The timing of parturition (the process of birth) is critical for survival of the neonate and the infant’s future health trajectory (Goldenberg et al., 2008; Howson et al., 2009; Liu et al., 2015; Muglia and Katz, 2010). This time in normal healthy pregnancy is referred to as term and in humans occurs at 37–42 completed weeks of gestation; the majority of spontaneous births in singleton human pregnancies take place during this window. Furthermore, neonatal death (death in the first 28 days of life) is lowest, and thus survival and fitness are highest, for neonates born after 37 and before 42 completed weeks of gestation (Figure 1). Reflecting these survival relationships, the current definition of a ‘full term’ pregnancy is now 39–40 weeks of completed gestation (https://www.acog.org/clinical/clinical-guidance/committee-opinion/articles/2013/11/definition-of-term-pregnancy).

Figure 1

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The observation that the peak of birth timing in women coincides with the trough of neonatal mortality suggests that developmental and physiological mechanisms that optimize the timing of parturition have likely been under strong selection through evolution. Similarly, genetic polymorphisms in mothers and newborns that contribute to optimization of parturition timing may too be under the influence of selection. Of course, the optimal time for birth is also influenced by an organism’s life history and ecology, such as litter size, maternal habitus, circadian and seasonal activity patterns, and social and environmental exposures, all of which vary widely across mammals. Therefore, it is not surprising that much diversity exists in the physiology of pregnancy and birth timing among mammals. This is evidenced by the observation that genes associated with reproduction exhibit high levels of sequence divergence among eutherian mammals, similar to those associated with adaptive immune system development and function (Chimpanzee Sequencing and Analysis Consortium, 2005; Waterston et al., 2002).

It is plausible, therefore, that the biological processes that determine the timing of human parturition are specific for the Homo lineage. This lineage specificity would explain why cross-species observations, although revealing some principles of birth timing, have not significantly advanced understanding of human birth timing. One reason for this evolutionary divergence in strategies between humans and other species may be the unique increase in brain size in humans, even in comparison to other primates, over the last few million years and the physical or metabolic constraints encountered because of it (Pavličev et al., 2020). This dearth of knowledge has clinical and sociological implications because it has slowed advances in development of therapies to prevent preterm birth (i.e. birth before the 37th week of gestation), which is the leading cause of death for newborns (Howson et al., 2012) and children under 5 years of age (Liu et al., 2015). For infants that survive past 5 years, preterm birth leads to increased incidence of lifelong health impairments, such as growth, neurological, and sensory deficiencies (Committee on Understanding Premature Birth and Assuring Healthy Outcomes Board on Health Sciences Policy, 2007). Despite the recognized importance of term pregnancy for optimizing reproductive fitness and lifelong health, and the enormous cost of preterm birth, understanding of the molecular signals that control human birth timing remains scant (Committee on Understanding Premature Birth and Assuring Healthy Outcomes Board on Health Sciences Policy, 2007). Importantly, not all populations are equally impacted by preterm birth, with African American women experiencing an especially increased burden (Collins and David, 2009; Kistka et al., 2007a). Social determinants of health disparities, and the consequences of racism, (Slaughter-Acey et al., 2016; Murrell, 1996) must be incorporated into efforts to improve outcomes for all populations. In this review, we focus on the biology of birth timing determination, recognizing that this biology is strongly influenced by social and environmental parameters.

One approach to addressing our knowledge gap on mammalian parturition is to develop a conceptual evolutionary framework. Birth timing is a key event in the reproductive cycle of eutherian mammals and as such is likely subject to past and ongoing selective pressure to optimize reproductive efficiency with respect to organisms’ life histories, ecologies, and social and environmental exposures. Although these selective pressures have given rise to the diversity in the physiology of pregnancy and birth timing that is observed among mammals, a conceptual framework to describe the processes common to all eutherian mammals can be developed based on six core principles:

1. pregnancy is a temporary state that imparts survival risk for the female and her fetus/neonate and as such must eventually end through expulsion or resorption of the conceptus;

2. retention of the conceptus requires that the parturition process is dormant or actively blocked for a specific amount of gestation time. The steroid hormone progesterone is a conserved endocrine signal across viviparous species that serves this purpose (Rothchild, 2003; Young et al., 2010);

3. parturition may be initiated by multiple pathways, some of which are part of the normal timing process and provide complementary, partially overlapping mechanisms, while others (e.g. pathways associated with response to infection) may override pregnancy maintenance signals to provide fail-safe mechanisms that serve the survival interests of the mother (and her future reproductive potential) and the fetus/neonate (Rothchild, 2003; Young et al., 2010; Challis, 1980; Challis and Mitchell, 1981; Mitchell and Taggart, 2009);

4. each mammalian species has evolved its own strategy for parturition timing, which may or may not be conserved in other species. Compared to other organs or systems, reproductive organs (e.g. uterus and placenta) are more recently evolved; new functions or novel cell types in these organs are thought to have evolved from existing tissues by rewiring existing genetic regulatory networks; (Kin et al., 2015; Lynch et al., 2011; Lynch et al., 2004; Wagner and Lynch, 2005; Wagner and Lynch, 2010; Griffith and Wagner, 2017; Plunkett et al., 2011; Wildman et al., 2006; Zhang et al., 2020)

5. pregnancy-associated traits, including parturition, evolved ‘on’ pre-existing cardiovascular, metabolic, and immune systems, and the reproductive strategy coordinates with these systems (Bainbridge, 2014). At the genetic level, these traits are influenced by many genetic variants with interactions between genes. The polygenic control of pregnancy-associated traits may facilitate adaptation and evolutionary robustness (Gibson and Lacek, 2020). The evolution of pregnancy-associated traits may have diverse effects on other systems and conversely, should be constrained by genetic correlations with other traits; and

6. pregnancy-associated traits, including parturition, are influenced by both maternal and fetal genomes and parental environmental effects (Figure 2). The involvement of the maternal and fetal genomes and the parental environmental and epigenetic cross-generational effects have profound evolutionary implications and have likely experienced both conflict and coadaptation (Miska and Ferguson-Smith, 2016; Badyaev and Uller, 2009). For example, as evidenced by the consequences of the Dutch famine, subsequent generations’ pregnancy outcomes were adversely affected (Roseboom et al., 2011).

Figure 2

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The core principles listed above are shared across eutherian mammals due, in part, to the ancestral evolution of viviparity—to understand the evolution and diversity of parturition we must uncover the evolutionary substrate upon which it was formed. The hallmark traits of eutherian viviparity are: (1) retention and gestation of the fertilized egg(s) in the female reproductive tract (uterus); (2) development of a placenta that facilitates the transfer of oxygen and nutrients from the maternal compartment to the conceptus, and (3) delivery of the fetus and its placenta via the process of parturition at a specific stage of gestation. Each trait is critical for the success of viviparity, and therefore has likely been under strong selective pressure to optimize reproductive fitness (Mitteroecker et al., 2017; Mitteroecker et al., 2016). The course of evolution among mammalian viviparous species, which has been influenced by both selective and neutral processes, has produced considerable variation in diverse reproductive traits, such as in the number of ovulated and retained eggs, the structure of the uterus, the anatomy of the maternal-placental interface, the structure and function of the placenta and its effect on maternal physiology, the rate of embryo/fetal development and functional maturity of the neonate, and the signals that lead to parturition (Rothchild, 2003; Swaggart et al., 2015; Plant and Zeleznk, 2015).

Phylogenetic analyses suggest that viviparity originated from oviparity (expulsion of the egg soon after fertilization and its independent development in the external environment) in at least 150 lineages, including in mammals, fish, and reptiles (Blackburn, 2015). The evolution of viviparity with the establishment and maintenance of prolonged gestation characteristic of eutherians may inform potential models of parturition initiation. The evolution of invasive placentation in eutherians that allowed for prolonged intrauterine gestation differentiates them from marsupials, which develop very transient placentas, and monotremes, which are oviparous (Wildman et al., 2006; Chavan et al., 2016). Elegant studies by Wagner and colleagues have shown that eutherian implantation evolved from the marsupial attachment reaction, with similar proinflammatory gene expression signatures (Griffith et al., 2017). An innovation in eutherians was the down-regulation of inflammation after embryo attachment to the maternal endometrium reflected in their endometrial stromal fibroblast transcriptomic profiles in comparison with marsupials (Kin et al., 2016). Additional anti-inflammatory mechanisms likely evolved in the fetus or placenta as suggested by the expansion of the tripartite-motif family of genes and their ability to finely tune inflammation during placentation (Zhang et al., 2020). Considering these evolutionary innovations that allowed for the establishment of eutherian gestational prolongation suggests two potential different strategies that natural selection could influence to determine birth timing. One strategy would be to suppress the specific anti-inflammatory signals that allowed sustained placentation to be established. The other strategy would be for selection to act on other molecular targets that would overcome the anti-inflammatory signals that down-regulated the proinflammatory signals requisite for the attachment reaction. The genes mediating these effects across species would themselves be subject to the diverse evolutionary pressures as suggested by recent genome wide association studies for human gestational duration (LaBella et al., 2020).

Parturition, and especially its timing, is a mission-critical event for the success of mammalian viviparity. Normal parturition occurs at a specific time referred to as term, when the fetus is sufficiently mature to survive as a neonate, and the mother is able to provide care for the neonate’s nutrition, protection and physiologic stability, while preserving her own fitness. Timing mechanisms for parturition have likely been selected to optimize reproductive fitness based on benefits to the mother and fetus for the current pregnancy, and benefits to the mother’s survival and future reproductive potential (note that these two are not always aligned). One important general association with birth timing is its correlation with body size at birth (Phillips et al., 2015). This association may reflect energy utilization particularly due to the developing fetal brain (Dunsworth et al., 2012) or physical constraints such as infant size related to the size of the birth canal (Rosenberg and Trevathan, 2002; Rosenberg and Trevathan, 2001).

Studies utilizing concordance in birth timing in offspring of twins, or family-based segregation or epidemiology, suggest that 30–40% of the variation in human birth timing is due to genetic factors, and these reside largely in the maternal genome (Kistka et al., 2008; Plunkett et al., 2009). The ‘compound genome’ of pregnancy is unique when considering the maternal-fetal unit during gestation, consisting of DNA composition of 3 distinct haplotypes. How these unique or shared haplotypes interact to produce the 30–40% variation in human gestation length is only beginning to be explored (Zhang et al., 2015; Zhang et al., 2018; Figure 2). The remaining 60–70% of the variation is thought to arise from environmental influences of uncertain origin. These may include nutrition, infectious disease, health behavior, and social circumstances/stress. Furthermore, recent genomic investigations have demonstrated a causal relationship between single nucleotide polymorphisms (SNPs) that associated with adult height and gestation length in humans such that taller maternal height and its genetic determinants leads to longer gestation (Zhang et al., 2015). Other maternal traits, such as fasting blood glucose and blood pressure, have also been shown to causally determine length of gestation or fetal size at birth in humans (Chen et al., 2020). Recent ability for GWAS comparison of those loci that uniquely determine gestational duration with those that have been associated with birth weight provide an interesting avenue moving forward to disentangle the underlying genetics responsible for the relationship of gestational duration and birth weight (Early Growth Genetics (EGG) Consortium et al., 2018; Zhang et al., 2017).

Do species other than humans exhibit a significant frequency of preterm birth? This question is difficult to answer since preterm birth in humans is an arbitrary definition. If we simply scale the assignment of preterm birth based upon duration of term gestation (37 out of 40 weeks, or 92.5% of gestation) then other eutherian mammals also experience preterm birth (Phillips et al., 2015). Frustratingly, the most commonly studied, genetically tractable animal model, the mouse, does not appear to exhibit spontaneous preterm birth (Phillips et al., 2015). Does this reflect laboratory selection in strains currently utilized or a fundamental trait of rodents? This question merits investigation. Other non-traditional animal models that demonstrate spontaneous preterm birth, such as mammals used in livestock (Nielsen et al., 2016; Fthenakis et al., 2012; Scott et al., 2008; Asher, 2007), could be utilized to investigate preterm birth and low birth weight pregnancies in the future.

Pregnancy is the physiologic state in eutherian mammals in which a fertilized egg is retained and gestated in the cavity of the uterus. For pregnancy to be maintained, the smooth muscle of the uterine wall (the myometrium) remains relaxed, quiescent, and grows and distends to accommodate growing conceptus, whereas the uterine cervix remains rigid and closed. In addition, maternal physiology adapts to provide nutrients and oxygen to the developing fetus. Remarkably, a conserved trait in all viviparous mammals examined so far is that the establishment and maintenance of pregnancy are dependent on the steroid hormone progesterone (P4) (Corner and Allen, 1929; Csapo, 1956). As its name implies, P4 is a pro-gestation hormone. It promotes myometrial quiescence, cervical closure, immunologic tolerance at the maternal-fetal interface and, importantly, blocks parturition. Remarkably, the embryo-retaining actions of P4 have been conserved through multiple viviparous lineages, including lizards (Jones, 2017).

P4 is synthesized by enzymatic modification of cholesterol. At the time pregnancy is established, P4 arises from the corpus luteum (CL) of the ovary. Some species, such as rodents, maintain ovarian P4 production as the sole source of P4 to maintain pregnancy, and parturition is initiated by loss of P4 due to CL regression (Ratajczak et al., 2010). In rodents, regression of the maternal CL is induced by prostaglandin F2α (PGF_2α) produced by the uterine endometrium acting on its receptors on cells in the CL. Thus, term parturition in rodents is induced by PGF_2α production in the endometrium. In other species, such as sheep and primates, the source of P4 for pregnancy maintenance shifts from the CL to the placenta (Mesiano et al., 2014; Tuckey, 2005). In humans, this occurs at approximately the 10th week of gestation. In pregnancies associated with fetal deficits, and inadequate function of fetal-placental-maternal signaling, miscarriage commonly occurs at this ovarian-placental progesterone transition point (Baird, 2009). In sheep, as in rodents, maternal circulating P4 declines acutely (due to decreased P4 production by the placenta), prepartum to promote parturition (Liggins et al., 1977). This, however, does not occur in primates. Although maternal blood P4 levels vary widely among anthropoid primates (New World monkeys, Old World monkeys, and apes), a conserved trait in this group is that parturition occurs without systemic P4 withdrawal (Ratajczak et al., 2010). Nonetheless, disruption of P4 signaling by treatment with the P4 receptor (PR) antagonist, RU486, induces parturition in all species examined so far, including humans (Garfield and Baulieu, 1987). One explanation for this inconsistency is that primate parturition involves a functional P4 withdrawal whereby target cells in the uterus become refractory to the P4 block to labor. Studies suggest that this occurs by multiple mechanisms including local metabolism of P4 to an inactive form (i.e. tissue or target cells P4 withdrawal) (Nadeem et al., 2016) and alteration in PR transcriptional activity in uterine target cells (Mesiano et al., 2014; Wu and DeMayo, 2017).

The control of human birth timing remains enigmatic, largely because of our limited ability to precisely predict its occurrence based upon absolute days of gestation. In contrast, the timing of birth in other species, exemplified by sheep and mice, is predictable and the underlying regulatory signals have been defined. For example, pioneering studies by Liggins, 1974 demonstrated that parturition in sheep is initiated by increased activity of the fetal hypothalamic-pituitary-adrenal axis to produce a surge of cortisol that decreases P4 production by the placenta leading to systemic P4 withdrawal that initiates parturition (Figure 3 and Table 1). Importantly, the cortisol surge also induces functional maturation of fetal organ systems, and especially surfactant production by the lungs, in preparation for life outside the uterus. Disruption of the fetal HPA inhibits ovine parturition and treatment with cortisol into the fetus initiates parturition. Thus, the ovine mechanism for birth timing is solely controlled by cortisol produced by the fetal HPA axis that coordinates the timing of birth with fetal maturation and readiness to exist as a neonate.

Figure 3

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In contrast, glucocorticoids do not induce labor in mice or humans. In mice, parturition is initiated after upregulation of endometrial cyclooxygenase (COX)–one encoded by PTGS1, which subsequently generates prostaglandin F2α (Gross et al., 2000; Gross et al., 1998; Sugimoto et al., 1997). PGF2α from the endometrium then acts on the corpus luteum of the murine ovary to induce luteolysis, a fall in serum progesterone and the induction of contractile proteins in the uterine myometrium (Figure 3 and Table 1).

Cortisol plays a key role in promoting fetal organ maturation in humans, however, parturition in women is not initiated by fetal HPA activity. Although the work of Liggins and colleagues in sheep was groundbreaking for understanding hormonal pathways that may promote parturition, the specific pathways operating in the sheep do not appear to operate in the same way in women (Liggins et al., 1977). The ancestral initiating signal for determining the time for mammalian birth remains elusive and as a consequence of this knowledge gap, rational effective interventions to prevent preterm labor and preterm birth in humans have been limited. Nonetheless, the work of Liggins and colleagues in sheep led to the widespread clinical use of synthetic glucocorticoid therapy to promote fetal lung maturation in women that are either experiencing preterm labor and that are at risk for preterm birth, which significantly improved survival of preterm neonates.

Beyond the glucocorticoid signal, several labor-permissive or promoting signals have been identified across mammals. Foundational among these are estrogens (mainly estradiol) that are also steroid hormones derived from cholesterol, whose abundance increases at the end of gestation in most species and act to augment uterine contraction by inducing the expression of genes in uterine smooth muscle cells encoding factors that increase contractility and excitability. For example, in the rat and mouse estradiol induces the expression in myometrial cells of GJA1 that encodes connexin-43 a major subunit of intracellular tight gap junctions that facilitate contractile synchrony between myometrial cells, and OXTR that encodes the oxytocin receptor and increases myometrial sensitivity of the uterotonic actions of oxytocin., PTGFR encodes the prostaglandin FP receptor and PTGS2 that encodes cyclooxygenase-2 (COX-2) and generates critical parturition proinflammatory prostanoids, such as PGE2 and PGF2alpha, that induce cytokines such as interleukin-1 that are also pro-labor (Keelan et al., 2003; Ratajczak and Muglia, 2008; Smith, 2007).

Uterine tissue-level inflammation is associated with normal term parturition across mammals. However, less clear is whether proinflammatory signals are involved in the parturition initiation process from those species that do not undergo luteolysis and systemic progesterone withdrawal or act to facilitate or accelerate the process once initiated. In primates, the inflammatory cascade is apparent but may come after the proximal initiator of parturition (Liu et al., 2019). For example, recent genome-wide association findings in humans identify the fetal pro-inflammatory locus encompassing the IL-1 family on chromosome two as significantly associated with gestational duration. Interestingly, the association with prolonged gestation, not preterm birth, suggests that the locus contributes to promoting the birth process downstream of the initiating signals; thus, initiating and facilitating signals may be distinct (Liu et al., 2019).

While the leading cause of perinatal death is preterm birth, postterm birth (delivery at gestational age more than 294 days or 42 full weeks of completed gestation) also places the newborn at higher risk for perinatal mortality and neonatal acute and long-term adverse health effects (Kortekaas et al., 2015; Seikku et al., 2016; Linder et al., 2017; Figure 1). Viewing preterm and post-term birth as the two tails of the gestational age distribution, it is reasonable to hypothesize that they may reflect opposite regulatory directions of action of the same pathophysiological pathways in at least some circumstances. Therefore, understanding the mechanisms for postterm birth might potentially yield insights into underlying mechanisms of normal and preterm parturition as well.

As in preterm birth, recent studies have shown potential genetic contributions to postterm birth, such as maternal recurrence and familial risk, ethnicity and common variant associations (Morken et al., 2011; Kistka et al., 2007b; Schierding et al., 2018; Oliver et al., 2018) For example, a mother born postterm has a 49% higher relative risk to have a postterm pregnancy, whereas a father delivered postterm contributes 23% increased risk. The risk is even higher when both the mother and father were born postterm (Morken et al., 2011). In addition, women with postterm delivery in their first pregnancy have significantly higher risk of recurrence in subsequent pregnancies (Morken et al., 2011). A recent genome-wide association study of prolonged gestation in the Northern Finland found a significant association with postterm birth in an intronic region within the ADAMTS13 gene, also known as von Willebrand factor-cleaving protease, that is involved in blood clotting (Schierding et al., 2018). As in preterm birth, there is also evidence for prolonged gestation duration in humans associated with geographic/genetic ancestry. For example, women of Somali ancestry have a significantly increased risk for prolonged gestation even after adjustment for potential confounding factors (Oliver et al., 2018).

The insights derived from recent evolutionary genomic analyses of mammalian pregnancy and genome-wide analyses of human populations and the identification of genes involved in gestation length described above showcase both the depth of knowledge on mammalian parturition as well as why its mechanisms largely remain mysterious. In particular, our knowledge of parturition mechanisms in humans is complicated by both the likelihood of lineage-specific mechanisms and our limited ability to experimentally interrogate human pregnancy due to ethical and technological considerations. While currently available data do not reveal a complete picture of the initiation of term and preterm parturition, they do allow us to develop a conceptual evolutionary framework upon which to test future hypotheses. As a first step toward establishing an evolutionary framework for the timing of mammalian parturition, we outline four theoretical models for how the onset of parturition is determined in a general way around core principles (Figure 4). These four models provide examples of testable hypotheses.

Figure 4

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It is important to note that the four models aim to explain the maintenance of pregnancy and initiation of parturition, which should be distinguished from the contractile mechanism to expel the fetus. The contractile mechanism is downstream of the initiation signal, is likely to involve redundant uterotonic pathways, and is probably going to be much more challenging to target effectively for preterm birth prevention compared to initiator pathways (Goldenberg et al., 2008). We encourage researchers to test these models or other models with empirical data to determine detailed mechanisms, confirming, refining or refuting their predictions, including how social stress, racism, and health behaviors affect risk for preterm birth.

Testing the four models

Can the four proposed models be experimentally distinguished? A useful starting exercise is to determine if existing data refute one or more of the models. Significant divergence in mechanisms may exist across species, so whether one species follows a specific model cannot be completely understood by findings in another. For example, one clear piece of evidence that argues against the Fixed Maternal Clock Model comes from examining the timing of birth in cross-species hybrids. Matings between female horses and male donkeys produce mules. Under the Fixed Maternal Clock Model, the time to birth in such pregnancies would be expected to reflect the mother’s clock. However, mules are delivered on average between (11.4 months) when a horse (11.2 months) and donkey (12 months) would normally deliver (Giger et al., 1997), consistent with expectations that both maternal and fetal genomes and parental effects govern the timing of parturition. To further distinguish between maternal and fetal fixed clocks regulating birth timing, generating pregnancies where maternal and fetal gestational duration are discordant may prove revealing. One such experiment could be to produce females that are pseudopregnant for different temporal windows, and transfer fertilized embryos of different gestational ages into their uteri. This experiment would test whether the day of delivery reflects the gestational duration of the mother or the fetus. A limitation of this experiment is the potential of these pre-implantation embryos to synchronize or re-set development at the time of implantation, which could be measured by counting somite number several days into the pregnancy (Tam, 1981) or using other staging measures.

In sheep, fetal hypothalamic-pituitary-adrenal axis activation is essential for parturition and may suggest a fetal fixed clock. However, fetal adrenal activation may still be downstream of the true parturition initiating signal and represent a downstream effector pathway. Rodent pseudopregnancy, the state which arises when receptive females are mated to sterile males, lasts approximately one-half the duration of a normal, fetus-containing pregnancy (Sulila et al., 1988). This suggests that fetal signals must be contributing to pregnancy maintenance through to the normal endpoint. However, this model does not establish evidence of a fixed fetal clock to end pregnancy.

A classic physiological approach to dissecting stimulatory or inhibitory signals influencing a phenotype, such as in our Models 2–4, is to perform cross-circulation, or parabiosis, experiments. These experiments link the circulations of two animals to allow circulating factors to be shared between them. As applied to rat gestation and parturition, studies have been performed which revealed the ability of a gravid female 2 or 3 days earlier in gestation (i.e. mated later) to delay the onset of birth in the gravid female that had been impregnated earlier (Mantalenakis and Ketchel, 1966). Interestingly, gravid females 4 days earlier in gestation than the partner did not delay the onset of labor (Mantalenakis and Ketchel, 1966). This suggests an inhibitory factor from the earlier gestation animal that rises through pregnancy is capable of inhibiting parturition. These studies did not conclusively identify such a factor, but the findings are consistent with the known pattern of P4 rise during gestation and the ability of P4 supplementation to delay the onset of labor. The systemic P4 withdrawal known to cause mouse and rat parturition is thus supported by these studies (Pepe and Rothchild, 1974; Winchester et al., 2002). What this approach did not reveal was the upstream signal that initiated P4 withdrawal that arises from local prostaglandin production from the endometrium as revealed through later genetic and other physiological studies (Winchester et al., 2002). Similar parabiosis approaches have been used in guinea pigs, which do not display systemic P4 withdrawal or labor extension with P4 supplementation, which differs from rats and mice. Those studies demonstrated circulating signals that maintain uterine quiescence but did not report consequences for birth timing (Porter, 1972).

The above methods for testing the proposed models for parturition initiation, provide interesting and useful information, although each has its own limitations. We propose that applying an evolutionary, comparative framework will complement these methods, together leading to otherwise unobtainable insights. It is generally accepted that the initiator of mammalian parturition must be under strong selective pressure to optimize reproductive fitness (Rosenberg and Trevathan, 2002; Haig, 1993). Indeed, using robust human genome-wide association findings from the maternal genome for gestational duration and preterm birth risk, a recent study showed that preterm birth-associated regions harbored diverse evolutionary signatures, including those of accelerated evolution, evolutionary conservation, long term balanced polymorphism, and population differentiation (LaBella et al., 2020). In addition, control of the parturition cascade would be expected to diverge across species depending upon their reproductive ecology and environmental exposures. These divergent control mechanisms may also reflect the theoretical evolutionary advantages of different models we put forward above. For example, the Fixed Clock model could be more resistant to transient environmental or biological perturbations. The Parturition Block and Parturition Stimulation models, alternately, could enable sensing of changes during pregnancy and immediate response by feedback loops to optimize pregnancy in more dynamic fashion.

Evolutionary approaches that collect, curate, and compare the same pregnancy-related data across species promise to be particularly informative, especially to shed light into the innovations leading to possibly the re-wiring of regulatory network of preexisting genes not previously involved in parturition into pregnancy regulation. The reproductive strategy differences and consequences of ecologic niche and environmental exposures will further inform the mechanisms that prompt birth. We return to principal proposed by the Danish physiologist Krogh, 1929 that “For such a large number of problems, there will be some animal of choice or a few such animals on which it can be most conveniently studied’ to apply to parturition initiation. The ideal ‘animals of choice’ would have sequenced and annotated genomes, the ability to isolate and characterize blood and tissues through gestation in the mother and fetus, and informative phenotypes that could be together analyzed to reveal molecular pathways that determine the duration of gestation; at least for the species in question. Genome editing technologies could then be used for functional validation.

Considering these potential animals of choice in an evolutionary framework promises to be particularly revealing. We will provide one example in the Muridae family that could be explored. The spiny mouse (Acomys carihinus), Mongolian gerbil (Meriones unguiculatus), and house mouse (Mus musculus) have evolutionary divergence times from one another of 18–24 million years (Kumar et al., 2017; Figure 5). Remarkably, the spiny mouse has a gestation duration of 39 days and delivers precocial neonates (Haughton et al., 2016), while house mice (Murray et al., 2010) and Mongolian gerbils (Cheal, 1983) have gestational durations of approximately 19.3 days and 25 days, respectively, and deliver altricial neonates.

Figure 5

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In Figure 5, we show other characteristics of these species relevant to pregnancy and birth timing. Importantly, each of these species has sequenced genomes (https://www.ncbi.nlm.nih.gov/nuccore/PVKX00000000.1, https://genome.ucsc.edu/cgi-bin/hgGateway, Cheng et al., 2019). Comparison of evolutionary signatures in these recently diverged species may reveal the genomic alterations that led to the prolonged gestation in the spiny mouse; these alterations can subsequently be functionally dissected through dense longitudinal -omics experiments across multiple tissues, genome editing, and other commonly used modern approaches. In this way, the key target molecules would be elucidated, potentially providing support for one of the models we describe. A similar strategy could be applied to other species, such as in anthropoid primates, which differ from Muridae in characteristics such as not showing systemic P4 withdrawal, having typically singleton pregnancies and longer gestational periods, but also where functional analyses are more challenging.

The ‘animal of choice’ evolutionary approach combined with recent evidence from human genome-wide association studies may reveal shared pathways, gene networks, transcription factors, and regulatory elements controlling human pregnancy and parturition. The initial gestation length loci identified by GWAS in the human maternal genome suggest critical roles of the decidua, the maternal interface with the developing placenta and fetus, and estrogen signaling in decidual cells (Zhang et al., 2017). For example, a noncoding variant in the WNT4 gene region shown to be involved in the regulation of gestational duration in mothers has been identified to mechanistically contribute to birth timing by establishing a new high affinity estrogen receptor binding site (Zhang et al., 2017). Is the decidua gauging a developmentally regulated fetal signal or is it the maternal mechanism of the clock that is activated possibly as early as implantation? The answers to these questions are not known and provide an interesting foundation to test hypotheses with emerging data. Exciting new data on the role of the vaginal microbiome (Callahan et al., 2017) and the ontogeny of pregnancy immune system modulation (Aghaeepour et al., 2017) provide further high-dimensional data sets, and together with emerging metabolic studies provide unprecedented opportunity for testing novel hypotheses. For example, does the maternal or fetal genome, in the context of maternal microbiome, modulate maternal metabolism in a consistent fashion? Does this then shape birth timing and risk for preterm birth? Additionally, new informatic methods that integrate findings across multi-omics platforms have found enhanced predictive power in relation to individual omics platforms and also revealed novel interactions (Ghaemi et al., 2019).

The determinant of birth timing is a critical and exciting big question that awaits elucidation. Situated at the intersection of biology, environment, and social context, including race and racism, preterm birth poses challenges that we must address. Are there other general models and frameworks for solving the enigma of birth timing? For example, an alternative framework and set of models would focus on the source of parturition initiation: maternal, fetal, interactive maternal-fetal, environmental, etc. The community of biomedical scientists interested in this area of investigation are encouraged to comment on this article with their ideas, constructively challenge one another, and us, and work to solve the problem. Further, one intent of this dialogue is to bring new voices and ideas into the discussion. We hope to stimulate the vision and curiosity of diverse investigators to gain new insights and answer this important question.

1. 1. Aghaeepour N
   2. Ganio EA
   3. Mcilwain D
   4. Tsai AS
   5. Tingle M
   6. Van Gassen S
   7. Gaudilliere DK
   8. Baca Q
   9. McNeil L
   10. Okada R
   11. Ghaemi MS
   12. Furman D
   13. Wong RJ
   14. Winn VD
   15. Druzin ML
   16. El-Sayed YY
   17. Quaintance C
   18. Gibbs R
   19. Darmstadt GL
   20. Shaw GM
   21. Stevenson DK
   22. Tibshirani R
   23. Nolan GP
   24. Lewis DB
   25. Angst MS
   26. Gaudilliere B

   (2017) An immune clock of human pregnancy

   Science Immunology 2:eaan2946.

   https://doi.org/10.1126/sciimmunol.aan2946

   • Google Scholar
2. 1. Allen WM

   (1930) Physiology of the corpus luteum VI. the production of progestational proliferation of the endometrium of the mature rabbit by progestin (an extract of the corpus luteum) after preliminary treatment with oestrin

   American Journal of Physiology 92:612–681.

   https://doi.org/10.1152/ajplegacy.1930.92.3.612

   • Google Scholar
3. 1. Allen WM
   2. Butenandt A
   3. Corner GW
   4. Slotta KH

   (1935) Nomenclature of corpus luteum hormone

   Science 82:153.

   https://doi.org/10.1126/science.82.2120.153-a

   • PubMed
   • Google Scholar
4. 1. Allen WM
   2. Reynolds SR

   (1935) Crystalline progestin and inhibition of uterine motility in vivo

   Science 82:155.

   https://doi.org/10.1126/science.82.2120.155

   • PubMed
   • Google Scholar
5. 1. Allen WM
   2. Wintersteiner O

   (1934) Crystalline progestin

   Science 80:190–191.

   https://doi.org/10.1126/science.80.2069.190-a

   • PubMed
   • Google Scholar
6. 1. Amini P
   2. Michniuk D
   3. Kuo K
   4. Yi L
   5. Skomorovska-Prokvolit Y
   6. Peters GA
   7. Tan H
   8. Wang J
   9. Malemud CJ
   10. Mesiano S

   (2016) Human parturition involves phosphorylation of progesterone Receptor-A at Serine-345 in myometrial cells

   Endocrinology 157:4434–4445.

   https://doi.org/10.1210/en.2016-1654

   • PubMed
   • Google Scholar
7. 1. Ananth CV
   2. Goldenberg RL
   3. Friedman AM
   4. Vintzileos AM

   (2018) Association of temporal changes in gestational age with perinatal mortality in the united states, 2007-2015

   JAMA Pediatrics 172:627–634.

   https://doi.org/10.1001/jamapediatrics.2018.0249

   • PubMed
   • Google Scholar
8. 1. Asher GW

   (2007) Gestation length in red deer: genetically determined or environmentally controlled?

   Reproduction in Domestic Ruminants 6:255–260.

   https://doi.org/10.5661/RDR-VI-255

   • Google Scholar
9. 1. Badyaev AV
   2. Uller T

   (2009) Parental effects in ecology and evolution: mechanisms, processes and implications

   Philosophical Transactions of the Royal Society B: Biological Sciences 364:1169–1177.

   https://doi.org/10.1098/rstb.2008.0302

   • Google Scholar
10. 1. Bainbridge DR

    (2014) The evolution of pregnancy

    Early Human Development 90:741–745.

    https://doi.org/10.1016/j.earlhumdev.2014.08.013

    • PubMed
    • Google Scholar
11. 1. Baird DD

    (2009) The gestational timing of pregnancy loss: adaptive strategy?

    American Journal of Human Biology 21:725–727.

    https://doi.org/10.1002/ajhb.20935

    • PubMed
    • Google Scholar
12. 1. Blackburn DG

    (2015) Evolution of vertebrate viviparity and specializations for fetal nutrition: a quantitative and qualitative analysis

    Journal of Morphology 276:961–990.

    https://doi.org/10.1002/jmor.20272

    • PubMed
    • Google Scholar
13. 1. Brubaker D
    2. Barbaro A
    3. R Chance M
    4. Mesiano S

    (2016) A dynamical systems model of progesterone receptor interactions with inflammation in human parturition

    BMC Systems Biology 10:79.

    https://doi.org/10.1186/s12918-016-0320-1

    • PubMed
    • Google Scholar
14. 1. Callahan BJ
    2. DiGiulio DB
    3. Goltsman DSA
    4. Sun CL
    5. Costello EK
    6. Jeganathan P
    7. Biggio JR
    8. Wong RJ
    9. Druzin ML
    10. Shaw GM
    11. Stevenson DK
    12. Holmes SP
    13. Relman DA

    (2017) Replication and refinement of a vaginal microbial signature of preterm birth in two racially distinct cohorts of US women

    PNAS 114:9966–9971.

    https://doi.org/10.1073/pnas.1705899114

    • PubMed
    • Google Scholar
15. 1. Challis JR

    (1980) Endocrinology of late pregnancy and parturition

    International Review of Physiology 22:277–324.

    https://doi.org/10.1016/S1569-2590(08)60071-3

    • PubMed
    • Google Scholar
16. 1. Challis JR
    2. Mitchell BF

    (1981)

    Hormonal control of preterm and term parturition

    Seminars in Perinatology 5:192–202.

    • PubMed
    • Google Scholar
17. 1. Chavan AR
    2. Bhullar B-AS
    3. Wagner GP

    (2016) What was the ancestral function of decidual stromal cells? A model for the evolution of eutherian pregnancy

    Placenta 40:40–51.

    https://doi.org/10.1016/j.placenta.2016.02.012

    • Google Scholar
18. 1. Cheal M

    (1983) Lifespan ontogeny of breeding and reproductive success in Mongolian gerbils

    Laboratory Animals 17:240–245.

    https://doi.org/10.1258/002367783781070713

    • Google Scholar
19. 1. Chen J
    2. Bacelis J
    3. Sole-Navais P
    4. Srivastava A
    5. Juodakis J
    6. Rouse A
    7. Hallman M
    8. Teramo K
    9. Melbye M
    10. Feenstra B
    11. Freathy RM
    12. Smith GD
    13. Lawlor DA
    14. Murray JC
    15. Williams SM
    16. Jacobsson B
    17. Muglia LJ
    18. Zhang G

    (2020) Dissecting maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes, and adult phenotypes: a mendelian-randomization and haplotype-based genetic score analysis in 10,734 mother-infant pairs

    PLOS Medicine 17:e1003305.

    https://doi.org/10.1371/journal.pmed.1003305

    • PubMed
    • Google Scholar
20. 1. Cheng S
    2. Fu Y
    3. Zhang Y
    4. Xian W
    5. Wang H
    6. Grothe B
    7. Liu X
    8. Xu X
    9. Klug A
    10. McCullagh EA

    (2019) Enhancement of de novo sequencing, assembly and annotation of the mongolian gerbil genome with transcriptome sequencing and assembly from several different tissues

    BMC Genomics 20:903.

    https://doi.org/10.1186/s12864-019-6276-y

    • PubMed
    • Google Scholar
21. 1. Chimpanzee Sequencing and Analysis Consortium

    (2005) Initial sequence of the chimpanzee genome and comparison with the human genome

    Nature 437:69–87.

    https://doi.org/10.1038/nature04072

    • PubMed
    • Google Scholar
22. 1. Collins JW
    2. David RJ

    (2009) Racial disparity in low birth weight and infant mortality

    Clinics in Perinatology 36:63–73.

    https://doi.org/10.1016/j.clp.2008.09.004

    • Google Scholar
23. Book

    1. Committee on Understanding Premature Birth and Assuring Healthy Outcomes Board on Health Sciences Policy

    (2007)

    Preterm Birth: Causes, Consequences, and Prevention

    Washington, D.C:  The National Academies Press.

    • Google Scholar
24. 1. Condon JC
    2. Jeyasuria P
    3. Faust JM
    4. Mendelson CR

    (2004) Surfactant protein secreted by the maturing mouse fetal lung acts as a hormone that signals the initiation of parturition

    PNAS 101:4978–4983.

    https://doi.org/10.1073/pnas.0401124101

    • PubMed
    • Google Scholar
25. Book

    1. Corner GW

    (1942)

    The Hormones in Human Reproduction

    London: Princton University Press.

    • Google Scholar
26. 1. Corner GW
    2. Allen WM

    (1929) Physiology of the corpus luteum; production of a special uterine reaction (progestational proliferation) by extracts of corpus luteum

    The American Journal of Physiology 88:826–839.

    https://doi.org/10.1152/ajplegacy.1929.88.2.326

    • Google Scholar
27. 1. Csapo A

    (1956) Progesterone ?block?

    American Journal of Anatomy 98:273–291.

    https://doi.org/10.1002/aja.1000980206

    • Google Scholar
28. 1. De Cure N
    2. Sullivan T
    3. Robertson M
    4. Hallam L
    5. Whale K

    (2013) Spontaneous expulsion of large submucosal uterine fibroid without embolisation - a case study

    Australasian Journal of Ultrasound in Medicine 16:37–40.

    https://doi.org/10.1002/j.2205-0140.2013.tb00096.x

    • Google Scholar
29. 1. Dunsworth HM
    2. Warrener AG
    3. Deacon T
    4. Ellison PT
    5. Pontzer H

    (2012) Metabolic hypothesis for human altriciality

    PNAS 109:15212–15216.

    https://doi.org/10.1073/pnas.1205282109

    • Google Scholar
30. 1. Early Growth Genetics (EGG) Consortium
    2. Beaumont RN
    3. Warrington NM
    4. Cavadino A
    5. Tyrrell J
    6. Nodzenski M
    7. Horikoshi M
    8. Geller F
    9. Myhre R
    10. Richmond RC
    11. Paternoster L
    12. Bradfield JP
    13. Kreiner-Møller E
    14. Huikari V
    15. Metrustry S
    16. Lunetta KL
    17. Painter JN
    18. Hottenga JJ
    19. Allard C
    20. Barton SJ
    21. Espinosa A
    22. Marsh JA
    23. Potter C
    24. Zhang G
    25. Ang W
    26. Berry DJ
    27. Bouchard L
    28. Das S
    29. Hakonarson H
    30. Heikkinen J
    31. Helgeland Ø
    32. Hocher B
    33. Hofman A
    34. Inskip HM
    35. Jones SE
    36. Kogevinas M
    37. Lind PA
    38. Marullo L
    39. Medland SE
    40. Murray A
    41. Murray JC
    42. Njølstad PR
    43. Nohr EA
    44. Reichetzeder C
    45. Ring SM
    46. Ruth KS
    47. Santa-Marina L
    48. Scholtens DM
    49. Sebert S
    50. Sengpiel V
    51. Tuke MA
    52. Vaudel M
    53. Weedon MN
    54. Willemsen G
    55. Wood AR
    56. Yaghootkar H
    57. Muglia LJ
    58. Bartels M
    59. Relton CL
    60. Pennell CE
    61. Chatzi L
    62. Estivill X
    63. Holloway JW
    64. Boomsma DI
    65. Montgomery GW
    66. Murabito JM
    67. Spector TD
    68. Power C
    69. Järvelin MR
    70. Bisgaard H
    71. Grant SFA
    72. Sørensen TIA
    73. Jaddoe VW
    74. Jacobsson B
    75. Melbye M
    76. McCarthy MI
    77. Hattersley AT
    78. Hayes MG
    79. Frayling TM
    80. Hivert MF
    81. Felix JF
    82. Hyppönen E
    83. Lowe WL
    84. Evans DM
    85. Lawlor DA
    86. Feenstra B
    87. Freathy RM

    (2018) Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics

    Human Molecular Genetics 27:742–756.

    https://doi.org/10.1093/hmg/ddx429

    • PubMed
    • Google Scholar
31. 1. Elovitz MA
    2. Mrinalini C

    (2004) Animal models of preterm birth

    Trends in Endocrinology & Metabolism 15:479–487.

    https://doi.org/10.1016/j.tem.2004.10.009

    • Google Scholar
32. 1. Fthenakis GC
    2. Arsenos G
    3. Brozos C
    4. Fragkou IA
    5. Giadinis ND
    6. Giannenas I
    7. Mavrogianni VS
    8. Papadopoulos E
    9. Valasi I

    (2012) Health management of ewes during pregnancy

    Animal Reproduction Science 130:198–212.

    https://doi.org/10.1016/j.anireprosci.2012.01.016

    • PubMed
    • Google Scholar
33. 1. Garfield RE
    2. Baulieu EE

    (1987) 10 The antiprogesterone steroid RU 486: a short pharmacological and clinical review, with emphasis on the interruption of pregnancy

    Baillière's Clinical Endocrinology and Metabolism 1:207–221.

    https://doi.org/10.1016/S0950-351X(87)80059-9

    • Google Scholar
34. 1. Ghaemi MS
    2. DiGiulio DB
    3. Contrepois K
    4. Callahan B
    5. Ngo TTM
    6. Lee-McMullen B
    7. Lehallier B
    8. Robaczewska A
    9. Mcilwain D
    10. Rosenberg-Hasson Y
    11. Wong RJ
    12. Quaintance C
    13. Culos A
    14. Stanley N
    15. Tanada A
    16. Tsai A
    17. Gaudilliere D
    18. Ganio E
    19. Han X
    20. Ando K
    21. McNeil L
    22. Tingle M
    23. Wise P
    24. Maric I
    25. Sirota M
    26. Wyss-Coray T
    27. Winn VD
    28. Druzin ML
    29. Gibbs R
    30. Darmstadt GL
    31. Lewis DB
    32. Partovi Nia V
    33. Agard B
    34. Tibshirani R
    35. Nolan G
    36. Snyder MP
    37. Relman DA
    38. Quake SR
    39. Shaw GM
    40. Stevenson DK
    41. Angst MS
    42. Gaudilliere B
    43. Aghaeepour N

    (2019) Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy

    Bioinformatics 35:95–103.

    https://doi.org/10.1093/bioinformatics/bty537

    • PubMed
    • Google Scholar
35. 1. Gibson G
    2. Lacek KA

    (2020) Canalization and robustness in human genetics and disease

    Annual Review of Genetics 54:189–211.

    https://doi.org/10.1146/annurev-genet-022020-022327

    • PubMed
    • Google Scholar
36. 1. Giger R
    2. Meier HP
    3. Küpfer U

    (1997)

    Length of gestation of freiberger mares with mule and horse foals

    Schweizer Archiv Fur Tierheilkunde 139:303–307.

    • PubMed
    • Google Scholar
37. 1. Goldenberg RL
    2. Hauth JC
    3. Andrews WW

    (2000) Intrauterine infection and preterm delivery

    New England Journal of Medicine 342:1500–1507.

    https://doi.org/10.1056/NEJM200005183422007

    • Google Scholar
38. 1. Goldenberg RL
    2. Culhane JF
    3. Iams JD
    4. Romero R

    (2008) Epidemiology and causes of preterm birth

    The Lancet 371:75–84.

    https://doi.org/10.1016/S0140-6736(08)60074-4

    • Google Scholar
39. 1. Griffith OW
    2. Chavan AR
    3. Protopapas S
    4. Maziarz J
    5. Romero R
    6. Wagner GP

    (2017) Embryo implantation evolved from an ancestral inflammatory attachment reaction

    PNAS 114:E6566–E6575.

    https://doi.org/10.1073/pnas.1701129114

    • Google Scholar
40. 1. Griffith OW
    2. Wagner GP

    (2017) The placenta as a model for understanding the origin and evolution of vertebrate organs

    Nature Ecology & Evolution 1:72.

    https://doi.org/10.1038/s41559-017-0072

    • PubMed
    • Google Scholar
41. 1. Gross GA
    2. Imamura T
    3. Luedke C
    4. Vogt SK
    5. Olson LM
    6. Nelson DM
    7. Sadovsky Y
    8. Muglia LJ

    (1998) Opposing actions of prostaglandins and oxytocin determine the onset of murine labor

    PNAS 95:11875–11879.

    https://doi.org/10.1073/pnas.95.20.11875

    • PubMed
    • Google Scholar
42. 1. Gross G
    2. Imamura T
    3. Muglia LJ

    (2000) Gene knockout mice in the study of parturition

    Journal of the Society for Gynecologic Investigation 7:88–95.

    https://doi.org/10.1016/S1071-5576(99)00075-1

    • Google Scholar
43. 1. Haig D

    (1993) Genetic conflicts in human pregnancy

    The Quarterly Review of Biology 68:495–532.

    https://doi.org/10.1086/418300

    • PubMed
    • Google Scholar
44. 1. Hallgrimsson B
    2. Green RM
    3. Katz DC
    4. Fish JL
    5. Bernier FP
    6. Roseman CC
    7. Young NM
    8. Cheverud JM
    9. Marcucio RS

    (2019) The developmental-genetics of canalization

    Seminars in Cell & Developmental Biology 88:67–79.

    https://doi.org/10.1016/j.semcdb.2018.05.019

    • Google Scholar
45. 1. Haughton CL
    2. Gawriluk TR
    3. Seifert AW

    (2016)

    The biology and husbandry of the african spiny mouse (Acomys cahirinus) and the research uses of a laboratory colony

    Journal of the American Association for Laboratory Animal Science : JAALAS 55:9–17.

    • PubMed
    • Google Scholar
46. 1. Hirsch E
    2. Saotome I
    3. Hirsch D

    (1995) A model of intrauterine infection and preterm delivery in mice

    American Journal of Obstetrics and Gynecology 172:1598–1603.

    https://doi.org/10.1016/0002-9378(95)90503-0

    • Google Scholar
47. 1. Hirsch E
    2. Muhle R

    (2002) Intrauterine bacterial inoculation induces labor in the mouse by mechanisms other than progesterone withdrawal

    Biology of Reproduction 67:1337–1341.

    https://doi.org/10.1095/biolreprod67.4.1337

    • PubMed
    • Google Scholar
48. Book

    1. Howson CP
    2. Merialdi M
    3. Lawn JE
    4. Requejo JH
    5. Say L

    (2009)

    March of Dimes White Paper on Preterm Birth: The Global and Regional Toll

    White Plains, NY: March of Dimes Foundation.

    • Google Scholar
49. Report

    1. Howson CP
    2. Kinney MV
    3. Lawn JE
    4. March of Dimes, PMNCH, Save the Children, Who

    (2012)

    Born Too Soon: The Global Action Report on Preterm Birth

    World health organization.

    • Google Scholar
50. 1. Jones SM

    (2017) Variations upon a theme: Australian lizards provide insights into the endocrine control of vertebrate reproductive cycles

    General and Comparative Endocrinology 244:60–69.

    https://doi.org/10.1016/j.ygcen.2015.09.004

    • Google Scholar
51. 1. Keelan JA
    2. Blumenstein M
    3. Helliwell RJ
    4. Sato TA
    5. Marvin KW
    6. Mitchell MD

    (2003) Cytokines, prostaglandins and parturition--a review

    Placenta 24 Suppl A:S33–S46.

    https://doi.org/10.1053/plac.2002.0948

    • PubMed
    • Google Scholar
52. 1. Kin K
    2. Nnamani MC
    3. Lynch VJ
    4. Michaelides E
    5. Wagner GP

    (2015) Cell-type phylogenetics and the origin of endometrial stromal cells

    Cell Reports 10:1398–1409.

    https://doi.org/10.1016/j.celrep.2015.01.062

    • PubMed
    • Google Scholar
53. 1. Kin K
    2. Maziarz J
    3. Chavan AR
    4. Kamat M
    5. Vasudevan S
    6. Birt A
    7. Emera D
    8. Lynch VJ
    9. Ott TL
    10. Pavlicev M
    11. Wagner GP

    (2016) The transcriptomic evolution of mammalian pregnancy: gene expression innovations in endometrial stromal fibroblasts

    Genome Biology and Evolution 8:2459–2473.

    https://doi.org/10.1093/gbe/evw168

    • PubMed
    • Google Scholar
54. 1. Kistka ZA-F
    2. Palomar L
    3. Lee KA
    4. Boslaugh SE
    5. Wangler MF
    6. Cole FS
    7. DeBaun MR
    8. Muglia LJ

    (2007a) Racial disparity in the frequency of recurrence of preterm birth

    American Journal of Obstetrics and Gynecology 196:131.e1.

    https://doi.org/10.1016/j.ajog.2006.06.093

    • Google Scholar
55. 1. Kistka ZA-F
    2. Palomar L
    3. Boslaugh SE
    4. DeBaun MR
    5. DeFranco EA
    6. Muglia LJ

    (2007b) Risk for postterm delivery after previous postterm delivery

    American Journal of Obstetrics and Gynecology 196:241.e1.

    https://doi.org/10.1016/j.ajog.2006.10.873

    • Google Scholar
56. 1. Kistka ZA-F
    2. DeFranco EA
    3. Ligthart L
    4. Willemsen G
    5. Plunkett J
    6. Muglia LJ
    7. Boomsma DI

    (2008) Heritability of parturition timing: an extended twin design analysis

    American Journal of Obstetrics and Gynecology 199:43.e1.

    https://doi.org/10.1016/j.ajog.2007.12.014

    • Google Scholar
57. 1. Kortekaas JC
    2. Kazemier BM
    3. Ravelli ACJ
    4. de Boer K
    5. van Dillen J
    6. Mol B
    7. de Miranda E

    (2015) Recurrence rate and outcome of postterm pregnancy, a national cohort study

    European Journal of Obstetrics & Gynecology and Reproductive Biology 193:70–74.

    https://doi.org/10.1016/j.ejogrb.2015.05.021

    • Google Scholar
58. 1. Krogh A

    (1929) The progress of physiology

    Science 70:200–204.

    https://doi.org/10.1126/science.70.1809.200

    • PubMed
    • Google Scholar
59. 1. Kumar S
    2. Stecher G
    3. Suleski M
    4. Hedges SB

    (2017) TimeTree: a resource for timelines, timetrees, and divergence times

    Molecular Biology and Evolution 34:1812–1819.

    https://doi.org/10.1093/molbev/msx116

    • PubMed
    • Google Scholar
60. 1. LaBella AL
    2. Abraham A
    3. Pichkar Y
    4. Fong SL
    5. Zhang G
    6. Muglia LJ
    7. Abbot P
    8. Rokas A
    9. Capra JA

    (2020) Accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci

    Nature Communications 11:3731.

    https://doi.org/10.1038/s41467-020-17258-6

    • PubMed
    • Google Scholar
61. 1. Liggins GC

    (1974) Parturition in the sheep and the human

    Basic Life Sciences 4:423–443.

    https://doi.org/10.1007/978-1-4684-2892-6_28

    • PubMed
    • Google Scholar
62. Book

    1. Liggins G
    2. Fairclough R
    3. Frieves S
    4. Forster C
    5. Knox B

    (1977) Parturition in the Sheep

    Amsterdam: Elsevier.

    https://doi.org/10.1002/9780470720295.ch2

    • Google Scholar
63. 1. Linder N
    2. Hiersch L
    3. Fridman E
    4. Klinger G
    5. Lubin D
    6. Kouadio F
    7. Melamed N

    (2017) Post-term pregnancy is an independent risk factor for neonatal morbidity even in low-risk Singleton pregnancies

    Archives of Disease in Childhood - Fetal and Neonatal Edition 102:F286–F290.

    https://doi.org/10.1136/archdischild-2015-308553

    • PubMed
    • Google Scholar
64. 1. Liu L
    2. Oza S
    3. Hogan D
    4. Perin J
    5. Rudan I
    6. Lawn JE
    7. Cousens S
    8. Mathers C
    9. Black RE

    (2015) Global, regional, and national causes of child mortality in 2000–13, with projections to inform post-2015 priorities: an updated systematic analysis

    The Lancet 385:430–440.

    https://doi.org/10.1016/S0140-6736(14)61698-6

    • Google Scholar
65. 1. Liu X
    2. Helenius D
    3. Skotte L
    4. Beaumont RN
    5. Wielscher M
    6. Geller F
    7. Juodakis J
    8. Mahajan A
    9. Bradfield JP
    10. Lin FTJ
    11. Vogelezang S
    12. Bustamante M
    13. Ahluwalia TS
    14. Pitkänen N
    15. Wang CA
    16. Bacelis J
    17. Borges MC
    18. Zhang G
    19. Bedell BA
    20. Rossi RM
    21. Skogstrand K
    22. Peng S
    23. Thompson WK
    24. Appadurai V
    25. Lawlor DA
    26. Kalliala I
    27. Power C
    28. McCarthy MI
    29. Boyd HA
    30. Marazita ML
    31. Hakonarson H
    32. Hayes MG
    33. Scholtens DM
    34. Rivadeneira F
    35. Jaddoe VWV
    36. Vinding RK
    37. Bisgaard H
    38. Knight BA
    39. Pahkala K
    40. Raitakari O
    41. Helgeland Ø
    42. Johansson S
    43. Njølstad PR
    44. Fadista J
    45. Schork AJ
    46. Nudel R
    47. Miller DE
    48. Chen X
    49. Weirauch MT
    50. Mortensen PB
    51. Børglum AD
    52. Nordentoft M
    53. Mors O
    54. Hao K
    55. Ryckman KK
    56. Hougaard DM
    57. Kottyan LC
    58. Pennell CE
    59. Lyytikainen LP
    60. Bønnelykke K
    61. Vrijheid M
    62. Felix JF
    63. Lowe WL
    64. Grant SFA
    65. Hyppönen E
    66. Jacobsson B
    67. Jarvelin MR
    68. Muglia LJ
    69. Murray JC
    70. Freathy RM
    71. Werge TM
    72. Melbye M
    73. Buil A
    74. Feenstra B

    (2019) Variants in the fetal genome near pro-inflammatory cytokine genes on 2q13 associate with gestational duration

    Nature Communications 10:3927.

    https://doi.org/10.1038/s41467-019-11881-8

    • PubMed
    • Google Scholar
66. 1. Lynch VJ
    2. Roth JJ
    3. Takahashi K
    4. Dunn CW
    5. Nonaka DF
    6. Stopper GF
    7. Wagner GP

    (2004) Adaptive evolution of HoxA–11 and HoxA–13 at the origin of the uterus in mammals

    Proceedings of the Royal Society of London. Series B: Biological Sciences 271:2201–2207.

    https://doi.org/10.1098/rspb.2004.2848

    • Google Scholar
67. 1. Lynch VJ
    2. Leclerc RD
    3. May G
    4. Wagner GP

    (2011) Transposon-mediated rewiring of gene regulatory networks contributed to the evolution of pregnancy in mammals

    Nature Genetics 43:1154–1159.

    https://doi.org/10.1038/ng.917

    • Google Scholar
68. 1. Mantalenakis SJ
    2. Ketchel MM

    (1966) Influence of pregnant parabiotic partners on time of parturition in rats

    Reproduction 11:313–316.

    https://doi.org/10.1530/jrf.0.0110313

    • Google Scholar
69. 1. Mendelson CR

    (2009) Minireview: fetal-maternal hormonal signaling in pregnancy and labor

    Molecular Endocrinology 23:947–954.

    https://doi.org/10.1210/me.2009-0016

    • PubMed
    • Google Scholar
70. 1. Menon R
    2. Bonney EA
    3. Condon J
    4. Mesiano S
    5. Taylor RN

    (2016) Novel concepts on pregnancy clocks and alarms: redundancy and synergy in human parturition

    Human Reproduction Update 22:535–560.

    https://doi.org/10.1093/humupd/dmw022

    • Google Scholar
71. Book

    1. Mesiano S
    2. DeFranco E
    3. Muglia LJ

    (2014) Parturition

    In: Plant T. M, Zeleznik A. J, editors. Knobil and Neill’s Physiology of Reproduction. Academic Press. pp. 1–2684.

    https://doi.org/10.1016/C2011-1-07288-0

    • Google Scholar
72. 1. Miska EA
    2. Ferguson-Smith AC

    (2016) Transgenerational inheritance: Models and mechanisms of non-DNA sequence-based inheritance

    Science 354:59–63.

    https://doi.org/10.1126/science.aaf4945

    • Google Scholar
73. 1. Mitchell BF
    2. Taggart MJ

    (2009) Are animal models relevant to key aspects of human parturition?

    American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 297:R525–R545.

    https://doi.org/10.1152/ajpregu.00153.2009

    • Google Scholar
74. 1. Mitteroecker P
    2. Huttegger SM
    3. Fischer B
    4. Pavlicev M

    (2016) Cliff-edge model of obstetric selection in humans

    PNAS 113:14680–14685.

    https://doi.org/10.1073/pnas.1612410113

    • PubMed
    • Google Scholar
75. 1. Mitteroecker P
    2. Windhager S
    3. Pavlicev M

    (2017) Cliff-edge model predicts intergenerational predisposition to dystocia and caesarean delivery

    PNAS 114:11669–11672.

    https://doi.org/10.1073/pnas.1712203114

    • PubMed
    • Google Scholar
76. 1. Morken N-H
    2. Melve KK
    3. Skjaerven R

    (2011) Recurrence of prolonged and post-term gestational age across generations: maternal and paternal contribution

    BJOG: An International Journal of Obstetrics & Gynaecology 118:1630–1635.

    https://doi.org/10.1111/j.1471-0528.2011.03154.x

    • Google Scholar
77. 1. Muglia LJ
    2. Katz M

    (2010) The enigma of spontaneous preterm birth

    New England Journal of Medicine 362:529–535.

    https://doi.org/10.1056/NEJMra0904308

    • Google Scholar
78. 1. Murray SA
    2. Morgan JL
    3. Kane C
    4. Sharma Y
    5. Heffner CS
    6. Lake J
    7. Donahue LR

    (2010) Mouse gestation length is genetically determined

    PLOS ONE 5:e12418.

    https://doi.org/10.1371/journal.pone.0012418

    • PubMed
    • Google Scholar
79. 1. Murrell NL

    (1996)

    Stress, self-esteem, and racism: relationships with low birth weight andpreterm delivery in African American women

    Journal of National Black Nurses' Association: JNBNA 8:45–53.

    • Google Scholar
80. 1. Nadeem L
    2. Shynlova O
    3. Matysiak-Zablocki E
    4. Mesiano S
    5. Dong X
    6. Lye S

    (2016) Molecular evidence of functional progesterone withdrawal in human myometrium

    Nature Communications 7:11565.

    https://doi.org/10.1038/ncomms11565

    • PubMed
    • Google Scholar
81. 1. Nielsen BW
    2. Bonney EA
    3. Pearce BD
    4. Donahue LR
    5. Sarkar IN
    6. Preterm Birth International Collaborative (PREBIC)

    (2016) A Cross-Species analysis of animal models for the investigation of preterm birth mechanisms

    Reproductive Sciences 23:482–491.

    https://doi.org/10.1177/1933719115604729

    • PubMed
    • Google Scholar
82. 1. Nnamani MC
    2. Plaza S
    3. Romero R
    4. Wagner GP

    (2013) Evidence for independent evolution of functional progesterone withdrawal in primates and guinea pigs

    Evolution, Medicine, and Public Health 2013:273–288.

    https://doi.org/10.1093/emph/eot022

    • Google Scholar
83. 1. Oliver EA
    2. Klebanoff M
    3. Yossef-Salameh L
    4. Oza-Frank R
    5. Moosavinasab S
    6. Reagan P
    7. Muglia L
    8. Buhimschi CS
    9. Buhimschi IA

    (2018) Preterm birth and gestational length in four Race-Nativity groups, including somali americans

    Obstetrics & Gynecology 131:281–289.

    https://doi.org/10.1097/AOG.0000000000002427

    • PubMed
    • Google Scholar
84. 1. Pavličev M
    2. Romero R
    3. Mitteroecker P

    (2020) Evolution of the human pelvis and obstructed labor: new explanations of an old obstetrical dilemma

    American Journal of Obstetrics and Gynecology 222:3–16.

    https://doi.org/10.1016/j.ajog.2019.06.043

    • Google Scholar
85. 1. Pepe GJ
    2. Rothchild I

    (1974) A comparative study of serum progesterone levels in pregnancy and in various types of pseudopregnancy in the rat

    Endocrinology 95:275–279.

    https://doi.org/10.1210/endo-95-1-275

    • PubMed
    • Google Scholar
86. 1. Phillips JB
    2. Abbot P
    3. Rokas A

    (2015) Is preterm birth a human-specific syndrome?

    Evolution, Medicine, and Public Health 2015:136–148.

    https://doi.org/10.1093/emph/eov010

    • Google Scholar
87. Book

    1. Plant TM
    2. Zeleznk AJ

    (2015)

    Knobil and Neill’s Physiology of Reproduction

    Amsterdam: Academic Press.

    • Google Scholar
88. 1. Plunkett J
    2. Feitosa MF
    3. Trusgnich M
    4. Wangler MF
    5. Palomar L
    6. Kistka ZA
    7. DeFranco EA
    8. Shen TT
    9. Stormo AE
    10. Puttonen H
    11. Hallman M
    12. Haataja R
    13. Luukkonen A
    14. Fellman V
    15. Peltonen L
    16. Palotie A
    17. Daw EW
    18. An P
    19. Teramo K
    20. Borecki I
    21. Muglia LJ

    (2009) Mother's genome or maternally-inherited genes acting in the fetus influence gestational age in familial preterm birth

    Human Heredity 68:209–219.

    https://doi.org/10.1159/000224641

    • PubMed
    • Google Scholar
89. 1. Plunkett J
    2. Doniger S
    3. Orabona G
    4. Morgan T
    5. Haataja R
    6. Hallman M
    7. Puttonen H
    8. Menon R
    9. Kuczynski E
    10. Norwitz E
    11. Snegovskikh V
    12. Palotie A
    13. Peltonen L
    14. Fellman V
    15. DeFranco EA
    16. Chaudhari BP
    17. McGregor TL
    18. McElroy JJ
    19. Oetjens MT
    20. Teramo K
    21. Borecki I
    22. Fay J
    23. Muglia L

    (2011) An evolutionary genomic approach to identify genes involved in human birth timing

    PLOS Genetics 7:e1001365.

    https://doi.org/10.1371/journal.pgen.1001365

    • PubMed
    • Google Scholar
90. 1. Porter DG

    (1972) Myometrium of the pregnant guinea pig: the probable importance of relaxin

    Biology of Reproduction 7:458–464.

    https://doi.org/10.1093/biolreprod/7.3.458

    • PubMed
    • Google Scholar
91. 1. Ratajczak CK
    2. Fay JC
    3. Muglia LJ

    (2010) Preventing preterm birth: the past limitations and new potential of animal models

    Disease Models & Mechanisms 3:407–414.

    https://doi.org/10.1242/dmm.001701

    • PubMed
    • Google Scholar
92. 1. Ratajczak CK
    2. Muglia LJ

    (2008) Insights into parturition biology from genetically altered mice

    Pediatric Research 64:581–589.

    https://doi.org/10.1203/PDR.0b013e31818718d2

    • PubMed
    • Google Scholar
93. 1. Romero R
    2. Espinoza J
    3. Gonçalves LF
    4. Kusanovic JP
    5. Friel LA
    6. Nien JK

    (2006) Inflammation in preterm and term labour and delivery

    Seminars in Fetal and Neonatal Medicine 11:317–326.

    https://doi.org/10.1016/j.siny.2006.05.001

    • Google Scholar
94. 1. Roseboom TJ
    2. Painter RC
    3. van Abeelen AFM
    4. Veenendaal MVE
    5. de Rooij SR

    (2011) Hungry in the womb: What are the consequences? Lessons from the Dutch famine

    Maturitas 70:141–145.

    https://doi.org/10.1016/j.maturitas.2011.06.017

    • Google Scholar
95. 1. Rosenberg KR
    2. Trevathan WR

    (2001) The evolution of human birth

    Scientific American 285:72–77.

    https://doi.org/10.1038/scientificamerican1101-72

    • PubMed
    • Google Scholar
96. 1. Rosenberg K
    2. Trevathan W

    (2002) Birth, obstetrics and human evolution

    BJOG: An International Journal of Obstetrics and Gynaecology 109:1199–1206.

    https://doi.org/10.1046/j.1471-0528.2002.00010.x

    • PubMed
    • Google Scholar
97. 1. Rothchild I

    (2003) The yolkless egg and the evolution of eutherian viviparity

    Biology of Reproduction 68:337–357.

    https://doi.org/10.1095/biolreprod.102.004531

    • PubMed
    • Google Scholar
98. 1. Sagoo B
    2. Ng KY
    3. Ghaleb G
    4. Brown H

    (2015) Spontaneous expulsion of intramural fibroid six weeks after emergency caesarean section

    Case Reports in Obstetrics and Gynecology 2015:1–4.

    https://doi.org/10.1155/2015/640570

    • PubMed
    • Google Scholar
99. 1. Schierding W
    2. Antony J
    3. Karhunen V
    4. Vääräsmäki M
    5. Franks S
    6. Elliott P
    7. Kajantie E
    8. Sebert S
    9. Blakemore A
    10. Horsfield JA
    11. Järvelin MR
    12. O'Sullivan JM
    13. Cutfield WS

    (2018) GWAS on prolonged gestation (post-term birth): analysis of successive finnish birth cohorts

    Journal of Medical Genetics 55:55–63.

    https://doi.org/10.1136/jmedgenet-2017-104880

    • PubMed
    • Google Scholar
100. 1. Scott IC
     2. Asher GW
     3. Archer JA
     4. Littlejohn RP

     (2008) The effect of conception date on gestation length of red deer (Cervus elaphus)

     Animal Reproduction Science 109:206–217.

     https://doi.org/10.1016/j.anireprosci.2007.11.025

     • Google Scholar
101. 1. Seikku L
     2. Gissler M
     3. Andersson S
     4. Rahkonen P
     5. Stefanovic V
     6. Tikkanen M
     7. Paavonen J
     8. Rahkonen L

     (2016) Asphyxia, neurologic morbidity, and perinatal mortality in Early-Term and postterm birth

     Pediatrics 137:e20153334.

     https://doi.org/10.1542/peds.2015-3334

     • PubMed
     • Google Scholar
102. 1. Slaughter-Acey JC
     2. Sealy-Jefferson S
     3. Helmkamp L
     4. Caldwell CH
     5. Osypuk TL
     6. Platt RW
     7. Straughen JK
     8. Dailey-Okezie RK
     9. Abeysekara P
     10. Misra DP

     (2016) Racism in the form of micro aggressions and the risk of preterm birth among black women

     Annals of Epidemiology 26:7–13.

     https://doi.org/10.1016/j.annepidem.2015.10.005

     • PubMed
     • Google Scholar
103. 1. Smith R

     (2007) Parturition

     New England Journal of Medicine 356:271–283.

     https://doi.org/10.1056/NEJMra061360

     • PubMed
     • Google Scholar
104. 1. Sugimoto Y
     2. Yamasaki A
     3. Segi E
     4. Tsuboi K
     5. Aze Y
     6. Nishimura T
     7. Oida H
     8. Yoshida N
     9. Tanaka T
     10. Katsuyama M
     11. Hasumoto K
     12. Murata T
     13. Hirata M
     14. Ushikubi F
     15. Negishi M
     16. Ichikawa A
     17. Narumiya S

     (1997) Failure of parturition in mice lacking the prostaglandin F receptor

     Science 277:681–683.

     https://doi.org/10.1126/science.277.5326.681

     • PubMed
     • Google Scholar
105. 1. Sulila P
     2. Lundkvist U
     3. Mattsson R

     (1988) Effects of pseudopregnancy on immunoglobulin-secreting cells in mice

     Journal of Reproductive Immunology 13:175–182.

     https://doi.org/10.1016/0165-0378(88)90060-5

     • Google Scholar
106. 1. Swaggart KA
     2. Pavlicev M
     3. Muglia LJ

     (2015) Genomics of preterm birth

     Cold Spring Harbor Perspectives in Medicine 5:a023127.

     https://doi.org/10.1101/cshperspect.a023127

     • PubMed
     • Google Scholar
107. 1. Tam PP

     (1981)

     The control of somitogenesis in mouse embryos

     Journal of Embryology and Experimental Morphology 65 Suppl:103–128.

     • PubMed
     • Google Scholar
108. 1. Tuckey RC

     (2005) Progesterone synthesis by the human placenta

     Placenta 26:273–281.

     https://doi.org/10.1016/j.placenta.2004.06.012

     • Google Scholar
109. 1. Wagner GP
     2. Lynch VJ

     (2005) Molecular evolution of evolutionary novelties: the vagina and uterus of therian mammals

     Journal of Experimental Zoology Part B: Molecular and Developmental Evolution 304B:580–592.

     https://doi.org/10.1002/jez.b.21074

     • Google Scholar
110. 1. Wagner GP
     2. Lynch VJ

     (2010) Evolutionary novelties

     Current Biology 20:R48–R52.

     https://doi.org/10.1016/j.cub.2009.11.010

     • Google Scholar
111. 1. Waterston RH
     2. Lindblad-Toh K
     3. Birney E
     4. Rogers J
     5. Abril JF
     6. Agarwal P
     7. Agarwala R
     8. Ainscough R
     9. Alexandersson M
     10. An P
     11. Antonarakis SE
     12. Attwood J
     13. Baertsch R
     14. Bailey J
     15. Barlow K
     16. Beck S
     17. Berry E
     18. Birren B
     19. Bloom T
     20. Bork P
     21. Botcherby M
     22. Bray N
     23. Brent MR
     24. Brown DG
     25. Brown SD
     26. Bult C
     27. Burton J
     28. Butler J
     29. Campbell RD
     30. Carninci P
     31. Cawley S
     32. Chiaromonte F
     33. Chinwalla AT
     34. Church DM
     35. Clamp M
     36. Clee C
     37. Collins FS
     38. Cook LL
     39. Copley RR
     40. Coulson A
     41. Couronne O
     42. Cuff J
     43. Curwen V
     44. Cutts T
     45. Daly M
     46. David R
     47. Davies J
     48. Delehaunty KD
     49. Deri J
     50. Dermitzakis ET
     51. Dewey C
     52. Dickens NJ
     53. Diekhans M
     54. Dodge S
     55. Dubchak I
     56. Dunn DM
     57. Eddy SR
     58. Elnitski L
     59. Emes RD
     60. Eswara P
     61. Eyras E
     62. Felsenfeld A
     63. Fewell GA
     64. Flicek P
     65. Foley K
     66. Frankel WN
     67. Fulton LA
     68. Fulton RS
     69. Furey TS
     70. Gage D
     71. Gibbs RA
     72. Glusman G
     73. Gnerre S
     74. Goldman N
     75. Goodstadt L
     76. Grafham D
     77. Graves TA
     78. Green ED
     79. Gregory S
     80. Guigó R
     81. Guyer M
     82. Hardison RC
     83. Haussler D
     84. Hayashizaki Y
     85. Hillier LW
     86. Hinrichs A
     87. Hlavina W
     88. Holzer T
     89. Hsu F
     90. Hua A
     91. Hubbard T
     92. Hunt A
     93. Jackson I
     94. Jaffe DB
     95. Johnson LS
     96. Jones M
     97. Jones TA
     98. Joy A
     99. Kamal M
     100. Karlsson EK
     101. Karolchik D
     102. Kasprzyk A
     103. Kawai J
     104. Keibler E
     105. Kells C
     106. Kent WJ
     107. Kirby A
     108. Kolbe DL
     109. Korf I
     110. Kucherlapati RS
     111. Kulbokas EJ
     112. Kulp D
     113. Landers T
     114. Leger JP
     115. Leonard S
     116. Letunic I
     117. Levine R
     118. Li J
     119. Li M
     120. Lloyd C
     121. Lucas S
     122. Ma B
     123. Maglott DR
     124. Mardis ER
     125. Matthews L
     126. Mauceli E
     127. Mayer JH
     128. McCarthy M
     129. McCombie WR
     130. McLaren S
     131. McLay K
     132. McPherson JD
     133. Meldrim J
     134. Meredith B
     135. Mesirov JP
     136. Miller W
     137. Miner TL
     138. Mongin E
     139. Montgomery KT
     140. Morgan M
     141. Mott R
     142. Mullikin JC
     143. Muzny DM
     144. Nash WE
     145. Nelson JO
     146. Nhan MN
     147. Nicol R
     148. Ning Z
     149. Nusbaum C
     150. O'Connor MJ
     151. Okazaki Y
     152. Oliver K
     153. Overton-Larty E
     154. Pachter L
     155. Parra G
     156. Pepin KH
     157. Peterson J
     158. Pevzner P
     159. Plumb R
     160. Pohl CS
     161. Poliakov A
     162. Ponce TC
     163. Ponting CP
     164. Potter S
     165. Quail M
     166. Reymond A
     167. Roe BA
     168. Roskin KM
     169. Rubin EM
     170. Rust AG
     171. Santos R
     172. Sapojnikov V
     173. Schultz B
     174. Schultz J
     175. Schwartz MS
     176. Schwartz S
     177. Scott C
     178. Seaman S
     179. Searle S
     180. Sharpe T
     181. Sheridan A
     182. Shownkeen R
     183. Sims S
     184. Singer JB
     185. Slater G
     186. Smit A
     187. Smith DR
     188. Spencer B
     189. Stabenau A
     190. Stange-Thomann N
     191. Sugnet C
     192. Suyama M
     193. Tesler G
     194. Thompson J
     195. Torrents D
     196. Trevaskis E
     197. Tromp J
     198. Ucla C
     199. Ureta-Vidal A
     200. Vinson JP
     201. Von Niederhausern AC
     202. Wade CM
     203. Wall M
     204. Weber RJ
     205. Weiss RB
     206. Wendl MC
     207. West AP
     208. Wetterstrand K
     209. Wheeler R
     210. Whelan S
     211. Wierzbowski J
     212. Willey D
     213. Williams S
     214. Wilson RK
     215. Winter E
     216. Worley KC
     217. Wyman D
     218. Yang S
     219. Yang SP
     220. Zdobnov EM
     221. Zody MC
     222. Lander ES
     223. Mouse Genome Sequencing Consortium

     (2002) Initial sequencing and comparative analysis of the mouse genome

     Nature 420:520–562.

     https://doi.org/10.1038/nature01262

     • PubMed
     • Google Scholar
112. 1. Wildman DE
     2. Chen C
     3. Erez O
     4. Grossman LI
     5. Goodman M
     6. Romero R

     (2006) Evolution of the mammalian placenta revealed by phylogenetic analysis

     PNAS 103:3203–3208.

     https://doi.org/10.1073/pnas.0511344103

     • PubMed
     • Google Scholar
113. 1. Winchester SK
     2. Imamura T
     3. Gross GA
     4. Muglia LM
     5. Vogt SK
     6. Wright J
     7. Watanabe K
     8. Tai HH
     9. Muglia LJ

     (2002) Coordinate regulation of prostaglandin metabolism for induction of parturition in mice

     Endocrinology 143:2593–2598.

     https://doi.org/10.1210/endo.143.7.8926

     • PubMed
     • Google Scholar
114. 1. Wu SP
     2. DeMayo FJ

     (2017) Progesterone receptor signaling in uterine myometrial physiology and preterm birth

     Current Topics in Developmental Biology 125:171–190.

     https://doi.org/10.1016/bs.ctdb.2017.03.001

     • PubMed
     • Google Scholar
115. Book

     1. Young IR
     2. Renfree MB
     3. Mesiano S
     4. Shaw G
     5. Jenkin G
     6. Smith R

     (2010) The comparative physiology of parturition in mammals: Hormones and parturition in mammals

     In: Norris D, Lopez K, editors. Hormones and Reproduction in Vertebrates. London: Academic Press. pp. 95–116.

     https://doi.org/10.1016/B978-0-12-374928-4.10006-9

     • Google Scholar
116. 1. Zhang G
     2. Bacelis J
     3. Lengyel C
     4. Teramo K
     5. Hallman M
     6. Helgeland Ø
     7. Johansson S
     8. Myhre R
     9. Sengpiel V
     10. Njølstad PR
     11. Jacobsson B
     12. Muglia L

     (2015) Assessing the causal relationship of maternal height on birth size and gestational age at birth: a mendelian randomization analysis

     PLOS Medicine 12:e1001865.

     https://doi.org/10.1371/journal.pmed.1001865

     • PubMed
     • Google Scholar
117. 1. Zhang G
     2. Feenstra B
     3. Bacelis J
     4. Liu X
     5. Muglia LM
     6. Juodakis J
     7. Miller DE
     8. Litterman N
     9. Jiang P-P
     10. Russell L
     11. Hinds DA
     12. Hu Y
     13. Weirauch MT
     14. Chen X
     15. Chavan AR
     16. Wagner GP
     17. Pavličev M
     18. Nnamani MC
     19. Maziarz J
     20. Karjalainen MK
     21. Rämet M
     22. Sengpiel V
     23. Geller F
     24. Boyd HA
     25. Palotie A
     26. Momany A
     27. Bedell B
     28. Ryckman KK
     29. Huusko JM
     30. Forney CR
     31. Kottyan LC
     32. Hallman M
     33. Teramo K
     34. Nohr EA
     35. Davey Smith G
     36. Melbye M
     37. Jacobsson B
     38. Muglia LJ

     (2017) Genetic associations with gestational duration and spontaneous preterm birth

     New England Journal of Medicine 377:1156–1167.

     https://doi.org/10.1056/NEJMoa1612665

     • Google Scholar
118. 1. Zhang G
     2. Srivastava A
     3. Bacelis J
     4. Juodakis J
     5. Jacobsson B
     6. Muglia LJ

     (2018) Genetic studies of gestational duration and preterm birth

     Best Practice & Research Clinical Obstetrics & Gynaecology 52:33–47.

     https://doi.org/10.1016/j.bpobgyn.2018.05.003

     • Google Scholar
119. 1. Zhang X
     2. Pavlicev M
     3. Jones HN
     4. Muglia LJ

     (2020) Eutherian-Specific Gene TRIML2 Attenuates Inflammation in the Evolution of Placentation

     Molecular Biology and Evolution 37:507–523.

     https://doi.org/10.1093/molbev/msz238

     • Google Scholar

Author details

1. Antonis Rokas

   Department of Biological Sciences, Vanderbilt University, Nashville, United States

   For correspondence

   antonis.rokas@vanderbilt.edu

   Competing interests

   Reviewing editor, eLife

   "This ORCID iD identifies the author of this article:" 0000-0002-7248-6551

2. Sam Mesiano

   Department of Reproductive Biology, Case Western Reserve University and Department of Obstetrics and Gynecology, University Hospitals of Cleveland, Cleveland, United States

   Competing interests

   No competing interests declared

3. Ortal Tamam

   The Shraga Segal Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben Gurion University, Beer Sheva, Israel

   Competing interests

   No competing interests declared

4. Abigail LaBella

   Department of Biological Sciences, Vanderbilt University, Nashville, United States

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-0068-6703

5. Ge Zhang

   Division of Human Genetics, Cincinnati Children’s Hospital Medical Center and Department of Pediatrics. University of Cincinnati College of Medicine, Cincinnati, United States

   Competing interests

   No competing interests declared

6. Louis Muglia

   1. Division of Human Genetics, Cincinnati Children’s Hospital Medical Center and Department of Pediatrics. University of Cincinnati College of Medicine, Cincinnati, United States
   2. Burroughs Wellcome Fund, Research Triangle Park, Durham, United States

   For correspondence

   LMuglia@bwfund.org

   Competing interests

   is currently President and CEO of the Burroughs Wellcome Fund. The content of this article does not convey the opinion of the Burroughs Wellcome Fund.

   "This ORCID iD identifies the author of this article:" 0000-0002-0301-8770

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