Background & Summary

Genetic data repositories are a key research component across scientific disciplines that rely on genetic sequences correctly assigned to a reference taxonomy. Although mistaken identity and composition of sequences within those repositories have long been acknowledged1,2,3,4,5, broad-scale data-quality evaluations remain scarce6,7,8 and rarely translate into improved databases. Therefore, the uncertainty of genetic data in global platforms such as GenBank3,9,10 represents a paramount obstacle for robust downstream analyses. Critically, quality-screening efforts can resolve misidentification of known, cryptic and undescribed taxa8,11, and inform the definition of reliable taxonomical units for management and biodiversity research12,13.

The widespread sequencing of, and access to, mitochondrial DNA (mtDNA) has boosted taxonomic studies via integrative taxonomy, barcoding, bioprospection, phylogenetics, phylogeography, population and conservation genetics, biogeography, macroecology, and paleoecology14,15,16. Available mtDNA data outcompetes nuclear DNA data in taxonomic coverage across the ‘Tree of Life’ mainly due to the popularity of 16 S, cytochrome-b (Cytb) and cytochrome oxidase 1 (Cox1) loci, while multiple sequences per species of those loci have proved crucial to define species limits17,18,19. While Cox1 was proposed as a universal barcode genetic marker20, GenBank’s Cytb records are currently more abundant than Cox1 for all five major vertebrate groups (Table 1).

Table 1 GenBank records for Cytochrome-b (Cytb) and Cytochrome oxidase subunit I (Cox1) for the main five vertebrate groups.

Amphibians have the highest rate of newly discovered vertebrate species21 given intense taxonomic efforts11. These ectotherms are however the most threatened vertebrates on Earth22,23, with many species facing extinction owing to emerging and spreading diseases24,25, habitat loss26 and climate change27. Therefore, accurate phylogenetic identification11,28,29 remains critical for future research and conservation actions. Here, we present the Amphibia’s Curated Database of Cytochrome-b sequences (ACDC30,, a comprehensive and curated database of all amphibian Cytb sequences available in GenBank. We targeted Cytb because it is the most common genetic marker, with the broadest genus- and species-level taxonomic coverage, in the amphibian literature31,32.

We created ACDC30 following a multi-step process implemented in a bioinformatic pipeline combining data retrieval from GenBank, local sequence alignments and quantification of genetic divergences (Fig. 1). On 01 February 2018, we retrieved a total of 39,202 Cytb sequences. Following curation (see Methods), ACDC contains 36,514 unique sequences representing 398 genera and 2,309 species (median = 2 species/genus with 50% interquartile ranges of [1,7]). For 1,363 species and 74 of the 75 amphibian families, there is more than one sequence available (Summary_statistics_ACDC.xlsx30) (median = 7 [3,22] species/family). ACDC represents 29% of the 7,963 currently known amphibian species covering most clades33. Despite the taxonomic accuracy of GenBank records seems to be accurate above the genus level34, our work demonstrates that the problematic issues mostly occur at the species level, and case-by-case assessments of taxonomic identity are necessary.

Fig. 1
figure 1

Workflow to collate and curate The Amphibia’s Curated Database of Cytochrome-b sequences (ACDC).

We identified 2,359 conflictive sequences (6% of the collated dataset) from 1,603 Anura, 743 Caudata, and 13 Gymnophiona records. These sequences suffered from wrong taxonomic assignments (>80%), contamination, introgression/hybridization, and submission/ sequencing errors (Fig. 2, Erroneous_sequences.xlsx30) and, as such, they qualify to be tagged as ‘UNVERIFIED’35 in GenBank. We updated the taxonomic identity of ca. 4,800 GenBank records (Taxonomic_corrections.xlsx30), and reverse-complemented reads from >1,000 sequences incorrectly uploaded as backward reads. We provide summary tables listing species/sequences with an uncertain taxonomic assignment (sp./ssp./cf./aff.; Uncertain_taxonomy_to_be_assessed.xlsx30) and potentially belonging to species complexes (Species_notes.xlsx30). These results suggest that several amphibian groups are in need of taxonomic revision. Lastly, we address general recommendations to improve data quality in public genetic repositories (Table 2) and append an R script30 to apply our data-curation protocol to other taxa and loci.

Fig. 2
figure 2

Frequency of error categories in amphibian Cytochrome-b sequences identified from GenBank sequences (01/02/2018). Those errors affect 6% (n = 2,359) of the sequences retrieved. Sequences identified due to incomplete lineage sorting are lumped in ‘Hybridization/Introgression’. Category definitions are explained in Erroneous_sequences.xlsx30.

Table 2 Recommendations to improve the quality of (meta)data reported in GenBank.

Ideally, the research community would benefit from future sequencing efforts giving full taxonomic coverage to a selected sample of loci, which could in turn improve our understanding of amphibian biodiversity, evolution, ecology or conservation. mtDNA markers are still the best candidates to implement those efforts, as they are easy to amplify (even in poorly preserved samples), align and curate36. Taxonomic coverage of mtDNA can also be widened as a by-product of full-transcriptome and -genome assemblage, including long-read Next Generation Sequencing. In that respect, the development, integration, and expansion of quality-curated databases like ACDC should promote the generation of novel genomic data covering multiple specimens per species across the amphibian tree of life.



Within the R environment37, on 01/02/2018, we used a key-word string to select and download all amphibian Cytb sequences from the GenBank’s website (, National Centre for Biotechnology Information) – see Steps 1–3 in the ACDCv1.0.R script30. We eliminated duplicates using GenBank labels ‘NC’, adjusted the nomenclature of each sequence to conform a genus_species_accession format (e.g., Bufo_bufo_AB123456), and exported all sequences as a single *.fasta file (Step 430). This includes single Cytb sequences, as well as mitochondrial genomes that contain this locus. All these sequences were then mapped against a reference mitochondrial genome (Xenopus tropicalis, AY789013), using the ‘high sensitivity’ option in Geneious® v11.038, and we extracted Cytb nucleotidic sequences (Fig. 1). Then, the nomenclature of all unique taxonomic identities was compared, confirmed and, if applicable, updated (Step 530) against the Amphibian Species of the World Database33.

We exported all mapped Cytb sequences in a *.fasta file from Geneious to the R environment. Therein, we performed ClustalW39 multiple sequence alignments for each species separately using the R package Bioconductor (Step 630). The resulting intraspecific alignments were imported back to Geneious as *.fasta files for batch-alignment through the MUSCLE algorithm (Fig. 1). The former step was mandatory because batch-MUSCLE alignments of multiple sequences (muscle function40 in Bioconductor) does not reorder sequences based on genetic similarity (A.T. Kalinka, pers. comm., 06/08/2018). Within Geneious, we visually resolved nucleotide gaps using the Vertebrate Mitochondrial Code41, and removed sequence ends with ambiguous nucleotides.

Taxonomic assessment and curation

We quantified accuracy on the assignation of sequences to species based on the genetic divergence (%) among sequences within species and genera and the identification of divergence outliers. We implemented three steps to detect sequencing and taxonomic errors based on pairwise-sequence alignments within each genus (Step 7; see Technical Validation). We used ‘uncorrected divergence’ as the genetic distance between every pair of sequences, using the seqinr package42. Firstly, we accepted sequences showing ≤3% divergence within multiple alignments across all sequences of the same species, and subset those with >3% divergence for further examination. Secondly, we also accepted sequences showing >3% divergence within a genus and subset those with ≤3% divergence for further examination. We caution that 3% is a reliable (conservative) divergence threshold for amphibian Cytb43,44,45,46 but should be re-estimated for other loci and taxonomical groups. Thirdly, for all potentially erroneous sequences, we assessed taxonomic and geographical veracity against (I) the data-source publication cited in GenBank, (II) the most recent papers dealing the taxon involved, (III) AmphibiaWeb ( and (IV) the Amphibian Species of the World Database33 (Fig. 1). References and rationale used to separate erroneous from non-erroneous sequences are given for each sequence (Erroneous_sequences.xlsx30). We removed all erroneous sequences from ACDC and compiled all Amphibia Cytb sequences with uncertain taxonomy (aff./cf./sp./ssp.) (Uncertain_taxonomy_to_be_assessed.xlsx30). Lastly, the curation of genetic data is dependent on the number of available sequences per species and the taxonomic coverage per genus. Therefore, we included summary data for the ACDC database (Summary_statistics_ACDC.xlsx30) to flag species in need of more data and taxonomic resolution in online genetic repositories.

Lastly, our R script includes a routine to assess the Cytb region that maximizes species coverage and number of sequences (Supplementary Files 1 and 2). To do so, we first mapped all ACDC sequences to the Cytb of X. tropicalis (AY789013) using the ‘highest sensitivity’ option in Geneious, then counted non-missing bases for each position (Step 830).

Data Records

The curated database, all files as well as the associated R script are freely available on figshare30. The database consists of two compressed batches of *.fasta files of species with (I) 1 sequence ( and (II) > 1 sequences (

Technical Validation

We implemented a three-step sequence of filters to assess Cytb-sequence quality. (I) We retained sequences with complete binominal nomenclature. (II) We mapped all sequences against the Xenopus tropicalis mitochondrial genome (AY789013) and reverse-complemented sequences incorrectly submitted in backward-read format (>1,000). (III) We visually scanned sequence alignments for sequencing errors, whereby non-amino acid gaps (≠3) were filled or replaced by ‘N’ in the absence or presence of diversity at the base in question, respectively.