the DNA barcoding approach (data set 1) failed to reveal the phylogenetic structure, resulting in numerous polytomies in the tree obtained. Combined analysis of the mitochondrial and nuclear sequences (data sets 2 and 3) revealed the species groups and the position within these species groups, even for the taxa for which only short DNA barcodes were available.

Next-Generation Sequencing of Ancient and Recent Fungarium Specimens.

Fungaria are an unmatched resource for providing genetic data from authoritative, taxonomically-correct fungal species, especially type specimens. These specimens serve to anchor species hypotheses by enabling the correct taxonomic placement of taxa in systematic studies. The DNA from ancient specimens older than 30 years is commonly fragmented, and sometimes highly contaminated by exogenous, non-target fungal DNA, making conventional PCR amplification and Sanger sequencing difficult or impossible. Here, we present the results of DNA extraction, PCR amplification of the ITS2 region, and Illumina MiSeq Nano sequencing of nine recent and 11 ancient specimens, including seven type specimens. The taxa sampled included a range of large and fleshy, to small and tough, or small, melanized specimens of Discina, Gyromitra, Propolis, Stictis, and Xerotrema, with a culture of Lasiosphaeria serving as a positive control. DNA was highly fragmented and in very low quantity for most samples, resulting in inconclusive or incorrect results for all but five samples. Taxonomically-correct sequences were generated from the holotype specimens of G. arctica, G. korshinskii, and G. leucoxantha, from the neotype of G. ussuriensis, and from the positive control. Taxonomic assignments were confirmed through morphology, top BLASTn hits, and maximum likelihood phylogenetic analyses. Though this study was not cost-effective due to the small number of samples submitted and few generating correct sequences, it did produce short DNA barcode fragments for four type specimens that are essential for their correct taxonomic placement in our ongoing systematic studies.

Sorting Nanoparticles by Valency with DNA Barcoding.

Self-assembly of DNA-labeled nanoparticles is an effective strategy to fabricate new nanocomposite materials and nanoscale devices from the bottom-up. To tailor the properties of the resulting material or device, one requires access to a wide range of nanoparticle sizes and shapes, as well as control over the number (valency) of DNA molecules on the nanoparticle surface. Currently, nanoparticles with a defined DNA valency can only be obtained in a narrow range of sizes, and in small quantities, limiting the properties of the resulting composite structures and their applications. Here, we leverage the digital information encoded in the number and sequence of short DNA barcodes to generate preparatory amounts of nanoparticles bearing a specific number of DNA molecules, irrespective of the identity of the nanocomponent. We show that this DNA valency sorting chromatography, which is driven by the selective affinity of Watson-Crick base pairs, is applicable to arbitrary DNA sequences and a broad range of nanoparticle sizes, shapes, and material compositions. To further demonstrate this fact, we use valency-sorted large gold nanospheres directly in self-assembly schemes to create, in one synthesis step, large amounts of several previously inaccessible molecule-like dimer and trimer nanostructures with unique optical properties. We anticipate that the expanded scope of DNA valency-defined nanoparticle reagents, and the increased scale at which they can be produced, will open new avenues for the molecularly precise manipulation of nanoscale matter.

Plant-herbivorous insect networks: who is eating what revealed by long barcodes using high-throughput sequencing and Trinity assembly.

Interactions between plants and insects are among the most important life functions for all organism at a particular natural community. Usually a large number of samples are required to identify insect diets in food web studies. Previously, Sanger sequencing and next generation sequencing (NGS) with short DNA barcodes were used, resulting in low species-level identification; meanwhile the costs of Sanger sequencing are expensive for metabarcoding together with more samples. Here, we present a fast and effective sequencing strategy to identify larvae of Lepidoptera and their diets at the same time without increasing the cost on Illumina platformin a single HiSeq run, with long-multiplex-metabarcoding (COI for insects, rbcL, matK, ITS and trnL for plants) obtained by Trinity assembly (SHMMT). Meanwhile, Sanger sequencing (for single individuals) and NGS (for polyphagous) were used to verify the reliability of the SHMMT approach.Furthermore, we show that SHMMT approach is fast and reliable, with most high-quality sequences of five DNA barcodes of 63 larvae individuals (54 species) recovered (full length of 100% of the COI gene and 98.3% of plant DNA barcodes) using Trinity assembly (up-sized to 1015 bp). For larvae diets identification, 95% are reliable; the other 5% failed because their guts were empty. The diets identified by SHMMT approach are 100% consistent with the host plants that the larvae were feeding on during our collection. Our study demonstrates that SHMMT approach is reliable and cost-effective for insect-plants network studies. This will facilitate insect-host plant studies that generally contain a huge number of samples.

Identification of a Short Dna Bar Code in the 18S rdna for Improved Differentiation of Common Eimeria Species Infecting Chickens

The coccidian species Eimeria is a parasitic protozoan that causes the gastrointestinal disease coccidiosis in numerous vertebrate species. Incidence of the disease in commercial chickens produces drastic economic losses. Traditionally, detection of Eimeria has been performed using classical methods such as observation of oocyst morphology. However, molecular methods to detect and speciate Eimeria are becoming more prevalent. The 18S ribosomal gene, in particular, has been a widely used DNA amplification target for detection of Eimeria. Although the full-length gene is typically used for this purpose, newer research targeting shorter regions of the gene is being performed. This study investigated the suitability of a 120-base pair (bp) DNA bar code within the 18S gene for species differentiation. When comparing sequence variation from the Eimeria species infecting chickens, shortening the 18S gene to the 120-bp highly variable region provided increased species differentiation, while also reducing intraspecies variation. This DNA bar code is useful for distinction of the Eimeria species infecting chickens and should be considered for future molecular detection assays and metagenomic sequencing.

Barcode identification for single cell genomics

BackgroundSingle-cell sequencing experiments use short DNA barcode ‘tags’ to identify reads that originate from the same cell. In order to recover single-cell information from such experiments, reads must be grouped based on their barcode tag, a crucial processing step that precedes other computations. However, this step can be difficult due to high rates of mismatch and deletion errors that can afflict barcodes.ResultsHere we present an approach to identify and error-correct barcodes by traversing the de Bruijn graph of circularized barcode k-mers. Our approach is based on the observation that circularizing a barcode sequence can yield error-free k-mers even when the size of k is large relative to the length of the barcode sequence, a regime which is typical single-cell barcoding applications. This allows for assignment of reads to consensus fingerprints constructed from k-mers.ConclusionWe show that for single-cell RNA-Seq circularization improves the recovery of accurate single-cell transcriptome estimates, especially when there are a high number of errors per read. This approach is robust to the type of error (mismatch, insertion, deletion), as well as to the relative abundances of the cells. Sircel, a software package that implements this approach is described and publically available.

Synthesis of DNA-coupled isoquinolones and pyrrolidines by solid phase ytterbium- and silver-mediated imine chemistry.

DNA-encoded libraries of chemically synthesized compounds are an important small molecule screening technology. The synthesis of encoded compounds in solution is currently restricted to a few DNA-compatible and water-tolerant reactions. Encoded compound synthesis of short DNA-barcodes covalently connected to solid supports benefits from a broad range of choices of organic solvents. Here, we show that this encoded chemistry approach allows for the synthesis of DNA-coupled isoquinolones by an Yb(iii)-mediated Castagnoli-Cushman reaction under anhydrous reaction conditions and for the synthesis of highly substituted pyrrolidines by Ag(i)-mediated 1,3-dipolar azomethine ylide cycloaddition. An encoding scheme for these DNA-barcoded compounds based on a DNA hairpin is demonstrated.

Boosting DNA metabarcoding for biomonitoring with phylogenetic estimation of operational taxonomic units’ ecological profiles

DNA metabarcoding has been introduced as a revolutionary way to identify organisms and monitor ecosystems. However, the potential of this approach for biomonitoring remains partially unfulfilled because a significant part of the sampled DNA cannot be affiliated to species due to incomplete reference libraries. Thus, biotic indices, which are based on the estimated abundances of species in a community and their ecological profiles, can be inaccurate. We propose to compute biotic indices using phylogenetic imputation of operational taxonomic units (OTUs') ecological profiles (OTU-PITI approach). First, OTUs sequences are inserted within a reference phylogeny. Second, OTUs' ecological profiles are estimated on the basis of their phylogenetic relationships with reference species whose ecology is known. Based on these ecological profiles, biotic indices can be computed using all available OTUs. Using freshwater diatoms as a case study, we show that short DNA barcodes can be placed accurately within a phylogeny and their ecological preferences estimated with a satisfactory level of precision. In the light of these results, we tested the approach with a data set of 139 environmental samples of benthic river diatoms for which the same biotic index (specific sensitivity index) was calculated using (a) traditional microscopy, (b) OTUs with taxonomic assignment approach, (c) OTUs with phylogenetic estimation of ecological profiles (OTU-PITI) and (d) OTU with taxonomic assignment completed by the phylogenetic approach (OTU-PITI) for unclassified OTUs. Using traditional microscopy as a reference, we found that the combination of the OTUs' taxonomic assignment completed by the phylogenetic method performed satisfactorily and substantially better than the other methods tested.

Do we similarly assess diversity with microscopy and high-throughput sequencing? Case of microalgae in lakes

Diatoms are a species-diverse phylum of microalgae often presenting high biomass in aquatic habitats. This makes them excellent ecological indicators in rivers and lakes. They are routinely used to assess ecological quality of rivers and lakes using microscopy, which is time consuming. An alternative is to determine species in samples based on short DNA barcodes and high-throughput sequencing (HTS). Former studies showed that community structure and water quality assessments based on diatoms deliver similar results with both methods. But, none evaluated if diversities were assessed in the same way despite the importance of this ecological metric. Based on littoral benthic samplings carried out in 56 pristine alpine lakes, we compared different diversity indices measured with microscopy and metabarcoding. Each lake was sampled in three different places of its littoral. We showed that α (diversity measured in a single sampling site of a given lake) and ϒ (total diversity in a lake where three independent samples were considered) diversities obtained with HTS were higher than those obtained with microscopy. This may be explained by the capacity of HTS to detect morphologically cryptic species and to better detect rare taxa. On the other hand, β diversity obtained with HTS was smaller, which may be explained by the capacity of HTS to detect very rare species and free-floating extracellular DNA. Nevertheless, diversity indices obtained with both methodologies were well correlated each other. This study validates the possibility to assess diatom diversity with HTS in a comparable way to the classical microscopic analysis.

Combinatorial pooled sequencing: experiment design and decoding

Owing to rapid advances in the next‐generation sequencing technology, the cost of DNA sequencing has been reduced by over several orders of magnitude. However, genomic sequencing of individuals at the population scale is still restricted to a few model species due to the huge challenge of constructing libraries for thousands of samples. Meanwhile, pooled sequencing provides a cost‐effective alternative to sequencing individuals separately, which could vastly reduce the time and cost for DNA library preparation. Technological improvements, together with the broad range of biological research questions that require large sample sizes, mean that pooled sequencing will continue to complement the sequencing of individual genomes and become increasingly important in the foreseeable future. However, simply mixing samples together for sequencing makes it impossible to identify reads that belongs to each sample. Barcoding technology could help to solve this problem, nonetheless, currently, barcoding every sample is costly especially for large‐scale samples. An alternative to barcoding is combinatorial pooled sequencing which employs pooling pattern rather than short DNA barcodes to encode each sample. In combinatorial pooled sequencing, samples are mixed into few pools according to a carefully designed pooling strategy which allows the sequencing data to be decoded to identify the reads that belongs to the sample that are unique or rare in the population. In this review, we mainly survey the experiment design and decoding procedure for the combinatorial pooled sequencing applied in rare variant and rare haplotype carriers screening, complex genome assembling and single individual haplotyping.

Extraction and amplification of DNA from aged and archaeological Populus euphratica wood for species identification

Abstract The wood samples of Populus euphratica Oliv. (Salicaceae) are common archaeological plant remains in the hot and arid regions of western China. However, it is difficult to identify P. euphratica wood based on traditional wood anatomical methods alone. DNA barcoding might provide a higher security for species identification. In this study, aged wood specimens stored for approximately 30, 60, and 80 years and archaeological wood up to 3600 years old were in focus to explore the potential of DNA extraction and PCR amplification for different-sized fragments, ranging between 100 and 800 bp, taken from wood stored for different periods. The results indicated that DNA fragments of more than 100 bp could be successfully retrieved from a wood specimen stored for about 80 years based on a modified Qiagen kit protocol. However, it was impossible to obtain DNA segments from the 3600-year-old wood according to the current extraction protocol. Moreover, it was deduced that two-stage PCR amplification could play a significant role in the analysis of DNA retrieved from aged wood materials. With the aid of phylogenetic analysis, based on the short DNA barcode rbcL-2 of 202 bp in length, it was possible to differentiate P. euphratica from the other species of the Populus genus.

Development of deft amplification refractory mutation sequencing system (ARMSS) for discriminating Pilos antler based on a short cytochrome b (Cytb) gene

Pilos antler (Lu-Rong in Chinese) is a famous traditional medicine in China. Many adulterants have been discovered in Chinese markets in recent years. However, few DNA-based methods are effective for discrimination of this DNA-degraded animal medicine. Here, novel and deft amplification refractory mutation sequencing system (ARMSS), integrating the advantages of the amplification refractory mutation system (ARMS) and the short DNA barcode, was first developed to discriminate Pilos antler from its adulterants. We aimed to provide a new sight and inspiration for deft detection. The results showed that developed ARMS achieved strong specificity and high sensitivity in rapid identification, while the short Cytb gene was of excellent identification power in terms of accurate identification, which suggested that ARMSS successfully integrated the advantages of the ARMS and short DNA barcode, and that it was useful for deft detection. Our study determined that the deft ARMSS could be the well candidate for discrimination of Pilos antler, as well as be a valuable tool for deft identification of Chinese medicine.

Alignment-free analysis of barcode sequences by means of compression-based methods

BackgroundThe key idea of DNA barcode initiative is to identify, for each group of species belonging to different kingdoms of life, a short DNA sequence that can act as a true taxon barcode. DNA barcode represents a valuable type of information that can be integrated with ecological, genetic, and morphological data in order to obtain a more consistent taxonomy. Recent studies have shown that, for the animal kingdom, the mitochondrial gene cytochrome c oxidase I (COI), about 650 bp long, can be used as a barcode sequence for identification and taxonomic purposes of animals. In the present work we aims at introducing the use of an alignment-free approach in order to make taxonomic analysis of barcode sequences. Our approach is based on the use of two compression-based versions of non-computable Universal Similarity Metric (USM) class of distances. Our purpose is to justify the employ of USM also for the analysis of short DNA barcode sequences, showing how USM is able to correctly extract taxonomic information among those kind of sequences.ResultsWe downloaded from Barcode of Life Data System (BOLD) database 30 datasets of barcode sequences belonging to different animal species. We built phylogenetic trees of every dataset, according to compression-based and classic evolutionary methods, and compared them in terms of topology preservation. In the experimental tests, we obtained scores with a percentage of similarity between evolutionary and compression-based trees between 80% and 100% for the most of datasets (94%). Moreover we carried out experimental tests using simulated barcode datasets composed of 100, 150, 200 and 500 sequences, each simulation replicated 25-fold. In this case, mean similarity scores between evolutionary and compression-based trees span between 83% and 99% for all simulated datasets.ConclusionsIn the present work we aims at introducing the use of an alignment-free approach in order to make taxonomic analysis of barcode sequences. Our approach is based on the use of two compression-based versions of non-computable Universal Similarity Metric (USM) class of distances. This way we demonstrate the reliability of compression-based methods even for the analysis of short barcode sequences. Compression-based methods, with their strong theoretical assumptions, may then represent a valid alignment-free and parameter-free approach for barcode studies.

Analysis of barcode sequences by means of compression-based methods

Motivations. The key idea of DNA barcode initiative is to identify, for each group of species belonging to different kingdoms of life, a short DNA sequence that can act as a true taxon barcode. DNA barcode represents a valuable type of information that can be integrated with ecological, genetic, and morphological data in order to obtain a more consistent taxonomy. Recent studies have shown that, for the animal kingdom, the mitochondrial gene cytochrome c oxidase I (COI), about 650 bp long, can be used as a barcode sequence for identification and taxonomic purposes of animals. The analysis of DNA barcode sequences is carried out with well known bioinformatics techniques: for example the most common approach to create a phylogenetic tree for a group of species uses the multi-alignment of genetic sequences, the computation of a dissimilarity matrix, using one of the current available evolutionary distance model, and finally the building of a tree by means of hierarchical algorithms such as Unweighted Pair Group Method with Arithmetic Mean (UPGMA) and Neighbor Joining (NJ). In the present work we aims at introducing the use of an alignment-free approach in order to make taxonomic analysis of barcode sequences. Our approach is based on the use of two compression-based versions of non-computable Universal Similarity Metric (USM) class of distances. This way we try to overcome some flaws of classic techniques, such as the time-consuming and parameter-dependent alignment procedure and the use of stochastic evolutionary distance models, that do not represent a distance metric. Methods. Universal Similarity Metric represents a class of distance measures based on the non-computable Kolmogorov complexity. That means it needs some approximation in order to be used. USM is said to be "universal" because it can be applied for computing a distance matrix among input data belonging to very different application domains. In fact it has been used for the analysis of text, images, music. In bioinformatics, it has been applied for obtaining phylogenetic trees from complete mythocondrial genome of mammalian species. Our purpose is to justify the employ of USM also for the analysis of short DNA barcode sequences, showing USM is able to correctly extract taxonomic information among those kind of sequences. We, then, downloaded from Barcode of Life data System database (BOLD) 20 datasets of barcode sequences belonging to different animal species. For each dataset we computed dissimilarity matrices by means of two compression-based approximation of USM, namely Normalized Compression Distance (NCD) and its conditional compression version. In both cases we used GenCompres compressor, that is a dictionary-based compressor suited to work with DNA sequences. From those matrices we built, using UPGMA and NJ algorithms, phylogenetic trees of every dataset and compared them, in terms of topology preservation, with the trees obtained through Kimura 2-parameter evolutionary distance model. Results. Experimental tests aim to evaluate the quality of phylogenetic reconstruction in terms of both topological similarity and differences in the relative branch length. As regard the tree similarity, we obtain good results with a percentage of similarity between evolutionary and compression-based tree greater than 82% and, for the most of datasets, between 90% and 100%. Lower results are for datasets having an high percentage of sequences with ambiguous bases. We detect the same trend for differences in the relative branch of trees, except that poorer results are reached by those datasets containing some COI-5P gene sequences longer than the other ones.

DNA Barcodes Provide a Quick Preview of Mitochondrial Genome Composition

DNA barcodes have achieved prominence as a tool for species-level identifications. Consequently, there is a rapidly growing database of these short sequences from a wide variety of taxa. In this study, we have analyzed the correlation between the nucleotide content of the short DNA barcode sequences and the genomes from which they are derived. Our results show that such short sequences can yield important, and surprisingly accurate, information about the composition of the entire genome. In other words, for unsequenced genomes, the DNA barcodes can provide a quick preview of the whole genome composition.