To address this gap, we simultaneously monitored three reefs along a cross-shelf gradient for an entire year over four seasons, collecting data on currents, temperature, salinity, dissolved oxygen (DO), chlorophyll-a, turbidity, inorganic nutrients, sedimentation, bacterial communities of reef water, and bacterial and algal composition of epilithic biofilms. Summer temperature (29–33°C) and salinity (39 PSU) exceeded average global maxima for coral reefs, whereas DO concentration was low (2–4 mg L-1). While temperature and salinity differences were most pronounced between seasons, DO, chlorophyll-a, turbidity, and sedimentation varied most between reefs. Similarly, biotic communities were highly dynamic between reefs and seasons. Differences in bacterial biofilms were driven by four abundant families: Rhodobacteraceae, Flavobacteriaceae, Flammeovirgaceae, and Pseudanabaenaceae. In algal biofilms, green crusts, brown crusts, and crustose coralline algae were most abundant and accounted for most of the variability of the communities. Higher bacterial diversity of biofilms coincided with increased algal cover during spring and summer. By employing multivariate matching, we identified temperature, salinity, DO, and chlorophyll-a as the main contributing physico-chemical drivers of biotic community structures. These parameters are forecast to change most with the progression of ocean warming and increased nutrient input, which suggests an effect on the recruitment of Red Sea benthic communities as a result of climate change and anthropogenic influence. In conclusion, our study provides insight into coral reef functioning in the Red Sea and a comparative baseline to support coral reef studies in the region.Coral reefs in the central Red Sea are sparsely studied and  Shallow-water coral reefs are marine ecosystems of high biodiversity and high economic value . They deCoral reefs are considered to be among the most sensitive ecosystems in regard to changing environmental conditions . Many stThe algal component of biofilms  is another crucial part of the coral reef benthos. Epilithic algal turfs and crusts comprise a great part of reef primary production and constitute an essential food source for grazing reef fish ,37. EpilDue to the geographic location of Red Sea, locked in between two arid landmasses, precipitation and riverine input are rare and temperature and salinity are high ,50. Thisin situ measurements. With increasing local and global anthropogenic stressors, comprehensive studies are needed that simultaneously record multiple physical, chemical, and biotic variables in situ to disentangle spatio-temporal dynamics and to provide a baseline against which impacts can be measured [In recent years, consequences of global climate change have been reported to affect coral reefs in the Red Sea. For instance, the Red Sea is already experiencing measurable ocean warming , is suscmeasured –71.in situ baseline data was an important motivation for monitoring and collecting continuous physico-chemical and biotic data in this study. We use these data to characterize the natural baselines of central Red Sea reef environments. We then link physico-chemical and biotic parameters to extract putative physico-chemical drivers that contribute insights into coral reef functioning. As such we address the natural environmental variability of coral reefs in the central Red Sea to provide a foundation for coral reef studies, which will aim at better understanding coral reef functioning in unique environments and estimating the impact of global and local environmental pressures in this region.The lack of et al. [This study was conducted in the Saudi Arabian central Red Sea encompassing three reefs along a cross-shelf gradient using a balanced two-factor design (3 reefs and 4 seasons). Monitoring stations were set up at 7.5–9 m depth on the forereef slope of three geographically and visually distinct reef sites facing the open sea at 3 km (nearshore), 10 km (midshore), and 25 km (offshore) from the coast . The neaet al. .Each reef monitoring setup comprised one aluminum tripod for mooring of oceanographic instrumentation and one aluminum frame for deployment of sediment traps and terracotta tiles . Four se-1) and direction were measured continuously using Nortek AS Aquadopp Doppler current meters . Instruments were moored vertically to tripod frames (®). Current profiles were recorded over a 0.5 m vertical profile (“bin”) at about 1.5 m above the substrate. Current speeds and directions were measured every 10 minutes. For each data point 20 measurements were averaged within 60 seconds, except in the midshore reef during spring measurements were taken every 5 minutes with 20 measurements averaged within 10 seconds. Rose plots were generated using the MATLAB  function wind_rose [-1) for each reef and season, and for the full year. Data are available from the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.9mj14.Current speed  were logged continuously over three-month intervals  [Physico-chemical variables  .To report on phosphate, silicate, nitrate & nitrite, and ammonia we used samples from Ziegler et al. . More sp-2 d-1. To assess the organic content (OC), sediments were ground using mortar and pestle. From each sediment trap a subsample was muffled at 550°C for 3 h, and the remaining ash-free dry weight was determined. Additional subsamples were used to measure organic carbon (C) and nitrogen (N) concentrations and isotopic signatures. Subsamples were acidified with 0.1 N HCl to remove inorganic C and CN content. Isotopic ratios (δ13C and δ15N) were analyzed relative to Pee Dee Belemnite standard and atmospheric nitrogen using an isotope ratio mass spectrometer .Three replicate sediment traps  were placed 1 m above the substrate to measure sedimentation rates . A funneUnivariate 2-factorial permutational MANOVAs  were usInorganic nutrient species  were analyzed in separate univariate 2-factorial ANOVAs testing the factors “reef”  and “season” (2 levels: summer and winter), followed by Tukey’s HSD post-hoc tests where applicable .To assess biofilms, terracotta tiles were first sanded on their non-glazed surface, autoclaved, and then deployed at the monitoring sites  in direct proximity of each monitoring setup at the end of each season on the day of the tile recovery. Water samples were transported on ice in the dark to the lab. From each sample, 1 L was filtered over a 0.22 μm Durapore PVDF filter  and filters were frozen at -80°C until DNA extraction. Half of each water filter was cut into small stripes with sterile razorblades and transferred into a 2 ml vial. After adding 400 μl AP1 buffer of DNeasy plant kit , the samples were incubated on a rotating wheel for 20 min and subsequently extracted following the manufacturer’s protocol.TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-35'-') and 805R (GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC-3’5'-) that target the 16S V3 and V4 regions [To assess bacterial biofilms, samples were retrieved from terracotta tiles. Frozen tiles were placed on ice, unwrapped, and half of each tile was scratched off with a sterile razorblade . Each bi regions . The prihttp://www.ncbi.nlm.nih.gov/bioproject/PRJNA306204).The software mothur  was useA 97% similarity cutoff was chosen to obtain Operational Taxonomic Units (OTUs) using the average neighbor algorithm in mothur. OTUs were classified based on their most abundant sequence. Stacked column plots were created based on the relative abundances of OTUs in the taxonomic families for each reef and season. To characterize and compare bacterial community composition in reef water and biofilms, mothur was used to derive the numbers of shared OTUs between biofilm and water samples via Venn diagrams. Mothur was further used to calculate Chao1 richness estimator  and the Due to different replication numbers for biofilm (n = 1 to 4) and water samples (n = 1), bacterial communities were evaluated using different statistical approaches. Alpha diversity indices of reef water communities were compared by two 1-way Kruskal-Wallis ANOVAs  followed by 2-tailed multiple comparisons tests where indicated. Two-factorial ANOVAs (for the factors “reef” and “season”) were performed for biofilms comparing alpha diversity indices. Where applicable, Tukey’s HSD post-hoc tests were conducted.p-value cutoff of 0.01  transformed and tested using two 1-factorial PERMANOVAs (one each for the factors “reef” and “season”). Test designs were based on Bray-Curtis similarities, partial sum of squares type III, 9,999 permutations of residuals under a reduced model using Monte-Carlo simulations, and followed by pair-wise tests where applicable. OTU based biofilm data were ln(x + 1) transformed and tested with a 2-factorial PERMANOVA for differences within each of the factors “reef” and “season”. Both data sets, bacterial communities of reef water and biofilms, were visualized in a non-Metric Multidimensional Scaling (nMDS) plot based on Bray-Curtis similarities. To test for differential abundance between “reefs” and “seasons”, the OTU data set was filtered to retain all OTUs present in > 50% of samples. This resulted in 72 reef water OTUs and 163 biofilm OTUs which were subjected to non-parametric Mack-Skillings analyses at a eV V4.9, ).After each three-month deployment period, algal biofilms on recovered terracotta tiles were photographed with a stereomicroscope . To quantify the cover of functional categories overgrowing each tile, four to five randomly photographed subsections (1.4 x 1 cm) were examined using image-based analysis (CPCe software 4.1 ). In eacp-value cutoff of 0.05.Algae community data were statistically analyzed using the same test design as for bacterial biofilms. Additionally, a SIMilarity PERcentage (SIMPER) analysis  was conAnalyses to characterize the overall physico-chemical conditions at the reef sites were based on 10 physico-chemical variables . First, significant correlations between physico-chemical variables were determined using Spearman's rank correlation analysis . Second, environmental data were tested for differences between “reefs” and “seasons” with a 2-factorial PERMANOVA  and visualized using an nMDS plot.To link multivariate physico-chemical to biotic data , biological-environmental (BIOENV) matching was performed in Primer-E V6 , based oWe monitored three reefs along a cross-shelf gradient in the central Red Sea over an entire year and provide a detailed description of the seasonal dynamics of physico-chemical and biotic properties in the three reef habitats . We orga-1 at the offshore reef, which also experienced higher frequencies of strong currents compared to the other reef sites  to the reef. Across all reefs, the main axis of current direction was parallel to the shore (NW to SE). Over the year, the offshore reef was dominated by currents from NW to SE , whereasef sites . Currentef sites . Over al in fall .Physico-chemical variables were continuously logged in the three reefs along the cross-shelf gradient over the full year using CTDs. Data are displayed in time series and density plots . All seaHighest temperatures in summer reached 33°C and the lowest in winter reached 24°C . In spriSalinity was lowest in spring (38.4 PSU) and increased over the summer reaching the highest values in fall  and highest in summer (0.63 NTU) at the offshore site. Chlorophyll-a values ranged between 0.16 μg Lectively . Only siectively , charactectively .p < 0.001, ANOVA). Additionally, nearshore silicate was significantly higher compared to offshore .Bi-annual measurements of phosphate, silicate, nitrate & nitrite, and ammonia revealed overall low inorganic nutrients . Nitrate-2 day-1), and the lowest at the midshore reef during summer , and C:N ratios of the sediments . Rates d-2 day-1 to 28.51 mg m-2 day-1  at 97% . Good’s p > 0.05, Kruskal-Wallis ANOVAs), but comparisons of reef water bacterial communities based on OTU abundance showed significant differences between seasons . Together with Flavobacteriaceae (5–21%), Pelagibacteraceae (4–10%), OCS15 (3–9%), Halomonadaceae (1–10%), Rhodospirillaceae (1–6%), Rhodobacteraceae (1–7%), and unclassified Proteobacteria (4–9%), these bacterial families comprised up to 85% of the entire community . Alpha d seasons . We wereDominant bacterial families were Rhodobacteraceae (11–31%), Flavobacteriaceae (7–17%), unclassified Proteobacteria (5–12%), and Pseudanabaenaceae (3–12%), which together comprised about 50% of the biofilm communities . Furtherp < 0.05, ANOVA; OTU-based alpha diversity of bacterial biofilm communities differed between seasons, with significantly lower ISI values in fall and winter and higher values in spring and summer , Cystobacterineae (unclassified OTU00030), and Gloeobacteraceae (OTU00010: Gloeobacter sp.). The overall most abundant OTU that significantly varyied between reefs was classified as Halomicronema sp. (OTU00021) in the family Pseudanabaenaceae. Muricauda sp. (OTU00015), a Flavobacteriaceae, varied between reefs and seasons. Bacterial taxa that significantly changed in abundance between the warmer and colder seasons were Rhodovulum sp. (OTU 00122), Rhodobaca sp. (OTU 00135), Gloeobacter sp. (OTU 00010), one unclassified bacterium of Flammeovirgaceae (OTU 00161), a bacterium of the order of Myxococcales (OTU 00232), and one from the family A4b (OTU 00419). All differentially abundant OTUs in reef biofilms were highly similar (94–99% identity) to sequences that had previously been encountered in marine and hypersaline environments  occurred nearshore and midshore during fall and winter, whereas the highest algal cover (79%) occurred in the midshore reef during spring. Dominant algal categories were green crusts (10–30%), brown crusts (5–40%), and CCA (5–30%). Filamentous algae were present at low proportions (1–9%). Other rare categories, such as cyanobacteria (< 2%) and sessile invertebrates (~ 1%) were only found on tiles in nearshore and midshore reefs. We did not encounter red macro algae. Red crusts were absent on most tiles, except for the midshore reef during winter where the cover was < 1% .p < 0.05), except summer and winter in the nearshore reef, and spring and summer in the offshore reef (p > 0.05)  . Algal cp < 0.001; Physico-chemical conditions structured reefs and seasons and were most different between summer and winter and the geographically most distant reefs, nearshore and offshore, as visualized in the nMDS plot  and temporal  variability. We uncovered connections between physico-chemical conditions and community structure of bacterial and algal biofilms, contributing valuable information on the potential major drivers of biotic coral reef processes in this naturally variable environment.In this study we present a first account of physical, chemical, and biotic in situ physico-chemical data show that coral reefs in the central Red Sea are subjected to summer temperature and salinity that exceed coral reef global average maxima [Our e maxima  and to re maxima ,90. Turbe maxima ,91. FurtDerived from ocean model simulations, currents on the eastern coast of the central Red Sea are influenced by strong seasonal or permanent gyres and by the eastern boundary current that carries water masses from the south . HoweverDuring summer we measured a highest seasonal mean temperature of 31.9°C and maxima of up to 33°C. The highest seasonal mean temperature exceeds the typical average maximum for coral reefs (29.5°C)  by 2.4°CAmong all measured physico-chemical variables, temperature and salinity fluctuate most between seasons. For instance, the annual temperature range (9°C) is 2- to 4-fold higher than in most equatorial reefs , and in a range with temperatures from more extreme regions that support coral habitats, such as the Sea of Oman (7°C) and the Persian/Arabian Gulf (12–20°C) . Althoug-1 which is derived from continuous data, including diurnal (elevated DO due to photosynthesis) and nocturnal values (lowered DO due to respiration). This is large in relation to the ranges from a majority of studies that only report on daytime measurements . This reduction in DO is likely driven by higher temperatures in the central Red Sea that decrease oxygen solubility.DO concentrations in coral reefs are primarily driven by biological processes such as respiration and photosynthesis . Lower D-1, e.g. ,100), bue.g. [-1 . Within w waters ) to the -1 DO and below have been characterized as hypoxic in the majority of studies, mostly for temperate regions [Globally, DO concentrations are predicted to decrease and hypoxic environments to spread as a consequence of climate change . Values  regions . As DO i-3) in the northern and northern-central Red Sea to chlorophyll-a concentrations exceeding typical coral reef conditions by an order of magnitude in the southern Red Sea (0.5–5.0 mg m-3) [in situ chlorophyll-a and dissolved inorganic nutrients to be mostly in the range of values from other oligotrophic coral reef regions. Conditions at the nearshore and midshore reefs in our study area were similar to inshore reefs of the GBR  and in a range with more oligotrophic reef sites such as reef systems in Hawaii (up to 0.31 μg L-1) [Chlorophyll-a concentration is frequently used as a proxy for primary production and nutrient availability in the water column . Chlorop mg m-3) . Accordill year; ), while  μg L-1) .Low chlorophyll-a concentrations in our study area also reflect the limited availability of inorganic nutrients. Nitrogen species concentrations  were comparably low . Phosph-2 day-1 [-2 day-1 [-2 day-1, which is only ~ 2% of the lowest natural sedimentation rate recorded elsewhere [Sedimentation rates and turbidity were very low in the study area and decreased from nearshore to offshore following a common pattern of land-based sedimentation ,107,108.-2 day-1 , while s-2 day-1 . Sedimenlsewhere . AccordiSimilar to chlorophyll-a, OC of sediments and turbidity showed no significant seasonal pattern that would indicate a period of higher productivity in the water column. However, the typical decrease of sedimentation rates from nearshore to offshore was reversed in spring. This may be related to the Indian Ocean monsoon, which causes dust storms and/or increases mixing in the water column during spring and fall . FurtherAll C:N ratios of sediments were above the Redfield ratio (6.6) , which cWe present a first account of basic biotic variables of coral reefs in the central Red Sea, including reef water bacteria, bacterial biofilms, and algal biofilms. The catalogue of bacterial taxa  and algaReef water bacterial communities at our study sites were similar to those reported from other oceans ,117. ComEpilithic bacterial biofilms in coral reefs have been characterized using molecular tools on spatial and temporal scales in Sulawesi, Indonesia  and in tWe show that in the central Red Sea five bacterial phyla dominate biofilms over all reef sites and seasons. Of these, Proteobacteria, Bacteroidetes, and Cyanobacteria were previously described from coral reef biofilms in the GBR, and Verrucomicrobia were previously found in coral reef sediments ,123 and Bacterial biofilm diversity in this study was at least 10-fold higher than bacterial diversity in reef water, and also in relation to reef water and coral microbiomes reported in other Red Sea studies ,60,62. ISimilar to findings for reef water bacterial communities, studies showed that seasonality of biofilm communities was minor or not detectable along nutrient or pollution gradients in coral reef systems, while the spatial gradient was strong ,32. ThisOur biofilm data includes algal assemblages following a three months succession from a cross-shelf gradient over four seasons. Composition of algal biofilms plays an essential role in coral and other invertebrates settlement and the survival of recruits ,43. BrowIn our study, algal community composition significantly differed between reefs and seasons, confirming that algal communities and their biomass are highly dynamic ,134,137.in situ.Increasing the understanding of environmental variability in coral reefs is essential to predicting ecosystem response to environmental change ,139. WhiEx situ experiments confirmed a temperature induced regulation of bacterial biofilm composition and physiology [Although nutrient enrichment or pollution related factors were shown to be the only drivers of bacterial communities in coral reefs elsewhere ,121,141,ysiology ,35,142. ysiology –145.The spatio-temporal structuring of algal biofilm communities at our sites were best explained by salinity, chlorophyll-a, and current speed. We expected chlorophyll-a to be associated with differences in algal composition, given that irradiance together with nutrient availability (both variables that are related to chlorophyll-a) are considered the most important requirements for algal growth ,146. SalIn situ data show that temperature and dissolved oxygen concentrations on reefs in this region are similar to projected ‘future ocean’ conditions on reefs elsewhere. Therefore, reefs in the central Red Sea provide an opportunity to study coral reef functioning under environmental change.The Red Sea is known as an oligotrophic, but sparsely studied region that maintains reefs of high coral cover at high temperature and salinity. Our analyses highlight spatio-temporal dynamics of physico-chemical and biotic variables in the central Red Sea. As such, our data provide a comparative foundation for future coral reef studies. S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.


These changes have driven major reductions in reef growth potential, which have declined from an average 4.2 to −0.4 mm yr−1. Thus these shallow fore-reef habitats are now in a phase of net erosion. Based on past bleaching recovery trajectories, and predicted increases in bleaching frequency, we predict a prolonged period of suppressed budget and reef growth states. This will limit reef capacity to track IPCC projections of sea-level rise, thus limiting the natural breakwater capacity of these reefs and threatening reef island stability.Sea-surface temperature (SST) warming events, which are projected to increase in frequency and intensity with climate change, represent major threats to coral reefs. How these events impact reef carbonate budgets, and thus the capacity of reefs to sustain vertical growth under rising sea levels, remains poorly quantified. Here we quantify the magnitude of changes that followed the ENSO-induced SST warming that affected the Indian Ocean region in mid-2016. Resultant coral bleaching caused an average 75% reduction in coral cover (present mean 6.2%). Most critically we report major declines in shallow fore-reef carbonate budgets, these shifting from strongly net positive (mean 5.92 G, where G = kg CaCO Coral reefs support a wealth of ecosystem goods and services that extend across the provisioning of food resources, through cultural and tourism benefits, to those associated with shoreline protection12456899103 m−2 yr−1). We use these data to address two specific questions: 1) what impact did the 2016 warming event have on the ecological composition and carbonate budgets of the shallow fore-reef (2 m depth) habitats, and how consistent were the responses across these reefs?; and 2) what have been the resultant impacts on reef growth potential?Negative budget trajectories have already become evident across regions such as the Caribbean, where the effects of prolonged and systematic ecological decline, caused both by direct human disturbances and a suite of coral diseases, have resulted in steady transitions to states of low coral carbonate production131516Acropora spp. . Observational data indicates that extensive Acropora spp. mortality occurred to depths of ~5–6 m at all sites. Whilst many massive and sub-massive morphology taxa (including Porites spp.) survived the bleaching , fundamental changes to the ecology of these shallow fore-reef habitats have occurred. As of early September 2016 most dead Acropora colonies remain in living position  in the net carbonate budgets at all five sites , which collectively accounted for between 52 ± 15.3% and 65.2 ± 13.7% of coral carbonate production  more than doubled , and was significant at all sites  taxa also increased   coral carbonate production was dominated by branching, corymbose and tabular species of oduction . Post-bl0–48.0%) , as did 0–48.0%) , but ove0–48.0%) .−1   . This pomm yr−1) , will prThe major and prolonged period of elevated SST that caused coral bleaching in the Maldives in 2016 resulted from the recent strong El Niño that originally begun forming in the central Pacific region in June 2014Acropora spp., the cover of which has declined by an average 91%. This not only has major budget implications, but also major ecological implications because of the high habitat complexity and diversity such corals provide within these shallow fore-reef habitatsPocillopora), which is often badly impacted by bleaching6A key driver of these declines has been the mass mortality of branched and tabular −1 to −0.4 mm yr−1. We note that pre-bleaching rates are similar to those measured at Acropora-dominated sites around the remote Chagos Archipelago  in mid-2015  Acropora–dominated reefs in the central Indian Ocean, a rate supported by metadata analyses of shallow water Indian Ocean accretion ratesThe net effect of these budget changes has been to drive very substantial declines in shallow fore-reef growth potential, which have declined from an average 4.2 mm yrA key implication of the major post-bleaching changes we report is that, at least at present, the shallow fore-reef habitats on these Maldivian reefs have shifted from states defined by strong growth potential to a situation dominated by net framework erosion and breakdown. This has potentially very significant implications in terms of the capacity of these reefs to continue acting as breakwater structures for the reef islands that they support. In the short-term (the next few years) the breakdown and loss of shallow fore-reef surface structural complexity will likely reduce the effectiveness of these reefs to reduce wave energy propagation across the reef flats25283As at other sites where relationships between coral cover and carbonate budgets have been examined14Acropora species is an especially important control on budgets and accretion potential. Acropora cover and accretion rate are strongly correlated  typically dominate in shallow-water Indian Ocean reef habitats. These same species also drive high rates of coral framework production and result in high potential accretion rates  which will be the most susceptible to future bleaching events, and thus the most susceptible to future rapid declines in carbonate production and reef accretion. Secondly, it must also be assumed that if bleaching events become more severe and frequent then the capacity  the recovery of Acropora communities will progressively diminish, potentially to the point that even the most remote and protected reefs will struggle to recover from disturbances in terms of their budgets and growth potential.In the present study we also note that the abundance of fast growing rrelated , and theleaching . In otheAcropora and Pocillopora. The timescales over which this recovery occurred varied between sites, but recovery of coral cover and communities to pre-1998 levels/states was generally evident by around 2009 to 2012, depending on location2236An important issue now will therefore be whether and when these reefs may recover, both ecologically and in terms of their carbonate budgets. Evidence from other sites in the region which were strongly impacted by the 1997/98 bleaching event suggest some grounds for optimism, especially where the reefs are relatively remote or isolated from high levels of direct human disturbance. For example, the reefs around the remote Chagos archipelago  showed an impressive capacity for recovery from the 1997/98 mass coral bleaching event. Coral cover on most reefs around Chagos had recovered to pre-bleaching levels by around 201022However, there will be three key factors that influence future recovery. The first, as outlined above, will be the frequency and magnitude of future SST warming events, and which are predicted to increase in the near future15163 m2 yr−1) we used a previously modified version of the ReefBudget methodologyet al.Acropora branching, Porites massive etc. ; sediment; bare substrate ; sediment; rubble; and other benthic organisms. Substrate rugosity was calculated as total reef surface divided by linear distance  were established running parallel to the reef crest, with a spacing of 5 m between transects. To quantify substrate composition, reef rugosity, and gross carbonate production and erosion, and thus to determine net carbonate budgets  and linear growth rates (cm year−1) across each transect to estimates carbonate production rates in kg CaCO3 m−2 year−1. In most cases we used mean regional growth rates and densities for each coral genera  based on published data for that species or for similar sized species with the same feeding functional group. We then used the following equation to calculate species specific erosion rates for the median value within each size class:To quantify rates of biological substrate erosion we used three approaches for different elements of the bioeroding communities. Rates of macro- and microendolithic bioerosion were based on published rates per unit area derived from experimental studies in the Indo-Pacific region, and these were applied to all available dead carbonate substrate available to bioeroding sponges, including that covered by macroalgae or algal turf and live coral cover and soft coralsv is bite volume (cm3), sprop is the proportion of bites leaving scars, br is bite rate (bites day−1) and d is substratum density (kg cm−3), here taken to be 1.49 after Morgan & Kench (2012).where −1) pre- and post-bleaching we converted our net production rate estimates to potential accretion rates (mm yr−1), using an approach previously applied to other Indian Ocean and Caribbean reefs1242To assess changes in the accretion potential of reefs .Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


However, these compounds have not been compared on an unbiased, raw-signal level. Here, we directly compare several in vivo SHAPE acylation reagents using the simple primer extension assay. We conclude that while multiple SHAPE technologies are effective at measuring purified RNAs in vitro, acylimidazole reagents NAI and NAI-N3 give markedly greater signals with lower background than 1M7 for in vivo measurement of the RNA structurome.Recent advances in SHAPE technology have converted the classic primer extension method to next-generation sequencing platforms, allowing transcriptome-level analysis of RNA secondary structure. In particular, icSHAPE and SHAPE-MaP, using NAI-N RNA molecules have the inherent ability to fold into complex structures through base-pairing and three-dimensional interactions, allowing them to interact with all types of molecules, while still containing genetic information . For decDimethylsulfate (DMS) RNA methylation, for example, is used to identify base-paired adenosine and cytosine nucleotides . DMS hasIn contrast, SHAPE (selective 2′-hydroxyl acylation and primer extension) is unique in that it interrogates all four nucleobases, enabling structure measurements at single-nucleotide resolution. Furthermore, there has been a recent expansion of SHAPE to the intracellular context. For the most part, this has been the result of novel chemical and biochemical designs that enable robust RNA modification inside cells. For these reasons, SHAPE is now regarded as a gold standard chemical strategy to measure RNA secondary structure . Chemica3, while SHAPE-MaP uses 1M7 or NMIA  and the 5S ribosomal RNA (rRNA). All four electrophiles generated robust cDNA truncations for these RNAs in vitro . A major difference between the in vivo and in vitro conditions for SHAPE mapping are the cell walls and membranes encasing the transcriptomes of these organisms. We therefore hypothesized that lack of 1M7 signal from in vivo experiments comes from the impermeability of 1M7 to cell barriers, and therefore, permeabilization of these barriers would increase 1M7's acylation signal. To this end, we compared the SHAPE signal of mouse ES cells modified with NAI-N3 and 1M7 in “intact” and “permeabilized” conditions, effectively live and dead cells, respectively. Briefly, to permeabilize cells we incubated them in a dilute, nonionic detergent (0.05% NP-40) for 5 min at 25°C. While NAI-N3 samples produced comparable SHAPE signals between the intact and permeabilized conditions, 1M7 modified samples had increased signal after cell permeabilization  as compared with NAI (−1.3) and NAI-Nlization C. 1M7 molization C. These By implementing a traditional approach to interpreting SHAPE modification, we were able to directly compare the RNA acylation capacity of four SHAPE electrophiles on in vivo and in vitro modified RNA. FAI and NAI derivatives were specifically designed and synthesized to have properties amenable for labeling of RNAs inside living cells, such as longer half-lives and higher solubilities . Comparitrans-acting RNAs and proteins  supplemented with 15% FBS, 1% PenStrep, 1% MEM NEAA, 1% GlutaMax, 0.2% β-mercaptoethanol, and 0.01% LIF. HST08 E. coli cells were grown in LB medium with ampicillin at 37°C.V6.5 mouse embryonic stem cells were grown at 37°C with 5% COE. coli RNA was extracted by bacterial lysis as stated in 2, 100 mM NH4Cl, 4 mM β-mercaptoethanol, and 16% (wt/vol) sucrose supplemented with 15 µL of 50 mg/mL lysozyme.Mouse ES cell RNA was collected from cells by TRIzol and chloroform preparation, followed by RNeasy Mini column (Qiagen). 2, and 100 mM NaCl. Samples were then modified for 5 min at 37°C with either the DMSO control or the SHAPE reagents FAI, NAI, NAI-N3 at 100 mM final or 1M7 at 10 mM final. Modified RNA was then cleaned up and eluted in pure, RNase-free water using RNeasy Mini columns (Qiagen) before primer extension.Purified RNA from both mouse and bacteria cells was folded by a 95°C denaturation, a quick cool to 4°C, followed by 5 min incubation at 37°C in 100 mM HEPES pH 7.5, 6 mM MgCl3, 10 mM 1M7, and 100 mM 1M7. Cells were modified for 5 min at 37°C. Media were removed, and RNA was purified by TRIzol and chloroform preparation followed by RNeasy Mini Column (Qiagen).RNA was modified and collected from mESCs using the same conditions as previously published for mammalian cell modification . Old medE. coli cells were modified with SHAPE reagent using the conditions as written in 3 at 30 mM and 1M7 at 5 mM, all with a final DMSO concentration of 3% (v/v) in LB. Modified RNA was extracted from bacteria by lysis as described earlier, followed by TRIzol chloroform preparation and RNeasy Mini column (Qiagen).Mouse U1 snRNA: 5′-CCCACTACCACAAATTATGCAG-3′Mouse 5S rRNA: 5′-AAAGCCTACAGCACCCGGTAT-3′E. coli 5S rRNA: 5′-TGCCTGGCAGTTCCCTACTC-3′32P using OptiKinase and [γ-32P]–ATP. RNA was reverse transcribed into cDNA with SuperScript III at 55°C for 25 min. After cDNA synthesis, the remaining template RNA was degraded by adding NaOH and heating for 5 min at 95°C. The samples were then run across a 35-cm-long 8% Urea PAGE gel. The gel was dried for 2 h on a vacuum gel drier and then exposed for 24 h.RT primers were synthesized by IDT, with basic desalting purification, and then radiolabeled with The signal-to-background (S/B) ratio reported for each lane is the arithmetic mean of the ratios  of three bands. Signal is defined as mean pixel intensity of a band as measured by ImageJ . Background is defined as mean pixel intensity of a low intensity region next to the signal band. The bands were in the same position for all lanes within a blot and were chosen based on presence in the greatest number of SHAPE modified condition lanes , but not in the unmodified  condition.


Neuronal cells express considerable plasticity responding to environmental cues, in part, through subcellular mRNA regulation. Here we report on the extensive changes in distribution of mRNAs in the cell body and axon compartments of peripheral sensory neurons and the 3′ untranslated region (3′UTR) landscapes after unilateral sciatic nerve entrapment (SNE) injury in rats. Neuronal cells dissociated from SNE-injured and contralateral L4 and L5 dorsal root ganglia were cultured in a compartmentalized system. Axonal and cell body RNA samples were separately subjected to high throughput RNA sequencing (RNA-Seq). The injured axons exhibited enrichment of mRNAs related to protein synthesis and nerve regeneration. Lengthening of 3′UTRs was more prevalent in the injured axons, including the newly discovered alternative cleavage and polyadenylation of NaV1.8 mRNA. Alternative polyadenylation was largely independent from the relative abundance of axonal mRNAs; but they were highly clustered in functional pathways related to RNA granule formation in the injured axons. These RNA-Seq data analyses indicate that peripheral nerve injury may result in highly selective mRNA enrichment in the affected axons with 3′UTR alterations potentially contributing to the mechanism of neuropathic pain. The uniqueness of neurons is highlighted by their exceptionally complex compartmental diversity. Within a single neuron, various cellular compartments may respond differently to environmental stimuli by initiating localized synaptic- and non-synaptic plasticity.Neurons in the central and peripheral nervous systems receive physiological stimuli as well as pathological insults that transiently or permanently modulate neuronal function. Neural plasticity, broadly described as the changes in neuronal morphology6, including synaptic plasticity and memory7. The initiation of translation is rigidly regulated by the formation of eukaryotic initiation factors (eIFs) and ribosomal complex that binds to the 5′-cap structure of mRNA8. All necessary factors for protein translation are found in the axon of peripheral neurons9. Using hyperalgesic priming models, it has been shown that translational regulation of localized mRNAs in sensory axons plays an important role in the maintenance of chronic pain11.In recent years, co/post-transcriptional mechanisms such as mRNA modification, axonal transport and subcellular protein synthesis have been recognized as key regulators of spatial-temporal control of neural plasticity12. The 3′UTR contains cis-binding sites for micro RNAs (miRNAs) and regulatory RNA binding proteins (RBPs). The alternative selection of canonical polyadenylation sites results in the variable lengths of the 3′UTR, which may generate different recognition cis-acting binding sites to miRNAs and/or RBPs, ultimately modulating mRNA stability, its subcellular localization, and protein synthesis15.Local protein translation depends on transport of mRNA from the cell body to distal sites. Axonal mRNA transport and localization are mostly controlled by untranslated regions (UTR) at the 3′ ends. With the advent of high throughput RNA sequencing (RNA-Seq), genome-wide analyses of mRNAs revealed a widespread use of alternative cleavage and polyadenylation yielding multiple 3′UTR structures16. These symptoms are widely considered due to the hyperexcitability of primary sensory neurons20 and the ectopic activation of the voltage-gated ion channels including the sensory neuron specific voltage gated sodium channel 1.8 (NaV1.8)21. It is highly conceivable that during the development of a painful neuropathy, neuronal cell bodies, axons and synapses undergo maladaptive plasticity as a response to the etiological events23. The present study used RNA-Seq analysis of rat dorsal root ganglia (DRG)-derived neuronal cell bodies and axons after sciatic nerve injury to characterize the compartmental distribution and 3′UTR changes of mRNAs.Pathological stimuli or injury to peripheral nervous system can result in painful neuropathies that commonly share clinical features such as light touch-evoked pain , burning sensation, exaggerated responses to noxious stimuli , and either spontaneous or evoked unpleasant abnormal sensations (dysesthesia)25 and its variant sciatic nerve entrapment (SNE) injury28 have been shown to induce a painful neuropathy in the ipsilateral hindpaw. The intact DRG and nerve proximal to the site of constriction/entrapment provide a convenient model for molecular biological experiments. In the present study, injury to the rat sciatic nerve was accomplished by unilateral SNE surgery ery Fig. . The devery Fig. . Seven dery Fig. . In thisAfter the quality and quantity of RNA were determined, we prepared 3 independent RNA samples from each cell body and axon group ipsilateral and contralateral to SNE. A total of 12 RNA samples were subjected to RNA-Seq using a commercially available protocol . About 67 to 78% (average 74%) of 16 to 31 million total raw reads (average 24 million raw reads) were uniquely aligned to Rat genome sequence (Build rn5) Table . Sequenc33 or neuron growth and development35.Neural plasticity in response to extracellular stimuli can occur partly through axonal redistribution of specific mRNAs thus altering their steady state levels in the subcellular domains. To determine the relative abundance of specific mRNAs in the axon and cell body compartments, we performed gene expression analysis of the RNA-Seq reads comparing axon to their cell body compartment on the SNE-ipsi and contralateral sides. Our analysis identified 2,146 and 2,716 mRNAs with significantly modulated expression (q < 0.05) between the axon and soma compartments on the SNE-conditioned (ipsi) and control (contra) sides respectively Fig. . Among tIn ipsi and contralateral axon compartments, 974 mRNAs on the SNE-conditioned (ipsi) side and 578 mRNAs on the control (contra) side showed at least two-fold difference (log2FC > 1), of which 424 mRNAs were common. The enriched mRNAs in the contra axon compartment as compared to the cell body were predominantly related to the structure and function of ribosomes and mitochondria, which generated a tightly connected network including an additional network of small nuclear RNA-related transcripts Fig. . The enrde novo alternative polyadenylation (APA) events at the 3′UTR and differentiate the occurrence of APA using the RNA-Seq read density data. Comparison between the ipsi and contra cell body samples revealed limited use of APA sites that was found only in 16 transcripts even when the significant level was adjusted to p < 0.05. By contrast, mRNAs containing alternative 3′UTR structures were significantly increased in the control (contra) and injury-conditioned (ipsi) axons  did not report these extended 3′UTRs of TRPV1 and TRPA1, suggesting these extended 3′UTRs to be novel.DaPars is a linear regression algorithm aiming to determine known and ons Fig. . Based oons Fig. , whereasons Fig. . The Nat37. Other NaV isoforms such as NaV1.3, NaV1.7 and NaV1.9 did not show RNA-Seq fragments beyond the end of the annotated 3′UTR structure; however, NaV1.6 did exhibit RNA-Seq fragments beyond the annotated data of rats  Fig. . DaPars ats Fig. . BecauseThe cluster of RNA-Seq reads distal to the annotated NaV1.8 3′UTR localized on rat chromosome 8: 127,501,055–127,502,247, where 3 additional consensus polyA signals were found  Fig. . TherefoThe exon encoding the long 3′UTR was used to assess the relative expression of NaV1.8 in the RNA-Seq data, which demonstrated that the NaV1.8 mRNA containing the long 3′UTR was exclusively observed in the SNE-conditioned axons Fig. . The genThe DaPars data demonstrated that the use of alternative short 3′UTR was common (62.8%) in the control (contra) axons, whereas the use of alternative long 3′UTR increased to 49.0% in the SNE-conditioned (ipsi) axons Fig. . AlternaWhen NaV isoforms were evaluated by real-time PCR, we observed a trend of increased NaV1.8 mRNA in the SNE-conditioned (ipsi) axons compared to the control (contra) axons, while other NaV species in the axon did not differ significantly between the SNE-conditioned (ipsi) and control (contra) axons Fig. . The RNAThe SNE-conditioned (ipsi) and the control (contra) axon samples contained 494 and 452 mRNAs, respectively, which used different 3′UTRs from the cell body samples (p < 0.05). The axonal mRNAs with differential 3′UTR use shared 162 transcripts; but 328 and 286 transcripts were unique to the ipsi and contra axon samples, respectively. These unique transcripts in the SNE-conditioned (ipsi) axons exhibited strong clustering within a total of 46 KEGG pathways such as the regulation of actin cytoskeleton and MAPK signaling pathway Fig. . By contWe further analyzed mRNAs with alternative 3′UTRs in the SNE-conditioned (ipsi) axons using Gene Ontology (GO) enrichment analysis for functions. Among 46 functional pathways identified, a large number of transcripts was clustered in pathways related to RNA/nucleic acid binding, protein binding/aggregation and ion binding functions, followed by enzyme/kinase activity and cytoskeleton binding functions Fig. . We foun39, resulting in the match with 61 enriched mRNAs, whereas none matched with the contra cell body compartment. It has been reported that when sciatic nerve was injured prior to acute dissociation and culturing, DRG neurite outgrowth was more robust and peripheral axons appeared to activate their intrinsic growth capacity, as compared to the uninjured DRG culture41. The axoplasm of peripheral neurons is characteristically long and axonal mRNA localization is particularly complex and prominent42, providing a local regulatory mechanism for responding to acute or chronic injury that may occur at the distant axon43. Gumy et al. (2011) performed a microarray analysis of axonal RNA isolated from compartmentalized chamber cultures, reporting 812 mRNA species in the axons of naïve and sciatic nerve crush injury rats44. Cross-referencing with our data revealed that 44.8% of the commonly upregulated mRNAs in axons and 37.7% of upregulated mRNAs unique to the control (contra) axons were matched. By contrast, only 6.7% of upregulated mRNAs unique to SNE-conditioned (ipsi) axons were matched. After peripheral nerve injury, neurotrophic factors were reported to become available in the surrounding environment, which were thought to promote axonal regeneration46. The present RNA-Seq analysis revealed that the increased mRNAs related to growth factor receptors 57 were also shown to facilitate rapid neurite extension in vitro. The activation of stress-induced MAPK and PI3K-Akt leads to the phosphorylation of various proteins, including eIF2a59. The present study also suggested that those mRNAs with alternative 3′UTRs in the SNE-conditioned (ipsi) axons clustered in the GO functional pathways of RNA binding proteins such as T-cell intracellular antigen-1 (TIA1), Fused in Sarcoma (FUS) and Pumillio homolog 2 (Pum2). These functional clusters are highly relevant to form RNA-protein complexes and cytoplasmic RNA granules60 NAs Fig. . The pres60 Fig. . Stress 65. By contrast, mRNAs clustered in the functional pathways related to RNA granules exhibited predominantly shortened 3′UTR  and followed the guideline of PHS Policy for the Humane Care and Use of Laboratory Animals and the UCLA Animal Care and Use Training Manual.75. Briefly, in anesthetized rats, the left sciatic nerve was surgically exposed, and three polyethylene cuffs  were loosely fitted to the sciatic nerve proximal to the trifurcation of common peroneal, tibial, and sural nerves. Muscle and skin were separately closed. A sham group of rats underwent surgeries without placing the polyethylene cuffs in tandem with the SNE group.Surgical procedure for the SNE model was described previously75. Hypersensitivity of ipsilateral hindpaws was confirmed for each SNE rat.Measurements of hindpaw withdrawal thresholds to mechanical stimuli were obtained in SNE rats every 2 days as described in detail previously74. Ipsilateral and contralateral DRG neurons from SNE rats were cultured on the Boyden chamber culture system76, which separates the upper compartment and the lower compartment by a porous membrane  coated with Matrigel. Uridine and deoxy 5-fluorouridine were added  into the culture medium to prevent non-neuronal cell proliferation. Cultures were maintained for 48 hrs. Then axons were isolated by carefully scraping the cellular contents from the lower membrane surface with a metal scraper . The DRG cell bodies on the upper compartment were similarly isolated by scraping the upper surface of the membrane.Seven days after SNE surgery, L4-L5 DRG were harvested from SNE male Sprague-Dawley rats and acutely dissociated as previously describedin vitro model allows acutely dissociated DRG neurons to develop long enough neurites, which passed through the membrane pores. In order to increase the amount of RNA collected from the axon compartment, we tested the extended (7-day) culture periods. However, despite the use of uridine and deoxy5-fluorouridine to prevent non-neuronal cell proliferation the 7-day cultures exhibited non-neuronal cell proliferation. This would have contaminated the sought after pure neuronal RNA. It is well known that while adult dissociated DRG neurons retain their phenotypic features shortly after dissociation and plating, the longer they are maintained in culture the less of the original phenotype remains. Willis et al. (2005) suggested 18 hours to collect RNA samples from the neurite/axon compartment of the Boyden chamber system77. In our study, mature neurite/axon was not consistently organized within this period. Li et al. (2004) isolated axons from dissociated DRG cultured for 48 hours and demonstrated axonal presence of eIF-4E78. We therefore decided 48 hours as appropriate time to harvest axonal RNA samples in order to obtain sufficient axonal RNA and retaining the phenotypic features of SNE conditioning.Our Total RNA from DRG cultures was isolated and treated using miRNeasy mini and micro kits (QIAGEN) with DNase I . The steady state mRNA levels of NaV1.3, NaV1.6, NaV1.7, NaV1.8, and NaV1.9 were determined by TaqMan-based real time PCR (RT-PCR): NaV1.3-Rn00565438_m1; NaV1.6- Rn00570506_m1, NaV1.7-Rn00581647_m1; NaV1.8-Rn00568393_m1; and NaV1.9-Rn00570487_m1. The mRNA expression levels were normalized using the comparative CT method.One hundred (100) ng of total RNA isolated from neuronal cultures was subjected to whole transcriptome amplification using the NuGEN′s Ovation RNA-Seq V2 kit  per manufacturer’s instructions. Amplified cDNA samples were then purified via the MinElute Reaction Cleanup Kit (Qiagen) and sheared into small fragments on the Covaris E210 acoustic focusing instrument , optimized to achieve an insert size of 350 bp. Paired-end cDNA libraries were prepared with TruSeq Nano DNA Library Preparation Kit (Illumina) according to manufacturer instructions and the final library size distribution was determined using the Agilent Bioanalyzer 2100. Prepared libraries were then sequenced on HiSeq 2500 sequencing system (Illumina) in rapid mode following the cluster generation on cBot. Briefly, cDNA libraries were each diluted to 6 pM and spiked with 1% phiX control to improve base calling while sequencing. A 6 pM dilution of phiX control sample was also prepared for analysis. Following the Illumina cBot and HiSeq protocols, the cDNA libraries and the phiX control underwent cluster generation on a HiSeq PE flow cell v3 followed by sequencing on HiSeq 2500 (Illumina). A paired-end (2 × 101) run was performed using the TruSeq SBS Kit (Illumina). Real-time analysis and base calling were performed using the HiSeq Control Software Version 1.4.5 (Illumina). The resulting base calling (.bcl) files were converted to FASTQ files using Illumina’s CASAVA 1.8 software. The number of reads for each sample type was analyzed using the Student′s t-test in SigmaPlot version 11.0 . A p-value < 0.05 was considered significant.Rattus norvegicus reference genome rn5 using TopHat v1.3.024 integrated with Bowtie v0.12.725on cloud computing, BaseSpace . The resulting aligned reads were analyzed further by Cufflinks v1.0.326. The aligned reads were assembled into transcripts, either with or without a reference genome, and the expression of those transcripts were reported in Fragments Per Kilobase of exon per Million fragments mapped (FPKM). Cuffdiff analysis was performed, with use of the reference genome, to determine differential expression of known isoforms between ipsi- and contralateral samples.Paired-end fastq sequence reads for each sample were aligned to the UCSC Differential gene expression analysis was performed using the RNA Express application on Basespace, Illumina. Briefly, paired-end reads from all samples were mapped to a rat reference genome (Rn5) using the STAR ultrafast read aligner. Post-alignment and read counting, raw read counts were used for differential gene expression analysis using R and DESeq2. A false discovery rate (FDR) adjusted q value < 0.05 was used to test for significance.51. Briefly, DaPars identifies distal polyA sites based on RNA-Seq data. It uses a regression model to infer the exact location of the proximal APA site after correcting the potential RNA-Seq non-uniformity bias along gene body and thus detects statistically significant dynamic APAs. Given two or more RNA-Seq samples, distal polyA site refers to the end point of the longest 3′UTR among all the samples, which is used to identify the proximal polyA within this longest 3′UTR region. To identify possible distal polyA site that might locate outside of gene annotation, DaPars extends the annotated gene 3′end by up to 10 kb before reaching a neighboring gene. RNA-Seq data from all input samples were merged to have a combined coverage along the extended gene model. Differential percentage of distal APA usage index (DPDUI) was determined to detect the most significant APA events.DaPars algorithm has been previously published79 (http://david.ncifcrf.gov) and the String Protein-Protein Interaction Network80 (http://string-db.org).Differentially expressed genes and genes with alternative 3′UTRs were subjected to KEGG and GO Enrichment analyses using the online tools. These gene lists were submitted to DAVIDwww.broadinstitute.org/igv/). The output files generated from TopHat were converted into files viewable in IGV on the BaseSpace and then processed further by the “count” function in IGV tools (included with the IGV software) to create an average alignment track viewable as a bar chart. The log2 of the frequency of the reads was plotted to better visualize the extensive range of the read coverage. Individual gene views were created by first merging the TopHat output files from the ipsi- and contralateral samples. These merged files were processed in the same way as above with the “count” function in IGV tools. The raw frequency of the reads was visualized in this case.Aligned reads were visualized using the Integrative Genomics Viewer (81. The match PWM function in v. 2.24.1 of the Biostrings Bioconductor package was used to predict binding sites in the NaV1.8 3′UTR.Position weight matrices (PWMs) for 72 RNA-binding proteins  were bulk downloaded from the RNA-binding protein databankRNA pooled from samples collected from the modified Boyden culture was used for cDNA cloning by reverse transcriptase PCR using 3′UTR targeted PCR primers Fig.  followint test for two-group comparison and one- or two-way analysis of variance (ANOVA) with Tukey’s multiple comparisons for multi-group comparison were used to analyze RT-PCR and RNA-Seq data with p < 0.05 accepted as statistically significant. Repeated measures ANOVA analysis was used to compare ipsi- and contralateral hindpaw sensitivity to mechanical stimuli of SNE injured rats.Student’s Supplemental Information


The functional implications of this striking colocalization have been unknown. Here, we show that slam mRNA translation is spatiotemporally controlled. We found that translation was largely restricted to the onset of cellularization when Slam protein levels at the basal domain sharply increase. slam mRNA was translated locally, at least partially, as not yet translated mRNA transiently accumulated at the basal region. Slam RNA accumulated at the basal domain only if Slam protein was present. Furthermore, a slam RNA with impaired localization but full coding capacity was only weakly translated. We detected a biochemical interaction of slam mRNA and protein as demonstrated by specific co-immunoprecipitation from embryonic lysate. The intimate relationship of slam mRNA and protein may constitute a positive feedback loop that facilitates and controls timely and rapid accumulation of Slam protein at the prospective basal region.Many mRNAs specifically localize within the cytoplasm and are present in RNA-protein complexes. It is generally assumed that localization and complex formation of these RNAs are controlled by trans-acting proteins encoded by genes different than the RNAs themselves. Here, we analyze  slam mRNA and its encoded protein during cellularization in early Drosophila embryos. slam RNA and protein are known to colocalize and are essential for epithelial compartmentalization and timely invagination of the plasma membrane between adjacent nuclei. We now show that Slam protein is required for RNA localization at the basal domain and that this event is needed for efficient translation. In addition to the functional interactions, we find that slam RNA and protein are both present in a specific molecular complex. Our findings indicate that slam is locally translated and that the interaction between Slam protein and RNA constitutes a self-enhancing mechanism leading to the fast accumulation of Slam protein at the basal domain during the first minutes of cellularization.While proteins and their encoding messenger RNAs share the same intracellular space during the translation process, thereafter they are usually spatially and biochemically separated. RNA localization follows a specific subcellular pattern—such as apical or basal—and is thought to have important physiological implications during development, which are generally independent from the protein function. Here, we investigate the potential mutual dependencies between  Drosophila embryos by RNA in situ hybridization with fluorescent probes revealed that about 70% of all tested transcripts were distributed in a specific subcellular pattern, such as apical or basal localization )  . These dslam[ACU] RNA, we could test whether Slam protein accumulation at the FC would depend on RNA localization. We stained embryos injected with the nonlocalizing slam[ACU] mRNA for Slam protein . S2 cells do not express Slam protein in detectable levels  into the slam[ACU] embryos  and lysates of embryos expressing GFP-slam from a genomic transgene in comparison to wild-type extracts  information for specific subcellular localization of the RNA at the FC, which is at least partially mediated by an interaction with Slam protein, and (2) information for spatial and temporal control of translation, which is high at the FC during the onset of cellularization. By comparing wild-type RNA with a variant RNA, slam[ACU] with the same coding information, the relevance of the noncoding information was uncovered. slam[ACU] RNA is widely distributed in the cell and gives rise to much less Slam protein. Containing coding and noncoding information distinguishes slam RNA from generic mRNAs, which contain only coding information. slam RNA may be related to the growing class of mRNAs with coding and noncoding functions (cncRNA)  RNA with slam[ACU] RNA. Although both RNAs contain the same coding information and give rise to similar amounts of Slam protein in cultured cells, slam[wild-type] RNA is more efficiently translated than slam[ACU] RNA in blastoderm embryos. Based on the correlation of impaired RNA localization and reduced translational efficiency, we favor the model that efficient translation is linked to RNA localization or interaction with Slam protein at the FC. However, the embryo-specific lower efficiency of slam[ACU] translation may alternatively be due to secondary RNA structures or disadvantageous codons, which were introduced in our mutagenesis.This initial rise in protein levels is partly due to the transcriptional up-regulation of slam is that the encoded protein is required for the elaboration of noncoding features. slam RNA requires Slam protein for accumulation at the FC. Not only do we observe a functional interaction of the RNA and protein but also colocalization and biochemical association, indicating molecular interactions. These molecular interactions between RNA and protein may be direct or indirect. They are likely to be indirect, as Slam protein does not contain a canonical RNA binding domain or does not share any detectable sequence homology to RNA binding proteins. Analysis of transcripts associated with Slam protein provided distinct lists depending on the experimental procedure. Importantly, slam RNA was identified by both approaches, which is consistent with our quantitative polymerase chain reaction (qPCR) analysis for a few selected genes. The list of associated transcripts contained transcripts with high and low abundance, indicating that the procedure was sufficiently sensitive to also detect weakly expressed genes. Screening through the gene functions, we did not detect a specific set of genes, such as genes involved in cellularization or cytoskeletal organization.A particular feature of slam mRNA and its protein has been unclear. Given the observed specific spatiotemporal profile of slam translation and Slam dynamics, we propose the following model slam Frt2L slam5′rescue/CyO females with hs-Flp122; ovoD2L Frt2L/CyO males and heat shock for 2× 1 h at 37°C in larvae  Frt2L; transgene/+ were crossed with males Df(2L)slam Frt2L slam5′rescue/CyO; transgene/transgene. Rescue of viability was tested with Df(2L)slam Frt2L slam5′rescue/Df(2L)slam Frt2L slam3′rescue; transgene/+  was cloned into the pattB-slam8.6 genomic construct , cDNAs were cloned in frame into pUASp-myc-GFP.Truncations and gene fusions of osophila  and syntonstruct  by PasI h 12xPP7 , 22 was slam RNA probes were generated with T7 RNA polymerase and antisense templates as previously described  at RT overnight. The labeling dye and salts were removed using a desalting Sephadex G50 spin column. For RNA in situ hybridization, escribed .slam[ACU] allele. The numbers in parentheses specify the position of the nucleotide within the cDNA, according to the coding sequence. For genome-wide analysis, RNA extracted from immunoprecipitates was subjected to next generation sequencing (Illumina HiSeq2000), according to the manufacturer’s protocols. Analysis was performed with 2–4 biological replicates. Weakly expressed genes  were not considered in the analysis. RNA expression data were obtained from wild-type embryos with 1.5–2.5 h . Reverse transcription was performed with 1–2 μg RNA and oligo-dT primers according to the instructions of the manufacturer (Roche). Two μl (12.5% of the sample) of reverse transcripts were analyzed by quantitative PCR with specific primers. qPCR reactions were performed in duplicates. Specificity was controlled by a sample in which reverse transcriptase enzyme was omitted and in reactions with defined amounts of templates. The following primer pairs were used for quantitative PCR: WT1 SY88 (603–622) + SY89 (885–903), WT2 SY94 (−334–−316) + SY95 (−24–−1), ACU SY92 (603–620) + SY93 (886–905). ACU is specific for the 5–2.5 h  and fluorescent RNA in situ hybridization was performed as previously described . Proteinslam RNA were recorded with a Leica epifluorescence microscope. Time-lapse recordings with differential interference contrast optics were recorded with an inverted microscope  with a computer-controlled stage, allowing simultaneous recordings of multiple embryos.Fluorescent images of fixed and immune-stained embryos and live imaging experiments were recorded with a confocal microscope (Zeiss LSM780). Images were processed with ImageJ/Fiji and Photoshop (Adobe). Images from FRAP experiments were analyzed as previously described . Time-laEmbryos were injected as previously described . The mRNslam wild type and slam[ACU]  were tested for protein production levels in cultured D. melanogaster Schneider line 2 (S2) cells. S2 cells were grown in Schneider’s Drosophila medium (Gibco/Invitrogen) supplemented with 10% fetal bovine serum (Gibco/Invitrogen) at 25°C. Cells were reseeded 1 day before transfection at about 1.0 million cells/ml (counted in Neubauer chamber). Transfection was performed according to the instruction of the manufacturer (Qiagen Transfection Kit containing Effectene Transfection Reagent). A control reaction (using pCS-GFP) indicated an approximately 6% transformation efficiency. Cells were harvested after 48–72 h. Half of the cells were dissolved in SDS loading buffer (Laemmli) to a final concentration of 50,000 embryos/μl. SDS gel electrophoresis was performed with 1 million cells per sample lane. RNA was extracted from the second half of the cells using Trizol Reagent (Invitrogen).2, 1 mM MgCl2, 0.05% NP40, 100 mM sucrose, 1 M DTT, protease inhibitors [Roche], RNAase inhibitors) in a Dounce homogenizer. The lysate was centrifuged for 15 min at 14,000 rpm to remove debris. The cleared supernatant was mixed with the beads coated with antibody and incubated on a rotator for 1 h at 4°C. A 200-μl sample was taken from the supernatant (unbound fraction). Beads were then washed 4 times with cold YSS buffer. 200 μl of YSS buffer was added to the bound samples. Unbound and bound samples were complemented with 20 μl 10% SDS and 0.5 μl glycogen (20 μg/ml). Samples were extracted with phenol/chloroform/isoamylalcohol. Protein was precipitated from the organic phase with 1 ml acetone. RNA was precipitated by the addition of 40 μl Na-acetat (3 M) and 500 μl 100% ethanol to the aqueous phase. Protein and RNA samples were analyzed by western blot, quantitative RT-PCR, and next generation sequencing, respectively. For co-immunoprecipitation with the single-chain GFP antibody , staged embryos from GFP-slam transgenic or wild-type flies were collected and lysed as described above, except for the following: 0.5 μl biotinylated-GFP binder (50 mM) was mixed with cleared embryo lysate for 1 h at 4°C. Then, 20 μl PBS-washed streptavidin-coupled Dynabeads were added and mixed for a further 1 h at 4°C.Guinea pig-α-Slam antibody  or guineN = 10–20) were lysed in Laemmli buffer with a Dounce homogenizer and analyzed by western blot.SDS polyacrylamide gel electrophoresis (PAGE) and western blot were performed as previously described . PrimaryS1 Figslam transgenes and slam cDNA constructs in comparison to the slam locus. Boxes indicate transcribed regions. Coding sequence is marked in light orange, sequences with alternative coding in red, untranslated region in grey, GFP in green, 6xmyc tag in blue, and 12xPP7 in dark blue. The stop codon following the GFP tag is marked with a triangle.Schematic drawing of genomic (JPG)Click here for additional data file.S2 Fig(A) Relative abundance of slam RNA determined by reverse transcription and quantitative PCR, with RNA isolated from embryo collections staged by time after egg lay. Corresponding nuclear cycles are indicated. (B) Abundance of Slam protein analyzed by western blot with extracts from heat fixed embryos staged by morphology and nuclear cycle. Detection of α-tubulin serves as a loading control. Corresponding absolute time after fertilization is indicated. (C) Wild-type embryos were fixed and stained for slam RNA by fluorescent RNA in situ hybridization (grey/red), for Slam protein by immunostaining (grey/green), and for DNA (blue). Images were recorded from 1 slide in 1 session, with the unchanged settings of the confocal microscope. Embryos were staged by the length of the furrow and nuclear density and morphology. Arrows in yellow point to punctate RNA staining inside the nucleus, which likely represent sites of primary transcription. (D) Expression of slamPP7 RNA in embryos with zygotic expression of slamPP7 in a wild-type background. RNA was detected with a probe specific for the PP7 sequence by fluorescent RNA in situ hybridization. For staging, embryos were stained for Slam protein (red) and DNA (blue), shown in side view. Scheme of the genomic slamPP7 transgenic construct is shown above the images. Scale bar = 10 μm. C, late cellularization (cycle 14); G, early gastrulation (stage 7); MW, apparent molecular weight; P, preblastoderm (nuclear cycle 1–9).(JPG)Click here for additional data file.S3 Fig(A) in mitosis 13, (B) at the onset of cellularization, and (C) in early cellularization. Scale bar = 10 μm.Images from time-lapse recordings of embryos expressing GFP-slam from a genomic transgene prior to and 10 min and 20 min after injection. Embryos were injected with either buffer or cycloheximide (1 mg/ml). Embryos were injected (JPG)Click here for additional data file.S4 Fig(A) Wild-type embryos or slam deficient embryos from germ line clones were injected with indicated mRNA and fixed and stained for Slam protein using Slam or Myc antibodies and RNA by probes for slam or GFP. slam embryos were recognized by the absence of overall slam RNA or protein signal. Scale bar = 10 μm. (B) Schematic representation of constructs. Detected FC localization of the injected RNA is indicated by “+” and red color of the construct and non-FC localization by “–”and faint red color of the construct. slam coding sequence is marked in red, 6xmyc tag in blue, and GFP in green. Dashed lines indicate deletions. Boxes in yellow mark the mapped regions, Loc1, Loc2, Loc3.(JPG)Click here for additional data file.S5 FigComparison of coding sequences of wild-type  and ACU  alleles. Sequences changes in ACU are marked in red. The exon-exon junction of the second intron is marked in yellow. cDNA clone LD22808 contains a third small intron (marked in blue), which is not annotated in the current genome annotation. This piece of sequence was not mutated in the ACU allele.(PDF)Click here for additional data file.S6 Fig Western blot probed with Slam and α-tubulin antibodies with extracts from cultured S2 cells transiently transfected for expression for slam, slam[ACU], or GFP. * marks a cross-reacting band that served as loading control. (C) Abundance of slam transcripts and Slam protein expressed from slam[ACU] in relation to slam[wild type] was determined by western blotting (protein) and reverse transcription with qPCR (RNA) in extracts of transiently transfected S2 cells. Error bar indicates standard error of the mean. N = 3, 3 biological replicates. The underlying data for this figure can be found in (JPG)Click here for additional data file.S7 Figslam germ line clones with or without the slam[ACU] genomic transgene. Embryos were grouped into mutant (red) and zygotically rescued (blue) according to the cellularization phenotype. Bars = standard error of the mean. The underlying data for this figure can be found in N, number of embryos; slam, slow as molasses.The length of the cellularization furrow was measured from time-lapse recordings with differential interference contrast of wild-type embryos and embryos from females with (JPG)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S1 Movieslam mRNA was injected into wild-type embryos. Images were recorded every 20 s. The movie starts in interphase 13. During mitosis, the furrow extends and retracts. During interphase 14, the furrow gradually elongates with the FC moving inwards.Rhodamine-labelled (AVI)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.


Here, we generated a Pdcd5 knockout mouse model to study the physiological role of PDCD5 in vivo. Knockout of the Pdcd5 gene resulted in embryonic lethality at mid-gestation. Histopathological analysis revealed dysplasia in both the LZs and JZs in Pdcd5–/– placentas with defects in spongiotrophoblasts and trophoblast giant cells. Furthermore, Pdcd5–/– embryos had impaired transplacental passage capacity. We also found that Pdcd5–/– embryos exhibited cardiac abnormalities and defective liver development. The growth defect is linked to impaired placental development and may be caused by insufficient oxygen and nutrient transfer across the placenta. These findings were verified in vitro in Pdcd5 knockout mouse embryonic fibroblasts, which showed increased apoptosis and G0/G1 phase cell cycle arrest. Pdcd5 knockout decreased the Vegf and hepatocyte growth factor (Hgf) levels, downregulated the downstream Pik3ca–Akt–Mtor signal pathway and decreased cell survival. Collectively, our studies demonstrated that Pdcd5 knockout in mouse embryos results in placental defects and embryonic lethality.Programmed cell death 5 (PDCD5) is an apoptosis promoter molecule that displays multiple biological activities. However, the function of PDCD5  PDCD5 (programmed cell death 5) gene, formerly designated as TFAR19 (TF-1 cell apoptosis-related gene-19), was first discovered in 1999.1 Existing studies on PDCD5 have revealed that its expression is downregulated in a variety of tumor tissues, and PDCD5 overexpression can promote apoptosis in different tumor cell types in response to various stimuli,3 as well as participate in other types of cell death such as paraptosis4 and autophagy.5 Studies have revealed that PDCD5 can interact with multiple molecules such as TIP60,3 TP53,7 MDM26 and HDAC3,7 and PDCD5 has been shown to play an important role in the TIP60/HDAC3-TP53 signaling pathway to promote apoptosis and G0/G1 phase cell cycle arrest. PDCD5 can also interact with CCT8 to inhibit β-tubulin folding and influence cell division and proliferation.The PDCD5 expression in cells is finely regulated. Transcription factor NF-κB p65 promotes the levels of PDCD5 mRNA and transcriptional activity.9 OTU deubiquitinase 5 (OTUD5) and YY1-associated factor 2 (YAF2) interact with PDCD5 to enhance its stability and inhibit proteasome-dependent degradation.11 In contrast, DNAJB1 enhances ubiquitination and degradation of PDCD5.1213 In PDCD5 transgenic (PDCD5tg) mice, PDCD5 overexpression could alleviate the severity of experimentally induced autoimmune encephalomyelitis (EAE).13 In a rat collagen-induced arthritis model, rats that were treated with recombinant human PDCD5 protein significantly delayed the occurrence and reduced the severity of arthritis.14 Moreover, rhPDCD5 also exerted anti-inflammatory effects in EAE mice.15 Additionally, PDCD5 may also play an important role in influenza virus (H1N1) infection,16 cerebral ischemia/reperfusion injury17 and cardiac remodeling,5 indicating the diversity and complexity of its functions.Recently, we found that PDCD5 interacts with FOXP3, increases acetylation of FOXP3 in synergy with TIP60 and enhances the repressive function of FOXP3.in vivo remains totally unknown. Therefore, in the present study, we generated Pdcd5 knockout (Pdcd5–/–) mice to study the physiological role of Pdcd5 in vivo.Thus far, however, the function of Pdcd5 Zp3-Cre transgenic mice, in which Pdcd5 is exclusively expressed in growing oocytes under the control of the zona pellucida glycoprotein 3 promoter,18 we obtained heterozygous Pdcd5 (Pdcd5+/–) mutant mice with deleted exons 2 and 3. Pdcd5 genomic structure, the LoxP-modified Pdcd5 loci and the mutant Pdcd5 structure. Long-term observation revealed that Pdcd5+/− mice appeared phenotypically normal, and the eldest mouse survived beyond 15 months of age without evidence of significant spontaneous disease. Theoretically, Pdcd5–/– mice can be generated by the intercrossing of Pdcd5+/− mice. However, genotyping of more than 100 pups identified no homozygous mice . Representative PCR identification of mouse embryos at E12.5 is shown in Pdcd5 mRNA and Pdcd5 protein were undetectable in Pdcd5–/– embryos , junctional zone (JZ) and labyrinth zone (LZ) where nutrient transfer occurs between the maternal and fetal blood spaces.19 However, LZ and JZ exhibited a drastic reduction in thickness in the Pdcd5–/–placenta  at E12.5  , glycogen trophoblasts (GlyTCs) and trophoblast giant cells (TGCs). The TGCs are located at the uterine trophoblastic border and play a role in endocrine function. As illustrated in at E12.5 . The bouat E12.5 , and thevessels) , left. H compact , right.  compact . PAS-pose nuclei , left. H present , right. 20 Abundant GLUT-1 expression is crucial to transplacental glucose transfer via the placenta. Next, we investigated Glut-1 protein expression in the placentas at E12.5. Membrane-expressed Glut-1 was detected in both SpTs and GlyTCs but not in the TGCs of the Pdcd5+/+ JZ  assay and cleaved caspase-3 staining. There were no significant differences between the Pdcd5–/– and Pdcd5+/+ placentas  and its high-affinity receptor tyrosine kinases Vegfr. The results revealed that Vegf is highly expressed in maternal vascular endothelial cells in the d5+/+ LZ . Vegfr-2lacentas , left. Od5–/– LZ .Pdcd5+/+ LZ zone but not in the Pdcd5−/− placenta . At E10.5 or E11.5, Pdcd5–/– MEFs failed to adhere to the plate after separation 8 h up to 24 h, unlike Pdcd5+/+ MEFs  and Akt (S473) phosphorylation in the Pdcd5−/− embryos at E12.5  and homozygous-null Tip60–/– mice do not survive up to the post-gastrulation stages of development.22 In another study, Hdac3–/– mice were reported to have died before E9.5 due to defects in gastrulation.23Ck2-deficient embryos stopped development at the blastocyst stage and were resorbed at E7.5.24 Similarly, Vhl KO mice have been found to exhibit embryonic lethality as a result of abnormal placental development.25Vhl-deficient mice died in utero from E10.5 to E12.5, following defective vasculogenesis and hemorrhage of the placental LZ. The Vegf levels in the labyrinth trophoblasts were greatly reduced in Vhl-deficient placentas relative to normal placentas;25 this is similar to the results obtained in Pdcd5–/– placentas. As a multitude of PDCD5-interacting molecules also trigger embryonic lethality when their expression levels are affected, Pdcd5 may function during embryonic development by regulating the above-mentioned molecules or in similar pathways.Several molecules that interact with Pdcd5, such as Vhl, Tip60, Hdac3 and Ck2, can cause embryonic lethality in the corresponding gene knockout mice. Histone acetyltransferase Tip60 and histone deacetylase Hdac3 interact with Pdcd5 to regulate Tp53 activation.19Pdcd5 deletion affected placental vascularization ,28 which is a classical HGF activator to mediate pro-HGF cleavage and maturation.29 In Pdcd5 KO placentas, the number and size of TGCs had significantly decreased, resulting in a reduction in the Vegf and Hgf levels in placentas and embryos. Vegf-deficient mice underwent embryonic lethality before E8.5 due to the lack of vasculogenesis and blood island development.30Hgf–/– mice embryos were found to exhibit reduced liver and placenta sizes and fewer hepatocytes and labyrinthine trophoblast cells relative to their wild-type counterparts. Moreover, the labyrinth region of the placenta was poorly developed, although the number of trophoblast cells in the JZ appeared normal.33 Based on these results, we can conclude that the decreased Vegf and Hgf levels in Pdcd5–/– mice may negatively regulate the expression and phosphorylation of Pik3ca/AKT–Mtor signaling, which occurred in the present study. This may play a contributory role in the defective vascularization and embryonic lethality.TGCs are the first cell type to terminally differentiate during embryogenesis and are of vital importance for implantation and modulation of post-implantation placentation. TGCs mediate blastocyst attachment and invasion into the uterine epithelium, regulate decidualization of the uterus and anastomose with maternal blood spaces to form the transient yolk sac placenta. TGCs secrete a wide array of hormones and paracrine factors, including Vegf, Hgf and prolactin-related cytokines, to target the maternal physiological systems for proper maternal adaptations to pregnancy and the fetal–maternal interface to ensure vasculature remodeling.34 Glucose is one of the most important substances transferred from the maternal blood to the fetal circulation across the placenta, and it is a primary energy source for the fetus. Glucose transport to the fetus across the placenta takes place via glucose transporters, and the Glut-1 glucose transporter appears to be the rate-limiting step in transplacental transport.35 The number of SpTs and GlyTCs was obviously reduced in Pdcd5–/– placentas than in Pdcd5+/+ placentas, and the Glut-1 expression level was lower in the former than in the latter. In particular, the rhodamine 123 transport assay revealed that the placental nutrient transport function was decreased in Pdcd5–/– mice. Together with the insufficient placental vascularization, the lack of energy and nutrition in Pdcd5–/– mice was responsible for the abnormal embryogenesis, and ultimately death.Thus far, the roles of SpTs and GlyTCs in the JZ of mouse placenta remain unknown. It is thought that GlyTCs participate in glucose metabolism and utilize glucose as a source of energy.21 However, heterozygous deletion of Pdcd5 in mice did not lead to the development of any tumors until 1 year of age (unpublished data). Perhaps the one remaining WT allele in heterozygous mice is sufficient to maintain the potential tumor suppressor function of Pdcd5. For many tumor suppressor genes, germline single-allele loss in combination with stochastic somatic loss has been shown to result in an increased incidence of tumors in certain organs. For example, total deletion of tumor suppressor gene Brac1 results in embryonic lethality, whereas mice heterozygous for Brac1 survived and did not develop tumors. Notably, introduction of a TP53-null allele significantly enhances mammary gland tumor formation in Brca1 conditional KO mice.36 Therefore, it is possible that another allele might function synergistically to enhance cancer development in Pdcd5 heterozygous mice. Future studies using Pdcd5 conditional knockout mice crossed with other mice tumor models will be necessary to identify if the embryonic lethality of Pdcd5 homozygous deletion can be overcome and to clarify the potential role of Pdcd5 as a tumor suppressor in vivo.Many tumors have been shown to have reduced Pdcd5 levels, implicating its potential role as a tumor suppressor.Pdcd5 were constructed by the Model Animal Research Center of Nanjing University . A FRT-Neo-FRT-LoxP cassette was inserted into intron 1 of the Pdcd5 gene and a LoxP site was inserted into intron 3. Mice carrying the floxed Pdcd5 allele (Pdcd5+/flox) were mated to mice expressing Cre recombinase under control of the Zp3 promoter (Zp3-Cre). The Cre recombinase can be expressed in the growing oocyte of Zp3-Cre transgenic mice prior to the completion of the first meiotic division.18 To generate heterozygous Pdcd5 knockout (Pdcd5+/−) mice, these Pdcd5+/flox:Zp3-Cre or Pdcd5flox/flox: Zp3-Cre mice were further mated with WT male mice. All mice were bred at the Experimental Animal Center, Peking University Health Sciences Center  under a 12-h light/dark cycle. All mice were given free access to water and standard mouse chow. All protocols used within this study were approved by the Animal Care and Use Committee of the University.Mice were maintained on a C57BL/6 genetic background. Mice harboring a floxed conditional knockout cassette of Pdcd5 genotyping was performed by PCR using DNA isolated from the yolk sacs of embryos or from tails of postnatal mice. Tissues were soaked in 100 μl of 25 mM NaOH and 0.2 mM EDTA lysis buffer, heated for 30 min at 95 °C, and neutralized using 100 μl of 40 mM Tris-HCl (pH 5.5). The following primer sequences were used for Pdcd5 genotyping: P1, 5′-GGACTCCAGAGATGGTGCTCAG-3′ P2, 5′-TTGTCATGGTCATGGGAGCT-3′ and P3, 5′-TTTTCAGGCTTTACAAGTGC-3′. The following PCR cycling conditions were used: denaturation at 95 °C for 3 min; 35 cycles of amplification at 95 °C for 30 s, 58 °C for 30 s and 72 °C for 30 s; and a final extension step at 72 °C for 5 min.6 The following other antibodies were used in this study: anti-Ki-67 (ab16667), anti-HGF (ab83760), anti-GLUT-1 (ab115730), anti-VEGFA (ab52917) and anti-cleaved caspase-3 (ab13847) were purchased from Abcam ; and anti-PECAM-1 (SAB4502167), rhodamine 123 (R8004) and Hoechst 33342 (14533) were purchased from Sigma Aldrich . Signaling pathway-related antibodies were purchased from Cell Signaling Technology : anti-PIK3CA p85 (4292 s), anti-phospho- PIK3CA p85 , anti-AKT (9272 s), anti-phospho-AKT , anti-Mtor (2983 s), anti-phospho-Mtor , anti-RPS6KB1 (2708 s), anti-phospho-RPS6KB1 , anti-RPS6 (2217 s), anti-phospho-RPS6 , anti-ERK (4695p), anti-phospho-ERK , anti-AMPK (2532 s), anti-phospho-AMPK , anti-LKB1 (3047 s), ani-phospho-LKB1 , anti-p38 MAPK (9212p) and anti-phospho-p38 MAPK . Secondary antibodies included DyLight 800/DyLight 680-conjugated IgG against mouse  or rabbit  antibodies. RIPA lysis buffer  was purchased from Beyotime .Rabbit anti-PDCD5 polyclonal antibodies used here have been described before.Gapdh housekeeping gene. RT-PCR and qRT-PCR assays were performed in triplicate for each sample. Total RNA was prepared from embryos or placentas using TRIzol reagent . cDNA was synthesized using ReverAid First Strand cDNA Synthesis Kit . mRNA expression was analyzed by RT-PCR or qRT-PCR and normalized to the expression of the μg) were resolved by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), transferred to nitrocellulose membrane  and probed by the indicated antibodies. The protein bands were visualized using DyLight 800/DyLight 680-conjugated secondary antibodies, and an infrared fluorescence image was obtained using an Odyssey infrared imaging system .Proteins from the embryos, placentas and MEFs were extracted using RIPA buffer containing phosphatase and protease inhibitor cocktail . The cell lysates (80 μm sections were stained with hematoxylin and eosin (H&E) using standard procedures. A PAS staining kit  was used to stain glycogen-containing cells.The embryos and placentas were fixed in formalin overnight and embedded in paraffin. For histopathological analysis, 4-2O2 to quench endogenous peroxidase activity, and incubated with 5% goat serum. After incubation with the primary antibodies and biotinylated secondary antibody , the color reaction was developed using 3,3′-diaminobenzidine .For immunohistochemical analysis, the embryo and placenta sections were dewaxed and rehydrated in xylol and a graded alcohol series containing decreasing concentrations of ethanol, followed by heat-induced antigen retrieval in citrate buffer. The sections were then treated by 3% Hμm sections were placed on monocrystalline silicon piece, and dewaxed in xylol and ethanol. The sections were desalinated by repeated washing in deionized water and dehydrated in ethanol. The samples were coated with gold spray, and the sections were observed under a scanning electron microscope .The placentas were fixed in formalin overnight and embedded in paraffin. For the scanning electron microscopy, 4-2 incubator at 37 °C. The following studies of MEF cells were used in their second generation.MEF cells were isolated from E10.5 or E11.5 mice embryos. Embryos were harvested, washed with phosphate-buffered saline, minced and trypsinized (0.25% trypsin) for 30 min at 25 °C. The cell suspensions were cultured in 10-cm dishes containing 10 ml of Dulbecco’s modified Eagle’s medium containing 10% fetal bovine serum and 1% penicillin/streptomycin in a CO3 cells/well) and incubated for 12, 36, 60 and 84 h. Then, 10 μl of CCK-8 solution was added to each well, and the cells were further incubated at 37 °C for 4 h. Absorbance was measured at 450 nm, and a reference was recorded at 630 nm with a microplate reader .Cell viability was determined with the CCK-8 reduction assay. MEF cells were seeded in a 96-well plate (3 × 104 cells per well) for 24 h, incubated with EdU at 37 °C for 4 h, fixed with 4% paraformaldehyde, permeabilized with 0.2% Triton X-100 and stained to observe EdU staining. The nuclei were stained by Hoechst 33342 for 5 min. Fluorescence signals were detected under a fluorescence microscope .The EdU incorporation assay was performed using an EdU Imaging Kit . MEF cells were seeded in the wells of a 24-well plate (1 × 105 cells per well) for 12, 24 and 36 h, and collected and stained with Annexin V-FITC and propidium iodide (PI). The cells were then run through a FACSCalibur flow cytometer  to determine the percentage of apoptotic cells.Cell apoptosis was detected using an Annexin V-fluorescein isothiocyanate (FITC) Apoptosis Detection Kit  according to the manufacturer’s instructions. MEFs were first cultured in six-well plates  by a TUNEL assay. Frozen placenta sections from both Pdcd5−/− and Pdcd5+/+ mice at E12.5 were treated and stained according to the manufacturer’s directions.Tissue apoptosis was detected using an 5 per well) and cultured for 24 or 48 h. The cells were then fixed with 70% ethanol at 4 °C overnight, treated with 100 μg/ml RNase A for 30 min at 37 °C, stained using PI in 0.2% Triton X-100, and analyzed with a FACSCalibur flow cytometer (BD Biosciences).MEF cells were seeded in a six-well plate . The total protein was detected by a BCA protein assay kit . Data were presented as the ratio of Hgf protein level to the total protein level.t-test for continuous variables. Statistical significance in this study was set at *P<0.05, **P<0.01 and ***P<0.001. All reported P-values are two-sided. All analyses were performed with GraphPad Prism 5 .Data were presented as the means±S.D. Differences between groups were analyzed using the Student’s