Museomics: Phylogenomics of the Moth Family Epicopeiidae (Lepidoptera) Using Target Enrichment

Abstract

Billions of specimens can be found in natural history museum collections around the world, holding potential molecular secrets to be unveiled. Among them are intriguing specimens of rare families of moths that, while represented in morphology-based works, are only beginning to be included in genomic studies: Pseudobistonidae, Sematuridae, and Epicopeiidae. These three families are part of the superfamily Geometroidea, which has recently been defined based on molecular data. Here we chose to focus on these three moth families to explore the suitability of a genome reduction method, target enrichment (TE), on museum specimens. Through this method, we investigated the phylogenetic relationships of these families of Lepidoptera, in particular the family Epicopeiidae. We successfully sequenced 25 samples, collected between 1892 and 2001. We use 378 nuclear genes to reconstruct a phylogenetic hypothesis from the maximum likelihood analysis of a total of 36 different species, including 19 available transcriptomes. The hypothesis that Sematuridae is the sister group of Epicopeiidae + Pseudobistonidae had strong support. This study thus adds to the growing body of work, demonstrating that museum specimens can successfully contribute to molecular phylogenetic studies.

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Molecular Phylogenetics, Phylogenomics, and Phylogeography
Museomics: Phylogenomics of the Moth Family
Epicopeiidae (Lepidoptera) Using Target Enrichment
ElsaCall,1,5, ChristophMayer,2, VictoriaTwort,1,3, LarsDietz,2, NiklasWahlberg,1, and
MarianneEspeland4,
1Department of Biology, Lund University, 22362 Lund, Sweden, 2Statistical Phylogenetics and Phylogenomics, Zoological Research Museum Alexander
Koenig, 53113 Bonn, Germany, 3University of Helsinki, Finnish Natural History Museum, Luomus, Helsinki, Finland, 4Arthropoda Department, Zoological
Research Museum Alexander Koenig, 53113 Bonn, Germany, and 5Corresponding author, e-mail: elsa.call.fr@gmail.com
Subject Editor: MarkoMutanen
Received 25 May 2020; Editorial decision 27 October 2020
Abstract
Billions of specimens can be found in natural history museum collections around the world, holding potential
molecular secrets to be unveiled. Among them are intriguing specimens of rare families of moths that, while rep-
resented in morphology-based works, are only beginning to be included in genomic studies: Pseudobistonidae,
Sematuridae, and Epicopeiidae. These three families are part of the superfamily Geometroidea, which has
recently been defined based on molecular data. Here we chose to focus on these three moth families to ex-
plore the suitability of a genome reduction method, target enrichment (TE), on museum specimens. Through
this method, we investigated the phylogenetic relationships of these families of Lepidoptera, in particular the
family Epicopeiidae. We successfully sequenced 25 samples, collected between 1892 and 2001. We use 378
nuclear genes to reconstruct a phylogenetic hypothesis from the maximum likelihood analysis of a total of 36
different species, including 19 available transcriptomes. The hypothesis that Sematuridae is the sister group
of Epicopeiidae + Pseudobistonidae had strong support. This study thus adds to the growing body of work,
demonstrating that museum specimens can successfully contribute to molecular phylogenetic studies.
Key words: Museomics, museum sample, target enrichment, phylogenomics, Lepidoptera
Over 3 billion specimens are estimated to be found in natural history
museum collections around the world, representing one of the most
important biobanks in the world (Duckworth etal. 1993, Suarez
and Tsutsui 2004, Chapman 2005). Until recently, this vast amount
of biological resource was mainly used for morphological studies
because the DNA from these specimens was thought to be too de-
graded to be used for molecular studies (Shapiro and Hofreiter
2012). Due to this, DNA work has, for a long time, been limited
to species for which freshly collected samples could be obtained,
while molecular work from collections was restricted to Sanger
sequencing of short fragments of DNA (Hajibabaei et al. 2006,
Lozier and Cameron 2009, Strutzenberger etal. 2012, Hebert etal.
2013, Cameron etal. 2016). Moreover, the methods were often de-
structive for the specimens (Hajibabaei etal. 2006, Strutzenberger
et al. 2012, Hebert et al. 2013). Recently, high-throughput
sequencing technologies have made the DNA in museum specimens
more accessible, either through whole-genome sequencing (Cong
etal. 2017, Sproul and Maddison 2017, Allio etal. 2019, Li etal.
2019, Zhang et al. 2019) or through genome reduction methods
(Suchan etal. 2016, Breinholt et al. 2018, Toussaint etal. 2018).
These advanced sequencing approaches have opened up a new eld
with great potential for studying the evolutionary history of taxa
that are difcult to collect: museomics.
The family Epicopeiidae is a small Asian family of Lepidoptera
represented by 25 species (Minet 2002, Wei and Yen 2017, Zhang
et al. 2020). Many of them are large diurnal species mimicking
butteries in the families Papilionidae and Pieridae. The history
of the family has been dynamic. Epicopeiidae had originally been
described to harbor only one genus Epicopeia Westwood, 1841
(Laithwaite and Whalley 1975). The pierid-like moths Nossa Kirby,
1892, were previously assigned to the family Epiplemidae (now
considered a subfamily of Uraniidae), but then were rightly placed
in Epicopeiidae by Fletcher (1979) and later conrmed by Minet
(1983, 1986). In latter studies, Minet (1983, 1986) added ve
genera to Epicopeiidae: Amana Walker, 1855; Chatamla Moore,
1881; Parabraxas Leech, 1897; Psychostrophia Butler, 1877; and
Schistomitra Butler, 1881. In 2002, Minet described two new genera,
Deuveia and Burmeia. Finally, in 2017, the number of genera in-
creased to 10 with the description of Mimapora by Wei and Yen.
The family was thought to be related to Drepanidae and was placed
in the superfamily Drepanoidea (Minet 2002), until recent mo-
lecular data suggested that they are in fact related to the superfamily
Insect Systematics and Diversity, (2021) 5(2): 6; 1–10
doi: 10.1093/isd/ixaa021
Research
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Geometroidea (Regier etal. 2009, Bazinet etal. 2013, Rajaei et al.
2015). The sister group of Epicopeiidae has been suggested to be
the recently described Pseudobistonidae (Rajaei etal. 2015, Wang
etal. 2019). Minet (2002) studied the relationships of genera within
Epicopeiidae based on 34 morphological characters obtained from
the head, thorax, pregenital abdomen, and male genitalia. He found
that Deuveia was sister to the rest of Epicopeiidae and that the rela-
tionships of the other genera were relatively clear (Fig.1, left side).
However, the position of Amana was not stable; it was either sister
to Chatamla + Parabraxas or sister to a clade containing Chatamla,
Parabraxas, Schistomitra, Nossa, and Epicopeia.
The rst attempt to infer the phylogeny of the family based on
genetic markers was done by Wei and Yen (2017). They used se-
quence data for three gene regions (COI, EF-1α, and 28S) and 14
species. Their study was mainly focused on describing a new genus,
Mimaporia, but they sampled widely throughout the family. The re-
sults of their analyses are highly incongruent with those of Minet
(2002), but showed poor or no support on many branches. Wei and
Yen (2017) showed that Epicopeia and Nossa likely are paraphy-
letic, and they were not able to resolve the relationships of the new
genus Mimaporia with any condence (Fig.1).
Recently, Zhang etal. (2020) used PCR-generated baits to infer
a multilocus phylogenetic hypothesis for Epicopeiidae based on 18
species and 94 loci. Their results were highly congruent with Minet’s
(2002) results based on morphology and also found that Epicopeia
and Nossa both were paraphyletic with regard to each other. In add-
ition to using fresh specimens, Zhang etal. (2020) used older speci-
mens with some degree of success, although they were able to recover
a signicantly smaller number of loci from the older specimens.
Epicopeiidae species are generally rare and difcult to collect,
as they are mainly distributed in areas that are not easy to access,
nevertheless they can be found in natural history museums. Here
we investigate the use of target enrichment (TE) methods to study
the phylogenetic relationships of this family of Lepidoptera based
only on museum specimens. Genome reduction methods, such as
TE, aim to sequence only specic segments of the genome. In the
case of highly fragmented genomes (e.g., museum specimens), such
genome reduction methods might be a very useful way of gathering
data for phylogenetic studies. To study phylogenetic relationships
among species, one usually analyzes an a priori known set of gen-
etic markers, e.g., a set of single-copy, protein-coding, homologous
genes. By targeting specic genes of interest, the TE method can be
particularly relevant for phylogenetic studies. However, it has gener-
ally been thought that such reduction methods require good-quality
DNA from fresh or properly stored tissue (Lemmon and Lemmon
2013, Jones and Good 2016). Regardless, TE methods have been
used successfully on stored DNA extractions (Faircloth etal. 2012,
McCormack et al. 2013), as well as museum specimens (Bi etal.
2013, Cruz-Dávalos etal. 2017, St Laurent etal. 2018).
Materials andMethods
Taxon Sampling
Specimens were taken from the collection at the Zoological
Research Museum Alexander Koenig (ZFMK, Bonn, Germany).
We sampled 16 available species of Epicopeiidae, including at most
four specimens per species. In addition, we sampled two species
of Sematuridae (Anurapteryx interlineata and Mania empedocles)
and two specimens of Pseudobistonidae (Pseudobiston pinratanai)
to investigate the relationships between these three families. In
total, 33 museum specimens collected between 1892 and 2001
were included (Table1). The oldest sample is a Parabraxas davidi
(Oberthür, 1885)specimen from 1892, whereas the most recent one
is Parabraxas avomarginaria (Leech, 1897)from 2001 (Table1).
We were not able to acquire samples of the genera Chatamla
(Moore, 1881), Burmeia (Minet, 2002), Mimaporia (Wei and Yen,
2017), or Amana (Walker, 1855), or samples of Heracula discivitta,
Fig. 1. Simplified representation of Epicopeiidae phylogenetic relationships according to Minet (2002) (left) and Wei and Yen (2017) (right). Each genus has a
specific color. Minet’s alternative hypothesis about the position of Amana is represented by gray lines.
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which was recently moved to the family Pseudobistonidae (Wang
etal. 2019). Details for all the specimens included can be found on
Zenodo (doi:10.5281/zenodo.3769000).
Sample Preparation and DNA Extractions
We used a semidestructive approach, i.e., we removed the abdomen
for DNA extraction without grinding the tissue, thus preserving the
genitalia for future preparation (Hundsdoerfer and Kitching 2010).
Genitalia dissections are routinely done for Lepidoptera by boiling
abdomens in KOH to remove soft tissue, thus destroying the DNA in
the process, so our approach is less destructive than what is normally
done. For large specimens (like Nossa or Epicopeia), the abdomen
was cut in half above the genitalia to ensure that they t inside 1.5-
ml Eppendorf tubes. Abdomens were rst soaked in 180-µl H2O, for
about 5min, to rehydrate tissues. Water was removed before starting
DNA extractions. Samples were lysed at 56°C overnight shaking
with 350rpm (by using a thermomixer) for approximately 12–18h.
We used the DNeasy Blood & Tissue kit (Qiagen, Hilden, Germany)
and followed the standard DNA extraction protocol for tissues, with
the following modications: we included an RNase-digestion step
and eluted the DNA in Milliq water. Finally, DNA concentration of
each sample was quantied using a Quantus Fluorometer (Promega,
Madison, WI), and fragment lengths were measured with a Fragment
Analyzer (Advanced Analytical, now Agilent Technologies Inc.,
Santa Clara, CA).
Library Preparation, TE, and Sequencing
There is still no consensus on how the DNA in museum specimens
is best accessed. Here we used TE, a genome reduction approach. TE
methods use probes, designed to target specic regions of the genome
(Breinholt etal. 2018, Toussaint etal. 2018, Espeland etal. 2019).
In the case of phylogenetic studies, this approach has the main ad-
vantage to recover exactly the loci of interest, and as long as a probe
kit exists for a group, no previous knowledge about the genomes of
the group of interest is required. This approach follows three major
steps: 1)bait design, 2) libraries preparations and sequencing, and
3)ltering and processing of thedata.
Regarding the bait design, new genes were selected and added
to the Buttery1.0 kit by Espeland etal. (2018). Mayer etal. (2021)
designed hybrid enrichment baits with BaitFisher software version
1.2.8 (Mayer et al. 2016). A bait length of 120 bp was specied
with a clustering threshold of 0.15, and a tiling design of 3 baits
per bait region with an overlap of 60bp for two consecutive baits
resulting in bait regions with a total length of 240bp. Individual
coding sequences (CDS) from Danaus plexippus (Linneaus),
Melitaea cinxia (Linneaus), Heliconius melpomene (Linneaus),
Papilio glaucus (Linneaus), Plutella xylostella (Linneaus), Bombyx
mori (Linneaus), and Manduca sexta (Linneaus) were used as ref-
erences. The LepZFMK1.0 kit includes 2,954 probe regions in dif-
ferent CDS regions belonging to 1,754 genes and is compatible with
BUTTERFLY1.0 (Espeland et al. 2018) and partially compatible
Table 1. Number of raw recovered loci and selected loci per specimen
Family Species Specimen Collection year Raw loci
Loci found in at
least 20 specimens Reference
Epicopeiidae Deuveia banghaasi (Hering, 1932) S35 1936 12 11 This study
D.banghaasi S37 1936 666 353 This study
Epicopeia hainseii (Holland 1889) S51 1932 549 327 This study
E.hainseii S53 1932 936 373 This study
E.hainseii (Moore, 1874) S43 1951 1,063 374 This study
E.hainseii S45 2001 1,383 376 This study
E.philenora (Westwood. 1841) S55 1937 736 358 This study
E.philenora S57 1938 467 306 This study
E.polydora (Westwood, 1841) S47 1992 1,270 378 Mayer etal. (2021)
E.polydora S49 1932 9 8 This study
Nossa moorei (Elwes, 1890) S11 1931 6 5 This study
N.moorei S13 1931 210 185 This study
N.nagaensis (Elwes, 1890) S9 1991 1 365 This study
N.nelcinna (Moore, 1875) S3 1932 0 0 This study
N.palaearctica (Staudinger, 1887) S5 1989 1 1 This study
N.palaearctica S7 1990 1,202 375 This study
N.palaearctica chinensis S1 1937 4 3 This study
Parabraxas davidi (Oberthür, 1885) S17 1892 516 330 Mayer etal. (2021)
P.davidi S19 1957 1 1 This study
P.davidi S21 1906 0 0 This study
P.avomarginaria (Leech, 1897) S23 2001 982 351 This study
P.nigromacularia (Leech, 1897) S25 1999 1,215 378 This study
Psychostrophia endoi (Inoue, 1992) S27 1995 1,275 373 This study
P.melanargia (Butler, 1877) S39 1956 1,115 372 This study
P.melanargia S41 1934 780 362 This study
P.nymphidiaria (Oberthür, 1893) S31 1938 848 367 This study
P.nymphidiaria S33 1946 739 364 Mayer etal. (2021)
P.picaria (Leech, 1897) S29 2001 1,219 375 This study
Schistomitra funeralis (Butler, 1881) S15 1966 151 131 This study
Pseudobistonidae Pseudobiston pinratanai (Inoue, 1994) S2 1999 232 170 Mayer etal. (2021)
P.pinratanai S63 1999 890 361 Mayer etal. (2021)
Sematuridae Anurapteryx interlineata (Walker. 1854) S61 ? 928 376 Mayer etal. (2021)
Mania empedocles (Cramer, 1782) S59 1960 431 283 This study
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with LEP1 (Breinholt etal. 2018). For more details on the kits, see
Mayer etal. (2021). In many cases, multiple exons of single genes
were targeted when they were longenough.
Library preparation was performed at the Zoological Research
Museum Alexander Koenig (Bonn, Germany). Most of our samples
contained less than 100-ng genomic DNA, which is the needed con-
centration according to standard protocol, but we included them
anyway. With the Fragment Analyzer we found that many fragments
of our samples were around 140bp; therefore, no fragmentation was
necessary for these samples. Other samples with higher quality and
longer fragments were fragmented with Bioruptor PICO sonicator
(Diagenode, Seraing, Belgium) to obtain DNA fragments with an
approximate length of 350bp.
We repaired the DNA with NEBNext FFPE DNA Repair Mix
(NEB, Ipswich, United Kingdom), following the manufacturer’s
protocol. We puried the reactions with Agencourt AMPure
XP beads with a ratio of (1:3). We quantied the resulting li-
braries with Quantus Fluorometer (Promega) and quality checked
with a Fragment Analyzer (Advanced Analytical, now Agilent
TechnologiesInc.).
We proceeded to the enrichment and captured steps with the
Agilent SureSelect XT2 protocol, with additional modication fol-
lowing Bank etal. (2017). Enrichment and sequencing were done
at StarSEQ GmbH (Mainz, Germany) on Illumina Nextseq 500
Systems with a read length of 150bp. Exons found in at least 20 of
the 33 specimens (with an average of 254 loci per specimen) were
used for downstream phylogenetic analyses (Table1). Sequencing
data is available at the NCBI under Bioproject PRJNA684488.
Data Clean up and Assembly
Reads were trimmed with fastq-mcf (Aronesty 2011) using de-
fault parameters to remove adapters and low-quality regions. Data
cleaning and assembly was done using the iterated bait assembly
(IBA) pipeline (Breinholt etal. 2018) with default parameters, ex-
cept that the paired gap length was set to 100 (-g 100). Genomic
sequences of the target regions from D.plexippus were used as a ref-
erence for the IBA pipeline. In brief, reads similar to the reference se-
quence were identied with USEARCH (Edgar 2010) and assembled
with Bridger (Chang etal. 2015). The resulting assembly was then
used as a reference sequence for another run of USEARCH, and this
process was repeated threetimes.
Alignments
The loci were aligned using the FFT-NS-i algorithm with two iter-
ations in MAFFT v.7 (Katoh and Standley 2013) prior to phylo-
genetic analyses. Alignments were trimmed to the probe regions
by using TrimAl (Capella-Gutierrez et al. 2009), with the options
‘-gapthreshold’ and ‘-conserve’. These commands were imple-
mented to remove gaps. The alignment cleanup was performed with
HmmCleaner (Di Franco etal. 2019), which allows the detection
and removal of primary sequence errors in multiple alignments. We
used the commands ‘-costs’ and ‘--noX’ and dened the four costs
as follows: −0.15, −0.08, 0.15, and 0.45. We subsequently manually
checked for frame shifts, gaps, and codon positions. Finally, align-
ments containing less than 20 samples (excluding references) were
discarded from the downstream analysis. The nal ltered data set
consisted of 378 genes.
Screening Available Genomes and Transcriptomes
Additional 19 taxa were added to our data set by mining avail-
able genomes and transcriptomes, including one epicopeiid and
one sematurid (Table2). Twelve of the transcriptomes were from
the superfamily Geometroidea, the remaining ones were from other
macroheteroceran superfamilies. Raw reads were downloaded from
the NCBI Sequence Read Archive (Leinonen etal. 2011). Reads were
rst processed to remove low-quality regions (Q < 30), adapters
and homopolymer stretches using Cutadapt 1.4.1 (Martin 2011;
minimum read length 50 bp) and Prinseq 0.20.4 (Schmieder and
Edwards 2011), respectively. De novo assembly was carried out with
Trinity 2.0.6 (Grabherr etal. 2011, Haas etal. 2013), with default
parameters, including a minimum contig length of 100bp and a
minimum kmer coverage of5.
Identication of the 378 genes was carried out with a BLAST ap-
proach. Areference sequence set was created from the TE alignments
from one representative per gene. Atblastn (Gertz etal. 2006) search
of the reference set against the transcriptomes (e-value threshold
Table 2. List of the 19 available transcriptomes and genomes added to this study
Family Subfamily Species
Source/acces-
sion numbers
Bombycidae Bombycinae Bombyx mori (Linnaeus, 1758) SilkDB
Crambidae Crambinae Chilo suppressalis (Walker, 1863) LepBase v4
Erebidae Arctiinae Callimorpha dominula (Linnaeus, 1758) SRR1191023
Epicopeiidae — Epicopeia hainseii (Holland, 1889) SRR1021610
Geometridae Larentiinae Operophtera brumata (Linnaeus, 1758) LepBase v4
Ennominae Biston betularia (Linnaeus, 1758) SRR1021599
Biston suppressaria (Guenée, 1858) SRR1777716
Ectropis obliqua (Prout, 1915) SRR3056076
Macaria distribuaria (Hubner, 1825) SRR1299213
Geometrinae Chlorosea margaretaria (Sperry, 1944) SRR1021603
Nemoria lixaria (Guenée, 1858) SRR1299347
Sterrhinae Idaea eremiata (Hulst, 1887) SRR1021615
Noctuidae Hadeninae Spodoptera frugiperda (Smith, 1797) SRR3406055
Notodontidae Nystaleinae Notoplusia minuta (Druce, 1900) SRR1299746
Pyralidae Phycitinae Amyelois transitella (Walker, 1863) LepBase v4
Sematuridae — Mania lunus (Linnaeus, 1758) SRR1299318
Sphingidae Sphinginae Manduca sexta (Linnaeus, 1763) LepBase v4
Uraniidae Uraniinae Lyssa zampa (Butler, 1869) SRR1299769
Epipleminae Calledapteryx dryopterata (Grote, 1868) SRR1021601
Published transcriptomes have their SRA accession numbers listed. SRA, NCBI Sequence Read Archive.
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10e-5) was carried out. The resulting BLAST output was used to
extract the coding regions from each assembly using a set of open
access python scripts from Dr. C.Peña (PyPhylogenomics, https://
github.com/carlosp420/PyPhyloGenomics). The extracted sequences
were aligned to the existing alignment with MAFFT 7.266 (Katoh
and Standley 2013) using the ‘add fragments’ and ‘auto’ options,
to preserve existing gaps in the alignment and choose the most ap-
propriate alignment strategy, respectively. The resulting alignments
were manually screened to ensure accurate alignment and frame
preservation.
Phylogenetic Analyses
To partition our data set, we calculated the relative rates of evo-
lution for each site in the alignment using TIGER (Cummins and
McInerney 2011) and created partitions using the RatePartitions
algorithm (Rota et al. 2018). We tested a range of d values (1.1,
1.5, 2.0, 3.0, and 4.0), which affects the number of partitions, and
calculated the Bayesian information criteria (BIC) values for each
partitioning scheme in PartitionFinder2 (Guindon et al. 2010,
Frandsen etal. 2015, Lanfear etal. 2017). The partitioning scheme
with the highest BIC value was found for d=2.0, which resulted in
14 subsets.
Using the optimal partitioning scheme, we inferred the phylo-
genetic relationships with IQ-TREE 1.6.10 (Nguyen et al.
2015, Chernomor et al. 2016) under the maximum likelihood
(ML) criterion. We used the model nding option in IQ-TREE
(Kalyaanamoorthy etal. 2017) to nd the optimal model for each
partition. To investigate the robustness of our inferences, we used
1,000 ultrafast bootstraps (-bb; Hoang et al. 2018) and 1,000
replicates for SH-aLRT (-alrt; Guindon etal. 2010), which is the
minimum recommended number.
Results
Genes
We recovered a total of 2,131 raw loci. From our total of 33 speci-
mens, two (6%) provided no data: Nossa nelcinna (S3) and P.davidi
(S21). Six specimens provided only 1–12 raw loci (18%); for 16 spe-
cimens, we obtained between 150 and 1,000 loci (48%); nally, nine
specimens gave more than 1,000 loci, with a maximum of 1,383 loci
recovered (27%; Table1, Fig.2).
There is a positive correlation between the collection date of the
specimens and the number of recovered loci (rho=0.46, P=0.008;
Fig.2). As expected, the younger a specimen is, the more loci we can
recover from it. However, there is a lot of variation, meaning some
recently collected specimens can give fewer loci than specimens col-
lected a long time ago. This is, e.g., the case in two specimens of
P.davidi. We recovered 516 raw loci from the older of the two, col-
lected in 1892, whereas the more recent one (1957) provided only a
single rawlocus.
We obtained on average 254 loci and a median of 353 loci per spe-
cimen (Table1). For our phylogenetic analyses, we rst used all the 31
specimens that produced some data, including the 6 from Mayer et al.
(2021). The samples Epicopeia philenora (S57) and Nossa palaeartica
(S5) appeared to be contaminated as their phylogenetic position in pre-
liminary analyses were highly doubtful, and thus they were excluded
from the rest of our analyses.
Our nal data set comprised 37 species, including 20 species
sequenced for this study and 17 outgroup species with published
transcriptomes. The data matrix included 378 nuclear loci (327
genes), for a total alignment of 134,881 base pairs. The average
length of the 378 loci involved in this study is 367bp.
Model Selection and Phylogenetic Analyses
The ML analyses for the different models tested gave the same
phylogenetic relationships, and there were no conicting nodes.
The taxon data set, extended with 17 outgroup species, analyzed in
IQ-TREE resulted in a highly supported ML tree (Fig.3). We also
performed the same phylogenetic analyses where we excluded speci-
mens with less than 10 loci, and we obtain the same topology (Supp
Material 1 [online only]), indicating that the necessarily somewhat
limited data recovered from old specimens are of sufcient quality
for phylogenetic analysis. Although our data set gave strong support
for many of the branches, the relationships among the Noctuoidea,
Bombycoidea, and Geometroidea were weakly supported.
The monophyly of Epicopeiidae is strongly supported, and the
sister group is Pseudobistonidae, with Sematuridae being sister to
these two, also with strong support (SH-like=100, UFBoot=100).
Within Epicopeiidae, almost all relationships are strongly sup-
ported, with the exception of the position of Schistomitra funeralis
(SH-like = 54.8, UFBoot= 81). Relationships of genera are con-
gruent with Minet (2002) and Zhang etal. (2020), i.e., Deuveia is
sister to the rest of Epicopeiidae, with Psychostrophia branching off
next, then Schistomitra, and nally Parabraxas being sister to a clade
containing paraphyletic Epicopeia and Nossa (Fig.3).
Within genera, species for which two or more individuals were
included were mainly monophyletic, with the exception of Epicopeia
hainseii and Epicopeia polydora, which were intermixed in a clade
with very short branches (Fig.3). The branch leading to P.davidi has
weak support values (66.1/94), and this species appears to be genet-
ically very closely related to P.avomarginaria. In addition, Nossa
moorei is not genetically differentiated from Nossa nagaensis, while
being morphologically very similar (Fig.3).
Discussion
Phylogenetic Relationships
Within Epicopeiidae, our results strongly support and are almost en-
tirely congruent with the relationships suggested by Minet (2002)
and Zhang etal. (2020) and thus highly incongruent with the re-
sults of Wei and Yen (2017). We nd Deuveia to be sister to the
rest of Epicopeiidae, with the monophyletic Psychostrophia being
sister to the rest of all taxa excluding Deuveia (Fig.3). Wei and Yen
(2017) found Parabraxas to be sister to Psychostrophia, but our
Fig. 2. Number of raw loci recovered for each sample per year of collection.
The dashed line is for reference and represents the trend. Plot made on R.
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results place Parabraxas in a clade with Schistomitra and (Epicopeia
+ Nossa) with strong support.
The position of S.funeralis (which has 131 loci in our dataset)
was incongruent with the hypothesis by Minet (2002), but with low
support. In our study, we found Schistomitra to be the sister group
of Parabraxas + (Epicopeia + Nossa) (Fig.3), whereas Minet (2002)
found it to be the sister group of Epicopeia + Nossa (Fig.1), and
Zhang etal. (2020) found it to be sister to Parabraxas + Chatamla.
Wei and Yen (2017) found it to be sister to Chatamla + the newly
described genus Mimapora, and this clade to be closer to Parabraxas
+ Psychostrophia than to Epicopeia + Nossa (Fig.1). However, we
are not able to condently resolve the relationships of Schistomitra,
Parabraxas, and (Epicopeia + Nossa). Our study does not include the
taxa Amana, Chatamla, or Mimapora, which are all potentially re-
lated to Schistomitra and Parabraxas (Minet, 2002). All four genera,
Schistomitra, Amana, Chatamla, and Mimapora, are currently being
considered to be monotypic, and their relationships based on morph-
ology are somewhat enigmatic (Minet 2002, Wei and Yen 2017).
Zhang etal. (2020) did include all four genera, and they were able to
resolve their phylogenetic positions with condence.
As in Zhang et al. (2020), we nd that Nossa and Epicopeia
are paraphyletic with regard to each other. Indeed, E.philenora ap-
pears to be the sister group to N.moorei and N.nagaensis, whereas
N.palaeartica comes out as related to E.hainseii and E.polydora.
Fig. 3. Phylogenetic tree from maximum likelihood analysis of 36 taxa based on 378 loci. If the support values are not displayed on the branch, it means it is
equal to 100/100. When displayed, numbers are the SH-aLRT support (%)/ultrafast bootstrap support (%). The images are representative species (indicated with
numbers; not to scale). The three families are represented by an arrow and a letter. S, Sematuridae; P, Pseudobistonidae; and E, Epicopeiidae.
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Furthermore, these relationships are well supported. Minet (2002)
also nds the two genera to be closely related and sharing six
apomorphic character states, despite being supercially quite distinct
with Epicopeia species tending to mimic papilionids, and Nossa spe-
cies tending to mimic pierid species (Fig.3). Clearly, these two genera
need to be studied in more detail by including all 12 described spe-
cies. It is possible that the genera should be synonymized, in which
case Epicopeia would have priority. Also, we found E.hainseii and
E.polydora to be genetically inseparable based on our dataset. In
contrast, Zhang et al. (2020) nd these two taxa to be completely
separate, with E. polydora being sister to N. moorei, in a similar
position to our E. philenora. Zhang et al. (2020) did not sample
E.philenora, but E.polydora and E.philenora are morphologically
very similar, suggesting that our sequences may be contaminants.
The paraphyly of Epicopeia and Nossa is surprising. These
two genera are morphologically supercially very different, with
Epicopeia species showing distinct tails on the hindwings, whereas
Nossa species lack these tails. Indeed, Minet separated these two
genera on morphological characters, including their genitalia (Minet
2002). However, one should keep in mind that Epicopeia are
mimicking species of butteries in the genera Papilio and Byasa (that
have tails on the hindwings), whereas Nossa is thought to mimic
species of Pieridae (that do not have tails; Wei and Yen 2017, Zhang
etal. 2020). It has been considered that mimicry might be one of
the causes for the rapid divergence of phenotypes (Turner 1976,
Counterman etal. 2010, Kozak etal. 2015). Thus, in further work,
we need to investigate this aspect by including more species and in-
dividuals of Epicopeia and Nossa.
Within Epicopeiidae, specimens with few loci explain most
branches with low support (the exception being Schistomitra de-
scribed above). When we removed the four specimens with less
than 10 loci (see Table1) from our analyses, the relationships do
not change, while the support greatly improved to reach the max-
imum value of 100/100 on some branches, like for N.moorei and
N.nagaensis, or for the relationships between Epicopeia hainseii and
E. polydora (Supp Material 1 [online only]). This would indicate
that specimens with few loci are only affecting the support values,
but not the general topology.
Here we obtain strong support for the hypothesis that Sematuridae
is the sister group of Epicopeiidae + Pseudobistonidae. Even with
few representatives for Sematuridae and Pseudobistonidae, the sup-
port for this hypothesis is compelling (100/100) and in line with
previous studies (Rajaei etal. 2015, Kawahara et al. 2019, Wang
etal. 2019). Furthermore, we conrmed that Epicopeiidae is mono-
phyletic with regard to Pseudobistonidae, strengthening the case for
the latterfamily.
The rst attempt to resolve the position of Pseudobistonidae
was made when the family was described by Rajaei etal. (2015) to
accommodate P. pinratanai. Rajaei et al. (2015) found the family
to be the sister group of Epicopeiidae. Recently, the position of
Pseudobistonidae was corroborated with the addition of another spe-
cies in the family: H.discivitta (Wang etal. 2019). However, Wang
etal. (2019) only included three Epicopeiidae and two Sematuridae
species. Furthermore, the support for the branches leading to these
three families was quite low, e.g., the branch supporting Sematuridae
as the sister group of Epicopeiidae + Pseudobistonidae had a boot-
strap value of 33. Zhang et al. (2020) include Heracula in their
dataset and nd it to be sister to Epicopeiidae with strong support;
thus, it would appear that Pseudobistonidae is indeed the sister lin-
eage to Epicopeiidae, with Sematuridae being sister to these two.
Old Material and Contamination
We see a tendency for old museum specimens to yield fewer loci
than the more recently collected ones (Fig.2). Overall, the older a
specimen is, the lower the chances are to get DNA out of it with the
TE approach. Nevertheless, some old specimens provide more loci
than younger ones. For instance, for the two specimens of P.davidi,
the older, collected in 1892, provided 516 raw loci, whereas the
younger, collected in 1957, provided only a single raw locus. There
is no clear explanation for these kinds of outliers, but they might
be due to different treatments during their curation (Espeland etal.
2010, Burrell et al. 2015, Vaudo etal. 2018). Unfortunately, nei-
ther a proper record of this kind of treatment nor how specimens
have been collected and curated are usually available, making it im-
possible here to infer what other factors than age can affect the
quality of DNA. Regardless, even if the tendency is, as expected, that
older samples have less and poorer DNA quality, it remains a trend.
Therefore, we should not discount these specimens just because they
are old, as they can still turn out to be real genetic treasuretroves.
Unfortunately, two specimens were denitely contaminated,
E.philenora (S57) and N.palaeartica (S5), and therefore were not
analyzed further. If they had been of good quality, they could have
helped us to conrm the position of E.philenora in the case of S57,
as well as the separation of Nossa in two groups with N.moorei +
N.nagaensis on one side and N.palaeartica (S5) on the other side.
In addition, our E.polydora specimens were found to be genetically
identical to E.hainseii, in stark contrast to Zhang etal. (2020). One
of our specimens (S47) yielded 1,270 raw loci (Table1), suggesting
large amounts of DNA in the extract. The two species cannot be con-
fused morphologically (see doi:10.5281/zenodo.3769000). Clearly,
this needs to be investigated in more detail, but for the moment, we
do not have a good explanation for these results.
The Importance of Museomics
Since their creation, natural history museums have been an essen-
tial source of biological knowledge and resources for both the scien-
tic community and the public (Duckworth etal. 1993, Suarez and
Tsutsui 2004). These collections of biological specimens are vital for
the study of systematics, global climate change research, biological
invasion studies, as well as for many other scientic disciplines (Bi
etal. 2013, Bradley etal. 2014, Bakker etal. 2020). Curated speci-
mens in museums have several advantages compared with collecting
fresh specimens; they can be easy to access, most of them are iden-
tied, and often possess information such as the date of collection
and the location. Moreover, nowadays, researchers in biology and
ecology face many challenges before being able to sample in the
eld. These issues can be monetary (e.g., lack of funding), stochastic
events (inaccessibility of species of interest, adverse weather condi-
tions, pandemic etc.), but also administrative difculties, with bur-
eaucratic hurdles being erected at an increasing pace (Neumann etal.
2018). Natural history museums also contain extinct taxa, rare and
challenging to collect species, which can be a crucial asset to studies.
However, until recently, this vast amount of biological resources was
mainly used for morphological studies because the DNA from these
specimens was thought to be too degraded to be used for molecular
studies (Shapiro and Hofreiter 2012). Due to this, DNA work has for
a long time mainly been limited to species for which freshly collected
samples could be obtained, whereas DNA work from collections has
been limited to sequencing short fragments DNA (Hajibabaei etal.
2006, Lozier and Cameron 2009, Strutzenberger etal. 2012, Hebert
etal. 2013, Cameron etal. 2016).
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8
We have taken advantage of recent advances in sequencing
technologies, which have opened up access to genomic data of mu-
seum specimens. Within the past few years, various studies emerged
applying these methods on a wide variety of species: from birds
(Anmarkrud and Lifjeld 2017, Cloutier et al. 2018) and mammals
(Fabre etal. 2014, Hawkins etal. 2016) to insects (Kanda etal. 2015,
Sproul and Maddison 2017), and plants (Zedane etal. 2016, Silva
etal. 2017). Part of these studies used whole-genome sequencing
(Kanda et al. 2015, Zedane et al. 2016, Sproul and Maddison
2017, Cloutier etal. 2018), whereas the others employed diverse
genome reduction methods, such as exon capture (Bi etal. 2013)
and TE (Hawkins et al. 2016). Although these studies used dif-
ferent kinds of sequencing methods, they focus on very distinct sci-
entic questions: from systematics (Silva etal. 2017), to the origin
and diversication of a taxon (Fabre etal. 2014), to population
genomics (Bi etal. 2013).
Here, we used a genome reduction method, TE, on curated mu-
seum specimens of rare and challenging to collect moth species, to
rene our knowledge of their phylogenetic relationships. We man-
aged to recover on average 566 nuclear loci per species using the
TE method. The present study also shows that it is possible to ex-
tract substantial amounts of DNA sequence data from specimens
collected up to 127 yr ago. Hence, our study contributes to the eld
of museomics, demonstrating the application of this sequencing
method on museum specimens, increasing the value of such spe-
cimens even further. Museomics opens a window to the past, pro-
viding possibilities for testing new hypotheses and for casting new
light on old ones.
Conclusion
In summary, we conducted a phylogenetic analysis on small and rare
families of Lepidoptera, using museum specimens. We successfully
sequenced samples that were collected between 1892 and 2001. By
utilizing a TE approach, we were able to recover between 150 and
1,383 loci per specimen for 75% of our samples. From all these raw
loci, we used 378 genes—present in at least 20 samples—to recon-
struct a phylogenetic hypothesis based on ML analysis of 37 taxa.
This analysis corroborates, with strong support, the hypothesis that
Sematuridae are the sister group of Epicopeiidae + Pseudobistonidae.
Within Epicopeiidae, our study nds Deuveia as sister group of the
rest of Epicopeiidae genera. The position of Schistomitra is incon-
gruent with the central hypothesis suggested by Minet (2002) for
this family; however, the support for this branch is low. The low sup-
port for this branch might be explained in our study by the lack of
some genera (Amana, Chatamla, and Mimapora). Indeed, these taxa
may help to clarify the phylogenetic position of Schistomitra, as seen
in Zhang et al. (2020). Although we showed that Psychostrophia
and Parabraxas are monophyletic, we also found that Nossa and
Epicopeia are paraphyletic. Overall, the genera of Epicopeiidae re-
quire more work to reveal their phylogenetic relationships.
Museum collections represent a varied and essential biobank of
samples for studying the diversity on earth. The availability of spe-
cimens, not only rare but also extinct, within worldwide museum
collection is a fantastic asset. Nowadays, sequencing techniques
are powerful enough to allow scientists to recover DNA from old
museum specimens. This is the beginning of an exciting era for
molecular studies. Our study makes its contribution to the eld
of museomics by successfully demonstrating that researchers can
use museum samples at a molecular level for phylogenetic studies.
Consequently, this study is paving the way for more molecular work
using museum specimens.
SupplementaryData
Supplementary data are available at Insect Systematics and
Diversityonline.
Supplementary Material 1.Phylogenetic tree from ML analysis
of 36 taxa based on 378 loci, specimens with less than 10 loci were
excluded.
Acknowledgments
We are thankful to Claudia Etzbauer for help with ordering the kit and
to Sandra Kukowka for assistance in the molecular lab. We highly appre-
ciate the effort of everyone depositing samples at the ZFMK. The study
was funded by the Zoological Research Museum Alexander Koenig, and
received funding from the European Union’s Horizon 2020 research and
innovation program under the Marie Skłodowska-Curie Grant Agreement
No. 6422141.
ReferencesCited
Allio,R., C.Scornavacca, B.Nabholz, A.-L.Clamens, F.A.H.Sperling, and
F.L.Condamine. 2019. Whole genome shotgun phylogenomics resolves
the pattern and timing of swallowtail buttery evolution. Syst. Biol. 69:
38–60.
Anmarkrud,J.A., and J.T.Lifjeld. 2017. Complete mitochondrial genomes
of eleven extinct or possibly extinct bird species. Mol. Ecol. Resour. 17:
334–341.
Aronesty,E. 2011. Fastq-mcf sequence quality lter, clipping and processor.
(Com/p/ea-utils/wiki/fastqmcf).
Bakker, F. T., A. Antonelli, J. A. Clarke, J. A. Cook, S. V. Edwards,
P.G.P.Ericson, S.Faurby, N.Ferrand, M.Gelang, and R.G.Gillespie,
etal. 2020. The Global Museum: natural history collections and the future
of evolutionary science and public education. PeerJ 8: e8225.
Bank,S., M.Sann, C.Mayer, K.Meusemann, A.Donath, L.Podsiadlowski,
A. Kozlov, M. Petersen, L. Krogmann, and R. Meier, et al. 2017.
Transcriptome and target DNA enrichment sequence data provide new
insights into the phylogeny of vespid wasps (Hymenoptera: Aculeata:
Vespidae). Mol. Phylogenetics Evol. 116: 213–226. doi:10.1016/j.
ympev.2017.08.020.
Bazinet,A. L., M.P.Cummings, K.T.Mitter, and C.W.Mitter. 2013. Can
RNA-Seq resolve the rapid radiation of advanced moths and butteries
(Hexapoda: Lepidoptera: Apoditrysia)? An exploratory study. PLoS One
8: e82615.
Bi,K., T.Linderoth, D.Vanderpool, J.M.Good, R.Nielsen, and C.Moritz.
2013. Unlocking the vault: next-generation museum population genomics.
Mol. Ecol. 22: 6018–6032.
Bradley,R. D., L.C.Bradley, H.J.Garner, and R.J.Baker. 2014. Assessing
the value of natural history collections and addressing issues regarding
long-term growth and care. BioScience 64: 1150–1158.
Breinholt, J. W., C. Earl, A. R. Lemmon, E. M. Lemmon, L. Xiao, and
A. Y.Kawahara. 2018. Resolving relationships among the megadiverse
butteries and moths with a novel pipeline for anchored phylogenomics.
Syst. Biol. 67: 78–93.
Burrell,A. S., T.R. Disotell, and C.M. Bergey. 2015. The use of museum
specimens with high-throughput DNA sequencers. J. Hum. Evol. 79:
35–44.
Cameron,S.A., H.C.Lim, J.D.Lozier, M.A.Duennes, and R.Thorp. 2016.
Test of the invasive pathogen hypothesis of bumble bee decline in North
America. Proc. Natl. Acad. Sci. USA 113: 4386–4391.
Capella-Gutierrez,S., J.M.Silla-Martinez, and T.Gabaldon. 2009. trimAl: a
tool for automated alignment trimming in large-scale phylogenetic ana-
lyses. Bioinformatics 25: 1972–1973.
Chang, Z., G. Li, J. Liu, Y.Zhang, C. Ashby, D. Liu, C. L. Cramer, and
X.Huang. 2015. Bridger: a new framework for de novo transcriptome
assembly using RNA-seq data. Genome Biol. 16: 30.
Chapman, A. D. 2005. Uses of primary species-occurrence data. Global
Biodiversity Information Facility, Copenhagen, Denmark.
Insect Systematics and Diversity, 2021, Vol. 5, No. 2
Copyedited by: OUP
Downloaded from https://academic.oup.com/isd/article/5/2/6/6244279 by elsa.call.fr@gmail.com on 22 April 2021

9
Chernomor,O., A.vonHaeseler, and B.QMinh. 2016. Terrace aware data
structure for phylogenomic inference from supermatrices. Syst. Biol. 65:
997–1008.
Cloutier,A., T.B.Sackton, P.Grayson, S.V.Edwards, and A.J.Baker. 2018.
First nuclear genome assembly of an extinct moa species, the little bush
moa (Anomalopteryx didiformis). bioRxiv, doi:10.1101/262816, 9
February 2018, preprint.
Cong,Q., J.Shen, D.Borek, R.K.Robbins, P.A.Opler, Z.Otwinowski, and
Grishin. V. 2017. When coi barcodes deceive: complete genomes reveal
introgression in hairstreaks. Proc. R.Soc. B Biol. Sci. USA 284: 20161735.
Counterman, B. A., F. Araujo-Perez, H. M. Hines, S. W. Baxter, C. M,
Morrison, D. P. Lindstrom, R. Papa, L. Ferguson, M. Joron, and
R. H. ffrench-Constant, etal. 2010. Genomic hotspots for adaptation:
the population genetics of Müllerian Mimicry in Heliconius erato. PLoS
Genet. 6: e1000796.
Cruz-Dávalos,D.I., B.Llamas, C.Gaunitz, A.Fages, C.Gamba, J.Soubrier,
P.Librado, A.Seguin-Orlando, M.Pruvost, A.H.Alfarhan, et al. 2017.
Experimental conditions improving in-solution target enrichment for an-
cient DNA. Mol. Ecol. Resour. 17: 508–522.
Cummins,C.A., and J.O.McInerney. 2011. A method for inferring the rate of
evolution of homologous characters that can potentially improve phylo-
genetic inference, resolve deep divergence and correct systematic biases.
Syst. Biol. 60: 833–844.
DiFranco,A., R.Poujol, D.Baurain, and H.Philippe. 2019. Evaluating the
usefulness of alignment ltering methods to reduce the impact of errors on
evolutionary inferences. BMC Evol. Biol. 19: 21.
Duckworth,W.D., H.H.Genoways, and C.L.Rose. 1993. Preserving natural
science collections: chronicle of our environmental heritage. Mammology
Papers: University of Nebraska State Museum No. 271. National Institute
for the Conservation of Cultural Property, Washington, DC. p 153.
Edgar,R. 2010. Usearch. Lawrence Berkeley National Lab. (LBNL), Berkeley,
CA. (https://www.osti.gov/sciencecinema/biblio/1137186).
Espeland, M., M. Irestedt, K. A. Johanson, M. Åkerlund, J.-E.Bergh, and
M.Källersjö. 2010. Dichlorvos exposure impedes extraction and ampli-
cation of DNA from insects in museum collections. Front. Zool. 7: 2.
Espeland, M., J. Breinholt, K. R. Willmott, A. D. Warren, R. Vila,
E. F. A. Toussaint, S. C. Maunsell, K. Aduse-Poku, G. Talavera, and
R.Eastwood, etal. 2018. A comprehensive and dated phylogenomic ana-
lysis of butteries. Curr. Biol. 28: 770–778.e5.
Espeland,M., J.W.Breinholt, E.P.Barbosa, M.M.Casagrande, B.Huertas,
G.Lamas, M.A.Marín, O.H.H.Mielke, J.Y.Miller, S.Nakahara, etal.
2019. Four hundred shades of brown: higher level phylogeny of the prob-
lematic Euptychiina (Lepidoptera, Nymphalidae, Satyrinae) based on hy-
brid enrichment data. Mol. Phylogenet. Evol. 131: 116–124.
Fabre,P.-H., J.T. Vilstrup, M.Raghavan, C.Der Sarkissian, E.Willerslev,
E.J.P.Douzery, and L.Orlando. 2014. Rodents of the Caribbean: origin
and diversication of hutias unravelled by next-generation museomics.
Biol. Lett. 10: 20140266–20140266.
Faircloth, B. C., J. E. McCormack, N. G. Crawford, M. G. Harvey,
R.T.Brumeld, and T.C.Glenn. 2012. Ultraconserved elements anchor
thousands of genetic markers spanning multiple evolutionary timescales.
Syst. Biol. 61: 717–726.
Fletcher,D. S. 1979. Geometroidea: apoprogonidae, Axiidae, Callidulidae,
Cyclidiidae, Drepanidae, Epicopeiidae, Epiplemidae, Geometridae,
Pterothysanidae, Sematuridae, Thyatiridae, Uraniidae, p. 243. In
I.W.B.Nye (ed.), The generic names of moths of the world, Vol. 3. British
Museum (Natural History), London, UK.
Frandsen,P.B., B.Calcott, C.Mayer, and R.Lanfear. 2015. Automatic se-
lection of partitioning schemes for phylogenetic analyses using iterative
k-means clustering of site rates. BMC Evol. Biol. 15: 13.
Gertz, E. M., Y.-K. Yu, R. Agarwala, A. A. Schäffer, and S. F. Altschul.
2006. Composition-based statistics and translated nucleotide searches:
improving the TBLASTN module of BLAST. BMC Biol. 4: 41.
Grabherr,M.G., B.J.Haas, M.Yassour, J.Z.Levin, D.A.Thompson, I.Amit,
X.Adiconis, L.Fan, R.Raychowdhury, and Q.Zeng, etal. 2011. Full-
length transcriptome assembly from RNA-Seq data without a reference
genome. Nat. Biotechnol. 29: 644–652.
Guindon, S., J.-F. Dufayard, V. Lefort, M. Anisimova, W. Hordijk, and
O.Gascuel. 2010. New algorithms and methods to estimate maximum-
likelihood phylogenies: assessing the performance of PhyML 3.0. Syst.
Biol. 59: 307–321.
Haas,B.J., A.Papanicolaou, M.Yassour, M.Grabherr, P.D.Blood, J.Bowden,
M.B.Couger, D.Eccles, B.Li, and M.Lieber, etal. 2013. De novo tran-
script sequence reconstruction from RNA-seq using the Trinity platform
for reference generation and analysis. Nat. Protoc. 8: 1494–1512.
Hajibabaei,M., M. A.Smith, D.H.Janzen, J.J.Rodriguez, J.B. Whiteld,
and P.D.N.Hebert. 2006. A minimalist barcode can identify a specimen
whose DNA is degraded. Mol. Ecol. Notes 6: 959–964.
Hawkins, M. T. R., C. A. Hofman, T. Callicrate, M. M. McDonough,
M.T.N.Tsuchiya, E.E.Gutiérrez, K.M.Helgen, and J.E.Maldonado.
2016. In-solution hybridization for mammalian mitogenome enrichment:
Pros, cons and challenges associated with multiplexing degraded DNA.
Mol. Ecol. Resour. 16: 1173–1188.
Hebert,P.D.N., J.R.Dewaard, E.V.Zakharov, S.W.J.Prosser, J.E.Sones,
J.T.A. McKeown, B.Mantle, and J. La Salle. 2013. A DNA ‘barcode
blitz’: rapid digitization and sequencing of a natural history collection.
PLoS One 8: e68535.
Hoang,D.T., O.Chernomor, A.vonHaeseler, B.Q.Minh, and L.S.Vinh.
2018. UFBoot2: improving the ultrafast bootstrap approximation. Mol.
Biol. Evol. 35: 518–522.
Hundsdoerfer,A.K., and I.J.Kitching. 2010. A method for improving DNA
Yield from century-plus old specimens of large lepidoptera while minim-
izing damage to external and internal abdominal characters. Arthropod
Syst. Phylog. 68: 151–155.
Jones,M. R., and J. M.Good. 2016. Targeted capture in evolutionary and
ecological genomics. Mol. Ecol. 25: 185–202.
Kalyaanamoorthy, S., B. Q. Minh, T. K. F. Wong, A. von Haeseler, and
L.S.Jermiin. 2017. ModelFinder: fast model selection for accurate phylo-
genetic estimates. Nat. Methods 14: 587–589.
Kanda,K., J.M. Pug, J.S.Sproul, M.A. Dasenko, and D.R.Maddison.
2015. Successful recovery of nuclear protein-coding genes from small in-
sects in museums using Illumina sequencing. PLoS One 10: e0143929.
Katoh,K., and D.M.Standley. 2013. MAFFT multiple sequence alignment
software version 7: improvements in performance and usability. Mol. Biol.
Evol. 30: 772–780.
Kawahara,A.Y., D.Plotkin, M.Espeland, K.Meusemann, E.F.A.Toussaint,
A.Donath, F.Gimnich, P.B.Frandsen, A.Zwick, and M.Reis, etal. 2019.
Phylogenomics reveals the evolutionary timing and pattern of butteries
and moths. Proc. Natl. Acad. Sci. USA 116: 22657–22663.
Kozak,K. M., N.Wahlberg, A.F.E.Neild, K.K. Dasmahapatra, J.Mallet,
and C.D.Jiggins. 2015. Multilocus species trees show the recent adaptive
radiation of the mimetic Heliconius butteries. Syst. Biol. 64: 505–524.
Laithwaite,E. R., and P.E. S. Whalley. 1975. Dictionary of butteries and
moths in color. Michael Joseph, London, United Kingdom. (http://agris.
fao.org/agris-search/search.do?recordID=US201300521786).
Lanfear,R., P.B.Frandsen, A.M.Wright, T.Senfeld, and B.Calcott. 2017.
PartitionFinder 2: new methods for selecting partitioned models of evo-
lution for molecular and morphological phylogenetic analyses. Mol. Biol.
Evol. 34: 772–773.
Leinonen, R., H. Sugawara, and M. Shumway. 2011. The sequence read
archive. Nucl. Acids Res. 39: D19–D21.
Lemmon,E.M., and A. R. Lemmon. 2013. High-throughput genomic data
in systematics and phylogenetics. Ann. Rev. Ecol. Evol. Syst. 44: 99–121.
Li, W., Q. Cong, J. Shen, J. Zhang, W. Hallwachs, D. H. Janzen, and
N.V.Grishin. 2019. Genomes of skipper butteries reveal extensive con-
vergence of wing patterns. Proc. Natl. Acad. Sci. USA 116: 6232–6237.
Lozier,J.D., and S.A.Cameron. 2009. Comparative genetic analyses of his-
torical and contemporary collections highlight contrasting demographic
histories for the bumble bees Bombus pensylvanicus and B.impatiens in
Illinois. Mol. Ecol. 18: 1875–1886.
Martin,M. 2011. Cutadapt removes adapter sequences from high-throughput
sequencing reads. EMBnet J. 17: 10–12.
Mayer,C., M.Sann, A.Donath, M.Meixner, L.Podsiadlowski, R.S.Peters,
M. Petersen, K. Meusemann, K. Liere, and J. W. Wägele, et al. 2016.
Insect Systematics and Diversity, 2021, Vol. 5, No. 2
Copyedited by: OUP
Downloaded from https://academic.oup.com/isd/article/5/2/6/6244279 by elsa.call.fr@gmail.com on 22 April 2021

10
BaitFisher: a software package for multispecies target DNA enrichment
probe design. Mol. Biol. Evol. 33: 1875–1886.
Mayer,C., L.Dietz, E.Call, S.Kukowka, S.Martin, and M.Espeland. 2021.
Adding leaves to the Lepidoptera tree: capturing hundreds of nuclear genes
from old museum specimens. Syst. Entomol. doi:10.1111/syen.12481.
McCormack, J. E., S. M. Hird, A. J. Zellmer, B. C. Carstens, and
R. T. Brumeld. 2013. Applications of next-generation sequencing to
phylogeography and phylogenetics. Mol. Phylogenet. Evol. 66: 526–538.
Minet, J. 1983. Étude morphologique et phylogénétique des organes
tympaniques des Pyraloidea. 1– Généralités et homologies (Lep. Glossata).
Ann. La Société Entomol. France 19: 175–207.
Minet, J. 1986. Ébauche d’une classication moderne de l’ordre des
Lepidoptères. Alexanor 14: 291–313.
Minet, J. 2002. The epicopeiidae: phylogeny and a redenition, with the
description of new taxa (Lepidoptera: Drepanoidea). Ann. La Société
Entomol. France 38: 463–487.
Neumann,D., A.V.Borisenko, J.A.Coddington, C.L.Häuser, C.R.Butler,
A.Casino, J.C. Vogel, G.Haszprunar, and P. Giere. 2018. Global bio-
diversity research tied up by juridical interpretations of access and benet
sharing. Organ. Divers. Evol. 18: 1–12.
Nguyen, L.-T., H. A. Schmidt, A. von Haeseler, and B. Q. Minh. 2015.
IQ-TREE: a fast and effective stochastic algorithm for estimating
maximum-likelihood phylogenies. Mol. Biol. Evol. 32: 268–274.
Rajaei, H., C. Greve, H. Letsch, D. Stüning, N. Wahlberg, J. Minet, and
B. Misof. 2015. Advances in Geometroidea phylogeny, with character-
ization of a new family based on Pseudobiston pinratanai (Lepidoptera,
Glossata). Zool. Scr. 44: 418–436.
Regier,J.C., A.Zwick, M.P.Cummings, A.Y.Kawahara, S.Cho, S.Weller,
A.Roe, J.Baixeras, J.W.Brown, and C.Parr, etal. 2009. Toward recon-
structing the evolution of advanced moths and butteries (Lepidoptera:
Ditrysia): an initial molecular study. BMC Evol. Biol. 9: 280.
Rota, J., T.Malm, N.Chazot, C.Peña, and N.Wahlberg. 2018. A simple
method for data partitioning based on relative evolutionary rates. PeerJ
6: e5498.
Schmieder,R., and R.Edwards. 2011. Quality control and preprocessing of
metagenomic datasets. Bioinformatics 27: 863–864.
Shapiro,B., and M.Hofreiter. 2012. Ancient DNA: methods and protocols.
Humana Press, New York, NY.
Silva, C., G. Besnard, A. Piot, J. Razanatsoa, R. P. Oliveira, and
M.S.Vorontsova. 2017. Museomics resolve the systematics of an endan-
gered grass lineage endemic to north-western Madagascar. Ann. Bot. 119:
339–351.
Sproul, J. S., and D. R. Maddison. 2017. Sequencing historical specimens:
successful preparation of small specimens with low amounts of degraded
DNA. Mol. Ecol. Resour. 17: 1183–1201.
StLaurent,R.A., C.A.Hamilton, and A.Y.Kawahara. 2018. Museum spe-
cimens provide phylogenomic data to resolve relationships of sack-bearer
moths (Lepidoptera, Mimallonoidea, Mimallonidae). Syst. Entomol. 43:
729–761.
Strutzenberger,P., G.Brehm, and K.Fiedler. 2012. DNA barcode sequencing
from old type specimens as a tool in taxonomy: a case study in the diverse
genus Eeois (Lepidoptera: Geometridae). PLoS One 7: e49710.
Suarez,A.V., and N.D.Tsutsui. 2004. The value of museum collections for
research and society. BioScience 54: 66.
Suchan, T., C. Pitteloud, N. S. Gerasimova, A. Kostikova, S. Schmid,
N. Arrigo, M. Pajkovic, M. Ronikier, and N. Alvarez. 2016.
Hybridization capture using RAD Probes (hyRAD), a new tool for
performing genomic analyses on collection specimens. PLoS One 11:
e0151651.
Toussaint,E.F.A., J.W.Breinholt, C. Earl, A.D.Warren, A.V.Z.Brower,
M.Yago, K.M.Dexter, M. Espeland, N.E.Pierce, and D. J.Lohman,
etal. 2018. Anchored phylogenomics illuminates the skipper buttery tree
of life. BMC Evol. Biol. 18: 101.
Turner,J.R.G. 1976. Adaptive radiation and convergence in subdivisions of
the buttery genus Heliconius (Lepidoptera: Nymphalidae). Zool. J.Linn.
Soc. 58: 297–308.
Vaudo,A.D., M.L.Fritz, and M.M.López-Uribe. 2018. Opening the door
to the past: accessing phylogenetic, pathogen, and population data from
museum curated bees. Insect Syst. Divers. 2: 4. doi:10.1093/isd/ixy014.
Wang,H., J.D.Holloway, N. Wahlberg, M.Wang, and S.Nylin. 2019.
Molecular phylogenetic and morphological studies on the sys-
tematic position of Heracula discivitta reveal a new subfamily of
Pseudobistonidae (Lepidoptera: Geometroidea). Syst. Entomol. 44:
211–225.
Wei,C.-H., and S.-H. Yen. 2017. Mimaporia, a new genus of Epicopeiidae
(Lepidoptera), with description of a new species from Vietnam. Zootaxa
4254: 537.
Zedane,L., C.Hong-Wa, J.Murienne, C.Jeziorski, B.G. Baldwin, and
G. Besnard. 2016. Museomics illuminate the history of an extinct,
paleoendemic plant lineage (Hesperelaea, Oleaceae) known from an
1875 collection from Guadalupe Island, Mexico. Biol. J. Linn. Soc.
117: 44–57.
Zhang,J., Q.Cong, J.Shen, E.Brockmann, and N.Grishin. 2019. Genomes
reveal drastic and recurrent phenotypic divergence in retip skipper
butteries (Hesperiidae: Pyrrhopyginae). Proc. R.Soc. B Biol. Sci. 286:
20190609.
Zhang,Y., S.Huang, D.Liang, H.Wang, and P. Zhang. 2020. A multilocus
analysis of Epicopeiidae (Lepidoptera, Geometroidea) provides new in-
sights into their relationships and the evolutionary history of mimicry.
Mol. Phylogenet. Evol. 149: 106847.
Insect Systematics and Diversity, 2021, Vol. 5, No. 2
Copyedited by: OUP
Downloaded from https://academic.oup.com/isd/article/5/2/6/6244279 by elsa.call.fr@gmail.com on 22 April 2021