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965 results for “placentation”
Data from: Novel and divergent genes in the evolution of placental mammals
Analysis of genome sequences within a phylogenetic context can give insight into the mode and tempo of gene and protein evolution, including inference of gene ages. This can reveal whether new genes arose on particular evolutionary lineages and were recruited for new functional roles. Here, we apply MCL clustering with all-vs-all reciprocal BLASTP to identify and phylogenetically date 'Homology Groups' amongst vertebrate proteins. Homology Groups include new genes and highly divergent duplicate genes. Focussing on the origin of the placental mammals within the Eutheria, we identify 357 novel Homology Groups that arose on the stem lineage of Placentalia, 87 of which are deduced to play core roles in mammalian biology as judged by extensive retention in evolution. We find the human homologues of novel eutherian genes are enriched for expression in preimplantation embryo, brain, and testes, and enriched for functions in keratinization, reproductive development, and the immune system.
Data from: Geomolecular dating and the origin of placental mammals
In modern evolutionary divergence analysis the role of geological information extends beyond providing a timescale, to informing molecular rate variation across the tree. Here I consider the implications of this development. I use fossil calibrations to test the accuracy of models of molecular rate evolution for placental mammals, and reveal substantial misspecification associated with life history rate correlates. Adding further calibrations to reduce dating errors at specific nodes unfortunately tends to transfer underlying rate errors to adjacent branches. Thus, tight calibration across the tree is vital to buffer against rate model errors. I argue that this must include allowing maximum bounds to be tight when good fossil records permit, otherwise divergences deep in the tree will tend to be inflated by the interaction of rate errors and asymmetric confidence in minimum and maximum bounds. In the case of placental mammals I sought to reduce the potential for transferring calibration and rate model errors across the tree by focusing on well-supported calibrations with appropriately conservative maximum bounds. The resulting divergence estimates are younger than others published recently, and provide the long-anticipated molecular signature for the placental mammal radiation observed in the fossil record near the 66 Ma Cretaceous-Paleogene extinction event.
Data from: Hyperandrogenism and insulin resistance-induced fetal loss: evidence for placental mitochondrial abnormalities and elevated ROS production in pregnant rats that mimic the clinical features of PCOS
Women with polycystic ovary syndrome (PCOS) commonly suffer from miscarriage, but the underlying mechanism of PCOS‐induced fetal loss during pregnancy remains obscure and specific therapies are lacking. We used pregnant rats treated with 5α‐dihydrotestosterone (DHT) and insulin to investigate the impact of hyperandrogenism and insulin resistance on fetal survival and to determine the molecular link between PCOS conditions and placental dysfunction during pregnancy. Our study shows that pregnant rats chronically treated with a combination of DHT and insulin exhibited endocrine aberrations such as hyperandrogenism and insulin resistance that are strikingly similar to those in pregnant PCOS patients. Of pathophysiological significance, DHT+insulin‐treated pregnant rats had greater fetal loss and subsequently decreased litter sizes compared to normal pregnant rats. This negative effect was accompanied by impaired trophoblast differentiation, increased glycogen accumulation, and decreased angiogenesis in the placenta. Mechanistically, we report that over‐production of reactive oxygen species (ROS) in the placenta, mitochondrial dysfunction, and disturbed SOD1 and Keap1/Nrf2 antioxidant responses constitute important contributors to fetal loss in DHT+insulin‐treated pregnant rats. Many of the molecular pathways leading to placental abnormalities and fetal loss in DHT+insulin treatment were also seen in pregnant rats treated with DHT alone, whereas pregnant rats treated with insulin alone often exerted distinct effects on placental gene expression compared to insulin treatment in combination with DHT. We also found that treatment with the antioxidant N‐acetylcysteine (NAC) improved fetal survival in DHT+insulin‐treated pregnant rats, an effect related to changes in Keap1/Nrf2 and NFκB signaling. However, NAC administration resulted in fetal loss in normal pregnant rats, most likely due to PCOS‐like endocrine abnormality induced by the treatment. Our results suggest that the deleterious effects of hyperandrogenism and insulin resistance on fetal survival are related to a constellation of mitochondrial‐ROS‐SOD1/Nrf2 changes in the placenta. Our findings also suggest that physiological levels of ROS are required for normal placental formation and fetal survival during pregnancy.
Data from: Costs and benefits of polyandry in a placental poeciliid fish Heterandria formosa are in accordance with the parent-offspring conflict theory of placentation
In viviparous species, a conflict over maternal resource allocation may arise between mothers and embryos, between siblings, and between maternal and paternal genes within an embryo due to relatedness asymmetries. We performed two experiments to study the effects of polyandry and brood relatedness on offspring growth in a placental fish (Heterandria formosa). Polyandry was beneficial as it increased the probability of pregnancy, possibly to avoid genetic incompatibility. However, females mated to four males produced offspring that had a longer maturation time than those of monandrous females. When within-brood relatedness was manipulated, the size of the newborn offspring decreased with time in low relatedness treatment, while in highly related broods offspring size was constant. Low within-brood relatedness may lead to less cooperative offspring in terms of resource extraction from the mother, which may lead to impaired development during gestation. Offspring conflict may thus reduce the benefits of polyandry in viviparous species.
Data from: Heterogeneous models place the root of the placental mammal phylogeny
Heterogeneity among life traits in mammals has resulted in considerable phylogenetic conflict, particularly concerning the position of the placental root. Layered upon this are gene- and lineage-specific variation in amino acid substitution rates and compositional biases. Life trait variations that may impact upon mutational rates are longevity, metabolic rate, body size and germ line generation time. Over the past 12 years, three main conflicting hypotheses have emerged for the placement of the placental root. These hypotheses place: the Atlantogenata (common ancestor of Xenarthra plus Afrotheria), the Afrotheria, or the Xenarthra as the sister group to all other placental mammals. Model adequacy is critical for accurate tree reconstruction and by failing to account for these compositional and character exchange heterogeneities across the tree and dataset, previous studies have not provided a strongly supported hypothesis for the placental root. For the first time, models that accommodate both tree and dataset heterogeneity have been applied to mammal data. Here we show the impact of accurate model assignment and the importance of datasets in accommodating model parameters while maintaining the power to reject competing hypotheses. Through these sophisticated methods, we demonstrate the importance of model adequacy, dataset power and provide strong support for the Atlantogenata over other competing hypotheses for the position of the placental root.
Data from: Maternal-fetal genomic conflict and speciation: no evidence for hybrid placental dysplasia in crosses between two house mouse subspecies
Interspecific hybridization between closely related mammalian species, including various species of the genus Mus, is commonly associated with abnormal growth of the placenta and hybrid fetuses, a phenomenon known as hybrid placental dysplasia (HPD). The role of HPD in speciation is anticipated but still poorly understood. Here we studied placental and fetal growth in F1 crosses between four inbred mouse strains derived from two house mouse subspecies, Mus musculus musculus and M. m. domesticus. These subspecies are in the early stage of speciation and still hybridize in nature. In accordance with the maternal-fetal genomic conflict hypothesis we found different parental influences on placental and fetal development, with placental weight most affected by the father's body weight, and fetal weight by the mother's body weight. After removing the effects of parents' body weight, we did not find any significant differences in fetal or placental weights between intra-subspecific and inter-subspecific F1 crosses. Nevertheless, we found that the variability in placental weight in inter-subspecific crosses is linked to the X chromosome, similarly as for HPD in interspecific mouse crosses. Our results suggest that maternal-fetal genomic conflict occurs in the house mouse system, but has not yet diverged sufficiently to cause abnormalities in placental and fetal growth in inter-subspecific crosses. HPD is thus unlikely to contribute to speciation in the house mouse system. However, we cannot rule out that it might have contributed to other speciation events in the genus Mus, where differences in the levels of polyandry exist between the species.
High prevalence of Prdm9-independent recombination hotspots in placental mammals
Open the record for dataset details and reuse information.
Human placental MeRIP-seq data-IP
Open the record for dataset details and reuse information.
ELABELA, as a potential diagnostic biomarker ofpre-eclampsia, regulates abnormally shallow placentation via APJ
<p>Supplememtary tables and figures</p>
Exploring the mechanisms of cow placental peptides in delaying liver aging based on mitochondrial energy metabolism
<p>By analyzing and integrating changes in liver transcriptomics and targeted mitochondrial energy metabolomics, the mechanisms by which CPP delays liver aging are revealed.</p>
Data from: Mass-independent maximal metabolic rate predicts geographic range size of placental mammals
1.Understanding the mechanisms driving geographic range sizes of species is a central issue in ecology, but remarkably few rules link physiology with the distributions of species. Maximal metabolic rate (MMR) during exercise is an important measure of physiological performance. It sets an upper limit to sustained activity and locomotor capacity, so MMR may influence ability to migrate, disperse, and maintain population connectivity. Using both conventional ordinary least squares (OLS) analyses and phylogenetically generalized least squares (PGLS), we tested whether MMR helps explain geographic range size in 51 species of placental mammals. 2.Log body mass alone (OLS r2 = 0.074, p = 0.053; PGLS r2 = 0.016, p = 0.373) and log MMR alone (OLS r2 = 0.140, p = 0.007; PGLS r2 = 0.061, p = 0.081) were weak predictors of log range size. 3.However, multiple regression of log body mass and log MMR accounted for over half of the variation in log range size (OLS R2 = 0.527, p < 0.001). The relationship was also strong after correcting for the phylogenetic non-independence (PGLS R2 = 0.417, p < 0.001). 4.In analyses restricted to rodents (34 species), neither log body mass alone (OLS r2 = 0.004, p = 0.720; PGLS r2 = 0.003, p = 0.77) nor log MMR alone was useful in predicting log geographic range size (OLS r2 = 0.008, p = 0.626; PGLS r2 = 0.046, p = 0.225), but multiple regressions of log body mass and log MMR accounted for roughly a third to a half of the variation in log range size (OLS R2= 0.443, p < 0.001, PGLS r2 = 0.381, p < 0.001). 5.Mass-independent MMR is a strong predictor of mass-independent geographic range size in placental mammals. The ability of body mass and MMR to explain nearly 50% of the variation in the geographic ranges of mammals is surprising and powerful, particularly when neither variable alone is strongly predictive. 6.A better understanding of MMR during exercise may be important to understanding the limits of geographic ranges of mammals, and perhaps other animal groups.
Fig. 1 in Morphology And Relationships Of Apternodus And Other Extinct, Zalambdodont, Placental Mammals
Fig. 1. Geographical distribution of ''apternodontids'' (sensu lato) in North America. Acronyms are given in parentheses for institutions that have made significant collections from each locality. Each number represents a locality, listed in alphabetical order, known to have produced ''apternodontid'' fossils, as follows: 1: Badwater (CM), 2: Banjo Quarry (YPMPU), 3: Bates's Hole (AMNH, UW), 4: Big Badlands (USNM, YPM), 5: Cameron Spring, Beaver Divide (USNM), 6: Canyon Ferry (CM, USNM), 7: Cook Ranch (MPUM, CM), 8: Cypress Hills, Lac Pelletier (RSM), 9: Diamond O Ranch (MPUM, CM), 10: Dilts Ranch (UW), 11: Douglass Creek Basin (FMNH), 12: East Fork Basin (AMNH), 13: Easter Lily (MPUM, CM), 14: Elderberry Canyon (USNM), 15: Emerald Lake (AMNH), 16: Eureka Valley Road (MPUM, CM), 17: Fitterer Ranch (USNM), 18: Flagstaff Rim (USNM, AMNH), 19: Fort Union Fm., Clark's Fork Basin (UMMP), 20: Fremont Butte (DMNH), 21: Harshman Quarry (UW), 22: Highway 10N (MPUM, CM), 23: Horsetail Creek (DMNH), 24: Iliff (FMNH, KU), 25: Little Pipestone Creek (MPUM, CM, AMNH), 26: Lonetree, Wyoming (UCM), 27: McCarty's Mountain (FMNH, MPUM, CM), 28: Mellinger (UCM), 29: Pipestone Springs (MPUM, CM, AMNH), 30: Powder River Basin (UCM), 31: Powder Wash (CM), 32: Red Mound (TMM), 33: Raben Ranch (SDSM), 34: San Diego (UCMP), 35: Sand Wash Basin (DMNH), 36: Seamen Hills (AMNH), 37: Tabernacle Butte (CM, UMMP), 38: Torrington (MCZ).
Figure 8 in Mandible shape in marsupial and placental carnivorous mammals: a morphological comparative study using geometric morphometrics
Figure 8. Simplified phylogeny showing the optimization of mandible shape on the main clades.
FIG. 31. —A in Dental ontogeny in the early Paleocene placental mammal Alcidedorbignya inopinata (Pantodonta) from Tiupampa (Bolivia)
FIG. 31. —A, transparent lateral view of the left mandible MHNC 8286 of juvenile Alcidedorbignya inopinata (stage 4) showing the trigonid of p4 and protoconid and probable metaconid of m3 in process of mineralisation in their respective crypts; B, enlarged view of the trigonid of p4 in the same position as in its crypt; C, enlarged view of the protoconid and metaconid of m3 in the same position as in its crypt (the cusps of the trigonid of m3 are not in their natural position since they have been displaced and rotated before filling of the crypt with sediment); D, occlusal view of the trigonid of p4; E, occlusal view of the protoconid and metaconid of m3, which have been restored in their original positions. Scale bars: A, 5 mm; B-E, 1 mm.
FIG. 48 in Dental ontogeny in the early Paleocene placental mammal Alcidedorbignya inopinata (Pantodonta) from Tiupampa (Bolivia)
FIG. 48. — Histograms showing the relative proportions of adult and juvenile specimens of Alcidedorbignya inopinata and in the eight stages defined here: A, relative number of minimum number of individuals of adults and juveniles; B, relative number of adult and juvenile jaws; C, distribution of the number of jaw specimens within the juvenile stages; D, distribution of the number of jaw specimens within the adults and juveniles stages defined in text; E, distribution of the minimum number of individuals within the juvenile stages; F, distribution of minimum number of individuals within the adults and juveniles stages defined in text; G, distribution of jaw specimens of the adults and juveniles stages defined in text (stages 1-8) according to their inclusion in IDAS 0-5; H, distribution minimum number of individuals of the adults and juveniles stages defined in text (stages 1-8) according to their inclusion in IDAS 0-5.
FIG. 14 in Dental ontogeny in the early Paleocene placental mammal Alcidedorbignya inopinata (Pantodonta) from Tiupampa (Bolivia)
FIG. 14. — Digital rendering of the skull and mandibles (MHNC 8416) of juvenile Alcidedorbignya inopinata (stage 3): A, ventral view of the skull; B, enlargement of part of the left palate; C, dorsal view of the mandible; D, enlargement of the posterior region of the mandible, showing the opening in the roof of crypts of M2. Scale bars: A, C, 5 mm; B, D, 2 mm.
FIG. 30E-G in Dental ontogeny in the early Paleocene placental mammal Alcidedorbignya inopinata (Pantodonta) from Tiupampa (Bolivia)
FIG. 30E-G. — Slices of lateral and coronal CT-scans of the mandible (MHNC 8286) of juvenile Alcidedorbignya inopinata (stage 4): E, slice 133 of the lateral CTscan; F, slice 154 of the lateral CT-scan; G, slice 553 of the coronal CT scan (slice 553 is dorsal to slice 644). The number for each illustrated slice refers to the position within the sequence of 223 images for A, B and D and 823 images for C and E (resolution binned images voxel size = 0.02781842 mm). Scale bar: 5 mm.
FIG. 34 in Dental ontogeny in the early Paleocene placental mammal Alcidedorbignya inopinata (Pantodonta) from Tiupampa (Bolivia)
FIG. 34. — Wear facets on the first molars of Alcidedorbignya inopinata: A, partial left maxillary (MHNC 13960) of juvenile (stage 4) with M1 featuring a small wear facet on the on the mesial edge of the paraconule and on the preparaconular crista; B, the same with wear facet outlined with a red line; C, partial left mandible (MHNC 13964) of juvenile (stage 4) with m1 showing wear facet on the posterior edge of the protocristid; D, the same with wear facet outlined with a red line. The photographs of this figure have been obtained using an RTI (Reflectance Transforming Imaging) setting as indicated by Decombeix et al. (2021) with some specifications, as follows: we used a Canon EOS 5DS digital camera equipped with a Canon MP-E 65 mm macro lens (both Tokyo, Japan); and LEDs of the two lower rings of the light dome were used (i.e., 42 LEDs). Snapshots were extracted using the default' mode (for A and B, light source coordinates X = –0.34, Y = –0.34); for C and D, light source coordinates X = –0.31, Y = 0.44). Scale bar: 2 mm.
Gestational and Peri-conceptional Exposure to Intra-nasal Instilled Air Pollutants Epigenetically Perturb Metabolic, Placental and Embryonic Phenotypes
<p><strong>Supplementary Figure legends</strong></p> <p> </p> <p><strong>Figure 1: </strong>Gestational study: Bar plots of plasma metabolites</p> <p> </p> <p><strong>Figure 2:</strong> Gestational study: Bar graph depicting gestational day 19 (GD19) maternal (left) and fetal (right) blood glucose concentrations presented as mean ± SEM. Air pollutant exposed group (AP) versus controls (CON), *p < 0.05 AP versus CON.</p> <p> </p> <p><strong>Figure 3: </strong>Gestational study: <strong>(A)</strong> GO term enrichment analysis of expressed genes between the AP group versus the CON group (n=6 each). Significant enrichment of pathways represented as q-values have been presented in a color-coded key. NES = normalized enrichment score. <strong>(B)</strong> Category cnet plot depicting the linkage of genes and biological concepts (hallmark pathways) as a network illustrating which genes are involved in enriched pathways, and genes that may belong to multiple annotation categories.</p> <p><strong>Figure 4: </strong>Gestational study:<strong> (A) </strong>Representative Western blots of various glucose and lipid transporter proteins and TNFα protein, with vinculin serving as an internal loading control, obtained from CON and AP GD19 placentas<strong>. (B) </strong>Bar plot showing densitometric analysis of Western blots of the various glucose and lipid transporters and TNFα (n=8 for each protein in each group). Data are depicted as Mean ± SEM. While trends are seen, statistical significance was not achieved.</p> <p><strong>Figure 5: </strong>Periconceptional study: <strong>(A)</strong> Bar plots demonstrating fasting blood glucose concentrations (left panel), Glucose tolerance tests (GTTs) (middle panel) and the area under the curves (AUCs) for GTTs (right panel) in non-pregnant (NP), pregnant (P), omega-3 diet exposed (P<em>n-3</em>) pregnant C57/BL6 (BL6) and CD1 pregnant mice are shown. <strong>(B)</strong> Bar plots demonstrating basal fed-state blood glucose concentrations (left panel), Insulin tolerance tests (ITTs) (middle panel) and AUCs for ITTs (right panel) in non-pregnant (NP), pregnant (P), omega-3 diet exposed (P<em>n-3</em>) pregnant C57/BL6 (BL6) and CD1 pregnant mice are shown (n=4-6 each). Data are presented as Mean ± SEM. Significance is shown as <sup>#</sup>compared to BL6-NP, *compared to BL6-P, and <sup>!</sup>compared to BL6-Pn-3 at a p< 0.05.</p> <p><strong>Figure 6: </strong>Periconceptional study:<strong> (A) </strong>Representative Western blots demonstrate various GD19 placental glucose and lipid transporter proteins, with vinculin serving as the internal loading control. <strong>(B) </strong>Bar plots show densitometric analysis of the Western blots of the various glucose and lipid transporters (n=8 for each protein in each group). Data are presented as Mean ± SEM.</p> <p><strong>Figure 7</strong>: Periconceptional study: Category cnet plot depicting the linkage of genes and biological concepts (hallmark pathways) as a network illustrating which genes are involved in enriched pathways, and the genes that may belong to multiple annotation categories between <strong>(A)</strong> AP and CON,<strong> (B)</strong> AP-<em>n-3</em> and AP, <strong>(C) </strong>AP-<em>n-3</em> and CON.</p> <p><strong>Figure 8: </strong>Periconceptional study:<strong> (A)</strong> Bar plots showing coverage of the 5’-hydroxymethylation DNA marks and genomic annotations in GD19 placentas from CON, AP, <em>n-3</em> and AP<em>-n-3</em> experimental groups (n=4 each). <strong>(B)</strong> Pie charts showing the distribution and genomic annotation of differentially methylated regions (DMRs) between the AP and CON groups. Upper panel depicts the distribution of DMRs across CpG-islands and associated regions, while the lower panel depicts the distribution of DMRs around different genomic regions. <strong>(C)</strong> Pie charts showing the distribution and genomic annotation of differentially methylated regions (DMRs) between AP<em>-n-3</em> and CON (left panel), <em>n-3</em> versus CON (middle panel) and AP<em>-n-3</em> versus AP (right panel).</p> <p><strong>Figure 9:</strong> Periconceptional study: <strong>(A-D) </strong>Volcano plots demonstrating the DNA methylation profiles of GD19 placentas from <strong>(A)</strong> AP versus CON, <strong>(B)</strong> AP<em>n-3</em> vs CON, <strong>(C)</strong> <em>n-3</em> vs CON, and <strong>(D)</strong> AP-<em>n-3</em> vs AP groups. Red and blue dots represent hypomethylated and hypermethylated loci respectively (n=4 each group). </p> <p> </p> <p> </p> <p> </p> <p> </p>
Antibiotic Prophylaxis in Ragged Placental Membranes
ClinicalTrials.gov study NCT03459599. IPD Sharing: NO. Countries: 0. Publications: 7.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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