The genome sequence of a long-legged fly, Scellus notatus (Fabricius, 1781)
Steven Falk, Liam M. Crowley, James McCulloch, Ruth Y. Akinmusola, Henrique Antoniolli, Komal Kumar Raja

TL;DR
This paper provides the genome sequence of the long-legged fly Scellus notatus, including a detailed assembly of its chromosomes and mitochondrial DNA.
Contribution
The novel contribution is the first genome assembly for Scellus notatus, including chromosomal pseudomolecules and mitochondrial genome.
Findings
The genome assembly is 446.83 megabases long, with 99.72% scaffolded into 5 chromosomal pseudomolecules.
The mitochondrial genome is assembled and is 17.7 kilobases in length.
Abstract
We present a genome assembly from a female Scellus notatus (long-legged fly; Arthropoda; Insecta; Diptera; Dolichopodidae). The genome sequence has a total length of 446.83 megabases. Most of the assembly (99.72%) is scaffolded into 5 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 17.7 kilobases in length.
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5| Project information | |||
|---|---|---|---|
|
| Scellus notatus | ||
|
| PRJEB74677 | ||
|
|
| ||
|
| SAMEA113425476 | ||
|
| 2998547 | ||
| Specimen information | |||
|
|
|
|
|
|
| idSceNota2 | SAMEA113425575 | whole organism |
|
| idSceNota1 | SAMEA112233188 | whole organism |
| Sequencing information | |||
|
|
|
|
|
|
| ERR12893015 | 6.39e+08 | 96.48 |
|
| ERR12875208 | 2.69e+06 | 25.19 |
| Genome assembly | ||
|---|---|---|
| Assembly name | idSceNota2.1 | |
| Assembly accession | GCA_964204855.1 | |
|
|
| |
| Assembly level for primary assembly | chromosome | |
| Span (Mb) | 446.83 | |
| Number of contigs | 163 | |
| Number of scaffolds | 83 | |
| Longest scaffold (Mb) | 123.42 | |
| Assembly metrics | Measure |
|
| Contig N50 length | 10.24 Mb |
|
| Scaffold N50 length | 121.74 Mb |
|
| Consensus quality (QV) | Primary: 63.6; alternate:
|
|
|
| Primary: 78.24%; alternate:
|
|
| BUSCO
| C:92.5%[S:91.5%,D:0.9%],
|
|
| Percentage of assembly mapped to
| 99.19% |
|
| Sex chromosomes | Not identified |
|
| Organelles | Mitochondrial genome:
|
|
| INSDC accession | Name | Length (Mb) | GC% |
|---|---|---|---|
| 1 | 123.42 | 26.5 | |
| 2 | 121.74 | 26.5 | |
| 3 | 105.4 | 25 | |
| 4 | 35.78 | 28 | |
| 5 | 56.84 | 25.5 | |
| MT | 0.02 | 20.5 |
| Software tool | Version | Source |
|---|---|---|
| BEDTools | 2.30.0 |
|
| BLAST | 2.14.0 |
|
| BlobToolKit | 4.3.9 |
|
| BUSCO | 5.5.0 |
|
| bwa-mem2 | 2.2.1 |
|
| Cooler | 0.8.11 |
|
| DIAMOND | 2.1.8 |
|
| fasta_windows | 0.2.4 |
|
| FastK | 427104ea91c78c3b8b8b49f1a7d6bbeaa869ba1c |
|
| Gfastats | 1.3.6 |
|
| GoaT CLI | 0.2.5 |
|
| Hifiasm | 0.19.8-r603 |
|
| HiGlass | 44086069ee7d4d3f6f3f0012569789ec138f42b84a
|
|
| MerquryFK | d00d98157618f4e8d1a9190026b19b471055b22e |
|
| Minimap2 | 2.24-r1122 |
|
| MitoHiFi | 3 |
|
| MultiQC | 1.14, 1.17, and 1.18 |
|
| NCBI Datasets | 15.12.0 |
|
| Nextflow | 23.10.0 |
|
| PretextView | 0.2.5 |
|
| samtools | 1.19.2 |
|
| sanger-tol/ascc | - |
|
| sanger-tol/blobtoolkit | 0.5.1 |
|
| Seqtk | 1.3 |
|
| Singularity | 3.9.0 |
|
| TreeVal | 1.2.0 |
|
| YaHS | 1.2a.2 |
|
- —Wellcome Trust
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsDiptera species taxonomy and behavior · Forensic Entomology and Diptera Studies · Orthoptera Research and Taxonomy
Species taxonomy
Eukaryota; Opisthokonta; Metazoa; Eumetazoa; Bilateria; Protostomia; Ecdysozoa; Panarthropoda; Arthropoda; Mandibulata; Pancrustacea; Hexapoda; Insecta; Dicondylia; Pterygota; Neoptera; Endopterygota; Diptera; Brachycera; Muscomorpha; Eremoneura; Empidoidea; Dolichopodidae; Hydrophorinae; Scellus; Scellus notatus (Fabricius, 1781) (NCBI:txid2998547)
Background
Scellus notatus (Fabricius, 1781) belongs to the Dolichopodidae family of long-legged flies. The members of this family are generally predators and are associated with moist habitats such as littoral and coastal habitats, freshwater seepages, waterfall areas and humid vegetation ( Kechev, 2012; Vilks, 2007). Some Dolichopodids are predominantly in drier areas, such as cultivated areas and grasslands ( Harterreiten-Souza et al., 2020). The ecological requirements of these flies make them vulnerable to environmental fluctuations, significantly impacting their population density ( Pollet, 1992, Pollet, 2001; Pollet et al., 1989; Pollet & Grootaert, 1991).
S. notatus possesses dark-tinted wings and a distinct dark spot towards the tip. The larva predates on smaller invertebrates, while the adults prefer other insects. They thrive well in grasslands and woodlands in lowlands and moderately high altitudes ( Kechev et al., 2022). The species has been recorded in Europe, with the highest occurrence in the Netherlands and the United Kingdom ( GBIF Secretariat, 2024). It is mainly found in England and Wales, and the peak adult activity is in summer ( NBN Atlas Partnership, 2024).
The Scellus notatus reference genome presented here is a component of the Darwin Tree of Life Project, a collaborative effort to sequence all named eukaryotic species in the Atlantic Archipelago of Britain and Ireland. This chromosomally complete genome sequence will facilitate future studies on the evolution and comparative genomics of Dolichopodid flies.
Genome sequence report
Sequencing data
The genome of a specimen of Scellus notatus ( Figure 1) was sequenced using Pacific Biosciences single-molecule HiFi long reads, generating 25.19 Gb from 2.69 million reads. GenomeScope analysis of the PacBio HiFi data estimated the haploid genome size at 415.51 Mb, with a heterozygosity of 1.20% and repeat content of 35.98%. These values provide an initial assessment of genome complexity and the challenges anticipated during assembly. Based on this estimated genome size, the sequencing data provided approximately 59.0x coverage of the genome. Chromosome conformation Hi-C sequencing produced 96.48 Gb from 638.92 million reads. Table 1 summarises the specimen and sequencing information.
Photograph of the Scellus notatus (idSceNota2) specimen used for genome sequencing.
Table 1.: Specimen and sequencing data for Scellus notatus.
Assembly statistics
The primary haplotype was assembled, and contigs corresponding to an alternate haplotype were also deposited in INSDC databases. The assembly was improved by manual curation, which corrected 51 misjoins or missing joins and removed four haplotypic duplications. These interventions decreased the scaffold count by 6.67% and the scaffold N50 by 1.14%. The final assembly has a total length of 446.83 Mb in 83 scaffolds, with 80 gaps, and a scaffold N50 of 121.74 Mb ( Table 2).
Table 2.: Genome assembly data for Scellus notatus.
The snail plot in Figure 2 provides a summary of the assembly statistics, indicating the distribution of scaffold lengths and other assembly metrics. Figure 3 shows the distribution of scaffolds by GC proportion and coverage. Figure 4 presents a cumulative assembly plot, with separate curves representing different scaffold subsets assigned to various phyla, illustrating the completeness of the assembly.
Genome assembly of Scellus notatus, idSceNota2.1: metrics.The BlobToolKit snail plot provides an overview of assembly metrics and BUSCO gene completeness. The circumference represents the length of the whole genome sequence, and the main plot is divided into 1,000 bins around the circumference. The outermost blue tracks display the distribution of GC, AT, and N percentages across the bins. Scaffolds are arranged clockwise from longest to shortest and are depicted in dark grey. The longest scaffold is indicated by the red arc, and the deeper orange and pale orange arcs represent the N50 and N90 lengths. A light grey spiral at the centre shows the cumulative scaffold count on a logarithmic scale. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the diptera_odb10 set is shown at the top right. An interactive version of this figure is available at https://blobtoolkit.genomehubs.org/view/GCA_964204855.1/dataset/GCA_964204855.1/snail.
Genome assembly of Scellus notatus, idSceNota2.1: BlobToolKit GC-coverage plot.Blob plot showing sequence coverage (vertical axis) and GC content (horizontal axis). The circles represent scaffolds, with the size proportional to scaffold length and the colour representing phylum membership. The histograms along the axes display the total length of sequences distributed across different levels of coverage and GC content. An interactive version of this figure is available at https://blobtoolkit.genomehubs.org/view/GCA_964204855.1/blob.
Genome assembly of Scellus notatus, idSceNota2.1: BlobToolKit cumulative sequence plot.The grey line shows cumulative length for all scaffolds. Coloured lines show cumulative lengths of scaffolds assigned to each phylum using the buscogenes taxrule. An interactive version of this figure is available at https://blobtoolkit.genomehubs.org/view/GCA_964204855.1/dataset/GCA_964204855.1/cumulative.
Most of the assembly sequence (99.19%) was assigned to 5 chromosomal-level scaffolds. These chromosome-level scaffolds, confirmed by Hi-C data, are named according to size ( Figure 5; Table 3). The specimen is homogametic, and thus female. We did not identify the sex chromosome(s) as sequence data from the heterogametic sex was not available and homology is unreliable for sex chromosome identification in Diptera due to frequent sex chromosome turnover ( Vicoso & Bachtrog, 2015).
Genome assembly of Scellus notatus: Hi-C contact map of the idSceNota2.1 assembly, visualised using HiGlass.Chromosomes are shown in order of size from left to right and top to bottom. An interactive version of this figure may be viewed at https://genome-note-higlass.tol.sanger.ac.uk/l/?d=Xh8l4ug7TjGtcsICsS7wFw.
Table 3.: Chromosomal pseudomolecules in the genome assembly of Scellus notatus, idSceNota2.
The mitochondrial genome was also assembled. This sequence is included as a contig in the multifasta file of the genome submission and as a standalone record in GenBank.
Assembly quality metrics
The estimated Quality Value (QV) and k-mer completeness metrics, along with BUSCO completeness scores, were calculated for each haplotype and the combined assembly. The QV reflects the base-level accuracy of the assembly, while k-mer completeness indicates the proportion of expected k-mers identified in the assembly. BUSCO scores provide a measure of completeness based on benchmarking universal single-copy orthologues.
The primary haplotype has a QV of 63.6, and the combined primary and alternate assemblies achieve an estimated QV of 62.8. The k-mer completeness for the primary haplotype is 78.24%, and for the alternate haplotype it is 77.91%, while the combined primary and alternate assemblies achieve a k-mer completeness of 99.00%. BUSCO analysis using the diptera_odb10 reference set ( n = 3,285) indicated a completeness score of 92.5% (single = 91.5%, duplicated = 0.9%).
Table 2 provides assembly metric benchmarks adapted from Rhie et al. (2021) and the Earth BioGenome Project (EBP) Report on Assembly Standards September 2024. The assembly achieves the EBP reference standard of 7.C.Q63.
Methods
Sample acquisition and DNA barcoding
An adult female Scellus notatus (specimen ID Ox002861, ToLID idSceNota2) was collected from Wytham Woods, Oxfordshire, United Kingdom (latitude 51.77, longitude –1.33) on 2022-07-14. The specimen was collected by Steven Falk (independent researcher) and Liam Crowley (University of Oxford), identified by Steven Falk and preserved on dry ice.
The specimen used for Hi-C sequencing (specimen ID Ox002500, ToLID idSceNota1) was collected from the same location on 2022-07-20. The specimen was collected by James McCulloch and Liam Crowley (University of Oxford), identified by James McCulloch and preserved on dry ice.
The initial identification was verified by an additional DNA barcoding process according to the framework developed by Twyford et al. (2024). A small sample was dissected from each specimen and stored in ethanol, while the remaining parts were shipped on dry ice to the Wellcome Sanger Institute (WSI) ( Pereira et al., 2022). The tissue was lysed, the COI marker region was amplified by PCR, and amplicons were sequenced and compared to the BOLD database, confirming the species identification ( Crowley et al., 2023). Following whole genome sequence generation, the relevant DNA barcode region was also used alongside the initial barcoding data for sample tracking at the WSI ( Twyford et al., 2024). The standard operating procedures for Darwin Tree of Life barcoding have been deposited on protocols.io ( Beasley et al., 2023).
Metadata collection for samples adhered to the Darwin Tree of Life project standards described by Lawniczak et al. (2022).
Nucleic acid extraction
The workflow for high molecular weight (HMW) DNA extraction at the Wellcome Sanger Institute (WSI) Tree of Life Core Laboratory includes a sequence of procedures: sample preparation and homogenisation, DNA extraction, fragmentation and purification. Detailed protocols are available on protocols.io ( Denton et al., 2023b). The idSceNota2 sample was prepared for DNA extraction by weighing and dissecting it on dry ice ( Jay et al., 2023). Tissue from the whole organism was homogenised using a PowerMasher II tissue disruptor ( Denton et al., 2023a).
HMW DNA was extracted in the WSI Scientific Operations core using the Automated MagAttract v2 protocol ( Oatley et al., 2023). The DNA was sheared into an average fragment size of 12–20 kb in a Megaruptor 3 system ( Bates et al., 2023). Sheared DNA was purified by solid-phase reversible immobilisation, using AMPure PB beads to eliminate shorter fragments and concentrate the DNA ( Strickland et al., 2023). The concentration of the sheared and purified DNA was assessed using a Nanodrop spectrophotometer and Qubit Fluorometer using the Qubit dsDNA High Sensitivity Assay kit. Fragment size distribution was evaluated by running the sample on the FemtoPulse system.
Hi-C sample preparation
Tissue from the whole organism of the idSceNota1 sample was processed for Hi-C sequencing at the WSI Scientific Operations core, using the Arima-HiC v2 kit. In brief, 20–50 mg of frozen tissue (stored at –80 °C) was fixed, and the DNA crosslinked using a TC buffer with 22% formaldehyde concentration. After crosslinking, the tissue was homogenised using the Diagnocine Power Masher-II and BioMasher-II tubes and pestles. Following the Arima-HiC v2 kit manufacturer's instructions, crosslinked DNA was digested using a restriction enzyme master mix. The 5’-overhangs were filled in and labelled with biotinylated nucleotides and proximally ligated. An overnight incubation was carried out for enzymes to digest remaining proteins and for crosslinks to reverse. A clean up was performed with SPRIselect beads prior to library preparation. Additionally, the biotinylation percentage was estimated using the Qubit Fluorometer v4.0 (Thermo Fisher Scientific) and Qubit HS Assay Kit and Arima-HiC v2 QC beads.
Library preparation and sequencing
Library preparation and sequencing were performed at the WSI Scientific Operations core.
** PacBio HiFi **
At a minimum, samples were required to have an average fragment size exceeding 8 kb and a total mass over 400 ng to proceed to the low input SMRTbell Prep Kit 3.0 protocol (Pacific Biosciences, California, USA), depending on genome size and sequencing depth required. Libraries were prepared using the SMRTbell Prep Kit 3.0 (Pacific Biosciences, California, USA) as per the manufacturer's instructions. The kit includes the reagents required for end repair/A-tailing, adapter ligation, post-ligation SMRTbell bead cleanup, and nuclease treatment. Following the manufacturer’s instructions, size selection and clean up was carried out using diluted AMPure PB beads (Pacific Biosciences, California, USA). DNA concentration was quantified using the Qubit Fluorometer v4.0 (Thermo Fisher Scientific) with Qubit 1X dsDNA HS assay kit and the final library fragment size analysis was carried out using the Agilent Femto Pulse Automated Pulsed Field CE Instrument (Agilent Technologies) and gDNA 55kb BAC analysis kit.
Samples were sequenced on a Revio instrument (Pacific Biosciences, California, USA). Prepared libraries were normalised to 2 nM, and 15 μL was used for making complexes. Primers were annealed and polymerases were hybridised to create circularised complexes according to manufacturer’s instructions. The complexes were purified with the 1.2X clean up with SMRTbell beads. The purified complexes were then diluted to the Revio loading concentration (in the range 200–300 pM), and spiked with a Revio sequencing internal control. Samples were sequenced on Revio 25M SMRT cells (Pacific Biosciences, California, USA). The SMRT link software, a PacBio web-based end-to-end workflow manager, was used to set-up and monitor the run, as well as perform primary and secondary analysis of the data upon completion.
** Hi-C **
For Hi-C library preparation, DNA was fragmented using the Covaris E220 sonicator (Covaris) and size selected using SPRISelect beads to 400 to 600 bp. The DNA was then enriched using the Arima-HiC v2 kit Enrichment beads. Using the NEBNext Ultra II DNA Library Prep Kit (New England Biolabs) for end repair, a-tailing, and adapter ligation. This uses a custom protocol which resembles the standard NEBNext Ultra II DNA Library Prep protocol but where library preparation occurs while DNA is bound to the Enrichment beads. For library amplification, 10 to 16 PCR cycles were required, determined by the sample biotinylation percentage. The Hi-C sequencing was performed using paired-end sequencing with a read length of 150 bp on an Illumina NovaSeq 6000 instrument.
Genome assembly, curation and evaluation
** Assembly **
Prior to assembly of the PacBio HiFi reads, a database of k-mer counts ( k = 31) was generated from the filtered reads using FastK. GenomeScope2 ( Ranallo-Benavidez et al., 2020) was used to analyse the k-mer frequency distributions, providing estimates of genome size, heterozygosity, and repeat content.
The HiFi reads were first assembled using Hifiasm ( Cheng et al., 2021) with the --primary option. Haplotypic duplications were identified and removed using purge_dups ( Guan et al., 2020). The Hi-C reads were mapped to the primary contigs using bwa-mem2 ( Vasimuddin et al., 2019). The contigs were further scaffolded using the provided Hi-C data ( Rao et al., 2014) in YaHS ( Zhou et al., 2023) using the --break option for handling potential misassemblies. The scaffolded assemblies were evaluated using Gfastats ( Formenti et al., 2022), BUSCO ( Manni et al., 2021) and MERQURY.FK ( Rhie et al., 2020).
The mitochondrial genome was assembled using MitoHiFi ( Uliano-Silva et al., 2023), which runs MitoFinder ( Allio et al., 2020) and uses these annotations to select the final mitochondrial contig and to ensure the general quality of the sequence.
** Assembly curation **
The assembly was decontaminated using the Assembly Screen for Cobionts and Contaminants (ASCC) pipeline (article in preparation). Flat files and maps used in curation were generated in TreeVal ( Pointon et al., 2023). Manual curation was primarily conducted using PretextView ( Harry, 2022), with additional insights provided by JBrowse2 ( Diesh et al., 2023) and HiGlass ( Kerpedjiev et al., 2018). Scaffolds were visually inspected and corrected as described by Howe et al. (2021). Any identified contamination, missed joins, and mis-joins were corrected, and duplicate sequences were tagged and removed. The curation process is documented at https://gitlab.com/wtsi-grit/rapid-curation (article in preparation).
** Assembly quality assessment **
The Merqury.FK tool ( Rhie et al., 2020), run in a Singularity container ( Kurtzer et al., 2017), was used to evaluate k-mer completeness and assembly quality for the primary and alternate haplotypes using the k-mer databases ( k = 31) that were computed prior to genome assembly. The analysis outputs included assembly QV scores and completeness statistics.
A Hi-C contact map was produced for the final version of the assembly. The Hi-C reads were aligned using bwa-mem2 ( Vasimuddin et al., 2019) and the alignment files were combined using SAMtools ( Danecek et al., 2021). The Hi-C alignments were converted into a contact map using BEDTools ( Quinlan & Hall, 2010) and the Cooler tool suite ( Abdennur & Mirny, 2020). The contact map is visualised in HiGlass ( Kerpedjiev et al., 2018).
The blobtoolkit pipeline is a Nextflow port of the previous Snakemake Blobtoolkit pipeline ( Challis et al., 2020). It aligns the PacBio reads in SAMtools and minimap2 ( Li, 2018) and generates coverage tracks for regions of fixed size. In parallel, it queries the GoaT database ( Challis et al., 2023) to identify all matching BUSCO lineages to run BUSCO ( Manni et al., 2021). For the three domain-level BUSCO lineages, the pipeline aligns the BUSCO genes to the UniProt Reference Proteomes database ( Bateman et al., 2023) with DIAMOND blastp ( Buchfink et al., 2021). The genome is also divided into chunks according to the density of the BUSCO genes from the closest taxonomic lineage, and each chunk is aligned to the UniProt Reference Proteomes database using DIAMOND blastx. Genome sequences without a hit are chunked using seqtk and aligned to the NT database with blastn ( Altschul et al., 1990). The blobtools suite combines all these outputs into a blobdir for visualisation.
The blobtoolkit pipeline was developed using nf-core tooling ( Ewels et al., 2020) and MultiQC ( Ewels et al., 2016), relying on the Conda package manager, the Bioconda initiative ( Grüning et al., 2018), the Biocontainers infrastructure ( da Veiga Leprevost et al., 2017), as well as the Docker ( Merkel, 2014) and Singularity ( Kurtzer et al., 2017) containerisation solutions.
Table 4 contains a list of relevant software tool versions and sources.
Wellcome Sanger Institute – Legal and Governance
The materials that have contributed to this genome note have been supplied by a Darwin Tree of Life Partner. The submission of materials by a Darwin Tree of Life Partner is subject to the ‘Darwin Tree of Life Project Sampling Code of Practice’, which can be found in full on the Darwin Tree of Life website here. By agreeing with and signing up to the Sampling Code of Practice, the Darwin Tree of Life Partner agrees they will meet the legal and ethical requirements and standards set out within this document in respect of all samples acquired for, and supplied to, the Darwin Tree of Life Project.
Further, the Wellcome Sanger Institute employs a process whereby due diligence is carried out proportionate to the nature of the materials themselves, and the circumstances under which they have been/are to be collected and provided for use. The purpose of this is to address and mitigate any potential legal and/or ethical implications of receipt and use of the materials as part of the research project, and to ensure that in doing so we align with best practice wherever possible. The overarching areas of consideration are:
• Ethical review of provenance and sourcing of the material
• Legality of collection, transfer and use (national and international)
Each transfer of samples is further undertaken according to a Research Collaboration Agreement or Material Transfer Agreement entered into by the Darwin Tree of Life Partner, Genome Research Limited (operating as the Wellcome Sanger Institute), and in some circumstances other Darwin Tree of Life collaborators.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1Abdennur N Mirny LA : Cooler: scalable storage for Hi-C data and other genomically labeled arrays. Bioinformatics. 2020;36(1):311–316. 10.1093/bioinformatics/btz 540 31290943 PMC 8205516 · doi ↗ · pubmed ↗
- 2Allio R Schomaker-Bastos A Romiguier J : Mito Finder: efficient automated large-scale extraction of mitogenomic data in target enrichment phylogenomics. Mol Ecol Resour. 2020;20(4):892–905. 10.1111/1755-0998.13160 32243090 PMC 7497042 · doi ↗ · pubmed ↗
- 3Altschul SF Gish W Miller W : Basic local alignment search tool. J Mol Biol. 1990;215(3):403–410. 10.1016/S 0022-2836(05)80360-2 2231712 · doi ↗ · pubmed ↗
- 4Bateman A Martin MJ Orchard S : Uni Prot: the universal protein knowledgebase in 2023. Nucleic Acids Res. 2023;51(D 1):D 523–D 531. 10.1093/nar/gkac 1052 36408920 PMC 9825514 · doi ↗ · pubmed ↗
- 5Bates A Clayton-Lucey I Howard C : Sanger Tree of Life HMW DNA fragmentation: diagenode Megaruptor ®3 for LI Pac Bio. protocols.io. 2023. 10.17504/protocols.io.81wgbxzq 3lpk/v 1 · doi ↗
- 6Beasley J Uhl R Forrest LL : DNA barcoding SO Ps for the Darwin Tree of Life project. protocols.io. 2023; [Accessed 25 June 2024]. 10.17504/protocols.io.261ged 91jv 47/v 1 · doi ↗
- 7Buchfink B Reuter K Drost HG : Sensitive protein alignments at Tree-of-Life scale using DIAMOND. Nat Methods. 2021;18(4):366–368. 10.1038/s 41592-021-01101-x 33828273 PMC 8026399 · doi ↗ · pubmed ↗
- 8Challis R Kumar S Sotero-Caio C : Genomes on a Tree (Goa T): a versatile, scalable search engine for genomic and sequencing project metadata across the eukaryotic Tree of Life [version 1; peer review: 2 approved]. Wellcome Open Res. 2023;8:24. 10.12688/wellcomeopenres.18658.1 36864925 PMC 9971660 · doi ↗ · pubmed ↗
