1. Evolutionary Biology
  2. Genetics and Genomics
Download icon

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

  1. Mirna Marinić
  2. Katelyn Mika
  3. Sravanthi Chigurupati
  4. Vincent J Lynch  Is a corresponding author
  1. Department of Human Genetics, University of Chicago, United States
  2. Department of Biological Sciences, University at Buffalo, United States
Research Article
  • Cited 3
  • Views 1,365
  • Annotations
Cite this article as: eLife 2021;10:e61257 doi: 10.7554/eLife.61257

Abstract

The developmental origins and evolutionary histories of cell types, tissues, and organs contribute to the ways in which their dysfunction produces disease. In mammals, the nature, development and evolution of maternal-fetal interactions likely influence diseases of pregnancy. Here we show genes that evolved expression at the maternal-fetal interface in Eutherian mammals play essential roles in the evolution of pregnancy and are associated with immunological disorders and preterm birth. Among these genes is HAND2, a transcription factor that suppresses estrogen signaling, a Eutherian innovation allowing blastocyst implantation. We found dynamic HAND2 expression in the decidua throughout the menstrual cycle and pregnancy, gradually decreasing to a low at term. HAND2 regulates a distinct set of genes in endometrial stromal fibroblasts including IL15, a cytokine also exhibiting dynamic expression throughout the menstrual cycle and gestation, promoting migration of natural killer cells and extravillous cytotrophoblasts. We demonstrate that HAND2 promoter loops to an enhancer containing SNPs implicated in birth weight and gestation length regulation. Collectively, these data connect HAND2 expression at the maternal-fetal interface with evolution of implantation and gestational regulation, and preterm birth.

Introduction

The ontogeny and evolutionary history of cell types, tissues, and organ systems, as well as the life histories of organisms bias the ways in which dysfunctions in those systems underlie disease (Varki, 2012). Thus, a mechanistic understanding of how cells, tissues, and organs evolved their functions, and how organism’s life histories influence them, may provide clues to the molecular etiologies of disease. The most common way of utilizing evolutionary information to characterize the genetic architecture of disease is to link genetic variation within a species to phenotypes using quantitative trait loci (QTL) or genome-wide association studies (GWAS). An alternative approach is to identify fixed genetic differences between species that are phylogenetically correlated with different disease relevant phenotypes. While the risk of cancer increases with the age of an individual, for example, the prevalence of cancer types varies by species (Abegglen et al., 2015), likely because of differences in genetic susceptibility to specific cancers, structure of organ and tissue systems, and life exposures to carcinogens (Varki and Varki, 2015). Similarly, the risk of cardiovascular disease (CVD) increases with age across species, but the pathophysiology of CVD can differ even between closely related taxa such as humans, in which CVD predominantly results from coronary artery atherosclerosis, and the other Great Apes (Hominids), in which CVD is most often associated with interstitial myocardial fibrosis (Varki et al., 2009).

Extant mammals span major stages in the origins and diversification of pregnancy, thus a mechanistic understanding of how pregnancy originated and diverged may provide unique insights into the ontogenetic origins of pregnancy disorders. The platypus and echidna (Monotremes) are oviparous, but the embryo is retained in the uterus for 10–22 days, during which the developing fetus is nourished by maternal secretions delivered through a simple placenta, prior to the laying of a thin, poorly mineralized egg that hatches in ~2 weeks (Hill, 1936). Live birth (viviparity) evolved in the stem-lineage of Therian mammals, but Marsupials and Eutherian (‘Placental’) mammals have dramatically different reproductive strategies. In Marsupials, pregnancies are generally short (~25 days) and completed within the span of a single estrous cycle (Renfree and Shaw, 2001; Renfree, 2010). Eutherians, in contrast, evolved a suite of traits that support prolonged pregnancies (up to 670 days in African elephant), including an interrupted estrous cycle, which allows for gestation lengths longer than a single reproductive cycle, maternal-fetal communication, maternal recognition of pregnancy, implantation of the blastocyst and placenta into uterine tissue, differentiation (decidualization) of endometrial stromal fibroblasts (ESFs) in the uterine lining into decidual stromal cells (DSCs), and maternal immunotolerance of the antigenically distinct fetus, that is the fetal allograft (Guleria and Pollard, 2000; Moffett and Loke, 2004; Erlebacher, 2013).

Gene expression changes at the maternal-fetal interface underlie evolutionary differences in pregnancy (Hou et al., 2012; Lynch et al., 2015; Armstrong et al., 2017), and thus likely also pathologies of pregnancy such as infertility, recurrent spontaneous abortion (Kosova et al., 2015), preeclampsia (Elliot, 2017; Arthur, 2018; Varas Enriquez et al., 2018), and preterm birth (Plunkett et al., 2011; Swaggart et al., 2015; LaBella, 2019). Here, we assembled a collection of gene expression data from the pregnant/gravid maternal-fetal interface of tetrapods and used evolutionary methods to reconstruct gene expression changes during the origins of mammalian pregnancy. We found that genes that evolved to be expressed at the maternal-fetal interface in the Eutherian stem-lineage were enriched for immune functions and diseases, as well as preterm birth. Among the recruited genes was the transcription factor Heart- and neural crest derivatives-expressed protein 2 (HAND2), which plays essential roles in neural crest development (Srivastava et al., 1997), cardiac morphogenesis (Srivastava et al., 1997; Shen et al., 2010; Tamura et al., 2013; Lu et al., 2016; Sun et al., 2016), and suppressing estrogen signaling during the period of uterine receptivity to implantation (Huyen and Bany, 2011; Li et al., 2011; Shindoh et al., 2014; Fukuda et al., 2015; Mestre-Citrinovitz et al., 2015; Murata et al., 2019; Šućurović et al., 2020). We determined that HAND2 expression at the first trimester maternal-fetal interface was almost entirely restricted to cell types in ESF lineage and is regulated by multiple transcription factors that control progesterone responsiveness. Moreover, the HAND2 promoter loops to an enhancer with single-nucleotide polymorphisms (SNPs) that have been implicated by GWAS in the regulation of gestation length (Warrington et al., 2019; Sakabe et al., 2020). Furthermore, we showed that HAND2 regulates interleukin 15 (IL15) expression in ESFs, and that ESF-derived IL15 influences the migration of natural killer and trophoblast cells. These data suggest that HAND2 and IL15 signaling played an important role in the evolution of implantation and regulation of gestation length.

Results

Genes that evolved endometrial expression in Eutherian mammals are enriched in immune functions

We previously used comparative transcriptomics to reconstruct the evolution of gene expression at the maternal-fetal interface during the origins of mammalian pregnancy (Lynch et al., 2015). Here, we assembled a collection of new and existing transcriptomes from the pregnant/gravid endometria of 15 Eutherian mammals, 3 Marsupials, 1 Monotreme (platypus), 2 birds, 5 lizards, and 1 amphibian (Figure 1A and Figure 1—source data 1). The complete dataset includes expression information for 21,750 genes from 27 species. Next, we transformed continuous transcript abundance estimates values into discrete character states such that genes with Transcripts Per Million (TPM) ≥ 2.0 were coded as expressed (state = 1), genes with TPM < 2.0 were coded as not expressed (state = 0), and genes without data in specific species were coded as missing (state = ?). We then used parsimony to reconstruct ancestral transcriptomes and trace the evolution of gene expression gains (0 → 1) and losses (1 → 0) in the endometrium (Figure 1—source data 2).

Figure 1 with 2 supplements see all
Recruitment of HAND2-mediated anti-estrogenic signaling in the Eutherian endometrium.

(A) Evolution of HAND2 expression at the maternal-fetal interface. Amniotes phylogeny with horizontal branch lengths drawn proportional to the number of gene expression changes inferred by parsimony (most parsimonious reconstruction). Circles indicate HAND2 expression in extant species and ancestral reconstructions. Black, expressed (state = 1). White, not expressed (state = 0). Inset legend shows the number of most gene expression changes from the root node to human (+ = gene expression gained; - = gene expression lost). Numbers to the right indicate HAND2 expression in TPM for each respective species. (B) WordCloud of biological pathways (green), human disease phenotypes (pink), and biological process gene ontology terms (blue) enriched among 149 unambiguously recruited genes in the Eutherian stem-lineage. Term size is shown scaled to -log10 p-value (see inset scale). (C) Cartoon model of estrogen signaling and HAND2-mediated anti-estrogenic signaling in the endometrium. The estrogen-mediated signaling network is suppressed by progesterone through the activation of HAND2 and antagonists of canonical WNT/β-catenin-mediated signaling pathways such as DKK1. In the proliferative phase of the reproductive cycle, estrogen acts through ESR1 in stromal cells to increase the production of fibroblast growth factors (FGFs), which serve as paracrine signals leading to sustained proliferation of epithelial cells. Active estrogen signaling maintains epithelial expression of Mucin 1 (MUC1), a cell surface glycoprotein that acts as a barrier to implantation. During the receptive phase of the cycle, however, progesterone induces HAND2 and DKK1 expression in the endometrial stroma, inhibiting production of FGFs, suppressing epithelial proliferation and antagonizing estrogen-mediated expression of MUC1, thereby promoting uterine receptivity to implantation. DSC = decidual stromal cells, LE = luminal epithelium. (D) Gene expression time course through opossum pregnancy. Upper, schematic of gestation length in Monodelphis domestica in which the histotrophic phase lasts from day 1 to day 12, hatching occurs on day 12.5, the placental phase lasts from day 13 to day 14.5, and birth occurs on day 14.5. Lower, data shown as square root (SqRT) transformed TPM. The TPM = 2 expression cutoff is shown as a horizontal gray line. M. domestica RNA-Seq data from Lynch et al., 2015; Hansen et al., 2016Griffith et al., 2017; Griffith et al., 2019.

Figure 1—source data 1

Species and gene expression information.

https://cdn.elifesciences.org/articles/61257/elife-61257-fig1-data1-v2.xlsx
Figure 1—source data 2

Binary encoded endometrial gene expression dataset.

https://cdn.elifesciences.org/articles/61257/elife-61257-fig1-data2-v2.nex.txt
Figure 1—source data 3

Genes (HUGO gene names) that unambiguously evolved endometrial expression in the Eutherian stem-lineage (‘Recruited Genes’).

https://cdn.elifesciences.org/articles/61257/elife-61257-fig1-data3-v2.xlsx
Figure 1—source data 4

Top 100 pathways (Wikipathway, Reactome, KEGG) in which Eutherian recruited genes are enriched.

https://cdn.elifesciences.org/articles/61257/elife-61257-fig1-data4-v2.xlsx
Figure 1—source data 5

Top 100 human phenotype (disease) ontology terms in which Eutherian recruited genes are enriched.

https://cdn.elifesciences.org/articles/61257/elife-61257-fig1-data5-v2.xlsx
Figure 1—source data 6

Top 100 biological process gene ontology (GO) terms in which Eutherian recruited genes are enriched.

https://cdn.elifesciences.org/articles/61257/elife-61257-fig1-data6-v2.xlsx
Figure 1—source data 7

RNA-Seq data from opossum endometrial samples.

Gene expression in TPM. NP = non-pregnant; d7, d12.5, d13, d13.5–14.5 = day 7, 12.5, 13, 13.5–14.5 of pregnancy, respectively; N2_9mo, N3_10mo = non-pregnant endometrium 9 and 10 months after pregnancy, respectively.

https://cdn.elifesciences.org/articles/61257/elife-61257-fig1-data7-v2.xlsx
Figure 1—source data 8

Database of genes implicated in preterm birth.

https://cdn.elifesciences.org/articles/61257/elife-61257-fig1-data8-v2.gmt.txt

We identified 958 genes that most parsimoniously evolved endometrial expression in the Eutherian stem-lineage, including 149 that unambiguously evolved endometrial expression (Figure 1A and Figure 1—source data 3). These 149 genes were significantly enriched in pathways related to the immune system (Figure 1B and Figure 1—source data 46), although only two pathways were enriched at False Discovery Rate (FDR) ≤ 0.10, namely, ‘Cytokine Signaling in Immune System’ (hypergeometric p = 1.97×10−5, FDR = 0.054) and ‘Signaling by Interleukins’ (hypergeometric p = 4.09×10−5, FDR = 0.067). Unambiguously recruited genes were also enriched in numerous human phenotype ontology terms but only two, ‘Immune System Diseases’ (hypergeometric p = 3.15×10−8, FDR = 2.52×10−4) and ‘Preterm Birth’ (hypergeometric p = 4.04×10−4, FDR = 8.07×10−4), were enriched at FDR ≤ 0.10. In contrast, these genes were enriched in numerous biological process gene ontology (GO) terms at FDR ≤ 0.10, nearly all of which were related to regulation of immune system, including ‘Leukocyte Migration’ (hypergeometric p = 1.17×10−7, FDR = 1.29×10−3), ‘Inflammatory Response’ (hypergeometric p = 8.07×10−7, FDR = 2.21×10−3), and ‘Cytokine-mediated Signaling Pathway’ (hypergeometric p = 2.18×10−5, FDR = 0.013).

Recruitment of HAND2 and anti-estrogenic signaling in Eutherians

Among the genes that unambiguously evolved endometrial expression in the Eutherian stem-lineage was the basic helix-loop-helix family transcription factor Heart- and neural crest derivatives-expressed protein 2 (HAND2). HAND2 plays an essential role in mediating the anti-estrogenic action of progesterone and the establishment of uterine receptivity to implantation (Figure 1C; Huyen and Bany, 2011; Li et al., 2011; Fukuda et al., 2015; Mestre-Citrinovitz et al., 2015), suggesting that the silencing of estrogen signaling during the window of implantation is a derived trait in Eutherian mammals. Notably, this silencing is not observed in the pregnant endometrium of Marsupials such as the brush-tailed possum (Trichosurus vulpecula) (Young and McDonald, 1982; Curlewis and Stone, 1987) and tammar wallaby (Macropus eugenii) (Renfree and Blanden, 2000).

To investigate further, we used the short-tailed opossum (Monodelphis domestica) as a model of pregnancy in Marsupials. M. domestica lacks implantation and thus is a good representative of pregnancy in the Therian common ancestor, in contrast to other Marsupials, such as the tammar wallaby, which have derived traits such as delayed ovulation, independently evolved maternal recognition of pregnancy and expression of HAND2 at low levels during gravidity (Figure 1A and Figure 1—figure supplement 1—source data 1, Figure 1—figure supplement 1). Using existing RNA-Seq data from short-tailed opossum endometria, we analyzed a time course consisting of day 7 (during the histotrophic phase), day 12.5 (just after hatching and during the transition from the histotrophic to the placental phase), day 13 (early placental phase), day 13.5–14.5 (during the late placental to early parturition phase), and 9–10 month post-partum, as well as non-pregnant control (Figure 1D; Lynch et al., 2015; Hansen et al., 2016; Griffith et al., 2017; Griffith et al., 2019). We found that HAND2 was abundantly expressed in the non-pregnant endometrium and down-regulated throughout the histotrophic phase, reaching a low (TPM < 2) at 12.5d, and subsequently increasing in expression in the 13.5-14d samples near term. ESR1, FGF2, FGF9, FGF18 and several WNT genes that stimulate proliferation of the luminal epithelia were abundantly expressed (Figure 1D and Figure 1—source data 7), consistent with persistent estrogen signaling during pregnancy (Renfree and Blanden, 2000). Both HAND2 and ESR1 decrease during gestation (Figure 1D), suggesting that the inhibition of estrogen signaling by HAND2 seen in Eutherians does not occur in opossum endometrium – if it did, one would expect ESR1 expression to increase as HAND2 expression decreased. Similarly, HAND2 is down-regulated during pregnancy in the tammar wallaby (Figure 1—figure supplement 1—source data 1, Figure 1—figure supplement 1). Immunohistochemistry (IHC) on opossum endometrial sections from day 12.5 pregnant endometrium stained strongly for estrogen receptor alpha (ESR1; ERα) phosphorylated at serine 118, a mark of transcriptionally active ERα (Kato et al., 1995), as well as phosphorylated ERK1/2, and MUC1 (Figure 1—figure supplement 2), which is also consistent with active estrogen signaling.

HAND2 is expressed in endometrial stromal fibroblast lineage cells

To determine which cell types at the human maternal-fetal interface express HAND2, we used previously generated single-cell RNA-Seq (scRNA-Seq) data from the first trimester decidua (Vento-Tormo et al., 2018). HAND2 expression was almost entirely restricted to cell populations in the endometrial stromal fibroblast lineage (see Materials and methods for cell type naming convention), with particularly high expression in ESF2s and DSCs (Figure 2A). Interestingly, while it is generally thought that ESFs are not present in the pregnant endometrium, previous studies have demonstrated that ESFs retain a presence in the endometrium from the first trimester all the way to term (Richards et al., 1995; Suryawanshi et al., 2018; Muñoz-Fernández et al., 2019; Sakabe et al., 2020).

Expression of HAND2 at the maternal-fetal interface.

(A) UMAP clustering of scRNA-Seq data from human first trimester maternal-fetal interface. Left, clusters colored according to inferred cell type. The ESF1, ESF2, and DSC clusters are highlighted. Right, cells within clusters are colored according to HAND2 expression level. scRNA-Seq data from Vento-Tormo et al., 2018. (B) HAND2 protein expression in human pregnant decidua, with strong staining and localization in the nuclei of endometrial stromal cells. Image credit: Human Protein Atlas. (C) Regulatory landscape of the HAND2 locus. Chromatin loops inferred from H3K27ac HiChIP, regions of open chromatin inferred from FAIRE-, DNaseI, and ATAC-Seq, and the locations of histone modifications and transcription factor ChIP-Seq peaks are shown. The location of SNPs associated with gestation length / birth weight is also shown (highlighted in gray). Note that the HAND2 promoter forms a long-range loop to a region marked by H3K27ac and bound by PGR, NR2F2 (COUP-TFII), GATA2, FOSL2, and FOXO1. (D) HAND2 expression is up-regulated by in vitro decidualization of ESFs into DSC by cAMP/progesterone treatment, and down-regulated by siRNA-mediated knockdown of PGR and GATA2, but not NR2F2 or FOXO1. n = 3 per transcription factor knockdown. (E) Relative expression of HAND2 in the proliferative (n = 6), early (n = 4), middle (n = 9), and late (n = 8) secretory phases of the menstrual cycle. Note that outliers are excluded from the figure but not the regression; 95% CI is shown in gray. Gene expression data from Talbi et al., 2006. (F) Relative expression of HAND2 in the basal plate from mid-gestation to term (14–40 weeks, n = 36); 95% CI is shown in gray. Inset, percent of up- (Up) and down-regulated (Down) genes between weeks 14–19 and 37–40 of pregnancy (FDR ≤ 0.10). Gene expression data from Winn et al., 2007. (G) HAND2 expression is significantly down-regulated in the endometria of women with implantation failure (IF, n = 5) and recurrent spontaneous abortion (RSA, n = 5) compared to fertile controls (n = 5), but is not differentially expressed in ESFs or DSCs from women with preeclampsia (PE, n = 5) compared to healthy controls (n = 5). Gene expression data for RSA and IF from Lédée et al., 2011 and for PE from Garrido-Gomez et al., 2017.

© 2021, Human Protein Atlas. Figure 2B is adapted from the Human Protein Atlas (lower left part of top image cropped and rotated, image color auto adjusted). Published under a CC BY SA 3.0 unported license.

HAND2 protein was localized to nuclei in ESF lineage cells in human pregnant decidua (Figure 2B) from Human Protein Atlas IHC data (Uhlén et al., 2015). We also used existing functional genomics data to explore the regulatory status of the HAND2 locus (see Materials and methods for references). Consistent with active expression, the HAND2 locus in human DSCs is marked by histone modifications that typify enhancers (H3K27ac) and promoters (H3K4me3) and is located in a region of open chromatin as assessed by ATAC-, DNaseI- and FAIRE-Seq. Additionally, it is bound by transcription factors that establish endometrial stromal cell type identity and mediate decidualization, including the progesterone receptor (PGR), NR2F2 (COUP-TFII), GATA2, FOSL2, FOXO1, as well as polymerase II (Figure 2C). The HAND2 promoter loops to several distal enhancers, as assessed by H3K27ac HiChIP data generated from a normal hTERT-immortalized endometrial cell line (E6E7hTERT), including a region bound by PGR, NR2F2, GATA2, FOSL2, and FOXO1, that also contains SNPs associated with gestation length in recent GWAS (Warrington et al., 2019; Sakabe et al., 2020; Figure 2C). HAND2 was significantly upregulated by decidualization of human ESFs into DSCs by cAMP/progesterone treatment (Log2FC = 1.28, p = 2.62×10−26, FDR = 1.16×10−24), and significantly downregulated by siRNAs targeting PGR (Log2FC = −0.90, p = 7.05×10−15, FDR = 2.03×10−13) and GATA2 (Log2FC = −2.73, p = 0.01, FDR = 0.19) (Figure 2D). In contrast, siRNA-mediated knockdown of neither NR2F2 (Log2FC = −0.91, p = 0.05, FDR = 1.0) nor FOXO1 (Log2FC = 0.08, p = 0.49, FDR = 0.74) significantly altered HAND2 expression (Figure 2D and see Materials and methods for references).

Differential HAND2 expression throughout the menstrual cycle and pregnancy

Our observation that HAND2 is progesterone responsive suggests it may be differentially expressed throughout the menstrual cycle and pregnancy. To explore this possibility, we utilized previously published gene expression datasets generated from the endometrium across the menstrual cycle (Talbi et al., 2006) and from the basal plate from mid-gestation to term (Winn et al., 2007). HAND2 expression tended to increase from proliferative through the early and middle secretory phases, reaching a peak in the late secretory phase of the menstrual cycle (Figure 2E). In stark contrast, HAND2 decreases in expression from the first trimester to term (Figure 2F). For comparison, 9% of genes were down-regulated between weeks 14–19 and 37–40 of pregnancy (FDR ≤ 0.10). We also used previously published gene expression datasets to explore if HAND2 was associated with disorders of pregnancy (Lédée et al., 2011; Garrido-Gomez et al., 2017). Although sample sizes of these datasets are small, and the intrinsic temporo-spatial heterogeneity of the endometrium remains a potential confounding factor, we found that HAND2 was dysregulated in the endometria of women with implantation failure (IF) and recurrent spontaneous abortion (RSA), while it was not differentially expressed in ESFs or DSCs from women with preeclampsia (PE), compared to controls (Figure 2G).

HAND2 regulates a distinct set of target genes

HAND2 expression has previously been shown to play a role in orchestrating the transcriptional response to progesterone during decidualization in human and mouse DSCs (Huyen and Bany, 2011; Li et al., 2011; McConaha et al., 2011; Shindoh et al., 2014; Murata et al., 2020). However, whether HAND2 has functions in other endometrial stromal lineage cells such as ESFs, which persist in the pregnant endometrium till term (Richards et al., 1995; Suryawanshi et al., 2018; Muñoz-Fernández et al., 2019; Sakabe et al., 2020) but have received less attention than DSCs during pregnancy, is unknown. Therefore, we used siRNA to knockdown HAND2 expression in human hTERT-immortalized ESFs (T-HESC) and assayed global gene expression changes by RNA-Seq 48 hr after knockdown. We found that HAND2 was knocked down ~78% (p = 7.79×10−3) by siRNA treatment (Figure 3A), which dysregulated the expression of 553 transcripts (489 genes) at FDR ≤ 0.10 (Figure 3A and Figure 3—source data 1). Genes dysregulated by HAND2 knockdown were enriched in several pathways and human phenotype ontologies relevant to endometrial stromal cells and pregnancy in general (Figure 3B and Figure 3—source data 2, 3).

HAND2 regulates a distinct set of target genes, including IL15.

(A) Volcano plot of gene expression upon HAND2 knockdown. Only genes that are significantly differentially expressed (DE) with FDR ≤ 0.10 are colored. Genes with ≥ 1 fold changes in expression are shown in pink (up-regulated), green (down-regulated) or gray (not differentially expressed). X-axis shows log2 fold change, Y-axis shows Wald statistic p-value, horizontal dashed line indicates FDR = 0.10. Full list of DE genes can be found in Figure 3—source data 1. (B) Pathways (purple) and human phenotype ontologies (pink) in which genes dysregulated upon HAND2 knockdown are enriched. We used a hypergeometric p-value to determine enriched pathway and disease ontology terms. The Benjamini-Hochburg Adjusted p-value (FDR), Odds Ratio, Combined Score, and Genes associated with each term can be found in Figure 3—source data 2 and Figure 3—source data 3.

Figure 3—source data 1

Genes differentially expressed (DE) upon HAND2 knockdown.

RNA-Seq reads were mapped to hg38 using HISAT2, transcripts were assembled and quantified using StringTie, and DE genes were identified using DESeq2. The reference file for StringTie guided assembly was wgEncodeGencodeBasicV33. Columns indicate: Ensembl stable transcript IDs (A), HUGO gene names (B), Base mean expression level (C), Log2 fold change upon HAND2 knockdown (D), Standard Error of Log2 fold change (E), Walds-Statistic for differential expression (F), p-value of the Walds-Statitic (G), and Benjamini-Hochberg corrected p-values (H).

https://cdn.elifesciences.org/articles/61257/elife-61257-fig3-data1-v2.xlsx
Figure 3—source data 2

Pathways (Wikipathway 2019) enriched among genes differentially expressed by HAND2 knockdown.

https://cdn.elifesciences.org/articles/61257/elife-61257-fig3-data2-v2.xlsx
Figure 3—source data 3

Human phenotype (disease) ontology terms enriched among genes differentially expressed by HAND2 knockdown.

https://cdn.elifesciences.org/articles/61257/elife-61257-fig3-data3-v2.xlsx

Enriched pathways play a role in decidualization (e.g. ‘Wnt Signaling’, ‘BMP Signaling’, ‘ErbB Signaling’, ‘TGF-beta Receptor Signaling’ and ‘BMP2-WNT4-FOXO1 Pathway in Human Primary Endometrial Stromal Cell Differentiation’), as well as in placental bed development disorders and preeclampsia, the induction of pro-inflammatory factors via nuclear factor-κB (NFκB), mediation of maternal immunotolerance to the fetal allograft, circadian rhythm in association with implantation and parturition, and the decidual inflammation, senescence, and parturition. Selected pathways and associated references are listed in Table 1.

Table 1
Genes dysregulated by HAND2 knockdown are enriched in pathways relevant to endometrial stromal cells and pregnancy in general.
Enriched pathwayRoles in ESFs and pregnancyReferences
Wnt SignalingDecidualizationPeng et al., 2008; Hayashi et al., 2009; Sonderegger et al., 2010; Franco et al., 2011; Wang et al., 2013
BMP SignalingDecidualizationYing and Zhao, 2000; Lee et al., 2007; Li et al., 2007; Wetendorf and DeMayo, 2012
ErbB SignalingDecidualizationLim et al., 1997; Klonisch et al., 2001; Large et al., 2014
TGF-beta Receptor SignalingDecidualizationJones et al., 2006; Li, 2014; Ni and Li, 2017
BMP2-WNT4-FOXO1 Pathway in Human Primary Endometrial Stromal Cell DifferentiationDecidualizationGellersen and Brosens, 2003; Buzzio et al., 2006; Lee et al., 2007; Li et al., 2007; Brayer et al., 2011; Lynch et al., 2009; Kajihara et al., 2013
AGE/RAGE PathwayPlacental bed development disorders
Preeclampsia
Induction of pro-inflammatory factors via nuclear factor-κB (NFκB)
Chekir et al., 2006; Lappas et al., 2007; Oliver et al., 2011; Guedes-Martins et al., 2013
Aryl Hydrocarbon Receptor PathwayMediation of maternal immunotolerance to fetal allograftMunn et al., 1998; Abbott et al., 1999; Funeshima et al., 2005; Hao et al., 2013
Circadian Rhythm Related GenesImplantation and parturitionRoizen et al., 2007; Olcese, 2012; Olcese et al., 2013; Greenhill, 2014; Menon et al., 2016
RAC1/PAK1/p38/MMP2 PathwayDecidual inflammation, senescence and parturitionMenon et al., 2016

Enriched human phenotype ontology terms were related to complications of pregnancy, including ‘Premature Rupture of Membranes’, ‘Premature Birth’, ‘Toxemia of Pregnancy’ (preeclampsia) and ‘Abnormal Delivery’. We also observed that several genes in the NFκB pathway, such as MYD88, CHUK, IκBKE, NFκBIE, and RTKN2 were differentially expressed; NFκB signaling has been associated with the molecular etiology of preterm birth (Allport et al., 2001; Lindström and Bennett, 2005).

HAND2 regulates IL15 expression in endometrial stromal fibroblast lineage cells

Among the genes dysregulated by HAND2 knockdown in ESFs was IL15 (Log2FC = 7.98, p = 7.91×10−8, FDR = 1.49×10−5), a pleiotropic cytokine previously shown to be expressed in the endometrium and decidua (Figure 3A and Table 2; Kitaya et al., 2000; Okada et al., 2000; Dunn et al., 2002; Okada et al., 2004; Godbole and Modi, 2010). IL15 was robustly expressed at the first trimester maternal-fetal interface in stromal fibroblast lineage cells (Figure 4A), and there was a general correlation between HAND2 and IL15 expression in single cells (Figure 4A inset) (Vento-Tormo et al., 2018). IL15 protein localized to cytoplasm in ESF lineage cells in human pregnant decidua (Figure 4B) in Human Protein Atlas IHC data. The IL15 promoter loops to several distal sites in H3K27ac HiChIP data from E6E7hTERT endometrial cells including to regions bound by PGR, NR2F2, GATA2, FOSL2, FOXO1, and SRC2, an intrinsic histone acetyltransferase that is a transcriptional co-factor of ligand-dependent hormone receptors (Figure 4C; see Materials and methods for references). The IL15 promoter also loops to a putative enhancer in its first intron that contains a PGR-binding site and SNPs marginally associated with a maternal effect on offspring birth weight (rs190663174, p = 6×10−4) by GWAS (Warrington et al., 2019). IL15 was significantly upregulated by in vitro decidualization of human ESFs into DSCs by cAMP/progesterone treatment (Log2FC = 2.15, p = 2.58×10−33, FDR = 1.59×10−31), and significantly downregulated by siRNAs targeting PGR (Log2FC = −1.24, p = 6.23×10−15, FDR = 1.80×10−13) and GATA2 (Log2FC = −2.08, p = 4.16×10−3, FDR = 0.14) (Figure 4D), but not NR2F2 (Log2FC = 0.19, p = 0.38, FDR = 0.93) or FOXO1 (Log2FC = 0.29, p = 0.04, FDR = 0.22) (Figure 4D; see Materials and methods for references). Although HAND2 binding data is not available for human stromal fibroblast lineage cells, several HAND2 binding motifs (≥0.85 motif match) are located within enhancers that loop to the IL15 promoter.

Expression of IL15 at the maternal-fetal interface.

(A) UMAP clustering of scRNA-Seq data from human first trimester maternal-fetal interface. Left, clusters colored according to inferred cell type. The ESF1, ESF2, and DSC clusters are highlighted. Inset, per cell expression of HAND2 and IL15 in ESF1s, ESF2s, and DSCs. Right, cells within clusters are colored according to IL15 expression level. scRNA-Seq data from Vento-Tormo et al., 2018. (B) IL15 protein expression in human pregnant decidua, with strong cytoplasmic staining in endometrial stromal cells. Image credit: Human Protein Atlas. (C) Regulatory landscape of the IL15 locus. Chromatin loops inferred from H3K27ac HiChIP, regions of open chromatin inferred from FAIRE-, DNaseI, and ATAC-Seq, and the locations of histone modifications and transcription factor ChIP-Seq peaks are shown. The location of an SNP associated with gestation length / birth weight is also shown (highlighted in gray). Note that the IL15 promoter forms many long-range loops to regions marked by H3K27ac and bound by PGR, NR2F2 (COUP-TFII), GATA2, FOSL2, FOXO1, and SRC2. (D) IL15 expression is upregulated by in vitro decidualization of ESFs into DSC by cAMP/progesterone treatment, and downregulated by siRNA-mediated knockdown of PGR and GATA2 but not NR2F2 or FOXO1. n = 3 per transcription factor knockdown. (E) Relative expression of IL15 in the proliferative (n = 6), early (n = 4), middle (n = 9), and late (n = 8) secretory phases of the menstrual cycle. Note that outliers are excluded from the figure but not the regression; 95% CI is shown in gray. Gene expression data from Talbi et al., 2006. (F) Relative expression of IL15 in the basal plate from mid-gestation to term (14–40 weeks, n = 36); 95% CI is shown in gray. Inset, percent of up- (Up) and downregulated (Down) genes between weeks 14–19 and 37–40 of pregnancy (FDR ≤ 0.10). Gene expression data from Winn et al., 2007. (G) IL15 expression is significantly upregulated in DSCs from women with preeclampsia (PE, n = 5) compared to healthy controls (n = 5), while it is only marginally upregulated in ESFs from the same patient group. It is also marginally downregulated in the endometria of women with implantation failure (IF, n = 5) and it is not differentially expressed in the endometria of women with recurrent spontaneous abortion (RSA, n = 5) compared to fertile controls (n = 5). Gene expression data for RSA and IF from Lédée et al., 2011 and for PE from Garrido-Gomez et al., 2017.

© 2021, Human Protein Atlas. Figure 4B is adapted from the Human Protein Atlas (top image cropped, image color auto adjusted). Published under a CC BY SA 3.0 unported license.

Table 2
Exemplar genes differentially expressed in ESFs upon siRNA-mediated HAND2 knockdown.

Mean, base mean expression level. FC, log2 fold change. SE, standard error in log2 fold change. WS, Wald statistic. p-Value, Wald test p-value. Adj-p, Benjamini-Hochberg (BH) adjusted p-value. Function, function of gene inferred from Wikipathway 2019 human annotation. Association with preterm birth (PTB, HP:0001622) and premature rupture of membranes (PROM, HP:0001788) inferred from human phenotype ontology annotation*.

GeneMeanFCSEWSp-ValueAdj-pFunction
ARNT244.471.200.284.301.73E-051.89E-03AHR signaling / Circadian rhythm
ARNTL42.52−2.950.80−3.672.46E-041.79E-02AHR signaling / Circadian rhythm
IL1563.317.981.495.377.91E-081.49E-05Cell migration
BMP458.10−8.341.25−6.662.75E-118.28E-09Decidualization
GSK3B69.23−5.531.48−3.731.94E-041.49E-02Decidualization
HAND2136.06−1.630.18−8.859.10E-197.64E-16Knocked down gene
CHUK765.770.440.143.141.67E-037.94E-02NFκB pathway
IκBKE9.91−5.411.65−3.271.06E-035.72E-02NFκB pathway
MYD8895.02−0.930.26−3.553.88E-042.59E-02NFκB pathway
NFκBIE106.63−0.780.25−3.082.10E-039.53E-02NFκB pathway
RTKN250.648.021.336.021.75E-094.05E-07NFκB pathway
CRKL1278.85−0.310.09−3.319.21E-045.10E-02PTB
EOGT233.65−2.770.80−3.455.63E-043.38E-02PTB
LMNA773.246.971.574.448.92E-061.06E-03PTB; PROM
PEX11B181.3110.051.129.002.28E-192.06E-16PTB
SERPINH11654.90−6.011.31−4.594.40E-065.61E-04PROM
SLC17A5826.280.760.135.816.34E-091.40E-06PTB
ZMPSTE242140.67−0.190.05−4.104.10E-053.92E-03PTB; PROM
  1. *Extended list of genes associated with the pathologies of pregnancy and their expression levels can be found in Table 2—source data 1 used to generate Figures 2G and 4G. (GSE26787 = recurrent spontaneous abortion [RSA] and implantation failure [IF]; GSE91077 = ESFs and DSCs from women with preeclampsia [PE]).

Table 2—source data 1

Differential expression of genes in RSA, IF and PE (in ESFs and DSCs) in relation to genes differentially expressed upon HAND2 knockdown in ESFs.

https://cdn.elifesciences.org/articles/61257/elife-61257-table2-data1-v2.xlsx

Differential IL15 expression throughout the menstrual cycle and pregnancy

Our observations that HAND2 is progesterone responsive and differentially expressed throughout the menstrual cycle and pregnancy suggest that IL15, which is controlled by HAND2 as well as cAMP/progesterone/PGR/GATA2, may be similarly regulated. Indeed, like HAND2, we found that IL15 expression increased as the menstrual cycle progressed, peaking in the middle-late secretory phases (Figure 4E; Talbi et al., 2006) and decreased in expression from the first trimester to term (Figure 4F; Winn et al., 2007). IL15 expression was also dysregulated in the endometria of women with implantation failure but not recurrent spontaneous abortion, compared to fertile controls (Figure 4G; Lédée et al., 2011). In women with preeclampsia, IL15 was not dysregulated in ESFs, but it was expressed significantly higher in DSCs, compared to controls (Figure 4G; Garrido-Gomez et al., 2017). Thus, like HAND2, IL15 is differentially expressed throughout the menstrual cycle and pregnancy, and in the endometria of women with implantation failure.

ESF-derived IL15 promotes NK and trophoblast migration

Endometrial stromal cells promote the migration of uterine natural killer (uNK) (Chen et al., 2011) and trophoblast cells (Graham and Lala, 1991; Paiva et al., 2009; Zhu et al., 2009; Godbole et al., 2011). IL15, in particular, stimulates the migration of uNK cells (Allavena et al., 1997; Verma et al., 2000; Ashkar et al., 2003; Barber and Pollard, 2003; Kitaya et al., 2005) and the human choriocarcinoma cell line, JEG-3 (Zygmunt et al., 1998). Therefore, we tested whether ESF-derived IL15 influenced the migration of primary human NK cells and immortalized first trimester extravillous trophoblasts (HTR-8/SVneo) in trans-well migration assays (Figure 5A). We found that ESF media supplemented with recombinant human IL15 (rhIL15) was sufficient to stimulate the migration of NK and HTR-8/SVneo cells to the lower chamber of trans-wells, compared to non-supplemented media (Figure 5B,C and Figure 5—source data 1, 2). Conditioned media from ESFs with siRNA-mediated HAND2 knockdown increased migration of both NK and HTR-8/SVneo compared to negative control (i.e. non-targeting siRNA; Figure 5B,C). Conditioned media from ESFs with siRNA-mediated IL15 knockdown reduced migration of both NK and HTR-8/SVneo cells compared to negative control (Figure 5B,C). Similarly, ESF conditioned media supplemented with anti-IL15 antibody reduced cell migration compared to media supplemented with control IgG antibody (Figure 5B,C).

ESF-derived IL15 promotes NK and trophoblast migration in trans-well assays.

(A) Cartoon of trans-well migration assay comparisons. Cells that migrated to the lower chamber were quantified using the CellTiter-Glo luminescent cell viability assay after 8 hr. (B) Primary natural killer (NK) cells. Raw luminescence data (RLU) from cells in the lower chamber is shown in the upper panel, mean difference (effect size) in experiment minus control luminescence values are shown as dots with the 95% confidence interval indicated by vertical bars in the lower panel; distribution estimated from 5000 bootstrap replicates. The mean difference between Media and media supplemented with recombinant human IL15 (Media+rhIL15) is 0.432 [95.0% CI: 0.376–0.492]; p = 0.00. The mean difference between ESFs transiently transfected with non-targeting siRNA (NT siRNA) and HAND2-specific siRNAs (siHAND2) is 0.847 [95.0% CI: 0.774–0.936]; p = 0.00. The mean difference between ESFs transiently transfected with NT siRNA and IL15-specific siRNAs (siIL15) is −0.223 [95.0% CI: −0.256 – −0.192]; p = 0.00. The mean difference between ESF media neutralized with a non-specific antibody (IgG) or IL15-specific antibody (abIL15) is −0.106 [95.0% CI: −0.147 – −0.067]; p = 0.00. n = 12. (C) Extravillous trophoblast cell line HTR-8/SVneo. Raw luminescence data (RLU) from cells in the lower chamber is shown in the upper panel, mean difference (effect size) in experiment minus control luminescence values are shown as dots with the 95% confidence interval indicated by vertical bars in the lower panel; distribution estimated from 5000 bootstrap replicates. The mean difference between Media and Media+rhIL15 is 0.482 [95.0% CI: 0.193–0.701]; p = 0.002. The mean difference between ESFs transiently transfected with NT siRNA and siHAND2 is 0.463 [95.0% CI: 0.291–0.559]; p = 0.00. The mean difference between ESFs transiently transfected with NT siRNA and siIL15 is −0.598 [95.0% CI: −0.698–0.490]; p = 0.00. The mean difference between ESF media neutralized with IgG or abIL15 is −0.267 [95.0% CI: −0.442 – −0.151]; p = 0.0004. n = 12. (D) Model of HAND2 functions in the endometrium. During the proliferative phase HAND2 inhibits IL15, and thus the migration of uNK and trophoblast cells. In the receptive phase, HAND2 activates IL15, which promotes migration of uNK and trophoblast cells. In the receptive phase and early pregnancy (EP), HAND2 suppresses estrogen signaling by down-regulating FGFs and directly binding and inhibiting the ligand-dependent transcriptional activation function of ESR1. During late pregnancy/term (LP/Term), reduced HAND2 expression mitigates its anti-estrogenic functions. Parturition signal unknown (???). ESF = endometrial stromal fibroblasts (proliferative phase), DSC = decidual stromal cells (receptive phase), LE = luminal epithelium.

Figure 5—source data 1

Raw and log transformed luminescence data for NK trans-well migration assays.

https://cdn.elifesciences.org/articles/61257/elife-61257-fig5-data1-v2.xlsx
Figure 5—source data 2

Raw and log transformed luminescence data for HTR-8 trans-well migration assays.

https://cdn.elifesciences.org/articles/61257/elife-61257-fig5-data2-v2.xlsx

Discussion

Eutherian mammals evolved a suite of traits that support pregnancy, including an interrupted estrous cycle allowing for prolonged gestation lengths, maternal-fetal communication, implantation, maternal immunotolerance and recognition of pregnancy, and thus are uniquely afflicted by disorders of these processes. When searching for clues as to how variation in normal physiological functions can lead to dysfunction and disease, deeper understanding of the evolutionary and developmental histories of organ and tissues has the potential to provide novel insights. Here, we used evolutionary transcriptomics to identify genes that evolved to be expressed on the maternal side (endometrium) of the maternal-fetal interface during the origins of pregnancy in Eutherians, and hence may also contribute to pregnancy complications such as infertility, recurrent spontaneous abortion, and preterm birth.

Among the genes recruited into endometrial expression in Eutherians, we identified HAND2, a pleiotropic transcription factor that plays an essential role in suppressing estrogen signaling at the time of uterine receptivity to blastocyst embedding, through its down-regulation of pro-estrogenic genes and by directly inhibiting the transcriptional activities of the estrogen receptor (Huyen and Bany, 2011; Li et al., 2011; Shindoh et al., 2014; Fukuda et al., 2015; Mestre-Citrinovitz et al., 2015; Murata et al., 2019). Consistent with these functions, we found evidence of estrogen activity in the endometrium of pregnant opossum. Earlier research detected similar activity in the gravid oviduct of birds and reptiles (Means et al., 1975; Kato et al., 1992; Girling, 2002; González-Morán, 2015). These data indicate that suppression of estrogen signaling during the window of uterine receptivity to implantation is an evolutionary innovation of Eutherian mammals, which involved the recruitment of HAND2 and its anti-estrogenic functions into endometrial expression.

The roles of HAND2 in DSCs and implantation are well-understood (Huyen and Bany, 2011; Li et al., 2011; Shindoh et al., 2014; Fukuda et al., 2015; Mestre-Citrinovitz et al., 2015; Murata et al., 2019; Šućurović et al., 2020). In contrast, the function(s) of HAND2 at other stages of pregnancy and in ESFs remain relatively unexplored, despite the persistence of ESFs in the pregnant endometrium until term (Richards et al., 1995; Suryawanshi et al., 2018; Muñoz-Fernández et al., 2019; Sakabe et al., 2020). HAND2, for example, plays a role in orchestrating the transcriptional response to progesterone during decidualization (Huyen and Bany, 2011; Li et al., 2011; McConaha et al., 2011; Shindoh et al., 2014; Murata et al., 2020). Similarly, Hand2 knockout mice are infertile because of persistent estrogen signaling during the window of implantation, leading to implantation failure (Li et al., 2011; Jones et al., 2013). The functions of Hand2 at other stages of pregnancy could unfortunately not be explored in these Hand2 knockout mice as the conditional targeting strategy knocks out Hand2 in Pgr-expressing cells. Hand2 expression is thereby eliminated upon initiation of Pgr expression in the uterus, coincident with the onset of sexual maturity.

We knocked down HAND2 in ESFs and found that downstream dysregulated genes were enriched for human phenotype ontologies related to disorders of pregnancy, including ‘Premature Rupture of Membranes’, ‘Premature Birth’, and ‘Abnormal Delivery’, suggesting that HAND2 has functions throughout pregnancy and in parturition. Indeed, we discovered that SNPs recently implicated in the regulation of gestation length and birth weight by GWAS (Warrington et al., 2019; Sakabe et al., 2020) make long-range interactions to the HAND2 promoter. Also of note, HAND2 expression is significantly higher in placental villous samples from idiopathic spontaneous preterm birth (isPTB) compared to term controls (Brockway et al., 2019). However, this difference may be related to gestational age rather than the etiology of PTB (Eidem et al., 2016).

Additionally, analyzing previously published datasets we noticed that HAND2 expression decreases throughout gestation. Unlike the majority of Eutherians, where parturition closely follows the significant drop in progesterone concentrations in maternal peripheral blood, this is not the case for humans and other Old World primates (Ratajczak et al., 2010), where progesterone levels keep rising throughout gestation, reaching maximum at birth. These observations, combined with the central role of HAND2 in mediating the anti-estrogenic actions of progesterone, suggest decreased HAND2 at the end of pregnancy may contribute to the estrogen-dominant uterine environment at the onset of labor (Pinto et al., 1966; Pepe and Albrecht, 1995; Mesiano et al., 2002; Smith et al., 2009a; Ratajczak et al., 2010; Welsh et al., 2012), despite high systemic progesterone. Low HAND2 at the end of pregnancy in humans is therefore most likely not directly related to progesterone concentrations, suggesting that an unidentified inhibitory signal reduces endometrial HAND2 expression. While taken collectively these data indicate a role for HAND2 in pre/term birth, a direct mechanistic link between HAND2 expression and the timing of parturition remains to be demonstrated.

One of the genes dysregulated by HAND2 knockdown was the multifunctional cytokine IL15, which plays important roles in innate and adaptive immunity. In the context of pregnancy, it is important for the recruitment of uterine natural killer (uNK) cells to the endometrium (Kitaya et al., 2000; Verma et al., 2000; Ashkar et al., 2003; Barber and Pollard, 2003; Kitaya et al., 2005; Laskarin et al., 2006). The roles of uNK cells in the remodeling of uterine spiral arteries and regulating trophoblast invasion are well known (Zygmunt et al., 1998; Hanna et al., 2006; Smith et al., 2009b; Burke et al., 2010; Hazan et al., 2010; Lash et al., 2010; Bany et al., 2012; Robson et al., 2012; Zhang et al., 2013; Lima et al., 2014; Fraser et al., 2015; Felker and Croy, 2016; Renaud et al., 2017). Endometrial stromal cell-derived IL15 is also necessary for the selective targeting and clearance of senescent endometrial stromal cells from the implantation site by uNK cells, which is essential for endometrial rejuvenation and remodeling at embryo implantation (Brighton et al., 2017). Dysregulation of uNK cell-mediated clearance of these senescent cells has also been implicated in recurrent pregnancy loss (Lucas et al., 2020). We found that, like HAND2, IL15 decreases throughout gestation and both genes increase in expression as the menstrual cycle progresses.

Unexpectedly, however, while previous studies showed that HAND2 induces IL15 in DSCs (Shindoh et al., 2014; Murata et al., 2020), we discovered that HAND2 inhibited IL15 expression in ESFs, indicating a switch in regulatory activity sometime during early menstrual cycle. These data suggest that HAND2 regulates the appropriate timing of endometrial IL15 expression during the menstrual cycle and throughout pregnancy, and thus the appropriate timing of uNK cell recruitment, trophoblast migration and the clearance of senescent endometrial stromal cells from the implantation site (Figure 5D). While the signals that initiate parturition in humans and other Catarrhine primates are unknown, it has been proposed that a ‘decidual clock’ may regulate the successful establishment and maintenance of pregnancy, such that severe decidualization defects lead to infertility, moderate defects lead to recurrent pregnancy loss/recurrent spontaneous abortion, and mild defects lead to preterm birth (Norwitz et al., 2015). Our results suggest that part of this clock may be the transition of ESFs that persist in the endometrium during pregnancy to DSCs, and/or DSCs into senescent DSCs (snDSCs) which no longer express IL15 (Lucas et al., 2020), leading to a shift in the balance of tolerizing immune cells at the maternal-fetal interface and thus withdrawal of maternal immunotolerance of the fetal allograft. Thus, our observation of low HAND2 and IL15 near term may reflect a reduction of anti-inflammatory DSCs (high HAND2 and IL15) and an accumulation of pro-inflammatory snDSCs (low HAND2 and IL15) at the maternal-fetal interface. Additional work is needed to elucidate the mechanisms that underlie change in HAND2-IL15 dynamics and determine whether these progressive cell state changes occur during gestation.

Decreased HAND2 and IL15 expression near term and their influence on immune cells at the maternal-fetal interface may also play a role in parturition. Pre/term labor is known to be associated with elevated inflammation and an influx of immune cells into utero-placental tissues (Thomson et al., 1999; Young et al., 2002; Osman et al., 2003; Gomez-Lopez et al., 2010; Rinaldi et al., 2011; Rinaldi et al., 2015; Hamilton et al., 2012; Shynlova et al., 2013; Bartmann et al., 2014; Menon et al., 2016; Peters et al., 2016; Wilson and Mesiano, 2020). uNK cells are abundant throughout gestation (Bulmer et al., 1991; King et al., 1991; Moffett-King, 2002; Williams et al., 2009; Bartmann et al., 2014), but whether they play a role in late pregnancy and parturition is unclear. However, depletion of uNK cells rescues LPS-induced preterm birth in IL10-null mice (Murphy et al., 2005), indicating they contribute to infection/inflammation-induced preterm parturition (Murphy et al., 2009). CD16+CD56dim (cytotoxic) uNK cells have also been observed in the decidua and the placental villi of women with preterm but not term labor, suggesting an association between dysregulation of uNK cells and preterm birth in humans (Gomaa et al., 2017). uNK cells are associated with other pregnancy complications in humans such as fetal growth restriction, preeclampsia, and recurrent spontaneous abortion (Moffett et al., 2004; Hiby et al., 2010; Wallace et al., 2013; Wallace et al., 2014; Kieckbusch et al., 2014). Taken together, these data indicate that uNK cells may act downstream of HAND2-IL15 signaling in the timing of parturition.

Conclusions

Here, we show that HAND2 evolved to be expressed in endometrial stromal cells in the Eutherian stem-lineage, coincident with the evolution of suppressed estrogen signaling during the window of implantation and an interrupted reproductive cycle during pregnancy, which necessitated a means to regulate the length of gestation. Our data suggest that HAND2 may contribute to the regulation of gestation length by promoting an estrogen dominant uterine environment near term and through its effect on IL15 signaling and uNK cell function. To further expand our understanding of HAND2 functions at the molecular mechanistic level, multiple technical and ethical difficulties associated with studying human pregnancy in vivo will need to be overcome. Therefore, recently developed organoid models of the human maternal-fetal interface (Rinehart et al., 1988; Boretto et al., 2017; Turco et al., 2017; Turco et al., 2018; Marinić et al., 2020), which allow for in vitro 3D manipulation, will be instrumental.

Materials and methods

Endometrial gene expression profiling and ancestral transcriptome reconstruction

Data collection

Request a detailed protocol

We obtained previously generated RNA-Seq data from endometria of amniotes by searching NCBI BioSample, Sequence Read Archive (SRA), and Gene Expression Omnibus (GEO) databases for anatomical terms referring to the portion of the female reproductive tract (FRT), including ‘uterus’, ‘endometrium’, ‘decidua’, ‘oviduct’, and ‘shell gland’, followed by manual curation to identify those datasets that included the FRT region specialized for maternal-fetal interaction or shell formation. Datasets that did not indicate whether samples were from pregnant or gravid females were excluded, as were those composed of multiple tissue types. Species included in this study and their associated RNA-Seq accession numbers are included in Figure 1—source data 1.

New RNA-Seq data

Request a detailed protocol

Endometrial tissue samples from the pregnant uteri of baboon (n = 3), mouse (n = 3), hamster (n = 3), bat (n = 2), and squirrel (n = 2) were dissected and mailed to the University of Chicago in RNA-Later. These samples were further dissected to remove myometrium, luminal epithelium, and extra-embryonic tissues, and then washed three times in ice cold PBS to remove unattached cell debris and red blood cells. Total RNA was extracted from the remaining tissue using the RNeasy Plus Mini Kit (74134, QIAGEN) per manufacturer’s instructions. RNA concentrations were determined by Nanodrop 2000 (Thermo Scientific). A total amount of 2.5 μg of total RNA per sample was submitted to the University of Chicago Genomics Facility for Illumina Next Gen RNA sequencing. Quality was assessed with the Bioanalyzer 2100 (Agilent). A total RNA library was generated using the TruSEQ stranded mRNA with RiboZero depletion (Illumina) for each sample. The samples were fitted with one of six different adapters with a different 6-base barcode for multiplexing. Completed libraries were run on an Illumina HiSEQ2500 with v4 chemistry on two replicate lanes for hamster and one lane for other species of an eight lane flow cell, generating 30–50 million 50 bp single-end reads per sample.

Multispecies RNA-Seq analysis

Request a detailed protocol

For all RNA-Seq analyses, we used Kallisto (Bray et al., 2016) version 0.42.4 to pseudo-align the raw RNA-Seq reads to reference transcriptomes (see Figure 1—source data 1 for reference genome assemblies) and to generate transcript abundance estimates. We used default parameters bias correction, and 100 bootstrap replicates. Kallisto outputs consist of transcript abundance estimates in Transcripts Per Million (TPM), which were used to determine gene expression.

Ancestral transcriptome reconstruction

Request a detailed protocol

We previously showed that genes with TPM ≥ 2.0 are actively transcribed in endometrium while genes with TPM < 2.0 lack hallmarks of active transcription such as promoters marked with H3K4me3 (Wagner et al., 2012; Wagner et al., 2013). Based on these findings, we transformed values of transcript abundance estimates into discrete character states, such that genes with TPM ≥ 2.0 were coded as expressed (state = 1), genes with TPM < 2.0 were coded as not expressed (state = 0), and genes without data in specific species coded as missing (state = ?). The binary encoded endometrial gene expression dataset generally grouped species by phylogenetic relatedness, suggesting greater signal-to-noise ratio than raw transcript abundance estimates. Therefore, we used the binary encoded endometrial transcriptome dataset to reconstruct ancestral gene expression states and trace the evolution of gene expression gains (0 → 1) and losses (1 → 0) in the endometria across vertebrate phylogeny (Figure 1A). We used Mesquite (Maddison and Maddison, 2019) (v3.02) with parsimony optimization to reconstruct ancestral gene expression states, and identify genes that gained or lost endometrial expression. Expression was classified as an unambiguous gain if a gene was not inferred as expressed at a particular ancestral node (state = 0) but inferred as expressed (state = 1) in a descendent of that node, and vice versa for the classification of a loss of endometrial expression (Figure 1—source data 2). Parsimony optimization of ancestral states results in three ancestral state reconstructions (ASRs): ‘ambiguous’, ‘most-parsimonious’, and ‘unambiguous’. An ambiguous ASR is not resolved and interpreted as unknown, a most-parsimonious ASR is ‘potentially’ the ASR but not necessarily so because other ancestral states are also possible, while an unambiguous ASR is the most-optimal state such that alternative ASRs can be rejected. The criterion for determining which genes belong in these categories was the parsimony optimization method implemented in Mesquite (v3.02). We thus identified 149 genes that unambiguously evolved endometrial expression in the stem-lineage of Eutherian mammals (Figure 1—source data 3).

Pathway enrichments

Request a detailed protocol

We used WebGestalt v. 2019 (Liao et al., 2019) to determine if the 149 identifies genes were enriched in ontology terms using over-representation analysis (ORA). A key advantage of WebGestalt is that it allowed for the inclusion of a custom background gene list, which was the set of 21,750 genes for which we could reconstruct ancestral states, rather than all annotated protein-coding genes in the human genome. We used ORA to identify enriched terms for three pathway databases (KEGG, Reactome, and Wikipathway), the Human Phenotype Ontology database, and a custom database of genes implicated in preterm birth by GWAS. The preterm birth gene set was assembled from the NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog), including genes implicated in GWAS with either the ontology terms ‘Preterm Birth’ (EFO_0003917) or ‘Spontaneous Preterm Birth’ (EFO_0006917), as well as two recent preterm birth GWAS (Warrington et al., 2019; Sakabe et al., 2020) using a genome-wide significant p-value of 9 × 10−6. The custom gmt file used to test for enrichment of preterm birth associated genes is included as a supplementary data file to Figure 1 (Figure 1—source data 8).

Marsupial gene expression analysis

Opossum uterine gene expression time course

Request a detailed protocol

To explore the expression of HAND2 and other genes throughout gestation in Marsupials, we analyzed previously generated short-tailed opossum (Monodelphis domestica) RNA-Seq data from virgin non-pregnant (SRR2972837, SRR2972848), day 7 (during the histotrophic phase; SRP111668), day 12.5 (just after hatching and during the transition from the histotrophic to the placental phase; GSM1611397), day 13 (early placental phase; SRP111668), day 13.5–14.5 (during the late placental to early parturition phase; SRR2969483, SRR2969536, SRR2970443), and 9–10 month post-partum utera (SRR2972728 and SRR2972729) (Figure 1—source data 7; Lynch et al., 2015; Hansen et al., 2016; Griffith et al., 2017; Griffith et al., 2019).

Wallaby RNA-Seq data from non-pregnant and pregnant animals

Request a detailed protocol

RNA-Seq data for tammar wallaby (Macropus eugenii) uterine tissue from pregnant and non-pregnant animals were from PRJDB1934.

RNA-Seq analysis

Request a detailed protocol

We used Kallisto version 0.42.4 to pseudo-align RNA-Seq reads to the M. domestica and M. eugenii reference transcriptomes with default parameters bias correction and 100 bootstrap replicates. Kallisto output quantifies transcript abundance estimates in TPM.

Immunohistochemistry (IHC)

Request a detailed protocol

Endometrial tissue from pregnant opossum (12.5d) was fixed in 10% neutral-buffered formalin, paraffin-embedded, sectioned at 4 μm, and mounted on slides. Paraffin sections were dried at room temperature overnight and then baked for 12 hr at 50°C. Prior to immunostaining, de-paraffinization and hydration were done in xylene and graded ethanol to distilled water. During hydration, a 5 min blocking for endogenous peroxidase was done in 0.3% H2O2 in 95% ethanol. Antigen retrieval was performed in retrieval buffer pH 6, using a pressure boiler microwave as a heat source with power set to full, allowing retrieval buffer to boil for 20 min, and then cooled in a cold water bath for 10 min. To stain sections, we used the Pierce Peroxidase IHC Detection Kit (cat # 36000) following the manufacturer's protocol. Briefly, uterine sections were incubated at 4°C overnight with polyclonal antibodies against HAND2 (Santa Cruz SC-9409), MUC1 (Novus Biologicals NB120-15481), p-ERα (Santa Cruz SC-12915), p-Erk1/2 (also known as MAPK1/2; Santa Cruz SC-23759-R) at 1:1000 dilution in blocking buffer. The next day sections were washed 3x in wash buffer, and incubated with HRP-conjugated rabbit anti-mouse IgG (H+L) secondary antibody (Invitrogen cat # 31450) at 1:10,000 dilution in blocking buffer. After 30 min at 4°C, slides were washed 3x in wash buffer. Slides were developed with 1x DAB/metal concentrate and stable peroxide buffer for 5 min, then rinsed 3x for 3 min in wash buffer, and mounted with Permount (SP15-100; Thermo Fisher Scientific).

Expression of HAND2 and IL15 at the maternal-fetal interface

Request a detailed protocol

We used previously published single-cell RNA-Seq (scRNA-Seq) data from the human first trimester maternal-fetal interface (Vento-Tormo et al., 2018) to determine which cell types express HAND2 and IL15. The dataset consists of transcriptomes for ~70,000,000 individual cells of many different cell types, including: three populations of tissue resident decidual natural killer cells (dNK1, dNK2, and dNK3), a population of proliferating natural killer cells (dNKp), type two and/or type three innate lymphoid cells (ILC2/ILC3), three populations of decidual macrophages (dM1, dM2, and dM3), two populations of dendritic cells (DC1 and DC2), granulocytes (Gran), T cells (TCells), maternal and lymphatic endothelial cells (Endo), two populations of epithelial glandular cells (Epi1 and Epi2), two populations of perivascular cells (PV1 and PV2), two endometrial stromal fibroblast populations (ESF1 and ESF2), and decidual stromal cells (DSCs), placental fibroblasts (fFB1), extravillous- (EVT), syncytio- (SCT), and villus- (VCT) cytotrophoblasts (Figure 2A). Data were not reanalyzed, rather previously analyzed data were accessed using the cell×gene website available at https://maternal-fetal-interface.cellgeni.sanger.ac.uk.

We note that Vento-Tormo et al. identified five populations of cells in the endometrial stromal lineage, including two perivascular populations (likely reflecting the mesenchymal stem cell-like progenitor of endometrial stromal fibroblasts and decidual stromal cells) and three cell types they call ‘decidual stromal cells’ and label ‘dS1-3’. However, based on the gene expression patterns of ‘dS1-3’ (shown in Vento-Tormo et al. Figure 3a), only ‘dS3’ are decidualized, as indicated by expression of classical markers of decidualization such and PRL (Tabanelli et al., 1992) and IGFBP1/2/6 (Tabanelli et al., 1992; Kim et al., 1999). In stark contrast, ‘dS1’ do not express decidualization markers but highly express markers of ESFs such as TAGLN and ID2, as well as markers of proliferating ESFs including ACTA2 (Kim et al., 1999). ‘dS2’ also express ESFs markers (TAGLN, ID2, ACTA2), but additionally LEFTY2 and IGFBP1/2/6, consistent with ESFs that have initiated the process of decidualization. These data indicate that the ‘dS1’ and ‘dS2’ populations are both ESFs, but ‘dS2’ are ESFs that have initiated decidualization (because they express IGFBPs but not PRL), and that ‘dS3’ are DSCs. Vento-Tormo et al. show that the differences in gene expression between ‘dS1-3’ are related to their topography in the endometrium, but degree of decidualization (‘dS1’/ESF1 < ‘dS2’/ESF2 < ‘dS3’/DSC) is also linked to differential gene expression.

Consistent with this, other scRNA-Seq studies have identified two ESF populations and one DSC population in the first trimester decidua, and used pseudotime analyses to show that they represent different states of differentiation from ESFs to mature DSCs (Suryawanshi et al., 2018). Therefore, we prefer to use the ESF1/ESF2/DSC nomenclature because it more accurately reflects the biology and gene expression profile of these cell types than the ‘dS1-3’ naming convention. We also note that while it is generally thought that ESFs are absent from the pregnant uterus, ESFs retain a presence in the endometrium from the first trimester until term (Richards et al., 1995; Suryawanshi et al., 2018; Muñoz-Fernández et al., 2019; Sakabe et al., 2020).

Expression of HAND2 and IL15 in human decidual cells

Request a detailed protocol

We used previously published IHC data for HAND2 and IL15 generated from pregnant human decidua as part of the Human Protein Atlas project (http://www.proteinatlas.org/; Uhlén et al., 2015). Image/gene/data available from IL15 (https://www.proteinatlas.org/ENSG00000164136-IL15/tissue) and HAND2 (https://www.proteinatlas.org/ENSG00000164107-HAND2/tissue).

Functional genomic analyses of the HAND2 and IL15 loci

Gene expression data

Request a detailed protocol

We used previously published RNA-Seq and microarray gene expression data generated from human ESFs and DSCs that were downloaded from National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) and processed remotely using Galaxy platform (https://usegalaxy.org/; Version 20.01) (Afgan et al., 2018) for RNA-Seq data and GEO2R. RNA-Seq datasets were transferred from SRA to Galaxy using the Download and Extract Reads in FASTA/Q format from NCBI SRA tool (version 2.10.4+galaxy1). We used HISAT2 (version 2.1.0+galaxy5; Kim et al., 2015) to align reads to the Human hg38 reference genome using single- or paired-end options depending on the dataset and unstranded reads, and report alignments tailored for transcript assemblers including StringTie. Transcripts were assembled and quantified using StringTie (v1.3.6) (Pertea et al., 2015; Pertea et al., 2016), with reference file to guide assembly and the ‘reference transcripts only’ option, and output count files for differential expression with DESeq2/edgeR/limma-voom. Differentially expressed genes were identified using DESeq2 (version 2.11.40.6+galaxy1) (Anders and Huber, 2010; Love et al., 2014). The reference file for StringTie guided assembly was wgEncodeGencodeBasicV33. GEO2R performs comparisons on original submitter-supplied processed data tables using the GEOquery (Davis and Meltzer, 2007) and limma (Smyth et al., 2002) R packages from the Bioconductor project (https://bioconductor.org/; Gentleman et al., 2004).

Datasets included gene expression profiles of primary human ESFs treated for 48 hr with control non-targeting, PGR-targeting (GSE94036), FOXO1-targeting (GSE94036) or NR2F2 (COUP-TFII)-targeting (GSE47052) siRNA prior to decidualization stimulus for 72 hr; transfection with GATA2-targeting siRNA was followed immediately by decidualization stimulus (GSE108407). We also explored the expression of HAND2 and IL5 in the endometria of women with recurrent spontaneous abortion and implantation failure using a previously published dataset (GSE26787), as well as in the endometrium throughout the menstrual cycle (GSE4888) and basal plate throughout gestation (GSE5999); HAND2 probe 220480_at, IL15 probe 205992_s_at. The expression of HAND2 and IL5 in ESFs and DSCs from women with normal pregnancy and severe preeclampsia was assessed from a previously generated Agilent Whole Human Genome Microarray 4 × 44K v2 dataset (GSE91077).

ChIP-Seq and open chromatin data

Request a detailed protocol

We used previously published ChIP-Seq data generated from human DSCs that were downloaded from NCBI SRA and processed remotely using Galaxy (Afgan et al., 2018). ChIP-Seq reads were mapped to the human genome (GRCh37/hg19) using HISAT2 (Kim et al., 2015) with default parameters and peaks called with MACS2 (Zhang et al., 2008; Feng et al., 2012) with default parameters. Samples included PLZF (GSE75115), H3K4me3 (GSE61793), H3K27ac (GSE61793), H3K4me1 (GSE57007), PGR (GSE69539), the PGR A and B isoforms (GSE62475), NR2F2 (GSE52008), FOSL2 (GSE69539), FOXO1 (GSE69542), PolII (GSE69542), GATA2 (GSE108408), SRC-2/NCOA2 (GSE123246), AHR (GSE118413), ATAC-Seq (GSE104720), and DNase1-Seq (GSE61793). FAIRE-Seq peaks were downloaded from the UCSC genome browser and not re-called.

Chromatin interaction data

Request a detailed protocol

To assess chromatin looping, we utilized a previously published H3K27ac HiChIP dataset from a normal hTERT-immortalized endometrial cell line (E6E7hTERT) and three endometrial cancer cell lines (ARK1, Ishikawa and JHUEM-14) (O’Mara et al., 2019). This study identified 66,092 to 449,157 cis HiChIP loops (5 kb–2 Mb in length) per cell line. The majority of loops involved interactions of over 20 kb in distance, 35–40% of loops had contact with a promoter and those promoter-associated loops had a median span >200 kb. Contact data were from the original publication and not re-called for this study. Note that Figures 2C and 4C were made using a combination of the UCSC genome browser to map the location of regions of open chromatin and ChIP-Seq peaks and Illustrator to simplify the images from the genome browser.

Cell culture and HAND2 knockdown

Request a detailed protocol

Human hTERT-immortalized endometrial stromal fibroblasts (T-HESC; CRL-4003, ATCC) were grown in maintenance medium, consisting of Phenol Red-free DMEM (31053–028, Thermo Fisher Scientific), supplemented with 10% charcoal-stripped fetal bovine serum (CS-FBS; 12676029, Thermo Fisher Scientific), 1% L-glutamine (25030–081, Thermo Fisher Scientific) , 1% sodium pyruvate (11360070, Thermo Fisher Scientific), and 1x insulin-transferrin-selenium (ITS; 41400045, Thermo Fisher Scientific). A total of 2 × 105 cells were plated per well of a six-well plate and 18 hr later cells in 1750 μl of Opti-MEM (31985070, Thermo Fisher Scientific) were transfected with 50 nM of siRNA targeting HAND2 (s18133; Silencer Select Pre-Designed siRNA; cat # 4392420, Thermo Fisher Scientific) and 9 μl of Lipofectamine RNAiMAX (133778–150, Invitrogen) in 250 μl Opti-MEM. BlockIT Fluorescent Oligo (44–2926, Thermo Fisher Scientific) was used as a scrambled non-targeting RNA control. Cells were incubated in the transfection mixture for 6 hr. Then, cells were washed with PBS and incubated in the maintenance medium overnight. Cells in the control wells were checked under the microscope for fluorescence the next day. Forty-eight hr post-treatment, cells were washed with PBS, trypsinized (0.05% Trypsin-EDTA; 15400–054, Thermo Fisher Scientific) and total RNA was extracted using RNeasy Plus Mini Kit (74134, QIAGEN) following the manufacturer’s protocol. The knockdown experiment was done in three biological replicates. To test for the efficiency of the knockdown, cDNA was synthesized from 100 to 200 ng RNA using Maxima H Minus First Strand cDNA Synthesis Kit (K1652, Thermo Fisher Scientific) following the manufacturer’s protocol. qRT-PCR was performed using QuantiTect SYBR Green PCR (204143, QIAGEN). HAND2 primers: forward CACCAGCTACATCGCCTACC, reverse ATTTCGTTCAGCTCCTTCTTCC. GAPDH housekeeping gene was used for normalization; primers forward AATCCCATCACCATCTTCCA, reverse TGGACTCCACGACGTACTCA. Samples that showed >70% knockdown efficiency were used for RNA-Seq.

HAND2 knockdown RNA-Seq analysis

Request a detailed protocol

RNA from knockdown and control samples were DNase treated with TURBO DNA-free Kit (AM1907, Thermo Fisher Scientific) and RNA quality and quantity were assessed on 2100 Bioanalyzer (Agilent Technologies, Inc). RNA-Seq libraries were prepared using TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human (RS-122–2201, Illumina Inc) following manufacturer’s protocol. Library quality and quantity were checked on 2100 Bioanalyzer and the pool of libraries was sequenced on Illumina HiSEQ4000 (single-end 50 bp) using manufacturer’s reagents and protocols. Quality control, Ribo-Zero library preparation and Illumina sequencing were performed at the Genomics Facility at The University of Chicago.

All sequencing data were uploaded and analyzed on the Galaxy platform (https://usegalaxy.org/; Version 20.01). Individual reads for particular samples were concatenated using the ‘Concatenate datasets’ tool (version 1.0.0). We used HISAT2 (version 2.1.0+galaxy5) (Kim et al., 2015) to align reads to the Human hg38 reference genome using ‘Single-end’ option, and reporting alignments tailored for transcript assemblers including StringTie. Transcripts were assembled and quantified using StringTie (v1.3.6) (Pertea et al., 2015; Pertea et al., 2016), with reference file to guide assembly and the ‘reference transcripts only’ option, and output count files for differential expression with DESeq2/edgeR/limma-voom. Differentially expressed genes were identified using DESeq2 (version 2.11.40.6+galaxy1; Anders and Huber, 2010; Love et al., 2014). The reference file for StringTie guided assembly was wgEncodeGencodeBasicV33. The volcano plot was generated using Blighe et al., 2020.

Trans-well migration assay

Request a detailed protocol

Human hTERT-immortalized ESFs (CRL-4003, ATCC) were selected as a model ESF cell line because they are proliferative, maintain hormone responsiveness, and gene expression patterns characteristic of primary ESFs, and have been relatively well characterized (Krikun et al., 2004). ESFs were cultured in the maintenance medium as described above in T75 flasks until ~80% confluent. Cryopreserved primary adult human CD56+ NK cells purified by immunomagnetic bead separation were obtained from ATCC (PCS-800–019) and cultured in RPMI-1640 containing 10% FBS and 500 IU/ml IL2 in T75 flasks for 2 days prior to trans-well migration assays. We used the immortalized first trimester extravillous trophoblast cell line HTR-8/SVneo (Graham et al., 1993), because it maintains characteristics of extravillous trophoblasts and has previously been shown to be a good model of trophoblast migration and invasion (Iacob et al., 2008; Paiva et al., 2009; Hannan et al., 2010). HTR-8/SVneo cells were obtained from ATCC (CRL-3271) and cultured in RPMI-1640 containing 5% FBS in T75 flasks for 2 days prior to trans-well migration assays. All cell lines were determined to be mycoplasma free before each experiment.

A total of 3 × 104 ESFs were plated per well of a 24-well plate and 18 hr later cells were transfected in Opti-MEM with 10 nM (per well) of siRNA targeting HAND2 (s18133; Silencer Select Pre-Designed siRNA, cat # 4392420; Thermo Fisher Scientific) or IL15 (s7377; Silencer Select Pre-Designed siRNA, cat # 4392420; Thermo Fisher Scientific) and 1.5 μl (per well) of Lipofectamine RNAiMAX (133778–150; Invitrogen). As a negative control we used Silencer Select negative control No. 1 (4390843; Thermo Fisher Scientific). ESFs were incubated in the transfection mixture for 6 hr. Then, ESFs were washed with warm PBS and incubated in the maintenance medium overnight. Efficiency of the knockdown was confirmed 48 hr post-treatment by qRT-PCR, media from each well was transferred to new 24-well plates and stored at 4°C. Total RNA from cells was extracted using RNeasy Plus Mini Kit (74134, QIAGEN) following the manufacturer’s protocol. cDNA was synthesized from 10 ng RNA using Maxima H Minus First Strand cDNA Synthesis Kit (K1652, Thermo Fisher Scientific) following the manufacturer’s protocol. qRT-PCR was performed using TaqMan Fast Universal PCR Master Mix 2X (4352042, Thermo Fisher Scientific), with primers for HAND2 (Hs00232769_m1), IL15 (Hs01003716_m1), and Malat (Hs00273907_s1) as a control housekeeping gene. Conditioned media from samples with >70% knockdown efficiency was used for trans-well migration assays.

Corning HTS Trans-well permeable supports were used for the trans-well migration assay (Corning, cat # CLS3398). Prior to the assays, 500 μl of media conditioned for 12 hr was centrifuged for 3 min at 1000 RPM to pellet any cells. For experiments using recombinant human IL15 (rhIL15), we added 10 ng/ml (AbCam, ab259403) of rhIL15 to fresh, non-conditioned ESF media; 10 ng/ml has previously been shown to induce migration of JEG-3 choriocarcinoma cells (Zygmunt et al., 1998). For neutralizing antibody experiments, either 1 μg/ml of anti-IL15 IgG (AbCam cat # MA5-23729) or control IgG (AbCam cat # 31903) were added to non-conditioned ESF media; 1 μg/ml has previously been shown to neutralize ESF-derived proteins and inhibit AC-1M88 trophoblast cell migration in trans-well assays (Gellersen et al., 2010; Gellersen et al., 2013). Plates were incubated with shaking at 37°C for 30 min prior to initiation of migration assays. During antibody incubation, NK and HTR-8/SVneo cells were collected and resuspended in fresh ESF growth media. For the trans-well migration assay, 5 × 106 of either NK or HTR-8/SVneo cells were added to each well of the upper chamber and either treatment or control media were added to the lower chambers. Plates were incubated at 37°C with 5% CO2.

After 8 hr incubation, we removed the upper plate (containing remaining NK and HTR-8/SVneo cells) and discarded non-migrated cells. Fifty μl from each well in the lower chamber was transferred into a single well of a 96-well opaque plate. We used the CellTiter-Glo luminescent cell viability assay (G7570, Promega) to measure luminescence, which is proportional to the number of live cells per well. Data are reported as effect sizes (mean differences) between treatment and control. Confidence intervals are bias-corrected and accelerated. The p-values reported are the likelihoods of the observed effect sizes, if the null hypothesis of zero difference is true and calculated from a two-sided permutation t-test (5000 reshuffles of the control and test labels). Cumming estimation plots and estimation statistics were calculated using DABEST R package (Ho et al., 2019).

Data availability

Sequencing data have been deposited in GEO under accession codes GSE155170 and GSE155322.

The following data sets were generated
    1. K Mika
    2. VJ Lynch
    (2020) NCBI Gene Expression Omnibus
    ID GSM4696518. Hamster Endometrium Individual 1 Replicate 1.
    1. K Mika
    2. VJ Lynch
    (2020) NCBI Gene Expression Omnibus
    ID GSM4696519. Hamster Endometrium Individual 2 Replicate 1.
    1. K Mika
    2. VJ Lynch
    (2020) NCBI Gene Expression Omnibus
    ID GSM4696520. Hamster Endometrium Individual 3 Replicate 1.
    1. K Mika
    2. VJ Lynch
    (2020) NCBI Gene Expression Omnibus
    ID GSM4696521. Hamster Endometrium Individual 1 Replicate 2.
    1. K Mika
    2. VJ Lynch
    (2020) NCBI Gene Expression Omnibus
    ID GSM4696522. Hamster Endometrium Individual 2 Replicate 2.
    1. K Mika
    2. VJ Lynch
    (2020) NCBI Gene Expression Omnibus
    ID GSM4696523. Hamster Endometrium Individual 3 Replicate 2.
    1. K Mika
    2. VJ Lynch
    (2020) NCBI Gene Expression Omnibus
    ID GSE155170. Evolutionary transcriptomics implicates HAND2 in the origins of implantation and regulation of gestation length.
    1. M Marinić
    2. VJ Lynch
    (2020) NCBI Gene Expression Omnibus
    ID GSE155322. Evolutionary transcriptomics implicates HAND2 in the origins of implantation and regulation of gestation length.

References

    1. MG Elliot
    (2017) Evolutionary origins of preeclampsia
    Pregnancy Hypertension: An International Journal of Women's Cardiovascular Health 7:56.
    https://doi.org/10.1016/j.preghy.2016.10.006
  1. Software
    1. WP Maddison
    2. DR Maddison
    (2019) Mesquite: A Modular System for Evolutionary Analysis
    Mesquite: A Modular System for Evolutionary Analysis.
  2. Book
    1. M Renfree
    2. G Shaw
    (2001) Reproduction in Monotremes and Marsupials
    In: M Renfree, editors. Encyclopedia of Life Sciences. Chichester, UK: John Wiley & Sons, Ltd. pp. 1–10.
    https://doi.org/10.1038/npg.els.0001856
    1. Y-M Sun
    2. J Wang
    3. X-B Qiu
    4. F Yuan
    5. R-G Li
    6. Y-J Xu
    7. X-K Qu
    8. H-Y Shi
    9. X-M Hou
    10. R-T Huang
    11. S Xue
    12. Y-Q Yang
    (2016)
    A HAND2 loss-of-function mutation causes familial ventricular septal defect and pulmonary stenosis
    G3 Genes|Genomes|Genetics 6:987–992.
    1. NM Varki
    2. A Varki
    (2015) On the apparent rarity of epithelial cancers in captive chimpanzees
    Philosophical Transactions of the Royal Society B: Biological Sciences 370:20140225.
    https://doi.org/10.1098/rstb.2014.0225
    1. NM Warrington
    2. RN Beaumont
    3. M Horikoshi
    4. FR Day
    5. Ø Helgeland
    6. C Laurin
    7. J Bacelis
    8. S Peng
    9. K Hao
    10. B Feenstra
    11. AR Wood
    12. A Mahajan
    13. J Tyrrell
    14. NR Robertson
    15. NW Rayner
    16. Z Qiao
    17. GH Moen
    18. M Vaudel
    19. CJ Marsit
    20. J Chen
    21. M Nodzenski
    22. TM Schnurr
    23. MH Zafarmand
    24. JP Bradfield
    25. N Grarup
    26. MN Kooijman
    27. R Li-Gao
    28. F Geller
    29. TS Ahluwalia
    30. L Paternoster
    31. R Rueedi
    32. V Huikari
    33. JJ Hottenga
    34. LP Lyytikäinen
    35. A Cavadino
    36. S Metrustry
    37. DL Cousminer
    38. Y Wu
    39. E Thiering
    40. CA Wang
    41. CT Have
    42. N Vilor-Tejedor
    43. PK Joshi
    44. JN Painter
    45. I Ntalla
    46. R Myhre
    47. N Pitkänen
    48. EM van Leeuwen
    49. R Joro
    50. V Lagou
    51. RC Richmond
    52. A Espinosa
    53. SJ Barton
    54. HM Inskip
    55. JW Holloway
    56. L Santa-Marina
    57. X Estivill
    58. W Ang
    59. JA Marsh
    60. C Reichetzeder
    61. L Marullo
    62. B Hocher
    63. KL Lunetta
    64. JM Murabito
    65. CL Relton
    66. M Kogevinas
    67. L Chatzi
    68. C Allard
    69. L Bouchard
    70. MF Hivert
    71. G Zhang
    72. LJ Muglia
    73. J Heikkinen
    74. CS Morgen
    75. AHC van Kampen
    76. BDC van Schaik
    77. FD Mentch
    78. C Langenberg
    79. J Luan
    80. RA Scott
    81. JH Zhao
    82. G Hemani
    83. SM Ring
    84. AJ Bennett
    85. KJ Gaulton
    86. J Fernandez-Tajes
    87. NR van Zuydam
    88. C Medina-Gomez
    89. HG de Haan
    90. FR Rosendaal
    91. Z Kutalik
    92. P Marques-Vidal
    93. S Das
    94. G Willemsen
    95. H Mbarek
    96. M Müller-Nurasyid
    97. M Standl
    98. EVR Appel
    99. CE Fonvig
    100. C Trier
    101. CEM van Beijsterveldt
    102. M Murcia
    103. M Bustamante
    104. S Bonas-Guarch
    105. DM Hougaard
    106. JM Mercader
    107. A Linneberg
    108. KE Schraut
    109. PA Lind
    110. SE Medland
    111. BM Shields
    112. BA Knight
    113. JF Chai
    114. K Panoutsopoulou
    115. M Bartels
    116. F Sánchez
    117. J Stokholm
    118. D Torrents
    119. RK Vinding
    120. SM Willems
    121. M Atalay
    122. BL Chawes
    123. P Kovacs
    124. I Prokopenko
    125. MA Tuke
    126. H Yaghootkar
    127. KS Ruth
    128. SE Jones
    129. PR Loh
    130. A Murray
    131. MN Weedon
    132. A Tönjes
    133. M Stumvoll
    134. KF Michaelsen
    135. AM Eloranta
    136. TA Lakka
    137. CM van Duijn
    138. W Kiess
    139. A Körner
    140. H Niinikoski
    141. K Pahkala
    142. OT Raitakari
    143. B Jacobsson
    144. E Zeggini
    145. GV Dedoussis
    146. YY Teo
    147. SM Saw
    148. GW Montgomery
    149. H Campbell
    150. JF Wilson
    151. TGM Vrijkotte
    152. M Vrijheid
    153. E de Geus
    154. MG Hayes
    155. HN Kadarmideen
    156. JC Holm
    157. LJ Beilin
    158. CE Pennell
    159. J Heinrich
    160. LS Adair
    161. JB Borja
    162. KL Mohlke
    163. JG Eriksson
    164. EE Widén
    165. AT Hattersley
    166. TD Spector
    167. M Kähönen
    168. JS Viikari
    169. T Lehtimäki
    170. DI Boomsma
    171. S Sebert
    172. P Vollenweider
    173. TIA Sørensen
    174. H Bisgaard
    175. K Bønnelykke
    176. JC Murray
    177. M Melbye
    178. EA Nohr
    179. DO Mook-Kanamori
    180. F Rivadeneira
    181. A Hofman
    182. JF Felix
    183. VWV Jaddoe
    184. T Hansen
    185. C Pisinger
    186. AA Vaag
    187. O Pedersen
    188. AG Uitterlinden
    189. MR Järvelin
    190. C Power
    191. E Hyppönen
    192. DM Scholtens
    193. WL Lowe
    194. G Davey Smith
    195. NJ Timpson
    196. AP Morris
    197. NJ Wareham
    198. H Hakonarson
    199. SFA Grant
    200. TM Frayling
    201. DA Lawlor
    202. PR Njølstad
    203. S Johansson
    204. KK Ong
    205. MI McCarthy
    206. JRB Perry
    207. DM Evans
    208. RM Freathy
    209. EGG Consortium
    (2019) Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors
    Nature Genetics 51:804–814.
    https://doi.org/10.1038/s41588-019-0403-1

Decision letter

  1. George H Perry
    Senior Editor; Pennsylvania State University, United States
  2. Antonis Rokas
    Reviewing Editor; Vanderbilt University, United States
  3. Abigail LaBella
    Reviewer

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

Parsing mechanisms of disease from the perspective of evolutionary biology is a powerful approach. The manuscript by Marinić et al. uses an innovative gene expression dataset in an evolutionary framework to identify a set of transcripts whose endometrial expression emerged at the eutherian mammal stem lineage. One of these transcripts is for the transcription factor HAND2. Using both existing datasets and experimental data the authors build a model of the activity of HAND2 and its associated protein IL15 at the maternal-fetal interface and implicate the proteins in both the evolution and disorders of pregnancy. The work illustrates the utility of evolutionary analysis for elucidating functional mechanisms of complex disorders and substantially contributes to our knowledge of the evolution and diseases of pregnancy.

Decision letter after peer review:

Thank you for submitting your article "Evolutionary transcriptomics implicates HAND2 in the origins of implantation and regulation of gestation length" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and George Perry as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Abigail LaBella (Reviewer #2).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

Parsing mechanisms of disease from the perspective of evolutionary biology is a powerful approach. The manuscript by Marinić et al. uses an innovative expression dataset in an evolutionary framework to identify a set of transcripts whose endometrial expression emerged at the eutherian stem lineage. One of these is the transcription factor HAND2. Using both existing datasets and experimental data the authors build a model of the activity of HAND2 and its associated protein IL15 at the maternal-fetal interface and implicate the proteins in both the evolution and disorders of pregnancy. The work illustrates the utility of evolutionary analysis for elucidating functional mechanisms of complex disorders and substantially contributes to our knowledge of the evolution and diseases of pregnancy.

Revisions:

1) Figure 1C appears interesting but there is no comparison or controls. Without comparison, for example the histotrophic phase, it appears difficult to conclude that estrogen signaling genuinely persists during pregnancy in the opossum. pESR1 staining in the tissue section is ubiquitous with no evidence of nuclear localisation, raising concerns about antibody specificity. KI67 staining may be more informative?

2) The authors used a large single-cell RNA-seq data set to map HAND2 expression at the human maternal-fetal interface in the first-trimester of pregnancy (Vento-Tormo et al., 2018). They demonstrate that HAND2 expression is confined to 3 maternal subsets, termed endometrial stromal fibroblast (ESF) 1 and 2 and decidual stromal cells (DSC). If we are not mistaken, in the Vento-Tormo paper, these populations of cells were labelled decidual stromal cells 1-3 (DS1-3), emphasizing that all these cells were decidualized, as expected in pregnancy. Vento-Tormo et al. further demonstrated that the differences in gene expression between DS subsets relate to their topography in the maternal tissue. Hence, it is confusing that the authors changed the terminology of these subsets, giving the erroneous impression of two undifferentiated ESF population and a single DS/DSC population in pregnancy. By doing so, the inference seems to be that T-HESC, a telomerase-transformed endometrial stromal cell line used in functional studies, is a good model of ESF populations in vivo, which is doubtful.

3) Figure 2G. The authors state that “We also used previously published gene expression datasets (see Materials and methods) to explore if HAND2 was associated with disorders of pregnancy and found significant HAND2 dysregulation in the endometria of women with infertility (IF) and recurrent spontaneous abortion (RSA) compared to fertile controls” – This bold statement is based on microanalysis of merely 5 biopsies in each group. Considering the intrinsic temporo-spatial heterogeneity of the cycling endometrium, this sample size is grossly inadequate. The microarray study was published in 2011. In fact there are several more recent and more robust datasets available (e.g. 115 IF biopsies in GSE58144 and 20 RM biopsies in GPL11154) that should instead be used. These comments also apply to Figure 4G.

4) The authors also state “HAND2 was not differentially expressed in ESFs or DSCs from women with preeclampsia (PE) compared to controls (Figure 2G).” It is unclear which dataset this was based on. The authors' claim seem to indicate that this was single-cell data? In any case, the sample size is again grossly inadequate to draw robust conclusions without further validation in a much larger cohort of samples.

5) Figure 3. The authors decided to knockdown HAND2 in T-HESC, a telomerase-transformed endometrial stromal cell line, and performed RNA-seq 48 h later. The cells were not decidualized or even treated with progesterone. Hence, the rationale for this experiment, and its relevance to the in vivo situation, is genuinely lost on me. See also comment regarding the renaming of DS subsets into ESF. In an undifferentiated state, these cells are not representative of gestational cells (with the possible exception that decidual senescence is characterized by progesterone resistance, i.e. re-activation of genes that are suppressed by progesterone). More importantly, as HAND2 is critical for the identity of these cells, perhaps knockdown triggers a stress response? For example, from the data presented in Figure 3—source data 1 (it would be helpful to add gene names), on of the strongest up-regulated gene upon HAND2 knockdown is BLCAP2 [Log2(FC): 10.2], which encodes a protein that reduces cell growth by stimulating apoptosis.

6) The authors illustrated the importance of examining the right cellular state: knockdown HAND2 in T-HESC increases IL15 expression whereas it is well established that HAND2 knockdown in decidual cells decreases IL15 expression. Further, IL15 is strongly induced upon decidualization and previous studies on primary endometrial stromal cells demonstrated that IL15 secretion is undetectable in undifferentiated cells whereas it is abundantly secreted upon decidualization (PMID: 31965050). Thus, we suggest that the should repeat HAND2 KD in decidualizing T-HESC and measure IL15 secretion in both states, with and without HAND2 knockdown, in future experiments.

7) Figure 3B – it is unclear what is compared here: genes deregulated upon HAND2 knockdown in T-HESC versus knockdown NR2F2, FOXO1 and GAT2 in decidualized primary cultures? If this is the case, the comparison is not informative as it involves two different cell states. It is surprising that FOSL2 was not included in this analysis.

8) We do not understand the relevance of the experiments described in Figure 5 to the context of gestation length or preterm birth. Trophoblast invasion will have been completed in the second trimester of pregnancy – what is the purpose/message of these experiments? What is the level of IL15 secreted by these cells? Again the T-HESC appear not decidualized – so, what is the relevance to either the midluteal implantation window or gestation?

9) What is the evolution of IL15 expression at the maternal-fetal interface? Does it parallel HAND2?

10) Of the 149 genes that unambiguously evolved endometrial expression why was only HAND2 analyzed? We are not suggesting that each gene be followed up with this level of rigor but would you hypothesize that each of the genes you identified play a role in eutherian reproduction? Or are there other major innovations that some of these genes may be associated with? How frequently would this pattern occur by chance?

11) Figures 2F and 4F – there appears to be a gap in the data points during the third trimester (which looks like it says "thirdr"). Is there still a negative trend if each section is analyzed independently as if they were independent datasets? Aka could this linear trend be composed of two separate trends instead?

12) Please provide the binary encoded data used for this analysis as it could be readily used by other research groups for similar analysis. The custom database of genes implicated in preterm birth would also be a useful dataset.

13) It was helpful to hear from one of the authors that the known HAND2 gene wasn't knocked out in mice, so it was an easy early pregnancy gene to start with. Perhaps this should be stated in the revised manuscript?

14) To reproduce the study, there were a couple of questions around the production of the conditioned media including, how long were the cells incubated in the media and what was the volume of the media use. Please include this information in the revised manuscript.

15) Can you further explain why the opossum was used to measure the estrogen levels?

16) The relationship between ESR1 and HAND2 is a little unclear. Is ESR1 expression correlated with HAND2 expression in all species studied?

https://doi.org/10.7554/eLife.61257.sa1

Author response

Revisions:

1) Figure 1C appears interesting but there is no comparison or controls. Without comparison, for example the histotrophic phase, it appears difficult to conclude that estrogen signaling genuinely persists during pregnancy in the opossum.

We agree that showing expression of HAND2, ESR1, and estrogen responsive genes at a single time point can make it difficult to conclude that estrogen signaling persists throughout opossum pregnancy, particularly in the absence of a “control”. Therefore, we have updated Figure 1C (now Figure 1D) to include RNA-Seq data from the uterus of non-pregnant control, pregnancy day 7, pregnancy day 12.5, pregnancy day 13, as well as pregnancy days 13.5-14.5 (late placental to early parturition phase) and 9-10 months post-partum. Note that previously we only showed data for day 12.5 (just after hatching), and that birth occurs on day 14.5. These new data are consistent with our claim that RNA-Seq data indicate persistent estrogen signaling during opossum pregnancy, for example, showing that ESR1, FGF9, and WNTs are expressed across all stages. A previous study has shown that ESR1 is an estrogen responsive gene in wallaby (Renfree and Blanden, 2000), providing an additional evidence for estrogen signaling during pregnancy in Marsupials. We have updated the manuscript to include a description of the new time course data, as well as indicate that ESR1 is an estrogen responsive gene in Marsupials (Renfree and Blanden, 2000).

More interestingly, these data also show that HAND2 expression is dynamic throughout pregnancy, and is highest in the non-pregnant uterus, down-regulated during mid- and late-pregnancy (below our expression cutoff of TPM=2), and increases in expression at 14d about 12 hours before parturition. We interpret these data to support our conclusions that HAND2 is generally not expressed during either the histotrophic or placental phase, and reinforces our conclusion that estrogen signaling (as evidenced by the expression of estrogen responsive genes such as ESR1) persists during pregnancy in the opossum. The coincidence of ESR1 and HAND2 down-regulation suggests that the negative regulatory interaction between HAND2 and ESR1 does not occur in opossum (if it did, as HAND2 expression decreased, ESR1 expression would increase). We have updated the manuscript to reflect this new finding. We thank the reviewers for these very useful suggestions.

pESR1 staining in the tissue section is ubiquitous with no evidence of nuclear localization, raising concerns about antibody specificity. KI67 staining may be more informative?

Previous studies have shown that progesterone and estrogen receptor proteins are expressed in the endometrium throughout pregnancy in Marsupials, and down-regulated in mid- and late-pregnancy (which is also reflected in our RNA-Seq time course shown in previous Figure 1C, now Figure 1D). Thus, our report of estrogen receptor protein expression in the pregnant opossum endometrium is supported by previous studies. We now include reference for those studies, demonstrating estrogen receptor expression in the pregnant endometrium of the brush-tailed possum (Trichosurus vulpecula) (Young and McDonald, 1982; Curlewis and Stone, 1982) and tammar wallaby (Macropus eugenii) (Renfree and Blanden, 2000). While we believe the staining is specific, we appreciate the concern that the pESR1 staining may not be specific and have therefore moved the immunohistochemistry figure from the main text to a figure supplement. We do not believe this alters the conclusions from this figure because the RNA-Seq time course data indicate that estrogen-responsive genes are expressed throughout pregnancy in opossum. Unfortunately, we were unable to find an antibody that cross-reacted with Monodelphis KI67, however, it is expressed just above our TPM=2 cutoff in both Monodelphis non-pregnant and pregnant endometria. These data are now shown in Figure 1D.

2) The authors used a large single-cell RNA-seq data set to map HAND2 expression at the human maternal-fetal interface in the first-trimester of pregnancy (Vento-Tormo et al., 2018). They demonstrate that HAND2 expression is confined to 3 maternal subsets, termed endometrial stromal fibroblast (ESF) 1 and 2 and decidual stromal cells (DSC). If we are not mistaken, in the Vento-Tormo paper, these populations of cells were labelled decidual stromal cells 1-3 (DS1-3), emphasizing that all these cells were decidualized, as expected in pregnancy. Vento-Tormo et al. further demonstrated that the differences in gene expression between DS subsets relate to their topography in the maternal tissue. Hence, it is confusing that the authors changed the terminology of these subsets, giving the erroneous impression of two undifferentiated ESF population and a single DS/DSC population in pregnancy. By doing so, the inference seems to be that T-HESC, a telomerase-transformed endometrial stromal cell line used in functional studies, is a good model of ESF populations in vivo, which is doubtful.

While we appreciate the concerns of the reviewers, the naming used by Vento-Tormo et al. (2018) based on the location of these three cell populations in the decidua does not reflect their cell-type identity. The authors identified five populations of cells in the endometrial stromal lineage, including two perivascular populations (likely reflecting the mesenchymal stem cell-like progenitor of endometrial stromal fibroblasts and decidual stromal cells) and three cell types they call “decidual stromal cells” and label “dS1-3”. However, based on the gene expression patterns of “dS1-3” (shown in Vento-Tormo et al. Figure 3a), only “dS3” are decidualized, as indicated by expression of classical markers of decidualization such and PRL (Tabanelli, Tang and Gurpide, 1992) and IGFBP1/2/6 (Tabanelli, Tang and Gurpide, 1992; Kim, Jaffe and Fazleabas, 1999). In stark contrast, “dS1” do not express decidualization markers but highly express markers of endometrial stromal fibroblasts (ESFs) such as TAGLN and ID2, as well as markers of proliferating ESFs including ACTA2 (Kim, Jaffe and Fazleabas, 1999). “dS2” also express ESFs markers (TAGLN, ID2, ACTA2), but additionally LEFTY2 and IGFBP1/2/6, consistent with ESFs that have initiated the process of decidualization. These data indicate that the “dS1” and “dS2” populations are both ESFs, but “dS2” are ESFs that have initiated decidualization (because they express IGFBPs but not PRL), and that “dS3” are DSCs. Vento-Tormo et al. show that the differences in gene expression between “dS1-3” are related to their topography in the endometrium, but degree of decidualization (“dS1”/ESF1 <“dS2”/ESF2 < “dS3”/DSC) is also linked to differential gene expression.

Consistent with this, other scRNA-Seq studies have identified two ESF populations and one DSC population in the first trimester decidua, and used pseudotime analyses to show that they represent different states of differentiation from ESFs to mature DSCs (Suryawanshi et al., 2018). Therefore, we prefer to use the ESF1/ESF2/DSC nomenclature because it more accurately reflects the biology and gene expression profile of these cell-types than the “dS1-3” naming convention.

Importantly, ESFs are present in the endometrium during the first trimester and persist in the endometrium until term (Sakabe et al., 2020; Richards et al., 1995; Munoz-Fernandez et al., 2019; Suryawanshi et al., 2018) – we apologize if this was unclear in the manuscript. Our naming of the “dS1” and “dS2” populations as ESF1 and ESF2 makes it clear that there are ESFs in the decidua during pregnancy and that the T-HESC cell line is a good model of these in vivo ESF populations. We appreciate that changing the terminology for these cell types can be confusing, and have added an explanation for our name change in the Materials and methods section describing the Vento-Tormo et al. We also indicate in the Results section that readers “see Materials and methods for cell-type naming convention” and to explain that ESFs persist in the endometrium till term. We hope this helps allay the concerns of the reviewers.

3) Figure 2G. The authors state that “We also used previously published gene expression datasets (see Materials and methods) to explore if HAND2 was associated with disorders of pregnancy and found significant HAND2 dysregulation in the endometria of women with infertility (IF) and recurrent spontaneous abortion (RSA) compared to fertile controls” – This bold statement is based on microanalysis of merely 5 biopsies in each group. Considering the intrinsic temporo-spatial heterogeneity of the cycling endometrium, this sample size is grossly inadequate. The microarray study was published in 2011. In fact there are several more recent and more robust datasets available (e.g. 115 IF biopsies in GSE58144 and 20 RM biopsies in GPL11154) that should instead be used. These comments also apply to Figure 4G.

While we agree that there can be significant temporo-spatial heterogeneity across endometrial samples, the sampling protocol for GSE58144 makes it more difficult to analyze than the GSE26787 dataset that we used, even though GSE26787 has fewer samples per condition (five endometrial biopsies in non-conceptional cycles in the mid-luteal phase). For example, RNA for the GSE58144 dataset was collected from mid-luteal phase endometrial biopsies between 2006 and 2013. Thus, while the GSE58144 data were published more recently than the GSE26787 data, at least some GSE58144 samples were collected earlier and it is not clear from the available information how the samples were stored or batch-processed on the Agilent microarray used to quantify gene expression. Unfortunately, this leads to difficulties in data analysis – for example, it is not clear how to appropriately batch-correct these samples. Based on the GEO submission information, there are at least two “cohorts”, but no genes are significantly differentially expressed (DE) among either cohort 1 or cohort 2 at FDR≤0.10, and only two genes are significantly DE at FDR≤0.10 (AQP11 and KYNU) when cohorts 1 and 2 are combined. Thus, while GSE58144 is much larger than the dataset we utilized, their study design reduces power to detect significantly DE genes. To reflect the reviewer’s concerns, we have added a caveat to the section of these results, which states that: “Although sample sizes of these datasets are small, and the intrinsic temporo-spatial heterogeneity of the endometrium remains a potential confounding factor, we found that HAND2 was dysregulated in the endometria of women with implantation failure (IF) and recurrent spontaneous abortion (RSA), while it was not differentially expressed in ESFs or DSCs from women with preeclampsia (PE), compared to controls (Figure 2G).”

We were unable to find a dataset of 20 recurrent miscarriage biopsies because the accession GPL11154 refers to all datasets generated on the Illumina HiSeq 2000 (Homo sapiens) platform and the search for “GEO (recurrent miscarriage) AND "Homo sapiens"[porgn: txid9606]” did not identify an RM dataset with 20 biopsies.

4) The authors also state “HAND2 was not differentially expressed in ESFs or DSCs from women with preeclampsia (PE) compared to controls (Figure 2G).” It is unclear which dataset this was based on. The authors' claim seem to indicate that this was single-cell data? In any case, the sample size is again grossly inadequate to draw robust conclusions without further validation in a much larger cohort of samples.

The expression of HAND2 and IL5 in ESFs and DSCs from women with normal pregnancies and severe preeclampsia was assessed from a previously generated Agilent Whole Human Genome Microarray 4x44K v2 dataset (GSE91077), not from scRNA-Seq data. We have included this information in the Materials and methods section to ensure it is clear which technology was used to generate this dataset. Also see the answer to the previous question.

5) Figure 3. The authors decided to knockdown HAND2 in T-HESC, a telomerase-transformed endometrial stromal cell line, and performed RNA-seq 48 h later. The cells were not decidualized or even treated with progesterone. Hence, the rationale for this experiment, and its relevance to the in vivo situation, is genuinely lost on me.

Previous studies have already explored the functions of HAND2 and IL15 in DSCs, including a recent study showing that IL15 is a direct target gene of HAND2 in DSCs (Murata et al., 2020). Both HAND2 and IL15 are expressed in ESFs, including ESFs at the maternal-fetal inference in the Vento-Tormo et al. (2018) dataset. Thus, the aim of our experiments was to determine if HAND2 also regulates IL15 in ESFs, and if so, what the consequences of IL15 expression in ESFs might be (Figure 5). We apologize if this rationale was not clear in the manuscript, and recognize that the differences in the “dS1-3” vs. “ESF1-2/DSC” nomenclatures may have contributed to the confusion. We have edited the text to make it explicit that “dS1-2” are “ESF1-2”, that ESFs are present at the maternal-fetal interface until term, and therefore the rationale for our experiment was to explore the functions of HAND2 and IL15 in ESFs at the maternal-fetal interface.

See also comment regarding the renaming of DS subsets into ESF. In an undifferentiated state, these cells are not representative of gestational cells (with the possible exception that decidual senescence is characterized by progesterone resistance, i.e. re-activation of genes that are suppressed by progesterone).

As discussed in greater detail above (response to comment 2), the “dS1” and “dS2” subsets are stromal cells located in the decidua, but they are not decidualized stromal cells and have a gene expression profile of ESFs rather than DSCs (shown in Vento-Tormo et al. Figure 3a). Endometrial mesenchymal stem cells (Munoz-Fernandez et al., 2019) and ESFs (Suryawanshi et al., 2018) are also present in the endometrium during the first trimester and persist until term (Richards et al., 1995; Sakabe et al., 2020). Thus, undifferentiated cells (ESFs) are representative of a population of endometrial stromal cells present at the maternal-fetal interface throughout gestation. This is a very important point, and we thank the reviewers for indicating we did not explain this sufficiently. In the revised manuscript we have made this rationale explicit in the Materials and methods section describing the scRNA-Seq data, and have included the statement “However, whether HAND2 has functions in other endometrial stromal lineage cells such as ESFs, which persist in the pregnant endometrium till term (Sakabe et al., 2020; Richards et al., 1995; Munoz-Fernandez et al., 2019; Suryawanshi et al., 2018), but have received less attention than DSCs during pregnancy, is unknown” in the Results section describing the knockdown experiment to ensure that the reason we focus on ESFs rather than DSCs is clear.

More importantly, as HAND2 is critical for the identity of these cells, perhaps knockdown triggers a stress response? For example, from the data presented in Figure 3—source data 1 (it would be helpful to add gene names), on of the strongest up-regulated gene upon HAND2 knockdown is BLCAP2 [Log2(FC): 10.2], which encodes a protein that reduces cell growth by stimulating apoptosis.

This is such an interesting question! The answer is beyond the scope of this manuscript, but as recent evidence indicates that decidualization evolved from a stress response (Erkenbrack et al., 2018 [PMID: 30142145]), it is likely that many genes playing a role in ESF/DSC biology, decidualization in particular, are also involved in mediating stress responses. In addition, decidualization induces cell cycle arrest (Logan et al., 2012 [PMID: 22534328]) and BLCAP has been reported to arrest the cell cycle at the G1/S checkpoint (Zhao et al., 2016 [PMID: 26986503]), suggesting that an additional function of HAND2 is to regulate cell cycle progression via BLCAP.

We note, however, that while HAND2 plays an important role in ESF/DSC biology, Hand2 KO mice have ESFs and DSCs (albeit dysfunctional ones with respect to specific gene expression), making it unlikely that HAND2 is required for cell-type identity (Li et al., 2011 [PMID: 21330545]). In addition, BLCAP is highly expressed in many tissues (see Author response image 1), meaning that its ability to induce cell cycle arrest/apoptosis and its differential expression upon HAND2 knockdown do not necessarily indicate that the HAND2 knockdown triggers either a stress response or apoptosis. Given these data, a mechanistic connection between HAND2 recruitment into endometrial cell expression and cell cycle regulation is very exciting – we thank the reviewer for pointing out this association and will follow up with additional studies of BLCAP in the future.

We have also updated the table to include HUGO gene names in addition to ENSEMBL stable transcript IDs.

Author response image 1
BLCAP expression in the Human Protein Atlas (HPA) RNA-Seq datasets, with tissues sorted by expression level.

6) The authors illustrated the importance of examining the right cellular state: knockdown HAND2 in T-HESC increases IL15 expression whereas it is well established that HAND2 knockdown in decidual cells decreases IL15 expression. Further, IL15 is strongly induced upon decidualization and previous studies on primary endometrial stromal cells demonstrated that IL15 secretion is undetectable in undifferentiated cells whereas it is abundantly secreted upon decidualization (PMID: 31965050). Thus, we suggest that the should repeat HAND2 KD in decidualizing T-HESC and measure IL15 secretion in both states, with and without HAND2 knockdown, in future experiments.

We agree that cell state is important, but note that several studies have already performed this experiment. Shindoh et al., 2014, showed that KD of HAND2 in human DSCs abrogated IL15 expression, whereas most recently Murata et al., 2020, demonstrated that HAND2 and IL15 levels significantly increase in the secretory phase of human endometrium, and that HAND2 binds the IL15 promoter. Thus, the role of HAND2 in the regulation of IL15 in DSCs is well established. For that reason, we focused on ESFs, again with the logic that ESFs persist in the endometrium till term, but have received less attention than DSCs.

7) Figure 3B – it is unclear what is compared here: genes deregulated upon HAND2 knockdown in T-HESC versus knockdown NR2F2, FOXO1 and GAT2 in decidualized primary cultures? If this is the case, the comparison is not informative as it involves two different cell states. It is surprising that FOSL2 was not included in this analysis.

This is a good point. What we had intended to show was that HAND2 regulates a smaller set of genes than other TFs and factors that mediate decidualization reaction, but agree that comparing KD in ESFs to KD in DSCs is confusing. Therefore, we have removed Figure 3B and the associated text from the Results section.

8) We do not understand the relevance of the experiments described in Figure 5 to the context of gestation length or preterm birth. Trophoblast invasion will have been completed in the second trimester of pregnancy – what is the purpose/message of these experiments? What is the level of IL15 secreted by these cells? Again the T-HESC appear not decidualized – so, what is the relevance to either the midluteal implantation window or gestation?

We did not mean to imply a direct connection between these experiments and either gestation length regulation or preterm birth – those inferences are made through the GWASs of gestation length and birth weight. Instead, we wanted to determine if HAND2 regulation of IL15 in ESFs had similar or different effects than HAND2 regulation of IL15 in DSCs (for which the HAND2 -> IL15 connection is quite clear). As we point out above, ESFs persist in the endometrium during pregnancy until term. Thus, the purpose of these experiments was to use T-HESCs as a model of the persistent ESF population. In our cartoon model figure and discussion we propose that the balance between ESF- and DSC-derived IL15 shifts during pregnancy from the first trimester till term, and that this balance may be important for establishing the window of implantation and regulating gestation length (either directly or through recruitment of immune cells, etc.). We have edited the manuscript to make this logic more clear. In addition, we note that it has been proposed that a “decidual clock” may regulate the successful establishment and maintenance of pregnancy, such that severe decidualization defects lead to infertility, moderate defects lead to recurrent pregnancy loss/recurrent spontaneous abortion, and mild defects lead to preterm birth. We were interpreting our results within the context of this model, but had not made that explicit. We now include a discussion of our results in the light of this model (Norwitz et al., 2015).

IL15 is expressed in ESFs with TPM=15.73, while in DSCs TPM=67.60, but unfortunately we have not quantified protein expression levels in these cells.

9) What is the evolution of IL15 expression at the maternal-fetal interface? Does it parallel HAND2?

IL15 is not among the unambiguously reconstructed genes and is dropped from the parsimony analyses.

10) Of the 149 genes that unambiguously evolved endometrial expression why was only HAND2 analyzed? We are not suggesting that each gene be followed up with this level of rigor but would you hypothesize that each of the genes you identified play a role in eutherian reproduction? Or are there other major innovations that some of these genes may be associated with? How frequently would this pattern occur by chance?

The 149 genes that unambiguously evolved endometrial expression were significantly enriched in pathways related to the immune system, as well as human phenotype and biological process GO terms related to regulation of immune system. These data suggest that the recruited genes play immune regulatory roles at the maternal-fetal interface, possibly in establishing maternal immunotolerance (to highlight these observations we have added a new “WordCloud” of enriched terms to Figure 1 – now Figure 1B). It is not clear how to estimate the number of genes one would expect to evolve endometrial expression by chance. We could generate parsimony reconstructions for other tissues to infer if greater or fewer gene expression gain/loss events occurred in the endometrium compared to other tissues. However, because it is unclear what would be an appropriate null model for such a comparison, we have avoided making claims that there is something special about the number of genes that evolved endometrial expression and focused on their functions.

HAND2 was selected for more detailed analyses because it has been previously shown to be important for silencing estrogen signaling and implantation, which are derived traits in Eutherians. We have added a description of this rationale to the Results section.

11) Figures 2F and 4F – there appears to be a gap in the data points during the third trimester (which looks like it says "thirdr"). Is there still a negative trend if each section is analyzed independently as if they were independent datasets? Aka could this linear trend be composed of two separate trends instead?

Unfortunately, there are no samples in the third trimester (the “thirdr” typo has been corrected). We have explored additional GEO and SRA datasets to determine if there are similar data on gene expression in the decidua throughout gestation that include the third trimester, but as far as we are aware, this is the only such dataset. However, we do not believe that the inference of HAND2 and IL15 down-regulation is spurious because of missing third trimester data. For example, we have re-analyzed the data comparing expression of HAND2 and IL15 in two groups corresponding to early gestation and term (14-24 vs. 37-40 weeks). The statistical test for significant differences in this case is not based on the linear regression of expression levels by gestation week.

Author response image 2

The Gardner-Altman estimation plots in Author response image 2 show the mean difference between relative HAND2 expression (left) and IL15 expression (right) at weeks 14-24 (blue dots) and weeks 37-40 (orange dots) of gestation. The relative expression of each gene for both gestation length groups is plotted on the left axes; the mean difference is plotted on floating axes on the right as a bootstrap sampling distribution. The mean difference is depicted as a black dot; the 95% confidence interval (CI) is indicated as a vertical error bar. The unpaired mean difference between HAND2 expression at 14-24w and 37-40w is -1.45 [95.0% CI: -1.85 – -0.989]; the P-value of the two-sided permutation t-test is 0.0004. The unpaired mean difference between IL15 expression at 14-24w and 37-40w is -0.816 [95.0% CI: -1.13 – -0.578]; the P-value of the two-sided permutation t-test is 0.002. The effect sizes and CIs are reported above as: effect size [CI width: lower bound – upper bound]. 5000 bootstrap samples were taken; the confidence interval is bias-corrected and accelerated. The P-values reported are the likelihoods of observing the effect sizes, if the null hypothesis of zero difference is true. For each permutation P-value, 5000 reshuffles of the control and test labels were performed.Thus, we believe that our inference that the expression of both HAND2 and IL15 decreases throughout gestation is robust, but without data from the third trimester we cannot make a claim about the pattern of decrease. For example, is it gradual from implantation to term, or is there a precipitous decrease during the onset of the third trimester that remains low until term? We have edited the manuscript to reflect this uncertainty – e.g. changing “decreases in expression until term” to “decreases in expression from the first trimester to term”.

12) Please provide the binary encoded data used for this analysis as it could be readily used by other research groups for similar analysis. The custom database of genes implicated in preterm birth would also be a useful dataset.

We have included the binary encoded data along with ancestral state reconstructions (Figure 1— source data 2) and the custom database of genes implicated in preterm birth (Figure 1—source data 9) as source data supplements to Figure 1.

13) It was helpful to hear from one of the authors that the known HAND2 gene wasn't knocked out in mice, so it was an easy early pregnancy gene to start with. Perhaps this should be stated in the revised manuscript?

We apologize if we were unclear. Previous studies have generated mice with a conditional knockout of Hand2 in uterine tissue (Jones et al., 2013; Li et al., 2011). These mice have implantation defects, thus while the effects of Hand2 in early pregnancy can be studied, Hand2 functions in late pregnancy cannot. We have clarified this in the revised manuscript.

14) To reproduce the study, there were a couple of questions around the production of the conditioned media including, how long were the cells incubated in the media and what was the volume of the media use. Please include this information in the revised manuscript.

500μl of media conditioned for 12 hrs – this information has been added to the Materials and methods section.

15) Can you further explain why the opossum was used to measure the estrogen levels?

We used opossum (Monodelphis domestica) as a Marsupial model because it lacks maternal recognition of pregnancy and thus is a good representative of the Therian common ancestor. In contrast, other Marsupials such as tammar wallaby have derived traits related to pregnancy, including delayed ovulation and independently evolved maternal recognition. To ensure this rationale is clear, we have expanded on why we selected opossum as a model Marsupial in the Results sections.

16) The relationship between ESR1 and HAND2 is a little unclear. Is ESR1 expression correlated with HAND2 expression in all species studied?

ESR1 is expressed in the endometria of all species studied. We cannot address whether ESR1 expression correlated with HAND2 expression because we don’t have non-pregnant samples from all studied species.

https://doi.org/10.7554/eLife.61257.sa2

Article and author information

Author details

  1. Mirna Marinić

    Department of Human Genetics, University of Chicago, Chicago, United States
    Present address
    Department of Organismal Biology and Anatomy, University of Chicago, Chicago, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7037-8389
  2. Katelyn Mika

    Department of Human Genetics, University of Chicago, Chicago, United States
    Present address
    Department of Organismal Biology and Anatomy, University of Chicago, Chicago, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Methodology, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2170-9364
  3. Sravanthi Chigurupati

    Department of Human Genetics, University of Chicago, Chicago, United States
    Present address
    AbbVie, North Chicago, United States
    Contribution
    Formal analysis, Writing - original draft
    Competing interests
    No competing interests declared
  4. Vincent J Lynch

    Department of Biological Sciences, University at Buffalo, Buffalo, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    vjlynch@buffalo.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5311-3824

Funding

Burroughs Wellcome Fund (Preterm Birth Initiative 1013760)

  • Vincent J Lynch

March of Dimes Foundation (UChicago-Northwestern-Duke Prematurity Research Center)

  • Vincent J Lynch

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

The authors thank the following researchers for providing pregnant endometrial samples: GP Wagner (Yale University) – Monodelphis domestica; RR Behringer (The University of Texas MD Anderson Cancer Center) – Carollia perspicillata; BC Paria (Vanderbilt University School of Medicine) – Mesocricetus auratusMus musculus; AT Fazleabas (Michigan State University) – Papio anubis; DK Merriman (University of Wisconsin Oshkosh) – Ictidomys tridecemlineatus. We are also grateful to AM Bamberger (University Hospital Eppendorf) for providing the trans-well migration assay protocol, D Glubb (QIMR Berghofer Medical Research Institute) for assistance in interpreting the HiChIP assay data, R Beaumont (University of Exeter Medical School) and RM Freathy (University of Exeter) for assistance with interpreting maternal-fetal birth weight GWAS data, and VL Hansen (University of New Mexico) for providing details on stages of opossum RNA-Seq data. VJL thanks the Department of Human Genetics at The University of Chicago for support during the planning and preliminary data generation phase of this work. MM thanks Michael Sulak for the help with editing the manuscript.

Senior Editor

  1. George H Perry, Pennsylvania State University, United States

Reviewing Editor

  1. Antonis Rokas, Vanderbilt University, United States

Reviewer

  1. Abigail LaBella

Publication history

  1. Received: July 20, 2020
  2. Accepted: January 29, 2021
  3. Accepted Manuscript published: February 1, 2021 (version 1)
  4. Version of Record published: March 9, 2021 (version 2)

Copyright

© 2021, Marinić et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,365
    Page views
  • 230
    Downloads
  • 3
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

  1. Further reading

Further reading

    1. Evolutionary Biology
    2. Epidemiology and Global Health
    3. Microbiology and Infectious Disease
    4. Genetics and Genomics
    Edited by George H Perry et al.
    Collection

    eLife is pleased to present a Special Issue to highlight recent advances in the growing and increasingly interdisciplinary field of evolutionary medicine.

    1. Developmental Biology
    2. Evolutionary Biology
    Tom Dierschke et al.
    Research Article

    Eukaryotic life cycles alternate between haploid and diploid phases and in phylogenetically diverse unicellular eukaryotes, expression of paralogous homeodomain genes in gametes primes the haploid-to-diploid transition. In the unicellular Chlorophyte alga Chlamydomonas KNOX and BELL TALE-homeodomain genes mediate this transition. We demonstrate that in the liverwort Marchantia polymorpha paternal (sperm) expression of three of five phylogenetically diverse BELL genes, MpBELL234, and maternal (egg) expression of both MpKNOX1 and MpBELL34 mediate the haploid-to-diploid transition. Loss-of-function alleles of MpKNOX1 result in zygotic arrest, whereas loss of either maternal or paternal MpBELL234 results in variable zygotic and early embryonic arrest. Expression of MpKNOX1 and MpBELL34 during diploid sporophyte development is consistent with a later role for these genes in patterning the sporophyte. These results indicate that the ancestral mechanism to activate diploid gene expression was retained in early diverging land plants and subsequently co-opted during evolution of the diploid sporophyte body.