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\begin{document}

\title{\emph{Charybdis japonica} genome provides insights into desiccation
adaptation and sex-determining region}



\author[1]{Fangrui Lou}%
\author[2]{Tianxiang Gao}%
\author[3]{Qi Liu}%
\author[4]{Zhiqiang Han}%
\affil[1]{Yantai University}%
\affil[2]{Fishery College}%
\affil[3]{Wuhan Gooalgene Technology Company}%
\affil[4]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 29, 2024}


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\selectlanguage{english}
\begin{abstract}
\emph{Charybdis japonica} predominantly inhabits the intertidal zones
and has high desiccation tolerance. We present the first
chromosome-level \emph{C. japonica} genome, which contains 51
chromosomes, and the revised genome is 1431.02 Mb in length and has a
contig N50 size of 29.67 Mb. Among the contigs, 91.42\% were anchored to
51 chromosomes. Additionally, 824.02 Mb repeat elements, 30,900 coding
genes, 474 miRNAs, 15,570 tRNAs, 309 rRNAs, and 157 miRNAs were
identified in the \emph{C. japonica} genome. The whole-genome
resequencing data can contribute to the identification of sex-related
single-nucleotide polymorphisms and insertion--deletion mutations. The
0-10,120,000 bp of chromosome 37 is the sex-determining region of
\emph{C. japonica}. Comparative genome analysis identified 1,138
\emph{C. japonica}-specific gene families. Phylogenetic analysis showed
that \emph{C. japonica} has a close relationship with \emph{Portunus
trituberculatus}, which also belonged to family Portunidae, and
differentiated 42.1-135.5 million years ago. Demographic history
analysis suggested that the maximum effective population size of
\emph{C. japonica} was maintained until 0.5\selectlanguage{ngerman}×105 years ago. Relative
evolution rate showed that \emph{C. japonica} evolved slower than
\emph{Daphnia magna}, \emph{Penaeus vannamei}, and \emph{P.
trituberculatus}. Compared with other species, metabolism rate, oxygen
supply, oxidative stress, and various transporter-related genes were
expanded or underwent positive selection in \emph{C. japonica}, which
might contribute to \emph{C. japonica}'s ability to overcome diverse
stresses in drought environment. Decoding the present genome provides
valuable information for revealing the desiccation-adaptive and
sex-determining mechanisms of \emph{C. japonica} and also enriches the
genetic information to explore the evolutionary history and
environmental adaptation strategies of other Portunidae crabs.%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


\textbf{1. Introduction}

The Portunidae family, which comprises approximately 300 identified
species, has successfully settled in a variety of habitats from ocean
trenches to hydrothermal vents, intertidal mud flats, and terrenes (Cui
et al., 2021). Portunidae crabs have high ecological and economic value.
Although genomic information is believed to reveal the regulatory
mechanism of the biological characteristics of Portunidae members, only
a handful of Portunidae genomes have been published, such as those
of\emph{Scylla paramamosain} (Zhao et al., 2021) and \emph{Portunus
trituberculatus} (Tang et al., 2020). Hence, completing the genome
database of Portunidae crabs is urgently needed.

\emph{Charybdis japonica} (H. Milne Edwards, 1861; Figure 1) belongs to
genus \emph{Charybdis} of family Portunidae (Decapoda, Crustacea). This
species is a eurythermic and euryhaline marine crab (Yu et al., 2005)
and predominantly inhabits the intertidal zones of China, Japan, the
Korean Peninsula, and Southeast Asia countries. \emph{C. japonica} is a
delicious aquatic food with high amino acid and unsaturated fatty acid
contents; thus, it has high economic and medicinal values (Yu et al.,
2004). This fishery resource was further developed after the 1990s and
gradually became an important fishery resource in China's coastal areas
(Zheng, 2015). Meanwhile, artificial \emph{C. japonica} farming is
active in China. The economic traits of \emph{C. japonica} is gender
specific during the farming process. Specifically, male \emph{C.
japonica} has a faster growth rate, but females show a higher economic
value (Kolpakov and Kolpakov, 2011). Additionally, \emph{C. japonica}has
a higher desiccation tolerance than other crabs (Yu et al., 2004; Yu et
al., 2005; Zheng et al., 2013), which seems to help improve survival
rates for intertidal living and during farming and transportation
processes.

Dry transportation is one of the important segments of artificial
crustacean culture, which is beneficial to improve crustacean welfare
and reduce economic loss. However, dry transportation can still more
easily break the balance between crustacean and water environment and
lead to the decrease of crustacean physique, vitality, and survival rate
(Lorenzon et al., 2008; Paital, 2013). The tissues of crustaceans under
desiccation are always subjected to water deficit stress and hypoxia
stress (Ridgway et al., 2006; Paital, 2013). The gills are the first
tissue to suffer from desiccation because it is the main respiratory
organ of many crustaceans. The gill prefers to use oxygen in water
rather than that in air. The absence of water media leads to the
aggregation of gill lamellae, which reduces the gas exchange area of the
gill and ultimately leads to gill dysfunction syndrome (Greenaway et
al., 1996; Taylor and Wheatley, 1989; Levin, 2003). Insufficient oxygen
supply will further hinder oxidative metabolism, reduce ATP production,
cause imbalance in cell homeostasis, and even cause body death (Li et
al., 2010). Therefore, desiccation tolerance is an important factor that
influences the biological processes and survival of many marine
crustaceans, whether living in the natural intertidal zone or in the dry
transport process of artificial farming.

Many aquatic organisms have evolved and obtained some adaptive
strategies to establish higher tolerance to desiccation. For example,
some organisms in drought conditions can increase oxygen supply by
beating their hearts faster (Morris et al., 1999). Reducing oxygen
consumption rate is also an effective strategy to deal with the hypoxia
stress caused by desiccation (Urbina et al., 2013). Aquatic organisms
exposed to desiccation can increase the synthesis of respiratory
proteins (such hemoglobin and hemocyanin) to enhance the oxygen-carrying
rate of proteins and oxygen transport (Pascual, 2003; Urbina et al.,
2013). Crustaceans living in intertidal zones may be exposed to air and
suffer from drought stress for several hours during low tide. These
crustaceans have evolved the hard chitin shell to keep their gills moist
for long periods of time to adapt to the periodic dryness of the
intertidal zone. Meanwhile, adjustments in metabolic mechanisms are also
valuable for crustaceans living in the intertidal zone (Taylor and
Greenaway, 1984; Lu et al., 2016). However, the molecular mechanism of
desiccation tolerance in crustaceans has not yet been satisfactorily
elucidated.

Considering the stronger desiccation tolerance of \emph{C. japonica} (Yu
et al., 2004; Yu et al., 2005; Zheng et al., 2013), this species can be
used as a model crustacean to understand the regulation mechanism of
desiccation tolerance. Whole-genome genetic information can provide a
microperspective for revealing the desiccation-adaptive plasticity
of\emph{C. japonica} , that is, its flexibility in terms of the
capability to cope with water deficit stress and hypoxia stress.
Meanwhile, the sex differentiation of \emph{C. japonica} may be similar
to that of many crustaceans and controlled by androgenic or estrogen
gland; thus, it is susceptible to the influence of the external
environment (Cui et al., 2021). Therefore, decoding the whole-genome
genetic information can also enhance our understanding of the molecular
mechanisms of the sex differentiation of \emph{C. japonica} . In fact,
the publication of the whole-genome information of \emph{C. japonica}
will help enrich the genetic resources of family Portunidae and provide
many insights into their evolutionary history and environmental
adaptation strategies. Therefore, the whole-genome sequencing of
\emph{C. japonica} is necessary to carry out.

Here, we characterized a high-quality chromosome-anchored reference
genome of\emph{C. japonica} for the first time by combining short
Illumina reads, long PacBio reads, and Hi-C reads. We tried to correlate
the reported genomic data with the biology, evolutionary history, and
desiccation tolerance mechanisms of this species. Additionally, the
genome regions associated with underlying sex determination in \emph{C.
japonica} were predicted based on whole-genome resequencing data.
In-depth study of this extensive data will provide groundbreaking
mechanical insights into the genetic mechanisms associated with sex
differentiation and desiccation tolerance in \emph{C. japonica} and
other crustaceans.

\textbf{2. Materials and methods}

\textbf{2.1 Sampling, DNA extraction, and RNA extraction}

Wild adult female \emph{C. japonica} (approximately 210 g) individuals
were collected in December 2019 from Zhoushan. The animal study and
procedure were approved by the Animal Ethics Committee of Yantai
University. Fresh gill, muscle, heart, and intestinal tissues were
collected using sterilized dissection scissor and scalpel and then
snap-frozen in liquid nitrogen. High-quality genomic DNA was extracted
from the muscle tissues of \emph{C. japonica} using the Blood \& Cell
Culture DNA Mini Kit (QIAGEN, GER), and high-quality RNA was extracted
from \emph{C. japonica} tissues using the TRIzol Reagent Kit
(Invitrogen, USA). The integrity, purity, and concentration of the
genomic DNA were assessed using 1\% agarose gel electrophoresis,
NanoDrop 2000 analyzer (Thermo Fisher Scientific, USA), and Qubit 3.0
analyzer (Thermo Fisher Scientific, USA). RNA integrity and
concentration were measured using the Agilent Bioanalyzer 2100 System
(Agilent Technologies, USA) and NanoDrop 2000 analyzer (Thermo Fisher
Scientific, USA).

\textbf{2.2 Library construction and sequencing}

Three libraries, including Illumina library, SMRTbell library, and Hi-C
library, were combined to construct the high-quality \emph{C.
japonica}genome information. A high-quality short-insert (300--350 bp)
paired-end (PE) Illumina library was constructed in accordance with the
Illumina standard protocol (Illumina, USA), and the Illumina library was
then sequenced on the Illumina NovaSeq-6000 platform. A high-quality
SMRTbell library with a fragment size of 20 Kb was prepared using the
SMRTBell Template Preparation Kit 1.0 (PacBio, USA) according to the
manufacturer's protocol to obtain long genomics reads for promoting
genome assembly. The constructed SMRTBell library was added to one SMRT
cell and then transferred to the PacBio Sequel II sequencing platform
for long-read genomic sequencing. A high-quality Hi-C library was
constructed to obtain a chromosome-scale genome assembly, and the Hi-C
library was sequenced using the Illumina NovaSeq-6000 platform.
Additionally, a high-quality 150 bp PE RNA-sequencing (RNA-seq) library
was constructed according to the Illumina standard protocol (Illumina,
USA) and then sequenced on an Illumina NovaSeq-6000 platform.

Twenty \emph{C. japonica} individuals (11 females and 9 males) were used
for whole-genome resequencing. High-quality short-insert (300--350 bp)
PE Illumina libraries were constructed in accordance with the Illumina
standard protocol (Illumina, USA) and then sequenced on the Illumina
NovaSeq-6000 platform.

\textbf{2.3 Data filtering}

All raw Illumina reads were filtered by removing reads that included
adapter sequences, duplicated sequences, unknown nucleotides greater
than 10\%, and low-quality bases (quality scores [?] 5) greater than 50\%.
Hi-C reads that contain adapter sequences or less than 50 bp in length
were removed, and only PE Hi-C reads were retained. Bases with a quality
score of less than 20 at both ends of the reads were eliminated. All
RNA-seq reads were filtered by removing reads with sequencing adaptors,
unknown nucleotides (N ratio \textgreater{} 10\%), and low quality
(quality scores [?] 5).

\textbf{2.4 K-mer analyses of clean Illumina reads}

The remaining clean Illumina reads can be used to estimate the genomic
characteristics of\emph{C. japonica} before its genome was assembled. In
the present study, K-mer-based analysis was used to estimate the size,
heterozygosity rate, and repeat sequence of the \emph{C. japonica}
genome (Liu et al., 2013). The 17-mer was selected for K-mer analysis to
ensure that enough K-mers (4\textsuperscript{17}) were produced to cover
the entire \emph{C. japonica} genome.

\textbf{2.5 \emph{C. japonica} genome assembly and evaluation}

The Wtdbg2 software (Ruan and Li, 2020) was applied to assemble
the\emph{C. japonica} genome with PacBio long sequencing reads, and the
parameters as follows: best depth from input reads, 50.0; Kmer psize,
21; readCutoff, 1k. Although the PacBio long sequencing reads are
reliable, they still need to reach a certain sequencing depth to ensure
accuracy. First, long PacBio reads were applied to polish the consensus
sequence output from the Wtdbg2 software. More specifically, the pbmm2
(Chaisson and Tesler, 2012) and minimap2 software (Li, 2018) were used
to align the long PacBio reads to the consensus sequences, and the
alignment results were then corrected using the Arrow and Racon methods
(Walker et al., 2014). Furthermore, clean Illumina reads were compared
with the abovementioned long PacBio read-based polished genome sequences
using the BWA software (version 0.7.10-r789; Li and Durbin, 2009) and
then corrected using the Plion software (Walker et al., 2014). Finally,
the de-redundancy of the corrected \emph{C. japonica} genome was
performed according to the depth distribution and sequence similarity of
the reads. The filtered Hi-C reads were mapped to the polished \emph{C.
japonica} genome to detect the positional and directional errors in
contigs during 3D DNA assembly (Dudchenko et al., 2017). The Juicerbox
software (Durand et al., 2016) was used to modify the order and
directions of some contigs and to help in the determination of
chromosome boundaries. Genomic overlap was identified based on sequence
homology and long-distance interaction patterns, and the
chromosome-level \emph{C. japonica} genome was obtained.

Three methods were performed to evaluate the assembly effect of the
\emph{C. japonica} genome. First, the genome sequence was interrupted
with a step length of 1000 bp, and the interrupted sequences were
compared with the nucleotide sequence (NT) database by the Basic Local
Alignment Search Tool (BLAST) software to evaluate the accuracy of the
genome sequences. Second, the BWA (version 0.7.10-r789; Li and Durbin,
2009) and minimap2 software (Li, 2018) were used to compare the short
Illumina reads and long PacBio reads with the genome sequence,
respectively. The consistency of sequencing reads and genome sequence
was evaluated according to comparison rate. Additionally, the
completeness of conserved \emph{C. japonica} genes was evaluated using
the Benchmarking Universal Single-copy Orthologs (BUSCO, version 2.0;
Simao et al., 2015) and based on the orthologous gene database of
arthropods. Meanwhile, RNA-seq reads were compared with the genome using
the hisat2 software (Vaser et al., 2017) to assess genomic integrity.

\textbf{2.6 \emph{C. japonica} genome repeat element, coding gene and
NcRNA annotation}

\emph{C. japonica} genome annotation was carried out from three
perspectives, including repeat recognition, non-coding RNA (ncRNA) and
gene structure prediction, and functional annotation.

As an important part of the genome, repeat elements, including tandem
repeat and interpersed repeat (also known as transposon element
{[}TE{]}). In the present study, the Tandem Repeat Finder software
(Benson, 1999) was applied to find the tandem repeats in the \emph{C.
japonica} genome sequences. Meanwhile, the RepeatMasker and
RepeatProteinMask software (http://www.repeatmasker.org) were executed
to annotate the interpersed repeats of the \emph{C. japonica} genome
sequence based on the Repbase database (Jurka et al., 2005).
Furthermore, the RepeatMasker software (Bedell et al., 2000) was used to
compare the genome sequence to the repeat element database obtained by
the abovementioned methods to obtain a set of repeat elements. The
ultimate \emph{C. japonica} genome repeat elements were obtained by
removing the redundant repeat elements in the three methods.

Coding gene annotation includes structural prediction and functional
annotation. First, three prediction strategies, including homologs, ab
initio, and RNA-seq reads, were applied to predict the coding genes. In
the present study, \emph{Eriocheir sinensis} , \emph{Penaeus monodon}
,\emph{Penaeus vanamei} , and \emph{P. trituberculatus} were selected as
they are closely related to \emph{C. japonica,} and the protein
sequences of these species were downloaded for the structural prediction
of \emph{C. japonica} coding genes. Ab initio coding gene prediction was
performed using Augustus (version 2.7) (Stanke et al., 2006) and the
GenScan software (Burge and Karlin, 1997) with default settings. The
filtered RNA-seq reads were mapped to the \emph{C. japonica} genome
sequences for transcript assembly using the TopHat software, and the
Cufflinks software (Ghosh and Chan) was then used to predict the coding
genes. The MAKER2 software (Carson and Mark, 2011) was used to remove
the redundancy of coding genes predicted by the abovementioned methods,
and the HiCESAP process was used to obtain more complete and accurate
coding gene datasets. Predicted coding genes were then functionally
annotated using InterPro (Zdobnov and Apweiler, 2001), Gene Ontology
(GO) (Ashburner et al., 2000), Kyoto Encyclopedia of Genes and Genomes
(KEGG)\_ALL (Kanehisa and Goto, 2000), KEGG Orthology (KEGG\_KO)
(Kanehisa and Goto, 2000), Swiss-Prot (Bairoch and Apweiler, 2000),
Translation of European Molecular Biology Laboratory nucleotide sequence
(TrEMBL) (Boeckmann et al., 2003), TF, Pfam (Griffiths-Jones et al.,
2005), NR, and Eukaryotic Orthologous Groups (KOG) (Tatusov et al.,
2003) databases to determine the biological function and metabolic
pathways involved in the coding gene products.

NcRNAs, such as ribosomal RNA (rRNA), microRNA (miRNA), transfer RNA
(tRNA), and small nuclear RNA (snRNA), are RNAs that do not translate
proteins but have important biological functions. MiRNA functions in
gene silencing and can degrade its target gene or inhibit the
translation of the target gene into protein. TRNA and rRNA are directly
involved in protein synthesis. SnRNA is involved in the processing of
RNA precursors and is the main component of RNA spliceosomes. The
tRNAscan-SE software (version 1.3.1) (Lowe and Eddy, 1997) can be used
to search for tRNA sequences in the \emph{C. japonica} genome according
to the structural characteristics of tRNA. Considering the high
conservation of rRNA, the BLASTN software (Altschul et al., 1990) can be
used to search for rRNA in the\emph{C. japonica} genome based on the
rRNA sequences of closely related species. Additionally, miRNA and snRNA
were predicted using the INFERNAL software (version 1.1) (Nawrocki,
2014).

\textbf{2.7 Whole-genome resequencing analyses}

The BWA software (version 0.7.10-r789) (Li and Durbin, 2009) was used to
compare high-quality whole-genome resequencing reads with the
assembled\emph{C. japonica} genomes, and reads with low mapping
efficiency were further removed. The parameters were as follows: mem --M
--t --K 10000000. Filtered reads in ``sam'' format was sorted using the
Picard software (https://github.com/broadinstitute/picard) to remove
polymerase chain reaction (PCR) duplication. Single-nucleotide
polymorphism (SNP) and short insertion/deletion (InDel) were called
using a Bayesian approach as implemented in the SAMtools software (Li et
al., 2009). Finally, population differentiation index (\emph{F}
\textsubscript{ST}) and genotype frequency were used to locate the
sex-determining regions of \emph{C. japonica} .

\textbf{2.8 Comparative genomic analyses and testing for genomic
selection}

We performed an extensive orthologous gene comparison of \emph{C.
japonica} with eight other model species with genome datasets,
including\emph{Chionoecetes opilio} (GCA\_016584305.1), \emph{Hyalella
azteca}(GCA\_000764305.3), \emph{Penaeus vannamei} (GCA\_003789085.1),
\emph{P. trituberculatus} (GCA\_017591435.1),\emph{Drosophila
melanogaster} (GCA\_003401745.1),\emph{Amphibalanus amphitrite}
(GCA\_019059575.1), and \emph{Daphnia magna}(GCA\_003990815.1). We
downloaded the protein sequences from the National Center for
Biotechnology Information database. Subsequently, we extracted the
orthologous groups using the ORTHOMCL software (version 2.0.9) (Chen et
al., 2006) and filtered the BLASTP results with default parameters. The
single-copy orthologous genes shared by all nine species were further
aligned using the MUSCLE software (version 3.8.31) (Edgar, 2004), and
conserved sequences were extracted from each concatenated nucleotide
sequence using the Gblocks software with parameter -t=c. We performed
1000 nonparametric bootstrap replicates for the optimal GTRGAMMA
substitution model of all concatenated nucleotide sequences, and then a
phylogenetic tree of the nine species was constructed using the RaxML
software (version 8) (Stamatakis, 2014). The divergence times of the
nine species was estimated using the r8s software, and fossil evidence
was used to calibrate the divergence time. Furthermore, the CAFE
software (version 3.1) (De Bie et al., 2006) was applied to analyze the
expansion and contraction of the gene family, and P \textless{} 0.05 was
used to indicate remarkably changed gene families. Gene enrichment
analysis was performed for the extended and contracted gene families
based on GO and KEGG databases, respectively.

\textbf{2.9 Demographic history of \emph{C. japonica}}

The demographic history of \emph{C. japonica} was estimated using
pairwise sequentially markovian coalescent (PSMC) method (Li and Durbin,
2011) based on a mutation rate of 2e-9 and generation year of 2.

\textbf{2.10 Relative evolution rate}

Two methods, namely, Tajima's relative rate test model in the MEGA7
software (Kumar et al., 2016) and tpcv model in the LINTRE software
(Takezaki et al., 1995), were applied to evaluate the relative evolution
rate between \emph{C. japonica} and other species. Meanwhile, \emph{D.
melanogaster} was used as an outgroup in both analyses.

\textbf{2.11 Desiccation-adaptive mechanisms of \emph{C. japonica}}

Two desiccation-tolerant species (including \emph{C. japonica}
and\emph{A. amphitrite} ) were selected as foreground species, and then
the CAFE software (version 3.1) (De Bie et al., 2006) was applied to
analyze the expansion and contraction of the gene family to explore the
desiccation adaptive mechanisms of \emph{C. japonica} . Multiple tree
files were constructed for the nine species using all single-copy
orthologous genes The codeml program in the PAML software (version 4.9)
(Yang, 2007) was applied to estimate the non-synonymous/synonymous ratio
(\emph{w} ) to determine the positively selected genes (PSGs) of
\emph{C. japonica} and \emph{A. amphitrite} . Finally, gene enrichment
analysis was performed for the expanded gene families and PSGs based on
GO and KEGG databases, respectively.

\textbf{3. Results}

\textbf{3.1 Evaluation of \emph{C. japonica} genomic characteristics}

A total of 164.57 Gb of Illumina data, which correspond to 1,101,954,864
Illumina reads, were generated from the Illumina NovaSeq-6000 platform.
The Q20, Q30, and GC content of the Illumina reads were 96.70\%,
91.57\%, and 42.29\%, respectively. After 17-mer was set,
123,219,056,032 K-mers with a depth of 84 were obtained. The\emph{C.
japonica} genome size assessed by K-mer analysis was 1,398 Mb. After the
negative effect caused by incorrect K-mer was eliminated, the
revised\emph{C. japonica} genome size was 1,384 Mb. Meanwhile, the
heterozygous ratio and repeat of Illumina reads were 1.09\% and 61.24\%,
respectively.

\textbf{3.2 Genome assembly and completeness of the assembled genome}

The PacBio Sequel II platform generated 219.37 Gb (156.92-fold coverage)
long sequencing reads, which correspond to 18,433,125 subreads. Of all
the subreads, 16,799,937 subreads were larger than 2 Kb in length. The
maximum length, mean length, N50, N90, and GC content of the long PacBio
reads were 264,033 bp, 11,900 bp, 17,148 bp, 6,872 bp, and 43.60\%,
respectively. The long reads were assembled into 27,518 contigs, which
correspond to 1,507,921,137 bp. Among all the contigs, 27,517 contigs
were larger than 2 Kb in length. The maximum length, N50, N90, and GC
content of the assembled contigs were 1,759,181 bp, 107,376 bp, 23,463
bp, and 40.90\%, respectively. After the contigs were polished with
short Illumina reads and long PacBio reads, 27,223 corrected contigs
(1,529,349,659 bp) were obtained, and 27,220 contigs were larger than 2
Kb in length. The maximum length, N50, N90, and GC content of the
assembled corrected contigs were 1,758,737 bp, 109,775 bp, 24,031 bp,
and 41.20\%, respectively. The genome was subsequently processed to
remove redundancies and produced a 1429.38 Mb genome with a contig N50,
N90, and GC content of 118,954 bp, 30,162 bp, and 41.30\%, respectively.
Approximately 240.85 Gb clean Hi-C data were generated, and 91.42\% of
the contigs were anchored to 51 chromosomes to assemble the genome into
chromosome level. The final chromosome-level \emph{C. japonica} genome
after Hi-C data-assisted assembly was 1431.02 Mb with a contig N50 size
of 29.67 Mb (Figure.2).

The short Illumina reads and long PacBio reads were further compared
with the assembled\emph{C. japonica} genome sequences to assess the
consistency of sequences. A comparison of the results showed that
94.11\% and 87.67\% of short Illumina reads and long PacBio reads were
successfully mapped to the assembled genome, respectively (Table.1).
Based on Arthropoda gene set, 86.40\% complete BUSCOs were found in the
\emph{C. japonica} genome, including 82.27\% of the complete and
single-copy BUSCOs and 4.13\% complete and duplicated BUSCOs (Table.2).

\textbf{3.3 Repeat element annotation, gene prediction, and gene
annotation}

Four methods were applied to annotate the repeat elements of \emph{C.
japonica} genome and 824.02 Mb repeat elements were identified, which
account for 57.65\% of the assembly genome. The top 3 repeat elements
included DNA transposable element (DNA, 318.62 Mb; 22.29\% of the
genome), long interspersed nuclear elements (236.31 Mb, 16.53\% of the
genome), and long terminal repeats (179.30 Mb, 12.54\% of the genome,
Table.3).

\textbf{3.4 Gene structure prediction and function annotation}

A total of 30,900 coding genes were eventually predicted using the three
strategies. The average gene length, average coding gene length, average
exon per gene, average exon length, and average intron length were
11,027, 1,386, 5.12, 341.12, and 2,255 bp, respectively (Table 4). We
also functionally annotated all coding genes based on 10 publicly
available protein databases. The results showed that 21,979, 16,540,
21,220, 11,310, 15,903, 23,894, 1,458, 20,810, 23,010, and 16,956 coding
genes were successfully mapped to the InterPro, GO, KEGG\_ALL, KEGG\_KO,
Swissprot, TrEMBL, TF, Pfam, NR, and KOG databases, respectively. Among
all the coding genes, 25,325 were annotated in at least one database,
and 5,575 were unannotated.

In the present study, 474 miRNAs, 15,570 tRNAs, 309 rRNAs, and 157
snRNAs were identified from the\emph{C. japonica} genome. The total
lengths of the miRNAs, tRNAs, rRNAs, and snRNAs were 57,561 bp
(0.004027\% of genome), 1,135,923 bp (0.079470\% of genome), 49,795 bp
(0.003484\% of genome), and 28,110 bp (0.001967\% of genome),
respectively (Table 5).

\textbf{3.5 Sex-determining region identification of \emph{C. japonica}}

The whole-genome resequencing of 20 \emph{C. japonica} individuals from
different genders provided a genome-wide scan of SNPs and InDels.
Results showed 9 SNP variants (Number: 1,811,614; Table 6) and 12 InDel
variants (Number: 1,671,995; Table 7). The allele in chromosome 37
of\emph{C. japonica} had the highest \emph{F}
\textsubscript{ST}aggregation, which means that chromosome 37 is the
sex-determining chromosome of \emph{C. japonica} (Figure 3).
Furthermore, we calculated the genotype frequencies using bulk segregant
analysis (BSA), and the distribution pattern of Euclidean distance (ED)
showed that a difference between 0 and 10,120,000 bp in the chromosome
37 of female and male\emph{C. japonica} (Figure 4).

\textbf{3.6 Phylogenetic relationship and evolutionary history
of\emph{C. japonica}}

We compared the \emph{C. japonica} genome with seven other model
species, including\emph{A. amphitrite} , which is also a
desiccation-tolerant species to analyze the desiccation-adaptive
evolution of \emph{C. japonica} . Of all the genes (30,900) of \emph{C.
japonica} , 23,684 genes were assigned to 12,396 gene families
(Figure.5). Compared with the seven other species, 1,138 gene families
were unique to \emph{C. japonica} (Table 8, Figure 6). Using ORTHOMCL
software, we identified a set of 968 single-copy orthologous genes
shared by eight species (Figure 6). Phylogenetic analysis based on
single-copy orthologous genes clustered \emph{C. japonica} and \emph{P.
trituberculatus} into one branch, and the differentiation time between
\emph{C. japonica} and \emph{P. trituberculatus} was 42.1--135.5 Mya
(Figure 7). Compared with seven other species, we identified 2,417
expanded and 2,709 contracted gene families in \emph{C. japonica}
(Figure 7). The expanded gene families of\emph{C. japonica} were
significantly enriched in 1,375 GO terms and 85 KEGG pathways (corrected
\emph{P} \textless{} 0.05).

We applied the PSMC method to estimate the demographic history
of\emph{C. japonica} . The historical demographic pattern (Figure 8)
shows that \emph{C. japonica} maintained a relatively stable population
size, followed by an obvious expansion, and reached their maximum
effective population size about 0.5\selectlanguage{ngerman}×10\textsuperscript{5} years ago.

\textbf{3.7 Relative evolution rate of \emph{C. japonica}}

Relative evolution rate can explore the historical status and molecular
evolution rate of species. The present study analyzed the relative
evolution rates of \emph{C. japonica} and other species. The results
showed that \emph{C. japonica} evolved faster than \emph{A. amphitrite}
,\emph{H. azteca} , and \emph{C. opilio} but evolved slower than
\emph{D. magna} , \emph{P. vannamei} , and \emph{P. trituberculatus}
(Figure 9, Table 9, and Table 10).

\textbf{3.8 Desiccation-adaptive evolution of \emph{C. japonica}}

Changes in gene copy number affect the desiccation-adaptive evolution
of\emph{C. japonica.} The present study examined the expansion and
contraction of gene families and PSGs in \emph{C. japonica} and \emph{A.
amphitrite} genomes to uncover the underlying desiccation-adaptive
mechanisms. Compared with other species, the expanded gene families or
PSGs were predominantly involved in metabolism rate (i.e., glycogen
phosphorylase gene), oxygen supply (i.e., inositol 1,4,5-trisphosphate
receptor {[}\emph{IP3} {]} gene, ribose-phosphate pyrophosphokinase A
{[}\emph{PRPS1} {]} gene, serine/threonine-protein phosphatase
{[}\emph{STK} {]} gene, glutathione reductase {[}\emph{GSR} {]} gene),
oxidative stress (i.e., heat shock protein {[}\emph{HSP} {]} gene, zinc
finger {[}\emph{ZNF} {]} gene), and various transporters (annotation
information of expanded gene families and PSGs, which might contribute
to \emph{C. japonica} 's ability to overcome diverse stresses in drought
environment.

\textbf{4. Discussion}

Despite their ecological and economic importance, few crab genomes have
been reported. \emph{C. japonica} is of major interest, because it is
the most important near-shore economic crab. Moreover, \emph{C.
japonica}has long tolerance to desiccation. In the present study, we
assembled the first chromosome-level \emph{C. japonica} genome with a
genome size of 1431.02 Mb and a contig N50 of 29.67 Mb, which is larger
than the genome size of \emph{P. trituberculatus} (1.00 Gb) (Tang et
al., 2020) of family Portunidae but smaller than that of \emph{S.
paramamosain}(1.55 Gb) (Zhao et al., 2021). The genome size after short
Illumina read correction and long PacBio read correction was also
confirmed by survey sequence results (1,398 Mb). Notably, the number (n
= 51) of chromosomes assembled based on Hi-C reads differs from the
karyotype analysis result (n = 57) (Yan et al., 2009). Some \emph{C.
japonica} chromosomes have extremely small morphology and are rich in
repeat elements, and most chromosomes in the mitosis metaphase are
spot-shaped and difficult to distinguish; therefore, identifying all
\emph{C. japonica} chromosomes through Hi-C interaction is very
difficult (Lou et al., 2004). In fact, we did find some unmanageable
repeat sequences through Hi-C interaction. A large number of sequencing
reads (short Illumina reads and long PacBio reads) can be successfully
mapped to the assembled genome sequence, which means that these reads
have high consistency. Meanwhile, 86.40\% complete BUSCOs were found in
the \emph{C. japonica} genome; thus, the genome that we assembled is
more complete. A total of 824.02 Mb of repeat elements were identified
and account for 57.65\% of the \emph{C. japonica} genome. We speculate
that the high proportion of repeat elements is one of the critical
reasons for the large genome size of\emph{C. japonica} . In fact,
previous association analysis between the number of whole-genome
repetitive sequences and genome size in 44 plants and 68 vertebrates
confirmed that the proportion of repetitive sequences is positively
correlated with genome size (Gao et al., 2018). Additionally, we
obtained accurate genome-annotated information through many methods. In
conclusion, we presented a basic resource for exploring\emph{C.
japonica} biological processes at the genomic level.

\textbf{4.1 Whole-genome resequencing reads predicted a potentially
sex-determining region}

Based on the whole-genome resequencing, we predicted a sex-determining
region (approximately 10 Mb) in chromosome 37 of \emph{C. japonica} .
Interestingly, we found some genes in this region that seem to be
involved in sex differentiation in \emph{C. japonica} , namely,
the\emph{F-box} gene and WD repeat domain (\emph{WDR} ) gene. A previous
study considered that the F-box protein encoded by recombinant
\emph{FBXW} gene (containing\emph{F-box} gene and \emph{WDR} gene) is
specific for substrate recognition in ubiquitin-mediated proteolysis
(Risseeuw et al., 2003). It can bind S-phase kinase-associated protein 1
(SKP1) and Cullin to form an evolutionary conserved Skp--Cullin--F-box
(SCF) ubiquitin ligase complex (Figure 10) (Zhang et al., 2002; Welcker
and Clurman, 2008; Roberts et al., 2020), which can selectively bind to
degraded proteins and participate in the ubiquitin--proteasome pathway
(UPP) (Li et al., 2010). The UPP system in plants causes functional loss
of male germ cells by regulating the conversion of functional proteins
(Kipreos and Pagano, 2000). The sex-determining mechanism of crustaceans
living in the open environment is still in the early stage of evolution,
and the intensity of genetic factors in determining the gender of
crustaceans is lower than that of the external environment (Lou et al.,
2004; Wu et al., 2002). Therefore, we have every reason to infer that
the UPP system regulated by recombinant \emph{FBXW} gene may potentially
limit the testis development of male \emph{C. japonica} , reduce sperm
production, and even promote vitellus formation. However, this mechanism
is still speculative and needs further verification.

\textbf{4.2 More accurate evolutionary history of \emph{C. japonica}}

The presented genomic resource can help us better understand the
evolutionary history of \emph{C. japonica} . The differentiation of
conserved single-copy orthologous genes always leads to species
differentiation; thus, we believe that the evolutionary history
of\emph{C. japonica} can be more accurately deetermined using widespread
single-copy orthologous genes (Liang et al., 2013; Fitch, 1970). In the
present study, 968 single-copy orthologous genes were obtained and then
applied to construct the phylogenetic relationship of \emph{C. japonica}
. Expectedly, the constructed phylogenetic structure is considerably
congruent with the prevailing morphological and molecular biological
views that crabs (\emph{P. trituberculatus} and \emph{C. japonica} )
from family Portunidae eventually cluster into one branch. Moreover, the
evolutionary sequence of \emph{C. japonica} was identified based on
differentiation times, and these results provided evidence to prove the
existence of ``carcinization'' (Keiler et al., 2017; Cui et al., 2021).
In fact, 1,138 unique gene families were found in the genome, and these
gene families can contribute to \emph{C. japonica} -specific adaptation
(Wissler et al., 2013). Additionally, the relatively evolution rates of
different species may also mean differences in environmental stability
(Tang et al., 2020).

\textbf{4.3 Desiccation-adaptive mechanisms of \emph{C. japonica}}

Comparative genomics can provide insights into the unique adaptive
plasticity of marine species (Han et al., 2021; Xu et al., 2021). In the
present study, we hypothesized the adaptive mechanisms of desiccation
tolerance based on comparative genomics. Previous studies suggested that
crustaceans may continuously undergo the double stress of dehydration
and hypoxia in a drought environment. Specifically, desiccation disrupts
the internal osmotic pressure and metabolic capacity of crustaceans
(Haupt et al., 2006; Carlson and Rowe, 2009). Moreover, desiccation can
reduce the oxygen-binding ability of hemoglobin and result in hypoxic
stress in crustaceans (Omori et al., 1998; Allen et al., 2012). The
prolonged disruption of the respiratory mechanism may further impair the
immune function of crustaceans and eventually lead to death (Madenjian
et al., 1987). Additionally, the activity of the antioxidant enzyme
system directly determines the desiccation tolerance of crustaceans
(Jiang et al., 2014). Based on the annotation information, the
desiccation-adaptive mechanisms of\emph{C. japonica} was supported by
the marked expansion of gene families or the positive selection of genes
related to metabolism rate, oxygen supply, oxidative stress, and various
transporters.

\textbf{4.3.1 Glycometabolism provides carbon skeleton and energy
for\emph{C. japonica} in drought environment}

Carbohydrates can provide carbon skeleton and energy for the growth and
metabolism of organisms and enhance stress resistance. Glycometabolism
is also the center of biological metabolism, which connects the
metabolism of proteins, lipids, nucleic acids, and secondary substances
(Sun et al., 2015). Based on the comparative genome, abundant
glycometabolism-related genes were expanded or positively selected
in\emph{C. japonica} and further contributed to the desiccation
tolerance of \emph{C. japonica} . The reasons for the improvement in the
desiccation tolerance of \emph{C. japonica} by carbohydrate may be as
follows: (i) carbohydrates can accumulate and regulate osmotic pressure
and enhance the water retention of cells (Savitch et al., 2000; Wilson
et al., 2001); (ii) carbohydrates can protect biological substances,
such as biofilms and biological macromolecules, to maintain cytoskeletal
integrity in drought environments (Hincha et al., 2002; Saadeldin et
al., 2020); (iii) carbohydrates can produce energy for resistance to
desiccation (Savitch et al., 2000); and (iv) carbohydrates can also be
used as a signal molecule involved in some desiccation resistance
regulation mechanisms (Paul et al., 2008).

\textbf{4.3.2 High oxygen transport ability improves the hypoxia
tolerance of \emph{C. japonica}}

Although hemocyanin has a low affinity for oxygen, it is still an
essential oxidizing medium for crustacean tissues in the absence of
oxygen (Figure 11) (Charlotte, 1980; Fujieda et al., 2010). Desiccation
can inhibit oxygen supply and induce respiratory acidosis in crustaceans
(Defur, 1988). Respiratory acidosis further reduces the ability of
oxygen and hemoglobin to bind, which exacerbates oxygen deficiency and
tissue hypoxia (Allen et al., 2012). However, desiccation-tolerant
crustaceans can regulate ion (including Ca\textsuperscript{2+} and
Mg\textsuperscript{2+}) concentration to improve the oxygen-binding
ability of hemocyanin and promote oxygen transfer between tissues
(Charlotte, 1980). The expansion or positive selection of the
\emph{IP3}and \emph{PRPS1} genes means that \emph{C. japonica} can
maintain Ca\textsuperscript{2+} and Mg\textsuperscript{2+} homeostasis
to ensure the oxygen-binding ability of hemocyanin to resist hypoxia in
drought environments. Hypoxia-inducible factors (HIFs) also play an
important role in hypoxia response by binding with hypoxia response
elements near the downstream gene promoter for transcriptional
activation (Hirota, 2002; Martens et al., 2007). The \emph{STK} gene in
\emph{C. japonica}can enhance HIF phosphorylation and increase the
molecular weight of HIFs (Richard et al., 1999). In addition, the
\emph{GSR} gene, which prevents the oxidative decomposition of
hemocyanin, was also positively selected or expanded. Glutathione
reductase encoded by the \emph{GSR}gene can effectively maintain reduced
glutathione in cells, which plays an important role in preventing the
oxidative decomposition of hemocyanin (Kanzok et al., 2001). In
conclusion, the maintenance of hemocyanin level and oxygen-carrying
capacity will help \emph{C. japonica} cope with hypoxia in drought
environment.

\textbf{4.3.3 \emph{C. japonica} seem to have a greater capacity for
oxidative stress}

We detected the remarkable expansion or positive selection of
\emph{HSP}genes (including \emph{HSP70} and \emph{HSP90} ), which
probably encode prototypical chaperonin to prevent the accumulation of
unfolding proteins and/or assist in the refolding or degradation of
denatured proteins (Haslbeck et al., 2005; Beck et al., 2009). The
\emph{ZNF} gene family was also enriched in the \emph{C. japonica}
genome. Zinc finger proteins are the most abundant protein in eukaryotes
and have a wide range of structures and functions (Laity et al., 2011).
Interestingly, the positive selection or expansion of RING-type zinc
finger proteins occurred in \emph{C. japonica} . As a zinc finger
protein widely found in plants and animals, RING-type zinc finger
protein confers a strong drought tolerance in \emph{Arabidopsis
thaliana} (Moon et al., 2010), because RING-type zinc finger protein can
regulate the ubiquitin--proteasome system to degrade misfolded proteins
and thus improve the defense of an organism against external
environmental stress (Ryota et al., 2002).

In conclusion, \emph{C. japonica} 's metabolism, oxygen supply, and
antioxidative stress abilities may help this species to survive longer
in drought environments. Due to the high desiccation-tolerance
capability of \emph{C. japonica} , this information will be valuable in
the transportation and farming strategies.

\textbf{5. Conclusion}

A chromosomal-level genome of \emph{C. japonica} has been published for
the first time by integrating the short Illumina reads, long PacBio
reads, and Hi-C reads. This is a highly assembled and reliable genome
and it enriches the crustacean genome database. Meanwhile, we
successfully annotated the repeat elements, coding genes, miRNAs, tRNA,
rRNAs, and snRNAs in the \emph{C. japonica} genome. These information
will be necessary for future research into \emph{C. japonica} biology.
Additionally, the whole-genome resequencing data of \emph{C.
japonica}with different gender provided a genome-wide scan of SNPs and
InDels, which were used to predict the sex-determining chromosome of
\emph{C. japonica} . \emph{C. japonica} is a crustacean with strong
desiccation tolerance. This study used comparative genome analysis to
study the evolutionary history of \emph{C. japonica} , as well as a
series of genes that may contribute to desiccation adaption in \emph{C.
japonica} . The present results were beneficial in elucidating the
evolution process in\emph{C. japonica} and other marine organisms under
desiccation stress.

\textbf{Acknowledgements}

This work was supported by the Zhejiang Provincial Natural Science
Foundation of China (LR21D060003) and the National Natural Science
Foundation of China (32070513).

Author contributions

Z.Q.H. and F.R.L. conceived and managed the project. Z.Q.H. and T.X.G.
collected the sequencing samples. Q.L. extracted the DNA/RNA and
performed the genome sequencing. F.R.L. analyzed the data. Z.Q.H. and
F.R.L. wrote the manuscript. All authors reviewed and approved the final
manuscript.

\textbf{Conflicts of interests}

No

\textbf{Data Accessibility Statement}

Raw sequencing data (including PacBio, Hi-C, Survey, and RNA-seq reads)
for\emph{C. japonica} genome has been deposited at the Sequence Read
Archive (SRA) (SRR16072374, SRR16072376, SRR16072375 and SRR16078881)
under BioProject number PRJNA766329. Raw whole-genome resequencing data
of 20 \emph{C. japonica} has been deposited at the SRR16894624 to
SRR16894643 under BioProject number PRJNA779101.

\textbf{References}

Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (2008) Basic Local
Alignment Search Tool (BLAST). \emph{J Mol Biol} , \textbf{215} ,
403-410. DOI: 10.1016/S0022-2836(05)80360-2.

Allen BJ, Rodgers B, Tuan YH, Levinton JS (2012) Size-dependent
temperature and desiccation constraints on performance capacity:
implications for sexual selection in a fiddler crab. \emph{J Exp Mar
Biol Ecol} , \textbf{438} , 93-99. DOI: 10.1016/j.jembe.2012.09.009.

Burge C, Karlin S (1997) Prediction of complete gene structures in human
genomic DNA. \emph{J Mol Biol} ,\textbf{268} , 78-94. DOI:
10.1111/j.1365-294X.2005.02509.x.

Benson G (1999) Tandem repeats finder: a program to analyze DNA
sequences. \emph{Nucleic Acids Res} , \textbf{27} , 573-580. DOI:
10.1093/nar/27.2.573.

Bairoch A, Apweiler R (2000) The SWISS-PROT protein sequence database
and its supplement TrEMBL in 2000.\emph{Nucl Acids Res} , \textbf{28} ,
45-48. DOI: 10.1093/nar/28.1.45.

Bedell JA, Korf I, Gish W (2000) MaskerAid: A performance enhancement to
RepeatMasker. \emph{Bioinformatics} , \textbf{16} , 1040-1041. DOI:
10.1093/bioin forma tics/16.11.1040.

Boeckmann B, Bairoch A, Apweiler R, Blatter M, Estreicher A, Gasteiger
E, Martin M, Michoud K, O'Donovan C, Phan I, Pilbout S, Schneider M
(2003) The SWISS-PROT protein knowledgebase and its supplement TrEMBL in
2003.\emph{Nucleic Acids Res} , \textbf{31} , 365-370. DOI:
10.1093/nar/gkg095.

Beck M, Malmstrom JA, Lange V, Schmidt A, Deutsch EW, Aebersold R (2009)
Visual proteomics of the human pathogen \emph{Leptospira interrogans}
.\emph{Nat Methods} , \textbf{6} , 817-823. DOI: 10.1038/nmeth.1390.

Charlotte PM (1980) Respiration function of the hemocyanins. \emph{Am
Zool} , \textbf{20} , 19-38.

Chen F, Mackey AJ, Jr CJS, Roos DS (2006) OrthoMCL-DB: querying a
comprehensive multi-species collection of ortholog groups. \emph{Nucleic
Acids Res} , \textbf{34} , D363-D368. DOI: 10.1093/nar/gkj123.

Carlson BE, Rowe MP (2009) Temperature and desiccation effects on the
antipredator behavior of\emph{Centruroides vittatus} (Scorpiones:
Buthidae).\emph{J Arachnol} , \textbf{37} , 321-330. DOI:
10.1636/Hi09-06.1.

Chaisson MJ, Tesler G (2012) Mapping single molecule sequencing reads
using basic local alignment with successive refinement (BLASR):
application and theory. \emph{BMC Bioinformatics} , \textbf{13} , 238.
DOI: 10.1186/1471-2105-13-238.

Cantarel BL, Korf L, Robb SMC, Parra G, Ross E, Moore B, Holt C,
Alvarado AS, Carson H, Mark Y (2011) MAKER2: an annotation pipeline and
genome-database management tool for second-generation genome projects.
\emph{BMC Bioinformatics} ,\textbf{12} , 491. DOI:
10.1186/1471-2105-12-491.

Cui ZX, Liu Y, Yuan JB, Zhang XJ, Ventura T, Ma KY, Sun S, Song CW, Zhan
DL, Yang YN, Fan GY, Cai QL, Du J, Shi CC, Hao SJ, Fitzgibbon QP, Smith
GG, Xiang JH, Chan TY, Hui M, Bao CC, Li FH, Chu KH (2021) The Chinese
mitten crab genome provides insights into adaptive plasticity and
developmental regulation. \emph{Nat Commun} , \textbf{12} , 2395. DOI:
10.1038/s41467-021-22604-3.

Defur PL (1988) Systemic respiratory adaptations to air exposure in
intertidal decapod crustaceans. \emph{Am Zool} , 28, 115-124. DOI:
10.1093/icb/28.1.115.

De Bie T, Cristianini N, Demuth JP, Hahn MW (2006) CAFE: a computational
tool for the study of gene family evolution. \emph{Bioinformatics}
,\textbf{22} , 1269-1271. DOI: 10.1093/bioinformatics/btl097.

Durand NC, Robinson JT, Shamim MS, Machol I, Mesirov JP, Lander ES,
Adien EL (2016) Juicebox provides a visualization system for Hi-C
contact maps with unlimited zoom. \emph{Cell Syst} , \textbf{3} ,
99-101. DOI: 10.1016/j.cels.2015.07.012.

Dudchenko O, Batra SS, Omer AD, Nyquist SK, Hoeger M, Durand NC, Shamim
MS, Machol I, Lander ES, Aiden AP, Aiden EL (2017) \emph{De
novo}assembly of the Aedes aegypti genome using Hi-C yields
chromosome-length scaffolds. \emph{Science} , \textbf{356} , 92-95. DOI:
10.1126/science.aal3327.

Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy
and high throughput. \emph{Nucleic Acids Res} , \textbf{32} , 1792-1797.
DOI: 10.1093/nar/gkh340.

Fitch WM (1970) Distinguishing homologous from analogous proteins.
\emph{Syst Zool} \textbf{19} , 99-113. DOI: 10.2307/2412448.

Fujieda N, Yakiyama A, Itoh S (2010) Catalytic oxygenation of phenols by
arthropod hemocyanin, an oxygen carrier protein, from \emph{Portunus
trituberculatus} . \emph{Dalton Trans} , \textbf{39} , 3083-3092. DOI:
10.1039/c000760a.

Greenaway P, Morris S, McMahon BR, Gallagher CAFL (1996) Air breathing
by the purple shore crab, \emph{Hemigrapsus nudus} (Dana). I.
Morphology, behaviour, and respiratory gas exchange. \emph{Physiol Zool}
, \textbf{69} , 785-805. DOI: 10.2307/30164230.

Griffiths-Jones S, Moxon S, Marshall M, Khanna A, Bateman A (2005) Rfam:
annotating non-coding RNAs in complete genomes. \emph{Nucleic Acids Res}
, \textbf{33} , D121-D124. DOI: 10.1093/nar/gki081.

Ghosh S, Chan CKK (2016) Analysis of RNA-Seq data using TopHat and
Cufflinks. \emph{Methods Mol Biol} , \textbf{1374} , 339-361. DOI:
10.1007/978-1-4939-3167-5\_18.

Gao SH, Yu HY, Wu SY, Wang S, Geng JN, Luo YF, Hu SN (2018) Advances of
sequencing and assembling technologies for complex
genomes.\emph{Hereditas} , \textbf{40} , 944-963. DOI:
10.16288/j.yczz.18-255.

Hirota K (2002) Hypoxia-inducible factor 1, a master transcription
factor of cellular hypoxic gene expression. \emph{J Anesth} ,
\textbf{16} , 150-159. DOI: 10.1007/s005400200011.

Haslbeck M, Franzmann T, Weinfurtner D, Buchner J (2005) Some like it
hot: the structure and function of small heat-shock proteins. \emph{Nat
Struct Mol Biol} , \textbf{12} , 842-846. DOI: 10.1038/nsmb993.

Haupt P, Brouwer SL, Branch GM, Gäde G (2006) Effects of exposure to air
on the escape behaviour and haemolymph chemistry of the South African
Cape lobster, \emph{Jasus lalandii} . \emph{Fish Res} ,\textbf{81} ,
210-218. DOI: 10.1016/j.fishres.2006.07.004.

Han ZQ, Guo XY, Liu Q, Liu SS, Zhang ZX, Xiao SJ, Gao TX (2021)
Whole-genome resequencing of Japanese whiting (\emph{Sillago japonica} )
provide insights into local adaptations. \emph{Zool Res} , 42, 548-561.
DOI: 10.24272/j.issn.2095-8137.2021.116.

Jurka J, Kapitonov VV, Pavlicek A, Klonowski P, Kohany O, Walichiewicz J
(2005) Repbase Update, a database of eukaryotic repetitive elements.
\emph{Cytogenet Genome Res} , \textbf{110} , 462-467. DOI:
10.1159/000084979\begin{CJK}{UTF8}{gbsn}。

\end{CJK}\selectlanguage{english}Jiang N, Wang F, Lu YL, Dong SL (2014) Effect of air-exposure stress on
antioxidant capacity and stress response of swimming crab
(\emph{Portunus trituberculatus} ). \emph{Journal of Fisheries of China}
, \textbf{38} , 1996-2004. (In Chinese).

Kanehisa M, Goto S (2000) KEGG: kyoto encyclopedia of genes and genomes.
\emph{Nucleic Acids Res} ,\textbf{28} , 27-30. DOI: 10.1093/nar/28.1.27.

Kipreos ET, Pagano M (2000) The F-box protein family. \emph{Genome Biol}
, \textbf{1} , 30021-30027. DOI: 10.1186/gb-2000-1-5-reviews3002.

Kanzok SM, Fechner A, Bauer H, Ulschmid JK, M\selectlanguage{ngerman}üller HM, Botella-Munoz J,
Schneuwly S, Schirmer R, Becker K (2001) Substitution of the thioredoxin
system for glutathione reductase in \emph{Drosophila melanogaster}
.\emph{Science} , \textbf{291} , 643-646. DOI:
10.1126/science.291.5504.643.

Kolpakov N, Kolpakov E (2011) On the biology of the Japanese swimming
crab \emph{Charybdis japonica} (Portunidae) in waters of primorye at the
northern boundary of their range. \emph{Russ J Mar Biol} , \textbf{37} ,
570-578. DOI: 10.1134/S1063074011070042.

Kumar S, Stecher G, Tamura K (2016) MEGA7: molecular evolutionary
genetics analysis version 7.0 for bigger datasets. \emph{Mol Biol Evol}
, \textbf{33} , 1870. DOI: 10.1093/molbe v/msw054.

Keiler J, Wirkner CS, Richter S (2017) One hundred years of
carcinization - the evolution of the crab-like habitus in Anomura
(Arthropoda: Crustacea). \emph{Biological Journal of the Linnean
Society} , \textbf{121} , 200-222.

Lowe TM, Eddy SR (1997) tRNAscan-SE: a program for improved detection of
transfer RNA genes in genomic sequence. \emph{Nucleic Acids Res} ,
\textbf{25} , 955-964. DOI: 10.1093/nar/25.5.955.

Levin LA (2003) Oxygen minimum zone benthos: adaptation and community
response to hypoxia. Oceanogr Mar Biol, 41, 1-45. DOI:
10.1007/s00248-002-2023-y.

Lou YD, Liu YH, Qiu GF (2004) Advances in sex determination of shrimps
(prwans) and crabs. \emph{J Shanghai Ocean Uni} , 2, 157-163. (In
Chinese)

Lorenzon S, Giulianini PG, Libralato S, Martinis M, Ferrero EA (2008)
Stress effect of two different transport systems on the physiological
profiles of the crab \emph{Cancer pagurus} .\emph{Aquaculture}
,\textbf{278} , 156-163. DOI: 10.1016/j.aquaculture.2008.03.011.

Li H, Durbin R (2009) Fast and accurate short read alignment with
Burrows-Wheeler transform.\emph{Bioinformatics} , \textbf{25} ,
1754-1760. DOI: 10.1093/bioinformatics/btp324.

Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G,
Abecasis G, Durbin R, 1000 Genome Project Data Processing Subgroup
(2009) The sequence alignment/map format and SAMtools.
\emph{Bioinformatics} ,\textbf{25} , 2078-2079. DOI:
10.1093/bioinformatics/btp352.

Li L, Xia K, Fu YF, Tian Y (2010) Plant F-box protein and its biological
function. \emph{Agricultural science and technology} , \textbf{11} ,
9-12. (In Chinese)

Li J, Chen P, Liu P, Gao B, Wang Q, Jian L (2010) The cytosolic
manganese superoxide dismutase cDNA in swimming crab\emph{Portunus
trituberculatus} : Molecular cloning, characterization and expression.
\emph{Aquaculture} , \textbf{309} , 31-37. DOI:
10.1016/j.aquaculture.2010.09.008.

Li H, Durbin R (2011) Inference of human population history from
individual whole-genome sequences.\emph{Nature} , \textbf{475} ,
493-496. DOI: 10.1038/nature10231.

Laity JH, Lee BM, Wright PE (2011) Zinc finger proteins: New insights
into structural and functional diversity.\emph{Curr Opin Struct Biol} ,
\textbf{11} , 39-46. DOI: 10.1016/S0959-440X(00)00167-6.

Liu BH, Shi YJ, Yuan JY, Hu XS, Zhang H, Li N, Li ZY, Chen YX, Mu DS,
Fan W (2013) Estimation of genomic characteristics by analyzing k-mer
frequency in \emph{de novo} genome projects. \emph{ArXiv} , 1308.2012.
DOI: 10.1016/S0925-4005(96)02015-1.

Liang D, Shen X, Zhang P (2013) One thousand two hundred ninety nuclear
genes from a genome-wide survey support lungfishes as the sister group
of tetrapods. \emph{Mol Biol Evol} , \textbf{30} , 1803-1807. DOI:
10.1093/molbev/mst072.

Lu Y, Zhang D, Wang F, Dong S (2016) Hypothermal effects on survival,
energy homeostasis and expression of energy-related genes of swimming
crabs \emph{Portunus trituberculatus} during air exposure.\emph{J Therm
Biol} , \textbf{60} , 33-40. DOI: 10.1016/j.jtherbio.2016.06.007.

Li H (2018) Minimap2: pairwise alignment for nucleotide
sequences.\emph{Bioinformatics} , \textbf{34} , 3094-3100. DOI:
10.1093/bioinformatics/bty191.

Madenjian CM, Rogers GL, Fast AW (1987) Predicting night time dissolved
oxygen loss in prawn ponds of Hawaii: Part I. Evaluation of traditional
methods.\emph{Aquacult Eng} , \textbf{6} , 191-208. DOI:
10.1016/0144-8609(87)90004-5.

Morris S, Oliver S (1999) Circulatory, respiratory and metabolic
response to emersion and low temperature of \emph{Jasus edwardsii} :
simulation studies of commercial shipping methods.\emph{Comp Biochem
Phys A} , \textbf{122} , 299-308. DOI: 10.2514/2.983.

Martens LK, Kirschner KM, Warnecke C, Scholz H (2007) Hypoxia-inducible
factor-1 (HIF-1) is a transcriptional activator of the TrkB neurotrophin
receptor gene. \emph{J Biol Chem} , \textbf{282} , 14379-14388. DOI:
10.1074/jbc.M609857200.

Moon YR, Seok KC, Woo TK (2010) The Arabidopsis C3H2C3-type RING E3
ubiquitin ligase AtAIRP1 is a positive regulator of an abscisic
acid-dependent response to drought stress.\emph{Plant Physiol} ,
\textbf{154} , 1983-1997. DOI: 10.1104/pp.110.164749.

Markl J (2013) Evolution of molluscan hemocyanin structures.
\emph{BBA-Proteins Proteom} ,\textbf{1834} , 1840-1852. DOI:
10.1016/j.bbapap.2013.02.020.

Nawrocki EP (2014) Annotating functional RNAs in genomes using infernal.
\emph{Methods Mol Biol} ,\textbf{1097} , 163-197. DOI:
10.1007/978-1-62703-709-9\_9.

Pascual C, Gaxiola G, Rosas C (2003) Blood metabolites and hemocyanin of
the white shrimp, \emph{Litopenaeus vannamei} : the effect of culture
conditions and a comparison with other crustacean species. \emph{Mar
Biol} , \textbf{142} , 735-745. DOI: 10.1007/s00227-002-0995-2.

Paul MJ, Primavesi LF, Jhurreea D, Zhang Y (2008) Trehalose metabolism
and signaling. \emph{Annu Rev Plant Biol} , \textbf{59} , 417-441. DOI:
10.1146/annurev.arplant.59.032607.092945.

Paital B (2013) Antioxidant and oxidative stress parameters in brain of
\emph{Heteropneustes fossilis} under air exposure condition; role of
mitochondrial electron transport chain. \emph{Ecotoxicol Environ Saf} ,
\textbf{95} , 69-77. DOI: 10.1016/j.ecoenv.2013.05.016.

Richard DE, Berra E, Gothié E, Roux D, Pouysségur J (1999) p42/p44
mitogen-activated protein kinases phosphorylate hypoxia-inducible factor
1\selectlanguage{greek}α \selectlanguage{english}(HIF-1\selectlanguage{greek}α\selectlanguage{english}) and enhance the transcriptional activity of HIF-1. \emph{J
Biol Chem} , \textbf{274} , 32631-32637. DOI: 10.1074/jbc.274.46.32631.

Ryota T, Noriyuki M, Akihiko N, Koji H, Chiharu A, Naoto S, Eiichi M
(2002) EL5, a rice N-acetylchitooligosaccharide elicitor-responsive
RING-H2 finger protein, is a ubiquitin ligase which functions in vitro
in co-operation with an elicitor-responsive ubiquitin-conjugating
enzyme, OsuBC5b.\emph{Plant J} , \textbf{30} , 447-455. DOI:
10.1046/j.1365-313x.2002.01299.x.

Risseeuw EP, Daskalchuk TE, Banks TW, Liu E, Cotelesage J, Hellmann H,
Estelle M, Somers DE, Crosby WL (2003) Protein interaction analysis of
SCF ubiquitin E3 ligase subunits from Arabidopsis. \emph{Plant J}
,\textbf{34} , 753-767. DOI: 10.1046/j.1365-313x.2003.01768.x.

Ridgway ID, Taylor AC, Atkinson R, Stentiford GD, Chang ES, Chang SA,
Neil DM (2006) Morbidity and mortality in Norway lobsters,
\emph{Nephrops norvegicus} : physiological, immunological and
pathological effects of aerial exposure.\emph{J Exp Mar Biol Ecol} ,
\textbf{328} , 251-264. DOI: 10.1016/j.jembe.2005.07.015.

Ruan J, Li H (2020) Fast and accurate long-read assembly with Wtdbg2.
\emph{Nat Methods} ,\textbf{17} , 155-158. DOI:
10.1038/s41592-019-0669-3.

Roberts JZ, Holohan C, Sessler T, Fox J, Crawford N, Riley JS, Khawaja
H, Majkut J, Evergren E, Humphreys LM, Ferris J, Higgins C,
Espona-Fiedler M, Moynagh P, McDade SS, Longley DB (2020) The
SCF\textsuperscript{Skp2} ubiquitin ligase complex modulates
TRAIL-R2-induced apoptosis by regulating FLIP(L). \emph{Cell Death
Differ} , \textbf{27} , 2726-2741. DOI: 10.1038/s41418-020-0539-7.

Savitch LV, Harney T, Huner NPA (2000) Sucrose metabolism in spring and
winter wheat in response to high irradiance, cold stress and cold
acclimation. \emph{Physiol Plantarum} ,\textbf{108} , 270-278. DOI:
10.1034/j.1399-3054.2000.108003270.x.

Stanke M, Keller O, Gunduz I, Hayes A, Waack S, Morgenstern B (2006)
AUGUSTUS: ab initio prediction of alternative transcripts. \emph{Nucleic
Acids Res} , \textbf{34} , W435-439. DOI: 10.1093/nar/gkl200.

Stamatakis A (2014) RAxML Version 8: a tool for phylogenetic analysis
and post-analysis of large phylogenies. \emph{Bioinformatics} ,
\textbf{30} , 1312-1313. DOI: 10.1093/bioinformatics/btu033.

Simao FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM (2015)
BUSCO: assessing genome assembly and annotation completeness with
single-copy orthologs. \emph{Bioinformatics} , \textbf{31} , 3210-3212.
DOI: 10.1093/bioinformatics/btv351.

Sun YM, Liu LJ, Feng MF, Wang JH, Cang J, Li S, Bao YZ, Wang XT (2015)
Research progress of sugar metabolism of plants under cold stress.
\emph{Journal of Northeast Agricultural University} , \textbf{46} ,
95-102. (In Chinese)

Saadeldin IM, Swelum AA, Elsafadi M, Mahmood A, Osama A, Shikshaky H,
Alfayez M, Alowaimer AN, Magdeldin S (2020) Thermotolerance and
plasticity of camel somatic cells exposed to acute and chronic heat
stress. \emph{J Adv Res} , \textbf{22} , 105-118. DOI:
10.1016/j.jare.2019.11.009.

Taylor HH, Greenaway P (1984) The role of the gills and branchiostegites
in gas exchange in a bimodally breathing crab, \emph{Holthuisana
transversa} : evidence for a facultative change in the distribution of
the respiratory circulation.\emph{J Exp Biol} , \textbf{111} , 103-121.

Takezaki N, Rzhetsky A, Nei M (1995) Phylogenetic test of the molecular
clock and linearized trees. \emph{Mol Biol Evol} ,\textbf{12} , 823-833.
DOI: 10.1093/oxfordjournals.molbev.a040259.

Taylor EW, Wheatley MG (1980) Ventilation, heart rate and respiratory
gas exchange in the crayfish\emph{Austropotamobius pallipes}
(Lereboullet) submerged in normoxic water and following 3 h exposure in
air at 15.\emph{J Comp Physiol B} , \textbf{138} , 67-78. DOI:
10.1007/bf00688737.

Tatusov RL, Fedorova ND, Jackson JD, Jacobs AR, Kiryutin B, Koonin EV,
Krylov DM, Mazumder R, Mekhedov SL, Nikolskaya AN, Rao BS, Smirnov S,
Sverdlov AV, Vasudevan S, Wolf AI, Yin JJ, Natale DA (2003) The COG
database: An updated version includes eukaryotes. \emph{BMC
Bioinformatics} , \textbf{4} , 41. DOI: 10.1186/1471-2105-4-41.

Tang BP, Zhang DZ, Li HR, Jiang SH, Zhang HB, Xuan FJ, Ge BM, Wang ZF,
Liu Y, Sha ZL, Cheng YX, Jiang W, Jiang H, Wang ZK, Wang K, Li CF, Sun
Y, She SS, Qiu Q, Wang W, Li XZ, Li YX, Liu QN, Ren YD (2020)
Chromosome-level genome assembly reveals the unique genome evolution of
the swimming crab (\emph{Portunus trituberculatus} ). \emph{GigaScience}
,\textbf{9} , giz161. DOI: 10.1093/gigascience/giz161.

Urbina MA, Paschke K, Gebauer P, Cumillaf JP, Rosas C (2013)
Physiological responses of the southern king crab, \emph{Lithodes
santolla} (Decapoda: Lithodidae), to aerial exposure. \emph{Comp Biochem
Phys A} ,\textbf{166} , 538-545. DOI: 10.1016/j.cbpa.2013.08.006.

Vaser R, Sovi\selectlanguage{polish}ć \selectlanguage{english}I, Nagarajan N, \selectlanguage{polish}Š\selectlanguage{english}iki\selectlanguage{polish}ć \selectlanguage{english}M (2017) Fast and accurate de novo
genome assembly from long uncorrected reads.\emph{Genome Res} ,
\textbf{27} , 737-746. DOI: 10.1101/gr.214270.116.

Wilson RG, Kachman SD, Martin AR (2001) Seasonal changes in glucose,
fructose, sucrose, and fructans in the roots of dandelion. \emph{Weed
Sci} , \textbf{49} , 150-155. DOI:
10.1614/0043-1745(2001)049{[}0150:SCIGFS{]}2.0.CO;2.

Wu CG, Xiang JH (2002) Genetic determination and exogenous influence in
sex differentiation in crustacean. \emph{Developmental and Reproductive
Biology} , \textbf{11} , 88-94.

Welcker M, Clurman BE (2008) FBW7 ubiquitin ligase: a tumour suppressor
at the crossroads of cell division, growth and differentiation.
\emph{Nat Rev Cancer} , \textbf{8} , 83-93. DOI: 10.1038/nrc2290.

Wissler L, Gadau J, Simola DF, Helmkampf M, Bornberg-Bauer E (2013)
Mechanisms and dynamics of orphan gene emergence in insect genomes.
\emph{Genome Biol Evol} , \textbf{5} , 439-455. DOI: 10.1093/gbe/evt009.

Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A, Sakthikumar S, Cuomo
CA, Zeng Q, Wortman J, Young SK, Earl AM (2014) Pilon: an integrated
tool for comprehensive microbial variant detection and genome assembly
improvement. \emph{Plos One} , \textbf{9} , e112963. DOI:
10.1371/journal.pone.0112963.

Xu SY, Lu ZC, Cao BB, Han DD, Cai SS, Han ZQ, Gao TX (2021)
Chromosome-scale genome assembly of brownspotted
flathead\emph{Platycephalus} sp.1 provides insights into demersal
adaptation in flathead fish. \emph{Zool Res} , \textbf{42} , 660-665.
DOI: 10.24272/j.issn.2095-8137.2021.236.

Yu CG, Song HT, Yao GZ (2004) Assessment of the crab stock biomass in
the continental shelf waters of the East China Sea. \emph{Journal of
Fisheries of China} , 28, 41-46. (In Chinese)

Yu CG, Song HT, Yao GZ (2005) The quantity distribution and biological
property of \emph{Charybdis japonica} in the East China Sea. \emph{J
Shanghai Ocean Uni} , \textbf{14} , 40-45. (In Chinese)

Yang ZH (2007) PAML 4: phylogenetic analysis by maximum likelihood.
\emph{Mol Biol Evol}\textbf{24} , 1586-1591. DOI: 10.1093/molbev/msm088.

Yan BL, Xu XH, Xu JT, Xu GC (2009) Karyotype analysis on \emph{Charybdis
japonica} . \emph{Marine Science} ,\textbf{33} , 41-45. DOI:
10.1360/972009-495. (In Chinese)

Zdobnov EM, Apweiler R (2001) InterProScan -- an integration platform
for the signature-recognition methods in InterPro. \emph{Bioinformatics}
,\textbf{17} , 847-848. DOI: 10.1093/bioinformatics/17.9.847.

Zheng N, Schulman BA, Song LZ, Miller JJ, Jeffrey PD, Wang P, Chu C,
Koepp DM, Elledge SJ, Pagano M, Conaway RC, Conaway JW, Harper JW,
Pavletich NP (2002) Structure of the Cul1-Rbx1-Skp1-F
box\textsuperscript{Skp2} SCF ubiquitin ligase complex. \emph{Nature} ,
\textbf{416} , 703-709. DOI: 10.1038/416703a.

Zheng W, Jia CH, Han ZQ (2013) Morphological variation among wild
populations of \emph{Charybdis japonica} from coastal waters of
China.\emph{Journal of Zhejiang Ocean University} , 32, 477-483. (In
Chinese)

Zheng W (2015) Molecular phylogeography study of \emph{Charybdis
japonica} and \emph{Charybdis bimaculata} in East China Sea and Yellow
Sea. \emph{Zhejiang Ocean University} , pp2. (In Chinese).

Zhao M, Wang W, Zhang FY, Ma CY, Liu ZQ, Yang MH, Chen W, Li QS, Cui MS,
Jiang KJ, Feng CL, Li JT, Ma LB (2021) A chromosome-level genome of the
mud crab (\emph{Scylla paramamosain} estampador) provides insights into
the evolution of chemical and light perception in this crustacean.
\emph{Mol Ecol Resour} , \textbf{21} , 1299-1317. DOI:
10.1111/1755-0998.13332.

\textbf{Figure legend}

Figure.1. \emph{Charybdis japonica} .

Figure.2. Genome-wide Hi-C heatmap of \emph{C. japonica} . From outer
circle to inner circle: chromosome (a), gene distribution (b), GC
content of the genome (c), short Illumina read sequencing depth (d),
long PacBio read depth (e), DNA transposable element (f), and ;ong
terminal repeat (g).

Figure 3. Manhattan plot of \emph{F} \textsubscript{ST}.

Figure 4. ED\textsuperscript{2} distribution.

Figure 5. Venn diagram of shared and unique gene families in four (A) or
five (B) species.

Figure 6. Number of homologous genes among the genomes of related
species.

Figure 7. Phylogenetic analysis based on 968 single-copy orthologous
genes.

Figure 8. Demographic history of \emph{C. japonica} .

Figure 9. Relative evolution rate analysis of different species.

Figure 10. Overall structure (left) and schematic (right) of an SCF
ubiquitin ligase. Note: Ub: Ubiquitin; UBA: Ubiquitin activating enzyme;
UBC: Ubiquitin conjugating enzyme; RBX1: E3 ubiquitin-protein ligase.

Figure 11. Schematic of hemocyanin binding to oxygen (Markl, 2013).\selectlanguage{english}
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