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\begin{document}

\title{A chromosome-level genome of Antechinus flavipes provides a reference
for an Australasian marsupial genus with suicidal reproduction}



\author[1]{Ran Tian}%
\author[2]{Kai Han}%
\author[1]{Yuepan  Geng}%
\author[1]{Chen Yang}%
\author[3]{Patrick Thomas}%
\author[3]{Coral  Pearce}%
\author[3]{Kate  Moffatt}%
\author[4]{Siming  Ma}%
\author[1]{shixia xu}%
\author[2]{Guang Yang}%
\author[2]{Xuming Zhou}%
\author[5]{Vadim  Gladyshev}%
\author[6]{Chengcheng  Shi}%
\author[7]{Xin  Liu}%
\author[8]{Diana Fisher}%
\author[3]{Lisa Chopin}%
\author[9]{Natália  Leiner}%
\author[3]{Andrew Baker}%
\author[7]{Guangyi  Fan}%
\author[10]{Inge Seim}%
\affil[1]{Nanjing Normal University}%
\affil[2]{Affiliation not available}%
\affil[3]{Queensland University of Technology}%
\affil[4]{Genome Institute of Singapore}%
\affil[5]{Harvard Medical School Department of Genetics}%
\affil[6]{BGI Group}%
\affil[7]{BGI}%
\affil[8]{The University of Queensland - Saint Lucia Campus}%
\affil[9]{Universidade Federal de Uberlândia}%
\affil[10]{Nanjing Normal University School of Life Sciences}%


\vspace{-1em}



  
  \date{May 25, 2024}


\begingroup
\let\center\flushleft
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\selectlanguage{english}
\begin{abstract}
The 15 species of small carnivorous marsupials that comprise the genus
Antechinus exhibit semelparity, a rare life-history strategy where death
occurs after one breeding season. Antechinus males, but not females, age
rapidly (demonstrate organismal senescence) during the breeding season
and show promise as new animal models of ageing. Some antechinus species
are also threatened or endangered. Here, we report chromosome-level
genomes of the yellow-footed antechinus Antechinus flavipes. The genome
assembly has a total length of 3.2 Gb with a contig N50 of 51.8 Mb and a
scaffold N50 of 636.7 Mb. We anchored and oriented 99.7\% of the
assembly on seven pseudochromosomes and found that repetitive DNA
sequences occupy 51.8\% of the genome. Draft genome assemblies of three
related species in the subfamily Phascogalinae, two additional
antechinus species (A. argentus and A. arktos) and the iteroparous
sister species Murexia melanurus were also generated. Preliminary
demographic analysis supports the hypothesis that climate change during
the Pleistocene isolated species in Phascogalinae and shaped their
population size. A transcriptomic profile across the A. flavipes
breeding season allowed us to identify genes associated with aspects of
the male die-off. The chromosome-level A. flavipes genome provides a
steppingstone to understanding an enigmatic life-history strategy and a
resource to assist the conservation of antechinuses.%
\end{abstract}%



\sloppy


\textbf{A chromosome-level genome of \emph{Antechinus flavipes} provides
a reference for an Australasian marsupial genus with suicidal
reproduction}

Ran Tian\textsuperscript{1,2,+}, Kai Han\textsuperscript{3,+},Yuepan
Geng\textsuperscript{1}, Chen Yang\textsuperscript{1}, Chengcheng
Shi\textsuperscript{3}, Patrick B. Thomas\textsuperscript{4,5,6}, Coral
Pearce\textsuperscript{7}, Kate Moffatt\textsuperscript{7}, Siming
Ma\textsuperscript{8}, Shixia Xu\textsuperscript{2}, Guang
Yang\textsuperscript{2}, Xuming Zhou\textsuperscript{9}, Vadim N.
Gladyshev\textsuperscript{10}, Xin Liu\textsuperscript{3}, Diana O.
Fisher\textsuperscript{11}, Lisa K. Chopin\textsuperscript{4,5}, Nat\selectlanguage{ngerman}ália
O. Leiner\textsuperscript{12}, Andrew M. Baker\textsuperscript{7,13},
Guangyi Fan\textsuperscript{3,14,15}, Inge Seim\textsuperscript{1,4,5,7}

\textsuperscript{1} Integrative Biology Laboratory, College of Life
Sciences, Nanjing Normal University, Nanjing, 210023, China

\textsuperscript{2} Jiangsu Key Laboratory for Biodiversity and
Biotechnology, College of Life Sciences, Nanjing Normal University,
Nanjing, Jiangsu, 210046, China

\textsuperscript{3} BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong,
266555, China

\textsuperscript{4} Ghrelin Research Group, Translational Research
Institute-Institute of Health and Biomedical Innovation, School of
Biomedical Sciences, Queensland University of Technology, Brisbane, QLD,
4102, Australia

\textsuperscript{5} Australian Prostate Cancer Research
Centre-Queensland, Translational Research Institute -- Institute of
Health and Biomedical Innovation, Queensland University of Technology,
Brisbane, QLD, 4102, Australia

\textsuperscript{6} Queensland Bladder Cancer Initiative, Translational
Research Institute-Institute of Health and Biomedical Innovation, School
of Biomedical Sciences, Queensland University of Technology,
Woolloongabba, QLD, 4102, Australia

\textsuperscript{7} School of Biology and Environmental Science,
Queensland University of Technology, Brisbane, QLD, 4000, Australia

\textsuperscript{8} Genome Institute of Singapore, Agency for Science,
Technology and Research (A*STAR), Singapore, 138672, Singapore

\textsuperscript{9} Key Laboratory of Animal Ecology and Conservation
Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing,
100101, China

\textsuperscript{10} Division of Genetics, Department of Medicine,
Brigham and Women's Hospital and Harvard Medical School, Boston, MA,
02115, USA

\textsuperscript{11} School of Biological Sciences, University of
Queensland, Brisbane, QLD, 4072, Australia

\textsuperscript{12} Laborato\selectlanguage{english}rio de Ecologia de Mami\selectlanguage{english}feros, Instituto de
Biologia, Universidade Federal de Uberla\selectlanguage{english}ndia, Uberl\selectlanguage{ngerman}ândia, MG, 38400-902,
Brazil

\textsuperscript{13} Natural Environments Program, Queensland Museum,
South Brisbane, QLD, 4101, Australia

\textsuperscript{14} State Key Laboratory of Quality Research in Chinese
Medicine, Institute of Chinese Medical Sciences, University of Macau,
Macau, China

\textsuperscript{15} State Key Laboratory of Agricultural Genomics,
BGI-Shenzhen, Shenzhen, Guangdong, 518083, China

\selectlanguage{english}\textsuperscript{+} These authors contributed equally to this work

Correspondence: Guangyi Fan, BGI-Qingdao, BGI-Shenzhen, Qingdao,
Shandong, 266555, China. E-mail: fanguangyi@genomics; Inge Seim,
Integrative Biology Laboratory, College of Life Sciences, Nanjing Normal
University, Nanjing, 210023, China. E-mail: inge@seimlab.org

\textbf{Abstract}

The 15 species of small carnivorous marsupials that comprise the
genus\emph{Antechinus} exhibit semelparity, a rare life-history strategy
where death occurs after one breeding season. Antechinus males, but not
females, age rapidly (demonstrating organismal senescence) during the
breeding season and show promise as new animal models of ageing. Some
antechinus species are also threatened or endangered. Here, we report
chromosome-level genomes of the yellow-footed antechinus\emph{Antechinus
flavipes} . The genome assembly has a total length of 3.2 Gb with a
contig N50 of 51.8 Mb and a scaffold N50 of 636.7 Mb. We anchored and
oriented 99.7\% of the assembly on seven pseudochromosomes and found
that repetitive DNA sequences occupy 51.8\% of the genome. Draft genome
assemblies of three related species in the subfamily Phascogalinae, two
additional antechinus species (\emph{A. argentus} and\emph{A. arktos} )
and the iteroparous sister species \emph{Murexia melanurus} were also
generated. Preliminary demographic analysis supports the hypothesis that
climate change during the Pleistocene isolated species in Phascogalinae
and shaped their population size. A transcriptomic profile across the
\emph{A. flavipes} breeding season allowed us to identify genes
associated with aspects of the male die-off. The chromosome-level
\emph{A. flavipes} genome provides a steppingstone to understanding an
enigmatic life-history strategy and a resource to assist the
conservation of antechinuses.

\textbf{Keywords} : \emph{Antechinus} ; dasyurid; semelparity; genome
assembly; chromosome-level; suicidal reproduction



\textbf{1. INTRODUCTION}

For every animal species, the most critical activity is mating and the
raising of offspring. Reproduction is a costly process, and animals
invest energy into strategies that maximize the number and survival of
offspring (Collett, Baker, \& Fisher, 2018). Broadly, these strategies
span the so-called iteroparity-semelparity continuum -- from a single
(\emph{semel} ) to repeated (\emph{itero} ) reproductive episode(s)
before death {[}reviewed in (Hughes, 2017; Krajewski, Woolley, \&
Westerman, 2000){]}. In mammals, semelparity is observed in Australian
dasyurids (males-only) and South American didelphids (both sexes)
(Fisher, Dickman, Jones, \& Blomberg, 2013; Leiner, Setz, \& Silva,
2008). Obligate male semelparity is the most extreme form of
semelparity, occurring in the marsupial subfamilies Phascogalinae
(15\emph{Antechinus} species and three \emph{Phascogale} species (A. J.
Bradley, 2003; Naylor, Richardson, \& McAllan, 2008)) and Dasyurinae
(the kaluta, \emph{Dasykaluta rosamondae} (Hayes et al., 2019)). In
these dasyurid species, all males die soon after a 1-3 week mating
period (`die-off' at 11.5 months of age), and a proportion of females
survive to breed in the subsequent year (A. Baker \& Dickman, 2018).

Breeding is a stressful life-history event, but the stress response
enables most animals to cope and to mobilise energy (Romero, 2004).
Hormones play a vital role in this process. While in antechinus, both
sexes have elevated stress hormone levels (chiefly the corticosteroid
cortisol) during breeding, males also exhibit surging plasma
testosterone levels (A. J. Bradley, 2003; Braithwaite \& Lee, 1979;
Croft, 2003; McAllan, 2006; Naylor et al., 2008). This interferes with
negative feedback mechanisms and reduces levels of corticosteroid
binding globulin (CBG), increasing the levels of free (i.e., unbound),
active corticosteroids in the blood (A. J. Bradley, 2003; Naylor et al.,
2008). As the breeding season progresses, corticosteroid levels continue
to rise; ultimately contributing to systemic collapse and death of all
males. Corticosteroids are anti-inflammatory and, at high
concentrations, immunosuppressive, triggering a decline of body
condition (Manoli et al., 2007; Perogamvros, Ray, \& Trainer, 2012).
Stress, combined with malnutrition, results in a significant negative
energy balance and is associated with numerous comorbidities (Argiles,
Campos, Lopez-Pedrosa, Rueda, \& Rodriguez-Manas, 2016). Cortisol is
also elevated in females throughout the short breeding season, but in
the absence of elevated testosterone, free cortisol levels remain
relatively constant.

There is mounting evidence that testosterone and cortisol contribute to
differences in ageing and related diseases (Austad \& Fischer, 2016;
Gems, 2014; Lemaitre et al., 2020; Martocchia et al., 2016). Moreover,
ageing (Childs et al., 2017; Froy et al., 2019) and obligate semelparity
manifest as a decline in immune function -- immunosenescence. In
contrast to current mammal models of ageing, antechinuses are `natural'
models of physiological senescence (see (Diamond, 1982; McAllan, 2006)).
For example, the brain of the ageing wild-type mouse and rat does not
accumulate amyloid-beta (A\selectlanguage{greek}β\selectlanguage{english}) (Jucker, 2010). A\selectlanguage{greek}β \selectlanguage{english}plaques, which are
associated with chronic stress and elevated cortisol levels {[}e.g., see
(Lesuis, Weggen, Baches, Lucassen, \& Krugers, 2018){]}, accumulate at
the end of the antechinus lifespan in antechinuses -- mirroring
Alzheimer's disease neuropathology and potentially making them a
suitable disease model (McAllan, 2006; Naylor et al., 2008). A
high-quality genome assembly is critical for future genetic experiments
(e.g., CRISPR). Moreover, considering the strong effects of cortisol and
testosterone on male obligate semelparity, identifying the expression of
genes associated to these hormones and its consequences may help to
understand the evolution of this extreme reproductive strategy.

Recent work has uncovered several new antechinus species, bringing the
total number of species to 15 (Mutton, Phillips, Fuller, Bryant, \&
Baker, 2019). In 2018, \emph{A. arktos} and \emph{A. argentus} were
listed as Endangered on the Australian Government's threatened species
list and were included in the 20 Australian mammals most likely to go
extinct in the next two decades (Geyle et al., 2018). Moreover, areas of
their habitat were recently ravaged by extensive wildfires and drought.
Genomic resources are urgently required to support research on the
population structure, speciation, and recovery of antechinus species.

To investigate the phylogeny, demographic history, and genomic diversity
of \emph{A. flavipes} and to pave the way to understanding the evolution
of semelparity, high-quality genomic data is required. A genome assembly
of the brown antechinus (\emph{A. stuartii} ) was recently reported
(Brandies, Tang, Johnson, Hogg, \& Belov, 2020a). However, a
chromosome-level genome is not yet available. PacBio long-read
sequencing combined with the chromosome conformation capture method Hi-C
resolves complex regions (such as repeat regions) and can greatly
improve downstream analyses (Schloissnig et al., 2021). Here, we
employed third-generation sequencing technologies to generate the first
chromosome-level genome of an antechinus, that of the yellow-footed
antechinus (\emph{A. flavipes} ), as well as draft genomes of three
related dasyurids (\textbf{Figure 1a} ). We highlight genome features,
phylogeny and historical demography, and the gene expression profile
of\emph{A. flavipes} male die-off.



\textbf{2. MATERIALS AND METHODS}

\textbf{2.1 Sample collection}

`AdamAnt', an adult male yellow-footed antechinus (\emph{Antechinus
flavipes} ) was sampled in Samford Valley (greater Brisbane), QLD,
Australia (27\selectlanguage{ngerman}°\selectlanguage{english} 22\selectlanguage{english}'\selectlanguage{english} S, 152deg\selectlanguage{english} 52\selectlanguage{english}'\selectlanguage{english} E) in September 2018. A second male
individual (`Ant2'), sampled at the same location in 2017, was not used
for genome assembly but employed in demographic analysis. Animals were
euthanised by inhalation of CO\textsubscript{2}. Once death was
confirmed, animals were placed directly on dry ice in the field and
transferred to a -80 degC freezer for later dissection. Tissue specimens
for short-insert whole-genome sequencing were obtained from the
black-tailed dusky antechinus \emph{A. arktos} (ear tissue; Lamington
National Park, QLD, Australia, 28deg\selectlanguage{english} 22\selectlanguage{english}'\selectlanguage{english} S, 153deg\selectlanguage{english} 15\selectlanguage{english}'\selectlanguage{english} E; specimen AA100
sampled by A.M.B. in 2015), the silver-headed antechinus \emph{A.
argentus} (ear tissue; from Blackdown Tableland National Park, QLD,
Australia; 23deg\selectlanguage{english} 82\selectlanguage{english}'\selectlanguage{english} S, 149deg\selectlanguage{english} 07\selectlanguage{english}'\selectlanguage{english} E; specimen BD-17-5A sampled by A.M.B. in
2017), and the black-tailed dasyure (\emph{Murexia melanurus} ; liver
tissue; Wau, Morobe, Papua New Guinea, 7deg\selectlanguage{english} 20\selectlanguage{english}'\selectlanguage{english} S, 146deg\selectlanguage{english} 42\selectlanguage{english}'\selectlanguage{english} E; specimen
ABTC46020 sampled by the South Australian Museum in 1985). All DNA and
RNA were extracted by BGI Hong Kong.

\textbf{2.2 Reference genome sequencing and assembly}

We used a combination of long-fragment sequencing, short-insert library
sequencing for error correction and gapfilling, and chromatin
conformation capture (Hi-C) to generate chromosome-level semelparous
mammal reference genomes. High-molecular weight (HMW) DNA extracted from
the testis of the \emph{A. flavipes} individual `AdamAnt' was used to
generate long-read (PacBio) sequencing data by Annoroad Gene Technology
(Beijing, China). Paired-end (2 x 100 bp) BGI-SEQ500 data were generated
from cerebrum, liver, heart, and lung tissue from the same individual by
BGI-Qingdao. A total of 323.85 Gb (\textasciitilde{}100x) \emph{A.
flavipes} PacBio reads were assembled using Canu v1.7 (Koren et al.,
2017) with the error correction module. The corrected subreads were used
for initial draft assembly using Wtdbg2 v1.2.8 (Ruan \& Li, 2020). To
reduce base errors, the assembly was `polished' using Pilon v1.23
(Walker et al., 2014) and 151.43 Gb (50x) 100 bp paired-end BGISEQ-500
reads {[}mapped to the initial PacBio assembly using Minimap2 v2.10 (Li,
2018) and SAMtools v1.9 (Li et al., 2009){]}.

Genome sizes were estimated by \emph{k} -mer frequency analysis (Liu et
al., 2013). Briefly, 100 bp paired-end WGS reads were used as input into
the GCE (Genomic Charactor Estimator) v1.0.0 (Marcais \& Kingsford,
2011) to obtain the \emph{k} -mer frequency and the genome size was
estimated using the equation `Genome size = \emph{k} -mer number
/\emph{k} -mer depth', where the `\emph{k} -mer number' is the total
number of \emph{k} -mers and `\emph{k} -mer depth' denotes the peak
frequency that occurred more than any other frequencies. Genome length
was estimated on the basis of total scaffold length of the assembly.
Using the frequency distribution of 17-mers of short paired-end reads
(\textbf{Figure S1} ), the \emph{A. flavipes} genome was estimated to be
3.2 Gb.

Assembly quality was assessed using BUSCO (Benchmarking Universal
Single-Copy Orthologs) v5.0.0\_cv1 (Seppey, Manni, \& Zdobnov, 2019),
employing the gene predictor AUGUSTUS v3.2.1 (Stanke \& Waack, 2003) and
the 9,226-gene BUSCO mammalian lineage data set (mammalia\_odb10).
Although, gene centric, the BUSCO Score is a good predictor of genome
completeness (Seppey et al., 2019).

\textbf{2.3 Assignment of scaffolds to chromosomes}

\emph{A. flavipes} Hi-C libraries from liver tissue were prepared, as
described previously (Lieberman-Aiden et al., 2009). Hi-C libraries were
sequenced on the BGISEQ-500 platform and quality controlled using the
HiC-Pro (v2.8.0\_devel) (Servant et al., 2015) pipeline, resulting in
51.0 Gb uniquely aligned read pairs. Reads validated by HiC-Pro were
next used to scaffold contigs into seven chromosome clusters (2\emph{n}
=14 karyotype) using the 3D-DNA v1.12 pipeline (O. Dudchenko et al.,
2017). The assembly was further improved by interactive correction using
Juicebox v1.11.08 (Olga Dudchenko et al., 2018; Durand et al., 2016). A
chromatin contact map can be found in \textbf{Figure S2} .

\textbf{2.4 Draft genomes assemblies of dasyurids}

Voucher specimens of the Australian dasyurids \emph{A. arktos}
and\emph{A. argentus} , and the New Guinean dasyurid \emph{M.
melanurus}were sequenced by short-insert whole-genome sequencing (WGS)
(see\textbf{Table S1} ). Reference-based (i.e., `pseudo') nuclear
genomes were obtained by mapping to the \emph{A. flavipes} reference
genome {[}see (Feigin et al., 2018) and Supplemental Methods{]}.

\textbf{2.5 RNA-seq and transcriptome data processing}

\emph{A. flavipes} were obtained by overnight live-trapping in Samford
Valley, QLD, Australia (27deg\selectlanguage{english} 22\selectlanguage{english}'\selectlanguage{english} S, 152deg\selectlanguage{english} 52\selectlanguage{english}'\selectlanguage{english} E). Animals were euthanised
by CO\textsubscript{2} and tissues frozen at -80 degC. Eight specimens
collected in 2017 were sequenced by BGI Hong Kong. The RNA of the
remainder {[}seven males and six females collected in 2018{]} was
extracted by BGI Hong Kong and sequenced by BGI Qingdao. Only the
samples collected during the 2018 breeding season in Samford Valley were
used for differential gene expression analysis (the samples collected in
2017 were used for gene annotation only). Raw data was filtered using
Flexbar v3.4.0 (Dodt, Roehr, Ahmed, \& Dieterich, 2012; Roehr,
Dieterich, \& Reinert, 2017) with default settings (removes reads with
any uncalled bases). BGISEQ-500 adapters were obtained from a
comparative study of Illumina and BGI sequencing platforms (Mak et al.,
2017). Any residual ribosomal RNA reads (the majority removed by poly(A)
selection prior to sequencing library generation) were removed from the
reads using SortMeRNA v2.1b (Kopylova, Noe, \& Touzet, 2012) against the
SILVA v119 ribosomal database (Quast et al., 2013). Tissue
transcriptomes were de novo assembled using Trinity v2.8.4 (Grabherr et
al., 2011; Haas et al., 2013; Henschel et al., 2012) with default
parameters. The \emph{A. flavipes} transcriptome assemblies were
assessed using BUSCO (Seppey et al., 2019). Details of transcriptome
sequencing data used in study are listed in \textbf{Tables S2-S4} (also
see Supplemental Methods).

\textbf{2.6 Genome annotation}

Repeat element annotation

We identified repetitive elements by integrating homology and de novo
predictions. Homology-based transposable elements (TEs) annotation were
obtained by interrogating a genome assembly with known repeats in the
Repbase database v16.02 (Bao, Kojima, \& Kohany, 2015) using
RepeatMasker v4.0.5 (DNA-level) (Tarailo-Graovac \& Chen, 2009) and
RepeatProteinMask (protein-level; implemented in RepeatMasker). De novo
TE predictions were obtained using RepeatModeler v1.1.0.4 (Smit \&
Hubley, 2010) and LTRharvest v1.5.8 (Ellinghaus, Kurtz, \& Willhoeft,
2008) to generate database for a RepeatMasker run. Tandem Repeat Finder
(v4.07) (Benson, 1999) was used to find tandem repeats (TRs) in the
genome. A non-redundant repeat annotation set was obtained by combining
the above data. Genome sequences of other marsupials were also
interrogated using the repeat element annotation pipeline. The following
were downloaded from DNA Zoo {[}Virginia opossum (\emph{Didelphis
virginiana} ; dv-2k (Olga Dudchenko et al., 2018)){]}, the NCBI
Reference Sequence Database (Release 86) (Pruitt, Tatusova, \& Maglott,
2007) {[}gray short-tail opossum (\emph{Monodelphis domestica} ;
MonDom5; GCF\_000002295.2), koala (\emph{Phascolarctos cinereus} ;
phaCin\_unsw\_v4.1; GCA\_002099425.1), Tasmanian devil
(\emph{Sarcophilus harrisii;} Devil\_ref v7.0, also known as sarHar1;
GCA\_000189315.1), Tammar wallaby (\emph{Notamacropus eugenii} ;
Meug\_1.1; GCA\_000004035.1), and common wombat (\emph{Vombatus ursinus}
; GCF\_900497805.2){]}, and the GigaScience Database {[}brown antechinus
(\emph{Antechinus stuartii} ; (Brandies et al., 2020a; Brandies, Tang,
Johnson, Hogg, \& Belov, 2020b){]}.

Protein-coding gene annotation

Protein-coding genes of \emph{A. flavipes} and \emph{Didelphis
virginiana} were annotated using homology-based prediction, de novo
prediction, and RNA-seq-assisted prediction methods. Sequences of
homologous proteins from five mammals {[}human (\emph{Homo sapiens}
),\emph{M. domestica} ), \emph{P. cinereus} , \emph{S. harrisii} ,
and\emph{V. ursinus} ){]} were downloaded from NCBI. These protein
sequences were aligned to the repeat-masked genome using BLAT v0.36
(Kent, 2002). Genewise v2.4.1 (Birney, Clamp, \& Durbin, 2004) was
employed to generate gene structures based on the alignments of proteins
to the genome assembly. De novo gene prediction was performed using
AUGUSTUS v3.2.3 (Stanke et al., 2006), GENSCAN v1.0 (Burge \& Karlin,
1997), and GlimmerHMM v3.0.1 (Majoros, Pertea, \& Salzberg, 2004) with a
human training set. Transcriptome data were mapped to the assembled
genome using HISAT2 v2.1.0 (Kim, Paggi, Park, Bennett, \& Salzberg,
2019) and SAMtools v1.9 (Li et al., 2009), and coding regions were
predicted using TransDecoder v5.5.0 (Grabherr et al., 2011; Haas et al.,
2013). A final non-redundant reference gene set was generated by merging
the three annotated gene sets using EVidenceModeler v1.1.1 (EVM) (Haas
et al., 2008) and excluding EVM gene models with only ab initio support.
The gene models were translated into amino acid sequences and used in
local BLASTp (Camacho et al., 2009) searches against the public
databases Kyoto Encyclopedia of Genes and Genomes (KEGG; v89.1)
(Kanehisa \& Goto, 2000), Clusters of Orthologous Groups (COG) (Tatusov,
Galperin, Natale, \& Koonin, 2000), NCBI non-redundant protein sequences
(NR; v20170924) (O'Leary et al., 2016), Swiss-Prot (release-2018\_07)
(UniProt, 2012), TrEMBL (TRanslation of EMBL {[}nucleotide sequences
that are not in Swiss-Prot{]}; release-2018\_07) (O'Donovan et al.,
2002), and InterPro (v69.0) (A. L. Mitchell et al., 2019). A total of
18,068 (93.5\%) of\emph{A. flavipes} genes could be functionally
annotated. Where specific genes are named in this manuscript, human
nomenclature assignments are used unless otherwise noted.

\textbf{2.7 Phylogeny and divergence time estimation}

Marsupials (metatherians) and eutherians diverged \textasciitilde{}160
million years ago, long before the radiation of extant eutherian clades
(\textasciitilde{}100 million years ago) (Luo, Yuan, Meng, \& Ji, 2011;
Phillips, Bennett, \& Lee, 2009). We employed the platypus
(\emph{Ornithorhynchus anatinus} ) as an outgroup as this species is
frequently used as an outgroup for both eutherian and marsupial mammals
and it has a high-continuity, well-annotated genome (contig N50 15.1 Mb;
scaffold N50 83.3 Mb). In contrast, the genomes of the most closely
related eutherian mammals, the edentates (sloth, armadillo and
anteaters) currently have relatively poor-quality genome assemblies.
These include, for example, the armadillo \emph{Dasypus
novemcinctus}(contig N50 0.03 Mb, scaffold N50 1.7 Mb) and the sloth
\emph{Choloepus hoffmanni} (contig N50 0.06 Mb; scaffold N50 0.4 Mb).

We identified 7,116 high-confidence 1:1 orthologs by interrogating the
predicted proteins from the gene models of 11 species (nine marsupials
and the platypus) using SonicParanoid v1.3.0 (Cosentino \& Iwasaki,
2019). Because the \emph{A. arktos} , \emph{A. argentus} , and \emph{M.
murexia} pseudo-genomes were derived from \emph{A. flavipes} , their
genes were extracted using the \emph{A. flavipes} gene annotation file.
The corresponding coding sequences (CDS) for each species were aligned
using PRANK v100802 (Loytynoja \& Goldman, 2005) and filtered by Gblocks
v0.91b (Talavera \& Castresana, 2007) to identify conserved blocks
(removing gaps, ambiguous sites, and excluding alignments less than 300
bp in size), leaving 7,116 genes. Maximum-likelihood (ML) phylogenetic
trees were generated using RAxML v7.2.8 (Stamatakis, 2006) and FastTree
v2.1.10 (Price, Dehal, \& Arkin, 2010) with three CDS data sets: the
whole sequence, first codon positions, and fourfold degenerate (4d)
sites. Identical topologies and similar support values were obtained
(1,000 bootstrap iterations were performed). The divergence time between
species was estimated using MCMCTree {[}Bayesian molecular clock model
implemented in PAML v4.7 (Yang, 2007){]} with the JC69 nucleotide
substitution model (Jukes \& Cantor, 1969), and 4d ML tree and
concatenated supergenes of first codon positions and fourfold degenerate
(4d) codons as inputs. We used 100,000 iterations after a burn-in of
10,000 iterations. MCMCTree calibration points (million years ago; Mya)
were obtained from TimeTree (Kumar, Stecher, Suleski, \& Hedges,
2017):\emph{O. anatinus} -\emph{P. cinereus} (\textasciitilde{}167-192
Mya),\emph{V. ursinus} -\emph{D. virginiana} (\textasciitilde{}72-86
Mya),\emph{V. ursinus} -\emph{M. melanurus} (\textasciitilde{}56-64
Mya),\emph{V. ursinus} -\emph{P. cinereus} (\textasciitilde{}31-39
Mya),\emph{M. domestica} -\emph{D. virginiana} (\textasciitilde{}24-39
Mya), and \emph{S. harrisii} -\emph{M. melanurus} (\textasciitilde{}4-22
Mya). For comparison, phylogenetic trees of marsupials in the marsupial
orders Dasyuromorphia and Didelphimorphia was obtained by querying the
PHYLACINE (The Phylogenetic Atlas of Mammal Macroecology) resource
(Faurby et al., 2018).

\textbf{2.8 Genomic diversity}

Genome-wide heterozygosity (\selectlanguage{greek}π\selectlanguage{english}) was calculated from (2 \selectlanguage{ngerman}× 100 bp) WGS read
mapped to the \emph{S. harrisii} genome. For details, see Supplemental
Methods.

\textbf{2.9 Demographic history}

We inferred demographic histories by applying the Pairwise sequentially
Markovian coalescent (PSMC) method (Li \& Durbin, 2011). Short-insert
paired-end WGS reads of \emph{A. flavipes} (two individuals), \emph{A.
arktos} , \emph{A. argentus} , and \emph{M. melanurus} were mapped to a
repeat-masked \emph{S. harrisii} genome. Putative X-linked scaffolds in
the \emph{S. harrisii} assembly were excluded (see Supplemental
Methods). Maps were generated using the R package `ggmap' (Kahle \&
Wickham, 2013).

\textbf{2.10 Transcriptome profiling of the \emph{Antechinus
flavipes}breeding}

To search for transcripts associated with obligate semelparity, we
performed differential gene expression analysis of a single \emph{A.
flavipes} population (Samford Valley, Queensland, Australia) from August
to October 2018. Every two days, we microscopically examined female
urine for cornified, anuclear vaginal epithelial cells, a sign of peak
oestrus (Selwood, 1980). Concurrent visual inspections of captured males
for behavioural changes (e.g., agitation) revealed evidence of stress
beginning in the last week of September, followed by progressive loss of
body condition (\textbf{Figure S3} ). The practical and ethical
challenges of longitudinal sampling from a wild population limited the
number of samples that could be obtained. In this study, we present
transcriptomes of eight male and six female antechinuses {[}liver,
kidney, skeletal muscle, cerebrum, and reproductive tissues (testis and
ovary){]}. See Supplemental Methods and \textbf{Figure S4} for data
processing and differential expression procedures, and \textbf{File
S2}for normalised counts.

\textbf{3. RESULTS AND DISCUSSION}

\textbf{3.1 Genome assembly and annotation}

We used PacBio sequencing and Hi-C (Burton et al., 2013) to create a 3.2
Gb (2\emph{n} =14) chromosome-level \emph{A. flavipes} nuclear genome
assembly with a contig N50 of 51.8 Mb and scaffold N50 of 636.7 Mb
(\textbf{Table 1} and \textbf{Figure 1} ). The seven chromosomes ranged
in size from 86.6 to 727.3 Mb (\textbf{Table 2} ) and covered
\textasciitilde{}99.7\% of the assembly. We also generated \emph{A.
flavipes} reference-based assemblies of \emph{A. arktos} , \emph{A.
argentus} , and \emph{M.} \emph{melanurus} from short-insert
whole-genome sequencing reads. Most \emph{A. flavipes} genome regions
had a GC-depth of about 50×, while a small peak at 25× depth revealed
heterozygous sex chromosomes (\textbf{Figure S5} ). Hi-C was able to
recover a \textasciitilde{}86.5 Mb X chromosome (chromosome 7), while
the Y chromosome could not be obtained (see Supplemental Methods). This
is unsurprising, as marsupial Y chromosomes are small
(\textasciitilde{}10-12 Mb; akin to microchromosomes of birds),
repeat-rich, and refractory to assembly (Deakin \& O'Neill, 2020). The
chromosomes of \emph{A. flavipes} were highly homologous to the related
Tasmanian devil (\emph{Sarcophilus harrisii} ) (\textbf{Figure 1C} ),
supporting the quality of the assemblies.

The GC content of \emph{A. flavipes} (\textasciitilde{}36\%)
(\textbf{Table 1} ) is similar to the brown antechinus (\emph{A.
stuartii} ) and \emph{S} . \emph{harrisii} . As indicated by 17-mer
frequency analysis (\textbf{Figure S1} ), the \emph{A. flavipes} genome
is repeat rich. Repetitive elements account for 51.8\%
(\textasciitilde{}1.7 Gb) of the assembly, with long interspersed
elements (LINEs; \textasciitilde{}45\%), long terminal retrotransposons
(LTRs; 15.4\%) and short interspersed elements (SINEs; 6.6\%) being the
major classes of transposable elements (TEs) (\textbf{Tables S5 and S6}
). We annotated 24,708 \emph{A. flavipes} protein-coding genes (82.2\%
supported by transcriptome data from 13 tissues). \emph{The A. flavipes}
reference assembly obtained a BUSCO (Benchmarking Universal Single-Copy
Orthologs) (Seppey et al., 2019) genome completeness score of 92.4\%) --
comparable to \emph{A. stuartii} (92.2\% and 92.3\% for a female and
male assembly, respectively) (Brandies et al., 2020a), the koala
(\emph{Phascolarctos cinereus} ; 93.9\%) (Johnson et al., 2018), and the
\emph{S} . \emph{harrisii} (91.6\%; 2019 assembly mSarHar1.1)
(\textbf{Table S7} ). The scores of the three dasyurid reference-based
assemblies, here used for phylogenetic and demography analyses, ranged
from 74.2\% to 90.0\% recovered complete BUSCO genes (\textbf{Table S8}
).

\textbf{3.2 Phylogeny and demographic history}

To construct a time-calibrated species tree (\textbf{Figure 2a} ), we
identified 7,116 high-confidence single-copy orthologs from nine
marsupial species and a monotreme, the platypus (\emph{Ornithorhynchus
anatinus} ). Extant Australasian and American marsupials diverged from a
South American ancestor approximately 80 million years ago (Kumar et
al., 2017; Nilsson et al., 2010), emphasising the deep evolutionary
history of marsupials. We estimated that the lineages leading to extant
Dasyuridae (e.g., \emph{Antechinus} ) and Didelphidae diverged 81.7
million years ago {[}77.7-85.8 Mya 95\% credibility interval (CI){]}.
The dasyurid subfamily Phascogalinae comprises three genera: the
semelparous Australian \emph{Antechinus} and \emph{Phascogale} , which
have male die-off, and the iteroparous New Guinean sister
genus\emph{Murexia} . Small dasyurids from mainland Australia are likely
to have dispersed into New Guinea 9-11 million years ago (K. J. Mitchell
et al., 2014). We found the divergence time of \emph{Antechinus}
and\emph{Murexia} to be about 7.1 Mya (95\% CI 5.9-7.3). Our analysis
show that the three antechinus species split from a common ancestor
\textasciitilde{}4.6 Mya (95\% CI 3.8-4.8), while \emph{A. flavipes}
and\emph{A. argentus} share an ancestor \textasciitilde{}2.4 Mya (95\%
CI 2.0-2.6). Our phylogeny and divergence times concord with trees
generated from the PHYLACINE database (Faurby et al., 2018)
(\textbf{Figure S6} ) and with recent estimates from a small set of
mitochondrial and nuclear genes (Mutton et al., 2019).

The pairwise sequentially Markovian coalescent (PSMC) method (Li \&
Durbin, 2011), which can infer changes in the effective population size
(\emph{N\textsubscript{e}} ) over the Pleistocene, was used to evaluate
the four sequenced dasyurid species (\textbf{Figure 2b,c} ). Until the
end of the Pleistocene, approximately 11,700 years ago, mainland
Australia, New Guinea, and Tasmania formed a single continent, Sahul
(Barrows, Stone, Fifield, \& Cresswell, 2002). Glaciation of Sahul was
restricted to the Snowy Mountains of southeastern mainland Australia and
the Tasmanian highlands, and the continent experienced cycles of aridity
and sea-level fluctuations (Barrows et al., 2002). Until about 250,000
years ago, the species in higher-elevation, wetter habitats; \emph{A.
argentus} , \emph{A. arktos} , and \emph{M. melanurus} , had larger
effective population sizes than \emph{A. flavipes} , which were found in
lower-elevation, drier habitats than today (A. M. Baker \& Van Dyck,
2013). After 250,000 years ago, the species in higher-elevations
declined in population size, while \emph{A. flavipes} populations
expanded (\textbf{Figure 2a,b} ). This pattern persisted into the Late
Pleistocene \textasciitilde{}11,700 to 126,000 years ago, a period when
temperature fluctuations were large, and many mesic-adapted species
declined, became restricted to wet refugia such as mountain-tops or
became extinct, and more arid-adapted species radiated (Saltre et al.,
2016). While the PSMC method cannot infer population dynamics after
\textasciitilde{}20,000 years ago, \emph{A. flavipes} had the
largest\emph{N\textsubscript{e}} in the most recent PSMC estimate,
consistent with the status of the yellow-footed antechinus being one of
the most common and broadly distributed species in genus
\emph{Antechinus} today (A. M. Baker \& Van Dyck, 2013; Lada, Thomson,
Mac Nally, \& Taylor, 2008; Mutton et al., 2019). This conclusion is in
agreement with a recent study showing that aridity and geographical
isolation led to dasyurid speciation (García\selectlanguage{english}-Navas, Kear, \& Westerman,
2020). In conclusion, our analysis suggests that climate change during
the Early (\textasciitilde{}2.5-0.78\selectlanguage{english} Mya) (Lisiecki \& Raymo, 2005) and
Mid Pleistocene (0.78-0.126\selectlanguage{english} Mya) (Elderfield et al., 2012) shaped the
evolution of the dasyurid subfamily Phascogalinae by isolating
populations in different habitats.

We found that all small dasyurid taxa have much higher (100 orders of
magnitude) genome-wide heterozygosity (\selectlanguage{greek}π \selectlanguage{english}from 0.048 to 0.096) than the
endangered \emph{S. harrisii} (\selectlanguage{greek}π\selectlanguage{english}=0.00032 (Miller et al., 2011))
(\textbf{Figure S7} ). Moreover, the heterozygosity of \emph{A.
flavipes}is twofold higher than \emph{A. arktos} , \emph{A. argentus} ,
and\emph{M. melanurus} . This may reflect its larger historical and
current population size (\textbf{Figure 2b,c} ). Although we are
comparing individuals from single populations, combined with factors
such as environmental change, loss of habitat, and population
fragmentation, the lower genetic diversity of \emph{A. arktos} and
\emph{A. argentus} may reflect their present-day low population and
threatened species status (Mutton et al., 2019; Riordan, Pearce,
McDonald, Gynther, \& Baker, 2020). Future studies, including assessment
of geographic population structures and the inclusion of historical and
current specimens (Diez-Del-Molino, Sanchez-Barreiro, Barnes, Gilbert,
\& Dalen, 2018) are required to assess the threat level of extant small
dasyurids. Our high-quality \emph{Antechinus flavipes} assembly serves
as an ideal reference genome for population genomic studies of \emph{A.
flavipes}and the 14 other antechinus species.

\textbf{3.3 A gene expression profile of male die-off
in\emph{Antechinus}}

We profiled gene expression during antechinus semelparity by surveying
multiple tissues from an \emph{A. flavipes} population in Samford Valley
in Queensland, Australia during the 2018 breeding season (\textbf{File
S1} ). We observed reproductive behaviour and peak oestrus on September
15, 2018 (see Supplemental Methods for details). Adult male \emph{A.
flavipes} disappear from this site after the first week of October.
Antechinus male die-off is characterised by a dramatic increase in free
cortisol (\textbf{Figure 3a} ), mediated by a surge in testosterone
which decreases the production of corticosteroid-binding globulin
(Boonstra, 2005; Naylor et al., 2008). The potent effects of cortisol
mean that the associated gene expression and its consequences (McDowell
et al., 2018; Phuc Le et al., 2005) become a suitable backdrop against
which comparisons can be made. While corticosteroids regulate a large
number of genes via the glucocorticoid receptor (GR) (McDowell et al.,
2018; Phuc Le et al., 2005), complicating gene expression analyses,
chronic (i.e., breeding male antechinus) exposure to free
corticosteroids has distinct outcomes (Manoli et al., 2007). The steroid
hormone mediates a stress response, alters metabolism and mobilises
glucose as energy from a series of stores, initially enhancing
short-term survival. Because of a limited number of samples in our
current data set, we identified genes differentially expressed by
moribund antechinus males; individuals sampled near the conclusion of
breeding, in early October, when all males die (right panel in
\textbf{Figure 3b} ).

There were more differentially expressed genes (limma-modified
Student's\emph{t} -test \emph{P} [?]0.01) in the liver and skeletal muscle
than the kidney and cerebrum (\textbf{Figure 3c} and \textbf{File S3} ),
and most of these were downregulated. Genes upregulated in moribund male
livers showed enrichment of biological process gene sets attributed to
the innate immune response (bootstrap \emph{P} [?]0.0001) (\textbf{Table
S9} ). However, several cytokine genes (\emph{PDGFRA} , \emph{PDGFRB}
,\emph{PRNP} , \emph{CD248} , \emph{CD79A} , \emph{CXCR5} , and
\emph{CXCR6} ) were downregulated in the moribund liver (\textbf{File
S3} ). Characteristic liver pathology of the moribund male antechinus
includes infections by bacteria such as \emph{Listeria monocytogenes}
(Barker, Beveridge, Bradley, \& Lee, 1978; A. Bradley, McDonald, \& Lee,
1980), viruses (e.g., dasyurid herpesvirus 1 (Amery-Gale et al., 2014)),
and parasitic infestation (Poskitt et al., 1984). Cortisol-mediated
immunosuppression in the preceding two weeks is likely to lead to poor
late-stage resistance to invading pathogens. We identified eight genes
that were downregulated and two genes that were upregulated by both
liver and skeletal muscle of moribund males (\textbf{Figure 3d} ). This
included decreased expression of the glycophagy receptor STBD1 (Johansen
\& Lamark, 2020) and increased expression of \emph{ASNS} -- a gene
induced by amino acid starvation stress (Balasubramanian, Butterworth,
\& Kilberg, 2013). Downregulation of \emph{SLC2A4} (encodes the glucose
transporter GLUT4 (Amoasii et al., 2019)) and \emph{NUR4A2} (NUR11; a
regulator of \emph{GLUT4} expression (Amoasii et al., 2019)) indicates
reduced glucose uptake by the skeletal muscle of moribund males. KEGG
pathway and biological process enrichment analysis revealed metabolic
dysregulation of skeletal muscle in moribund males, with marked
downregulation of genes associated with glycolysis, gluconeogenesis, and
insulin signalling -- indicating insulin resistance (bootstrap\emph{P}
[?]0.0001) (\textbf{Figure 3e} , \textbf{Tables S9 and S10} ). These genes
included \emph{PRKAG3} (-4.7-fold; limma-modified Student's\emph{t}
-test, \emph{P} =3.7 \selectlanguage{ngerman}× 10\textsuperscript{-4}), which encodes a subunit
of a key energy-sensing molecule, AMP-activated protein kinase, and its
regulator LKB1 (\emph{STK11} ; -2.0-fold, \emph{P} =2.4 ×
10\textsuperscript{-3}) (\textbf{File S3} ). AMPK responds to energetic
stress to regulate multiple metabolic pathways. Reduced expression of
LKB1 was limited to the skeletal muscle of moribund \emph{A.
flavipes}males (\textbf{Figure 3f} ). LKB1 has a tissue-specific role in
energy metabolism. Complete or partial loss of \emph{Stk11} expression
in mouse skeletal muscle prevents AMPK activation and causes metabolic
defects such as acceleration of ageing-induced myopathy (Bujak et al.,
2015; Koh et al., 2006; Sakamoto et al., 2005; Thomson et al., 2007).
Our work is the first gene expression profile of a semelparous mammal.
In agreement with observational data from \emph{A. flavipes} and other
antechinuses (A. Bradley et al., 1980; Naylor et al., 2008; Woollard,
1971), our results indicate near-complete depletion of fat stores and
skeletal muscle atrophy -- leading to a catastrophic energy crisis and
an inability to maintain cognitive and physical function in moribund
males.

Further experimental work on the endocrine system of semelparous mammal
species is needed to characterise the role of testosterone and the
dysregulation of the hypothalamic-pituitary-adrenal axis and negative
feedback by cortisol. We were not able to capture gene expression
changes in brain regions other than the whole cerebrum of \emph{A.
flavipes} during the breeding season, limiting our insights into the
effects on major organs. Nevertheless, the \emph{A. flavipes} reference
genome permits future studies on gene expression and regulation (e.g.,
glucocorticoid receptor ChIP-seq).

\textbf{4.0 CONCLUSION}

Our study and accompanying data sets, including the first
chromosome-level genome of a semelparous mammal, provide a critical
resource for future studies on semelparity and its association with the
universal ageing process. Complementary genomic data, including the
genomes of additional Australasian and South American semelparous and
iteroparous marsupials, is forthcoming and promises to shed light on
whether semelparity in lineages with a common ancestor
\textasciitilde{}80 million years ago evolved by independent,
lineage-specific molecular changes or by shared molecular convergence.
The genomic resources also provide tools for broader studies on the
ecology, evolution, and conservation of marsupials.

\textbf{Acknowledgements}

Supported by the National Natural Science Foundation of China (NSFC)
grants 31950410545 (to I.S.) and 31900310 (to R.T.), the Jiangsu Science
and Technology Agency (to I.S.), the Queensland University of Technology
Faculty of Health/School of Biomedical Sciences Industry Collaboration
Preparedness Pilot Research Support Scheme (I.S., L.K.C., and A.M.B.),
and a Brazilian Council of Research and Scientific Development
(CNPQ/PELD) grant 441225/2016-0 (to N.O.L.). We thank Dr. Penny Jeffery
(Queensland University of Technology) for help with sample processing,
and Leanne Wheaton (South Australian Museum) for providing
the\emph{Murexia melanurus} tissue sample. We also thank the staff of
the Samford Ecology Research Facility (SERF) at Queensland University of
Technology for supporting our \emph{A. flavipes} field collection
activities. \emph{Antechinus flavipes} collection was approved by the
Queensland University of Technology University Animal Ethics Committee
(permit numbers 1700000661 and 1800000141) and the Queensland Department
of Environment and Science (WITK18736718).

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\textbf{Data Accessibility}

\emph{Antechinus flavipes} PacBio reads are available at China National
GenBank (CNGB) Project ID CNP0001147. Short-read whole-genome sequencing
and RNA sequencing data (BGISEQ-500) generated in this project is
available at NCBI BioProject PRJNA565840. The \emph{A. flavipes} genome
assembly is available at NCBI Genomes (JADWMD000000000). Pseudo
(reference-based) and de novo genome assemblies of \emph{Antechinus
arktos} , \emph{Antechinus argentus} and \emph{Murexia melanurus} (Seim,
2020a, 2020b), and a ROPUS Singularity image (Seim, 2020c) are available
at Zenodo. Mitochondrial genome assemblies of \emph{A.
flavipes}(MN447797), \emph{A. arktos} (MK977601), and \emph{M.
melanurus}(MK977600) are available at GenBank. Various scripts used for
data processing and analyses are available on GitHub at
https://github.com/sciseim/semelparity-genomics.

\textbf{Author contributions}

I.S. and G.F. initiated and coordinated the project. C.P., K.M, and
A.B.M. collected \emph{Antechinus flavipes} samples. L.K.C.
dissected\emph{Antechius flavipes} . A.M.B. provided voucher specimens
of\emph{Antechinus arktos} and \emph{Antechinus argentus} . P.B.T.,
L.K.C. provided frozen tissue samples for whole-genome, Hi-C, and
transcriptome sequencing. C.S. led the sequencing and assembly efforts
with G.F. R.T., K.H., and C.S. contributed to genome assembly and
annotation. R.T., K.H., C.S., and I.S. performed comparative genomics
analyses. The de novo and reference-based assemblies of \emph{A. arktos}
, \emph{A. argentus} , and \emph{M.} \emph{melanurus} were generated by
I.S. I.S. performed population history analysis. K.H. performed
diversity analysis. I.S. assembled transcriptomes and performed gene
expression analysis. R.T. performed molecular evolution analyses.
L.K.C., D.O.F., N.O.L., and A.M.B. provided direction on marsupial
ecology and physiology. R.T., L.K.C., D.O.F., A.M.B., and I.S. wrote the
paper with input from all authors.

\textbf{Tables and Figures}

\textbf{Figure 1 Overview of sequenced species and reference genome
assemblies generated in this study} . (a)~Photographs of the five
marsupial species sequenced. A yellow-footed antechinus
(\emph{Antechinus flavipes} ), silver-headed antechinus
(\emph{Antechinus argentus} ), and~black-tailed dusky antechinus
(\emph{Antechinus arktos} ) from Australia; a black-tailed dasyure
(\emph{Murexia melanurus} ) from Papua New Guinea.~\emph{Antechinus
spp.} and \emph{M. melanurus}photographs are courtesy of A.M. Baker and
John Hornbuckle, respectively. (b) Circos plot of the reference genome
assembly of\emph{A. flavipes} . The outermost segment represents
chromosome sequences, with the numbers on the external surface
indicating genome size in Mb. Chr7 in \emph{A. flavipes} corresponds to
the X chromosome. The line plots, from outside to inside represent the
distribution of CDS density (from 0 to 0.15), GC content (from 0.30 to
0.65) and TE ratio (from 0.2 to 1.0). Frequencies were calculated in
500-kb sliding windows. (c) Circos plot showing shared synteny of
\emph{Antechinus flavipes} (chr1-chr7) and \emph{Sarcophilus
harrisii}(NC\_045426.1-NC\_045432.1). Aligned using LASTZ. The synteny
blocks are linked using lines coloured in accordance with the \emph{A.
flavipes}chromosomes. Aligned blocks with length shorter than 20 kb are
not shown. Chr7 in \emph{A. flavipes} corresponds to the X chromosome
of\emph{Sarcophilus harrisii} .

\textbf{Figure 2 Evolutionary history of semelparous mammals.} (a)
Inferred phylogeny of ten marsupials and the platypus (outgroup) based
on fourfold degenerate sites from 6,431 1:1 orthologs. Blue numbers at
nodes represent the estimated divergence time from present (million
years ago; Mya) between lineages. Semelparous lineages are indicated in
red. (b) Demography of the dasyurid subfamily Phascogalinae. Historic
population sizes (\emph{N\textsubscript{e}} ) were estimated using the
pairwise sequentially Markovian coalescent (PSMC) method (Li \& Durbin,
2011) and diploid genome sequences. The \emph{x} -axis shows the time
before present in years on a log scale; the dashed gray line shows human
arrival in Australia 59.3 to 65 kya (Clarkson et al., 2017); red dots
indicate the extinction times of 15 species of Pleistocene Sahul (Saltre
et al., 2016). The \emph{y} -axis shows\emph{N\textsubscript{e}}
\textsubscript{,} with bootstrap estimates indicated by lighter lines.
Plots were scaled using a mutation rate (\selectlanguage{greek}\emph{μ} \selectlanguage{english}) of 1.37 \selectlanguage{ngerman}×
10\textsuperscript{-9} substitutions nucleotide\textsuperscript{-1}
generation\textsuperscript{-1} and species-specific generation times
(\emph{g} ) of one year. Two \emph{A. flavipes} individuals were
interrogated (coloured in orange and blue). (c) Map showing the location
(coloured circles) and elevation (mamsl; metres above sea level) of
sampled dasyurids (see subfigure b).

\textbf{Figure 3 Gene expression profiling of the \emph{Antechinus
flavipes} breeding cycle.} (a) Schematic overview of the yellow-footed
antechinus (\emph{Antechinus flavipes} ) breeding season in Samford
Valley, Queensland, Australia. Free-CORT illustrates an increase in the
level of free (unbound) stress hormones (chiefly the corticosteroid
cortisol) in males during the breeding season of antechinuses (based on
three studies illustrated in (Naylor et al., 2008)). (b) Rapid
organismal senescence of male \emph{A. flavipes} . Left, male
(\textasciitilde{}11 months of age) prior to the breeding season. Right,
late breeding stage male (\textasciitilde{}11.5 months of age). Note the
loss of fur clumps and deterioration of body condition. (c) In the
moribund state, when other energy stores have been depleted, skeletal
muscle catabolism generates amino acids for gluconeogenesis, induced by
the corticosteroid, cortisol. (d) Venn diagram for the overlap of
significantly up-regulated (left) or down-regulated (right) genes in
moribund male antechinuses. Called by limma v3.22.1 (\selectlanguage{english}[?]1.5-fold change
and \emph{P} \selectlanguage{english}[?]0.01). (e) Heat map of selected energy metabolism genes
differentially expressed in the skeletal muscle of moribund male
antechinuses. Moribund samples are indicated by a red bar below the map.
Scaled TMM-normalised read counts (denoted as the row \emph{Z} score)
are plotted, with red indicating high expression and blue indicating low
expression. \emph{BPGM} , 2,3-bisphosphoglycerate mutase; \emph{FBP2} ,
fructose-bisphosphatase 2; \emph{GPI} , glucose-6-phosphate
isomerase;\emph{LDHA} , lactate dehydrogenase A; \emph{PFKM} ,
phosphofructokinase, muscle; \emph{PGK2} , phosphoglycerate kinase 2;
\emph{PKM} , pyruvate kinase M1/2; \emph{GPD1} , glycerol-3-phosphate
dehydrogenase 1;\emph{GPD2} , glycerol-3-phosphate dehydrogenase 2;
\emph{SLC2A5} , solute carrier family 2 member 5; \emph{SLC37A4} ,
solute carrier family 37 member 4; \emph{PRKAG3} , protein kinase
AMP-activated non-catalytic subunit gamma 3; \emph{STK11} ,
serine/threonine kinase 11. (f) Expression pattern of the AMPK regulator
LKB1 (\emph{STK11} ) in male (left) and female (right) tissues
throughout the breeding season. Counts per million TMM-normalized
counts, with standard error bars.

\textbf{Table 1. \emph{Antechinus flavipes} genome assembly statistics}\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
\textbf{Assembly methods:} & \selectlanguage{ngerman}\textbf{PacBio (100×) + BGISEQ-500 (50×)
polishing} & \textbf{PacBio + BGISEQ-500 polishing+Hi-C}\tabularnewline
\midrule
\endhead
Contig number & 1,107 & 1,107\tabularnewline
Contig length (bp) & 3,192,388,871 & 3,192,388,871\tabularnewline
Contig N50 (bp) & 51,843,704 & 51,843,704\tabularnewline
Contig max length (bp) & 168,884,005 & 168,884,005\tabularnewline
Scaffold number & 1,105 & 487\tabularnewline
Scaffold N50 (bp) & 51,843,704 & 636,717,922\tabularnewline
GC content (\%) & 36.21\% & 36.21\%\tabularnewline
\bottomrule
\end{longtable}

\subsection*{\texorpdfstring{Table 2. Summary of
assembled\emph{Antechinus
flavipes}pseudochromosomes}{Table 2. Summary of assembledAntechinus flavipespseudochromosomes}}

{\label{table-2.-summary-of-assembled-antechinus-flavipes-pseudochromosomes}}\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
\textbf{Chr ID} & \textbf{Sequence number} & \textbf{Sequence Length
(bp)}\tabularnewline
\midrule
\endhead
Chr 1 & 88 & 727,308,865\tabularnewline
Chr 2 & 83 & 686,337,178\tabularnewline
Chr 3 & 146 & 636,717,922\tabularnewline
Chr 4 & 50 & 486,195,733\tabularnewline
Chr 5 & 104 & 300,479,852\tabularnewline
Chr 6 & 63 & 264,590,327\tabularnewline
Chr 7 & 91 & 86,570,782\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
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\includegraphics[width=0.70\columnwidth]{figures/Fig-1-2000px/Fig-1-2000px}

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

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

\end{center}
\end{figure}

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