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\begin{document}

\title{Comparative genomics of Sarcoptes scabiei provides new insights into
adaptation to permanent parasitism and within-host species divergence}



\author[1]{Guang-You Yang}%
\author[1]{Jing Xu}%
\author[2]{Qianghui Wang}%
\author[3]{Sen Wang}%
\author[2]{Wanlong Huang}%
\author[1]{Yue Xie}%
\author[1]{xiaobin gu}%
\author[1]{Ran He}%
\author[1]{Xuerong Peng}%
\author[4]{Shuangyang Wu}%
\affil[1]{Sichuan Agricultural University - Chengdu Campus}%
\affil[2]{Novogene Bioinformatics Institute Beijing 100083 China}%
\affil[3]{Beijing University of Agriculture}%
\affil[4]{Gregor Mendel Institute Austrian Academy of Sciences Vienna 1030 Austria}%


\vspace{-1em}



  
  \date{May 20, 2024}


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\selectlanguage{english}
\begin{abstract}
\textbf{Background:} Mites represent the second largest group with
diverse niches and feeding habits, except for insects. Scabies mites are
the causative agents of highly contagious skin disease in humans and
more than 100 mammals. Although several versions of \emph{Sarcoptes
scabiei} genome have been published, i.e. var. \emph{suis}, var.
\emph{canis} and var. \emph{hominis}, the chromosome-level genome and
population divergence is still desired for the community. Besides, the
molecular mechanisms that scabies mites adapt to a parasitic lifestyle
remains unclear. The taxonomy and ancestral origin of the scabies mite
is unknown. \textbf{Results:} Here, we reported the first
chromosome-level reference genome of \emph{S. scabiei,} which was
isolated from rabbits. The genome has a contig N50 size of 5.92 Mb, a
total assembled length of 57.30 Mb, and \textasciitilde{}12.65\% of
repetitive sequences and 9,333 protein-coding genes were predicted.
Population genetics analysis supported that scabies mites isolated from
different hosts can be subdivided by hosts, and humans are likely the
primary hosts of scabies mites, followed by pigs, dogs, and rabbits.
However, phylogeny results suggested that rabbit was infected with
scabies long before they were domesticated by humans, contradicting
previous hypothesis that humans transmitted scabies mites to animals
through domestication. Comparative genomics between scabies mites and
mites of other feeding habits provided clues concerning the mechanisms
of adaptation to permanent parasitic life from morphology,
detoxification, and metabolism. \textbf{Conclusions:} Together, the
first chromosome-level \emph{S. scabiei} genome and population genetics
analysis indicated its genetic subdivisions and within-host species
divergence, which also provide evidence for further control of this
highly contagious skin disease.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Mites (belonging to the Chelicerata, Arachnida, Acari) represent the
most abundant group of species in the subphylum Chelicerata, with
approximately 48,200 described species and an estimated total diversity
up to 1 million species (Halliday \emph{et al.} , 2000; Krantz, 2009).
Their ecological niches and lifestyles are varied, such as the
free-living house dust mites, plant-feeding spider mites, predatory
mites, and parasitic mites. Among them, \emph{Sarcoptes scabiei}
represents a very rare species that has a unique permanent parasitic
life in the epidermis of humans and mammals, including pets (dogs,
cats), domestic animals (e.g., cattle, sheep, pig, horse, and rabbits,
etc.), and more than 100 species of wild animals. \emph{S. scabiei}
causes scabies in humans or sarcoptic mange in animals, which is
characterized by irritation, inflammation, hyperkeratosis, alopecia,
pruritis, dermatitis, and lesions, and is generally accompanied by
secondary infections (Arlian \& Morgan, 2017; Escobar \emph{et al.} ,
2021; Pence \& Ueckermann, 2002). Scabies has afflicted human societies
for at least 2500 years (Orion \emph{et al.} , 2006), and was also the
first disease in the history of medicine with a definite known cause
(Friedman, 1934). Not only has scabies been listed among the top 50 most
prevalent diseases and the top 15 most burdensome dermatological
conditions worldwide, but also was officially designated as a neglected
tropical diseases in 2017 (Hay \emph{et al.} , 2014; Karimkhani \emph{et
al.} , 2017; WHO, 2017). A recent study showed that the human scabies
disease burden was estimated as 204 million, with a prevalence ranging
from 0.2\% to 71.4\% (Romani \emph{et al.} , 2015). For animals,
sarcoptic mange provokes distress, causing economic loss in the
livestock industry, disease and death in wildlife (Fraser \emph{et al.}
, 2016). Therefore,\emph{S. scabiei} is globally important for public
health, pet health, animal husbandry production, and wildlife
conservation.

As a permanent ectoparasitic mite, scabies mites have evolved from
various levels. They have short and stubby legs to facilitate burrowing
and crawling, legs III and IV of both sexes do not extend beyond the
lateral-posterior margin of the idiosoma (Arlian \& Morgan, 2017), while
their relatives, such as surface-feeding mites \emph{P. ovis} and
\emph{T. mercedesae} , as well as plant surface resident \emph{T.
urticae} , they use longer legs to secure themselves on the surface of
their hosts. Moreover, using unique chewing mouthparts instead of
piercing-sucking mouthparts make scabies mites more efficient in
burrowing the skin, contributing to their highly contagious nature, and
their activity in the epidermis induces extreme itching in the mammalian
hosts. Compared with those mites whose niches and lifestyles are
diverse, the potential parasitic mechanisms of \emph{S. scabiei} in
mammal skin are still poorly understood.

The \emph{S. scabiei} species that parasitize various hosts are
morphologically indistinguishable and have a `high degree of host
specificity and low degree of cross-infestivity'(Arlian \emph{et al.} ,
1984; Currier \emph{et al.} , 2011; Fain, 1978); therefore, there is an
ongoing debate regarding the taxonomy and origin of \emph{S}
.\emph{scabiei} from different hosts (Alasaad \emph{et al.} , 2011;
Engelman \emph{et al.} , 2013; Gakuya \emph{et al.} , 2011; Matsuyama
\emph{et al.} , 2015; Pence \& Ueckermann, 2002; Rasero \emph{et al.} ,
2010; Walton \emph{et al.} , 1999). Although the taxonomy of \emph{S.
scabiei} from different hosts is uncertain, it is believed that a
single, but variable, species that has evolved adaptations to infect a
variety of mammals with limited cross-infestations between different
hosts (Heukelbach \& Feldmeier, 2006; Kraabl \emph{et al.} , 2015),
e.g.,\emph{S. scabiei} var. \emph{hominis} , var. \emph{chimp} ,
var.\emph{canis} , var. \emph{suis} and so on (Matsuyama \emph{et al.} ,
2015; Walton \emph{et al.} , 1999). However, the inconsistent use of
gene loci across studies and conflicting results provided by limited
gene markers cannot lead to the exact nature of the host specific
adaptations, origin, and species differentiation (V Andriantsoanirina,
Ariey, Izri, Bernigaud, Fang, Charrel\emph{, et al.} , 2015; V
Andriantsoanirina, Ariey, Izri, Bernigaud, Fang, Guillot\emph{, et al.}
, 2015; V. Andriantsoanirina \emph{et al.} , 2016; Gakuya \emph{et al.}
, 2011; Mofiz \emph{et al.} , 2016). To explain these questions, the
high-quality genome assembly is essential. At present, although several
versions of \emph{S. scabiei} genome has been published, including var.
\emph{suis} , var. \emph{canis} and var.\emph{hominis} (Korhonen
\emph{et al.} , 2020; Mofiz \emph{et al.} , 2016; Rider \emph{et al.} ,
2015), among which, Korhonen et al.(Korhonen \emph{et al.} , 2020)
reported a scaffold-level genome assembly of \emph{S. scabiei,}the
chromosome-level genome is still absent for the study of this highly
contagious pathogen.

In this study, we employed a combination of sequencing methods,
including Illumina pair-end sequencing, Pacific Biosciences (PacBio)
single-molecule real-time (SMRT) sequencing, and chromosome interaction
mapping (Hi-C) sequencing to get a chromosome-level genome of \emph{S.
scabiei} that isolated from rabbits. We also carried out whole-genome
resequencing of 13 sarcoptic mite populations and downloaded 7 Illumina
short read datasets from scabies mites distributed in four host species
and three geographical locations to clarify the controversial taxonomic
status and origin of \emph{S. scabiei.} Comparative genomics study
revealed the potential mechanism of the \emph{S. scabiei} adaption to
the parasitic life. These results will increase the awareness,
education, and research into taxonomy, pathogenic biology, diagnosis,
treatment, and prevention of scabies or sarcoptic mange.

\textbf{Materials and Methods}

\textbf{Source of samples}

The \emph{S. scabiei} var. \emph{cuniculi} was originated from a
farm-collected New Zealand rabbit (Ya'an, China), and maintained in New
Zealand rabbit, the strain has undergone sibmating to maximize
homozygosity.

Twelve scabies mite colonies from three different mammal hosts (one from
dog, three from pigs and eight from rabbits) were collected to perform
re-sequencing (\textbf{Table S1)} . In addition, we also downloaded the
7 publicly available datasets from other representative \emph{S.
scabiei}populations to do further analysis (\textbf{Table S1)} ,
including one isolated from dogs, 2 isolated from humans and 4 isolated
from pigs (Mofiz \emph{et al.} , 2016; Rider \emph{et al.} , 2015).

\textbf{DNA preparation and genome sequencing}

Adult mites, nymphs, larvae and eggs were collected in a 1.5 mL
Eppendorf tube, treated with bleach solution to remove rabbit tissue and
possible microbial contaminants and prepared for DNA extraction.
Pool-staged mites were ground in a glass tissue grinder and DNA
extraction was performed using Qiagen DNA purification kit (Qiagen,
Valencia, CA, USA) according to manufacturer's protocol and the
extracted DNA was qualified with Qubit 3.0 Fluorometer (Thermo Fisher
Scientific, USA).

To obtain a high-quality scabies mite genome assembly, a combination of
sequencing methods was used, including Illumina paired-end sequencing,
Pacific Biosciences (PacBio) single-molecule real-time (SMRT) sequencing
and chromosome interaction mapping (Hi-C) sequencing. In details, one
short-insert (230 bp, paired-end) DNA library was constructed according
to standard Illumina library prep protocols and sequenced on the
Illumina HiSeq platform as 2 \selectlanguage{ngerman}× 150 bp reads, which generated 4.7 Gb raw
data. And then, a 20 kb PacBio long-reads library was constructed using
the BluePippinTM Size-Selection System recommended by Pacific
Biosciences and sequenced on the Pacbio sequel platform. A total of 16
Gb sequencing data was generated, including 1.4 million clean subreads
with an average length of 12.065 kb and N50 value of 19.706 kb. Finally,
to scaffold the genome, one Hi-C library was constructed from the
purified DNA using the Illumina Mate Pair Sample Preparation Kit and
sequenced using the Illumina HiSeq X platform, and 12.7 Gb was
generated.

\textbf{2.3 RNA preparation and sequencing}

Total RNA was extracted from the tissues of pooled mites (adult mites,
nymphs, larvae and eggs) using TRIzol reagent (Invitrogen, Carlsbad, CA,
USA) according to the manufacturer's instructions. RNA degradation and
contamination were monitored by 1 \% agarose gel electrophoresis. RNA
purity was assessed using Nanodrop®2000 spectrophotometer (ThermoFisher
Scientific, UK) and then quantified. RNA integrity was assessed using an
RNA Nano 6000 Assay Kit with the Bioanalyzer 2100 system (Agilent
Technologies, Santa Clara, CA, USA). RNA sequencing libraries were
constructed using the NEB Next mRNA Library Prep Kit following the
manufacturer's instructions and sequenced on the Illumina HiSeq X
platform. Finally, a total of 25.03 Gb clean data were generated.

\textbf{Genome assembly and evaluation of \emph{S. scabiei}
var.\emph{cuniculi} genome}

Jellyfish (v2.0) was used to estimate genome size based on \emph{k} -mer
(kmer=17) distribution using short-insert size libraries (Kingsford,
2011). The estimated genome size of \emph{S. scabiei} var.
\emph{cuniculi} is 49.83 Mb and the heterozygous ratio is 1.02\%.

Using long reads generated by the PacBio Sequel platform, contigs were
assembled using the canu (canu-1.7) software (Koren \emph{et al.} ,
2017) with parameters setting as `-correct genomeSize=50m
gnuplotTested=true stopOnReadQuality=false -pacbio-raw pacbio.fasta
-trim genomeSize=50m gnuplotTested=true stopOnReadQuality=false
-pacbio-corrected PacBio.correctedReads.fasta.gz -assemble
genomeSize=50m gnuplotTested=true stopOnReadQuality=false
-pacbio-corrected PacBio.trimmedReads.fasta.gz'. The initial assembly
was then polished using Quiver (smrtlink 6.0.1) with default parameters
(Chin \emph{et al.} , 2013). Heterozygosity in the assembly was removed
by Purge Haplotigs software (v1.0.4) (Roach \emph{et al.} , 2018). Short
Illumina reads were then used to correct any remaining errors by pilon
(v1.22) with parameters set as follows: `-Xmx300G --diploid --threads
20' (Walker \emph{et al.} , 2014). Finally, we used Hi-C data to
scaffold \emph{S. scabiei} var.\emph{cuniculi} genome to
chromosome-level by Lachesis software (version-201701) with default
parameters (Burton \emph{et al.} , 2013).

To evaluate the accuracy of the assembly at single base level, short
Illumina reads were mapped to the \emph{S. scabiei} var.
\emph{cuniculi}genome using BWA (H. Li \& Durbin, 2009) with parameters
setting as `-k 32 -w 10 -B 3 -O 11 -E 4' and performed variant calling
with SAMtools (v1.8) (H. Li, 2011). Meanwhile, assembly completeness was
assessed based on Benchmarking Universal Single-Copy Orthologs (BUSCO
v4.0, arthropoda\_odb9) (Simao \emph{et al.} , 2015) and Core Eukaryotic
Genes Mapping Approach (CEGMA V2.5) (Parra \emph{et al.} , 2007).

\textbf{Genome annotation}

Homologous comparison and \emph{de novo} prediction methods were used to
annotate the repeat sequences on \emph{S. scabiei} var.
\emph{cuniculi}genome. RepeatMasker and the RepeatProteinMask v4.0.8
(https://www.girinst.org/repbase/) were performed for homologous
comparison against Repbase database
(\emph{https://www.girinst.org/repbase/}) (Jurka \emph{et al.} , 2005).
For \emph{ab initio} prediction, LTR\_FINDER
(http://tlife.fudan.edu.cn/ltr\_finder/)(Xu \& Wang, 2007), RepeatScout
(http://www.repeatmasker.org/)(Price\emph{et al.} , 2005) and
RepeatModeler (v2.1) (http://www.repeatmasker.org/RepeatModeler.html)
were first used for repetitive elements \emph{de novo} candidate
database constructing, and further annotated using RepeatMasker. Tandem
repeat was predicted using TRF (http://tandem.bu.edu/trf/trf.html).

Gene prediction was performed through combination methods of
homology-based prediction, \emph{de novo} prediction and
transcriptome-based prediction. For homologous annotation, protein
sequences including \emph{S. scabiei} var. \emph{canis}
,\emph{Metaseiulus occidentalis} , \emph{Ixodes scapularis}
,\emph{Tetranychus urticae} , \emph{Drosophila melanogaster}
,\emph{Tropilaelaps mercedesae} , \emph{Pediculus humanus}
,\emph{Tribolium castaneum} and \emph{Stegodyphus mimosarum} were
aligned against the \emph{S. scabiei} var. \emph{cuniculi} genome using
TBLASTN (Altschul \emph{et al.} , 1990). Blast hits that correspond to
reference proteins were concatenated by Solar software (version 0.9.6)
and low-quality records were filtered. Sequence of each reference
protein was extended upstream and downstream by 1000 bp to represent a
protein-coding region. GeneWise (Birney \emph{et al.} , 2004) software
was used to predict gene structure contained in each protein region.
Homology predictions were denoted as ``Homology-set''. All RNA-seq clean
data were first \emph{de novo} assembled using Trinity (v2.0)(Grabherr
\emph{et al.} , 2011) and the assembled sequences were then aligned
against the \emph{S. scabiei}var. \emph{cuniculi} genome using PASA
pipeline v2.0.2(Haas \emph{et al.} , 2003) with BLAT (Kent, 2002) as the
aligner. Gene models created by PASA were denoted as PASA-T-set (PASA
Trinity set). We simultaneously employed five tools of Augustus (Stanke
\& Morgenstern, 2005), GeneID (Guigo \emph{et al.} , 1992), GeneScan
(Burge \& Karlin, 1997), GlimmerHMM (Majoros \emph{et al.} , 2004), and
SNAP(Korf, 2004) for \emph{ab initio}prediction, in which Augustus,
SNAP, and GlimmerHMM were trained by PASA-T-set gene models. In
addition, RNA-seq reads were directly mapped to the genome using Tophat
(v2.0.9) (Trapnell \emph{et al.} , 2009), and then the mapped reads were
assembled into gene models (Cufflinks-set) by Cufflinks (Trapnell
\emph{et al.} , 2010). According to these three approaches, all the gene
models were finally integrated by EvidenceModeler(EVM v1.1.1)(Haas
\emph{et al.} , 2008). Weights for each type of evidence were set as
follows: PASA-T-set \textgreater{} Homology-set \textgreater{}
Cufflinks-set \textgreater{} Augustus \textgreater{} GeneID = SNAP =
GlimmerHMM = GeneScan. In order to get the untranslated regions (UTRs)
and alternative splicing information, PASA2 was used to update the gene
structure. To achieve the functional annotation, the predicted protein
sequences were aligned against public databases, including SwissProt
(Bairoch \& Apweiler, 2000), NR database (from NCBI), InterPro and KEGG
pathway (Kanehisa \& Goto, 2000) (release 76). Of that, InterproScan
tool (Jones \emph{et al.} , 2014) in coordination with InterPro database
(Finn \emph{et al.} , 2017) were applied to predict protein function
based on the conserved protein domains and functional sites. NR, KEGG
pathway and SwissProt database were mainly used to map gene set to
identify the best match for each gene.

\textbf{Reconstruction of phylogenetic relationship and estimation of
divergence time}

We retrieved the protein-coding sequence of 7 arthropod
including\emph{T. urticae} , \emph{Apis mellifera} , \emph{D.
melanogaster} ,\emph{I. scapularis} , \emph{S. mimosarum} , \emph{M.
occidentalis} ,\emph{T. mercedesae} and \emph{a nematode Caenorhabditis
elegans} from Ensembl (Release 85). For gene model with multiple
alternative isoforms, only the longest transcript was selected to
represent this gene. To identify orthologous genes, OrthoMCL pipeline
with the parameter of ``-inflation 1.5'' (L. Li \emph{et al.} , 2003) as
used to construct gene families. In total, 15,542 gene families were
identified, involved in 1,338 single-copy orthologous gene families.

The phylogenetic relationship of \emph{S. scabiei} var.
\emph{cuniculi}was reconstructed using the 1,338 shared single-copy
orthologous genes. The sequences were aligned by MUSCLE tool with
default parameters (Edgar, 2004). Sequences were then concatenated to
one super-gene sequence for each species and formed a data matrix. The
GTR-GAMMA was selected as the best substitution model deduced by
jModeltest tool (Darriba\emph{et al.} , 2012). Then the phylogenetic
analysis was performed using maximum-likelihood (ML) algorithm in RAxML
tool (Stamatakis, 2006). The best-scoring ML tree was inferred by rapid
BP algorithm and ML searches after performing 1,000 rapid bootstraps.
The MEGA (version 7) was used for visualizing the constructed
phylogenetic tree (Kumar\emph{et al.} , 2016).

Furthermore, divergence time between \emph{S. scabiei}
var.\emph{cuniculi} and other species were estimated based on the
phylogeny. Four calibration times obtained from TimeTree database were
used to calibrate divergence dates of other nodes on this phylogenetic
tree (Sudhir \emph{et al.} , 2017). In this process, we implemented the
Monte Carlo Markov Chain algorithm for divergence time estimation by
MCMCtree tool in PAML package (Yang, 2007). Finally, we found
that\emph{S. scabiei} var. \emph{cuniculi} was separated away from its
closest species of \emph{T. urticae} at approximate 338.8 million years
ago.

Homolog annotation method was applied for gene models prediction of
scabies mites variants (isolated from pigs and humans)(Mofiz \emph{et
al.} , 2016),\emph{Psoroptes ovis} (Burgess \emph{et al.} , 2018) and
\emph{Dermatophagoides pteronyssinus}(Waldron \emph{et al.} , 2017) that
only have genome assembly files available in public database. OrthoMCL
pipeline was employed to acquire shared single copy genes, molecular
phylogenetic relationship of scabies mites from four hosts with
plant-living, free-living, predatory mites, and other parasitic mite
species that have available genomic data sets was constructed based on
shared single copy genes generated from the same methods mentioned
above.

\textbf{Gene-family evolution and identification of gene families
related with detoxification}

The evolutionary dynamics (expansion/contraction) of gene families were
analyzed using CAFÉ tool(De Bie \emph{et al.} , 2006 ) with a stochastic
birth and death model. Global parameter \selectlanguage{greek}λ \selectlanguage{english}was estimated based on the
phylogenetic tree and the datasets of gene family clustering. Viterbi
method in CAF\selectlanguage{ngerman}É was employed to identify the significantly changed
families (\emph{p} -value \textless{} 0.05). Finally, significantly
changed expansion/contraction gene families were used to perform
enrichment analysis.

To further analyze gene families of detoxification enzymes and
transporters, the \emph{S. scabiei} var. \emph{cuniculi} genome sequence
assembly was searched by TBLASTN (\emph{E}
-value=10\textsuperscript{-5}) (Altschul \emph{et al.} , 1990) with
close arthropod relatives including \emph{T. urticae} , \emph{T.
mercedesae} ,\emph{M. occidentalis} , and \emph{D. melanogaster} target
gene family protein sequences. The Basic Local Alignment Search Tool
(BLAST) hits were then conjoined by Solar software (Yu\emph{et al.} ,
2006). GeneWise was used to predict the exact gene structure of the
corresponding genomic region on each BLAST hit (Birney \emph{et al.} ,
2004). We then annotated preliminary identified candidate genes with
Pfam database (\emph{http://pfam.xfam.org/}) and NR database to get
putative gene sets. Finally, a The proteins of target genes were aligned
with mafft software (Katoh \& Standley, 2014) and a neighbor-joining
tree was constructed with TreeBest (Vilella \emph{et al.} , 2009) with
aligned by MAFFT software (Katoh \& Standley, 2014).

\textbf{Characterization of Hox genes}

We identified putative Homeobox genes in \emph{S. scabiei}
var.\emph{cuniculi} genome sequence assembly by performing TBLASTN
(\emph{E} -value=10\textsuperscript{-5})(Altschul\emph{et al.} , 1990),
using curated Homeobox proteins from \emph{A. mellifera, Bombyx mori,
Anopheles gambiae, Daphnia pulex, D. melanogaster, I. scapularis,
Pachycrepoideus vindemmiae, Strigamia maritima, T. urticae,} and
\emph{Tribolium castaneum} . The Basic Local Alignment Search Tool
(BLAST) hits were then conjoined by Solar software (Yu \emph{et al.} ,
2006). GeneWise was used to predict the exact gene structure of the
corresponding genomic region on each BLAST hit (Birney \emph{et al.} ,
2004). HMM searches of the above genes against the Pfam database
(http://pfam.xfam.org/) revealed each to have PF00046.29 domain. The
classification of deduced proteins and their integrity were verified
using BlASTP with model species \emph{D. melanogaster} Hox
genes.\emph{E} -values \textless{} 10\textsuperscript{-5} was considered
as significant hits of similarity.

\textbf{Phylogenetic and population genetic analysis}

Twelve scabies mite colonies from three different mammal hosts (one from
dog, three from pigs and eight from rabbits) were sequenced on the
Illumina HiSeq X sequencing platform using standard procedures. In
addition, we also downloaded 7 individuals in the public database from
other representative populations, including one mite population isolated
from dogs, 2 isolated from humans and 4 isolated from pigs (Mofiz
\emph{et al.} , 2016; Rider \emph{et al.} , 2015). Detailed information
for all 20 samples was shown in \textbf{Tables S1} . Consequently, a
total of 136.45 Gb high-quality paired-end DNA sequence was obtained.
For downloaded datasets, high sequencing depth data were truncated to
around 50x coverage for further analysis.

FASTQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) was
used for reads quality control. Clean reads were then aligned to
the\emph{S. scabiei} var. \emph{cuniculi} genome using Burrows-Wheeler
Alignment MEM (BWA-MEM) version 0.7.8 with default parameters except for
the ``-t 4 -k 32 -M -R'' option (H. Li \& Durbin, 2009). The `sort' and
`rmdup' commands of SAMtools (v1.3) were used to perform data
manipulation and alignment statistics. SNP calling was performed by
SAMtools (v1.3) `mpileup' command (H. Li \emph{et al.} , 2009), bcftools
`call' command. To estimate individual admixture assuming different
numbers of clusters, the genetic structure was inferred using sNMF
(\emph{http://membres-timc.imag.fr/Olivier.Francois/snmf/software.htm)}
, which is based on sparse non-negative matrix factorization algorithms.
We calculated the numbers of genetic clusters from 2 to 7 to explore the
convergence of individuals with default settings and plotted
\emph{K}from 2-4.

The software GCTA (\emph{http://cnsgenomics.com/software/gcta/}) was
used for principal component analysis (PCA) with biallelic SNPs of the
20 individuals. Only the first two significant components were plotted.
The pam function of Rggfortify package
(\emph{https://cran.r-project.org/web/packages/ggfortify/index.html})
was used to determine the significant level of the principal components.

\textbf{2.10 Demographic history reconstruction}

To reconstruct the demographic history for 20 scabies mite populations,
we applied the pairwise sequentially Markovian coalescence (PSMC) model
to evaluate the long-term changes in effective population size (H. Li \&
Durbin, 2011). To ensure the consensus sequence quality, all 20 samples
with high sequencing depth were used for each geographic region. Bases
of low sequencing depth (a third of the lowest depth) or high depth
(three times of the highest depth) were masked. The required input
format files were converted from consensus sequence by the utility
fq2psmcfa provided by the PSMC software. The parameters were set as
follows: -N30 -t15 -r5 -p 4+25*2+4+6. The generation time (g) was 0.0575
year per generation (21 days) and the mutation rate (u) is 8.4 x
10\textsuperscript{-9} per site per generation.

\textbf{2.11 Selection signature analysis}

Two complementary approaches based on the allele frequencies of variable
sites were used to identify regions potentially affected by long-term
selection. We calculated population fixation statistics (FST) and
nucleotide diversity (\selectlanguage{greek}θπ\selectlanguage{english}) for each sliding window in 10-kb windows with
5-kb step size. We Z-transformed the distribution of FST and calculated
the log value of \selectlanguage{greek}θπ \selectlanguage{english}ratios. Top 5\% of log-odds ratios for both \selectlanguage{greek}θπ \selectlanguage{english}and
FST were chosen as putative selection targets.

\textbf{Results}

\textbf{3.1 A high-quality, chromosome-scale \emph{S. scabiei} reference
genome}

A total of 33.4 Gb of sequence data (670.28-fold genome coverage based
on an estimated genome size of 49.83Mb) was generated (\textbf{Table S2;
Figure S1)} . We obtained a high-quality chromosome-scale reference
genome of \emph{S} . \emph{scabiei} var\emph{. cuniculi} , with contig
N50 size of 5.92 Mb and total assembled length of 57.30 Mb
(\textbf{Table 1} ), of which 100\% was anchored to nine chromosomes
(\textbf{Figure 1; Table S3} ). The high accuracy and completeness was
represented by the normal GC content (33.23\% of genome) (\textbf{Figure
S2} ), the mapping rate of 97.27\% of short sequencing reads, 0.001472\%
of homozygous SNPs (\textbf{Table S4} ), and the 97.98\% and 89.0\% of
genome completeness assessed by the Core Eukaryotic Genes Mapping
Approach (CEGMA)(Parra \emph{et al.} , 2007) and Benchmarking Universal
Single-Copy orthologues (BUSCOs) (Simao \emph{et al.} , 2015) strategies
(\textbf{Tables S5-6} ).

Genome-wide searching and homology prediction results showed 12.65\% of
the scabies mite genome belongs to transposable element (TE) families
(7,247,159 bp, \textbf{Figure S3; Tables S7--8} ). We annotated the
genes using combination methods of homology searching, \emph{ab
initio}prediction, and direct mRNA sequencing evidence. In total, 9,333
protein-coding genes were identified (\textbf{Table S9; Figure S4} ),
and approximately 99.30\% of these genes were functional annotated
either in Kyoto Encyclopedia of Genes and genomes (KEGG) pathway
database (Kanehisa \& Goto, 2000), InterPro (Mulder \emph{et al.} ,
2007) and Gene Ontology (GO) (Ashburner, 2000) (\textbf{Table S10} ).

\textbf{3.2 Evolution of the scabies mite genome}

To determine the evolution of the scabies mite genome in the context of
the Chelicerata, we collected seven other arthropods and a nematode as
outgroup for phylogeny analysis. A total of 15,542 gene families and
1,338 shared high confidence single-copy orthologous genes
(\textbf{Figure S5} ) were identified. The phylogenetic tree resulted in
a well-supported phylogeny (\textbf{Figure 2a} ): scabies mite and
spider mite clustered together (Acariformes), while \emph{Tropilaelaps}
mite, predatory mite, and black-legged tick clustered together
(Parasitiformes) and formed a separate group with \emph{Stegodyphus
mimosarum.} Based on this phylogenetic tree, we estimated that \emph{S.
scabiei} and \emph{Tetranychus urticae} separated at approximately 338.8
Mya (\textbf{Figure 2a} ), which indicated a relatively distant
relationship between these two species. To further understand the
phylogenetic relationship of scabies mites from various hosts, we used
protein-coding single-copy orthologous genes of scabies mites from four
hosts, as well as free-living mite \emph{Dermatophagoides pteronyssinus
and} parasitic mite \emph{Psoroptes ovis} . This result showed
that\emph{S. scabiei} isolated from rabbits is genetically similar
to\emph{S. scabiei} isolated from humans, and then with pigs and dogs,
followed by the free-living dust mite and the surface living scab mite,
but distantly related to the spider mite (\emph{T. urticae} )
(\textbf{Figure 2b} ). The phylogeny structure supported the previous
study that the subclass Acari is diphyletic, with the superorders
Acariformes (scabies mite and spider mite) and Parasitiformes
(\emph{Tropilaelaps} mite and predatory mite) being distantly related
(Gu \emph{et al.} , 2014; Hoy \emph{et al.} , 2016). As only colonies
from one individual animal and one geographical location were used for
one host species, whether scabies mites from individual animals have any
intrinsic relationship remains unknown. Thus, we are wondering that the
so called ``variants'' more reasonable to be classified by host species
or geographical locations?

To answer these questions, we expanded the sample size to 20 including
four host species (humans, dogs, pigs and rabbits) and three
geographical locations (China, Australia and America) (\textbf{Table S1;
Figure S6} ). Genome alignment indicated a mapping rate of
82.74--98.09\% and \textasciitilde{}40-fold depth for each individual
relative to our rabbit mite reference genome (\textbf{Table S11)} .
After single nucleotide polymorphism (SNP) calling (\textbf{Table S12}
), we examined the correlation between host species and geographical
locations. The results showed that, although extremely similar genetic
diversities were observed among these populations, both principal
components analysis (PCA) consistently supported four distinct groups
according to the host species (\textbf{Figure 2c} ). Specifically,
rabbit mites seem to be relatively distinct with mites from other three
host species. Varying the number of presumed ancestral populations
(\emph{K} ) from two to four, we found that rabbit mites remain distinct
with mites from other three hosts (\textbf{Figure S7} ). Interestingly,
mites from humans and dogs cluster together, which may reflect the
intimate relationship of these two hosts and indicated potential
transmission between each other.

Although no direct evidence reported, the current scientific community
believed that humans are the primary host of scabies mites, and other
animals get infected from humans during the domestication (Currier
\emph{et al.} , 2011). To provide clues for the origin and transmission
of scabies mites, PSMC was used and the results revealed a varied
demographic history from over 100 kyr (1,000 years) to 10 kyr ago
(\textbf{Figure 2d} ), a period significantly younger than any of the
currently reported fossil mites, including a nearly modern looking
fossil oribatid mite (order Acariformes) that existed in the Devonian
(late Paleozoic) period at \textasciitilde{}380 mya (million years
ago)(Norton \emph{et al.} , 1988), and the earliest fossil Astigmata
mites at \textasciitilde{}28 mya (Petrunkevitch \& Alexander, 1952). For
human mites, the origin time is around 100 kyr ago (\textbf{Figure 2d}
), nearly the same time with the emerging of the modern humans (Fenner,
2010; Hu \emph{et al.} , 2017), supporting that humans are the primary
host of scabies mites (Currier \emph{et al.} , 2011b). However, for
mites from other hosts, the origin time of these mites is far earlier
than their hosts were domesticated by humans. To be specific, pigs,
dogs, and rabbits became infected with mites at around 100 kyr, 61 kyr,
and 45 kyr ago, while these hosts were domesticated at around 10 kyr, 15
kyr, and 1.5 kyr ago (\textbf{Figure 2d; Table S13} ). We also noticed
that the effective population size of rabbit mites is significantly
larger than mites from any of the other three hosts, which may reflect
the parasite load of these hosts.

\textbf{3.3 Specialized morphology to adapt an obligate parasitic life}

The skin of mammalian species is composed of epidermis, dermis and
hypodermis (\textbf{Figure 3a} ). As a permanent parasitic mite species,
scabies mites burrow into the epidermis of the skin, and resident at the
interface of stratum lucidum and stratum granulosum (\textbf{Figure3b}
). Belonging to a member of chelicerate, the adult scabies mite body
plan comprises the anterior prosoma bearing the chelicerae, pedipalps,
and the four pairs of walking legs, and the posterior opisthosoma
(\textbf{Figure 3c} ). After long time of adaptation, the four walking
legs of scabies mites has become extremely stubby to adapted to its
parasitic environment in the epidermis, while for other mites such as
surface living and free-living mites, the length of walking legs remains
long (\textbf{Figure 3c} ). Interestingly, when we observed the
morphology of species in class Acari, we found that for species in the
superorder Acariformes, the anterior and posterior two pairs of legs
were distantly distributed and the proportion of the abdominal segments
were reduced, while for species in the superorder Parasitiformes and the
velvet spider, all the legs were very close to each other and the
abdominal segment is relatively longer (except\emph{Metaseiulus
occidentalis} , which seems a transactional species) (\textbf{Figure 3c;
Figure 3d, left panel} ). Therefore, we analyzed the structurally and
functionally conserved Hox genes of these related species, including
\emph{lab} , \emph{pb} , \emph{Hox3/Zen} , \emph{Dfd} ,\emph{Scr} ,
\emph{ftz} , \emph{Antp} , \emph{Ubx} , \emph{Abd-A} , and\emph{Abd-B} ,
hoping to find potential clues to explain this phenomenon. The results
showed that \emph{S. scabiei} has eight of ten canonical Hox genes that
are present in the arthropod ancestor, except Z\emph{en} and\emph{Abd-A}
, and no gene duplication events (\textbf{Table S14} ). The loss of
Z\emph{en} and \emph{Abd-A} seems common and unique for species in
superorder Acariformes (\textbf{Figure 3d, central and right panel} ).

\textbf{3.4 Specialized metabolism to adapt an obligate parasitic life}

The scabies mite~burrows into the skin of its host, and then resides in
the lower epidermis close to the dermis, using host skin and
intracellular fluid (lymph) that seeps into the burrow as food (Estes
\emph{et al.} , 1983; Neste \& Lachapelle, 1981; Van Neste, 1984).
Compared with the other eight species genes in specific families to
\emph{S. scabiei} were significantly enriched in protein
metabolic-related GO categories, especially in proteolysis, serine-type
peptidase activity, serine-type endopeptidase activity, cysteine-type
peptidase activity, peptidase activity, and endopeptidase activity
(\textbf{Figure 4} ). KEGG analysis results showed categories associated
with the digestive system (Protein digestion and absorption, and
Pancreatic secretion), lipid metabolism (Fatty acid metabolism, and
Biosynthesis of unsaturated fatty acids), transport and catabolism
(Lysosome) and cell growth and death (Apoptosis) (\textbf{Figure 4} )
were also highly enriched. These results reflected that \emph{S.
scabiei} var. \emph{cuniculi} may underwent natural selection pressure
by living in mammalian skin, evolved to have better ability of digesting
proteins to break through the skin barrier and migrate in the epidermis,
and most importantly, to meet the requirement of nutrition.

Besides, genes in the families that were shared only by ectoparasite
scabies mite and \emph{Tropilaelaps} mite are highly enriched in the
biological process of cellular nitrogen compound metabolic process and
nitrogen compound metabolic process (\textbf{Figure S8-S9} ), probably
related to carnivorous diets of both scabies mite and\emph{Tropilaelaps}
mite. These genes were also enriched in KEGG pathway of human diseases,
such as Alzheimer's disease, Arrhythmogenic right ventricular
cardiomyopathy (ARVC), Dilated cardiomyopathy, and Cardiac muscle
contraction (\textbf{Figure S8; Table S15} ). We speculated that the
enhancement of heart muscle-like function is an adaption of the aerobic
nature of scabies mites in the hypoxic skin environment (Arlian \emph{et
al.} , 1988).

Scabies mites have been known to well adapted to live in the epidermis
of the skin, protecting them from the environment. According to
expansion and contraction analysis, three gene families were expanded,
and 34 gene families were contacted. The primary contributor to the
acquisition of new functions and physiology is gene duplication (Nasvall
\emph{et al.} , 2012). The three expanded gene families including the
vitamin D-binding protein (46 genes), synaptotagmin (12 genes) and HAUS
complex (7 genes). The vitamin D-binding protein is the major
binding/transport protein for all vitamin D metabolites (Bouillon
\emph{et al.} , 2020), genes in synaptotagmin family encode proteins
that regulate calcium-dependent membrane fusion events (Wolfes \& Dean,
2020), both were associated with enhanced absorption ability of
nutrients. Among the 34 contracted gene families in scabies mites, genes
were over-represented in the process of materials transport
\textbf{(Tables S16-17} ). We discovered four gene families that
implicated in digestion, detoxification and transport of xenobiotics,
including cytochrome P450 (CYP), carboxyl/cholinesterases (CCE),
glutathione-S-transferase genes and ATP-binding cassette transporter C
group and found unique scabies mite composition (\textbf{Tables 2-3;
Table S19-S20)} . A total of only 25 cytochrome P450 (CYP) genes in
\emph{Sarcoptes scabiei} , followed by\emph{Pediculus humanus} (36
genes), \emph{T. mercedesae} (42 genes), and \emph{Apis mellifera} (46
genes) (\textbf{Table 2} ); of which the number of genes in \emph{CYP4}
clan being close to the number of counterparts in \emph{A. mellifera} (4
genes), but far less than the number found in other mites
(16\textasciitilde{}23 genes); members of CYP2 clan (three genes) and
Mito clan (three genes) have orthologs in\emph{Drosophila melanogaster}
(\textbf{Figure S10} ), indicating that scabies mites only retain the
genes that support basic life. A notable contraction is also found in
the family of carboxyl/cholinesterases (CCE) that include 11 genes
compared with other three mites (31-69 genes), and 6 genes in subclass
acetylcholinesterase (AChEs) compared with 22--59 genes in other mites
(\textbf{Table 3} ). Although the total number of ABC transporters
remain the same, we discovered 14 multidrug resistance proteins that
belong to the ATP-binding cassette (ABC) transporters (class C), while
other mites have 20--39 genes (\textbf{Table S18 and Figure S11} ).
Finally, scabies mites have 13 glutathione-\emph{S} -transferase genes
(\textbf{Table S19 and Figure S12} ) that can be assigned to four
subfamilies: Delta/Epsilon (4 genes), Mu (6 genes), Zeta (1 gene), and
Kappa (2 genes), interestingly, both mu and kappa appear to be tandem
repeats in the genome. The relatively small number of P450 genes in
honey bee was thought to be a consequence of the social organization of
beehive, which shields the queen and larvae from environmental exposure
to toxins (Claudianos \emph{et al.} , 2006). It is likely that the
extremely contracted detoxification genes in scabies mites might be the
consequences of long time living in the epidermis of the skin, protect
mites from environmental exposure to toxins.

\textbf{3.5 Strong selective sweep signals provided clues to the genetic
basis of variant divergence and cross-infestivity}

Scanning electron microscopy and light microscopy showed that \emph{S.
scabiei} lives in the skin stratum corneum reside at the interface of
stratum lucidum and stratum granulosum (Estes \emph{et al.} , 1983;
Neste \& Lachapelle, 1981; Van Neste, 1984). As shown in\textbf{Table
S20} , the epidermis of humans, pigs, dogs and rabbits are 46.9 \selectlanguage{ngerman}± 2.3
\selectlanguage{greek}μ\selectlanguage{english}m, 65.8 \selectlanguage{ngerman}± 1.8 \selectlanguage{greek}μ\selectlanguage{english}m, 18.94 \selectlanguage{ngerman}± 2.29 \selectlanguage{greek}μ\selectlanguage{english}m, and 17.0 \selectlanguage{ngerman}± 1.2 \selectlanguage{greek}μ\selectlanguage{english}m thick,
respectively (Bhandal \emph{et al.} , 2012; Bronaugh \emph{et al.} ,
1982; Nicoli \emph{et al.} , 2008), while the stratum corneum of them
are 16.8\selectlanguage{ngerman}±0.7 \selectlanguage{greek}μ\selectlanguage{english}m, 26.4\selectlanguage{ngerman}±0.4 \selectlanguage{greek}μ\selectlanguage{english}m, NA and 11.7\selectlanguage{ngerman}±0.5 \selectlanguage{greek}μ\selectlanguage{english}m. According to the
results of PSMC, humans, pigs, dogs and rabbits get infected with
scabies mites for more than 30 kyr ago, to reveal the potential genome
footprint that may left by a couple of hundred thousand years
co-evolution of the scabies mites and the hosts, we used FST \& \selectlanguage{greek}θπ \selectlanguage{english}to
find possible selection sweeping signal between any of the two hosts. As
shown in \textbf{Figure 5,} strong selective signals were observed
between pig mites and human mites: about 10 times as many genomic
regions with strong selective sweep signals in pig mites (3.84\% of the
genome, containing 358 genes) as there are in human mites (0.40\% of the
genome, containing 37 genes), with significant enrichment in
``cysteine-type peptidase activity (10 genes), Neuroactive
ligand-receptor interaction (18 genes), and Apoptosis (11 genes)
(\textbf{Table S21} ).There are three times as many genomic regions with
strong selective sweep signals in dog mites (0.81\% of the genome,
containing 77 genes) as there are in human mites (0.27\% of the genome,
containing 25 genes), with high enrichment in ``cysteine-type peptidase
activity (five genes) and apoptosis (five genes)(\textbf{Table S21} ).
As shown in \textbf{Table S22-24} , the involved genes mainly including
Sar s 1 allergen SMIPP-C (Peptidase C1A, papain C-terminal) and group 3
allergen SMIPP-S (Peptidase S1). However, as a recently emerging mite
variant, rabbit scabies mites showed very limited selective sweeping
signals compared with mites from any of the other three hosts
(\textbf{Table S21} ), especially with human mites and dog mites, which
might be the explanation of cross-infestivity between rabbits and the
other three hosts.

\textbf{Discussion}

\textbf{Genome assembly and evolution}

Scabies mites represent a highly contagious ectoparasite that can affect
more than 100 mammal species (Escobar\emph{et al.} , 2021). In this
study, we presented the chromosome-scale genome assembly for
ectoparasite \emph{S. scabiei} . To the best of our knowledge, this is
the first chromosome-level genome of all mite species to be determined
to date (\textbf{Table 1} ), providing a reference genome for
comparative genomics of mite biology and further study of scabies mite.

Genome evolution results showed that scabies mites from four hosts
clustering together, and rabbit mite is closer to human mites followed
by pig mites and dog mites. However, the population genetics results
indicated the clear cluster was defined by hosts, and rabbit mites seems
distantly related with other mites, providing evidence supporting the
hypothesis that \emph{S. scabiei} is not a single panmictic population
and genetic subdivisions occurs according to the hosts (Alasaad \emph{et
al.} , 2011; Walton \emph{et al.} , 2004). It thus can be concluded that
\emph{S. scabiei} from various hosts are genetically similar to each
other and are likely variants of one species that mainly clustered by
host species.

If the variants classified by hosts is the case, is there any order of
infection time for mites from these hosts? Surprisingly, the origin time
of human mites support the current scientific consensus that humans are
the principal host for Sarcoptes mites. Domestication of dogs can be
traced back to at least around 15,000 years, and possibly earlier, being
domesticated from the gray wolf in East Asia around 100,000 years ago
(Bardeleben \emph{et al.} , 2005; Currier \emph{et al.} , 2011;
Savolainen \emph{et al.} , 2002; Wayne \emph{et al.} , 1997); moreover,
recent studies have shown that, in southern East Asia, the groups of
dogs and wolves began to diverge about 33,000 years ago (Skoglund
\emph{et al.} , 2015; Wang \emph{et al.} , 2016; Wang \emph{et al.} ,
2013). The estimated origin time of dogs (about 37 kyr - 61 kyr) all
fall within the time frame of human domestication of domestic dogs
(15,000 years to 100,000 years ago), indicating that the canine-derived
scabies mites may have come from human-derived scabies mites. However,
the results showed that pigs and rabbits get infected with scabies mites
long before they were domesticated by humans, contradicting the
hypothesis that humans transmitted scabies mites to animals through
domestication activity (Currier \emph{et al.} , 2011a; Friedman, 1936).
The possible transfer of human-derived mites to dogs probably reflected
the intimate relationship of humans and dogs.

\textbf{4.2 Genetic basis of scabies mites to adapt an obligate and
permanent parasitic life}

As a permanent ectoparasitic mite, scabies mites have evolved from
various levels. When we analyzed the mechanism that influenced
morphology of the species in Acari, we found the Hox gene family
divergence may cause the differences of body plan in superorder
Acariformes and Parasiformes, especially the absence of Z\emph{en}
and\emph{Abd-A} . For Chelicerate species like spiders and mites,
Z\emph{en}and \emph{Abd-A} were reported to function in body plan of the
prosoma and the opisthosoma (Hughes \& Kaufman, 2002). Previous study
showed that, the function of \emph{Zen} has transferred from a Hox-like
role to a role in the extraembryonic tissues due to the functional
overlap with other Hox proteins (Hughes \& Kaufman, 2002; Pick, 2016),
thus pretended to be lost for species in the Acariformes that generally
have small genomes (\textbf{Table S25)} . The expression of \emph{Abd-A}
and \emph{Abd-B}reflects the differences in the insect abdomen, and
\emph{Abd} -\emph{B}acts to suppress \emph{Abd-A} in posterior segments,
and suppresses posterior segmentation (Celniker \emph{et al.} , 1989;
Jordi \emph{et al.} , 1986; Karch \emph{et al.} , 1990). Previous data
supportted a model that inversion of the \emph{Abd-B} locus results in
the loss of \emph{Abd-A} , and correlated with reduced trunk
segmentation (Pace \emph{et al.} , 2016), and in this study, the Hox
clusters and transcription direction in \emph{S. scabiei} , \emph{P.
ovis} and \emph{T. urticae} implicated the same mechanisms for the trunk
segmentation of species in Acariforms. These results indicated that the
morphological evolution correlated with the loss of specific Hox genes.

Genes in families specific to scabies mainly enriched in nutrition
absorption and digestion of proteins and lipids. And genes in families
of cytochrome P450 (CYP), carboxyl/cholinesterases (CCE), and multidrug
resistance proteins of the ATP-binding cassette transporter C group are
strikingly contracted, and members in these families were reported to
function in a wide range of detoxification events (Dermauw \emph{et al.}
, 2013; Enayati \emph{et al.} , 2005; X. Li \emph{et al.} , 2007).
Scabies mite lives in the epidermis of the mammal skin, which is a
relatively enclosed stable environment. Compared with \emph{P. humanus}
and\emph{T. mercedesae} that live on the surface of the hosts, scabies
mites have limited chances of encountering toxicants than other
ectoparasites, thus the strikingly contracted gene families that are of
important in metabolizing toxic xenobiotics in insects and the
acquisition of insecticide resistance indicated a less effective
detoxification system and an adaption to the enclosed environment.

\textbf{Genetic basis of variant divergence and cross-infestivity}

To date, there is no well-accepted standard to define subspecies or
variants of mites, especially by using limited gene markers. In this
study, we considered mites from different hosts as variants based on
results of PCA and phylogenetic analysis. Although there is no direct
evidence of host shift, comparative genomics analysis may provide clues
for the cross-infectivity of these mites. It is known that \emph{S.
scabiei} reside at the interface of stratum lucidum and stratum
granulosum (Estes \emph{et al.} , 1983; Neste \& Lachapelle, 1981; Van
Neste, 1984), and mites have to burrow deep through stratum corneum to
get to their destination, therefore, the thickness of stratum corneum
may partly reflected the difficulties of mites to break through the
barriers of the skin.

The selection signal between human mites/pig mites, human mite/dog mites
quantitatively reflected the adaption to the new host in shaping the
genome. Genes enriched in ``cysteine-type peptidase activity'' and
``apoptosis'' mainly encode Sar s1 allergen scabies mite inactive
cysteine proteases (SMIPP-Cs). The function of these proteins is
promoting blood coagulation and changing the structure and density of
fibrin clots, making them resistant to fibrinolysis, thus protecting
scabies mites from the host immune system (Fernando \emph{et al.} ,
2021). These functions were thought to contribute to parasitic
lifestyle. Neuroactive ligand-receptor interaction (18 genes) is a
function of environmental information processing (\textbf{Table S28} ).
Most of the group 3 allergen SMIPP-S genes occur in tandem, studies have
shown that these proteins might function by binding and protecting
target substrates from cleavage by host immune proteases, thus
preventing the host from mounting an effective immune challenge (Fischer
\emph{et al.} , 2009). Besides, the presence of receptors, such as the
olfactory receptor, rhodopsin-like G protein-coupled receptor, and the
5-hydroxytryptamine receptor family, suggested that scabies mites in
omnivorous pigs have evolved to have a better ability to process
environmental information, and thus adapted to a more complicated pig
skin environment.

A previous study reported that mites from scabies-infected dogs can
establish permanent infections on domestic rabbits and these mites can
then re-infect dogs (Nicoli \emph{et al.} , 2008). Interestingly, it is
reported that the human and the pig stratum corneum share very similar
lipid types and percentage of lipids (Hammond \emph{et al.} , 2000),
which suggested the possibility of the transmission of scabies mites
from humans to dogs. Compared with the other three hosts, rabbits have
the shortest generation time (\textbf{Table S13} ) and are more
susceptible to scabies mites. According to the statement of local farm
workers, we also learned that humans who come in contact with rabbit
mites experience intensive itching symptoms; however, because humans
generally apply drugs before the mites settle down on the skin, we do
not know if rabbit mites can establish a permanent infection on humans
or vice versa. The condition of pigs living with rabbits is very rare,
thus few reports have been published about the cross-infestivity between
pig mites and rabbit mite. The results of the pairwise selective
sweeping analysis provided clues to investigate cross-infestivity.
Except in humans, it is feasible to investigate the genetic basis of
cross-infestivity by performing artificial infection experiments to test
cross-infestivity and differentially expressed genes during host shift.


\textbf{Conclusions}

In this study, a chromosome-scale genome assembly was reported
for\emph{S. scabiei} , a highly contagious ectoparasite that can affect
more than 100 mammal species. Comparative genome analysis illustrated
the possible mechanisms of scabies mites adapted to a permanent
parasitic life, including metabolism, morphology and detoxification.
Whole genome re-sequencing analysis showed that scabies mites cluster by
host species rather than geographical location, and analysis of their
demographic history supported the view new insights that humans were the
primary hosts of scabies mites, followed by pigs, dogs, and rabbits, but
was inconsistent with the previous hypothesis that humans transmitted
scabies mite according to the domestication time of these hosts. As the
first chromosome-scale genome of mites, \emph{S.scabiei} genome and
comparative genomics study will provide solid foundation to promote the
study of mites phylogeny and biology, especially for the study of
control strategy for scabies and other mites.

\textbf{Acknowledgements}

We thank Nengxing Shen, Chunyan Li, Lang Xiong, Song Liu, and Yuejun Luo
for assistance in raising animals or collecting mites.

\textbf{Conflict of Interest}

The authors declare no competing interests.

\textbf{Ethical Statement}

The animal study was reviewed and approved by the Animal Care and Use
Committee of Sichuan Agricultural University (SYXK2019-187). All animal
procedures used in this study were carried out in accordance with the
Guide for the Care and Use of Laboratory Animals (National Research
Council, Bethesda, MD, USA) and recommendations of the ARRIVE guidelines
(https://www.nc3rs.org.uk/arrive-guidelines).

\textbf{Supplementary information}

Supplemental information has been submitted as supplemental material.

\textbf{Authors' contributions}

Conceptualization, G.Y.Y., J.X.; Data curation, Q.H.W., S.W., S.Y.W.;
Formal analysis, J.X., Q.H.W., S.Y.W.; Funding acquisition, G.Y.,
S.Y.W.; Investigation, W.H., X.G., R.H., X.P.; Methodology, J.X.,
Q.H.W., S.W.; Project administration, G.Y.Y., J.X.; Resources, G.Y.Y,
J.X.; Software, Q.W., S.W.; Supervision, G.Y.Y., J.X.; Validation,
Q.H.W., S.Y.W., S.W.; Visualization, J.X., S.Y.W., Q.H.W.;
Writing--original draft, J.X.; Writing--review \& editing, G.Y.Y., J.X.,
Q.H.W., S.W., S.Y.W., W.H., Y.X., X.B.G., R.H., X.R.P.. All authors
contributed to the writing and review of the final manuscript, with
G.Y., J.X., S.Y.W., Q.H.W., and S.W. playing the key roles. All authors
read and approved the final manuscript.

\textbf{Funding}

This work was supported by research grants from Chengdu Giant Panda
Breeding Research Foundation (Project No. CPF2014-17) (G.Y.Y.) and China
Postdoctoral Science Foundation (2020M683652XB) (J.X.), and also
received funding from the European Union's Framework Programme for
Research and Innovation Horizon 2020 (2014-2020) under the Marie Curie
Sk\selectlanguage{polish}ł\selectlanguage{english}odowska Grant Agreement Nr. 847548 (S.Y.W.).

\textbf{Availability of data and materials}

All raw data for the genome sequencing, RNA-seq and whole genome
re-sequencing in this study have been deposited into the GenBank
Sequence Read Archive (SRA) database with the BioProject accession
PRJNA749654, the BioSample accession SAMN20424381 to SAMN20424399, and
the accession for raw data from SRR15371646 to SRR15371664. The genome
assembly and annotation information are available in figshare
through\emph{https://doi.org/10.6084/m9.figshare.16999372.v1.}The genome
assembly is also available in NCBI under accession GCA\_020844145.1.

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\textbf{Figure legends}

\textbf{Figure 1.} \textbf{Heat map and genomic landscape of the\emph{S.
scabiei} var. \emph{cuniculi} genome.} (a) Heat map of the\emph{S.
scabiei} var. \emph{cuniculi} genome. (b) Genomic landscape of the
\emph{S. scabiei} var. \emph{cuniculi} assembly over 100-kb chromosomal
intervals. Tracks from outside to inside: 1. Positions of the nine
chromosomes of \emph{S. scabiei} ; 2. Gene density; 3. Repeat sequences
across the genome; 4. GC content.

\textbf{Figure 2. Evolution of the scabies mite genome.} (a)
Phylogenetic tree of \emph{S. scabiei} var. \emph{cuniculi} constructed
using 1,338 shared single-copy orthologous genes and estimation of
divergence time and expansion and contraction in gene families. (b)
Genetic relationship of \emph{S. scabiei} mite derived from four human,
pig, dog and rabbit. (c) Principal component analysis (PCA) plot
of\emph{S. scabiei} populations using autosomal single nucleotide
polymorphisms (SNPs). The fraction of the variance explained is 47.44\%
for eigenvector 1 and 12.97\% for eigenvector 2. (d) Demographic history
of \emph{S. scabiei} variants\textbf{.} Ancestral population size was
inferred using pairwise sequentially Markovian coalescence (PSMC). Data
are shown individually for 20 mite populations. Generation time
(\emph{g} ) = 0.0575 years, mutation rate (\selectlanguage{greek}µ\selectlanguage{english}) = 5.8 \selectlanguage{ngerman}×
10\selectlanguage{english}\textsuperscript{-9} mutations per bp per generation. Cartoon humans
and animals in black represent the hosts of corresponding mite
populations. Marked year on the top indicated the emerging of Archaic
hunans and modern humans, as well as the domestication time of dogs,
pigs and rabbits from currently available literatures.

\textbf{Figure 3. Morphology of representative mites in the Acari and
organization of \emph{Hox} genes} . (a) Schematic diagram of mammal
skin. (b) Life cycle of sarcoptic mites. (c) Morphology of six species
of female mites. (d) Organization of \emph{Hox} genes of \emph{S.
scabiei}and other chelicerate species. Left panel, phylogenetic
relationship adapted from Figure 2a; central panel, \emph{Hox} genes and
transcript directions; right panel, traditional taxonomy.

\textbf{Figure 4. GO and KEGG enrichment of \emph{S. scabiei} specific
genes identified by orthoMCL.} (a) GO. (b) KEGG.

\selectlanguage{greek}\textbf{Figure 5. Distribution of θπ ratios and \emph{F}ST values, which
are calculated in 10-kb windows sliding in 5-kb steps.}\selectlanguage{english} (a) Genomic
regions with strong selective sweep signals between human mites and pig
mites. Data points located to the left and right of the left and right
vertical dashed lines, respectively (corresponding to the 5\% left and
right tails of the empirical \selectlanguage{greek}θπ \selectlanguage{english}ratio distribution, where the \selectlanguage{greek}θπ \selectlanguage{english}ratios
are -0.7 and 1.4, respectively), and above the horizontal dashed line
(the 5\% right tail of the empirical FST distribution, where FST is
1.91) were identified as selected regions for human mites (blue points)
and pig mites (red points), respectively. (b) Genomic regions with
strong selective sweep signals between human mites and dog mites. Data
points located to the left and right of the left and right vertical
dashed lines, respectively (corresponding to the 5\% left and right
tails of the empirical \selectlanguage{greek}θπ \selectlanguage{english}ratio distribution, where the \selectlanguage{greek}θπ \selectlanguage{english}ratios are
-0.7 and 1.4, respectively), and above the horizontal dashed line (the
5\% right tail of the empirical FST distribution, where FST is 1.91)
were identified as selected regions for human mites (blue points) and
dog mites (red points), respectively.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-1/Figure-1}

\end{center}
\end{figure}\selectlanguage{english}
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\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-2/Figure-2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-3/Figure-3}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-4/Figure-4}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-5/Figure-5}

\end{center}
\end{figure}

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