Dataset Information

Evaluating the feasibility of using candidate DNA barcodes in discriminating species of the large Asteraceae family.

ABSTRACT:

Background

Five DNA regions, namely, rbcL, matK, ITS, ITS2, and psbA-trnH, have been recommended as primary DNA barcodes for plants. Studies evaluating these regions for species identification in the large plant taxon, which includes a large number of closely related species, have rarely been reported.

Results

The feasibility of using the five proposed DNA regions was tested for discriminating plant species within Asteraceae, the largest family of flowering plants. Among these markers, ITS2 was the most useful in terms of universality, sequence variation, and identification capability in the Asteraceae family. The species discriminating power of ITS2 was also explored in a large pool of 3,490 Asteraceae sequences that represent 2,315 species belonging to 494 different genera. The result shows that ITS2 correctly identified 76.4% and 97.4% of plant samples at the species and genus levels, respectively. In addition, ITS2 displayed a variable ability to discriminate related species within different genera.

Conclusions

ITS2 is the best DNA barcode for the Asteraceae family. This approach significantly broadens the application of DNA barcoding to resolve classification problems in the family Asteraceae at the genera and species levels.

SUBMITTER: Gao T

PROVIDER: S-EPMC3087544 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Evaluating the feasibility of using candidate DNA barcodes in discriminating species of the large Asteraceae family.

Gao Ting T Yao Hui H Song Jingyuan J Zhu Yingjie Y Liu Chang C Chen Shilin S

BMC evolutionary biology 20101026

<h4>Background</h4>Five DNA regions, namely, rbcL, matK, ITS, ITS2, and psbA-trnH, have been recommended as primary DNA barcodes for plants. Studies evaluating these regions for species identification in the large plant taxon, which includes a large number of closely related species, have rarely been reported.<h4>Results</h4>The feasibility of using the five proposed DNA regions was tested for discriminating plant species within Asteraceae, the largest family of flowering plants. Among these mar ...[more]

PMID: 20977734

Similar Datasets

Project description:BackgroundMajority of the species within Senecioneae are classified in Senecio, making it the tribe's largest genus. Certain intergeneric relationships within the tribe are vaguely defined, with the genus Senecio being partly linked to this ambiguity. Infrageneric relationships within Senecio remain largely unknown and consequently, the genus has undergone continuous expansion and contraction over the recent past due to addition and removal of taxa. Dendrosenecio, an endemic genus in Africa, is one of its segregate genera. To heighten the understanding of species divergence and phylogeny within the tribe, the complete chloroplast genomes of the first five Senecio and six Dendrosenecio species were sequenced and analyzed in this study.ResultsThe entire length of the complete chloroplast genomes was?~?150 kb and?~?151 kb in Dendrosenecio and Senecio respectively. Characterization of the 11 chloroplast genomes revealed a significant degree of similarity particularly in their organization, gene content, repetitive sequence composition and patterns of codon usage. The chloroplast genomes encoded an equal number of unique genes out of which 80 were protein-coding genes, 30 transfer ribonucleic acid, and four ribosomal ribonucleic acid genes. Based on comparative sequence analyses, the level of divergence was lower in Dendrosenecio. A total of 331 and 340 microsatellites were detected in Senecio and Dendrosenecio, respectively. Out of which, 25 and five chloroplast microsatellites (cpSSR) were identified as potentially valuable molecular markers. Also, through whole chloroplast genome comparisons and DNA polymorphism tests, ten divergent hotspots were identified. Potential primers were designed creating genomic tools to further molecular studies within the tribe. Intergeneric relationships within the tribe were firmly resolved using genome-scale dataset in partitioned and unpartitioned schemes. Two main clades, corresponding to two subtribes within the Senecioneae, were formed with the genus Ligularia forming a single clade while the other had Dendrosenecio, Pericallis, Senecio and Jacobaea. A sister relationship was revealed between Dendrosenecio and Pericallis whereas Senecio, and Jacobaea were closely placed in a different clade.ConclusionBesides emphasizing on the potential of chloroplast genome data in resolving intergeneric relationships within Senecioneae, this study provides genomic resources to facilitate species identification and phylogenetic reconstructions within the respective genera.

Project description:Recent estimates suggest that the global insect fauna includes fewer than six million species, but this projection is very uncertain because taxonomic work has been limited on some highly diverse groups. Validation of current estimates minimally requires the investigation of all lineages that are diverse enough to have a substantial impact on the final species count. This study represents a first step in this direction; it employs DNA barcoding to evaluate patterns of species richness in 27 orders of Canadian insects. The analysis of over one million specimens revealed species counts congruent with earlier results for most orders. However, Diptera and Hymenoptera were unexpectedly diverse, representing two-thirds of the 46 937 barcode index numbers (=species) detected. Correspondence checks between known species and barcoded taxa showed that sampling was incomplete, a result confirmed by extrapolations from the barcode results which suggest the occurrence of at least 94 000 species of insects in Canada, a near doubling from the prior estimate of 54 000 species. One dipteran family, the Cecidomyiidae, was extraordinarily diverse with an estimated 16 000 species, a 10-fold increase from its predicted diversity. If Canada possesses about 1% of the global fauna, as it does for known taxa, the results of this study suggest the presence of 10 million insect species with about 1.8 million of these taxa in the Cecidomyiidae. If so, the global species count for this fly family may exceed the combined total for all 142 beetle families. If extended to more geographical regions and to all hyperdiverse groups, DNA barcoding can rapidly resolve the current uncertainty surrounding a species count for the animal kingdom. A newly detailed understanding of species diversity may illuminate processes important in speciation, as suggested by the discovery that the most diverse insect lineages in Canada employ an unusual mode of reproduction, haplodiploidy.This article is part of the themed issue 'From DNA barcodes to biomes'.

Project description:BackgroundSpecific fragments, coming from short portions of DNA (e.g., mitochondrial, nuclear, and plastid sequences), have been defined as DNA Barcode and can be used as markers for organisms of the main life kingdoms. Species classification with DNA Barcode sequences has been proven effective on different organisms. Indeed, specific gene regions have been identified as Barcode: COI in animals, rbcL and matK in plants, and ITS in fungi. The classification problem assigns an unknown specimen to a known species by analyzing its Barcode. This task has to be supported with reliable methods and algorithms.MethodsIn this work the efficacy of supervised machine learning methods to classify species with DNA Barcode sequences is shown. The Weka software suite, which includes a collection of supervised classification methods, is adopted to address the task of DNA Barcode analysis. Classifier families are tested on synthetic and empirical datasets belonging to the animal, fungus, and plant kingdoms. In particular, the function-based method Support Vector Machines (SVM), the rule-based RIPPER, the decision tree C4.5, and the Naïve Bayes method are considered. Additionally, the classification results are compared with respect to ad-hoc and well-established DNA Barcode classification methods.ResultsA software that converts the DNA Barcode FASTA sequences to the Weka format is released, to adapt different input formats and to allow the execution of the classification procedure. The analysis of results on synthetic and real datasets shows that SVM and Naïve Bayes outperform on average the other considered classifiers, although they do not provide a human interpretable classification model. Rule-based methods have slightly inferior classification performances, but deliver the species specific positions and nucleotide assignments. On synthetic data the supervised machine learning methods obtain superior classification performances with respect to the traditional DNA Barcode classification methods. On empirical data their classification performances are at a comparable level to the other methods.ConclusionsThe classification analysis shows that supervised machine learning methods are promising candidates for handling with success the DNA Barcoding species classification problem, obtaining excellent performances. To conclude, a powerful tool to perform species identification is now available to the DNA Barcoding community.

Dataset Information

Evaluating the feasibility of using candidate DNA barcodes in discriminating species of the large Asteraceae family.

Background

Results

Conclusions

Publications

Evaluating the feasibility of using candidate DNA barcodes in discriminating species of the large Asteraceae family.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets