Abstract
Maternal effects, encompassing both genetic (maternally expressed gene products) and non‐genetic (maternal state) influences, are powerful determinants of offspring phenotype, yet their RNA‐level mechanisms remain incompletely resolved. In parallel, epitranscriptomics, an emerging field centered on chemical modifications to RNA, has revealed new layers of gene regulation with implications for cell fate, plasticity, and response to environmental cues. In this perspective article, a conceptual link is proposed between maternal effects and epitranscriptomic mechanisms, focusing on how maternal environments may shape offspring phenotypes through RNA modifications. Evidence is examined from diverse systems, including maternal deposition of modified RNAs, environmental modulation of RNA‐modifying enzymes, and early developmental windows sensitive to maternal inputs. A clear distinction is drawn between placenta‐mediated pathways that reprogram trophoblast/placental epitranscriptomics and direct fetal‐tissue routes that act within developing organs. Although causal demonstrations are still emerging, convergent observations indicate that maternal environments can tune the offspring epitranscriptome with lasting phenotypic consequences. To articulate this emerging connection, the concept of “maternal RNA imprinting” is proposed, the idea that offspring development is shaped by maternal cues via targeted RNA modifications. This article aims not only to synthesize emerging insights across fields but also to stimulate interdisciplinary discussion and encourage investigation into the unexplored intersections of maternal biology and RNA regulation.
Keywords: developmental programming, epitranscriptomics, maternal effects, non‐genetic inheritance, RNA modifications
1. MATERNAL EFFECTS: BEYOND GENETIC INHERITANCE
Maternal effects have been increasingly recognized as important regulators of offspring phenotype, which can operate independently of the inherited DNA sequence. 1 , 2 Traditionally viewed through the lens of genetics, developmental outcomes were once largely attributed to allelic combinations passed from parents to progeny. 3 , 4 Classical forward genetic screens in Drosophila and, in zebrafish, four‐generation natural‐mating maternal‐effect screening strategies have identified numerous maternal‐effect mutations, including strict maternal‐effect alleles in which the mother's genotype alone determines embryonic phenotype via maternally deposited transcripts and proteins. 5 , 6 , 7 , 8 , 9 More recently, CRISPR/Cas9‐based approaches such as maternal crispants, primordial germ cell transplantation‐based germline editing, oocyte‐specific Cas9 transgenes, and F0 null‐mutation strategies now enable rapid generation and analysis of maternal and maternal‐zygotic mutants in zebrafish, substantially expanding the accessible repertoire of vertebrate maternal‐effect genes. 10 , 11 , 12 , 13 However, it has become evident that the maternal environment exerts a substantial influence on offspring development through a variety of non‐genetic mechanisms. 14 , 15 , 16 , 17 These maternal effects encompass physiological, biochemical, and behavioral cues, transmitted during oogenesis, gestation, or early postnatal life. 3 , 18 , 19
In animal systems, maternal effects have been well‐documented in contexts such as nutrition, stress exposure, metabolic state, and immune status. 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 These factors have been shown to influence offspring traits ranging from growth rate and metabolism to neurodevelopment and immune function. In many cases, such effects have persisted into adulthood and even across generations, suggesting involvement of mechanisms capable of inducing stable, long‐term changes in gene expression or cellular state. 18 , 27 , 28 , 29 , 30 , 31 , 32 Importantly, these influences are often mediated through the maternal provisioning of molecular substrates during early development, including hormones, metabolites, proteins, and RNAs. 33 , 34 , 35 , 36 , 37 , 38 In addition to the classical maternal‐effect genetics in Drosophila and zebrafish defining extensive sets of maternally required loci, 5 , 6 , 7 , 8 , 9 recent research has expanded the understanding of maternal effects to include the regulation of gene expression programs during embryogenesis. 35 , 39 , 40 , 41 , 42 , 43 Notably, maternal contributions have been implicated in modulating chromatin architecture and DNA methylation landscapes in the developing embryo. 44 , 45 , 46 , 47 , 48 These epigenetic alterations offer a mechanistic explanation for how transient environmental exposures in the mother can produce sustained phenotypic outcomes in the offspring. 44 , 49 , 50 , 51 However, while considerable attention has been given to DNA‐level epigenetic marks, a growing body of evidence now points to RNA as another critical layer of regulatory control.
Maternal RNAs, transcripts deposited into the oocyte during oogenesis, serve as essential regulators of early embryonic development, particularly in organisms where zygotic genome activation (ZGA) is delayed (e.g., zebrafish and Drosophila; ex ovo), with RNA modifications on maternal mRNAs (notably m6A and m5C) directing their clearance and translation. 52 , 53 , 54 , 55 , 56 , 57 , 58 These RNAs direct early cell divisions, patterning, and axis formation before the embryo begins transcribing its own genome. 59 , 60 , 61 The stability, translation, and function of these transcripts can be influenced by post‐transcriptional modifications, for example, m6A and m5C, which are now understood to be dynamic and responsive to environmental conditions, as shown in zebrafish, Drosophila, Xenopus, and mammalian oocytes/embryos. 52 , 55 , 57 , 58 , 62 , 63 , 64 As such, maternal effects may extend into the realm of post‐transcriptional regulation, potentially involving mechanisms such as RNA methylation or editing, with evidence from human preimplantation embryos (RNA editing) and from mouse oocytes/embryos (m6A), as well as cross‐species m5C maps of maternal mRNAs. 52 , 65 , 66 , 67 These findings raise the possibility that maternal effects may be exerted, in part, through modulation of the embryonic epitranscriptome. 68 , 69 , 70 Though this concept remains underexplored, it introduces a compelling hypothesis: that maternal effects and epitranscriptomic regulation may intersect to form a unified system of non‐genetic developmental programming. By considering maternal effects as more than mere nutrient or hormonal signals, and by integrating recent discoveries from RNA biology, this article sets the stage for examining how RNA modifications may act as a mechanistic bridge linking maternal cues to offspring phenotype. This emerging perspective opens new avenues for research and invites a reevaluation of how maternal environments shape development at the molecular level.
2. EPITRANSCRIPTOMICS: ADDING REGULATORY DIMENSION TO RNA BIOLOGY
Epitranscriptomics, the study of post‐transcriptional chemical modifications on RNA molecules, has added an important new layer of regulatory complexity to gene expression. Unlike canonical epigenetics, which primarily targets DNA and histone proteins, epitranscriptomic modifications act directly on RNA, influencing its splicing, stability, localization, translation, and degradation. 71 , 72 , 73 , 74 , 75 , 76 More than 170 types of RNA modifications have been identified, with N6‐methyladenosine (m6A) the most prevalent on eukaryotic mRNA, 77 , 78 first reported on mRNA in the 1970s. 79 , 80 The core machinery comprises the METTL3–METTL14 writer complex, 81 , 82 the demethylases FTO and ALKBH5, 83 , 84 and YTH‐domain “reader” proteins. 85 , 86
Epitranscriptomic control is now known to be tightly integrated with developmental processes, with maternal exposure routes differing across taxa; pre‐fertilization oocyte provisioning in ex ovo systems versus continuous in utero exposure (oviduct, uterus, and placenta) in mammals. For example, m6A modifications have been shown to guide cell fate transitions during early embryogenesis in mouse embryos/ESCs, neural differentiation in mammalian systems, and skeletogenesis in zebrafish/mouse models. 74 , 87 , 88 , 89 , 90 , 91 By selectively destabilizing certain transcripts while stabilizing others, RNA modifications serve as molecular timers that fine‐tune gene expression in a context‐ and stage‐specific manner. These regulatory features are especially relevant in systems undergoing rapid and tightly coordinated transcriptional changes, such as the early embryo. Importantly, the deposition and removal of RNA modifications are influenced by various cellular and environmental signals. 92 , 93 Stress conditions, nutrient availability, heat, hypoxia, and inflammatory cues have all been shown to alter the activity or expression of RNA‐modifying enzymes. 93 , 94 , 95 , 96 This raises the possibility that external factors, such as those originating from the maternal environment, could influence the transcriptomic output of developing tissues through epitranscriptomic means. 68 , 69 , 70 In this way, epitranscriptomics not only contributes to intrinsic gene regulatory logic but also offers a potential interface between environmental exposure and cellular response. Although the field is still in its early stages, advances in techniques such as MeRIP‐seq, miCLIP, single‐cell m6A profiling, direct RNA nanopore sequencing and live‐cell RNA biosensors can accelerate the identification of functional RNA modifications across developmental contexts. 97 , 98 , 99 Future applications of these tools in maternal‐fetal models may reveal novel regulatory pathways whereby maternal signals modulate the fetal transcriptome via direct chemical modification of RNA. 100 , 101 , 102 In this framework, epitranscriptomics emerges not just as a standalone regulatory system but as a candidate mediator of environmentally responsive, non‐genetic inheritance (Figure 1).
FIGURE 1.

A general overview of intersections between maternal effects and RNA modifications at the developmental level.
3. EARLY DEVELOPMENTAL WINDOWS AND MATERNAL REGULATION OF THE FETAL EPITRANSCRIPTOME
Early embryonic development is marked by a series of tightly regulated transitions, during which the embryo is highly sensitive to environmental cues, including those derived from the maternal organism. In ex ovo embryos these cues are primarily encoded in the oocyte/egg and perivitelline environment, whereas in mammals additional cues arise during oviductal transit, uterine residence, and placentation. 103 , 104 These windows of developmental plasticity offer unique opportunities for maternal signals to influence gene expression and cell fate decisions. 105 It is being proposed that such influence may extend to the epitranscriptomic layer, wherein RNA modifications could mediate adaptive responses to maternal inputs during critical periods of embryogenesis 68 , 90 , 102 , 106 (representative examples across taxa are summarized in Table 1).
TABLE 1.
Maternal cues, epitranscriptomic mechanisms, and outcomes across models.
| Maternal cue/context | Route | Model | Window and tissue | Modification/enzyme | Mechanistic effect/target process | Outcome/phenotype | References |
|---|---|---|---|---|---|---|---|
| Maternal deposition of modified RNAs (baseline control of MZT) | Ex ovo | Zebrafish | MZT; early embryo | m6A–YTHDF2 | Maternal mRNA clearance; timing of ZGA | Timely MZT; normal early development | 58 |
| Maternal deposition of modified RNAs (granule‐mediated decay) | Ex ovo | Fruit fly | Early embryo | m6A → FMR1 granule phase switch | Maternal RNA decay via RNP phase transition | Proper early developmental progression | 57 |
| Maternal deposition of modified RNAs (cytosine methylation) | Ex ovo | Fruit fly | Early embryo | m5C (NSUN2/NSUN6) | Cell‐cycle control and MZT timing via maternal mRNA m5C | Proper cleavage timing/MZT | 52, 102 |
| Oocyte maturation and early embryo control | Ex ovo | Xenopus | Oocyte maturation; early embryo | m6A | Translational control of maternal mRNAs | Competent oocyte maturation/early development | 107 |
| Maternal METTL3 requirement for oocyte/embryo | Direct fetal tissue | Mouse | Oocyte maturation; preimplantation | m6A (METTL3) | Writer activity needed for oocyte maturation and MZT | Defects in maturation/MZT when impaired | 108 |
| Maternal mettl3 function in gamete maturation | Ex ovo | Zebrafish | Gametogenesis | m6A (Mettl3) | Writer activity supports gamete maturation/fertility | Reduced fertility when mutated | 109 |
| Progesterone signaling at implantation | Placenta‐mediated (uterine/implantation axis) | Mouse/Human | Peri‐implantation; endometrium/trophoblast | m6A (METTL3; readers) | m6A‐mediated translation of PR and implantation factors | Implantation failure when METTL3 is deficient | 110 |
| Trophoblast invasion defects in preeclampsia | Placenta | Human | First trimester placenta; trophoblast | m6A (WTAP–HMGN3 axis) | m6A program limits invasion | Early‐onset preeclampsia association | 111 |
| Placental programs affecting FGR | Placenta | Human | Placenta; trophoblast | m6A (METTL3; IGF2BP2 → FOSL1) | m6A –reader stabilization of FOSL1 | Reduced invasion; fetal growth restriction | 112 |
| Maternal obesity | Placenta | Human | Term placenta | Global m6A decrease (writers/erasers) | Altered placental RNA methylation landscape | Adverse fetal growth association | 113 |
| Preeclampsia case–control methylome | Placenta | Human | Placenta | m6A mapping differences | Pathway changes in diseased placenta | Disease‐linked m6A signatures | 114, 115, 116 |
| Maternal microbiome | Direct fetal tissue | Mouse | Fetal brain and intestine | m6A patterns | Maternal microbial metabolites modulate fetal m6A | Region‐specific fetal m6A changes | 117 |
| Maternal low‐protein diet | Direct fetal tissue | Rat | Fetal hypothalamus | m6A pathway genes | Altered metabolic gene regulation | Programming of metabolic pathways | 68 |
| Maternal high‐fat diet | Direct fetal tissue | Mouse | Offspring adipose and skeletal muscle (postnatal) | m6A dynamics | Modification changes in metabolic tissues | Long‐term metabolic effects | 118 |
| Gestational diabetes model | Direct fetal tissue | Mouse | Offspring liver | m6A (RBM15 → CLDN4) | m6A‐mediated regulation of tight junction gene | Reduced hepatic insulin sensitivity in offspring | 119 |
| Maternal heat stress | Direct fetal tissue | Pig | Neonatal adipose | m6A changes | m6A‐linked modulation of fat deposition | Altered early fat deposition | 120 |
| High temperature during early embryogenesis | Direct fetal tissue | Pig | Early embryo | m6A; FTO dynamics | Temperature‐driven m6A changes | Reduced embryonic competence | 121 |
| Gestational arsenic exposure | Placenta → fetal | Mouse | Placenta → fetus | m6A (Cyr61) | Placental m6A on implantation/growth regulator | Placental and fetal developmental effects | 122 |
| Maternal EV‐mediated signaling | Placenta‐mediated/direct delivery | Bovine/human (in vitro) | Endometrium ↔ blastocyst; early embryo | EV cargo (RNAs, RBPs) | Transfer of RNA/RBP to conceptus | Modulation of implantation/early development | 123, 124, 125 |
| Transgenerational effect of maternal hypertension | Mixed (placenta + fetal) | Rodent | Development → adult offspring | m6A changes | Altered vascular injury response via m6A | Aggravated vascular dysfunction in adult males | 126 |
In externally developing species, maternal effects are primarily encoded via oocyte provisioning of RNAs and their epitranscriptomic marks (m6A/m5C) and by egg‐associated environments; mechanistic studies demonstrate m6A–YTHDF2‐dependent maternal mRNA clearance in zebrafish and m6A‐instructed FMR1 granule phase switching in Drosophila. 57 , 58 Functional redundancy among zebrafish YTHDF readers also buffers aspects of maternal m6A control. 127 In mammals, additional maternal inputs occur after fertilization via oviductal and uterine secretions and the placenta, extending opportunities to modulate RNA‐modifying enzymes and fetal epitranscriptomic states. Several lines of evidence support the idea that maternal environments can shape the molecular landscape of the early embryo in a lasting manner. 128 , 129 , 130 , 131 Maternal diet, metabolic state, microbiome, and environmental stressors and chemicals modulate the expression and activity of genes and enzymes involved in RNA metabolism and modification. In mammals, two complementary routes are distinguished: (i) a placenta‐mediated axis, in which trophoblast/placental epitranscriptomics are altered and fetal supply and signaling are secondarily affected, and (ii) a direct fetal tissue axis, in which maternal cues modify epitranscriptomic machinery within fetal organs, with effects on embryonic and placental development. 68 , 113 , 117 , 122 , 126 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 For instance, maternal protein restriction in rat has been associated with altered m6A methylation in the developing fetal hypothalamus, coinciding with changes in metabolic gene expression. 68 On the other hand, maternal obesity has been shown to dramatically affect m6A mRNA profile in human placenta with adverse effects on fetal growth. 113 Another study in human showed that maternal stress and psychological disturbances can lead to substantial changes in fetal m6A RNA modification patterns in association with developmental growth. 137 These findings suggest that maternal nutritional status may modulate the fetal epitranscriptome, potentially leading to persistent physiological consequences (Box 1).
BOX 1. Key concepts referenced in this article.
Maternal effects: Influences of a mother's genotype (genetic maternal effects) and/or phenotype/environment (non‐genetic maternal effects) on offspring phenotype; may act via maternally supplied gene products and maternal‐state–dependent cues.
Genetic maternal effects: Offspring phenotype determined by the maternal genotype through maternally expressed transcripts/proteins deposited during oogenesis and early embryogenesis.
Non‐genetic maternal effects: Influences arising from the maternal environment/physiology/behavior (e.g., hormones, metabolites, cytokines, extracellular vesicles) during oogenesis, gestation, or early postnatal life can modulate RNA‐modifying enzymes and RNA marks in the conceptus.
Ex ovo vs in utero maternal influence: Ex ovo—maternal inputs are primarily pre‐packaged in the oocyte/egg and egg‐associated environments; in utero—additional post‐fertilization exposures occur via the oviduct, uterine milieu, and placenta.
Placenta‐mediated vs direct fetal tissue influence: Placenta‐mediated—maternal cues reprogram trophoblast/placental epitranscriptomic machinery, secondarily altering fetal supply/signals; direct fetal tissue—maternal cues traverse the placenta and act within fetal organs to modify local RNA‐modification pathways.
Epitranscriptomics: Study of chemical modifications on RNA that regulate its function post‐transcription.
m 6 A (N6‐methyladenosine): The most abundant mRNA modification; affects RNA stability, splicing, and translation.
RNA‐modifying enzymes: Proteins that install (writers), remove (erasers), or recognize (readers) RNA modifications.
Maternal RNAs: Transcripts deposited into the oocyte, guiding early embryonic development.
Maternal‐to‐zygotic transition (MZT): Developmental phase where embryonic control shifts from maternal RNAs to the zygotic genome.
Placental interface: The maternal–fetal exchange site transmits nutrients, signals, and possibly RNA regulators.
Developmental plasticity: The capacity of an organism to alter its developmental trajectory in response to environmental cues.
Non‐genetic inheritance: Transmission of traits across generations independent of DNA sequence changes.
Single‐cell epitranscriptomics: Techniques that profile RNA modifications at the single‐cell level for spatial and temporal precision.
TRIM‐away: A proteolysis method used to rapidly degrade endogenous proteins, including RNA‐modifying enzymes.
Phenotypic programming: The process by which environmental factors during development shape long‐term traits.
Timing appears to be a key factor in this interaction. During pre‐implantation development, the zygote undergoes maternal‐to‐zygotic transition (MZT), during which maternal RNAs are degraded and zygotic transcription begins; major ZGA occurs at the two‐cell stage in mouse and around the eight‐cell stage in human. In zebrafish, by contrast, MZT is coupled to the midblastula transition (MBT), which occurs at approximately the 10th cleavage cycle (∼1000‐cell stage), when bulk ZGA is initiated, shaping when maternal epitranscriptomic influences can act in ex ovo versus in utero contexts. 58 , 141 It is during this phase that maternal signals, including metabolites and hormones, could influence the expression or activity of RNA‐modifying enzymes, as shown for METTL3‐dependent m6A in mouse oocytes/embryos, and for cytoplasmic polyadenylation control of maternal transcripts in zebrafish. 62 , 67 , 108 , 142 , 143 , 144 In later stages, such as gastrulation and organogenesis, 90 , 145 , 146 tissue‐specific m6A RNA modification patterns may also be shaped by maternal conditions, with direct fetal tissue modulation observed in mouse liver (postnatal; sphingolipid/m6A programs), rat fetal hypothalamus (protein restriction), and mouse fetal brain/intestine (maternal microbiome), alongside distinct placenta‐mediated effects in placental compartments. 118 , 119 , 120 , 147 , 148 , 149 , 150 Furthermore, the placenta itself represents a dynamic interface between maternal and fetal environments. 151 Epitranscriptomic regulation (m6A) in human and mouse placenta has been increasingly recognized, including trophoblast cell studies and human trophoblast stem cells showing METTL3‐dependent programs, and patient placentas from preeclampsia cohorts, with studies identifying m6A‐dependent pathways that affect nutrient transport, vascular development, and immune modulation. 102 , 111 , 114 , 115 , 116 , 149 , 152 , 153 For clarity, placenta‐mediated influence refers to changes in trophoblast/placental epitranscriptomic machinery (e.g., METTL3–METTL14, FTO/ALKBH5, YTH readers) that secondarily reprogram fetal physiology, whereas direct fetal tissue influence refers to maternal cues acting within fetal organs (e.g., brain, liver, hypothalamus) to modify local RNA‐modifying enzymes and targets. Given the placenta's role in interpreting and relaying maternal cues, it is plausible that epitranscriptomic changes in placental RNA may also reflect or mediate maternal effects. Collectively, these findings support a model in which maternal influences on the fetal epitranscriptome are not only possible but likely occur during defined developmental windows when cells are transcriptionally and metabolically primed for such modulation. Investigating these windows further could yield insights into how early environmental exposures are translated into molecular phenotypes, with consequences for long‐term health and development.
4. POTENTIAL MEDIATORS: MATERNAL RNAs AND RNA‐MODIFYING ENZYMES
A central question in linking maternal effects to epitranscriptomic regulation is identifying the molecular mediators responsible for transmitting information from the mother to the embryonic RNA landscape. Two highly plausible routes have been proposed: maternal RNAs deposited during oogenesis and the regulation of RNA‐modifying enzymes in the embryo or placenta (mechanistic instances and routes are compiled in Table 1). Maternal transcripts orchestrate early developmental events and, in many species, persist beyond ZGA. For example, in oviparous models such as Drosophila and zebrafish, maternally supplied RNAs and proteins frequently perdure through gastrulation and even segmentation, whereas in mammals, where ZGA occurs earlier, most maternal transcripts are cleared sooner via regulated deadenylation and decay. 53 , 54 , 55 , 56 , 58 , 154 Large‐scale maternal‐effect screens in Drosophila and zebrafish are consistent with this view. 5 , 6 , 7 , 8 , 9 Recent studies have suggested that these maternal RNAs are not merely inert templates but may carry post‐transcriptional modifications such as m6A, demonstrated in Xenopus oocytes, mouse oocytes/embryos, Drosophila embryos, and zebrafish during MZT, as well as maternal mRNA m5C in Drosophila, which influence their translation efficiency, subcellular localization, and degradation kinetics. 52 , 57 , 58 , 66 , 67 , 107 Thus, the maternal RNA pool may encode regulatory information both in sequence and in epitranscriptomic form, with reader‐mediated control exhibiting species‐specific features; for example, zebrafish YTHDF reader redundancy. 127
In parallel, maternal influences on the enzymatic machinery responsible for RNA modifications have also been noted. For example, the expression of METTL3, a major m6A writer enzyme, has been implicated in both routes: placenta‐mediated regulation during implantation/trophoblast programs in mouse/human systems and direct fetal tissue regulation during murine oocyte/embryo MZT and organogenesis. 57 , 108 , 109 , 110 , 126 Similarly, maternal stress has been linked to altered expression of FTO, an m6A demethylase, in fetal tissues such as porcine embryos under heat stress and human chorionic villi at the maternal–fetal interface. 100 , 121 Maternal factors can influence the abundance or activity of RNA‐modifying enzymes via three routes: (i) peri‐conception and pre‐implantation exposure to oviductal and uterine secretions; (ii) a placenta‐mediated pathway in which trophoblast/placental epitranscriptomic machinery is reprogrammed and fetal supply lines are altered; and (iii) direct fetal tissue pathways involving transplacental transfer of hormones, metabolites, cytokines, and extracellular vesicles (EVs) that act within fetal organs. The possibility that maternal hormones, cytokines, or metabolites affect the abundance or activity of these RNA‐modifying enzymes presents a promising avenue for mechanistic studies (see Figure 2 for different potential scenarios). Moreover, recent work has shown that EVs released from maternal tissues can carry RNAs and RNA‐binding proteins into fetal circulation, for example, bovine blastocyst/endometrium co‐culture and human blastocyst uptake of endometrial EVs. 123 , 124 , 125 These findings support both a placenta‐mediated exchange (maternal–endometrial–trophoblast) and direct fetal tissue exposure to epitranscriptomically active cargo. Though largely speculative at present, this mechanism would provide a direct route for maternal epitranscriptomic signals to reach developing fetal tissues. Taken together, these mechanisms underscore the plausibility that maternal effects could influence offspring development via modulation of RNA modifications, either through the deposition of modified RNAs or the regulation of RNA‐modifying enzymes. As tools for detecting and manipulating RNA modifications become more precise, these hypotheses are increasingly testable and could reveal a new class of maternally derived regulatory cues in development.
FIGURE 2.

Potential outcomes for regulatory influence of maternal versus zygotic RNA modification machinery in early developmental stages.
5. EVIDENCE FOR MATERNAL‐EPITRANSCRIPTOMIC CROSSTALK: WHAT DO WE KNOW SO FAR?
While the direct regulatory connections between maternal effects and epitranscriptomics are still emerging, several independent lines of research support the plausibility of their interaction (Table 1). Early clues come from models in which maternal conditions alter RNA methylation landscapes in embryonic and fetal tissues. In one notable example, the maternal microbiome was shown to affect m6A patterns in the developing mouse fetal brain and intestine of mouse fetuses, illustrating a direct fetal tissue route in which maternal metabolites/signals reach and reprogram fetal epitranscriptomic machinery. 117 This finding provided one of the first functional demonstrations of maternal influence on the fetal epitranscriptome. Further supporting evidence arises from maternal nutritional studies. 18 , 68 , 117 , 155 , 156 For instance, maternal methionine supplementation, known to affect methyl group availability, has been associated with shifts in fetal brain m6A levels; this implies that methyl donors in the maternal diet could influence the activity of methyltransferase complexes. 156 Similarly, maternal exposure to a low‐protein diet in rats (fetal hypothalamus) and a high‐fat diet in mice (offspring adipose/skeletal muscle and liver) has been linked to altered expression of m6A writers and erasers in both placental and fetal tissues, with downstream consequences for metabolic gene expression and differentiation outcomes. 18 , 68 , 117 , 155 , 157
Stress and inflammation in the maternal organism have also been associated with epitranscriptomic changes in offspring. 69 , 102 , 130 , 140 , 158 , 159 Inflammatory cytokines, glucocorticoids, and oxidative stress, factors commonly elevated during gestational stress, can influence the abundance of m6A RNA‐modifying enzymes and alter the translation of key regulatory transcripts in human placenta. 112 , 160 These stress‐responsive changes have been observed in brain, liver, and hematopoietic systems during fetal development in mice, and in human placenta 140 , 160 ; they point toward an environmentally sensitive epitranscriptomic layer that may reflect maternal physiological states. Although most of these studies are correlational, they set the stage for more mechanistic investigations. A major limitation so far has been the difficulty in temporally and spatially resolving RNA modifications in early development. However, innovations in RNA immunoprecipitation and sequencing, combined with targeted gene editing tools, are beginning to overcome these barriers. 161 , 162 Single‐cell m6A mapping, for example, has allowed researchers to track RNA methylation states across cell types and developmental stages in vivo in mouse tissues 163 , 164 ; while still technically challenging, it holds promise for tracing maternal signal‐dependent changes in RNA modification patterns. The accumulating evidence underscores a growing consensus that maternal conditions do influence the epitranscriptomic state of offspring; however, the mechanistic links remain to be fully clarified. The current data justify targeted experiments to determine whether these RNA modifications are merely correlative signatures of maternal states or functionally involved in transmitting phenotypic effects across developmental time.
6. EVOLUTIONARY AND ECOLOGICAL IMPLICATIONS OF MATERNAL EPITRANSCRIPTOMIC INFLUENCE
If maternal regulation of offspring epitranscriptomics proves to be a functional mechanism, it could represent a powerful form of developmental plasticity, 89 , 165 enabling rapid phenotypic tuning in response to environmental variability without requiring genetic change. 93 , 94 , 166 From an evolutionary standpoint, such a system would provide a mechanism for the transgenerational transmission of adaptive traits in response to maternal environmental cues, 144 , 167 particularly under conditions where environmental conditions fluctuate more rapidly than genetic adaptation can occur. 93 In ecological systems, maternal effects have often been interpreted as anticipatory mechanisms, preparing offspring for expected environmental conditions based on maternal experience. 14 , 15 Epitranscriptomic modifications, being reversible yet stable across short developmental windows, may offer an ideal molecular substrate for such transient, tunable responses. 165 , 168 By modulating RNA stability and translation in specific tissues, maternal environments might prime offspring physiology or behavior in context‐specific ways: for example, enhancing stress resilience, altering metabolic capacity, or modifying developmental timing. 102 , 169 , 170 , 171 This potential utility is further amplified in species with external development, where maternal investment through the oocyte becomes the primary avenue for environmental signaling. 172 , 173 , 174 In these systems, maternal provisioning of modified RNAs or regulators of RNA modification may serve as early warning systems, tuning gene expression programs in advance of environmental exposure.
Despite these possibilities, the evolutionary dynamics of RNA modification systems remain poorly understood. Few studies have assessed the heritability, variability, or fitness consequences of altered RNA modification profiles across generations. 126 , 139 , 175 If maternal epitranscriptomic regulation is indeed a widespread mechanism, it may challenge conventional models of non‐genetic inheritance by providing a rapid, semi‐stable, and reversible method for transferring information from mother to offspring. Furthermore, different species may rely on distinct epitranscriptomic strategies based on their reproductive biology, embryonic timing, or environmental unpredictability. Comparative studies across taxa, especially those with contrasting maternal provisioning modes, 176 will be essential for understanding how and why such mechanisms may have evolved. These questions open up not only new empirical challenges but also opportunities to refine theoretical models of inheritance, adaptation, and plasticity.
7. EXPERIMENTAL CHALLENGES AND EMERGING TOOLS TO UNCOVER MECHANISTIC LINKS
Investigating the potential mechanistic connections between maternal effects and epitranscriptomic regulation presents significant experimental hurdles, primarily due to the dynamic and context‐specific nature of both systems. First, RNA modifications are often transient and highly cell‐type‐specific; detecting these marks in early embryos, which are composed of rapidly dividing and differentiating cells, requires both spatial and temporal resolution that few current methods fully provide. Another challenge lies in distinguishing whether observed RNA modifications are a direct consequence of maternal signals or arise as secondary responses during embryonic development. This distinction necessitates experimental systems that allow precise manipulation of maternal environments while tracking downstream molecular consequences in fetal tissues at defined stages.
To address these challenges, a growing set of molecular tools has been applied. Antibody‐based techniques such as MeRIP‐seq and miCLIP have enabled transcriptome‐wide mapping of RNA modifications, particularly m6A. 98 These methods, though powerful, are limited by antibody specificity and often require high input material, making them less suitable for early developmental samples. More recently, the development of single‐cell epitranscriptomic methods has begun to fill this gap, allowing for resolution of RNA modifications at the level of individual cells or lineages. 177 In addition, the advent of direct RNA nanopore sequencing has enabled transcriptome‐wide profiling of m6A modifications without the need for chemical conversion or enrichment, offering a powerful advantage for studying RNA methylation at the zygotic or fetal stage with single‐molecule precision. 99 In parallel, CRISPR‐based tools have been adapted to target RNA methylation enzymes to specific transcripts; although still in early development, these systems allow direct testing of the functional role of epitranscriptomic marks in gene regulation and development. 178 , 179 Of particular relevance to maternal–fetal studies is the application of TRIM‐away, a proteolysis‐based technique that enables acute depletion of specific endogenous proteins, including RNA‐modifying enzymes. 180 TRIM‐away has proven effective in depleting RNA methyltransferases or demethylases in zebrafish and Xenopus embryos without genetic manipulation, offering a rapid and reversible method for testing the requirement of these enzymes during sensitive developmental windows. 180 , 181 , 182 This tool may be especially valuable for dissecting the temporal dynamics of maternal influences on the fetal epitranscriptome. Despite these advancements, technical and interpretive challenges remain. Cross‐reactivity of antibodies, the functional redundancy of RNA modification enzymes, and the incomplete understanding of modification “readers” complicate the attribution of phenotypic effects to specific molecular events. Nevertheless, with the continuing refinement of tools and model systems, the field is well‐positioned to explore how maternal cues may operate through RNA modifications to shape developmental trajectories.
8. CONCLUDING THOUGHTS: CONCEPTUAL BRIDGES AND OPEN QUESTIONS
The possibility that maternal effects and epitranscriptomic regulation intersect to shape offspring development presents a compelling framework for rethinking non‐genetic inheritance. While both domains have been extensively studied in isolation, their potential integration opens a new dimension in developmental biology, one where environmental cues from the maternal organism could be translated into post‐transcriptional regulatory changes in the offspring, with implications for phenotype, health, and even evolutionary fitness. This perspective article has outlined several lines of evidence that support such a connection; however, it must be emphasized that definitive mechanistic links remain largely speculative at present. Observations that maternal nutritional, microbial, or stress‐related environments alter RNA modification patterns in fetal tissues are intriguing, yet causality has not been consistently demonstrated. Whether these RNA modifications are central mediators or merely responsive markers remains unresolved in many contexts.
Key questions remain to be addressed. For instance, how specific and selective are maternal influences on RNA modification machinery? Are these changes preserved through cell divisions, and can they be transmitted beyond one generation? Which transcripts are most susceptible to maternal modulation, and how do these modifications intersect with other regulatory layers such as microRNAs, alternative splicing, or chromatin state? Furthermore, to what extent do these interactions vary across tissues, developmental windows, or species?
Addressing these questions requires multidisciplinary collaboration; developmental biologists, molecular geneticists, and RNA biochemists must work in concert with systems biologists and evolutionary theorists to establish a common language and set of priorities. The development of temporally controlled, tissue‐specific tools, such as TRIM‐away, inducible CRISPR interference systems, and advanced imaging of modified RNAs in vivo, will be essential to disentangle maternal inputs from autonomous embryonic processes. Moreover, more comparative studies across model organisms and ecological systems are needed to test the generality, adaptability, and interactomics of this regulatory axis. 183 The purpose of this article has not been to assert a definitive model but rather to highlight an underexplored conceptual space that may prove fruitful for future research. By framing maternal effects and epitranscriptomics as potentially interconnected systems, the goal is to stimulate discussion, generate testable hypotheses, and encourage researchers in both fields to consider overlapping mechanisms. Whether or not maternal regulation of the offspring epitranscriptome proves to be widespread or only context‐specific, the exploration of this intersection promises to deepen our understanding of how environment, regulation, and inheritance are woven together in shaping organismal development. In conclusion, the maternal–epitranscriptomic axis, while still in its theoretical infancy, offers a promising conceptual bridge in developmental biology—one that may ultimately transform how we understand phenotypic plasticity, intergenerational signaling, and the molecular logic of early life.
FUNDING INFORMATION
The author received no specific funding for this work.
CONFLICT OF INTEREST STATEMENT
The author declares that he has no competing interests.
ACKNOWLEDGMENT
Open access publishing facilitated by Helsingin yliopisto, as part of the Wiley ‐ FinELib agreement.
DATA AVAILABILITY STATEMENT
Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
REFERENCES
- 1. Mousseau TA, Uller T, Wapstra E, Badyaev AV. Evolution of maternal effects: past and present. Philos Trans R Soc Lond B Biol Sci. 2009;364:1035‐1038. doi: 10.1098/RSTB.2008.0303 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Wolf JB, Wade MJ. What are maternal effects (and what are they not)? Philos Trans R Soc Lond B Biol Sci. 2009;364:1107‐1115. doi: 10.1098/RSTB.2008.0238 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Mitchell LE. Maternal effect genes: update and review of evidence for a link with birth defects. Hum Genet Genomics Adv. 2022;3:100067. doi: 10.1016/J.XHGG.2021.100067/ATTACHMENT/126E6053-5ED7-4E22-944E-36D1D703C421/MMC1.XLSX [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Wolf JB. Gene interactions from maternal effects. Evolution. 2000;54:1882‐1898. doi: 10.1111/J.0014-3820.2000.TB01235.X [DOI] [PubMed] [Google Scholar]
- 5. Dosch R, Wagner DS, Mintzer KA, Runke G, Wiemelt AP, Mullins MC. Maternal control of vertebrate development before the midblastula transition: mutants from the zebrafish I. Dev Cell. 2004;6:771‐780. doi: 10.1016/J.DEVCEL.2004.05.002/ATTACHMENT/C0BC0418-7E35-4A98-BC46-D4DD65422A66/MMC3.MP4 [DOI] [PubMed] [Google Scholar]
- 6. Luschnig S, Moussian B, Krauss J, Desjeux I, Perkovic J, Nüsslein‐Volhard C. An F1 genetic screen for maternal‐effect mutations affecting embryonic pattern formation in Drosophila melanogaster. Genetics. 2004;167:325‐342. doi: 10.1534/GENETICS.167.1.325 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Pelegri F, Dekens MPS, Schulte‐Merker S, Maischein HM, Weiler C, Nüsslein‐Volhard C. Identification of recessive maternal‐effect mutations in the zebrafish using a gynogenesis‐based method. Dev Dyn. 2004;231:324‐335. doi: 10.1002/DVDY.20145 [DOI] [PubMed] [Google Scholar]
- 8. Pelegri F, Mullins MC. Genetic screens for maternal‐effect mutations. Methods Cell Biol. 2004;77:21‐51. doi: 10.1016/S0091-679X(04)77002-8 [DOI] [PubMed] [Google Scholar]
- 9. Schüpbach T, Wieschaus E. Maternal‐effect mutations altering the anterior‐posterior pattern of the drosophila embryo. Roux Arch Dev Biol. 1986;195:302‐317. doi: 10.1007/BF00376063/METRICS [DOI] [PubMed] [Google Scholar]
- 10. Moravec CE, Voit GC, Otterlee J, Pelegri F. Identification of maternal‐effect genes in zebrafish using maternal crispants. Development. 2021;148:dev199536. doi: 10.1242/DEV.199536/VIDEO-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Wang Y, Wang X, Wang W, Cao Z, Zhang Y, Liu G. Screening of functional maternal‐specific chromatin regulators in early embryonic development of zebrafish. Commun Biol. 2024;7(1):1354‐. doi: 10.1038/s42003-024-06983-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Zhang C, Lu T, Zhang Y, et al. Rapid generation of maternal mutants via oocyte transgenic expression of CRISPR‐Cas9 and sgRNAs in zebrafish. Sci Adv. 2021;7:eabg4243. doi: 10.1126/SCIADV.ABG4243 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Zhang F, Li X, He M, et al. Efficient generation of zebrafish maternal‐zygotic mutants through transplantation of ectopically induced and Cas9/gRNA targeted primordial germ cells. J Genet Genomics. 2020;47:37‐47. doi: 10.1016/J.JGG.2019.12.004 [DOI] [PubMed] [Google Scholar]
- 14. Galloway LF. Maternal effects provide phenotypic adaptation to local environmental conditions. New Phytol. 2005;166:93‐100. doi: 10.1111/J.1469-8137.2004.01314.X [DOI] [PubMed] [Google Scholar]
- 15. Potticary AL, Duckworth RA. Multiple environmental stressors induce an adaptive maternal effect. Am Nat. 2020;196:487‐500. doi: 10.1086/710210/ASSET/IMAGES/LARGE/FG2.JPEG [DOI] [PubMed] [Google Scholar]
- 16. Räsänen K, Kruuk LEB. Maternal effects and evolution at ecological time‐scales. Funct Ecol. 2007;21:408‐421. doi: 10.1111/J.1365-2435.2007.01246.X [DOI] [Google Scholar]
- 17. Wells JCK. The thrifty phenotype as an adaptive maternal effect. Biol Rev. 2007;82:143‐172. doi: 10.1111/J.1469-185X.2006.00007.X [DOI] [PubMed] [Google Scholar]
- 18. Melnik BC, Weiskirchen R, Stremmel W, John SM, Schmitz G. Risk of fat mass‐ and obesity‐associated gene‐dependent obesogenic programming by formula feeding compared to breastfeeding. Nutrients. 2024;16:2451. doi: 10.3390/NU16152451 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Ruebel ML, Latham KE. Listening to mother: long‐term maternal effects in mammalian development. Mol Reprod dev. 2020;87:399‐408. doi: 10.1002/MRD.23336 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Besson AA, Lagisz M, Senior AM, Hector KL, Nakagawa S. Effect of maternal diet on offspring coping styles in rodents: a systematic review and meta‐analysis. Biol Rev. 2016;91:1065‐1080. doi: 10.1111/BRV.12210 [DOI] [PubMed] [Google Scholar]
- 21. Burgueño AL, Juárez YR, Genaro AM, Tellechea ML. Prenatal stress and later metabolic consequences: systematic review and meta‐analysis in rodents. Psychoneuroendocrinology. 2020;113:104560. doi: 10.1016/J.PSYNEUEN.2019.104560 [DOI] [PubMed] [Google Scholar]
- 22. Edwards PD, Lavergne SG, McCaw LK, et al. Maternal effects in mammals: broadening our understanding of offspring programming. Front Neuroendocrinol. 2021;62:100924. doi: 10.1016/J.YFRNE.2021.100924 [DOI] [PubMed] [Google Scholar]
- 23. Grueber CE, Gray LJ, Morris KM, Simpson SJ, Senior AM. Intergenerational effects of nutrition on immunity: a systematic review and meta‐analysis. Biol Rev. 2018;93:1108‐1124. doi: 10.1111/BRV.12387 [DOI] [PubMed] [Google Scholar]
- 24. Kaiser S, Sachser N. The effects of prenatal social stress on behaviour: mechanisms and function. Neurosci Biobehav Rev. 2005;29:283‐294. doi: 10.1016/J.NEUBIOREV.2004.09.015 [DOI] [PubMed] [Google Scholar]
- 25. Lecorguillé M, Teo S, Phillips CM. Maternal dietary quality and dietary inflammation associations with offspring growth, placental development, and DNA methylation. Nutrients. 2021;13:3130. doi: 10.3390/NU13093130 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Ma J, Cain KD. Maternal effects on offspring immunity in fish. Fish Shellfish Immunol. 2025;161:110261. doi: 10.1016/J.FSI.2025.110261 [DOI] [PubMed] [Google Scholar]
- 27. Pollak DD, Weber‐Stadlbauer U. Transgenerational consequences of maternal immune activation. Semin Cell dev Biol. 2020;97:181‐188. doi: 10.1016/J.SEMCDB.2019.06.006 [DOI] [PubMed] [Google Scholar]
- 28. Bjorklund DF. Mother knows best: epigenetic inheritance, maternal effects, and the evolution of human intelligence. Dev Rev. 2006;26:213‐242. doi: 10.1016/J.DR.2006.02.007 [DOI] [Google Scholar]
- 29. Cummings JA, Clemens LG, Nunez AA. Mother counts: how effects of environmental contaminants on maternal care could affect the offspring and future generations. Front Neuroendocrinol. 2010;31:440‐451. doi: 10.1016/J.YFRNE.2010.05.004 [DOI] [PubMed] [Google Scholar]
- 30. Ho DH. Transgenerational epigenetics: the role of maternal effects in cardiovascular development. Integr Comp Biol. 2014;54:43‐51. doi: 10.1093/ICB/ICU031 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Shama LNS, Mark FC, Strobel A, Lokmer A, John U, Mathias Wegner K. Transgenerational effects persist down the maternal line in marine sticklebacks: gene expression matches physiology in a warming ocean. Evol Appl. 2016;9:1096‐1111. doi: 10.1111/EVA.12370 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Zhang TY, Bagot R, Parent C, et al. Maternal programming of defensive responses through sustained effects on gene expression. Biol Psychol. 2006;73:72‐89. doi: 10.1016/J.BIOPSYCHO.2006.01.009 [DOI] [PubMed] [Google Scholar]
- 33. Dworkin MB, Dworkin‐Rastl E. Functions of maternal mRNA in early development. Mol Reprod dev. 1990;26:261‐297. doi: 10.1002/MRD.1080260310 [DOI] [PubMed] [Google Scholar]
- 34. Groothuis TGG, Hsu BY, Kumar N, Tschirren B. Revisiting mechanisms and functions of prenatal hormone‐mediated maternal effects using avian species as a model. Philos Trans R Soc B. 2019;374:20180115. doi: 10.1098/RSTB.2018.0115 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Harry ND, Zakas C. Maternal patterns of inheritance alter transcript expression in eggs. BMC Genomics. 2023;24:1‐13. doi: 10.1186/S12864-023-09291-8/FIGURES/5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Macartney EL, Crean AJ, Bonduriansky R. Parental dietary protein effects on offspring viability in insects and other oviparous invertebrates: a meta‐analysis. Curr Res Insect Sci. 2022;2:100045. doi: 10.1016/J.CRIS.2022.100045 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Meylan S, Miles DB, Clobert J. Hormonally mediated maternal effects, individual strategy and global change. Philos Trans R Soc Lond B Biol Sci. 2012;367:1647‐1664. doi: 10.1098/RSTB.2012.0020 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Moore MP, Whiteman HH, Martin RA. A mother's legacy: the strength of maternal effects in animal populations. Ecol Lett. 2019;22:1620‐1628. doi: 10.1111/ELE.13351 [DOI] [PubMed] [Google Scholar]
- 39. Adrian‐Kalchhauser I, Walser JC, Schwaiger M, Burkhardt‐Holm P. RNA sequencing of early round goby embryos reveals that maternal experiences can shape the maternal RNA contribution in a wild vertebrate. BMC Evol Biol. 2018;18:1‐14. doi: 10.1186/S12862-018-1132-2/TABLES/3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Almeida MV, de Jesus Domingues AM, Ketting RF. Maternal and zygotic gene regulatory effects of endogenous RNAi pathways. PLoS Genet. 2019;15:e1007784. doi: 10.1371/JOURNAL.PGEN.1007784 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41. Chille E, Strand E, Neder M, et al. Developmental series of gene expression clarifies maternal mRNA provisioning and maternal‐to‐zygotic transition in a reef‐building coral. BMC Genomics. 2021;22:1‐17. doi: 10.1186/S12864-021-08114-Y/FIGURES/7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42. Hu Y, Feng B, Wang F. Analysis of maternal effect genes from maternal mRNA in eggs of Sogatella furcifera . Heliyon. 2024;10:e34014. doi: 10.1016/j.heliyon.2024.e34014 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43. Videvall E, Sletvold N, Hagenblad J, Agren J, Hansson B. Strong maternal effects on gene expression in Arabidopsis lyrata hybrids. Mol Biol Evol. 2016;33:984‐994. doi: 10.1093/MOLBEV/MSV342 [DOI] [PubMed] [Google Scholar]
- 44. Agrelius TC, Dudycha JL. Maternal effects in the model system daphnia: the ecological past meets the epigenetic future. Heredity. 2025;134(2):142‐154. doi: 10.1038/s41437-024-00742-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45. Branco MR, King M, Perez‐Garcia V, et al. Maternal DNA methylation regulates early trophoblast development. Dev Cell. 2016;36:152‐163. doi: 10.1016/J.DEVCEL.2015.12.027/ATTACHMENT/69AB44F7-E5F3-4258-8C01-CA29AA70844D/MMC3.PDF [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Champagne FA, Curley JP. Epigenetic mechanisms mediating the long‐term effects of maternal care on development. Neurosci Biobehav Rev. 2009;33:593‐600. doi: 10.1016/J.NEUBIOREV.2007.10.009 [DOI] [PubMed] [Google Scholar]
- 47. Das A, Iwata‐Otsubo A, Destouni A, et al. Epigenetic, genetic and maternal effects enable stable centromere inheritance. Nat Cell Biol. 2022;24(5):748‐756. doi: 10.1038/s41556-022-00897-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48. Meaney MJ, Szyf M. Maternal care as a model for experience‐dependent chromatin plasticity? Trends Neurosci. 2005;28:456‐463. doi: 10.1016/J.TINS.2005.07.006/ASSET/758AC0F9-90ED-413A-869D-9F33E6FBBFBF/MAIN.ASSETS/GR5.SML [DOI] [PubMed] [Google Scholar]
- 49. Champagne FA. Maternal imprints and the origins of variation. Horm Behav. 2011;60:4‐11. doi: 10.1016/J.YHBEH.2011.02.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. Sharp GC, Lawlor DA, Richardson SS. It's the mother!: how assumptions about the causal primacy of maternal effects influence research on the developmental origins of health and disease. Soc Sci Med. 2018;213:20‐27. doi: 10.1016/J.SOCSCIMED.2018.07.035 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51. Sharp GC, Salas LA, Monnereau C, et al. Maternal BMI at the start of pregnancy and offspring epigenome‐wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium. Hum Mol Genet. 2017;26:4067‐4085. doi: 10.1093/HMG/DDX290 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52. Liu J, Huang T, Chen W, et al. Developmental mRNA m5C landscape and regulatory innovations of massive m5C modification of maternal mRNAs in animals. Nat Commun. 2022;131:1‐13. doi: 10.1038/s41467-022-30210-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53. Schier AF. The maternal‐zygotic transition: death and birth of RNAs. Science. 2007;316:406‐407. doi: 10.1126/SCIENCE.1140693 [DOI] [PubMed] [Google Scholar]
- 54. Sha QQ, Zhang J, Fan HY. A story of birth and death: mRNA translation and clearance at the onset of maternal‐to‐zygotic transition in mammals. Biol Reprod. 2019;101:579‐590. doi: 10.1093/BIOLRE/IOZ012 [DOI] [PubMed] [Google Scholar]
- 55. Winata CL, Korzh V. The translational regulation of maternal mRNAs in time and space. FEBS Lett. 2018;592:3007‐3023. doi: 10.1002/1873-3468.13183 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56. Yang G, Xin Q, Dean J. Degradation and translation of maternal mRNA for embryogenesis. Trends Genet. 2024;40:238‐249. doi: 10.1016/J.TIG.2023.12.008/ASSET/0DCE9A94-DE3E-4932-ADCF-936F61416B23/MAIN.ASSETS/GR4.SML [DOI] [PubMed] [Google Scholar]
- 57. Zhang G, Xu Y, Wang X, et al. Dynamic FMR1 granule phase switch instructed by m6A modification contributes to maternal RNA decay. Nat Commun. 2022;131(13):1‐16. doi: 10.1038/s41467-022-28547-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58. Zhao BS, Wang X, Beadell AV, et al. M6 A‐dependent maternal mRNA clearance facilitates zebrafish maternal‐to‐zygotic transition. Nature. 2017;542:475‐478. doi: 10.1038/nature21355 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59. Bettegowda A, Smith GW. Mechanisms of maternal mRNA regulation: implications for mammalian early embryonic development. Front Biosci. 2007;12:3713‐3726. doi: 10.2741/2346 [DOI] [PubMed] [Google Scholar]
- 60. Farley BM, Ryder SP. Regulation of maternal mRNAs in early development. Crit Rev Biochem Mol Biol. 2008;43:135‐162. doi: 10.1080/10409230801921338 [DOI] [PubMed] [Google Scholar]
- 61. Kojima ML, Hoppe C, Giraldez AJ. The maternal‐to‐zygotic transition: reprogramming of the cytoplasm and nucleus. Nat Rev Genet. 2024;26(4):245‐267. doi: 10.1038/s41576-024-00792-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62. Despic V, Neugebauer KM. RNA tales—how embryos read and discard messages from mom. J Cell Sci. 2018;131:jcs201996. doi: 10.1242/JCS.201996 [DOI] [PubMed] [Google Scholar]
- 63. Lorenzo‐Orts L, Pauli A. The molecular mechanisms underpinning maternal mRNA dormancy. Biochem Soc Trans. 2024;52:861‐871. doi: 10.1042/BST20231122 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64. Vejnar CE, Messih MA, Takacs CM, et al. Genome wide analysis of 3′ UTR sequence elements and proteins regulating mRNA stability during maternal‐to‐zygotic transition in zebrafish. Genome Res. 2019;29:1100‐1114. doi: 10.1101/GR.245159.118 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65. Ding Y, Zheng Y, Wang J, et al. Recurrent RNA edits in human preimplantation potentially enhance maternal mRNA clearance. Commun Biol. 2022;5:1400. doi: 10.1038/S42003-022-04338-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66. Wu Y, Xu X, Qi M, et al. N6‐methyladenosine regulates maternal RNA maintenance in oocytes and timely RNA decay during mouse maternal‐to‐zygotic transition. Nat Cell Biol. 2022;24(6):917‐927. doi: 10.1038/s41556-022-00915-x [DOI] [PubMed] [Google Scholar]
- 67. Zhu W, Ding Y, Meng J, et al. Reading and writing of mRNA m6A modification orchestrate maternal‐to‐zygotic transition in mice. Genome Biol. 2023;24:1‐16. doi: 10.1186/S13059-023-02918-9 /FIGURES/2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68. Frapin M, Guignard S, Meistermann D, et al. Maternal protein restriction in rats alters the expression of genes involved in mitochondrial metabolism and epitranscriptomics in fetal hypothalamus. Nutrients. 2020;12:1464. doi: 10.3390/NU12051464 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69. Wang Q, Pan M, Zhang T, et al. Fear stress during pregnancy affects placental m6A‐modifying enzyme expression and epigenetic modification levels. Front Genet. 2022;13:927615. doi: 10.3389/FGENE.2022.927615/BIBTEX [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70. Wu S, Liu K, Zhou B, Wu S. N6‐methyladenosine modifications in maternal‐fetal crosstalk and gestational diseases. Front Cell Dev Biol. 2023;11:1164706. doi: 10.3389/FCELL.2023.1164706/XML/NLM [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71. Arzumanian VA, Dolgalev GV, Kurbatov IY, Kiseleva OI, Poverennaya EV. Epitranscriptome: review of top 25 Most‐studied RNA modifications. Int J Mol Sci. 2022;23:13851. doi: 10.3390/IJMS232213851/S1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72. Moshitch‐Moshkovitz S, Dominissini D, Rechavi G. The epitranscriptome toolbox. Cell. 2022;185:764‐776. doi: 10.1016/J.CELL.2022.02.007/ASSET/E41797F6-C9DF-41CA-9E0B-6B5E1F317329/MAIN.ASSETS/GR2.JPG [DOI] [PubMed] [Google Scholar]
- 73. Motorin Y, Helm M. RNA nucleotide methylation: 2021 update. Wiley Interdiscip Rev RNA. 2022;13:e1691. doi: 10.1002/WRNA.1691 [DOI] [PubMed] [Google Scholar]
- 74. Ahi EP. Regulation of skeletogenic pathways by m6A RNA modification: a comprehensive review. Calcif Tissue Int. 2025;116(1):1‐23. doi: 10.1007/S00223-025-01367-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 75. Singh P, Ahi EP. The importance of alternative splicing in adaptive evolution. Mol Ecol. 2022;31:1928‐1938. doi: 10.1111/mec.16377 [DOI] [PubMed] [Google Scholar]
- 76. Zhao BS, Roundtree IA, He C. Post‐transcriptional gene regulation by mRNA modifications. Nat Rev Mol Cell Biol. 2016;18:31‐42. doi: 10.1038/nrm.2016.132 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77. Meyer KD. m6A‐mediated translation regulation. Biochim Biophys Acta—Gene Regul Mech. 2019;1862:301‐309. doi: 10.1016/J.BBAGRM.2018.10.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 78. Meyer KD, Jaffrey SR. The dynamic epitranscriptome: N6‐methyladenosine and gene expression control. Nat Rev Mol Cell Biol. 2014;15(5):313‐326. doi: 10.1038/nrm3785 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 79. Desrosiers R, Friderici K, Rottman F. Identification of methylated nucleosides in messenger RNA from Novikoff hepatoma cells. Proc Natl Acad Sci USA. 1974;71:3971‐3975. doi: 10.1073/PNAS.71.10.3971 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 80. Perry RP, Kelley DE, Friderici K, Rottman F. The methylated constituents of L cell messenger RNA: evidence for an unusual cluster at the 5′ terminus. Cell. 1975;4:387‐394. doi: 10.1016/0092-8674(75)90159-2 [DOI] [PubMed] [Google Scholar]
- 81. Bokar JA, Shambaugh ME, Polayes D, Matera AG, Rottman FM. Purification and cDNA cloning of the AdoMet‐binding subunit of the human mRNA (N6‐adenosine)‐methyltransferase. RNA. 1997;3:1233‐1247. [PMC free article] [PubMed] [Google Scholar]
- 82. Liu J, Yue Y, Han D, et al. A METTL3–METTL14 complex mediates mammalian nuclear RNA N6‐adenosine methylation. Nat Chem Biol. 2013;10(10):93‐95. doi: 10.1038/nchembio.1432 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83. Jia G, Fu Y, Zhao X, et al. N6‐methyladenosine in nuclear RNA is a major substrate of the obesity‐associated FTO. Nat Chem Biol. 2011;7(12):885‐887. doi: 10.1038/nchembio.687 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 84. Zheng G, Dahl JA, Niu Y, et al. ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. Mol Cell. 2013;49:18‐29. doi: 10.1016/j.molcel.2012.10.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85. Wang X, Lu Z, Gomez A, et al. N6‐methyladenosine‐dependent regulation of messenger RNA stability. Nature. 2013;505(7481):117‐120. doi: 10.1038/nature12730 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86. Wiener D, Schwartz S. The epitranscriptome beyond m6A. Nat Rev Genet. 2020;22(2):119‐131. doi: 10.1038/s41576-020-00295-8 [DOI] [PubMed] [Google Scholar]
- 87. Che YH, Lee H, Kim YJ. New insights into the epitranscriptomic control of pluripotent stem cell fate. Exp Mol Med. 2022;54(10):1643‐1651. doi: 10.1038/s12276-022-00824-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88. Haran V, Lenka N. Deciphering the epitranscriptomic signatures in cell fate determination and development. Stem Cell Rev Rep. 2019;15:474‐496. doi: 10.1007/S12015-019-09894-3/METRICS [DOI] [PubMed] [Google Scholar]
- 89. Livneh I, Moshitch‐Moshkovitz S, Amariglio N, Rechavi G, Dominissini D. The m6A epitranscriptome: transcriptome plasticity in brain development and function. Nat Rev Neurosci. 2020;21:36‐51. doi: 10.1038/s41583-019-0244-z [DOI] [PubMed] [Google Scholar]
- 90. Yao Y, Liu P, Li Y, et al. Regulatory role of m6A epitranscriptomic modifications in normal development and congenital malformations during embryogenesis. Biomed Pharmacother. 2024;173:116171. doi: 10.1016/J.BIOPHA.2024.116171 [DOI] [PubMed] [Google Scholar]
- 91. Zhang M, Zhai Y, Zhang S, Dai X, Li Z. Roles of N6‐Methyladenosine (m6A) in stem cell fate decisions and early embryonic development in mammals. Front Cell Dev Biol. 2020;8:566543. doi: 10.3389/FCELL.2020.00782/XML/NLM [DOI] [PMC free article] [PubMed] [Google Scholar]
- 92. Ahi EP, Schenekar T. The promise of environmental RNA research beyond mRNA. Mol Ecol. 2025;34:e17787. doi: 10.1111/MEC.17787 [DOI] [PubMed] [Google Scholar]
- 93. Ahi EP, Singh P. An emerging orchestrator of ecological adaptation: m6A regulation of post‐transcriptional mechanisms. Mol Ecol. 2024;34:17545. doi: 10.1111/MEC.17545 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 94. Cayir A, Byun HM, Barrow TM. Environmental epitranscriptomics. Environ Res. 2020;189:109885. doi: 10.1016/J.ENVRES.2020.109885 [DOI] [PubMed] [Google Scholar]
- 95. Frapin M, Quispe L, Troka J, et al. Density‐dependent expression of epitranscriptomic, stress, and appetite regulating genes in Atlantic salmon. Molecular Ecology 2026;35:e70230. doi: 10.1111/mec.70230 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 96. Ahi EP, Papakostas S, Moulistanos A, Schenekar T. MeRIP‐seq detects temperature related variation in methylated environmental RNA in fish. bioRxiv 2025. doi: 10.1101/2025.11.03.686443 [DOI]
- 97. Ahi EP, Khorshid M. Potentials of RNA biosensors in developmental biology. Dev Biol. 2025;526:173‐188. doi: 10.1016/J.YDBIO.2025.07.011 [DOI] [PubMed] [Google Scholar]
- 98. Sağlam B, Akgül B. An overview of current detection methods for RNA methylation. Int J Mol Sci. 2024;2024:3098. doi: 10.3390/IJMS25063098 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 99. Zhong ZD, Xie YY, Chen HX, et al. Systematic comparison of tools used for m6A mapping from nanopore direct RNA sequencing. Nat Commun. 2023;14:1‐14. doi: 10.1038/s41467-023-37596-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100. Li P, Lin Y, Ma H, et al. Epigenetic regulation in female reproduction: the impact of m6A on maternal‐fetal health. Cell Death Discov. 2025;111(11):1‐30. doi: 10.1038/s41420-025-02324-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 101. Khorshid M, Ahi EP. RNA Aptamers and Epitranscriptomics: Charting Unexplored Territories in RNA Biology. 2025. doi: 10.20944/PREPRINTS202509.1838.V1 [DOI] [PMC free article] [PubMed]
- 102. Liu H, Zheng J, Liao A. The regulation and potential roles of m6A modifications in early embryonic development and immune tolerance at the maternal‐fetal interface. Front Immunol. 2022;13:988130. doi: 10.3389/FIMMU.2022.988130/XML/NLM [DOI] [PMC free article] [PubMed] [Google Scholar]
- 103. Fawcett TW, Frankenhuis WE. Adaptive explanations for sensitive windows in development. Front Zool. 2015;12:1‐14. doi: 10.1186/1742-9994-12-S1-S3/TABLES/2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 104. Wells JCK. Developmental plasticity as adaptation: adjusting to the external environment under the imprint of maternal capital. Philos Trans R Soc B. 2019;374:20180122. doi: 10.1098/RSTB.2018.0122 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 105. Bedzhov I, Graham SJL, Leung CY, Zernicka‐Goetz M. Developmental plasticity, cell fate specification and morphogenesis in the early mouse embryo. Philos Trans R Soc Lond B Biol Sci. 2014;369:20130538. doi: 10.1098/RSTB.2013.0538 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 106. Quarto G, Li Greci A, Bizet M, et al. Fine‐tuning of gene expression through the Mettl3‐Mettl14‐Dnmt1 axis controls ESC differentiation. Cell. 2025;188:998‐1018.e26. doi: 10.1016/J.CELL.2024.12.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 107. Qi ST, Ma JY, Wang ZB, Guo L, Hou Y, Sun QY. N6‐methyladenosine sequencing highlights the involvement of mRNA methylation in oocyte meiotic maturation and embryo development by regulating translation in xenopus laevis. J Biol Chem. 2016;291:23020‐23026. doi: 10.1074/jbc.M116.748889 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 108. Sui X, Hu Y, Ren C, et al. METTL3‐mediated m6A is required for murine oocyte maturation and maternal‐to‐zygotic transition. Cell Cycle. 2020;19:391‐404. doi: 10.1080/15384101.2019.1711324 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 109. Xia H, Zhong C, Wu X, et al. Mettl3 mutation disrupts gamete maturation and reduces fertility in zebrafish. Genetics. 2018;208:729‐743. doi: 10.1534/GENETICS.117.300574/-/DC1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 110. Zheng ZH, le Zhang G, Jiang RF, et al. METTL3 is essential for normal progesterone signaling during embryo implantation via m6A‐mediated translation control of progesterone receptor. Proc Natl Acad Sci USA. 2023;120:e2214684120. doi: 10.1073/PNAS.2214684120/SUPPL_FILE/PNAS.2214684120.SD09.XLSX [DOI] [PMC free article] [PubMed] [Google Scholar]
- 111. Bian Y, Li J, Shen H, et al. WTAP dysregulation‐mediated HMGN3‐m6A modification inhibited trophoblast invasion in early‐onset preeclampsia. FASEB J. 2022;36:e22617. doi: 10.1096/FJ.202200700RR [DOI] [PubMed] [Google Scholar]
- 112. Chen R, Wang T, Tong H, et al. METTL3 and IGF2BP2 coordinately regulate FOSL1 mRNA via m6A modification, suppressing trophoblast invasion and contributing to fetal growth restriction. FASEB J. 2024;38:e70154. doi: 10.1096/FJ.202401665R [DOI] [PMC free article] [PubMed] [Google Scholar]
- 113. Shen WB, Ni J, Yao R, et al. Maternal obesity increases DNA methylation and decreases RNA methylation in the human placenta. Reprod Toxicol. 2022;107:90‐96. doi: 10.1016/J.REPROTOX.2021.12.002 [DOI] [PubMed] [Google Scholar]
- 114. Wang J, Gao F, Zhao X, Cai Y, Jin H. Integrated analysis of the transcriptome‐ wide m6A methylome in preeclampsia and healthy control placentas. PeerJ. 2020;8:e9880. doi: 10.7717/PEERJ.9880/SUPP-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 115. Taniguchi K, Kawai T, Kitawaki J, et al. Epitranscriptomic profiling in human placenta: N6‐methyladenosine modification at the 5′‐untranslated region is related to fetal growth and preeclampsia. FASEB J. 2020;34:494‐512. doi: 10.1096/FJ.201900619RR [DOI] [PMC free article] [PubMed] [Google Scholar]
- 116. Zhou W, Xue P, Yang Y, Xia L, Yu B. Research progress on N6‐methyladenosine in the human placenta. J Perinat Med. 2022;50:1115‐1123. doi: 10.1515/JPM-2021-0665 /MACHINEREADABLECITATION/RIS. [DOI] [PubMed] [Google Scholar]
- 117. Xiao Z, Liu S, Li Z, et al. The maternal microbiome programs the m6A epitranscriptome of the mouse fetal brain and intestine. Front Cell Dev Biol. 2022;10:882994. doi: 10.3389/FCELL.2022.882994/BIBTEX [DOI] [PMC free article] [PubMed] [Google Scholar]
- 118. Li X, Yang J, Zhu Y, Liu Y, Shi X, Yang G. Mouse maternal high‐fat intake dynamically programmed mRNA m6A modifications in adipose and skeletal muscle tissues in offspring. Int J Mol Sci. 2016;17:1336. doi: 10.3390/IJMS17081336 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 119. Fang J, Wu X, He J, et al. RBM15 suppresses hepatic insulin sensitivity of offspring of gestational diabetes mellitus mice via m6A‐mediated regulation of CLDN4. Mol Med. 2023;29:1‐16. doi: 10.1186/S10020-023-00615-8/TABLES/1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 120. Heng J, Tian M, Zhang W, Chen F, Guan W, Zhang S. Maternal heat stress regulates the early fat deposition partly through modification of m6A RNA methylation in neonatal piglets. Cell Stress Chaperones. 2019;24:635‐645. doi: 10.1007/S12192-019-01002-1/FIGURES/6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 121. Sun MH, Jiang WJ, Li XH, et al. High temperature‐induced m6A epigenetic changes affect early porcine embryonic developmental competence in pigs. Microsc Microanal. 2023;29:2174‐2183. doi: 10.1093/MICMIC/OZAD131 [DOI] [PubMed] [Google Scholar]
- 122. Song YP, Lv JW, Zhang ZC, et al. Effects of gestational arsenic exposures on placental and fetal development in mice: the role of Cyr61 m6A. Environ Health Perspect. 2023;131:097004. doi: 10.1289/EHP12207 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 123. Aguilera C, Wong YS, Gutierrez‐Reinoso MA, et al. Embryo‐maternal communication mediated by extracellular vesicles in the early stages of embryonic development is modified by in vitro conditions. Theriogenology. 2024;214:43‐56. doi: 10.1016/J.THERIOGENOLOGY.2023.10.005 [DOI] [PubMed] [Google Scholar]
- 124. Segura‐Benítez M, Carbajo‐García MC, Quiñonero A, et al. Endometrial extracellular vesicles regulate processes related to embryo development and implantation in human blastocysts. Hum Reprod. 2025;40:56‐68. doi: 10.1093/HUMREP/DEAE256 [DOI] [PubMed] [Google Scholar]
- 125. Fabbiano F, Corsi J, Gurrieri E, et al. RNA packaging into extracellular vesicles: an orchestra of RNA‐binding proteins? J Extracell Vesicles. 2020;10:e12043. doi: 10.1002/JEV2.12043 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 126. Zheng D, Jiang J, Shen A, Zhong Y, Zhang Y, Xiu J. Maternal hypertension aggravates vascular dysfunction after injury in male adult offspring through transgenerational transmission of N6‐Methyladenosine. Hypertension. 2024;82:255‐266. doi: 10.1161/HYPERTENSIONAHA.124.23373/ASSET/1980714D-B489-4EDF-8126-F8145C7C0DFD/ASSETS/GRAPHIC/HYPERTENSIONAHA.124.23373.FIG07.JPG [DOI] [PubMed] [Google Scholar]
- 127. Kontur C, Jeong M, Cifuentes D, Giraldez AJ. Ythdf m6A readers function redundantly during zebrafish development. Cell Rep. 2020;33:108598. doi: 10.1016/J.CELREP.2020.108598/ATTACHMENT/CBA6DA32-6591-4A58-AC92-701DD6A91611/MMC6.PDF [DOI] [PMC free article] [PubMed] [Google Scholar]
- 128. Basak S, Mallick R, Navya Sree B, Duttaroy AK. Placental epigenome impacts fetal development: effects of maternal nutrients and gut microbiota. Nutrients. 2024;16:1860. doi: 10.3390/NU16121860 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 129. Klibaner‐Schiff E, Simonin EM, Akdis CA, et al. Environmental exposures influence multigenerational epigenetic transmission. Clin Epigenetics. 2024;16(1):1‐13. doi: 10.1186/S13148-024-01762-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 130. Ma X, Chen X, Mu X, Cao M, Zhang Y. Epigenetics of maternal‐fetal interface immune microenvironment and placental related pregnancy complications. Front Immunol. 2025;16:1549839. doi: 10.3389/FIMMU.2025.1549839/XML/NLM [DOI] [PMC free article] [PubMed] [Google Scholar]
- 131. Sainty R, Silver MJ, Prentice AM, Monk D. The influence of early environment and micronutrient availability on developmental epigenetic programming: lessons from the placenta. Front Cell dev Biol. 2023;11:1212199. doi: 10.3389/FCELL.2023.1212199/XML [DOI] [PMC free article] [PubMed] [Google Scholar]
- 132. Ahi EP, Panda B, Primmer CR. The hippo pathway: a molecular bridge between environmental cues and pace of life. BMC Ecol Evol. 2025;25(1):35. doi: 10.1186/s12862-025-02378-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 133. Du ZY, Zhu HL, Chang W, et al. Maternal prednisone exposure during pregnancy elevates susceptibility to osteoporosis in female offspring: the role of mitophagy/FNDC5 alteration in skeletal muscle. J Hazard Mater. 2024;469:133997. doi: 10.1016/J.JHAZMAT.2024.133997 [DOI] [PubMed] [Google Scholar]
- 134. Dvoran M, Nemcova L, Kalous J. An interplay between epigenetics and translation in oocyte maturation and embryo development: assisted reproduction perspective. Biomedicine. 2022;10:1689. doi: 10.3390/BIOMEDICINES10071689 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 135. Kunovac A, Hathaway QA, Pinti MV, et al. Enhanced antioxidant capacity prevents epitranscriptomic and cardiac alterations in adult offspring gestationally‐exposed to ENM. Nanotoxicology. 2021;15:812‐831. doi: 10.1080/17435390.2021.1921299 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 136. Kunovac A, Hathaway QA, Thapa D, et al. N6‐methyladenosine (M6A) in fetal offspring modifies mitochondrial gene expression following gestational nano‐TiO2 inhalation exposure. Nanotoxicology. 2023;17:651‐668. doi: 10.1080/17435390.2023.2293144 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 137. Li J, Gao X, Wang S, et al. The role of m6A methylation in prenatal maternal psychological distress and birth outcome. J Affect Disord. 2023;338:52‐59. doi: 10.1016/J.JAD.2023.05.098 [DOI] [PubMed] [Google Scholar]
- 138. Li X, Zhao S, Zhai M, et al. Extractable organic matter from PM2.5 inhibits cardiomyocyte differentiation via AHR‐mediated m6A RNA methylation. J Hazard Mater. 2025;486:137110. doi: 10.1016/J.JHAZMAT.2025.137110 [DOI] [PubMed] [Google Scholar]
- 139. Xiong YW, Zhu HL, Zhang J, et al. Multigenerational paternal obesity enhances the susceptibility to male subfertility in offspring via Wt1 N6‐methyladenosine modification. Nat Commun. 2024;15:1353. doi: 10.1038/s41467-024-45675-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 140. Zhang S, Meng P, Cheng S, et al. Pregnancy exposure to carbon black nanoparticles induced neurobehavioral deficits that are associated with altered m6A modification in offspring. Neurotoxicology. 2020;81:40‐50. doi: 10.1016/J.NEURO.2020.07.004 [DOI] [PubMed] [Google Scholar]
- 141. Bai S, Fu K, Yin H, et al. The maternal‐to‐zygotic transition revisited. Development. 2019;146:dev161471. doi: 10.1242/DEV.161471 [DOI] [PubMed] [Google Scholar]
- 142. Jiang ZY, Fan HY. Five questions toward mRNA degradation in oocytes and preimplantation embryos: when, who, to whom, how, and why? Biol Reprod. 2022;107:62‐75. doi: 10.1093/BIOLRE/IOAC014 [DOI] [PubMed] [Google Scholar]
- 143. Winata CL, Łapinśki M, Pryszcz L, et al. Cytoplasmic polyadenylation‐mediated translational control of maternal mRNAs directs maternal‐to‐zygotic transition. Development. 2018;145:dev159566. doi: 10.1242/DEV.159566/264461/AM/CYTOPLASMIC-POLYADENYLATION-MEDIATED-TRANSLATIONAL [DOI] [PubMed] [Google Scholar]
- 144. Xiang Y, Chang H‐M, Leung PCK, Bai L, Zhu Y. RNA modifications in female reproductive physiology and disease: emerging roles and clinical implications. Hum Reprod Update. 2025;31:333‐360. doi: 10.1093/HUMUPD/DMAF005 [DOI] [PubMed] [Google Scholar]
- 145. Xiao Y, Chen J, Yang S, et al. Maternal mRNA deadenylation and allocation via Rbm14 condensates facilitate vertebrate blastula development. EMBO J. 2023;42:e111364. doi: 10.15252/EMBJ.2022111364 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 146. Yang Y, Wang L, Han X, et al. RNA 5‐methylcytosine facilitates the maternal‐to‐zygotic transition by preventing maternal mRNA decay. Mol Cell. 2019;75:1188‐1202.e11. doi: 10.1016/J.MOLCEL.2019.06.033/ATTACHMENT/D590E202-0CE2-45DA-8184-90B792FE9FBE/MMC6.PDF [DOI] [PubMed] [Google Scholar]
- 147. Frasch MG, Schulkin J, Metz GAS, Antonelli M. Animal models of fetal programming: focus on chronic maternal stress during pregnancy and neurodevelopment. Animal Models for the Study of Human Disease. 2nd ed. Elsevier; 2017:839‐849. doi: 10.1016/B978-0-12-809468-6.00032-2 [DOI] [Google Scholar]
- 148. Wang S, Chen S, Sun J, et al. m6A modification‐tuned sphingolipid metabolism regulates postnatal liver development in male mice. Nat Metab. 2023;5(5):842‐860. doi: 10.1038/s42255-023-00808-9 [DOI] [PubMed] [Google Scholar]
- 149. Wu S, Xie H, Su Y, et al. The landscape of implantation and placentation: deciphering the function of dynamic RNA methylation at the maternal‐fetal interface. Front Endocrinol. 2023;14:1205408. doi: 10.3389/FENDO.2023.1205408/XML/NLM [DOI] [PMC free article] [PubMed] [Google Scholar]
- 150. Xiao S, Cao S, Huang Q, et al. The RNA N6‐methyladenosine modification landscape of human fetal tissues. Nat Cell Biol. 2019;21:651‐661. doi: 10.1038/s41556-019-0315-4 [DOI] [PubMed] [Google Scholar]
- 151. O'Brien K, Wang Y. The placenta: a maternofetal Interface. Annu Rev Nutr. 2023;43:301‐325. doi: 10.1146/ANNUREV-NUTR-061121-085246/CITE/REFWORKS [DOI] [PubMed] [Google Scholar]
- 152. Kumar RP, Kumar R, Ganguly A, et al. METTL3 shapes m6A epitranscriptomic landscape for successful human placentation. bioRxiv 2024. doi: 10.1101/2024.07.12.603294 [DOI]
- 153. Qiu W, Zhou Y, Wu H, et al. RNA demethylase FTO mediated RNA m6A modification is involved in maintaining maternal‐fetal Interface in spontaneous abortion. Front Cell dev Biol. 2021;9:617172. doi: 10.3389/FCELL.2021.617172/BIBTEX [DOI] [PMC free article] [PubMed] [Google Scholar]
- 154. Lee MT, Bonneau AR, Giraldez AJ. Zygotic genome activation during the maternal‐to‐zygotic transition. Annu Rev Cell dev Biol. 2014;30:581‐613. doi: 10.1146/ANNUREV-CELLBIO-100913-013027 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 155. Kaspi A, Khurana I, Ziemann M, et al. Diet during pregnancy is implicated in the regulation of hypothalamic RNA methylation and risk of obesity in offspring. Mol Nutr Food Res. 2018;62:1800134. doi: 10.1002/MNFR.201800134 [DOI] [PubMed] [Google Scholar]
- 156. Yan C, He B, Wang C, et al. Methionine in embryonic development: metabolism, redox homeostasis, epigenetic modification and signaling pathway. Crit Rev Food Sci Nutr. 2025;65:8051‐8074. doi: 10.1080/10408398.2025.2491638 [DOI] [PubMed] [Google Scholar]
- 157. Izquierdo V, Palomera‐ávalos V, Pallàs M, Griñán‐Ferré C. Resveratrol supplementation attenuates cognitive and molecular alterations under maternal high‐fat diet intake: epigenetic inheritance over generations. Int J Mol Sci. 2021;22:1‐18. doi: 10.3390/IJMS22031453 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 158. Du R, Li L, Wang Y. N6‐Methyladenosine‐related gene signature associated with monocyte infiltration is clinically significant in gestational diabetes mellitus. Front Endocrinol. 2022;13:853857. doi: 10.3389/FENDO.2022.853857/BIBTEX [DOI] [PMC free article] [PubMed] [Google Scholar]
- 159. Yu X, Xu J, Song B, et al. The role of epigenetics in women's reproductive health: the impact of environmental factors. Front Endocrinol. 2024;15:1399757. doi: 10.3389/FENDO.2024.1399757/XML/NLM [DOI] [PMC free article] [PubMed] [Google Scholar]
- 160. Schroeder M, Fuenzalida B, Yi N, et al. LAT1‐dependent placental methionine uptake is a key player in fetal programming of metabolic disease. Metabolism. 2024;153:155793. doi: 10.1016/J.METABOL.2024.155793 [DOI] [PubMed] [Google Scholar]
- 161. Binan L, Jiang A, Danquah SA, et al. Simultaneous CRISPR screening and spatial transcriptomics reveal intracellular, intercellular, and functional transcriptional circuits. Cell. 2025;188:2141‐2158.e18. doi: 10.1016/J.CELL.2025.02.012/ASSET/E8611363-E988-486D-98DA-52A86346D8E0/MAIN.ASSETS/FX1.JPG [DOI] [PMC free article] [PubMed] [Google Scholar]
- 162. Ren J, Zhou H, Zeng H, et al. Spatiotemporally resolved transcriptomics reveals the subcellular RNA kinetic landscape. Nat Methods. 2023;20:695‐705. doi: 10.1038/S41592-023-01829-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 163. Li Y, Wang Y, Vera‐Rodriguez M, et al. Single‐cell m6A mapping in vivo using picoMeRIP‐seq. Nat Biotechnol. 2023;42(4):591‐596. doi: 10.1038/s41587-023-01831-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 164. Ren Z, He J, Huang X, et al. Isoform characterization of m6A in single cells identifies its role in RNA surveillance. Nat Commun. 2025;2025:1‐19. doi: 10.1038/s41467-025-60869-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 165. Park CW, Lee SM, Yoon KJ. Epitranscriptomic regulation of transcriptome plasticity in development and diseases of the brain. BMB Rep. 2020;53:551‐564. doi: 10.5483/BMBREP.2020.53.11.204 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 166. Wei S, Tao HY, Duan Z, Wang Y. Environmental exposure, Epitranscriptomic perturbations, and human diseases. Environ Sci Technol. 2025;59:6387‐6399. doi: 10.1021/ACS.EST.5C00907/SUPPL_FILE/ES5C00907_SI_001.PDF [DOI] [PMC free article] [PubMed] [Google Scholar]
- 167. Legoff L, D'Cruz SC, Tevosian S, Primig M, Smagulova F. Transgenerational inheritance of environmentally induced epigenetic alterations during mammalian development. Cells. 2019;8:1559. doi: 10.3390/CELLS8121559 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 168. Yoon KJ, Vissers C, Ming GL, Song H. Epigenetics and epitranscriptomics in temporal patterning of cortical neural progenitor competence. J Cell Biol. 2018;217:1901‐1914. doi: 10.1083/JCB.201802117 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 169. Kisliouk T, Rosenberg T, Ben‐Nun O, Ruzal M, Meiri N. Early‐life m6A RNA demethylation by fat Mass and obesity‐associated protein (FTO) influences resilience or vulnerability to heat stress later in life. eNeuro. 2020;7:1‐14. doi: 10.1523/ENEURO.0549-19.2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 170. Wagner A, Schosserer M. The epitranscriptome in ageing and stress resistance: a systematic review. Ageing Res Rev. 2022;81:101700. doi: 10.1016/J.ARR.2022.101700 [DOI] [PubMed] [Google Scholar]
- 171. Yang L, Ma M, Gao Y, Liu J. Decoding N6‐methyladenosine's dynamic role in stem cell fate and early embryo development: insights into RNA–chromatin interactions. Curr Opin Genet Dev. 2025;91:102311. doi: 10.1016/J.GDE.2025.102311 [DOI] [PubMed] [Google Scholar]
- 172. Ahi EP, Singh P, Lecaudey LA, Gessl W, Sturmbauer C. Maternal mRNA input of growth and stress‐response‐related genes in cichlids in relation to egg size and trophic specialization. Evodevo. 2018;9:23. doi: 10.1186/s13227-018-0112-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 173. Beck SV, Räsänen K, Ahi EP, et al. Gene expression in the phenotypically plastic Arctic charr (Salvelinus alpinus): a focus on growth and ossification at early stages of development. Evol dev. 2019;21:16‐30. doi: 10.1111/ede.12275 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 174. Segers FHID, Taborsky B. Juvenile exposure to predator cues induces a larger egg size in fish. Proc Biol Sci. 2012;279:1241‐1248. doi: 10.1098/rspb.2011.1290 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 175. Bresnahan ST, Lee E, Clark L, et al. Examining parent‐of‐origin effects on transcription and RNA methylation in mediating aggressive behavior in honey bees (Apis mellifera). BMC Genomics. 2023;24:1‐13. doi: 10.1186/S12864-023-09411-4/FIGURES/3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 176. Navarro‐Martín L, Martyniuk CJ, Mennigen JA. Comparative epigenetics in animal physiology: an emerging frontier. Comp Biochem Physiol Part D Genomics Proteomics. 2020;36:100745. doi: 10.1016/J.CBD.2020.100745 [DOI] [PubMed] [Google Scholar]
- 177. Crespo‐García E, Bueno‐Costa A, Esteller M. Single‐cell analysis of the epitranscriptome: RNA modifications under the microscope. RNA Biol. 2024;21(1):1‐8. doi: 10.1080/15476286.2024.2315385 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 178. Breunig CT, Köferle A, Neuner AM, Wiesbeck MF, Baumann V, Stricker SH. Crispr tools for physiology and cell state changes: potential of transcriptional engineering and epigenome editing. Physiol Rev. 2021;101:177‐211. doi: 10.1152/PHYSREV.00034.2019/ASSET/IMAGES/LARGE/Z9J0042029630011.JPEG [DOI] [PubMed] [Google Scholar]
- 179. Fang L, Wang W, Li G, et al. CIGAR‐seq, a CRISPR/Cas‐based method for unbiased screening of novel mRNA modification regulators. Mol Syst Biol. 2020;16:10025. doi: 10.15252/MSB.202010025/SUPPL_FILE/MSB202010025-SUP-0004-DATASETEV3.XLSX [DOI] [PMC free article] [PubMed] [Google Scholar]
- 180. Clift D, So C, McEwan WA, James LC, Schuh M. Acute and rapid degradation of endogenous proteins by Trim‐away. Nat Protoc. 2018;13(10):2149‐2175. doi: 10.1038/s41596-018-0028-3 [DOI] [PubMed] [Google Scholar]
- 181. Chen X, Liu M, Lou H, et al. Degradation of endogenous proteins and generation of a null‐like phenotype in zebrafish using Trim‐away technology. Genome Biol. 2019;20:1‐6. doi: 10.1186/S13059-019-1624-4/FIGURES/2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 182. Weir E, McLinden G, Alfandari D, Cousin H. Trim‐away mediated knock down uncovers a new function for Lbh during gastrulation of Xenopus laevis . Dev Biol. 2021;470:74‐83. doi: 10.1016/J.YDBIO.2020.10.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 183. Ahi EP. Fish Evo‐devo: moving toward species‐specific and knowledge‐based interactome. J Exp Zool B Mol Dev Evol. 2025;344;158‐168. doi: 10.1002/JEZ.B.23287 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
