Literature DB >> 27598793

Transcriptomic Changes Associated with Pregnancy in a Marsupial, the Gray Short-Tailed Opossum Monodelphis domestica.

Victoria Leigh Hansen1, Faye Dorothy Schilkey2, Robert David Miller1.   

Abstract

Live birth has emerged as a reproductive strategy many times across vertebrate evolution; however, mammals account for the majority of viviparous vertebrates. Marsupials are a mammalian lineage that last shared a common ancestor with eutherians (placental mammals) over 148 million years ago. Marsupials are noted for giving birth to highly altricial young after a short gestation, and represent humans' most distant viviparous mammalian relatives. Here we ask what insight can be gained into the evolution of viviparity in mammals specifically and vertebrates in general by analyzing the global uterine transcriptome in a marsupial. Transcriptome analyses were performed using NextGen sequencing of uterine RNA samples from the gray short-tailed opossum, Monodelphis domestica. Samples were collected from late stage pregnant, virgin, and non-pregnant experienced breeders. Three different algorithms were used to determine differential expression, and results were confirmed by quantitative PCR. Over 900 opossum gene transcripts were found to be significantly more abundant in the pregnant uterus than non-pregnant, and over 1400 less so. Most with increased abundance were genes related to metabolism, immune systems processes, and transport. This is the first study to characterize the transcriptomic differences between pregnant, non-pregnant breeders, and virgin marsupial uteruses and helps to establish a set of pregnancy-associated genes in the opossum. These observations allowed for comparative analyses of the differentially transcribed genes with other mammalian and non-mammalian viviparous species, revealing similarities in pregnancy related gene expression over 300 million years of amniote evolution.

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Year:  2016        PMID: 27598793      PMCID: PMC5012577          DOI: 10.1371/journal.pone.0161608

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

The transition from oviparity to viviparity has occurred independently multiple times in vertebrate evolution. Indeed, most vertebrates including cartilaginous fishes, bony fishes, amphibians, squamate reptiles, and mammals have lineages that transitioned to viviparity from oviparous ancestors [1]. In many viviparous vertebrates the transition away from oviparity involved the evolution of the placenta, which serves as an interface between the maternal system and the conceptus. The placenta is a specialized organ that facilitates the transfer of gases, nutrients, and waste as well as providing a physical barrier to protect the fetus from pathogens [2]. Based on phylogenetic relationships between metatherian (marsupial) and eutherian ("placental") mammals, viviparity appears to have evolved once early in the therian lineage [3-5]. There are three general categories of placental invasiveness in therians. The least invasive is epitheliochorial placentation, which is a superficial apposition of fetal and maternal membranes, where as the most is the hemochorial placenta where fetal trophoblast invades the uterine endometrium and remodels maternal capillaries [6, 7]. The third major type, an intermediary endotheliochorial placenta, also invades into the endometrium but does not directly contact maternal circulation [7]. Eutherians vary from species to species in placental invasiveness [6]. Primates and rodents typically have hemochorial placentation, whereas ruminants like cows and sheep use epitheliochorial placentas [8, 9]. Most branches of eutherians also have species that use endotheliochorial placentation, such as canines and bats [6, 9]. Prior to the widespread use of molecular phylogenetics, most theories of placental evolution were based on assuming a progression from less invasive to more invasive [10]. The current view is that the ancestral eutherian placenta was either hemochorial or endotheliochorial [9, 11–15]. The less invasive epitheliochorial placenta in eutherian species is likely an evolutionary innovation to give the mother greater control over nutrient and gas exchange [14, 15]. There is a correlation between forming an epitheliochorial placenta and giving birth to more precocial offspring in eutherians [14]. Garratt and colleagues [15] hypothesized that this may be due to maternal and fetal interests deviating relatively quickly after birth in many eutherian species with epitheliochorial placentation. The marsupials are the sister group to eutherians that give birth to relatively altricial young [16]. In contrast to the eutherian placentation trend, marsupials tend to form epitheliochorial-like placentas despite their altricial offspring. Moreover most marsupials use the yolk sac, as opposed to the allantois, to contact the chorion and form the trophoblast that is apposed to maternal membranes [16, 17]. A notable exception is within the family Peramelidae (bandicoots and echymiperas) where an invasive chorioallantoic placenta forms in the last few days before parturition [16, 18]. The morphological changes of the placenta throughout pregnancy have been well characterized in several marsupial species such as Sminthopsis crassicaudata, Macropus eugenii, and M. domestica [19-23]. M. domestica forms an invasive endotheliochorial yolk sac placenta in the last 60 hours prior to birth and, characteristic for marsupials, a permeable shell coat separates the fetal and maternal membranes for the majority of gestation [21]. M. domestica is a member of the Didelphidae family, considered to be among the least derived marsupial lineage and likely represents the ancestral reproductive characteristics of marsupials [17, 21]. Therefore M. domestica is potentially an important model for discovering other basal characteristics of reproduction in marsupials and perhaps even therians in general. More recent analyses of gene expression in reproductive tissues during opossum pregnancy have made important contributions to our understanding of the evolution of the placenta in eutherian mammals [24, 25]. Kin and colleagues described the distribution of important eutherian transcription factors (TFs) in M. domestica endometrium, determining the ancestral cell type of eutherian endometrial stromal fibroblasts (ESFs) that undergo decidualization [24]. Lynch and colleagues recently revealed that endometrially-expressed transposable elements (TEs), ancient in the eutherian lineage, have played an important role in the evolution of decidual tissues; a tissue type lacking in marsupials [25]. This has demonstrated key adaptations in endometrial tissue that may have enabled the successful extended gestation periods seen in eutherians. Needed for a greater understanding of the mammalian adaptation to viviparity are analyses of those genes differentially transcribed between pregnant and non-pregnant tissues within a non-eutherian mammal. This may also facilitate the discovery of genes crucial to marsupial pregnancy that may or may not be shared with eutherians or, indeed, other viviparous vertebrates. Presented here is just such a comparison with an analysis of the pregnant and non-pregnant uterine transcriptomes of M. domestica.

Results

To investigate changes in gene expression patterns associated with opossum pregnancy, transcriptome analyses were performed on uterine tissues from late stage pregnant (P), virgin (V), and non-pregnant (N) experienced breeders. Three biological replicates were used for each condition. Paired-end reads were generated on the Illumina HiSeq 2000 platform and aligned to the M. domestica genome. The number of mapped reads per sample ranged from 17.1 to 25.9 million at the high end, with an average of 20.4 million (S1 Table). The numbers of aligned reads per sample were more than sufficient for differential expression analysis with treatment groups containing three biological replicates [26]. Comparing the global transcriptomes individually, the nine samples segregated into pregnant (P) and non-pregnant groups (N and V) based on Jensen-Shannon (JS) distances (Fig 1). The P transcriptomes grouped together and were more similar to each other than they were to any other samples. Of the non-pregnant individuals, all three N grouped together and two of the three V individuals grouped together. Virgin opossum V1 did not group with the other virgin animals, but her uterine transcriptome was more similar to the other non-pregnant animals than to the pregnant animals (Fig 1). For this reason analyses both including and excluding V1 were performed when testing the P group against the V and N groups. No other replicate in any group was dissimilar enough to warrant being separated for further analyses. Three replicates per treatment group appeared to be adequate since they grouped together well overall indicating consistency between biological replicate transcriptomes (Fig 1). The P group was tested for differentially transcribed genes compared to N, all three V, and V2 and V3 alone (V2 & V3) (Fig 2).
Fig 1

Global transcriptomic similarities between samples.

Dendrogram of Jensen-Shannon (JS) distances between transcriptomes of replicates with the pregnant (P), virgin (V), and non-pregnant past breeder (N) transcriptomes.

Fig 2

Overlap of genes called as significant in differential expression programs.

Venn diagrams of the numbers of gene transcripts found to be significantly more abundant (A, C, and E) or less abundant (B, D, and F) when comparing the dataset from the P group to N (A and B), V (C and D) and V2 & V3 only (E and F). Genes were tested for differential expression according to Cuffdiff (pink), DESeq (yellow), and edgeR (blue). Red triangles denote the cases where at least two out of three programs were in agreement.

Global transcriptomic similarities between samples.

Dendrogram of Jensen-Shannon (JS) distances between transcriptomes of replicates with the pregnant (P), virgin (V), and non-pregnant past breeder (N) transcriptomes.

Overlap of genes called as significant in differential expression programs.

Venn diagrams of the numbers of gene transcripts found to be significantly more abundant (A, C, and E) or less abundant (B, D, and F) when comparing the dataset from the P group to N (A and B), V (C and D) and V2 & V3 only (E and F). Genes were tested for differential expression according to Cuffdiff (pink), DESeq (yellow), and edgeR (blue). Red triangles denote the cases where at least two out of three programs were in agreement. The three sample groups, V, N, and P, were compared in a pair-wise manner and independently assessed for differential transcription using Cuffdiff, DESeq, and edgeR. Since these algorithms assess differential expression using different parameters they identified partially, but not fully, overlapping sets of genes (Fig 2). Genes that were identified as being differentially transcribed by at least two of the three programs were used for this study (red triangles in Fig 2). Transcripts of 2202 genes were significantly more abundant in the P uterus compared to N (Fig 2A), whereas 2910 genes were significantly less (Fig 2B). When the P samples were compared to all three V only 986 gene transcripts increased in abundance (Fig 2C). However when V1 was excluded this number was 2061 (Fig 2E), more similar to the comparison with N (Fig 2A). There were 1798 and 2972 decreased gene transcripts in the same comparisons, respectively (Fig 2D and 2F). Therefore, including the outlier V1 suppressed the number of differentially genes. Its exclusion made the V group more similar to N in numbers of differentially transcribed genes.

Validation of differential gene transcript abundance

To validate the Illumina data, we developed quantitative PCR (qPCR) assays for a subset of genes that were differentially represented in the different groups. These were membrane cofactor protein (CD46), MAC-inhibitory protein (CD59), interleukin-6 (IL6), lysosomal-associated membrane protein 1 (LAMP1), and lumican (LUM). The direction of log2-fold change of gene expression in P compared to N samples in the Illumina datasets was recapitulated by the qPCR (Fig 3). The same was found in a P vs V comparison. These genes were not significantly differentially expressed in V compared to the N group in either Illumina or by qPCR (S1 Fig).
Fig 3

Gene transcription levels in P vs N according to differential expression programs compared to qPCR data.

Log2-fold changes in the transcription of membrane cofactor protein (CD46), MAC-inhibitory protein (CD59), interleukin 6 (IL-6), lysosomal-associated membrane protein 1 (LAMP1), and lumican (LUM) in the pregnant group compared to the non-pregnant past breeder group. Log2-fold changes were according to Cuffdiff (pink bars), DESeq (yellow bars), edgeR (blue bars), and qPCR using the Vandesompele method (black bars). Red line indicates the threshold of log2-fold change needed for significance according to the Vandesompele method of relative quantification of qPCR data. * Adjusted p < 0.05 for differential expression programs or >2 log2-fold change for qPCR.

Gene transcription levels in P vs N according to differential expression programs compared to qPCR data.

Log2-fold changes in the transcription of membrane cofactor protein (CD46), MAC-inhibitory protein (CD59), interleukin 6 (IL-6), lysosomal-associated membrane protein 1 (LAMP1), and lumican (LUM) in the pregnant group compared to the non-pregnant past breeder group. Log2-fold changes were according to Cuffdiff (pink bars), DESeq (yellow bars), edgeR (blue bars), and qPCR using the Vandesompele method (black bars). Red line indicates the threshold of log2-fold change needed for significance according to the Vandesompele method of relative quantification of qPCR data. * Adjusted p < 0.05 for differential expression programs or >2 log2-fold change for qPCR.

Pregnancy-associated genes in the opossum

To determine gene sets that were explicitly differentially transcribed during pregnancy, the intersections of differentially transcribed genes in the P set compared to both non-pregnant sets (N and V) were identified. Such genes should represent a minimal, high confidence “pregnancy-associated” set for the opossum. In the intersections of all three comparisons 932 genes were significantly more abundant and 1482 genes were less abundant in the P group (Fig 4). These increased and decreased differentially transcribed pregnancy-associated genes are listed in S2 and S3 Tables. Gene Ontology (GO) analyses of the pregnancy defining genes revealed 18 GO terms were overrepresented and 6 GO terms were underrepresented (Table 1). In the pregnancy-associated genes with decreased transcription during pregnancy, 25 GO terms were overrepresented and two were underrepresented (Table 2). The most overrepresented GO term in the increased in pregnant gene set was ion transport (p = 9.86E-06) (Table 1); the most overrepresented in the decreased in pregnant gene set was ectoderm development (p = 2.23E-09) (Table 2).
Fig 4

Pregnancy-associated gene sets.

Venn diagrams describing the intersection of genes that were considered differentially transcribed in comparisons of the P group to the N, V, and V2 & V3 control groups. The genes that were differentially transcribed in the P group compared to all three control groups (red circles) were considered to be differentially transcribed at a high level of confidence for this study.

Table 1

Overrepresented and underrepresented Biological Process GO terms in the increased transcription during pregnancy gene set.

Overrepresented GO-Slim Biological ProcessP-value
ion transport9.86E-06
immune system process9.15E-05
proteolysis1.08E-04
cellular amino acid metabolic process2.12E-04
amino acid transport3.04E-04
cation transport4.99E-04
lipid metabolic process7.04E-04
cell-matrix adhesion1.08E-03
blood coagulation1.12E-03
extracellular transport1.40E-03
cell-cell adhesion3.53E-03
angiogenesis4.64E-03
response to external stimulus7.30E-03
transport1.14E-02
response to stimulus1.52E-02
system development1.61E-02
localization2.15E-02
blood circulation2.42E-02
Underrepresented GO-Slim Biological ProcessP-value
nucleobase-containing compound metabolic process1.98E-06
RNA metabolic process4.21E-05
cell cycle2.90E-03
translation4.79E-03
DNA metabolic process1.34E-02
mRNA processing1.42E-02
Table 2

Overrepresented and underrepresented Biological Process GO terms in the decreased transcription during pregnancy gene set.

Overrepresented GO-Slim Biological ProcessP-value
cellular process2.92E-14
ectoderm development2.23E-09
nervous system development5.17E-09
multicellular organismal process9.91E-09
single-multicellular organism process9.91E-09
chromosome segregation3.10E-08
cell-cell adhesion9.10E-08
developmental process2.02E-07
system process2.76E-07
cell adhesion4.81E-07
biological adhesion4.81E-07
system development5.78E-07
cell cycle2.31E-06
neurological system process4.95E-06
mitosis4.59E-05
cellular component organization1.68E-04
cell communication4.66E-04
cellular component organization or biogenesis6.41E-04
muscle organ development1.35E-03
cell-cell signaling1.73E-03
cellular component morphogenesis8.77E-03
mesoderm development1.18E-02
cellular component movement1.81E-02
cytokinesis2.99E-02
muscle contraction3.23E-02
Underrepresented GO-Slim Biological ProcessP-value
primary metabolic process2.47E-03
metabolic process8.20E-03

Pregnancy-associated gene sets.

Venn diagrams describing the intersection of genes that were considered differentially transcribed in comparisons of the P group to the N, V, and V2 & V3 control groups. The genes that were differentially transcribed in the P group compared to all three control groups (red circles) were considered to be differentially transcribed at a high level of confidence for this study.

Differential transcript abundance between pre- vs. post-estrus

There is evidence that marsupial uterine differentiation is not completed until the first estrus occurs [16, 27]. The data sets generated for this study allow for investigation of transcriptomic differences between the N and V groups that might be linked to this differentiation. The V and N samples were transcriptomically similar to each other when compared to the P group (Fig 1). In order to determine the genes that might be linked to uterine differentiation, the pre-estrus V dataset was compared to the post-estrus N dataset. The intersections of N vs V and N vs V2 & V3 were examined and 8 genes were significantly more abundant and 4 were less abundant in V relative to N, respectively (Table 3).
Table 3

Significantly differentially transcribed genes in the virgin group as compared to the non-pregnant past breeder group.

Expression in V GroupGene SymbolEnsembl Gene IDGene Description
IncreasedSLC6A15ENSMODG00000020492Solute carrier family 6 (neutral amino acid transporter), member 15
IncreasedTFAP2CENSMODG00000016445Transcription factor AP-2 gamma (activating enhancer binding protein 2 gamma
IncreasedGPR115ENSMODG00000018861G protein-coupled receptor 115
IncreasedARG1ENSMODG00000017584Arginase 1
IncreasedZAR1ENSMODG00000020634Zygote arrest 1
IncreasedACTC1ENSMODG00000001384Actin, alpha, cardiac muscle 1
IncreasedKRT13ENSMODG00000014608Keratin 13
IncreasedRAB3BENSMODG00000000791RAB3B, member RAS oncogene family
DecreasedNTSR1ENSMODG00000016798Neurotensin receptor 1 (high affinity)
DecreasedIGKaENSMODG00000009815Ig kappa chain constant domain
DecreasedIGHaENSMODG00000029124IgG heavy chain constant domain
DecreasedIGJENSMODG00000019083Immunoglobulin J polypeptide, linker protein for immunoglobulin alpha and mu polypeptides

a Not annotated for M. domestica in Ensembl; BLASTN of gene sequence

a Not annotated for M. domestica in Ensembl; BLASTN of gene sequence

Conservation of genes regulated during pregnancy

Transcriptomic changes in M. domestica uterus during pregnancy were compared to previously published uterine transcriptome studies in pig (Sus scrofa), skink (Chalcides ocellatus), and seahorse (Hippocampus abdominalis) [28-30]. For this meta-analysis, “top-100” gene sets were identified. The top-100 significantly increased genes in opossum pregnancy are the 100 genes with the greatest transcript abundance among the 932 increased in P (Fig 4A). These were then compared to the published analyzed differentially expressed gene sets for the pig, skink, and seahorse [28-30]. Fifty-five of the top 100 gene transcripts most abundant during pregnancy for the opossum were identified as also increased in pregnant skink (Table 4). Only 11 and 1 of the selected top 100 opossum genes were identified as increased in pregnant pig and seahorse, respectively (Table 4). Of the 1482 genes identified as being decreased in pregnant (Fig 4B), the top 100 is that subset that had the greatest abundance of transcripts in the opossum N samples. Forty-three of these genes were also identified as significantly decreased in skink pregnancy (Table 5). Only 8 of these were identified in the pig pregnancy and none in the seahorse analyses (Table 5).
Table 4

Comparison of “top 100” genes with significantly higher transcription during pregnancy than a non-pregnant state for opossum (M. domestica), skink (C. ocellatus), pig (S. scrofa), and seahorse (H. abdominalis).

Gene SymbolGene DescriptionAverage Opossum Count in PregnantAverage Opossum Log2-fold ChangeSkink Log2-fold ChangeaPig Log2-fold ChangebSeahorse Log2-fold Changec
RBP4retinol binding protein 4 plasma1440358.149.040.8N/A
SOD3superoxide dismutase 3 extracellular1369027.531.64N/AN/A
LAMC1laminin gamma 1904483.470.93N/AN/A
MFGE8milk fat globule-EGF factor 8 protein686792.340.96NAN/A
VEGFAvascular endothelial growth factor A574485.161.68N/AN/A
FN1fibronectin 1563092.862.910.9N/A
OATornithine aminotransferase555773.911.25N/AN/A
TC2Ntandem C2 domains nuclear460834.624.22N/AN/A
FUCA2fucosidase alpha-L- 2 plasma456195.748.13N/AN/A
HPGDhydroxyprostaglandin dehydrogenase 15-(NAD)446493.004.46N/AN/A
APOA4apolipoprotein A-IV3571311.532.33N/AN/A
FBLN1fibulin 1356365.010.53N/AN/A
APOA1apolipoprotein A-I3475710.186.19N/A6.7
CD9Tetraspanin332562.121.13N/AN/A
GLULglutamate-ammonia ligase313782.424.47N/AN/A
BSGbasigin305802.412N/AN/A
CTGFconnective tissue growth factor273654.112.09-1.5N/A
S100A6S100 calcium binding protein A6254149.611.43N/AN/A
UGP2dUDP-glucose pyrophosphorylase 2237904.072.770.8N/A
CA15dcarbonic anhydrase 15-like)228577.984N/AN/A
SGK1serum/glucocorticoid regulated kinase 1212414.433.790.9N/A
CLUclusterin182301.881.88N/AN/A
LAMP1lysosomal-associated membrane protein 1173511.960.6N/AN/A
SLC39A9solute carrier family 39 member 9169242.041.57N/AN/A
KRT18keratin 18162872.982.6-1.6N/A
SLC41A2solute carrier family 41 member 2160394.650.71N/AN/A
CTSL1-likedcathepsin L1-like156653.129.8N/AN/A
SLC16A5solute carrier family 16 member 5152705.021.86N/AN/A
LGMNlegumain146921.697.8N/AN/A
SPINT2serine peptidase inhibitor Kunitz type 2146292.292.39N/AN/A
ABCA2ATP-binding cassette sub-family A member 2144711.370.45N/AN/A
HEXBhexosaminidase B138392.827.090.7N/A
PCK1phosphoenolpyruvate carboxykinase 1131584.547.767.7N/A
GLRXglutaredoxin128032.582.461.5N/A
HIF1Ahypoxia inducible factor 1 alpha subunit120331.431.13N/AN/A
EDEM3ER degradation enhancer mannosidase alpha-like 3116083.141.18N/AN/A
CTSAcathepsin A112522.723.49N/AN/A
EZRdezrin110852.001.67N/AN/A
ATP6V0A4ATPase H+ transporting lysosomal V0 subunit a4109735.303.53N/AN/A
TACSTD2tumor-associated calcium signal transducer 2109072.533.21N/AN/A
F3coagulation factor III103173.880.56N/AN/A
FERMT1fermitin family member 199723.471.2N/AN/A
GPX3glutathione peroxidase 398902.817.011.9N/A
FGAfibrinogen alpha chain98299.294.25N/AN/A
MDM2MDM2 oncogene E3 ubiquitin protein ligase97712.560.49N/AN/A
DPP4dipeptidyl-peptidase 497232.945.17N/AN/A
RHOUras homolog family member U94132.592.55N/AN/A
CD164CD164 molecule sialomucin93761.720.97N/AN/A
PRCPprolylcarboxypeptidase (angiotensinase C)91094.634.811.8N/A
CCNG2cyclin G290762.770.51N/AN/A
CDO1cysteine dioxygenase type 188865.032.98-1.9N/A
ENTPD5ectonucleoside triphosphate diphosphohydrolase 588532.532.33N/AN/A
HEBP1heme binding protein 188003.281.71N/AN/A
LIMA1LIM domain and actin binding 187811.391.72N/AN/A
DAG1dystroglycan 182571.710.96N/A-1.1
AURKAIP1daurora kinase A interacting protein 117522210.98Not DEN/AN/A
SLC16A1solute carrier family 16 member 1902195.11Not DE3.5N/A
GJA1gap junction protein alpha 1289362.98Not DEN/AN/A
CLSTN1calsyntenin 1255413.10Not DEN/AN/A
SEC62SEC62 homolog221111.58Not DEN/AN/A
SAT1spermidine/spermine N1-acetyltransferase 1206833.02Not DEN/AN/A
SDC4syndecan 4170652.21Not DEN/AN/A
CCNG1cyclin G1158421.56Not DEN/AN/A
GNAI1G protein alpha inhibiting activity polypeptide 1104692.27Not DEN/AN/A
ERBB3Erb-B2 receptor tyrosine kinase 381822.20Not DE1.2N/A
TIMP3TIMP metallopeptidase inhibitor 34235595.04-2.51N/AN/A
IGFBP3insulin-like growth factor binding protein 33651825.62-1.4N/AN/A
PLATplasminogen activator tissue588513.70-0.61N/AN/A
SLCO2A1solute carrier organic anion transporter family member 2A1533046.80-0.56N/A-1.6
PTGS2prostaglandin-endoperoxide synthase 2529026.44-4.64-1.7N/A
SRD5A2steroid-5-alpha-reductase alpha polypeptide 2409097.54-4.03N/AN/A
UCK2uridine-cytidine kinase 2340804.08-0.72N/AN/A
TSC22D1TSC22 domain family member 1212512.85-1.46N/AN/A
WFDC2WAP four-disulfide core domain 2188121.88-0.91N/AN/A
SLC39A8solute carrier family 39 member 8183863.51-1.831.2N/A
PROM1prominin 1181274.68-1.7N/AN/A
RNASELribonuclease L144982.67-2.12N/AN/A
METmet proto-oncogene124033.11-0.7N/AN/A
APOBdapolipoprotein B85309.77-3.32N/AN/A
ULK2unc-51 like autophagy activating kinase 285211.81-0.63N/AN/A
SERPINA1serpin peptidase inhibitor clade A member 11249878.30N/AN/AN/A
STC1stanniocalcin 1930909.48N/AN/AN/A
HBE1-likedhemoglobin subunit epsilon-like432947.45N/AN/AN/A
AFPalpha-fetoprotein4204410.50N/AN/AN/A
GABRPgamma-aminobutyric acid A receptor pi357812.29N/AN/AN/A
PIGRpolymeric immunoglobulin receptor284374.90N/AN/AN/A
CSTL1-likedcystatin-like266243.46N/AN/AN/A
SLC34A2-likedsodium-dependent phosphate transport protein 2B-like130045.03N/AN/AN/A
ESM1endothelial cell-specific molecule 1127306.66N/AN/AN/A
MDFICMyoD family inhibitor domain containing120312.08N/AN/AN/A
RBBP9retinoblastoma binding protein 9105425.81N/AN/AN/A
IL6interleukin 6105258.59N/AN/AN/A
FXYD3dFXYD domain containing ion transport regulator 3104953.86N/AN/AN/A
SLC2A1solute carrier family 2 member 1103343.24N/A3.3N/A
SUCOSUN domain containing ossification factor101632.08N/AN/AN/A
OXTRoxytocin receptor96374.46N/AN/AN/A
PCpyruvate carboxylase96262.40N/AN/AN/A
IL1R2interleukin 1 receptor type II92484.28N/A4.5N/A
CLIC6chloride intracellular channel 692024.03N/AN/AN/A
FAM213Afamily with sequence similarity 213 member A85744.33N/AN/AN/A

a Data pulled from Brandley et al. 2012

b Data pulled from Samborski et al. 2013

c Data pulled from Whittington et al. 2015

d Not annotated for M. domestica in Ensembl; BLASTN of gene sequence

Table 5

Comparison of “top 100” genes with significantly lower transcription during pregnancy than a non-pregnant state for opossum (M. domestica), skink (C. ocellatus), pig (S. scrofa), and seahorse (H. abdominalis).

Gene SymbolGene DescriptionAverage Opossum Count in Non-pregnantAverage Opossum Log2-fold ChangeSkink Log2-fold ChangeaPig Log2-fold ChangebSeahorse Log2-fold Changec
MYH11myosin heavy chain 11 smooth muscle146637-2.06-2.3N/AN/A
RPL3ribosomal protein L360395-1.79-0.11N/AN/A
MYLKmyosin light chain kinase39309-1.73-2.52N/AN/A
RPS24ribosomal protein S2430918-1.35-1.38N/AN/A
DPTdermatopontin23739-2.58-4.91N/AN/A
RPL23ribosomal protein L2323312-1.29-0.97N/AN/A
SMOC2SPARC related modular calcium binding 222716-3.88-2.52N/AN/A
IGFBP5insulin-like growth factor binding protein 521266-3.18-4.11N/AN/A
RPS8ribosomal protein S820773-1.33-1.67N/AN/A
EEF1B2eukaryotic translation elongation factor 1 beta 220740-1.70-1.02N/AN/A
RPL35ribosomal protein L3520346-1.80-0.48N/AN/A
RPS20ribosomal protein S2020268-1.82-0.53N/AN/A
RPL22ribosomal protein L2220209-1.72-1.02N/AN/A
RGS5regulator of G-protein signaling 519385-2.50-3.33N/AN/A
VCANversican18616-2.19-2N/AN/A
RPS27ribosomal protein S2718449-1.23-0.43N/AN/A
DSTdystonin17957-2.22-2.43N/AN/A
PTRFpolymerase I and transcript release factor17692-1.70-0.99N/AN/A
FGFR2fibroblast growth factor receptor 213337-2.12-1.33N/AN/A
PGRprogesterone receptor12650-2.77-3.05N/AN/A
RPL30ribosomal protein L3011864-1.28-1.94N/AN/A
DDX50DEAD (Asp-Glu-Ala-Asp) box polypeptide 5011747-1.92-1.53N/AN/A
PPP1R12Bprotein phosphatase 1 regulatory subunit 12B11508-2.37-1.93N/AN/A
CD55decay accelerating factor for complement10820-4.27-1.23N/AN/A
LMNB2lamin B29510-1.41-1.04N/AN/A
HNRNPA1dheterogeneous nuclear ribonucleoprotein A18817-2.49-1.53N/AN/A
PDGFRAplatelet-derived growth factor receptor alpha polypeptide8580-1.94-1.15N/AN/A
MYH10myosin heavy chain 10 non-muscle7912-2.43-1.01N/AN/A
ALCAMactivated leukocyte cell adhesion molecule7551-1.88-1.180.8N/A
LAMA4laminin alpha 47452-2.36-2.6N/AN/A
CCDC135coiled-coil domain containing 1357242-3.56-1.63N/AN/A
NR2F2nuclear receptor subfamily 2 group F member 26722-1.68-2.12N/AN/A
EMILIN1elastin microfibril interfacer 16590-1.77-1.62-0.7N/A
PPP1R12Aprotein phosphatase 1 regulatory subunit 12A6479-1.72-1.27N/A1.7
TPPP3tubulin polymerization-promoting protein family member 36362-2.21-0.66N/AN/A
SYNMsynemin intermediate filament protein6298-1.86-1.7N/AN/A
EDNRAendothelin receptor type A6105-3.05-1.96N/AN/A
LTBP1latent transforming growth factor beta binding protein 16017-1.61-1.6N/AN/A
EFEMP1EGF containing fibulin-like extracellular matrix protein 16003-1.89-2.77-0.8N/A
SEMA3Csemaphorin 3C5929-2.06-0.74-1.3N/A
MDN1midasin homolog (yeast)5918-1.22-2.92N/AN/A
HMGB2high mobility group box 25717-1.81-1.281N/A
LBRlamin B receptor5421-1.94-2.78N/AN/A
COL15A1collagen type XV alpha 129091-4.40Not DEN/AN/A
SERPINE2serpin peptidase inhibitor clade E member 221379-2.17Not DE1.61.6
SPOCK3testican 312675-6.37Not DEN/AN/A
WDR52WD repeat domain 5212099-3.03Not DEN/AN/A
CCDC40coiled-coil domain containing 4010227-3.37Not DEN/AN/A
OLFM4olfactomedin 410012-2.97Not DEN/AN/A
SYNE1spectrin repeat containing nuclear envelope 19834-2.62Not DEN/AN/A
ZANzonadhesin8676-5.96Not DEN/AN/A
SULF1sulfatase 17471-2.01Not DEN/AN/A
WDR78WD repeat domain 787202-3.58Not DEN/AN/A
PDLIM3PDZ and LIM domain 37000-2.16Not DE-3N/A
GPAMglycerol-3-phosphate acyltransferase mitochondrial6496-1.60Not DEN/AN/A
ADAMTS2ADAM metallopeptidase with thrombospondin type 1 motif 26288-2.07Not DEN/AN/A
DNAH9dynein axonemal heavy chain 96100-2.72Not DEN/AN/A
HTRA3HtrA serine peptidase 35795-3.19Not DEN/AN/A
CCDC39coiled-coil domain containing 395639-3.13Not DEN/AN/A
TEKT2tektin 25538-4.33Not DEN/AN/A
KIF9kinesin family member 95504-3.09Not DEN/AN/A
MAKmale germ cell-associated kinase5409-2.23Not DEN/AN/A
GSTA4glutathione S-transferase alpha 45073-6.82Not DEN/AN/A
GSNgelsolin27062-1.642.53N/AN/A
ZWILCHzwilch kinetochore protein18376-1.730.86N/AN/A
EIF3Deukaryotic translation initiation factor 3 subunit D16024-1.240.24N/AN/A
MSLNmesothelin14443-4.246.88-2.9N/A
ANXA6annexin A610093-1.571.35N/AN/A
ENPP2ectonucleotide pyrophosphatase/phosphodiesterase 28322-2.938.52N/AN/A
PCOLCEprocollagen C-endopeptidase enhancer8165-2.653.07N/AN/A
TOP2Atopoisomerase II alpha8162-4.785.36N/AN/A
TNFRSF19tumor necrosis factor receptor superfamily member 196330-3.234.17N/AN/A
CALCOCO2calcium binding and coiled-coil domain 26299-1.651.16N/AN/A
LDHBL-lactate dehydrogenase B chain6010-3.210.7N/AN/A
DNAH2dynein axonemal heavy chain 25401-4.421.62N/AN/A
DMBT1deleted in malignant brain tumors 15398-3.919.5N/AN/A
MFSD4major facilitator superfamily domain containing 45167-5.695.17-1.4N/A
KRT7keratin 75166-1.731.86N/AN/A
EIF5A2eukaryotic translation initiation factor 5A220527-1.89N/AN/AN/A
CCDC78coiled-coil domain containing 7818291-3.31N/AN/AN/A
NPTX2neuronal pentraxin II14803-7.71N/AN/AN/A
COL14A1collagen type XIV alpha 113659-4.09N/AN/AN/A
CCDC108coiled-coil domain containing 1089196-4.18N/AN/AN/A
CCDC141coiled-coil domain containing 1419031-2.23N/AN/AN/A
FILIP1Lfilamin A interacting protein 1-like8940-2.14N/AN/AN/A
COL11A2collagen type XI alpha 28803-2.17N/AN/AN/A
CIRBPcold inducible RNA binding protein8169-1.30N/AN/AN/A
ARMC3armadillo repeat containing 37039-4.05N/AN/AN/A
VTCN1V-set domain containing T cell activation inhibitor 16889-3.22N/A-3N/A
F10coagulation factor X6794-2.32N/AN/AN/A
C15orf26chromosome 15 open reading frame 266624-4.31N/AN/AN/A
C1orf87chromosome 1 open reading frame 876467-3.59N/AN/AN/A
unknownUncharacterized protein ENSMODG000000234226271-2.56N/AN/AN/A
CA3carbonic anhydrase III6219-3.87N/A4N/A
CKAP5cytoskeleton associated protein 56212-1.21N/AN/AN/A
MBL2mannose-binding lectin 26109-6.70N/AN/AN/A
MXRA5matrix-remodelling associated 55872-3.67N/AN/AN/A
TWSG1twisted gastrulation BMP signaling modulator 15738-2.08N/AN/AN/A
HDAC2histone deacetylase 25627-1.24N/AN/AN/A
DPYSL3dihydropyrimidinase-like 35169-2.07N/A-0.9N/A

a Data pulled from Brandley et al. 2012

b Data pulled from Samborski et al. 2013

c Data pulled from Whittington et al. 2015

d Not annotated for M. domestica in Ensembl; BLASTN of gene sequence

a Data pulled from Brandley et al. 2012 b Data pulled from Samborski et al. 2013 c Data pulled from Whittington et al. 2015 d Not annotated for M. domestica in Ensembl; BLASTN of gene sequence a Data pulled from Brandley et al. 2012 b Data pulled from Samborski et al. 2013 c Data pulled from Whittington et al. 2015 d Not annotated for M. domestica in Ensembl; BLASTN of gene sequence

Discussion

Pregnancy involves substantial tissue remodeling and physiological changes. This study was aimed at investigating the changes that occur at the level of uterine gene transcription in a model marsupial species. Marsupials are a distinct lineage of mammals noteworthy for their short gestation times, relative immaturity at birth, and minimal placentation [16]. Viviparity likely has a single common origin in marsupials and eutherians, which last shared a common ancestor at least 148 million years (MY) ago, making marsupials an important comparative contrast to pregnancy in eutherians [3-5]. The comparison between pregnant and non-pregnant samples was chosen to identify the most differentially transcribed uterine genes during pregnancy. All the P and N samples used in this study came from opossums that had successfully given birth to at least one litter prior to this study. Based on what genes were being transcribed and the transcript number, the P transcriptomes were distinctly different from those of non-pregnant animals, whether N or V (Fig 1). Sets of pregnancy-associated genes were identified as those at the intersection of differentially transcribed in the P versus all non-pregnant animals (N and V). Identifying the overlap in differentially transcribed genes in P vs N, P vs V, and P vs V2 & V3 generated gene sets with of high confidence for being significantly increased or decreased during opossum pregnancy. It is noteworthy that there were more genes with decreased transcription in the opossum uterus than increased transcription during pregnancy (n = 550; the difference between Fig 4A and 4B). The top 100 most differentially transcribed opossum genes in the P and N groups were compared to results from pregnant uterine transcriptome studies in the pig, skink, and seahorse [28-30]. The pattern of differentially expression during pregnancy in skink had the most in common with the results in M. domestica. This similarity is unlikely due to shared structural similarities between the opossum and skink since the skink (C. ocellatus) has an epitheliochorial chorioallantoic placenta [28, 31, 32]. Rather the similarity in transcriptomes is likely due to the skink study focusing on a pregnancy time point more similar to that used here in the opossum. The opossum P samples were from uteruses preceding parturition by only 12–24 hours and there was likely to be late-pregnancy and parturition-specific gene transcription represented in the datasets. In contrast there was less overlap with the transcriptome in the pig. This may due to the pig study focusing primarily on early pregnancy stages and also the pig’s chorioallantoic epitheliochorial placenta type and the source of embryonic nutrition, which primarily histotrophic rather than hemotrophic [29, 33, 34]. Likewise, there was very little overlap with the seahorse, which may be due to evolutionary distance or, again, the pregnancy time points examined. Since there was substantial overlap in genes differentially transcribed in both the opossum and the skink, we focused on this comparison further. Keratin 18 (KRT18) is has been previously shown to be essential to maintaining pregnancy in mice [35] and KRT18 is increased during pregnancy in both opossum and skink (Table 4). KRT18 is the only keratin gene that is increased in pregnant opossum (S2 Table). This is in contrast to eutherian pregnancy, such as in pigs and humans, where in addition to KRT18, KRT8 and KRT19 are also up-regulated [29, 36]. Other notable genes transcripts encoding structural molecules that are more abundant consistently in opossum and skink pregnancy are fibronectin (FN1) and fibulin (FBLN1) (Table 4). Both of these have been shown to be important to maintaining pregnancy in eutherian species such as mice [37, 38] and this conservation across a long evolutionary history is consistent with such proteins being critical to placental formation. In contrast serpin peptidase inhibitor clade member 2 (SERPINE2), an up-regulated tissue remodeling gene in human, mouse, pig, and even seahorse pregnancy [29, 30, 39, 40], was among the most decreased gene transcripts during opossum pregnancy (Table 5). SERPINE2 is also not differentially regulated in skinks [28]. Therefore, although SERPINE2 transcription in pregnancy is shared between a teleost and eutherians, this does not appear to be a critically conserved gene. Not surprisingly, an area of broad conservation was hormonal regulation. For example, progesterone receptor (PGR) had fewer transcripts during pregnancy in both opossum and skink (Table 5), and down-regulation of PGR in endometrial cells is observed in eutherian species at implantation [41-44]. Kin and colleagues used immunohistochemistry (IHC) to demonstrate that term pregnant M. domestica uterine epithelium and uterine glands express PGR weakly in comparison to non-pregnant uterine tissues [24]. The transcriptome results described here are consistent with that finding (S4 Table). Oxytocin receptor (OXTR) is more abundant in opossum at terminal pregnancy and in human pregnancy OXTR expression increases over time peaking prior to parturition and playing a role in inducing contractions [45-48]. Interestingly, Yamashita and Kitano [49] hypothesized that the evolution of OXTR associated with labor contractions in eutherians occurred after the marsupial-eutherian split. However, OXTR was a top 100 most abundant gene in pregnant opossum raising the possibility of its role in parturition being more ancient than the marsupial-eutherian split. Prostaglandins have been shown to be important to normal birth mechanisms in other marsupials such as the tammar wallaby [50, 51]. Injection of exogenous prostaglandin F2 (PGF2) have also been shown to induce birthing in marsupials [50, 52]. The pregnant samples used in this study were taken from opossums that were within 24 hours of giving birth and it is probable that gene transcript values in these pregnant transcriptomes were influenced by birth mechanisms at work. Genes involved in prostaglandin synthesis and detection such as prostaglandin E synthase (PTGES), prostaglandin-endoperoxide synthase 2 (PTGS2), and prostaglandin E receptor 4 subtype EP4 (PTGER4) were all included in the increased in pregnancy-associated set (S2 Table). Eight solute carrier proteins (SLC39A9, SLC41A2, SLC16A5, SLC16A1, SLCO2A1, SLC39A8, SLC34A2L, SLC2A1) are included in the top 100 most abundant genes in opossum during pregnancy (Table 4). This is consistent with ion transport being the most highly overrepresented GO term in the datasets. Two of these, SLC39A9 and SLC41A2 are zinc and magnesium ion transporters that are also up-regulated during skink pregnancy [28, 53, 54]. Transporters of cholesterol and chylomicrons like ATP-binding cassette sub-family A member 2 (ABCA2) and apolipoprotein genes APOA1, APOA4, and APOB are also in the top 100 most abundant gene transcripts in opossum pregnancy (Table 4) which is consistent with what is known about cholesterol transport across eutherian placentas [55]. Two different non-pregnant control groups were used in this study due to concern over previous observations on sexual maturation in M. domestica [27]. Briefly, M. domestica females do not appear to reach reproductive maturity until they enter estrus and mate for the first time, a process dependent on male pheromones. Therefore, both virgin (V) females (pre-first estrus) as well as non-pregnant (N) experienced past breeders (post-first estrus) were used. In addition to providing controls for the pregnant state, this also allowed for a direct comparison between presumably immature pre-estrus and more mature post-estrus uterine tissues. In the analyses comparing the V group to P and N, only 12 genes were uniquely differentially transcribed in common (Table 3). Interestingly three of the four genes less abundant (Ig J chain, Ig kappa chain, IgG heavy chain constant domain) in virgin uterine tissue were genes associated with antibody expression (Table 3). This may indicate a need for humoral immunity in uterine tissues only after copulation and could point to a mechanism for controlling sexually transmitted infections in opossums. The morphological changes described by Stonerook and Harder [27], which is primarily organ weight, do not appear to be substantially reflected in changes in gene regulation in the uterus. Actin alpha cardiac muscle 1 (ACTC1) and keratin 13 (KRT13) are two of eight significantly more abundant genes in the virgin samples but no other major structural genes are differentially transcribed between the non-pregnant groups (Table 3). The V group had the most variation between biological replicates than any other group as illustrated by V1 being an outlier (Fig 1). Nonetheless, V1 was transcriptomically more similar to the non-pregnant samples than to the pregnant ones. V1’s outlier status may have been due to her being 4.8 months and old at the time of collection, whereas the other two virgin animals (V2 and V3) were 10 months old. M. domestica individuals are generally considered to be sexually mature at 5–6 months old [56], but V1’s uterus was likely in a different stage of development from the older virgin animals. Aside from V1, all biological replicates were more similar to each other than to samples from other treatment groups (Fig 1). Non-pregnant individuals (groups N and V) were more similar to each other than they were to the pregnant individuals (Fig 1). This was an expected result and provided justification for retaining V1 in the analyses of differential transcription. There were more differentially transcribed genes shared between the P vs N and P vs V2 & V3 comparisons than between the P vs V and P vs V2 & V3 comparisons (Fig 4). This confirmed that V1 was skewing the differential transcription results in the P vs V comparison. Kin and colleagues identified TFs spatially in M. domestica endometrium tissue sections in non-pregnant, pre-implantation pregnancy, and term pregnancy using IHC [24]. They concluded that the stromal mesenchymal cells seen in M. domestica endometrium are homologous to eutherian ESFs based on the expression of TFs and certain cytoskeletal proteins, and no marsupial has definitive decidualization. Two of the transcription factors (TFs) examined by Kin and colleagues were found in our pregnancy-associated gene sets. These were PGR, which was less abundant in pregnant samples, and CEBPB which was more abundant in pregnant samples (S4 Table). All samples examined in this study did have gene transcripts from the TFs evaluated in the Kin et al study (S4 Table). This is not surprising since Kin and colleagues observed transcription factors in a spatial manner by comparing IHC-stained endometrium of pregnant and non-pregnant M. domestica, whereas our study used whole sections of tissue without separating by cell type. Indeed, a limitation of the data sets used in this study is that they contain multiple cell and tissue types and therefore a specific transcript cannot be ascribed to a particular cell or tissue. Therefore in future studies on the genes identified as pregnancy-associated here, a spatial analysis of gene expression would be informative. In conclusion, the analysis of the opossum late pregnancy uterine transcriptome enabled the discovery of a set of genes that can be described as being pregnancy-associated in the opossum. Curiously, morphological changes associated with sexual maturation in the opossum uterus reported previously are not obviously reflected in the transcriptome of this species. These analyses also revealed significant conservation of gene regulation among distantly related species. Reptiles and mammals are separated by over 300 MY of evolution and the opossum and skink do not share a common viviparous ancestor [57, 58]. While the similar nature of the gene regulation is likely indicative of convergence on common mechanisms in the evolution of live birth, the transcriptomic similarities in these studies could be explained by the similar pregnancy stages examined here and in the skink.

Materials and Methods

Animals and tissue collection

This study was approved under protocol numbers 13-100920-MCC and 15-200334-B-MC from the University of New Mexico Institutional Animal Care and Use Committee. Animals were from a captive-bred research colony housed at the University of New Mexico Department of Biology Animal Research Facility. Founders were obtained from M. domestica Populations 1 and 2 at the Southwest Foundation for Biomedical Research, San Antonio, TX [59]. All animals were fed ad libitum a diet of Labdiet Short Tailed Opossum #2 pellets (90%, Lab Supply TX) and dried mealworms (10%, Lab Supply TX). They were given drinking water ad libitum in sterile glass sipper bottles. All animals were housed individually in standard rat caging and bedding. When not breeding adult females and males were caged separately. All animals used in tissue collection were euthanized by inhaled isoflurane overdose (>5%) until breathing stopped for one minute. Uterine tissues were collected from virgin (V), pregnant (P), and non-pregnant (N) experienced breeders. Non-pregnant past breeders had at least one successful pregnancy prior to harvesting. Uterine horns were excised and separated from surrounding tissues. In the case of pregnant uteri, the uterine horns were opened laterally and the intact embryos and amnions removed. Endometrium was separated from myometrium by teasing apart the tissue layers in shallow petri dishes filled with RNALater buffer (Ambion). In pregnant samples invasive fetal chorion and yolk sac membranes could not be fully separated from maternal endometrium. RNA extractions were either performed immediately or tissues were stored in RNALater overnight at 4°C. For longer-term storage, excess RNALater was removed and tissues were stored at -80°C until use.

RNA extraction

Total RNA was isolated by homogenizing tissue in TRIzol (Ambion) using a sterile glass homogenizer followed by chloroform extraction and centrifugation at 4°C for 15 min. Protein and DNA contamination was removed using the PureLink RNA Mini (Ambion) and On-Column DNase Treatment (Invitrogen) kits following manufacturers' recommended protocols. RNA was stored in RNase-free water at -80°C. RNA quality was assessed using a 2100 Bioanalyzer (Agilent) and concentration was determined using a Qubit 2.0 Fluorometer (Life Technologies).

cDNA library synthesis and Illumina sequencing

All cDNA library synthesis for high-throughput RNA-seq and Illumina sequencing procedures were performed at the National Center for Genome Resources (NCGR) in Santa Fe, New Mexico, USA. A Sciclone G3 Automated Liquid Handling Workstation (Caliper Life Sciences) with a Multi TEC Control for heating and cooling steps (INHECO) was used for the majority of liquid handling. Poly-A RNA was isolated using magnetic RNA Purification Beads (Dynabeads: Invitrogen). RNA was fragmented by high temperature (95°C for 8 min). SuperScript II enzyme (Intvitrogen), First Strand Master Mix (Illumina), and random hexamer primers (Illumina) were added to RNA to conduct first strand cDNA synthesis by reverse transcription. Second Strand Master Mix (Illumina) was used to conduct second strand cDNA synthesis, resulting in double-stranded cDNA. Double-strand cDNA was isolated using Agencourt AMPure XP beads (Beckman Coulter). Blunt end cDNA was prepared by removing 3’ overhangs and filling in 5’ overhangs using End Repair Mix (Illumina). 3’ ends were then adendylated using A-Tailing Mix (Illumina). Universal and barcoded TruSeq Adapters (Illumina) were ligated to cDNA ends. Polymerase Chain Reaction (PCR) was conducted with KAPA HiFi HotStart ReadyMix (KAPA Biosystems) and PCR Primer Cocktail (Illumina) to selectively amplify the cDNA fragments that had TruSeq adapters ligated to both ends. PCR products were purified using Agencourt AMPure XP beads. PCR product quality was assessed using a 2100 Bioanalyzer and cDNA quantity was measured by Nanodrop ND-1000 (Thermo Scientific). Samples were normalized to 10nM equimolar concentrations and pooled prior to flow cell injection. All Illumina sequencing was performed on an Illumina HiSeq 2000 instrument (Illumina) to generate 50bp paired-end reads. Read data was de-multiplexed (segregated by library index) using Illumina CASAVA v1.8.2 to produce FASTQ files. Thereafter, NCGR’s custom contaminant filtering pipeline removed anomalous sequences (i.e. Illumina PhiX control, library adapters, primer dimmers, and library indexes not part of the experiment). Quality assessment of read data was performed using FASTQC.

Data access

All high-throughput sequence data sets generated for this study have been deposited at NCBI Sequence Read Archive (SRA) under the accession numbers SRR2969483, SRR2969536, SRR2970443, SRR2972728, SRR2972729, SRR2972792, SRR2972837, SRR2972840, and SRR2972848.

Illumina read quality control, alignment, and quantification

All alignment and differential expression bioinformatics programs were run through the online Lumenogix platform (api.lumenogix.com, [60]). Reads were aligned to the annotated M. domestica genome (assembly: monDom5, annotation: Ensembl release 76) using Tophat2 [61, 62]. For a summary of Illumina read counts for this study see S1 Table. Read-count based differential expression was performed by Cufflinks, which normalizes by transcript length and apportions multi-mapped reads, and HTSeq which counts at the gene level and counts only uniquely mapped reads. Differential expression analysis was performed in three different algorithms: Cuffdiff, DESeq, and edgeR. Filtering was performed using log2-fold changes and adjusted p-value ≤ 0.05.

Quantitative PCR

All RNA used for qPCR originated from the same RNA samples used for Illumina sequencing. Prior to cDNA synthesis, all RNA used in cDNA synthesis was treated with DNase using the TURBO DNA-free Kit (Ambion) according to manufacturers’ recommended protocols. 500ng of total RNA was used to make cDNA libraries by reverse transcriptase PCR (RT-PCR) using the SuperScript III First Strand Synthesis kit (Invitrogen) according to the manufacturer’s instructions. All cDNA libraries were made in triple replicates and then pooled to reduce bias generated during reverse transcription. Transcription levels of specific genes were assessed by qPCR using ABsolute Blue QPCR SYBR Green ROX Mix (Thermo Scientific) according to manufacturer’s instructions. Primers used in qPCR were designed for the M. domestica genome and according to manufacturer’s recommendations for qPCR primer properties. Primer sequences and properties are in S2 Table. All qPCR reactions were performed in triplicate repeats on an ABI Prism 7000 Sequence Detection System (Applied Biosystems) using the default cycling parameters with a dissociation step. qPCR data were assessed by the Vandesompele method [63, 64] using tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta polypeptide (YWHAZ) and TATA box-binding protein (TBP) as reference genes. These reference genes were chosen based on relatively consistent transcription across Illumina data samples (S5 Table), as well as literature recommending them as reference genes for placental gene expression studies [65, 66]. All pregnant and virgin qPCR gene transcription levels described here were relative to the non-pregnant past breeder group, and greater than 2-fold change was considered significant. Genes were chosen for qPCR confirmation based on being differentially transcribed in the Illumina data set, having >20 reads per sample in the Illumina data set, and novel qPCR primers passing efficiency testing. All primers were generated using the online tool Primer 3 (http://primer3.ut.ee/, [67]) with M. domestica gene sequences from the MonDom5 genome assembly. Primer sets used for qPCR and their associated properties are listed in S5 Table.

Differential transcription analysis

Three separate differential expression analysis tools, Cuffdiff version 2.2.1, [68, 69], DESeq version 1.2.1 [70], and edgeR version 2.0.5 [71], were used to assess relative gene transcription between the P, N and V groups. All Venn diagrams were created using the R package VennDiagram [72]. The R package cummeRbund [73] was used to produce a dendrogram describing Jensen-Shannon (JS) distances between sample transcriptomes. The dendrogram was modified for readability in Microsoft PowerPoint. Since DESeq and edgeR use read counts and Cuffdiff uses Fragments Per Kilobase of transcript per Million mapped reads (FPKM) to calculate differential expression, the log2-fold change and associated adjusted p-value of genes were reported in cases where differential expression analysis results of specific genes were compared. The adjusted p-value threshold was ≤ 0.05 for all used differential expression programs.

Gene Ontology analysis

Gene Ontology (GO) analysis was performed using online PANTHER tools (http://www.pantherdb.org/ [74, 75]. Specific gene sets were tested for statistical overrepresentation or underrepresentation of PANTHER GO-Slim Biological Process terms. Gene sets were compared to the whole uterine transcriptome gene set (all genes with expression of ≥ 1 FPKM in at least one uterine sample transcriptome) and GO terms with p < 0.05 (Bonferroni corrected for multiple testing) were considered significant. The “Unclassified” GO category was ignored in all analyses.

Gene transcription levels in P vs V according to differential expression programs compared to qPCR data.

Log2-fold changes in the expression of membrane cofactor protein (CD46), MAC-inhibitory protein (CD59), interleukin 6 (IL-6), lysosomal-associated membrane protein 1 (LAMP1), and lumican (LUM) in the virgin group compared to the non-pregnant past breeder group. Log2-fold changes were according to Cuffdiff (pink bars), DESeq (yellow bars), edgeR (blue bars), and qPCR using the Vandesompele method (black bars). Red line indicates the threshold of log2-fold change needed for significance according to the Vandesompele method of relative quantification of qPCR data. None significant. (TIF) Click here for additional data file.

Summary of Illumina read counts for each sequenced sample.

(XLSX) Click here for additional data file.

Genes with significantly higher transcription in pregnant samples.

List of all pregnancy-associated increased transcription genes (n = 932) in P group compared to N, V, and V2 & V3. Gene list includes transcript counts for all samples and p-values and log2-fold change values as measured by Cuffdiff, edgeR, and DESeq for all comparisons. (XLSX) Click here for additional data file.

Genes with significantly lower transcription in pregnant samples.

List of all pregnancy-associated decreased transcription genes (n = 1482) in P group compared to N, V, and V2 & V3. Gene list includes transcript counts for all samples and p-values and log2-fold change values as measured by Cuffdiff, edgeR, and DESeq for all comparisons. (XLSX) Click here for additional data file.

Illumina read counts for selected transcription factor genes.

(XLSX) Click here for additional data file.

Primers used in qPCR reactions and their properties.

(XLSX) Click here for additional data file.
  67 in total

Review 1.  The marsupial placenta: a phylogenetic analysis.

Authors:  Claudia Freyer; Ulrich Zeller; Marilyn B Renfree
Journal:  J Exp Zool A Comp Exp Biol       Date:  2003-09-01

2.  The effect of elevated progesterone and pregnancy status on mRNA expression and localisation of progesterone and oestrogen receptors in the bovine uterus.

Authors:  L A Okumu; N Forde; A G Fahey; E Fitzpatrick; J F Roche; M A Crowe; P Lonergan
Journal:  Reproduction       Date:  2010-04-19       Impact factor: 3.906

Review 3.  The role of maternal-fetal cholesterol transport in early fetal life: current insights.

Authors:  Maria E Baardman; Wilhelmina S Kerstjens-Frederikse; Rolf M F Berger; Marian K Bakker; Robert M W Hofstra; Torsten Plösch
Journal:  Biol Reprod       Date:  2013-01-31       Impact factor: 4.285

4.  Functional characterization of the mouse [corrected] solute carrier, SLC41A2.

Authors:  Angela Goytain; Gary A Quamme
Journal:  Biochem Biophys Res Commun       Date:  2005-05-13       Impact factor: 3.575

5.  The hormonal control of birth behavior in the gray short-tailed opossum (Monodelphis domestica).

Authors:  R Rose; B H Fadem
Journal:  Horm Behav       Date:  2000-03       Impact factor: 3.587

6.  Uterine epithelial cell changes during pregnancy in a marsupial (Sminthopsis crassicaudata; Dasyuridae).

Authors:  Melanie K Laird; Michael B Thompson; Christopher R Murphy; Bronwyn M McAllan
Journal:  J Morphol       Date:  2014-04-16       Impact factor: 1.804

7.  Evolution of the mammalian placenta revealed by phylogenetic analysis.

Authors:  Derek E Wildman; Caoyi Chen; Offer Erez; Lawrence I Grossman; Morris Goodman; Roberto Romero
Journal:  Proc Natl Acad Sci U S A       Date:  2006-02-21       Impact factor: 11.205

8.  Temporal and spatial alterations in uterine estrogen receptor and progesterone receptor gene expression during the estrous cycle and early pregnancy in the ewe.

Authors:  T E Spencer; F W Bazer
Journal:  Biol Reprod       Date:  1995-12       Impact factor: 4.285

9.  Phylogenetic evidence for early hemochorial placentation in eutheria.

Authors:  M G Elliot; B J Crespi
Journal:  Placenta       Date:  2009-10-02       Impact factor: 3.481

10.  Ancient transposable elements transformed the uterine regulatory landscape and transcriptome during the evolution of mammalian pregnancy.

Authors:  Vincent J Lynch; Mauris C Nnamani; Aurélie Kapusta; Kathryn Brayer; Silvia L Plaza; Erik C Mazur; Deena Emera; Shehzad Z Sheikh; Frank Grützner; Stefan Bauersachs; Alexander Graf; Steven L Young; Jason D Lieb; Francesco J DeMayo; Cédric Feschotte; Günter P Wagner
Journal:  Cell Rep       Date:  2015-01-29       Impact factor: 9.423

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  10 in total

1.  A pronounced uterine pro-inflammatory response at parturition is an ancient feature in mammals.

Authors:  Victoria L Hansen; Lauren S Faber; Ali A Salehpoor; Robert D Miller
Journal:  Proc Biol Sci       Date:  2017-10-25       Impact factor: 5.349

Review 2.  Cooperative inflammation: The recruitment of inflammatory signaling in marsupial and eutherian pregnancy.

Authors:  Daniel J Stadtmauer; Günter P Wagner
Journal:  J Reprod Immunol       Date:  2019-10-25       Impact factor: 4.054

3.  Embryo implantation evolved from an ancestral inflammatory attachment reaction.

Authors:  Oliver W Griffith; Arun R Chavan; Stella Protopapas; Jamie Maziarz; Roberto Romero; Gunter P Wagner
Journal:  Proc Natl Acad Sci U S A       Date:  2017-07-26       Impact factor: 11.205

4.  Endometrial recognition of pregnancy occurs in the grey short-tailed opossum ( Monodelphis domestica).

Authors:  Oliver W Griffith; Arun R Chavan; Mihaela Pavlicev; Stella Protopapas; Ryan Callahan; Jamie Maziarz; Günter P Wagner
Journal:  Proc Biol Sci       Date:  2019-06-19       Impact factor: 5.349

5.  Evidence for regulation of the complement system during pregnancy being ancient and conserved in mammals.

Authors:  Victoria L Hansen; Robert D Miller
Journal:  Dev Comp Immunol       Date:  2019-11-27       Impact factor: 3.636

6.  Uterine epithelial remodelling during pregnancy in the marsupial Monodelphis domestica (Didelphidae): Implications for mammalian placental evolution.

Authors:  Melanie K Laird; Victoria L Hansen; Bronwyn M McAllan; Christopher R Murphy; Michael B Thompson
Journal:  J Anat       Date:  2020-02-12       Impact factor: 2.921

7.  Transcriptomic changes in the pre-implantation uterus highlight histotrophic nutrition of the developing marsupial embryo.

Authors:  Camilla M Whittington; Denis O'Meally; Melanie K Laird; Katherine Belov; Michael B Thompson; Bronwyn M McAllan
Journal:  Sci Rep       Date:  2018-02-05       Impact factor: 4.379

8.  Didelphis albiventris: an overview of unprecedented transcriptome sequencing of the white-eared opossum.

Authors:  Íria Gabriela Dias Dos Santos; Tiago Antônio de Oliveira Mendes; Gerluza Aparecida Borges Silva; Amanda Maria Sena Reis; Cláudia Barros Monteiro-Vitorello; Patricia Dayane Carvalho Schaker; Roberto Hirochi Herai; André Brait Carneiro Fabotti; Luiz Lehmann Coutinho; Erika Cristina Jorge
Journal:  BMC Genomics       Date:  2019-11-15       Impact factor: 3.969

9.  Evolutionary transcriptomics implicates HAND2 in the origins of implantation and regulation of gestation length.

Authors:  Mirna Marinić; Katelyn Mika; Sravanthi Chigurupati; Vincent J Lynch
Journal:  Elife       Date:  2021-02-01       Impact factor: 8.140

10.  Identification of regenerative processes in neonatal spinal cord injury in the opossum (Monodelphis domestica): A transcriptomic study.

Authors:  Benjamin J Wheaton; Johnny Sena; Anitha Sundararajan; Pooja Umale; Faye Schilkey; Robert D Miller
Journal:  J Comp Neurol       Date:  2020-08-04       Impact factor: 3.215

  10 in total

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