MIDORI2: A collection of quality controlled, preformatted, and regularly updated reference databases for taxonomic assignment of eukaryotic mitochondrial sequences

Abstract

Analysis of environmental DNA is increasingly used to characterize ecological communities, but the effectiveness of this approach depends on the accuracy of taxonomic reference databases. The MIDORI databases, first released in 2017, were built to improve accuracy for mitochondrial metazoan (animal) sequences. MIDORI has now been significantly improved and renamed MIDORI2 (available at http://www.reference-midori.info). Like MIDORI, MIDORI2 is built from GenBank and contains curated sequences of thirteen protein‐coding and two ribosomal RNA mitochondrial genes. Coverage has been substantially expanded to cover all eukaryotes, including fungi, green algae and land plants, other multicellular algal groups, and diverse protist lineages. MIDORI2 also now includes not only species with full binomials, but also taxa referred to by genus with species left unspecified (“sp.”). Another new feature is the updating of the databases approximately every two months with version numbers corresponding to each new GenBank release. Additional potentially erroneously annotated sequences have also been removed. Finally, the ability to export data files to BLAST+ has been added to the original ability to export preformatted data to five taxonomic assignment programs, and databases of amino acid sequences are also made available for protein‐coding genes. As a technical validation, we conducted a preliminary comparison of the performance of MIDORI2 with five taxonomic assignment programs. Results suggest that BLAST+ top hits performed better for assigning CO1 sequences than alignment‐free methods based on compositional features. Comparing MIDORI2 with two other commonly used curated databases of mitochondrial sequences, CO‐ARBitrator and BOLD, we show that MIDORI2 includes sequences from a broader range of metazoan and non‐metazoan taxa. Overall, in many contexts, MIDORI2 offers clear advantages: a higher diversity of taxa than other databases, a variety of user‐friendly features, and regular updates. MIDORI2 is particularly well‐suited for environmental DNA studies that target mitochondrial genes with broad primers.

crabs—A software program to generate curated reference databases for metabarcoding sequencing data

“…Comparative studies have revealed that, irrespective of the taxonomic assignment method used, comprehensive, curated and wellannotated reference databases are critical for accurate taxonomic assignment (Gold et al, 2021;Hleap et al, 2021;Leray et al, 2022).…”

“…Comparative studies have revealed that, irrespective of the taxonomic assignment method used, comprehensive, curated and well‐annotated reference databases are critical for accurate taxonomic assignment (Gold et al, 2021; Hleap et al, 2021; Leray et al, 2022). The early adoption of metabarcoding in microbial research, as well as a focus on the 16 S rRNA gene for bacterial species identification (Johnson et al, 2019), have led to the creation of curated reference databases used to assign taxonomy in the majority of microbiome studies, such as rdp (Wang et al, 2007).…”

Metatranscriptomics reveals higher species compositional homogeneity in smaller size coral reef zooplankton

“…The assembled contigs were assigned to one of the thirteen mitochondrial proteins, either small or large mitochondrial rRNA. For the gene assignment, BLAST+ (Camacho et al 2009) in conjunction with MIDORI Leray et al, 2022) and SILVA (Quast et al 2013) references were performed. SILVA was included as a reference to count nuclear rRNA sequence contaminations, although no nuclear rRNA sequences were detected in our libraries.…”

An automated workflow to assess completeness and curate GenBank for eDNA metabarcoding: the marine fish assemblage as case study

“…Others rely on filtered versions of GenBank containing only the target barcode of the sequences from the species of interest. This filtering can be done either using the reference description (Iwasaki, Fukunaga et al 2013; Machida, Leray et al 2017; Arranz, Pearman et al 2020; Gold, Curd et al 2021; Mariani, Fernandez et al 2021; Russo, Maiello et al 2021; Barco, Kullmann et al 2022) or based on similarity searches (Heller, Casaletto et al 2018; Leray, Knowlton et al 2022). Yet, although the use of these filtered versions is popular in marine fish eDNA metabarcoding studies (Nguyen, Shen et al 2020; Kawato, Yoshida et al 2021; Kume, Lavergne et al 2021; Oka, Doi et al 2021; Polanco F, Richards et al 2021), the methods used to extract the sequences are not meant to remove potential contaminations other than those identifiable through their labeling (e.g.…”