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A Chromosome-Level Genome Assembly and Annotation
for the Clouded Apollo Butterfly (Parnassius mnemosyne):
A Species of Global Conservation Concern
6,1

Animal Ecology Program, Department of Ecology and Genetics (IEG), Uppsala University, Uppsala SE-752 36, Sweden

2

National Bioinformatics Infrastructure Sweden (NBIS), Science for Life Laboratory, Uppsala 752 37, Sweden

3

Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna 17165, Sweden

4

Uppsala Genome Center, Department of Immunology, Genetics and Pathology, Uppsala University, National Genomics Infrastructure

hosted by SciLifeLab, Uppsala, Sweden
5

Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala 752 37, Sweden

6

Evolutionary Biology Program, Department of Ecology and Genetics (IEG), Uppsala University, Uppsala SE-752 36, Sweden*Corresponding author: E-mail: niclas.backstrom@ebc.uu.se.
Accepted: February 10, 2024

Abstract
The clouded apollo (Parnassius mnemosyne) is a palearctic butterfly distributed over a large part of western Eurasia, but popu­
lation declines and fragmentation have been observed in many parts of the range. The development of genomic tools canhelp to shed light on the genetic consequences of the decline and to make informed decisions about direct conservation ac­
tions. Here, we present a high-contiguity, chromosome-level genome assembly of a female clouded apollo butterfly and pro­vide detailed annotations of genes and transposable elements. We find that the large genome (1.5 Gb) of the clouded apollo
is extraordinarily repeat rich (73%). Despite that, the combination of sequencing techniques allowed us to assemble all chro­mosomes (nc = 29) to a high degree of completeness. The annotation resulted in a relatively high number of protein-coding
genes (22,854) compared with other Lepidoptera, of which a large proportion (21,635) could be assigned functions based on
homology with other species. A comparative analysis indicates that overall genome structure has been largely conserved,
both within the genus and compared with the ancestral lepidopteran karyotype. The high-quality genome assembly and de­tailed annotation presented here will constitute an important tool for forthcoming efforts aimed at understanding the gen­etic consequences of fragmentation and decline, as well as for assessments of genetic diversity, population structure,
inbreeding, and genetic load in the clouded apollo butterfly.
Key words: Parnassius mnemosyne, clouded apollo butterfly, genome assembly, gene annotation, repeat annotation, gen­ome size.

© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits
non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

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Jacob Höglund1, Guilherme Dias2, Remi-André Olsen3, André Soares2, Ignas Bunikis4,5, Venkat Talla
and Niclas Backström 6,*

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Höglund et al.

SignificanceIntroduction
Genomic data can be used to inform practical conservation
efforts of threatened species, a research field generally re­ferred to as conservation genomics (e.g. Hohenlohe et al.
2021; DeWoody et al. 2022). Genomic approaches have,for example, proven useful to infer demographic histories,
to estimate genetic diversity and inbreeding, and to quan­tify genetic load (Supple and Shapiro 2018; Wright et al.
2020; Bortoluzzi et al. 2023; Theissinger et al. 2023), infor­
mation that is crucial for informed conservation actions for
species that are rare or endangered and/or difficult to moni­
tor with traditional methods (DeWoody et al. 2022; Hogg
et al. 2022). Conservation genomic efforts have traditional­
ly been focused on flagship species that comprise a small
proportion of the extant biodiversity (Bortoluzzi et al.
2023). Butterflies and moths (Lepidoptera), for example,
comprise over 150,000 species (Triant et al. 2018), but
compared with mammals and birds, they are extensively
overlooked in assessments of species under conservation
concern (Cardoso et al. 2011; Podsiadlowski et al. 2021;
Duffus and Morimoto 2022; Bortoluzzi et al. 2023). Many
lepidopterans have also been reported to be rapidly declin­
ing in number (e.g. Cardoso et al. 2020; Warren et al.
2021), a major concern since they often constitute key indi­cator species for ecosystem functioning (Schowalter et al.
2018; Warren et al. 2021).
Several initiatives have been started, aiming at generat­
ing genomic data for specific organism groups (e.g. 5,000
insect genomes [i5k]; Sills et al. 2011), for biodiversity incertain countries (e.g. The Darwin Tree of Life [DToL]
Project Consortium et al. 2022) or larger geographicalregions (e.g. The European Reference Genome Atlas[ERGA]; Mc Cartney et al. 2023). While such initiatives arepromising for future access to genome information for alarge proportion of the extant biodiversity, targeted efforts
are needed to swiftly get data for species under immediate
conservation concern. As part of the ERGA pilot effort (McCartney et al. 2023), we present a high-contiguity genome
assembly and detailed annotation of the clouded apollo(Parnassius mnemosyne), a butterfly of general conserva­
tion concern (Gratton et al. 2008; Bolotov et al. 2013;
Talla et al. 2023). The clouded apollo is widely distributed

across the western Palearctic, but population numbers
have declined dramatically in many regions (Kuussaari
et al. 2015; Johansson et al. 2017; Talla et al. 2023), likely
a consequence of a decline in the preferred habitat—
mosaics of low-intensity grazed pastures intermixed withsheltering vegetation and rich access to host plants
Corydalis sp. (Konvič ka and Kuras 1999; Luoto et al. 2001;
Kuussaari et al. 2015; Johansson et al. 2017). Previous gen­etic analyses have unveiled considerable population struc­ture, both across the distribution range in general(Gratton et al. 2008) and between populations in specificregions (e.g. Sweden; Talla et al. 2023), but currently avail­able data are insufficient for detailed assessment of demog­
raphy, genetic load, and levels of genetic diversity. The
chromosome-level genome assembly we developed here
will therefore be a useful tool for forthcoming investiga­
tions of inbreeding, local adaptation and loss of genetic di­versity in the clouded apollo, and comparative genomic
analyses in Lepidoptera in general (Bortoluzzi et al. 2023).

Results
Assembly statistics are presented in Table 1. We predicted
a genome size of ∼1.4 Gbp and a genome-wide heterozygos­
ity (π) of 0.74% (supplementary fig. S1, Supplementary
Material online). The mean GC content was 37.8%, and nu­
cleotide composition was stable across all chromosomes(Fig. 1). The assembly had high contiguity, with the longest 29
scaffolds (≥25 Mbp) comprising 95.2% of the total length. Of
the 29 longest scaffolds, 10 contained telomere sequences atboth ends, 13 at 1 end, and only 5 lacked telomere sequencescompletely (Fig. 1). We estimated the quality metrics recom­
mended by the Earth BioGenome Project (https://www.earth
biogenome.org/analysis-standards-report) and found highbase pair quality scores and a low rate of false duplications(supplementary table S1, Supplementary Material online).
The results from the Benchmarking Universal
Single-Copy Orthologs (BUSCO) analysis indicate that theassembly completeness is very high, with 99.0% of the5,286 analyzed genes completely covered (Table 1,
supplementary table S2, Supplementary Material online).
A BUSCO analysis using the bacteria_odb10 gene set did

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The quality of the assembly of the clouded apollo (Parnassius mnemosyne) genome and the annotation of genes are wellin line with the standards of the Earth BioGenome Project (https://www.earthbiogenome.org/analysis-standardsreport). The analyses revealed a comparatively large genome with a high repeat content for a butterfly and considerable
synteny compared with both a close and a distant lepidopteran relative. We therefore predict that the genomic re­sources provided here will be important tools for forthcoming investigations aimed at understanding demographic his­
tory, loss of genetic variation, population structure, and mutation load in the clouded apollo butterfly in particular andfor comparative genomic approaches in Lepidoptera in general.

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Parnassius mnemosyne Genome Assembly

Table 1
Summary statistics for the P. mnemosyne genome assembly
Assembly statistics

Value
1,494,393,142
169
49.64
34.77
285
23.93
4.73
38
22,854
21,635
1,076
4,788
16,610
99.0%
97.8%
1.2%
0.2%
0.8%

bp, base pairs; Mb, mega bases; #, number of. The BUSCO analysis was based
on 5,286 lepidopteran genes.

not identify any genes of bacterial origin in the final
assembly.
The mtDNA contig was 15,425 bp, with 18.3% GC. The
gene composition was typical for an insect mtDNA, with 13
protein-coding genes, 22 transfer RNA (tRNA) genes, and 2
ribosomal RNA (rRNA) genes (supplementary fig. S2,
Supplementary Material online). The gene order was
similar to that of the close relative Parnassius apollo(Chen et al. 2014) and more distantly related Lepidopterasuch as the Monarch (Danaus plexippus; https://www.
ncbi.nlm.nih.gov/nuccore/NC_021452.1) and the silkworm(Bombyx mori; https://www.ncbi.nlm.nih.gov/nuccore/NC_
002355.1).
The automatized repeat annotation revealed that the
majority of classified repeats was retroelements but also ahigh proportion of unclassified repeats (supplementarytable S3, Supplementary Material online). We therefore
made a more detailed analysis of repeats using partly
manually curated repeat libraries for other butterfly species.
This analysis showed that the overall proportion of repeats
was significantly higher (72.90%) than with the automa­
tized pipeline (61.53%) (supplementary table S4,
Supplementary Material online). Both the clouded apollo
and the close relative, apollo P. apollo (Podsiadlowski
et al. 2021), have comparatively large genome sizes and ahigh repeat content. We therefore compared the relative
contribution of different repeat classes to the genome sizes
in both species using the same pipeline. This analysis re­vealed that the apollo has a higher repeat content thanDiscussion
The assembly of the clouded apollo genome resulted in 29
chromosome-sized scaffolds where the majority seems tohave sequence information including the telomeric re­peats (data not shown). This is compatible with achromosome-scale assembly since the clouded apollo
has been shown to have 29 chromosomes (Vlašánek
et al. 2017). The shorter contigs, not associated with thelarger scaffolds, constituted a minute fraction of the entire
assembly and can be omitted from most types of down­
stream analyses without risks for biased results. We pre­dicted a considerably larger set of coding genes(∼22,800) compared with most other lepidopterans withannotated genome sequences (e.g. Shipilina et al. 2022;
Smolander et al. 2022; Höök et al. 2023). However, thegene number was lower than the estimated number(∼28,300) in the close relative P. apollo (Podsiadlowski
et al. 2021), likely a consequence of the more fragmented
genome assembly and/or the less strict annotation of re­peats in this species (Shipilina et al. 2022). The repeat con­tent is high in P. mnemosyne compared with otherlepidopterans, and this can lead to overestimation of thenumber of coding genes (e.g. Baril and Hayward 2022;
Shipilina et al. 2022; Höök et al. 2023). It should also be
noted that, with the exception of well-conserved families,
many of the predicted ncRNAs should be considered withcare.

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Assembly length (bp)# Scaffolds
Scaffold N50 (Mb)
Scaffold N90 (Mb)
# Contigs
Contig N50 (Mb)
Contig N90 (Mb)
GC content (%)
Gene annotation# Protein-coding genes# Genes with functional information# tRNA genes# Putative pseudogenes# Putative ncRNA genes
BUSCO analysis
Complete
Single-copy
DuplicatedFragmented
Missing

the clouded apollo and that the difference predominantly
has been driven by expansions of long interspersed nuclear
elements (LINEs), long terminal repeats (LTRs), and DNA
transposons in the apollo (supplementary fig. S3,
Supplementary Material online).
The structural annotation of coding sequences identified
22,854 genes and 27,378 transcripts (Table 1). A complete­ness assessment of the predicted proteins (longest isoform
used) indicated complete coverage of 96.3% of the5,286 lepidopteran BUSCOs (supplementary table S5,
Supplementary Material online). A total of 21,635(94.7%) of the identified genes could be assigned a func­
tional annotation with 14,890 unique gene names(Table 1, supplementary table S6, Supplementary Material
online). We also predicted 1,076 putative tRNA genes,
4,788 putative pseudogenes, and 16,610 ncRNAs (includ­ing the tRNAs; Table 1).
The alignments between larger scaffolds revealed a highdegree of synteny conservation between the 2 Apollo
species (supplementary fig. S4, Supplementary Material
online). The comparison between P. mnemosyne andB. mori unveiled a high degree of collinearity of aligned
fragments within most scaffolds (supplementary fig. S5,
Supplementary Material online).

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Höglund et al.

The detailed repeat annotation of both Parnassius spe­
cies confirmed that the extreme genome sizes are a conse­
quence of accumulation of a high number of transposable
elements (TEs) (Podsiadlowski et al. 2021). LINEs in particu­
lar constitute a large portion of the genome in both species,
but also LTRs, DNA transposons, and short interspersed nu­
clear elements (SINEs) are present in high numbers.
Another Parnassius species (Parnassius orleans) has an esti­
mated genome size of 1.2 Gb (Liu et al. 2020), which showsthat large genomes are ubiquitous in the genus and thatthe accumulation of TEs predominantly has occurred before
the radiation of currently extant Parnassius lineages (Liuet al. 2020; Wiemers et al. 2020; Podsiadlowski et al.
2021). However, in contrast to other butterflies with large
genomes and high TE content (e.g. Leptidea sp.; Talla
et al. 2017; Höök et al. 2023) and in agreement with previ­
ous results (Podsiadlowski et al. 2021), our results showthat the overall genome structure is relatively conserved
in Parnassius.

Methods
DNA and RNA Extractions and Library Preparations
Two adult female clouded apollos from a captive
population, recently established (2019) from a natural
population (Blekinge; Talla et al. 2023) to aid the con­servation actions in Sweden (https://en.nordensark.se/
conservation/), were used for sequencing (sampled2021 May 11). One individual (PM1) was used for
PacBio HiFi sequencing and the other individual (PM2)for Illumina Hi-C and RNA-sequencing. For the PacBio
HiFi and Illumina Hi-C libraries, frozen muscle tissue
from the thorax was ground with pestle and mortar.
Muscle tissue was also used for RNA-sequencing with
Illumina short inserts and PacBio Iso-Seq. High molecularweight DNA was extracted from the muscle tissue using
SDS lysis, followed by phenol:chloroform:isoamyl alco­hol (25:24:1) treatment. DNA was precipitated with ahigh salt/low ethanol solution, washed twice with 70%

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FIG. 1.—The structure of the clouded apollo (P. mnemosyne) genome assembly for the 29 largest scaffolds (>25 Mb). Scaffolds are scaled by relative size
and regional repeat (heat map) and GC content (blue polygons to the right of each scaffold) are indicated. Colors below each scaffold indicate if the scaffold
contains both telomeres (n = 10, orange), 1 telomere (n = 13, blue), or no telomeres (n = 6, pale yellow). Dark horizontal bars indicate the center of eachscaffold.

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Parnassius mnemosyne Genome Assembly

Genome Assembly
The genome was assembled using a combination of PacBio(HiFi) and Illumina Hi-C data (supplementary table S7,
Supplementary Material online). The HiFi reads had a cover­age of ∼30× and were assembled using Hifiasm v0.16.0(Cheng et al. 2021). Purge_Dups v1.2.5 (Guan et al.
2020) was used to remove putative duplications. The Hi-C
sequence reads were aligned to the purged assembly andprocessed with pairtools v0.3.0 (Abdennur et al. 2023),
and contigs were scaffolded with YaHS v1.1a (Zhou et al.
2022). Hi-C scaffolds were manually edited with JBAT
v2.20.00 (Dudchenko et al. 2018), using the Hi-C contact
maps and telomere motif annotation from tidk v0.2.31(https://github.com/tolkit/telomeric-identifier) to produce
the final assembly.
Potential contamination was assessed using Mash v2.3
(Ondov et al. 2019) and the National Center for
Biotechnology Information (NCBI) RefSeq database (https://
gembox.cbcb.umd.edu/mash/refseq.genomes.k21s1000.
msh), and no substantial contamination was found. Genome
properties were estimated from both the HiFi reads and thefinal assembly using the k-mer counter FastK (https://github.
com/thegenemyers/FASTK) with 31 mers and GeneScopeFK(https://github.com/thegenemyers/GENESCOPE.FK), a modi­
fied version of GenomeScope v2.0 (Ranallo-Benavidez et al.
2020). Additionally, MERQURY.FK (https://github.com/thegenemyers/MERQURY.FK) was used to estimate the k-mer
completeness and the false duplication rate. Assembly
quality was assessed with general statistics (Table 1), andcompleteness and duplication rate were evaluated using
BUSCO v5.4.6 (Manni et al. 2021), with the lepidopter­a_odb10 gene set from OrthoDB v10 (Kriventseva et al.
2018). The mitochondrial genome was recovered from theprimary assembly after haplotig removal using MitoHiFi v2.2
(Uliano-Silva et al. 2023) and annotated using MitoFinder
v1.4.1 (Allio et al. 2020). The mtDNA assembly was reoriented
to match the P. apollo mtDNA assembly (NCBI accession
NC_024727.1; Chen et al. 2014).

Genome Annotation
A custom repeat library was created with RepeatModeler2
v2.0.2a (Flynn et al. 2020), and the genome was softmasked with RepeatMasker (https://www.repeatmasker.
org/) v4.1.5 prior to gene annotation. The candidate re­peats obtained by RepeatModeler were vetted against
UniProt/SwissProt to exclude nucleotide motifs stemmingfrom protein-coding sequences. For comparative purposes,
we also generated a detailed annotation of the different
classes of repeats present in the genomes of both the apollo(Podsiadlowski et al. 2021) and the clouded apollo butterfly
and estimated the proportions of the genomes covered byeach class of repeat, again using RepeatModeler2 v2.0.2a(Flynn et al. 2020), but including manually curated repeat
libraries from other butterfly species (Shipilina et al. 2022;
Höök et al. 2023).
Gene prediction was performed in 3 steps that were later
combined, incorporating standard RNA-seq, protein se­quences from multiple organisms, and PacBio Iso-Seq as
evidence. (i) The RNA-seq reads for P. mnemosyne (Table 1)
were aligned to the assembly with HiSat2 v2.1.0 (Kim et al.
2019), and BRAKER v3.0.3 (Gabriel et al. 2023) was used to
extract splicing signals and to train and predict genes using
Augustus. (ii) Arthropod proteins from OrthoDB v11(https://bioinf.uni-greifswald.de/bioinf/partitioned_odb11;
Kriventseva et al. 2018) were aligned to the assembly withminiprot v0.10-r226-dirty (Li, 2023) and used to train andpredict genes with Augustus within the GALBA pipeline
v1.0.6 (Brů na et al. 2023). (iii) High-quality transcripts
from PacBio Iso-Seq were aligned to the genome using
minimap2
v2.26(https://github.com/lh3/minimap2/
releases) and used to obtain gene predictions with
GeneMarkS-T v5.1 (Tang et al. 2015), following the longread protocol from BRAKER (https://github.com/GaiusAugustus/BRAKER/blob/master/docs/long_reads/long_read_
protocol.md). Finally, the gene models from BRAKER,GALBA, and GeneMarkS-T were combined and filteredusing TSEBRA (long_reads branch, commit 1f2614c;
Gabriel et al. 2021). The combined gene models were pro­
cessed with AGAT v1.2.0 (https://zenodo.org/record/
8178877) to remove overlapping genes, and functional an­
notation was done using the NBIS functional_annotation
nextflow pipeline v2.0.0 (https://github.com/NBISweden/
pipelines-nextflow) which uses BLAST for similarity searches
between the annotated proteins and the UniProtKB/
SwissProt database (Magrane and UniProt Consortium2011) (downloaded 2022 to 2012; 568,363 proteins),
InterProScan (Jones et al. 2014) to query the proteins
against InterPro v59-91 (Paysan-Lafosse et al. 2022), andmerge results using AGAT (https://zenodo.org/record/
8178877). To reduce potential false-positives, single-exon
genes without any InterPro annotation were removed.
Each predicted protein sequence was blasted against the

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ethanol, and eluted in TE buffer. RNA was also extracted frommuscle tissue using a standard TRIzol protocol including
DNase treatment (RNeasy, Invitrogen). Eluted RNA was storedat −70 °C. The PacBio HiFi library preparation and sequencing
was performed at the National Genomics Infrastructure (NGI)
node in Uppsala, Sweden. All DNA and RNA extractions weredone at Uppsala Genome Center (https://www.ugc.igp.uu.
se/). Both RNA-Seq libraries and the Illumina Hi-C librarywere prepared at the ERGA node in Antwerp, Belgium, andsequenced at the node in Florence, Italy. Both individuals
were kept as voucher specimens (PM1; ERGA-ID:
ilParMnem1 as UPSZTY 184741 and PM2 as UPSZTY
184901) and stored at the Evolution Museum at Uppsala
University (supplementary fig. S6, Supplementary Material
online).

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Supplementary Material
Supplementary material is available at Genome Biology and
Evolution online.

Acknowledgments
The authors would also like to acknowledge the support
from the Science for Life Laboratory (SciLifeLab), NGI,
and Uppsala Multidisciplinary Center for Advanced
Computational Science (UPPMAX) for providing assistancein massive parallel sequencing and computational infra­
structure. The computations were performed on resources
provided by the SNIC through the Uppsala Multidisciplinary
Center for Advanced Computational Science (UPPMAX)
under the Project SNIC 2020-5-20. We thank Veronika
Mrazek for the help with the dissections.

Author Contributions
J.H.: conceived of the project, project management, manu­
script writing, and acquisition of funding. G.D.: assembly
QC, structural and functional annotation, and manuscript
writing. R.-A.O.: Hi-C scaffolding and Hi-C curation. A.S.:
assembly QC, assembly curation, and mitogenome assem­
bly. I.B.: contig assembly with Hifiasm. V.T.: analysis of re­peat content and report writing. N.B.: conceived of the
project, project management, synteny analysis, manuscript
writing, and acquisition of funding.

Funding
This work was supported by the Swedish Research Council(VR research grant #019-04791 to N.B.), NBIS/SciLifeLablong-term bioinformatics support (WABI to N.B.), andSwedish Rescue Program for P. mnemosyne through thelocal administrative board (Länsstyrelsen) of Blekinge (toJ.H. and N.B.).

Data Availability
All data have been deposited at the European Nucleotide
Archive under accession PRJEB67749. Scripts used for the
TE analysis are available at GitHub (https://github.com/
EBC-butterfly-genomics-team/clouded_apollo_genomics).
Assembly and annotation files are also available via
the ERGA portal (https://portal.erga-biodiversity.eu/data_
portal/Parnassius%20mnemosyne).

Literature Cited
Abdennur N, Fudenberg G, Flyamer IM, Galitsyna AA, Goloborodko A,
Imakaev M, Venev SV. Pairtools: from sequencing data to chromo­
some contacts. bioRxiv 2023.02.13.528389. https://doi.org/10.
1101/2023.02.13.528389., 15 February 2023, preprint: not peer
reviewed.
Allio R, Schomaker-Bastos A, Romiguier J, Prosdocimi F, Nabholz B,
Delsuc F. MitoFinder: efficient automated large-scale extractionof mitogenomic data in target enrichment phylogenomics. Mol
Ecol Resour. 2020:20(4):892–905. https://doi.org/10.1111/17550998.13160.
Baril T, Hayward A. Migrators within migrators: exploring transposable
element dynamics in the monarch butterfly, Danaus plexippus.
Mob DNA. 2022:13(1):5. https://doi.org/10.1186/s13100-02200263-5.
Bolotov I, Gofarov M, Frolov A, Kogut Y. Northern boundary of therange of the clouded apollo butterfly Parnassius mnemosyne (L.)(Papilionidae): climate influence or degradation of larval hostplants? Nota Lepidopterol. 2013:36:19–33.
Bortoluzzi C, Wright CJ, Lee S, Cousins T, Genez TAL, Thybert D,
Martin FJ, Haggerty L, The Darwin Tree of Life Project
Consortium, M., Blaxter M, et al. (2023). Lepidoptera
genomics based on 88 chromosomal reference sequences
informs population genetic parameters for conservation.
bioRxiv 2023.04.14.536868. https://doi.org/10.1101/2023.04.
14.536868., 14 April, 2023, preprint: not peer reviewed.
Brů na T, Li H, Guhlin J, Honsel D, Herbold S, Stanke M, Nenasheva N,
Ebel M, Gabriel L, Hoff KJ. Galba: genome annotation with mini­prot and AUGUSTUS. BMC Bioinformatics. 2023:24(1):327.
https://doi.org/10.1186/s12859-023-05449-z.
Cabanettes F, Klopp C. D-GENIES: dot plot large genomes in an inter­
active, efficient and simple way. PeerJ. 2018:6:e4958. https://doi.
org/10.7717/peerj.4958.
Cardoso P, Barton PS, Birkhofer K, Chichorro F, Deacon C, Fartmann T,
Fukushima CS, Gaigher R, Habel JC, Hallmann CA, et al.
Scientists’ warning to humanity on insect extinctions. Biol
Conserv. 2020:242:108426. https://doi.org/10.1016/j.biocon.
2020.108426.
Cardoso P, Borges PAV, Triantis KA, Ferrández MA, Martín JL.
Adapting the IUCN Red List criteria for invertebrates. Biol
Conserv. 2011:144(10):2432–2440. https://doi.org/10.1016/j.
biocon.2011.06.020.
Chen Y, Huang D, Wang Y, Zhu C, Hao J. The complete mitochondrial
genome of the endangered apollo butterfly, Parnassius apollo(Lepidoptera: Papilionidae) and its comparison to other
Papilionidae species. J Asia Pac Entomol. 2014:17(4):663–671.
https://doi.org/10.1016/j.aspen.2014.06.002.

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UniProt/SwissProt reference data set (downloaded 2022 to2012) in order to infer, when available, the gene and pro­tein name. The inference was made using the best hit
with a maximum e-value cutoff of 1*10−6. Gene namesthat were encountered several times were suffixed tokeep each gene name unique (complete list of gene names
is available upon request). tRNAs were predicted using
tRNAscan-SE v2.0.12 (https://github.com/UCSC-LoweLab/tRNAscan-SE) with default parameters for eukaryotes.
Noncoding RNAs (ncRNAs) were predicted with Infernal
v1.1.4 (Nawrocki and Eddy 2013) and the Rfam v14.1 co­variance models (Nawrocki et al. 2014).
To assess synteny conservation, whole genome align­
ments between P. mnemosyne and P. apollo and B. mori,respectively, were done using D-GENIES (Cabanettes andKlopp 2018) with default settings. The scaffold plot in
Fig. 1 was generated with the R package RIdeogram (Haoet al. 2020).

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Parnassius mnemosyne Genome Assembly

protein function classification. Bioinformatics. 2014:30(9):1236–1240. https://doi.org/10.1093/bioinformatics/btu031.
Kim D, Paggi JM, Park C, Bennett C, Salzberg SL. Graph-based
genome alignment and genotyping with HISAT2 and
HISAT-genotype. Nat Biotechnol. 2019:37(8):907–915. https://doi.org/10.1038/s41587-019-0201-4.
Konvič ka M, Kuras T. Population structure, behaviour and selection of
oviposition sites of an endangered butterfly, Parnassius mnemos­yne, in Litovelské Pomoravíl. Czech Republic. J Insect Conserv.
1999:3(3):211–223. https://rdcu.be/dnSNW https://doi.org/10.
1023/A:1009641618795.
Kriventseva EV, Kuznetsov D, Tegenfeldt F, Manni M, Dias R, Simão FA,
Zdobnov EM. OrthoDB v10: sampling the diversity of animal, plant,
fungal, protist, bacterial and viral genomes for evolutionary andfunctional annotations of orthologs. Nucleic Acids Res.
2018:47(D1):D807–D811. https://doi.org/10.1093/nar/gky1053.
Kuussaari M, Heikkinen RK, Heliölä J, Luoto M, Mayer M, Rytteri S,
vonBagh P. Successful translocation of the threatened clouded
apollo butterfly (Parnassius mnemosyne) and metapopulation es­
tablishment in southern Finland. Biol Conserv. 2015:190:51–59.
https://doi.org/10.1016/j.biocon.2015.05.011.
Li H. Protein-to-genome alignment with miniprot. Bioinformatics. 2023:
39(1):btad014. https://doi.org/10.1093/bioinformatics/btad014.
Liu G, Chang Z, Chen L, He J, Dong Z, Yang J, Lu S, Zhao R, Wan W, MaG,
et al. Genome size variation in butterflies (Insecta, Lepidotera,
Papilionoidea): a thorough phylogenetic comparison. Syst Entomol.
2020:45(3):571–582. https://doi.org/10.1111/syen.12417.
Luoto M, Kuussaari M, Rita H, Salminen J, von Bonsdorff T.
Determinants of distribution and abundance in the clouded apollobutterfly: a landscape ecological approach. Ecography 2001:24(5):601–617. https://doi.org/10.1111/j.1600-0587.2001.tb00494.x.
Magrane M, UniProt Consortium. UniProt knowledgebase: a hub of in­tegrated protein data. Database (Oxford). 2011:2011(0):bar009.
https://doi.org/10.1093/database/bar009.
Manni M, Berkeley MR, Seppey M, Simão FA, Zdobnov EM. BUSCO up­
date: novel and streamlined workflows along with broader anddeeper phylogenetic coverage for scoring of eukaryotic, prokaryot­
ic, and viral genomes. Mol Biol Evol. 2021:38(10):4647–4654.
https://doi.org/10.1093/molbev/msab199.
Mc Cartney AM, Formenti G, Mouton A, Panis DD, Marins LS,
LeitaoHG, Diedericks G, Kirangwa J, Morselli M, Salces J,
et al.The European Reference Genome Atlas: piloting adecentralised approach to equitable biodiversity genomics.
bioRxiv 2023.09.25.559365. https://doi.org/10.1101/2023.09.
25.559365., 28 September, 2023, preprint: not peer reviewed.
Nawrocki EP, Burge SW, Bateman A, Daub J, Eberhardt RY, Eddy SR,
Floden EW, Gardner PP, Jones TA, Tate J, et al. Rfam 12.0: updates
to the RNA families database. Nucleic Acids Res. 2014:43(D1):
D130–D137. https://doi.org/10.1093/nar/gku1063.
Nawrocki EP, Eddy SR. Infernal 1.1: 100-fold faster RNA homology
searches. Bioinformatics. 2013:29(22):2933–2935. https://doi.
org/10.1093/bioinformatics/btt509.
Ondov BD, Starrett GJ, Sappington A, Kostic A, Koren S, Buck CB,
Phillippy AM. Mash screen: high-throughput sequence contain­
ment estimation for genome discovery. Genome Biol.
2019:20(1):232. https://doi.org/10.1186/s13059-019-1841-x.
Paysan-Lafosse T, Blum M, Chuguransky S, Grego T, Pinto BL, Salazar
GA, Bileschi ML, Bork P, Bridge A, Colwell L, et al. InterPro in 2022.
Nucleic Acids Res. 2022:51(D1):D418–D427. https://doi.org/10.
1093/nar/gkac993.
Podsiadlowski L, Tunström K, Espeland M, Wheat CW. The genome as­sembly and annotation of the apollo butterfly Parnassius apollo, aflagship species for conservation biology. Genome Biol Evol.
2021:13(8):evab122. https://doi.org/10.1093/gbe/evab122.

Genome Biol. Evol. 16(2) https://doi.org/10.1093/gbe/evae031 Advance Access publication 18 February 2024

7

Downloaded from https://academic.oup.com/gbe/article/16/2/evae031/7610114 by Uppsala Universitetsbibliotek user on 04 April 2024

Cheng H, Concepcion GT, Feng X, Zhang H, Li H. Haplotype-resolved
de novo assembly using phased assembly graphs with Hifiasm. Nat
Methods. 2021:18(2):170–175. https://doi.org/10.1038/s41592020-01056-5.
DeWoody JA, Jeon JY, Bickham JW, Heenkenda EJ, Janjua S, Lamka
GF, Mularo AJ, Black A, Brüniche-Olsen A, Willoughby JR. The
threatened species imperative: conservation assessments would
benefit from population genomic insights. Proc Natl Acad Sci.
2022:119(35):e2210685119. https://doi.org/10.1073/pnas.2210
685119.
Dudchenko O, Shamim MS, Batra SS, Durand NC, Musial NT, Mostofa
R, Pham M, Hilaire BGS, Yao W, Stamenova E, et al. The Juicebox
assembly tools module facilitates de novo assembly of mammalian
genomes with chromosome-length scaffolds for under $1000.
bioRxiv 254797. https://doi.org/10.1101/254797, 28 January,
2018, preprint: not peer reviewed.
Duffus NE, Morimoto J. Current conservation policies in the UK and
Ireland overlook endangered insects and are taxonomically biased
towards Lepidoptera. Biol Conserv. 2022:266:109464. https://doi.
org/10.1016/j.biocon.2022.109464.
Flynn JM, Hubley R, Goubert C, Rosen J, Clark AG, Feschotte C, Smit
AF. RepeatModeler2 for automated genomic discovery of trans­posable element families. Proc Natl Acad Sci. 2020:117(17):9451–9457. https://doi.org/10.1073/pnas.1921046117.
Gabriel L, Brů na T, Hoff KJ, Ebel M, Lomsadze A, Borodovsky M, Stanke
M. BRAKER3: fully automated genome annotation using RNA-seq
and protein evidence with GeneMark-ETP, AUGUSTUS and
TSEBRA. bioRxiv 2023.06.10.544449. https://doi.org/10.1101/
2023.06.10.544449., 12 June, 2023, preprint: not peer reviewed.
Gabriel L, Hoff KJ, Brů na T, Borodovsky M, Stanke M. TSEBRA: tran­
script selector for BRAKER. BMC Bioinformatics. 2021:22(1):566.
https://doi.org/10.1186/s12859-021-04482-0.
Gratton P, Konopinski MK, Sbordoni V. Pleistocene evolutionary his­
tory of the clouded apollo (Parnassius mnemosyne): genetic signa­tures of climate cycles and a ‘time-dependent’ mitochondrial
substitution rate. Mol Ecol. 2008:17(19):4248–4262. https://doi.
org/10.1111/j.1365-294X.2008.03901.x.
Guan D, McCarthy SA, Wood J, Howe K, Wang Y, Durbin R. Identifying
and removing haplotypic duplication in primary genome assem­
blies. Bioinformatics. 2020:36(9):2896–2898. https://doi.org/10.
1093/bioinformatics/btaa025.
Hao Z, Lv D, Ge Y, Shi J, Weijers D, Yu G, Chen J. RIdeogram: drawing
SVG graphics to visualize and map genome-wide data on the idio­
grams. Peer J Comput Sci. 2020:6:e251. https://doi.org/10.7717/
peerj-cs.251.
Hogg CJ, Ottewell K, Latch P, Rossetto M, Biggs J, Gilbert A, RichmondS, Belov K. Threatened Species Initiative: empowering conservation
action using genomic resources. Proc Natl Acad Sci. 2022:119(4):e2115643118. https://doi.org/10.1073/pnas.2115643118.
Hohenlohe PA, Funk WC, Rajora OP. Population genomics for wild-life
conservation and management. Mol Ecol. 2021:30(1):62–82.
https://doi.org/10.1111/mec.15720.
Höök L, Näsvall K, Vila R, Wiklund C, Backström N. High-density link­
age maps and chromosome level genome assemblies unveil direc­
tion and frequency of extensive structural rearrangements in wood
white butterflies (Leptidea spp.). Chromosome Res. 2023:31(1):2.
https://doi.org/10.1007/s10577-023-09713-z.
Johansson V, Knape J, Franzén M. Population dynamics and future per­sistence of the clouded apollo butterfly in southern Scandinavia:
the importance of low intensity grazing and creation of habitat
patches. Biol Conserv. 2017:206:120–131. https://doi.org/10.
1016/j.biocon.2016.12.029.
Jones P, Binns D, Chang H-Y, Fraser M, Li W, McAnulla C, McWilliam H,
Maslen J, Mitchell A, Nuka G, et al. InterProScan 5: genome-scale

GBE

Höglund et al.

Hollingsworth P, Wilson W, et al. Sequence locally, thinkglobally: The Darwin Tree of Life Project. Proc Natl Acad
Sci. 2022:119(4):e2115642118. https://doi.org/10.1073/pnas.
2115642118.
Theissinger K, Fernandes C, Formenti G, Bista I, Berg PR, Bleidorn C,
Bombarely A, Crottini A, Gallo GR, Godoy JA, et al. How genomics
can help biodiversity conservation. Trends Genet. 2023:39(7):545–559. https://doi.org/10.1016/j.tig.2023.01.005.
Triant DA, Cinel SD, Kawahara AY. Lepidoptera genomes:
current knowledge, gaps and future directions. Curr Opin
Insect Sci. 2018:25:99–105. https://doi.org/10.1016/j.cois.2017.
12.004.
Uliano-Silva M, Ferreira JGRN, Krasheninnikova K, Blaxter M,
Mieszkowska N, Hall N, Holland P, Durbin R, Richards T, Kersey P,
et al. MitoHiFi: a python pipeline for mitochondrial genome as­sembly from PacBio high fidelity reads. BMC Bioinformatics.
2023:24(1):288. https://doi.org/10.1186/s12859-023-05385-y.
Vlašánek P, Bartonova AS, Marec F, Konvicka M. Elusive Parnassius
mnemosyne (Linnaeus, 1758) larvae: habitat selection, sex deter­
mination and sex ratio (Lepidoptera: Papilionidae). SHILAPRevista de Lepidopterología. 2017:45:180. https://www.redalyc.
org/journal/455/45553890003/movil/
Warren MS, Maes D, van Swaay CAM, Goffart P, Dyck HV, Bourn NAD,
Wynhoff I, Hoare D, Ellis S. The decline of butterflies in Europe: pro­blems, significance, and possible solutions. Proc Natl Acad Sci.
2021:118(2):e2002551117. https://doi.org/10.1073/pnas.20025
51117.
Wiemers M, Chazot N, Wheat CW, Schweiger O, Wahlberg N. A com­plete time-calibrated multi-gene phylogeny of the European
butterflies. ZooKeys 2020:938:97–124. https://doi.org/10.3897/
zookeys.938.50878.
Wright BR, Farquharson KA, McLennan EA, Belov K, Hogg CJ, Grueber
CE. A demonstration of conservation genomics for threatened spe­
cies management. Mol Ecol Resour. 2020:20(6):1526–1541.
https://doi.org/10.1111/1755-0998.13211.
Zhou C, McCarthy SA, Durbin R. YaHS: yet another Hi-C scaffolding
tool. Bioinformatics. 2022:39(1):btac808. https://doi.org/10.
1093/bioinformatics/btac808.
Associate editor: John Wang

8 Genome Biol. Evol. 16(2) https://doi.org/10.1093/gbe/evae031 Advance Access publication 18 February 2024

Downloaded from https://academic.oup.com/gbe/article/16/2/evae031/7610114 by Uppsala Universitetsbibliotek user on 04 April 2024

Ranallo-Benavidez TR, Jaron KS, Schatz MC. GenomeScope 2.0 and
Smudgeplot for reference-free profiling of polyploid genomes.
Nat Commun. 2020:11(1):1432. https://doi.org/10.1038/s41467020-14998-3.
Schowalter TD, Noriega JA, Tscharntke T. Insect effects on ecosystemservices—introduction. Basic Appl Ecol. 2018:26:1–7. https://doi.
org/10.1016/j.baae.2017.09.011.
Shipilina D, Näsvall K, Höök L, Vila R, Talavera G, Backström N. Linkage
mapping and genome annotation give novel insights into
gene family expansions and regional recombination rate variation in
the painted lady (Vanessa cardui) butterfly. Genomics2022:114(6):110481. https://doi.org/10.1016/j.ygeno.2022.110481.
Sills J, Robinson GE, Hackett KJ, Purcell-Miramontes M, Brown SJ, Evans
JD, Goldsmith MR, Lawson D, Okamuro J, Robertson HM, et al.
Creating a buzz about insect genomes. Science 2011:331(6023):
1386–1386. https://doi.org/10.1126/science.331.6023.1386.
Smolander O-P, Blande D, Ahola V, Rastas P, Tanskanen J, Kammonen
JI, Oostra V, Pellegrini L, Ikonen S, Dallas T, et al. Improved
chromosome-level genome assembly of the Glanville fritillarybutterfly (Melitaea cinxia) integrating Pacific Biosciences long reads
and a high-density linkage map. GigaScience 2022:11:giab097.
https://doi.org/10.1093/gigascience/giab097.
Supple MA, Shapiro B. Conservation of biodiversity in the genomics
era. Genome Biol. 2018:19(1):131. https://doi.org/10.1186/
s13059-018-1520-3.
Talla V, Mrazek V, Höglund J, Backström N. Whole genome resequencing uncovers significant population structure and low gen­etic diversity in the endangered clouded apollo (Parnassius mne­
mosyne) in Sweden. Conserv Genet. 2023:24(3):305–314.
https://doi.org/10.1007/s10592-023-01502-9.
Talla V, Suh A, Kalsoom F, Dincă V, Vila R, Friberg M, Wiklund C,
Backström N. Rapid increase in genome size as a consequence oftransposable element hyperactivity in wood-white (Leptidea)
butterflies. Genome Biol Evol. 2017:9(10):2491–2505. https://doi.org/10.1093/gbe/evx163.
Tang S, Lomsadze A, Borodovsky M. Identification of protein coding
regions in RNA transcripts. Nucleic Acids Res. 2015:43(12):e78–e78. https://doi.org/10.1093/nar/gkv227.
The Darwin Tree of Life Project Consortium, Mieszkowska N,
Palma FD, Holland P, Durbin R, Richards T, Berriman M, Kersey P,