Baeza and García‑De León BMC Genomics (2022) 23:320
https://doi.org/10.1186/s12864-022-08482-z
RESEARCH ARTICLE
Are we there yet? Benchmarking lowcoverage
nanopore long-read sequencing
for the assembling of mitochondrial genomes
using the vulnerable silky shark Carcharhinus
falciformis
J. Antonio Baeza1,2,3*
 and F. J. García‑De León4
 
Abstract 
Background:  Whole mitochondrial genomes are quickly becoming markers of choice for the exploration of withinspecies
genealogical and among-species phylogenetic relationships. Most often,‘primer walking’or‘long PCR’
strategies plus Sanger sequencing or low-pass whole genome sequencing using Illumina short reads are used for
the assembling of mitochondrial chromosomes. In this study, we first confirmed that mitochondrial genomes can
be sequenced from long reads using nanopore sequencing data exclusively. Next, we examined the accuracy of the
long-reads assembled mitochondrial chromosomes when comparing them to a‘gold’standard reference mitochon‑
drial chromosome assembled using Illumina short-reads sequencing.
Results:  Using a specialized bioinformatics tool, we first produced a short-reads mitochondrial genome assembly
for the silky shark C. falciformis with an average base coverage of 9.8x. The complete mitochondrial genome of C.
falciformis was 16,705 bp in length and 934 bp shorter than a previously assembled genome (17,639 bp in length)
that used bioinformatics tools not specialized for the assembly of mitochondrial chromosomes. Next, low-pass whole
genome sequencing using a MinION ONT pocket-sized platform plus customized de-novo and reference-based work‑
flows assembled and circularized a highly accurate mitochondrial genome in the silky shark Carcharhinus falciformis.
Indels at the flanks of homopolymer regions explained most of the dissimilarities observed between the‘gold’stand‑
ard reference mitochondrial genome (assembled using Illumina short reads) and each of the long-reads mitochon‑
drial genome assemblies. Although not completely accurate, mitophylogenomics and barcoding analyses (using
entire mitogenomes and the D-Loop/Control Region, respectively) suggest that long-reads assembled mitochondrial
genomes are reliable for identifying a sequenced individual, such as C. falciformis, and separating the same individual
from others belonging to closely related congeneric species.
Conclusions:  This study confirms that mitochondrial genomes can be sequenced from long-reads nanopore
sequencing data exclusively. With further development, nanopore technology can be used to quickly test in situ
mislabeling in the shark fin fishing industry and thus, improve surveillance protocols, law enforcement, and the
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Open Access
*Correspondence: jbaezam@clemson.edu
1
Department of Biological Sciences, 132 Long Hall, Clemson University,
Clemson, SC 29634, USA
Full list of author information is available at the end of the article
Page 2 of 18Baeza and García‑De León BMC Genomics (2022) 23:320
Background
Entire or partially complete mitochondrial genomes are
quickly becoming markers of choice for examining phylogenetic
relationships [1–10]. The appeal for using entire
(or partially complete) mitochondrial genomes has to do
with its nearly neutral fashion of molecular evolution as
well as its mutation rate that is high compared to that of
most nuclear markers [1, 11], (but see [12]). Furthermore,
extraction, purification, and sequencing of mitochondrial
DNA is straightforward. The mitochondrial genome also
behaves as a single non-recombining locus because mitochondrial
inheritance is maternal-only (clonal) (but see
[2, 13]).
The customary approach for sequencing and assembling
partial or entire mitochondrial genomes has historically
relied on ‘long PCR’ or ‘primer walking’ and
cloning plus Sanger sequencing [14]. Most recently, however,
2nd generation sequencing technologies (i.e., Illumina
short reads) have been used to assemble complete
mitochondrial genomes using low-pass (=low-coverage)
whole genome sequencing (WGS) [6]. The aforementioned
strategy almost invariably results in the assembly
of complete and fully accurate mitochondrial genomes.
Nonetheless, the main problem with the use of short
reads for assembling mitochondrial genomes is that it is
time demanding; from gDNA extraction to mitochondrial
genome assembly, studies can take weeks, months,
or even years [4–10]. Mitochondrial genome sequencing
approaches that rely solely on Illumina short reads
are not the optimal solution for studies that demand
the speedy recovery of molecular markers, including
complete mitochondrial genomes. Such studies include,
among others, the in-situ detection of mislabeling in the
supply chain (either legal or illegal) of biological commodities
[15] and the real-time genomic surveillance of
disease agents [16].
The use of 3rd generation sequencing technology (e.g.,
long reads from Oxford Nanopore Technologies [ONT]
or Pacific Biosciences [PacBio] platforms) represents an
alternative to short-read sequencing for assembling complete
mitochondrial genomes. Currently, third generation
sequencing technology yields molecules as long as mitochondrial
genomes (i.e., ~ 10–20 kbp and up to 1–2 Mbp
– 17). However, the initial sequence error rate of 3rd generation
sequencing technology is high (PacBio = 11–15%;
ONT = 5–15% - 20, 21) and much greater than Illumina
sequencing (0.3% - 18, 19). In-silico read ‘polishing’ algorithms
have been developed to correct for the high initial
error rate of long reads (i.e., nanopore – [17] and
references therein). Assembling complete and accurate
mitochondrial genomes using 3rd generation sequencing
exclusively should be straightforward because they are
short, circular, non-repetitive, haploid genomes.
Currently, only three studies have employed nanopore
long reads exclusively for the de novo assembly of complete
mitochondrial genomes: in the cosmopolitan silky
shark Carcharhinus falciformis [18], in the neotropical
rodent Melanomys caliginosus [19], and in the Caribbean
spiny lobster Panulirus argus [20]. Other studies have
used both short- and long-reads datasets concomitantly
for the ‘hybrid assembly’ of mitochondrial genomes [21,
22], (see also [23–26]). Importantly, among the studies
assembling mitochondrial genomes with long reads
exclusively, only the spiny lobster study benchmarked
the long-reads assembled mitochondrial genome with a
short-reads mitochondrial genome assembly generated
from the same individual; the comparison revealed that
long reads can assemble complete and highly accurate,
but not perfect, mitochondrial genomes [20]. The Carcharhinus
falciformis study did not successfully benchmark
the long-reads mitochondrial assembly, but in the
M. caliginosus study it was benchmarked using two short
protein coding gene fragments [19]. Benchmarking of
long-reads assemblies with full reference genomes is of
paramount significance given the high initial error rate
of 3rd generation sequencing technologies. This information
will assist with the optimization of bioinformatics
workflows for the de novo assembly of mitochondrial
genomes.
In this study, we are interested in benchmarking longreads
assembled mitochondrial genomes, and confirming
the utility of 3rd generation sequencing technologies
for the rapid sequencing and assembling of relatively
short (i.e., mitochondrial) genomes. For this purpose,
we used the silky shark Carcharhinus falciformis as a
model system, a large and highly migratory shark with
a circumglobal distribution in tropical and subtropical
oceanic and coastal-pelagic waters [27, 28]. Carcharhinus
falciformis is one of the most commonly fished
sharks worldwide and is targeted by both regional and
regulation of this fishery. This study will also assist with the transferring of high-throughput sequencing technology
to middle- and low-income countries so that international scientists can explore population genomics in sharks using
inclusive research strategies. Lastly, we recommend assembling mitochondrial genomes using specialized assemblers
instead of other assemblers developed for bacterial and/or nuclear genomes.
Keywords:  Long-read sequencing, Nanopore, Elasmobranch
Page 3 of 18Baeza and García‑De León BMC Genomics (2022) 23:320	
international fisheries [29]. It also comprises a large portion
of the bycatch in fisheries targeting tunas (Thunnus
spp.) around the world [29–32]. Fishing pressure appears
to have resulted in steady silky shark population declines
therefore, the species has been classified globally as vulnerable
since 2017 by the International Union for Conservation
of Nature [33]. The silky shark was also added
to Appendix II of the Convention on International Trade
in Endangered Species the same year [33].
Despite its vulnerable status, only a few (but increasing)
number of genomic resources exist for this species [18,
34–37]. The mitochondrial genome of C. falciformis was
assembled using short-reads by Galván-Tirado et al. [34].
An unusual insertion ~ 939 bp in length was detected in
this short-reads assembled mitochondrial genome after
comparison to other congeneric sharks, whose mitochondrial
genomes are usually ~ 16,700 bp in length. The
bioinformatics pipeline used in [34] was not specifically
developed for assembling mitochondrial genomes, thus,
the odd insertion could be a bioinformatics artifact. Most
recently, Johri et  al. [18, 35] used nanopore long reads
exclusively to assemble the mitochondrial genome of this
species and did not find a long insertion. The length of
the long-reads mitochondrial assembly was similar to
that of other mitochondrial genomes in Carcharhinus
spp. The authors claimed that the long-reads assembly
was highly accurate. However, no benchmarking of this
assembly was conducted and the authors provided no
information about the algorithm used for final assembly
curation [18, 35].
To accomplish the aims of this study, we first attempted
to assemble a high-quality, gold-standard mitochondrial
genome for C. falciformis using Illumina short reads and
a specialized bioinformatics pipeline exclusively developed
for the retrieval of entire mitochondrial genomes.
We used the same dataset from Galván-Tirado et al. [34]
to determine if the unusually long insertion observed in
the first assembly by these authors was a by-product of
using a bioinformatics pipeline not customized for the
assembly of mitochondrial genomes. Second, we de novo
assembled the mitochondrial genome of C. falciformis
using long reads exclusively and benchmarked the accuracy
of these long-reads assembled genomes by comparing
them to the ‘gold’ standard mitochondrial genome
assembled using short-reads (Illumina) sequencing data.
To achieve this second goal, we used the same dataset
from Johri et al. [18, 35] but employed different de novo
and reference-based bioinformatics pipelines specifically
developed for the rapid retrieval of mitochondrial
genomes using long reads exclusively [20], (see also [38]).
The sequence accuracy of the long-reads assemblies was
explored with multiple metrics; completeness, identity,
and coverage, as in [20]. A detailed quantitative analysis
of error type in long-reads assemblies was conducted.
Finally, we explored whether or not de novo and reference-based
long-reads mitochondrial genome assemblies
are useful for mitophylogenomics and barcoding
research.
Results
Assembly of the mitochondrial genome using short reads
The software GetOrganelle [39] assembled and circularized
the mitochondrial genome of the silky shark C. falciformis
with an average base coverage of 9.8x (Fig. 1). The
complete mitochondrial genome of C. falciformis was
16,705 bp in length (OM885432) and 934 bp shorter than
the previously assembled genome, 17,639 bp in length
(KF801102), which used SOAP de novo [34].
Annotation in MITOS2 [40] and MitoFish [41] indicated
that the mitochondrial genome of C. falciformis
encoded 22 transfer RNA (tRNA) genes, 2 ribosomal
RNA genes (rrnS [12S ribosomal RNA] and rrnL [16S
ribosomal RNA]), and 3 protein-coding genes (PCGs). All
but one PCG (nad6) and 14 tRNA genes were encoded
on the H-strand (Fig. 1). The two ribosomal RNA genes
were also encoded in the H-strand. The D-loop/Control
Region was assumed to be a relatively long inter-genic
space, 1065 bp long, in the mitochondrial genome of C.
falciformis. Mitochondrial synteny observed in C. falciformis
is identical to that reported before in the genus
Carcharhinus ([34] and references therein).
Assembly of the mitochondrial genome using long reads
The mitochondrial genome of C. falciformis was assembled
and circularized by all used bioinformatics pipelines:
Unicycler [42], Flye [43], and Rebaler [44], and with or
without ‘extra’ polishing with the software Medaka (see
[45]). Assembled contigs by each of the pipelines above
identified as circular with the program Bandage [46]
matched the mitochondrial genome of C. falciformis and
other congeneric species available in NCBI’s GenBank
after blasts against the nucleotide non-redundant database
(all e-values << ­1e− 10
).
All long-reads assemblies, either de novo (i.e., Unicycler
and Flye) or reference-based (i.e., Rebaler), before
extra polishing using the software Medaka, varied in
length between 16,690 bp (Flye with 1 polishing cycle)
and 16,801 bp (Unicycler Normal, Bold, and Conservative).
Interestingly, the long-reads mitochondrial
genomes assembled with Flye were shorter than the reference
genome assembled with short reads. However, the
mitochondrial genomes assembled with Unicycler and
Rebaler were longer than the reference genome (Table 1).
Furthermore, all mitochondrial genomes extra-polished
with Medaka were shorter than the same assemblies
Page 4 of 18Baeza and García‑De León BMC Genomics (2022) 23:320
before extra-polishing using Medaka was applied to them
(Table 1).
Alignment of the different long-reads assemblies
to the reference genome and subsequent p-distance
estimation revealed that long-reads assemblies were
either identical (i.e., Unicycler Normal = Unicycler
Conservative = Unicycler Bold; Unicycler Normal +
Medaka = Unicycler Conserative + Medaka = Unicycler
Bold + Medaka; Flye with 5 polish rounds = Flye with 10
polish rounds; Flye with 1 polish round + Medaka = Flye
with 5 polish rounds + Medaka = Flye with 10 polish
rounds + Medaka) or very similar to each other with
p-distances that ranged between 1.203732 × ­10− 4
and
1.6250376 × ­10− 3
when dissimilar.
Identity, estimated as p-distance between the shortreads
assembly versus a specific long-reads assembly,
Fig. 1  Circularized mitochondrial genome ideogram of the silky shark Carcharhinus falciformis. The map is annotated and depicts a single
putative control region, 22 transfer RNA (tRNA) genes, 2 ribosomal RNA genes (rrnS [12S ribosomal RNA] and rrnL [16S ribosomal RNA]), and 13
protein-coding genes (PCGs). Shark photograph: Joi Ito (Attribution 2.0 Generic [CC BY 2.0])
Page 5 of 18Baeza and García‑De León BMC Genomics (2022) 23:320	
was also very high; all long-reads assemblies were not
identical but a close match to the reference shortreads
mitochondrial genome with p-distances ranging
between 3.611195 × ­10− 4
(reference compared to Rebaler
using C. amboinensis as a reference + Medaka) and
1.3241047 × ­10− 3
(reference compared to Rebaler using
C. amblyrhynchos as a reference) (Table 1).
Error estimation in long‑read assembled mitochondrial
genomes in the silky shark
Discordance between the reference assembly and each
of the long-reads assemblies was mostly due to indels
at the flanks of homopolymer regions comprised of all
four nucleotide types (Fig.  2). By far, the most common
errors identified in all long-reads assemblies were
single nucleotide homopolymer insertions (range = 18
errors in the Flye + 1 polish assembly to 60 errors in
all three Unicycler assemblies polished with Medaka;
aggregate number of errors in all assemblies ­[nT] = 716)
followed by single nucleotide homopolymer deletions
­(nT = 240) and double nucleotide homopolymer
insertions ­(nT = 177). Errors due to single substitutions
­(nT = 105), single deletions ­(nT = 69), and single
insertions ­(nT = 65), were moderately abundant.
Triple, quadruple, quintuple, sextuple, and septuplet
nucleotide homopolymer insertions were much less
common (Fig. 2). Similarly, short oligonucleotide deletions
and double homopolymer deletions were not
common. We did not observe errors due to triple,
quadruple, quintuple, sextuple, and septuplet nucleotide
homopolymer deletions in any of the long-read
assemblies (Fig. 2).
The effect of extra-polishing long-reads assemblies
with the program Medaka was not homogenous across
assembly pipelines. For instance, a decrease in the
number of errors (mostly single nucleotide homopolymer
deletions and double nucleotide homopolymer
insertions) after Medaka extra-polishing was evident
for mitochondrial genomes assembled with the de
novo assembly pipeline Unicycler (all three strategies)
and the reference-based assembly pipeline Rebaler (all
three strategies) (Fig.  2). However, for mitochondrial
genomes assembled with the de novo assembly pipeline
Flye, the total number of errors increased slightly when
Medaka extra-polishing was applied to them. In the
Flye assemblies (all strategies), Medaka extra-polishing
decreased the number of errors due to single nucleotide
homopolymer deletions but disproportionally
increased the number of single nucleotides homopolymer
insertions, explaining the slight increase in overall
Table 1  Accuracy metrics for different de novo and reference-based mitochondrial genome assemblies using nanopore long reads
exclusively in the silky shark Carcharhinus falciformis 
a
Unicycler normalizes the depth of contigs to the median value
b
Error refers to total number of errors quantified in the long-read assemblies compared to the short read assembly. Errors were classified as single, double, triple,
quadruple, quintuple, sextuple, or septuple“homopolymer insertions’or‘homopolymer deletions’,‘simple substitution’,‘single insertion’,‘short insertion (< 5 bp)’,‘single
deletion’, and‘short deletion (< 5 pb)’
Assembly Pipeline Contigs Length Coverage p-dist Errorsb
Flye +1p circular 16,690 20x 0.001023172 65
Flye +1p + Medaka circular 16,475 20x 0.000541679 70
Flye +5p circular 16,691 20x 0.001023172 69
Flye +5p + Medaka circular 16,475 20x 0.000541679 71
Flye +10p circular 16,691 20x 0.001023172 69
Flye +10p + Medaka circular 16,475 20x 0.000541679 71
Unicycler - N circular 16,801 2.28xa
0.001143545 110
Unicycler - N + Medaka circular 16,781 2.28xa
0.000601866 89
Unicycler - B circular 16,801 2.28xa
0.001143545 110
Unicycler - B + Medaka circular 16,781 2.28xa
0.000601866 89
Unicycler - C circular 16,801 2.28xa
0.001143545 110
Unicycler - C + Medaka circular 16,781 2.28xa
0.000601866 89
Rebaler - P. amblyrhynchos circular 15,782 50.59x 0.001324105 106
Rebaler - P. ambly. + Medaka circular 16,774 50.59x 0.000541679 81
Rebaler - P. amboinensis circular 15,790 49.94x 0.000902799 95
Rebaler - P. ambo. + Medaka circular 16,776 49.94x 0.000361119 73
Rebaler - P. falciformis circular 16,789 52.52x 0.000842612 96
Rebaler - P. falci. + Medaka circular 16,777 52.52x 0.000541679 81
Reference mtDNA circular 16,705 9.8x – –
Page 6 of 18Baeza and García‑De León BMC Genomics (2022) 23:320
Fig. 2  Sequence errors per de novo (Unicycler and Flye) and reference-based assemblers (Rebaler) without and with‘extra polishing’using the
program Medaka for the silky shark Carcharhinus falciformis mitochondrial genome. Benchmarking of all long-read assemblies occurred against the
Illumina short-read assembly (‘gold’standard)
Page 7 of 18Baeza and García‑De León BMC Genomics (2022) 23:320	
assembly error observed in these Medaka extra-polished
Flye assemblies. In general, extra-polishing with
Medaka resulted in increased accuracy for mitochondrial
genomes assembled with the pipelines Rebaler
and Unicycler but not with the program Flye.
Overall, accuracy of the long-reads assemblies was similar
when assessed in terms of completeness (circularization),
coverage, length, identity, and sequence errors.
Additionally, long-reads genome accuracy was very high
(but not perfect; < 100%) when compared to the shortreads
assembled mitochondrial genome herein used as a
gold standard (Fig. 2; Table 1).
Annotation of mitochondrial genomes assembled
with long reads
Annotation of the de novo and reference-based longreads
assembled mitochondrial genomes, with or without
extra-polishing with Medaka, demonstrated that synteny
and gene number were either identical or very similar to
that of the reference genome (Fig.  3). In all long-reads
assemblies, 9 to 12 PCGs had at least one internal, but
often more, stop codon that disrupted their open reading
frames. In several of the long-reads assemblies
(n = 11), the relatively short PCG atp8 was not detected
by the in-silico annotation tools. However, manual curation
demonstrated that this short gene was present in all
the assemblies but disrupted due to the occurrence of
stop codons (Fig. 3). Overall, even though all long-reads
assemblies were highly accurate, the errors contained in
each long-reads assembled mitochondrial genome precluded
generating a reliable annotation with MITOS2
and MitoFish (Fig. 3).
Mitophylogenomics using long‑read mitochondrial
genome assemblies
In the phylogenetic tree resulting from the ML analysis
(49 terminals, 14,245 nucleotide characters, 3396 parsimony
informative sites), the short-reads assembled
reference genome plus all of the long-reads assembled
mitochondrial genomes (n = 18) clustered together into
a single, fully supported monophyletic clade (bootstrap
value [bv] = 100) (Fig. 4). Interestingly, the phylogenetic
Fig. 3  Annotation of reference-based (Rebaler) and de novo (Fyer and Unicycler) mitochondrial genomes assembled using long reads in the silky
shark Carcharhinus falciformis. Assemblies depicted include those with and without‘extra polishing’with the program Medaka
Page 8 of 18Baeza and García‑De León BMC Genomics (2022) 23:320
Fig. 4  Mitophylogenomic analysis of the genus Carcharhinus and allies, including mitochondrial genomes of the silky shark Carcharhinus falciformis
assembled with long reads exclusively and short reads (‘gold standard’). Nodes with bootstrap support values > 90 are marked with an orange circle.
Shark photograph: Joi Ito (Attribution 2.0 Generic [CC BY 2.0])
Page 9 of 18Baeza and García‑De León BMC Genomics (2022) 23:320	
analysis did not confirm the monophyletic status of the
genus Carcharhinus. The blue shark Prionace glauca
and the whitetip reef shark Triaenodon obesus clustered
together in the same fully supported clade containing all
the representatives belonging to the genus Carcharhinus.
Specifically, the tree placed P. glauca in a position
sister to C. falciformis (short-reads reference + all longreads
assemblies) while T. obesus comprised a moderately
supported (bv = 86) monophyletic clade with C.
amboinensis, C. acronotus, C. brachyurus, C. brevipinna,
and C. leucas (Fig.  4). Support values did not decrease
towards the root of the phylogenetic tree. The above suggests
that mitochondrial genomes alone will likely have
enough phylogenetic information to reveal relationships
at higher taxonomic levels within the family Carcharhinidae,
including the genus Carcharhinus and other closely
related genera (i.e., Glyphis, Laminopsis, Sphyrna).
Barcoding using long‑reads assemblies
In the barcoding analysis based on the Control Region,
the aligned molecular data matrix was comprised of 1188
characters, of which 570 were parsimony informative. A
total of 476 terminals belonged to sharks in the genus
Carcharhinus, other related confamilial species (Prionace
glauca [n = 1] and Triaenodon obesus [n = 1]), outgroup
terminals from the genera Glyphis (n = 5 terminals) and
Sphyrna (n = 4), plus Galeocerdo cuvier (n = 5) and Loxodon
macrorhynus (n = 1) (Fig. 5). In the ML molecular
phylogenetic tree (Fig. 5), the Control Region fragment
retrieved from the short-reads assembled reference
genome plus the totality (n = 18) of the long-reads assembled
mitochondrial genomes and 15 other sequences
belonging to C. falciformis retrieved from Genbank clustered
together into a fully supported (bv = 100) monophyletic
clade (Fig.  5). Other fully or well supported
Fig. 5  Barcoding analysis of the genus Carcharhinus using the D-Loop/Control Region (CR), including the CR retrieved from mitochondrial
genomes of the silky shark Carcharhinus falciformis mitochondrial genome assembled with long reads alone and short reads (‘gold standard’) plus
447 other specimens belonging to the genus Carcharhinus retrieved from Genbank. Shark drawings from M. Dando (used with permission) [47]
Page 10 of 18Baeza and García‑De León BMC Genomics (2022) 23:320
clades in the analysis included the dusky shark C. obscurus,
the spot-tail shark C. sorrah, the sandbar shark C.
plumbeus, the pig-eye or java shark C. amboinensis, the
black-nose shark C. acronotus, the fine-tooth shark C.
isodon, and the small-tail shark C. porosus. Interestingly,
specimens of the blacktip shark C. limbatus, the Australian
blacktip shark C. tilstoni, and the Queensland or
graceful shark C. amblyrhynchoides clustered together
into a single, fully supported monophyletic clade and
specimens did not segregate according to species within
this clade. Similarly, specimens of the silvertip shark C.
albimarginatus and the bull shark C. leucas clustered
together into a single but moderately supported (bv = 62)
clade. The aforementioned suggests either errors in the
identification of sharks prior to sequencing, ancient
introgression, or recent interbreeding among specimens/
species in each clade.
In contrast to that observed in the mitophylogenomic
analysis, nodes towards the root of the tree were poorly
supported. This is expected because short fragments of
the Control Region should not have any phylogenetic
information to resolve deep phylogenetic relationships in
Carcharhinus and related genera.
In summary, although not entirely accurate (= ‘imperfect’),
mitochondrial genomes assembled using long
reads reliably identified the studied (and sequenced) individual
of C. falciformis and differentiated the same individual
from other closely and distantly related congeneric
sharks.
Discussion
We have successfully assembled a complete and high
quality (gold-standard) mitochondrial genome for C.
falciformis using Illumina short reads and a specialized
bioinformatics pipeline exclusively developed for the
retrieval of short chromosomes, including entire mitochondrial
genomes (see [20]). Importantly, we used the
same dataset from Galván-Tirado et al. [34] to explore if
an odd ~ 939 bp long insertion observed in the original
assembly [34] was a by-product of using a non-specialized
assembly pipeline. Our assembled mitochondrial
genome was 16,705 bp long, 934 bp shorter than the
previously assembled genome by Galvan-Tirado et  al.
[34]. The gene order observed in C. falciformis was
identical to other reports in the genus Carcharhinus
[34] and the length of our assembly was most similar to
that of other congeneric sharks whose mitochondrial
genomes are often ~ 16,700 bp in length ([18, 35], and
references therein). We concluded that the unusually
long mitochondrial genome of Galván-Tirado et al. [34]
was an artifact due to the use of non-specific assembly
tools. We suggest that future studies should assemble
mitochondrial genomes only using specialized assembly
pipelines ([39] and references therein). Overall, the
results from this study tell us that specialized assemblers
like GetOrganelle (among a few others) should be
preferred over non-specialized tools when the goal is to
assemble mitochondrial genomes. Furthermore, we argue
that mitochondrial genomes assembled with non-specialized
bioinformatics workflows that exhibit peculiarities
(i.e., unusual repeats, missing genes, and duplicated
regions) need to be revisited.
The gold standard mitochondrial genome generated
using short-reads Illumina sequencing data permitted us
to benchmark the accuracy of the reference-based and de
novo assembled mitochondrial genomes in C. falciformis
using nanopore long reads exclusively. We used the same
dataset of Johri et al. [35, 36] but employed different de
novo and reference-based bioinformatics pipelines specifically
developed for the rapid retrieval of mitochondrial
genomes using long reads exclusively [20]. All of the
workflows used in this study assembled a circular mitochondrial
chromosome, as indicated after comparison of
each of these long-reads assemblies with the ‘reference’
assembly generated with Illumina short reads. Furthermore,
the accuracy of each long-reads assembled mitochondrial
genome was high. All workflows circularized
the genome with relatively high coverages (20–52.52x)
and sequence (mitochondrial genome) identity, as measured
by p-distance, was very high. Differences in accuracy
among mitochondrial genomes assembled with the
different pipelines used in this study, either de novo or
reference-based, were minimal. These results agree with
previous studies examining the accuracy of assembled
chromosomes from long-reads nanopore sequences
exclusively. For instance, Baeza [20] detected a slight
decrease in accuracy when the mitochondrial genome of
the spiny lobster P. argus was assembled using the program
Rebaler and a distantly related congeneric species.
Similarly, a second recently published study that successfully
assembled chloroplast genomes using (nanopore)
long reads reported decreasing accuracy when the reference
genome was from a distantly related species [48].
Altogether, the information above confirms that nanopore
sequencing data exclusively can be used to assemble
complete and highly accurate (but not perfect, see below)
mitochondrial genomes using both de novo and reference-based
pipelines.
Benchmarking of assemblies using long reads with reference
genomes obtained with Sanger or Illumina short
reads is rarely reported (see [20, 48, 49]). In this study,
we provided a quantitative comparison of error types in
mitochondrial genomes assembled using long reads. By
far, the errors that were most often observed were insertions
in homopolymer runs, in agreement with that
Page 11 of 18Baeza and García‑De León BMC Genomics (2022) 23:320	
observed by the few other studies that have reported a
detailed analysis of error type for small chromosomes
assembled relatively short genomes [i.e., in chloroplast
genomes – [48, 50], in mitochondrial genomes – [20], in
bacterial genomes – [49]]. This type of error (insertions
in homopolymer runs) is common in nanopore sequencing
[49, 50]. We expect that this detailed report on error
type will assist with the optimization of bioinformatics
workflows for the de novo assembly of mitochondrial
genomes using 3rd generation sequencing technologies
exclusively. Importantly, the initial error rate of long-read
nanopore sequencing has steadily diminished during the
last few years [51]. As the authors write this paper, ONT
is testing new chemistry that can produce Q20+ single
pass raw read accuracy. The base-caller software Guppy
is also expected to continue improving in the coming
years (www.​nanop​orete​ch.​com). Further development of
nanopore sequencing technology is likely to result in the
assembly of complete and totally accurate chromosomes
(mitochondrial, plastic, nuclear) in the near future.
Mitophylogenomics and barcoding studies using
long‑reads assembled mitogenomes
We assembled complete and highly accurate mitochondrial
genomes in the silky shark C. falciformis using longreads
nanopore sequencing exclusively with the addition
of different bioinformatics workflows. Although highly
accurate, the assemblies were not perfect. Annotation
of the different long-reads assembled mitochondrial
genomes with the pipelines MITOS2 and MitoFish demonstrated
that the few observed errors resulted in stop
codons that disrupted the ORF of nearly every PCG, in
line with that observed in [20]. In some cases, the errors
resulted in the annotation pipelines missing short PCGs
(i.e., atp8). Importantly, the observed sequence errors
might constrain the reliable identification of a sequenced
specimen such as C. falciformis and might also inhibit the
differentiation of the same specimen from others belonging
to the same genus in a phylogenomic and/or barcoding
analysis. On the other hand, even if not fully accurate,
the assembled mitochondrion or particular genes might
be useful for mitophylogenomics and barcoding studies.
If that was the case, and in line with [20], we predicted
that entire mitochondrial genomes or fragments of them
(i.e., D-Loop/Control Region) assembled with de novo
and reference-based pipelines will cluster together with
the ‘gold-standard’ short-reads assembled mitochondrial
chromosome as well as with other entire or partial (CR)
mitochondrial genomes from the same species available
in GenBank. Furthermore, the complete or partial
mitochondrial genomes will be expected to segregate
from others belonging to closely related species in the
same genus Carcharhinus. Supporting the view that
long-read assembled mitochondrial genomes are suitable
for mitophylogenomics and barcoding research, in a
first mitophylogenomic analysis that used all PCGs, the
short-reads assembled reference genome and all of the
long-reads assembled mitochondrial genomes clustered
together into a single, fully supported monophyletic
clade. Interestingly, the analysis positioned C. falciformis
(reference [short-reads] plus all long-reads assemblies)
as sister to the blue shark Prionace glauca, in line with
that reported by a recent study that used complete mitochondrial
genomes with a smaller number of shark species
([18, 35] and references therein). Additionally, in our
second barcoding analysis that used the D-Loop/Control
Region, the short-reads assembled reference genome
and the totality of the long-reads assembled mitochondrial
genomes with 15 other sequences belonging to C.
falciformis available in Genbank clustered together into
a fully supported monophyletic clade. The C. falciformis
monophyletic clade segregated from other clades, comprised
of 457 sequences belonging to other closely related
(congeneric) species. Altogether, the information above
allows us to conclude that long-reads assembled mitochondrial
genomes, although imperfect, are consistently
able to identify the sequenced individual as belonging to
C. falsiformis and genetically differentiate it from other
closely related species.
Together with other recent studies [20, 48, 49], our
results suggest that nanopore long reads (with further
development) and customized pipelines can be used
to address major conservation and management issues
in marine organisms, including the silky shark C. falciformis,
and likely, other closely and distantly related
species experiencing similar conservation problems. For
instance, nanopore technology (after further improvement
of initial read error) and ancillary bioinformatics
pipelines can be used to quickly test in situ mislabeling in
the shark fin fishing industry and thus, improve surveillance
protocols, law enforcement, and the regulation of
this fishery [52]. Overall, in situ mislabeling in the shark
fin fishing industry is expected to inform and improve
conservation strategies in silky sharks and other species
experiencing major conservation issues [52].
Second, we argue that nanopore long read sequencing
technology has the potential to democratize genomic
research in middle- and low-income countries by
breaking cost-barriers; it can provide relatively cheap
and quick access to high-throughput sequencing technologies
to researchers in those countries. Importantly,
library preparation is relatively rapid and straightforward
for nanopore sequencing, and the sequencing
device itself is inexpensive compared to PacBio, the
only other current long-read sequencing technology
alternative to nanopore [17, 53]. Nanopore sequencing
Page 12 of 18Baeza and García‑De León BMC Genomics (2022) 23:320
can be used for the rapid retrieval of genomic information
(i.e., mitochondrial genomes) in studies surveilling
the shark-fin fishing industry and studies
exploring population genomic structure and connectivity
among close and distant populations in silky sharks.
The understanding of connectivity, demographic history,
source-and-sink metapopulations dynamics, and
genomic diversity, among others, is expected to inform
and improve the implementation and design of marine
protected areas for C. falciformis and other sharks ([18,
52] and references therein). As stated above, these studies
need to be implemented in situ and in collaboration
with local scientists to avoid ‘parachute science’, a pervasive
practice in the USA and Europe [54]. Long-reads
nanopore technology can be used to deliver rapid and
cheap genetic marker retrieval to international teams
of scientists interested in contributing to environmental
problem solutions using inclusive research strategies
[54].
This study differs in several ways from that of Baeza
[20], the only previous study that has benchmarked longreads
assembled mitochondrial genomes generated from
ONT long-read sequences with a short-reads mitochondrial
genome assembly from Illumina short-reads [20].
First, in this study we have used the software Guppy v.
3.3.1 (instead of Albacore used in [20]) to improve basecalling
accuracy. The use of Guppy with updated versions
of the different programs comprising the pipeline used
in this study (compared to the versions used in [20]) was
expected to increase base-calling accuracy, as well as the
accuracy of the final long-reads mitochondrial genome
assemblies. Importantly, we observed a greater number of
total mitochondrial genome assembly errors in this study
(mean [S.D.] = 85.78 ± 15.87, range = 65–110) compared
to that in [20] (mean [S.D.] = 60.5 ± 9.34, range = 51–77).
In other words, even though we have used a more sophisticated
or advanced pipeline, the final mitochondrial
genome assemblies accuracy did not improve but rather
decreased. Furthermore, we observed that the most common
errors in this study were insertions (e.g., mostly
1 pb insertions) at the flanks of homopolymer regions,
while in [20], the most common error were due to deletions
at the flanks of homopolymer regions. We do not
know which conditions explain the observed differences.
Nonetheless, the observed dissimilarities between this
study and that of Baeza [20] argue in favor of conducting
additional research to understand the parameters and
conditions driving the accuracy of assemblies (as well
as type of errors) when relying solely on ONT long read
sequencing. During the preparation of this manuscript,
we are aware that ONT has started to introduce new
cartridges and chemistries that are expected to increase
the accuracy of long read sequencing. Furthermore, the
software Guppy is constantly improving in terms of basecalling
accuracy (Oxford Nanopore Technologies). We
think that in the near future (5–10 years), ONT long-read
sequencing alone will be fully reliable for the assembling
of fully accurate relatively short (mitochondrial, viral),
intermediate (bacteria), and long genomes (nuclear
genomes) in a wide variety of organisms.
Conclusion
Using nanopore long-read sequencing technology and
specialized bioinformatics pipelines, we have assembled
a complete and highly accurate mitochondrial genome
belonging to the silky shark C. falciformis. The silky
shark is an ecologically relevant species in pelagic environments
and is heavily targeted by a profitable fishery
worldwide. The long-reads assembled mitochondrial
genomes were highly accurate, reliably identified the
sequenced individual as belonging to C. falciformis, and
differentiated the same individual from others belonging
to congeneric species. This study will facilitate the
transferring of high throughput genomic technologies
to middle- and low-income countries worldwide, allowing
collaboration and cooperation among international
teams of researchers interested in conducting inclusive
research on the conservation biology of vulnerable and
endangered sharks.
Methods
Sampling of the silky shark Carcharhinus falciformis
One adult individual (already euthanized by fishermen)
was bought from fishermen near Playa Palo de
Santa Rita Sur (24.1414° N, 110.3417° W), La Paz, Baja
California Sur, Mexico. The specimen was transported
to the Laboratorio de Organismos Acuaticos, Instituto
de Ciencias del Mar y Limnologia (ICMyL), Universidad
Autonoma de Mexico (UNAM). Muscle was
extracted from the specimen with forceps, and the
tissue was immediately preserved in 95% ethyl alcohol.
Total genomic DNA (gDNA) was extracted from
muscle tissue using an EZNA Genomic DNA Purification
kit (Omega Bio-Tek, Norcross, GA). The gDNA
sample was then transported to the Georgia Genomics
and Bioinformatics Core, University of Georgia, Athens,
GA, USA, where library preparation and Illumina
paired-end shotgun sequencing were carried out.
Illumina short reads library preparation and sequencing
An Illumina®
library was prepared by shearing ~ 1 μg
of gDNA (using a Covaris instrument) following the
standard protocol of the Illumina Truseq DNA Library
Preparation kit using a multiplex identifier adaptor
Page 13 of 18Baeza and García‑De León BMC Genomics (2022) 23:320	
index (Illumina). Illumina sequencing was conducted
on a MiSeq v2®
platform using a 2 × 500 cycle to produce
250 pb paired-end reads. A total of 478,450 PE
reads was generated by the sequencing facility (available
in the short-read archive [SRA] repository [accession
number SRR18001997]) at GenBank. These reads
were used for the mitochondrial genome assembly of C.
falciformis.
Short‑reads mitochondrial genome assembly of the silky
shark Carcharhinus falciformis
The mitogenome of C. falciformis was de novo assembled
using the pipeline GetOrganelle v1.6.4 [39]. A fragment
of the cox1 PCG available in GeneBank (MK308176) was
used as a reference. A relatively large word (kmer) size
of 39 was used during the assembly. Next, the web servers
MITOS2 (http://​mitos2.​bioinf.​uni-​leipz​ig.​de/​index.​
py) [40] and MitoFish v3.63 (http://​mitof​ish.​aori.u-​tokyo.​
ac.​jp/) [41] were used to annotate the newly assembled
mitochondrial genome with the vertebrate genetic code.
Manual curation of the in silico annotated mitochondrial
genome, including start and stop codon corrections, were
conducted using the Expasy translate tool (https://​web.​
expasy.​org/). Visualization of the mitochondrial genome
was conducted with MitoFish v3.63 [41]. This short-read
assembled mitochondrial genome represents the ‘ground
truth’ or ‘golden standard’ reference (i.e., the trusted reference)
which we used for benchmarking the quality (i.e.,
accuracy) of the reference-based and de novo assembled
genomes using nanopore long reads, exclusively.
Silky shark Carcharhinus falciformis nanopore long reads
dataset
We assembled the mitochondrial genome of C. falciformis
using long reads exclusively and benchmarked the
accuracy of the long-reads assembled genomes by comparing
them to a ‘gold’ standard mitochondrial genome
generated using short-read Illumina sequencing data (see
above) as in [4]. We used the same dataset of Johri et al.
[18, 35] but employed different de novo and a referencebased
bioinformatics pipelines specifically developed for
the rapid retrieval of mitochondrial genomes using long
reads exclusively (see [20] for an example). Details on
specimen collection, gDNA extraction, library preparation,
sequencing in a MinION ONT device, and raw signal
(FAST5 files) base-calling with the software Guppy
v. 3.3.1 (Oxford Nanopore Technologies) can be found
in [18, 35]. A total of 74,536 nanopore long reads were
downloaded from GenBank (SRA accession number
SRX4977038) and used for assembling the mitochondrial
genome of C. falciformis using different de novo and a
reference-based bioinformatics pipelines.
Quality control of long reads
First, we used the software Porechop (https://​github.​
com/​rrwick/​Porec​hop) to trim adapters from the ends
of the reads and to split sequences with internal adapters
into two. Next, we used the program fastp [55] to
quality-filter the reads and retain only those sequences
with Q-score ≥ 6. The aforementioned QC step resulted
in a total of 50,780 ‘clean’ reads that were used for the de
novo and reference-based assembly of the mitochondrial
genome of C. falciformis.
De novo long‑reads mitochondrial genome assembly
of the silky shark Carcharhinus falciformis
We de novo assembled the mitochondrial chromosome
of C. faciformis using the pipelines Unicycler 0.4.8–1 [42]
and Flye 2.8–0 [43] (Fig. 6).
We ran Unicycler as in [20] using three different modes:
normal (the default), bold, and conservative. The bold
mode is the most likely to assemble complete genomes
but conveys the greatest risk of misassembly, while the
conservative mode has a very low risk of misassembly but
it is least likely to produce a complete assembly. Finally,
the normal mode is intermediate with respect to completeness
and misassembly risk (see https://​github.​com/​
rrwick/​Unicy​cler).
Flye polishes a final set of assembled contigs with the
program Flye polisher [42]. By default, a single polishing
iteration is run by Flye. In this study, we ran Flye with 1,
5, and 10 iterations with the goal of improving the final
assembly. We assumed that with increased iterations, a
larger number of errors would be corrected by Flye polish.
After the assembly step, either with Flye or Unicycler,
we used the program Bandage [46] to visualize the
assembly graph produced by the two de novo pipelines
as in [4]. If Flye and/or Unicycler successfully assembled
and circularized the mitochondrial chromosome of C.
falciformis, we predicted that a circular sequence ~ 16
kpb long would be observed among the contigs in the
assembly graph. We blasted any observed circular assembled
contigs from each assembly pipeline to the nucleotide
non-redundant database in NCBI’s GenBank and
calculated the statistical significance of the matches.
Lastly, we used the software Medaka v 1.0.3 (https://​
github.​ com/​nanop​orete​ch/​medaka) [45] to apply a final
‘extra polishing’ employing the model r941_prom_high_
g330 to the different mitochondrial genomes assembled
with the two de novo pipelines above as in [4, 20]. Medaka
uses neural networks to a pileup of individual nanopore
reads against a draft assembly to create a new final consensus
sequence. In this study, the draft assembly corresponds
to the final assembly produced by either Flye or Unicycler
while the new final consensus sequence corresponds to the
extra-polished mitochondrial genome assembly.
Page 14 of 18Baeza and García‑De León BMC Genomics (2022) 23:320
Reference‑based long‑reads mitochondrial genome
assembly of Carcharhinus falciformis
Reference-based assemblies of the C. falciformis mitochondrial
genome were conducted using the pipeline
Rebaler (https://​github.​com/​rrwick/​Rebal​er) [44] (Fig. 6).
We executed Rebaler using three different reference
genomes: C. amboinensis (NC_026696), C. amblyrhyncos
(MT663280) and the short-read mitochondrial
genome of C. falciformis assembled during this study.
Carcharhynus amboinensis is less distantly related to C.
falciformis that C. amblyrhyncos [56]. The choice of different
mitochondrial genomes above allowed us to check
Fig. 6  Bioinformatics pipeline to assemble the mitochondrial chromosome of the silky shark Carcharhinus falciformis using nanopore long reads
exclusively
Page 15 of 18Baeza and García‑De León BMC Genomics (2022) 23:320	
for differences in accuracy of the final assembly due to
genetic differences among reference genomes. Also, we
ran Rebaler with the option ‘circular = true’ indicating
that the reference genome was circular so that Rebaler
‘rotated’ contigs between polishing rounds to ensure
improved accuracy of the final assembled mitochondrial
genome (https://​github.​com/​ rrwick/​Rebal​er). A
final ‘extra-polishing’ step with the software Medaka was
applied to each mitochondrial genome assembled with
Rebaler (https://​github.​com/​nanop​orete​ch/​ medaka)
Evaluation of accuracy in long‑reads mitogenome
assemblies
We evaluated the quality (i.e., accuracy) of each longread
assembled mitochondrial genome (without and
with ‘extra polishing’ using Medaka) using four metrics
as in [4, 20]: number of contigs, assembly length, coverage,
and identity. We implemented p-distance (patristic
distance, uncorrected) as a measure of sequence identity.
Low and high p-values indicate, respectively, low and
high sequence accuracy. Identical short-reads reference
and long-reads assembled mitogenomes are indicated
by a p-distance value equal to zero. To calculate Patristic
distance (p-distance) between each long-reads assembled
mitochondrial genome and the short-reads assembled
reference genome, we aligned mitochondrial genomes
assembled using long reads to the short-reads reference
genome with the program Muscle [57] as implemented in
MEGAX [58].
Lastly, long-reads assembly error was quantified in a
manner similar to that of [4, 20]. After each long-reads
assembly (without and with ‘extra polishing’ using the
program Medaka) was aligned to the reference assembly,
errors were classified as single, double, triple, quadruple,
quintuple, sextuple, or septuple “homopolymer insertions’
or ‘homopolymer deletions’ if the error added or
removed, respectively, a single, two, three, four, five, six,
or seven bases from a homopolymer (i.e. multiple consecutive
appearances of the same nucleotide) regions two
or more bases in length [4]. Other errors that did not fit
with any of the categories mentioned above were classified
as ‘simple substitution’, ‘single insertion’, ‘short insertion
(<5 bp)’, ‘single deletion’, and ‘short deletion (<5 pb)’.
We note that the gold standard short-reads mitochondrial
genome assembly used in this study was retrieved
from a specimen different than that from which ONT
long-reads were obtained. Taking into account that (i)
the rate of molecular evolution (nucleotide substitution)
in mitochondrial genomes belonging to elasmobranchs is
low ([36] and references therein), and (ii) deletion and/
or insertions at the flanks of homopolymer regions represent
the overwhelming majority of errors previously
detected in contigs assembled with ONT long-read
[20], we expect to observe an obvious error-signal when
the different long-reads assemblies and the short-reads
gold standard assembly used in this study are compared,
even if they are retrieved from different conspecific
individuals.
Annotation of mitochondrial genomes assembled using
long reads
We annotated each reference-based and de novo longreads
assembled mitogenome with the online pipelines
MITOS2 [40] and MitoFish [41] using the vertebrate
mitochondrial code. The presence/absence of stop
codons causing truncated PCGs (i.e., with interruptions
in the open reading frame) was recorded. The latter constitutes
an additional proxy for long-read assembly accuracy
estimated in this study.
Phylogenomic and barcoding utility of long‑reads
mitochondrial assemblies
We determined the utility of the long-reads, newly
assembled mitochondrial genomes for phylogenomics
and barcoding research. Following [4, 20], we predicted
that, in both mitophylogenomic and barcoding analyses,
the mitochondrial genomes assembled using long
reads will cluster with the reference short-reads assembly
genome and will segregate from other mitochondrial
genome sequences belonging to closely and distantly
related species (i.e., in the same genus and family) available
in Genbank.
First, to test the phylogenomic utility of long-reads
mitochondrial assemblies, the mitochondrial genomes
(N = 16) belonging to different species in the genus Carcharhinus
were retrieved from GenBank (available as of
05 252,021). Carcharhinus has diversified since the middle
Eocene, about 45 Myr ago [59, 60]. We also retrieved
mitochondrial genomes from the genus Glyphis (n = 5
species), Lamiopsis (n = 2), Sphyrna (n = 4), and Loxodon
(n = 1) that were used as outgroups in the analysis. Lastly,
we retrieved the mitochondrial genomes of the whitetip
reef shark Triaenodon obesus (NC026287) and the blue
shark Prionace glauca (NC022819) considering that
previous studies clustered these two species within the
genus Carcharhinus [56]. Next, all 13 PCGs plus the two
ribosomal RNA genes (12S and 16S) from each long-read
assembled mitochondrial genome of C. falciformis and
the short-read assembled reference genome of C. falciformis
plus the 29 mitogenomes retrieved from Genbank
were aligned using the software Muscle (with default
options) as implemented in the program MEGA X. The
final alignment, comprised of 14,245 bp, was provided to
the web server IQ-TREE 1.6.12 (http://​iqtree.​cibiv.​univie.​
ac.​at/) for Maximum Likelihood (ML) analysis [61]. The
Page 16 of 18Baeza and García‑De León BMC Genomics (2022) 23:320
software ModelFinder [62], as implemented in IQ-TREE,
was used for selecting a base substitution model that best
fits each dataset. The optimal models found by ModelFinder
(selected with the Bayesian Information Criterion)
were the TN + F + G4 for atp6, HKY + F + G4 for
atp8, TIM2 + F + R3 for cox1, TN + F + I + G4 for cox2,
TIM2 + F + I + G4 for cytb, nad1, nad2, nad4, nad5, 12S
rRNA DNA, and 16S rRNA DNA, TIM2 + F + R3 for
cox3, TIM2 + F + G4 for nad3, TN + F + I + G4 for nad4l,
and TIM + F + G4 for nad6. A total of 1000 bootstrap
replications were conducted to estimate support for each
node in the Maximum Likelihood tree [61].
Second, to test the barcoding usefulness of long-reads
mitochondrial assemblies, a total of 457 D-Loop/CR
sequences belonging to the genus Carcharhinus plus 19
other sequences used as outgroup (Galeocerdo spp. = 5
sequences, Glyphis spp. = 5, Lamiopsis spp. = 2, Loxodon
macrorhinus = 1, Prionace glauca = 1, Sphyrna spp.
= 4, Triaenodon obesus = 1) were retrieved from GenBank
(available as of 05 152,021). Next, the software
Clustal Omega [63] as implemented in the web server
EMBO (https://​www.​ebi.​ac.​uk/​Tools/​ msa/​clust​alo/) was
used to align all of the retrieved sequences plus the CR
fragment from all of the long-read and short-read (reference
genome) assemblies using the default parameters.
The final alignment consisted of 1188 bp. Next, the
aligned dataset was exported to the web server IQ-TREE
1.6.12 (http://​iqtree.​cibiv.​univie.​ac.​at/) for Maximum
Likelihood (ML) analysis [61]. Selection of a base substitution
model that best fits each dataset was conducted
with ModelFinder [62] as implemented in IQ-TREE. The
optimal models found by ModelFinder (selected with the
Bayesian Information Criterion) was the TIM + F + R4.
All the parameters used for the ML analyses were those
of the default options in IQ-TREE and 1000 bootstrap
replications were conducted to estimate support for each
node in each Maximum Likelihood tree [61].
We note that the great majority of the complete mitochondrial
genomes and CR fragments deposited in GenBank
are assembled using Sanger sequencing or Illumina
short-reads, (https://​www.​ncbi.​nlm.​nih.​gov/​genba​nk/).
Abbreviations
DNA: Deoxyribonucleic Acid; ONT: Oxford Nanopore Technologies; gDNA:
Genomic DNA; PCG: Protein-coding genes; PCR: Polymerase chain reaction;
RNA: Ribonucleic Acid; tRNA: Transfer RNA; rrnS: 12S ribosomal RNA; rrnL: 16S
ribosomal RNA; WGS: Whole genome sequencing.
Acknowledgments
The author thanks Dr. Vince P. Richards for bioinformatics support during
the development of this project. The abstract of this manuscript has been
published recently on https://​userm​eeting.​jgi.​doe.​gov/​wp-​conte​nt/​uploa​ds/​
sites/2/​2021/​08/​revis​ed_​2021-​JGI-​Annual-​Meeti​ng-​Full-​Abstr​act-​Book.​pdf
and https://​integ​rativ​econs​ervat​ionco​nfere​nce.​weebly.​com/​uploa​ds/1/​3/8/​8/​
13887​1669/​icc_​2022_​abstr​act_​guide_1-​17-​22.​pdf.
Authors’contributions
JAB and FJGL: Conceptualization, Methodology, Analysis, Data curation, Writ‑
ing, Original draft preparation. Visualization, Writing, Reviewing, and Editing.
All authors have read and approved the manuscript.
Funding
This work was partially funded by the‘Programa de Apoyo a Proyectos de
Investigación e Innovación Tecnológica, Universidad Autónoma de México’
(PAPIIT-UNAM), grant IN210711. Also funds were received from‘Secretaría de
Agricultura y Desarrollo Rural (SAGARPA), Gobierno Federal Mexicano’grant
2005–12058 and‘Consejo Nacional de Ciencia y Tecnología’(CONACYT). The
funding bodies played no role in the design of the study and collection, analy‑
sis, and interpretation of data and in writing the manuscript.
Availability of data and materials
All datasets on which the conclusions of the manuscript rely are presented in
the main paper.
Short read sequences are available in the short-read archive (SRA) repository
(Bioproject ID: PRJNA772885; Biosample accession: SAMN25885101; SRA
accession: SRR18001997) at GenBank. Long read sequences are available in
the SRA repository (accession number SRX4977038). Mitochondrial genome
assemblies generated in this study are available in the short-read archive
(SRA) repository (SRA accessions: OM885432 - OM885450). The specimen is
deposited at the‘Laboratorio de Genética de Organismos Acuáticos’. Instituto
de Ciencias del Mar y Limnología, Universidad Nacional Autonoma de Mexico,
Mexico (Curator: Dr. Píndaro Díaz Jaimes).
Declarations
Ethics approval and consent to participate
Experimental work was conducted with a shark specimen bought from local
fishermen.
No permits are needed and extended to users for the collection of vertebrates
from privately-owned fishes according to state and federal laws in Mexico.
Consent for publication
Not applicable.
Competing interests
The author declares no competing interests.
Author details
1
 Department of Biological Sciences, 132 Long Hall, Clemson University, Clemson,
SC 29634, USA. 2
 Smithsonian Marine Station at Fort Pierce, 701 Seaway Drive,
Fort Pierce, Florida 34949, USA. 3
 Departamento de Biología Marina, Facultad
de Ciencias del Mar, Universidad Católica del Norte, Larrondo, 1281 Coquimbo,
Chile. 4
 Laboratorio de Genética para la Conservación, Centro de Investigaciones
Biológicas del Noroeste, S.C., La Paz, Baja California Sur, Mexico.
Received: 27 July 2021 Accepted: 18 March 2022
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