Interaction between hypoxia and coagulation is important given the increased risk of thrombotic diseases in chronically hypoxic patients who reside at sea level and in residents at high altitude. Hypoxia alters the proteome of platelets favouring a prothrombotic phenotype, but studies of activation and consumption of specific coagulation factors in hypoxic humans have yielded conflicting results. We tested blood from 63 healthy lowland volunteers acclimatizing to high altitude  using thromboelastometry and assays of platelet function to examine the effects of hypoxia on haemostasis. Using data from two separate cohorts of patients following identical ascent profiles, we detected a significant delay in clot formation, but increased clot strength by day 7 at 5,200 m. The latter finding may be accounted for by the significant rise in platelet count and fibrinogen concentration that occurred during acclimatization. Platelet function assays revealed evidence of platelet hyper-reactivity, with shortened PFA-100 closure times and increased platelet aggregation in response to adenosine diphosphate. Post-expedition results were consistent with the normalization of coagulation following descent to sea level. These robust findings indicate that hypoxia increases platelet reactivity and, with the exception of the paradoxical delay in thromboelastometry clotting time, suggest a prothrombotic phenotype at altitude. Further work to elucidate the mechanism of platelet activation in hypoxia will be important and could impact upon the management of patients with acute or chronic hypoxic respiratory diseases who are at risk of thrombotic events. Reports of arterial and venous thrombosis at high altitude have fuelled research testing the hypothesis that hypoxia provokes a prothrombotic phenotype.Field studies investigating coagulation at altitude are inherently difficult. Cold, exercise, heterogeneous ascent profiles, and sensitivity of equipment and assays potentially compromise conclusions. We aimed to reduce these problems by conducting near-patient tests in a high-altitude laboratory setting after a controlled non-exertional ascent. In two separate groups of patients, we investigated the effects of hypobaric hypoxia on thromboelastometry and platelet function, testing the hypothesis that hypoxia activates coagulation.Data are included from two expeditions, Apex 2 and Apex 4. Both studies were approved by the Lothian Research Ethics Committee and all participants gave written informed consent. Participants received no remuneration for their role in the research.2) was measured for each patient prior to departure and on each day of investigation using a pulse oximeter . Patients self-recorded symptoms of acute mountain sickness (AMS) using the Lake Louise self-assessment score (LLS)All patients were resident at altitudes less than 600 m and had not been to heights greater than 1,500 m in the 3 months preceding the study. Patients flew to La Paz, Bolivia , and spent 4 or 5 days there before ascending for 90 minutes by road to the Chacaltaya Laboratory .Thromboelastometry was performed on Apex 2 using a ROTEG05  and on Apex 4 using a ROTEM Pactem analyser . Each citrated blood sample was assayed within 60 minutes of venepuncture using activators of the extrinsic (EXTEM: tissue factor) and intrinsic (INTEM: phospholipid and ellagic acid) pathways and results were recorded digitally. FIBTEM  tests were performed on each blood sample on Apex 4. Internal quality control tests were also recorded at regular intervals throughout the sampling period and values fell within the accepted ranges at all altitudes. Each rotational thromboelastometry (ROTEM) test requires 300 µL of citrated whole blood. Tests were run to obtain an A20 clot amplitude at 20 minutes, and results of clotting time (CT) and clot formation time  were recorded.On Apex 2, citrated blood was analysed, within 5 minutes, by a PFA-100 analyser . PFA-100 closure time was recorded using collagen-epinephrine cartridges. On Apex 4, blood was taken into a Hirudin tube  and Multiplate analysis was conducted exactly 20 minutes following venepuncture. Platelet activation with thrombin receptor activating peptide , collagen (3.2 μg/mL) and adenosine diphosphate  stimulation was performed and quantified using the area under the curve of arbitrary aggregation units against time (AUC).Full blood count (FBC) analysis was performed at sea level using a KX21-N  within 24 hours of blood collection in EDTA. FBC was measured in La Paz, Bolivia, using a Micros 60  30 hours after blood collection at 5,200 m. The EDTA tubes had been stored and transported upright at 20°C.Citrated venous blood (10 mL) was centrifuged immediately at 2,500 g for 15 minutes and the supernatant pipetted into a 10-mL propylene centrifugation tube. Plasma was centrifuged again at 2,500 g for 15 minutes . Plasma aliquots of 500 µL were pipetted into 1 mL propylene aliquot tubes, stored vertically, snap frozen to −80°C and transported on dry ice by specialist international courier to a −80°C storage facility in the UK. Plasma fibrinogen, prothrombin time (PT) and activated partial thromboplastin time (aPTT) were measured in a NHS haematology laboratory.t-tests were used to compare differences in parameters between sample days. Comparisons of sea-level results versus each time point at altitude and between time points at altitude were made  andp-value was adjusted by the Bonferroni method. Therefore, for measures recorded on four occasions,p < 0.0083 (0.05/6) was accepted as significant. Relationships between continuous variables were examined by means of individual scatter-plots and where these graphs were suggestive of at least a very weak linear trend, Pearson's correlation coefficients were calculated and R-squared provided as a measure of the strength of the corresponding linear trends.Statistical analysis was performed using GraphPad Prism 6.0. The normality of datasets was assessed using Kolmogorov–Smirnov tests and pairedData are included from 63 patients across two expeditions and comparative demographics are presented inProfound hypoxaemia was observed from day 1 at 5,200 m and persisted for the duration of the sojourn at altitude . Haematr20.4,p < 0.0001) and EXTEM CT  on Apex 2  or versus EXTEM CT  was significantly greater on day 7 at 5,200 m on both expeditions  and INTFIBTEM uses cytochalasin D to inhibit platelet function and assesses fibrin clot strength in the absence of platelet activation. Fibrinogen levels were significantly elevated on day 3 and day 7 at 5,200 m compared with sea level . ConsisMultiplate assays demonstrated no significant changes in platelet aggregation upon stimulation with either TRAP or collagen . AggregHypoxia, whether local or systemic, frequently complicates thromboembolism, but the role it plays in altering haemostasis is poorly understood. Using near-patient tests on healthy volunteers in an extreme hypoxic environment, we have gathered unique data describing altitude-induced alterations in coagulation. Data from two separate expeditions to high altitude revealed an increase in the clotting time at 5,200 m when compared with pre-expedition or post-expedition sea-level values, as measured by thromboelastometry. Although there was a latency in clot formation, we found evidence of an increase in clot strength, indicated by an increase in amplitude of the TEM trace 20 minutes after clot was first detected. Furthermore, after 3 days at altitude, there was an increase in plasma fibrinogen concentration and this was associated with an increase in fibrin-formed clot strength. Finally, using two different measurements of platelet function, we revealed an increase in platelet reactivity at high altitude in response to ADP and collagen-epinephrine stimulation.Rotational thromboelastometry allows a measurement of global haemostatic function in whole blood samples. The technique analyses the dynamics of clot formation and gives information on the interaction of platelets, clotting factors and fibrinogen to generate a graphical depiction of the coagulation process. Unlike specific blood component assays, thromboelastometry examines the complete interaction between plasma constituents revealing the net consequences of abnormalities affecting the formation of the clot. Despite our apparent paradoxical findings of a latency in clot formation but an increase in clot strength, our results are remarkably consistent with previous work performed at altitude. Using a similar method, thromboelastography (TEG), the Caudwell Everest expedition assessed coagulation at 5,300 m in 17 healthy volunteers who ascended to the base camp of Mount Everest over 13 days.The prolongation of CT described here and by othersIn contrast to the results from patients with CCHD,Our finding of increased platelet count at altitude on both expeditions is notable given inconsistent historical results.2+,1receptor activation by ADP. Although this proposed interaction between ADP and calpains requires further investigation, the alteration of the hypoxic platelet proteome adds credibility to our observed changes in platelet function at altitude and suggests a possible mechanism for the rise in fibrinogen concentration at altitude.To explore how hypoxia alters platelet reactivity, we performed further tests of platelet activation on Apex 4, screening different platelet agonists using Multiplate impedance aggregometry assays. These revealed a specific increase in platelet aggregation in response to ADP by day 7 at 5,200 m. Consistent with this finding, platelets isolated from rats exposed to hypoxia for 6 hours also display increased aggregation in response to ADP, associated with increased ATP release and increased surface expression of platelet activation markers.Multiplate results may be affected by platelet count and haematocrit.This work has several limitations. First, while we provide evidence of hypercoagulability in the form of increased TEM clot strength and platelet activation, how these parameters might relate to risk of subsequent thrombotic events is not clear. Studies using TEG have indicated a possible relationship between clot strength and thrombosis risk in the context of surgery,In conclusion, we demonstrate evidence of increased platelet reactivity and increased clot strength in whole blood assays in healthy volunteers exposed to altitude hypoxia. The increase in clot strength may be explained by rises in platelet count and fibrinogen while the recent discovery of hypoxia-induced changes in the platelet proteome


Lake Tanganyika is the oldest and phenotypically most diverse of the three East African cichlid fish adaptive radiations. It is also the cradle for the younger parallel haplochromine cichlid radiations in Lakes Malawi and Victoria. Despite its evolutionary significance, the relationships among the main Lake Tanganyika lineages remained unresolved, as did the general timescale of cichlid evolution. Here, we disentangle the deep phylogenetic structure of the Lake Tanganyika radiation using anchored phylogenomics and uncover hybridization at its base, as well as early in the haplochromine radiation. This suggests that hybridization might have facilitated these speciation bursts. Time-calibrated trees support that the radiation of Tanganyika cichlids coincided with lake formation and that Gondwanan vicariance concurred with the earliest splits in the cichlid family tree. Genes linked to key innovations show signals of introgression or positive selection following colonization of lake habitats and species’ dietary adaptations are revealed as major drivers of colour vision evolution. These findings shed light onto the processes shaping the evolution of adaptive radiations. Lake Tanganyika’s cichlid radiation is the main source of East African cichlid diversity. Irisarri et al. resolve its phylogenetic backbone using anchored phylogenomics and identify trans-lineage hybridization prior to major speciation bursts and adaptive loci underlying ecological innovations. Several lineages have diversified through this process, including Hawaiian silverswords2, Darwin’s finches3, and East African cichlids4. Investigating adaptive radiations is crucial for better understanding the factors that drive speciation5. However, disentangling the geographical setting, ecology, genetic causes, commonalities and peculiarities in different adaptive radiations has proven difficult7. Sudden abiotic changes such as new volcanic islands or lakes can provide empty niches that facilitate diversification. Speciation can also be promoted by key traits that allow the exploitation of new niches, or gene flow between divergent lineages that produce transgressive phenotypes showing faster responses to divergent selection8.Rapid speciation, when coupled with ecological opportunity, can give rise to a multitude of species within short time periods, a process known as adaptive radiation6. East African Great Lakes harbor ~90% of all the described cichlid species so far9, which are the result of a successful evolution shaped by vicariance-driven and opportunity-driven speciation10. Understanding the evolutionary history of cichlids and the factors contributing to their diversification have been major quests for an ever-growing community of evolutionary biologists. However, despite decades of research, some crucial evolutionary relationships remain unresolved and also the timing of divergences among the major lineages is still controversial. Thus, establishing a robust time-calibrated phylogeny is a first requirement for tracing the patterns of diversification (in time and space) and to better understanding the factors that shaped their adaptive radiation. In addition, the role and relative importance of hybridization, ecology, or life history in shaping cichlid radiations remains poorly understood.Cichlid fishes (Cichlidae), with >1700 described species, are a model system for the study of adaptive radiation, ecomorphological diversification, and speciation4 and molecules11. Fast diversification prevents the accumulation of shared derived changes and increases the retention of incomplete lineage sorting (ILS) in the genomes, whereas ecomorphological convergence and hybridization further confound phylogenetic inference methods. Despite the many studies that have contributed to clarifying the phylogeny of cichlids , considerable disagreements still exist regarding key relationships, partly due to the few and lowly informative markers available and the scarcity of fossils, which are also problematic due to frequent parallel evolution of similar ecomorphologies14. One of the main open questions is the deep phylogenetic structure of the Lake Tanganyika radiation, the oldest among East African Great Lakes. Lake Tanganyika hosts the ecologically, morphologically, and genetically most diverse species assemblage12. It also holds the key to understanding the origin of haplochromine cichlids, the most species-rich lineage that seeded the radiations in Lakes Malawi and Victoria and also re-colonized Lake Tanganyika15. While the monophyly of cichlid tribes is well established, their interrelationships remain hotly debated18. Several studies have investigated cichlid macroevolution19, but given current phylogenetic uncertainties, employed trees might not reflect the ‘true’ species history16. A robust phylogenetic hypothesis for cichlids will not only resolve existing controversies but it will also allow to understand the origin and evolution of key innovations, life history changes, and further clarify the patterns of convergence and parallel evolution that characterize cichlid radiations.Phylogenetic inference of adaptively radiated lineages has proven difficult both with morphology20, (ii) vision adaptation to different water turbidity21, and (iii) body coloration associated with sexual selection and reproductive isolation22. The relative importance of these innovations is poorly understood, given that most previous studies have focused on the effect of single factors on these traits, or analysed traits in isolation. The lack of studies simultaneously modelling different ecological and life-history factors hampers the identification of hierarchical relationships among them, as well as the identification of lineage-specific shifts6.The rapid diversification of East African cichlids has been attributed to key innovations including (i) functional decoupling of oral and pharyngeal jaws facilitating exploitation of diverse trophic sources8. Hybridization has been demonstrated at the onset of the Lake Malawi and Victoria cichlid flocks24 and suggested to fuel these radiations. Some studies proposed a similar scenario for Lake Tanganyika25, but so far no study has demonstrated the presence of hybridization at the base of this radiation, an imperative for invoking its role in boosting this diversification.In addition to key innovations, hybridization has also been proposed as a major factor shaping East African cichlid radiations26. However, molecular dating analyses have suggested markedly different ages from ca. 51 to 16 Ma31. Controversy persists also regarding the age estimates for the deepest divergences in the cichlid family tree. These were initially assumed to follow Gondwanan vicariance35. Recent molecular dating recovered significantly younger ages for these splits that contradict the vicariance scenario and therefore hypothesized the long-distance trans-oceanic dispersal of cichlids30. In contrast, earlier molecular datings using vicariant calibrations estimated much older divergences in African cichlids that are difficult to reconcile with the age and geological history of the African Great Lakes and the biology of their endemic species12. The difficulty in estimating consistent divergences simultaneously at deeper and shallower regions of the tree originates in part from the scarcity of reliable fossils for calibration (the oldest known is only 45 Myr old36) and the lack of a reliable molecular clock rate estimate for cichlids.The integration of molecular dating with geological events can identify relevant ecological factors facilitating radiations and provide an independent control for hybridization hypotheses. The Lake Tanganyika species flock is assumed to have originated in step with the lake formation and maturation 12–9 Ma37. Phylogenetic networks and Patterson’s D-statistics are used to examine hybridization signals among cichlid tribes. We find evidence for hybridizations at the bases of the Lake Tanganyika flock and the tribe Haplochromini that seeded the radiations in Lakes Malawi and Victoria. These findings support the role of hybridization in boosting all major cichlid radiations in East Africa. Using the new phylogenetic framework, we analyse the molecular evolution of genes associated with key cichlid innovations. We find positive selection associated with the colonization of Lake Tanganyika and identify diet as one of the most important ecological factors.Here, we attempt to reconstruct a robust cichlid family tree focusing on the Lake Tanganyika flock, which is time-calibrated employing a newly described East African cichlid fossil38 for these nodes, in contrast to the relatively high values (>80%) for the monophyly of most tribes , representing all major cichlid lineages with emphasis on the Lake Tanganyika radiation , Ptychochrominae (Madagascar), and Neotropical (Cichlasomatini + Heroini) and African cichlids as sister clades31. As in the most recent and taxonomically comprehensive study of African cichlids41, we recovered early-branching of Heterochromidini and Tylochromini but found alternative relationships among most other tribes  within the Lake Tanganyika flock, as sister to all other tribes to the exclusion of Bathybathini + Boulengerochromini . Within the Haplochromini, the riverine genera Astatoreochromis and Astatotilapia branch off prior to the two major clades representing the adaptive radiations in Lake Victoria (>500 spp.) and Lake Malawi (>800 spp.). Our phylogeny supports the evolution of Tanganyika-endemic Tropheini from riverine ancestors that re-colonized Lake Tanganyika and diversified in parallel with the already existing radiation15.The coalescent species tree recovered Steatocranini , which provided new niches and ecological opportunities required for adaptive radiation10. Likewise, it is not possible to exclude an alternative scenario of an earlier origin of some major lineages. However, the fact that all Tanganyika-endemic tribes, except the early-branching Lamprologini, occupy distinct gross fundamental niches 12 suggests that the initial radiation likely occurred within the confines of the emerging lake system. Instead, if much of the initial divergence had happened in different rivers systems prior to the lake formation  one could expect each lineage to radiate into an array of species occupying broader niches, which contradicts the pattern observed today. Importantly, members from cichlid tribes of the Lake Tanganyika flock are not present in any nearby river system, with only three exceptions: (i) Orthochromini, found exclusively in the Malagarazi drainage and nearby rivers that drain into Lake Tanganyika; (ii) the Haplochromini that originated in Tanganyika, colonized large parts of Africa, and later re-colonized Tanganyika too (Tropheini); and (iii) the Lamprologini that contain two lineages that dispersed from Lake Tanganyika into the Congo and Malagarazi river systems47. Again, an origin of Lake Tanganyika species flock much earlier than the lake formation would need to explain the extinction of many riverine members of Tanganyikan tribes. In fact, other closely related cichlid lineages, some of which have also colonized Lake Tanganyika41, continue to occur in nearby water bodies.We performed independent timetree analyses using 10 calibration schemes based on fossil or biogeography (Supplementary Table 36). The estimated divergence times for the deepest splits in the tree, namely those between Etroplinae-Ptychochrominae at 175.8–121.0 Ma and between African and Neotropical cichlids at 143.9–98.9 Ma, are consistent overall with a vicariance scenario of Gondwanan fragmentation35 but contradict other proposed scenarios31. The Gondwanan vicariance is robustly supported by all fossil-based calibration schemes, with the exception of schemes C03 and C08, which produce seemingly biased older estimates and larger confidence intervals  and thus it should be applied to calibrate this event. The use of maximum bounds in schemes C05 and C10 diminishes the detrimental effect of misplacing †Mahengechromis (Supplementary Data 50). In addition, the estimated divergence of the Tanganyika species flock agrees with the radiation occurring within the confines of the incipient lake.Our analyses date the origin of the cichlid family to between the Jurassic and Early Cretaceous, depending on the assumed calibration scheme, clearly predating the oldest known cichlid fossil  and dominated by mitochondrial markers (~66%) and missing data (~40%). Expanding our anchored loci dataset to include other non-cichlid taxa, which is straightforward for anchored loci, would allow the incorporation of additional informative fossils in the outgroup as in Matschiner et al.31 and help clarify current disagreements on cichlid diversification. Further insight into the apparent contradiction between existing cichlid timetrees would be possible by conducting an in-depth study comparing different dating software/methodologies and molecular datasets with comparable assumptions and models.The recent study proposing long-distance trans-oceanic dispersal of cichlids inferred divergences that are seemingly too old (~50 Ma) for the Tanganyika species flock51, and propose hypotheses of inter-tribal hybridization that are later tested using Patterson’s D statistic (or ABBA/BABA test)52. Galled networks show substantial topological discordance among loci , the ancestor of Bathybathini + Boulengerochromini, and the remaining lineages ('modern' tribes) of the Lake Tanganyika flock, and (ii) a second hybridization between Benthochromini and Perissodini.We investigated our dataset for signals of hybridization/introgression by analysing high-frequency discordances in galled networksD tests were performed on all possible permutations of four individuals belonging to each of the three test groups and gene flow interpreted from distributions of D-statistics . This hybridization signal was consistent whether Bathybatini or Boulengerochromini were used as P2 and regardless of the used outgroup taxa, whereas it clearly disappeared when Steatocranini (P3) was replaced by other close non-Tanganyikan lineages   and weaker for Lamprologini  and the opsin sws1, had strong introgression signals . Together, these lines of evidence suggest differential introgression of genes at the origin of the adaptive radiation in Lake Tanganyika. Previous studies have demonstrated several instances of interspecific hybridization among twigs rather than deeper branches of Lake Tanganyika cichlids, sometimes suggested by cytonuclear discordance54 but no evidence existed until now for the hybridization between the oldest major lineages (tribes) at the base of the Lake Tanganyika radiation. Intriguingly, comparable hybridization scenarios with riverine lineages have been proposed to boost cichlid radiations in Lake Malawi, Lake Victoria, and the Cameroonian crater lakes55.Based on the observed patterns of gene flow, we hypothesize that the riverine Steatocranini contributed genetic material to the Lake Tanganyika radiation, which is in line with a hybrid swarm scenario. The hybrid swarm theory was proposed as a mechanism that can instantaneously generate novel genetic combinations from standing variation, thus facilitating subsequent rapid radiation25 that employed a novel approach based on age distribution of gene trees. Meyer et al. proposed introgression of Cyphotilapiini into (a) the common ancestor of the Lake Tanganyika haplochromines  and (b) Pseudocrenilabrus. Our analyses found that not only Tropheini, but also Astatoreochromis and Lake Malawi and Victoria haplochromines showed signs of introgression, but Pseudocrenilabrus did not .In addition to testing the two newly proposed hybridization events, we used our dataset to revisit the hybridization events proposed by Meyer et al.25 proposed additional introgression events involving Boulengerochromini (or the common ancestor of Boulengerochromini + Bathybatini) and either (i) the H-lineage or (ii) the ancestor of Perissodini + Cyprichromini. Our results show conflicting gene flow patterns whenever Boulengerochromini or Bathybatini are tested  in relation to gene function, phylogeny (lineage effects), ecology, and life-history traits. General measurements of dN/dS  showed that the three gene categories evolved under different strengths of purifying selection: strongest for tooth and bone development genes (ωM0 = 0.014–0.321), weakest in colour vision genes (ωM0 = 0.223–0.469), and intermediate in coloration genes (ωM0 = 0.105–0.463). All other anchored loci not considered in the previous three categories had a wide range of coefficients of selection (mean ωM0 = 0.166 ± 0.14)  and these had functions related to reproduction, craniofacial growth, or to digestive and immune systems , coloration, and colour vision. The link between traits and genes is based on previous investigations including forward genetic studies on model organisms, gene ontology annotations or differential gene expression patterns in cichlids (Supplementary Table 14) Fig. . The dif57, χ2-test with 2 df, after Benjamini-Hochberg correction for multiple testing)  showed signs of positive selection. The differential regulation of these genes in the lower pharyngeal jaw across developmental stages and in experimental studies of plasticity in response to diet59 suggests that they play a role in determining size and shape of the lower pharyngeal jaw, a key innovation tightly associated with food source60. Four out of eleven coloration genes previously associated with melanocyte survival, differentiation, and migration  analyses found that an alternative scenario of rate changes at the origin of the Lake Tanganyika flock and in the Haplochromini was more likely . The CmC models for kitla were not found to statistically deviate from neutral evolution. Even though the M2a/M1a site test was not significant for hag . Premature stop codons were also prevalent in Bathybatini for dlc and hag, where some naturally occurring species have disrupted barred patterns resembling zebrafish knockout mutants of these genes63.Adaptive radiations, which display vast phenotypic diversity in the absence of pronounced molecular differences, might be seen as a laboratory of “natural mutants” that can help identify functional variants of genes, much like mutagenesis screens in model organisms21 provides a solid basis for the interpretation of our results. Sites at chromophore-binding pockets are highly variable in all cone-opsin genes  was analysed in further detail. The genotype–phenotype association in cone opsins is straightforward, the phenotypic consequences of amino acid replacements are well understood and extensive work on cichlid opsinsnes Fig.  and oftenes Fig. . This su64. For the seventh gene lws, a model showing deceleration of positive selection in the Lake Tanganyika flock followed by acceleration in Haplochromini fitted the data best. According to AIC, CmC considering divergent rates associated with ecological traits explained sequence variation better than neutral models in five out of seven opsins  show the fastest rates in the green-sensitive opsin rh2a-α. CmC allowing different rates in shallow-dwelling versus deep-dwelling cichlids fit data best for lws (absorption λmax ~565 nm) and second best for sws1 (absorption λmax ~375 nm), in both cases shallow-dwelling cichlids having faster rates of positive selection. In contrast, deep-water dwellers had higher rates for sws2b (absorption λmax ~425 nm). This makes sense given that UV and red light are diminished from the light spectrum in deep water66. This evidence further agrees with the pseudogenization of sws1 in the deep-water tribe Bathybatini . Despite notable differences in AIC with other models, CmC partitioning for depth was not significant for lws after Benjamini-Hochberg correction. These results, together with previous studies that found divergent evolution in the dim light opsin rh1 between deep and shallow water Tanganyika cichlids67, support depth as an important driver in the evolution of colour-sensitive opsins. CmC models accounting for differences between species with and without sex-related colour dimorphism and between substrate- versus mouth-breeding cichlids fit data significantly better than the null model  only for short wavelength sensitive opsin genes (absorption λmax < 470 nm). In all cases, sexually monomorphic and substrate-breeding species had faster rates than sexually dimorphic or mouth-brooding cichlids . Taxon sampling emphasized the Lake Tanganyika radiation by including all tribes except Trematocarini . Detailed information of taxon sampling is available in Supplementary Table www.anchoredphylogeny.com) using the anchored hybrid enrichment methodology68. Briefly, DNA was extracted from fin clips using the ZR-96 Genomic DNA Tissue MiniPrep  and DNA extracts sheared to 150–300 bp using a Covaris E220 Focused-ultrasonicator. Indexed libraries were prepared on a Beckman–Coulter Biomek FXp liquid-handling robot following Meyer et al.69 with an additional size-selection step after blunt-end repair using SPRIselect beads . Indexed samples were pooled at equal quantities (12–16 samples per pool) and enrichments were performed on each multi-sample pool using an Agilent Custom SureSelect kit . After enrichment, the pools were grouped in equal quantities for sequencing into four paired-end 150 bp Illumina HiSeq2000 lanes. Sequencing was performed in the Translational Science Laboratory, College of Medicine, Florida State University. Paired overlapping reads from fragments <280 bp were merged, sequencing errors corrected, and adapter sequences trimmed off. Reads were assembled using a quasi-de novo approach in an in-house pipeline70. Orthologous sets were identified from the assembled consensus sequences using sequence similarity and clustering in a neighbour-joining-like process70.Phylogenomic data were generated at the Center for Anchored Phylogenetics  with functions related to colour vision, coloration, and bone and tooth formation  using the annotations from the O. niloticus genome (Orenil1.0).Targeted loci correspond to the anchored loci for teleostsO. niloticus72, Astotilapia burtoni72, M. zebra72, Neolamprologus brichardi72, P. nyererei72, Amphilophus citrinellus , Andinoacara coeruleopunctatus , Petrochromis trewavasae and Tropheus moorii . Orthologs were identified by reciprocal BLAST searches and the hit coordinates were extended by 500 bp upstream and downstream to capture less conserved regions flanking exons. Individual loci were aligned with MAFFT v.724573 and positions with >80% gaps were removed. Eight out of the 541 initially assembled loci were excluded because of suspected paralogy: one locus (KCNJ13) produced BLAST hits in two regions of the O. niloticus genome and has been identified as duplicated72 and the remaining seven loci had a high proportion (>3%) of ambiguous base calls suggesting that consensus sequences might have been assembled from reads originated from several paralogs. Pairwise genetic distances and manual visualization of alignments were used to ensure correct orthology and remove any non-homologous sequence stretch in the added genomes.In addition to sampled species, homologous sequences from nine available cichlid genomes were added to the alignments of anchored loci: 74 using independent GTR + Γ models per gene and branch support assessed by 500 pseudoreplicates of non-parametric bootstrapping. A coalescent tree was estimated with ASTRAL II75 with default parameters using maximum likelihood locus trees estimated with RAxML. Branch support for the coalescent tree was assessed by local posterior probabilities and 100 replicates of multi-locus bootstrapping with site resampling. We assessed the degree of conflict at internal branches using internode certainty as implemented in RAxML v.8.1.20 after applying a probabilistic correction for partial gene trees38. A gene jackknifing analysis76 was performed to estimate the proportion of final-tree bipartitions recovered by coalescence vs. concatenation as a function of dataset size. 100 jackknife replicates were generated each for sets of 10, 100, 200, 300, 400 and 500 randomly selected loci and separately analysed with ASTRAL and RAxML.A concatenated maximum likelihood tree was constructed with RAxML v.7.3.177 as implemented in MEGA-CC v.7.0.2078. We used the GTR + Γ with five gamma categories , assumed the “local clocks” model, set the branch swap filter to “None” and fixed the topology to that of maximum likelihood tree  that correspond to the percentage of locus trees that support the network edges. We used the galled network with reticulated edges supported by ≥20% locus trees  following Durand et al.83. In addition, we revisited hybridization hypotheses proposed by Meyer et al.25. For each hypothesis, we selected three relevant lineages and one outgroup conforming a four-taxon asymmetric tree required by D tests, following the maximum likelihood topology . To measure the significance of these tests, Z-scores and p-values were calculated from 100 bootstrap replicates of the tests. P-values were adjusted for multiple testing using the Benjamini-Hochberg method. For the main hybridization hypothesis  and summarized with REVIGO84. To avoid possible biases in base calling due to heterozygosity, all D tests were performed on bioinformatically-phased haplotypes85, randomly choosing one allele per individual and locus. To rule out biases due to outgroup choice in D tests, these were repeated with different outgroups. The summary of all D tests is available in Supplementary Table The signal for hybridization was explored using galled networks, constructed as follows: SplitsTree4sis Fig.  per-geneO. niloticus genome as reference. Any sequence containing premature stop codons within the ORF was excluded. Gene alignments for rh2a-α and rh2a-ß were derived from bioinformatically-phased alleles85 because the default assembly pipeline could not disentangle these close paralogs. We analysed dN/dS using random site models in PAML v.4.857. Likelihood ratio tests (LRT) were used to calculate significance of random site models testing for dN/dS variation across sites (M3/M0) and positive selection (M2a/M1a) and in the latter case, sites under positive selection were identified using the Bayes’ Empirical Bayes method in PAML and compared results to those obtained by SLAC, MEME, FUBAR, and FEL methods in HYPHY86. Using Clade model C (CmC) in PAML, we tested lineage effects and ecological and life history factors as drivers of molecular evolution, similarly to previous work in Neotropical cichlids’ rh1 gene64. CmC allows rates of positively selected sites to vary among a priori defined groups of species (background vs. foreground branches). Significance of CmC was tested against a null model of neutral evolution (M2a_rel87) by LRT and the relative fit of the different CmC models assuming different taxa partitions were compared by AIC. The following lineage-specific partitions were used: (i) Tanganyika species flocks vs. all other cichlids, (ii) Haplochromini vs. all other cichlids, and (iii) Tanganyika-Haplochromini, similar to (i) but assuming independent rates for Haplochromini , and field observations (S. Koblmüller). To minimize the number of transitions and avoid stochastic errors of single gene trees, ancestral reconstructions and dN/dS calculations assumed the maximum likelihood topology .Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2


Here we perform unbiased de novo annotation of transcripts expressed during the human humoral immune response to find 30% of the human genome transcribed during this process, yet 58% of these transcripts manifest striking differential expression, indicating an lncRNA phylogenetic relationship among cell types that is more robust than that of coding genes. We provide an atlas of lncRNAs in naive and GC B-cells that indicates their partition into ten functionally categories based on chromatin features, DNase hypersensitivity and transcription factor localization, defining lncRNAs classes such as enhancer-RNAs (eRNA), bivalent-lncRNAs, and CTCF-associated, among others. Specifically, eRNAs are transcribed in 8.6% of regular enhancers and 36.5% of super enhancers, and are associated with coding genes that participate in critical immune regulatory pathways, while plasma cells have uniquely high levels of circular-RNAs accounted for by and reflecting the combinatorial clonal state of the Immunoglobulin loci. Long non-coding RNAs (lncRNA) constitute a large fraction of human transcriptome, and are reported, individually, for context-specific regulatory functions. Here the authors expand our understanding by providing a systemic, unbiased annotation of lncRNA to establish an atlas of lncRNA landscape during the induction of human humoral immune responses. Mechanistic studies indicate that lncRNAs are key regulators of biological processes including cell differentiation, development, and the immune system6. With the advent of new RNA-sequencing (RNA-seq) strategies, the annotation of human lncRNAs has remarkably expanded in the past few years8. However, the complete landscape of lncRNAs in the humoral immune response and their functional genomic characterization and links to chromatin features remains largely unexplored.The human transcriptome is extraordinarily complex, consisting of tens of thousands of long non-coding RNAs (lncRNAs) that far exceed the number of messenger RNAs (mRNAs) coding for proteins. LncRNAs are a highly heterogeneous group of functional molecules that have in common being longer than 200 nucleotides in length with little or no coding potential. The overwhelming abundance of lncRNAs in the human transcriptome was previously considered to be a consequence of transcriptional noise. However, recent studies indicate that many lncRNAs exhibit significant tissue- and cell-type specificity10. These cells eventually migrate to the light zone and become centrocytes (CCs) that undergo clonal selection and terminal differentiation to memory B cells (MEM) or plasma cells (PCs). PCs exiting the lymph nodes then migrate to the bone marrow to become long-lived PCs, specialized in the production and secretion of immunoglobulins (Igs)11. Although there is extensive experimental data regarding the molecular and cellular signals that control the proliferation and differentiation of B cells13, information on global transcription during the humoral immune response is limited.Humoral immunity is a multilayered process that involves activation and maturation of B cells. Germinal centers (GCs) are the focal point of this process. GCs form upon activation by the T cell-dependent antigen response, when naive B (NB) cells migrate to the interior of lymphoid follicles. The GC reaction is highly dynamic and features repeated cycling of B cells from the B cell-rich dark zone to the more heterogeneous light zone. Dark zone GC B cells are called centroblasts (CBs), which undergo repeated rounds of rapid proliferation and somatic hypermutation14 analyzed the expression of lncRNAs in 11 discrete human B cell subsets using exon array-based technology. In this study, they detected 1183 lncRNAs associated with seven coding genes sub-networks related to distinct stage of B cell development, including terminal differentiation. In a subsequent study, Brazão et al.15 reported a catalog of 4516 lncRNAs expressed across 11 mouse B cell populations, including stages of terminal B cell differentiation using the stranded polyA+ RNA-seq strategy. They identified 1878 novel intergenic lncRNAs, some of which were related to histone modification marks associated with enhancer or promoter regions. These studies point to importance of fully characterizing the full transcriptome of B cells as they undergo the GC reaction and subsequent terminal differentiation. When taken together with the rapidly shifting chromatin landscape of B cells undergoing Ig affinity maturation, the lncRNA transcriptome could provide a more complete understanding of basic molecular immune mechanisms and the B cell context-specific transcriptome. Therefore, herein we set out to perform a full de novo annotation of the B cell non-coding transcription and its functional relationship with the epigenome and coding transcriptome. Our studies provide evidence that lncRNAs are specifically expressed in each stage of the humoral immune response and are transcribed from specific enhancer regions related to key stage -specific phenotype-driving genes.Recently, Petri et al.To characterize the lncRNA transcriptome of B cells reflecting the humoral immune response, we obtained tonsils and bone marrow of healthy human donors and used multiparameter fluorescence-activated cell sorting to isolate the distinct B cell populations. Based on the expression level of nine different surface antigens, we isolated NB cells, CBs, CCs, MEM cells, tonsillar plasma cells (TPCs—these are plasmablasts), and bone marrow plasma cells (BMPCs)  value of expression >1 in at least three of the analyzed samples and an overlap <75% of their length with repetitive elements. We used PhyloCSF to predict the coding potential of the newly detected transcripts, where a coding transcript would have a score >0 for the majority of its codons17  comparing genome transcription fraction by cell type). Thus, 7–8% of the genome is transcribed in NB cells, CBs, CCs, and MEM cells and 4–5% in plasma cells . Although plasma cells had higher ratio of transcription from the Ig loci  revealed robust segregation of B cell subsets Fig. . The firTo measure the magnitude of lncRNAs transcriptome changes during the humoral immune response, we performed differential gene expression analyses between the sequential stages of the humoral response (see Methods section). Each of these transitions featured differential expression of non-coding RNAs. We observed 3719 lncRNAs (novel + annotated) differentially expressed between NB cells and CBs, 508 between CBs and CCs, 458 between CCs and MEM, 2776 between CCs and TPCs, and 1397 between TPCs and BMPCs Fig. . Thus, d18 was significantly higher than the specificity of coding genes   Fig. . Betweenst) Fig. . Thus, lk-means clustering on the normalized expression of the transcript across the six different cell types . Performing enrichment analysis for each cluster revealed that cell-stage-specific lncRNAs tend to be near coding genes that are also significantly differentially expressed and functionally relevant to each particular cell type Fig. . For exap < 2.2 × 10−16, Wilcoxon's rank-sum test), to coding genes near non-differentially expressed lncRNAs or coding genes that do not have any expressed lncRNAs in their upstream/regulatory regions  profiles for H3K4me1, H3K4me2, H3K4me3, and H3K27Ac in primary human NB and GC cells. Of note, whereas lncRNAs that were upregulated in GC vs. NB cells featured mainly gain of H3K4me1 and H3K4me2 in GCs. In contrast, lncRNAs regulated in GCs were generally associated with more impressive loss of H3K27Ac and to some extent H3K4me3 . The multi-dimensional data for lncRNAs were embedded in two dimensions by t-distributed stochastic neighbor embedding (t-SNE) and clustered using SamSPECTRAL for spectral clustering23. This analysis indicated that lncRNAs distribute into 10 distinct clusters in GC B cells based on their chromatin regulatory state  compared to enhancer and super-enhancer regions without eRNA transcription  difference between genes that are <250 kb away from eRNAs and non-enhancer lncRNAs). Similarly, the protein-coding genes closer to enhancer regions with eRNA transcription showed higher expression than those coding genes closer to enhancer regions without eRNAs . In addition, super-enhancer regions with eRNA transcription were associated with critical genes linked to B cell receptor signaling, B cell activation, and humoral immune response , we observed this negative correlation between the expression of circRNAs and genes related with cell proliferation like MKi67 and PCNA, but not in the case of NB cells  in our B cell subsets using the CIRI algorithmnse Fig. . The hignse Fig. . Recent lls Fig. . We furtNPL Fig. . These rNotably, the circRNAs with by far the highest levels of expression in plasma cells were derived from Ig genes. Indeed the higher circRNA observed in plasma cells is fully accounted for by Ig transcripts Fig. . The cirNext, we cloned the amplification products Fig.  of circR2. As in other human tissues4, the expression of lncRNAs was highly cell type specific even within subsets of fully mature B cells, and marking the identity of cell subsets that undergo functional transitions and terminal differentiation of B cell lineage during the humoral immune response with more precision than the coding genes. Furthermore, lncRNAs expressed specifically in each B cell subset were transcribed from genomic regions located close to protein-coding genes that are enriched and relevant for the function of each B cell subpopulations, suggesting critical cis functionality of lncRNAs in the regulation of protein-coding genes during the humoral immune response.In this study, we provide the first comprehensive atlas of lncRNA and circRNA expression during the human humoral immune response. We identified 11,495 previously non-annotated lncRNAs featuring massive changes of their expression patterns during the human humoral immune response. These lncRNAs significantly expand the number of formerly defined and expressed lncRNAs in human B cells. Contrary to the long-held view that <2% of the human genome is transcribed, the findings of our study indicate that the lncRNAs in each of the B cell subpopulations are transcribed from a higher proportion of the human genome compared to the protein-coding genes30. These characteristics allowed us to classify lncRNAs expressed during the human humoral immune response in six different novel functional groups: eRNAs, promoter lncRNAs, bivalent lncRNAs, repressive lncRNAs, CTCF lncRNAs, and other lncRNAs. Although eRNAs exhibited the expression in B cell subpopulations, especially those that were transcribed from super-enhancer regions, these eRNAs were detected from a relatively low percentage of active enhancer regions. Only 8.6% of the active enhancer regions led to eRNA expression in our study, increasing this percentage to 36.5% in the case of super-enhancer regions. It is possible that this low detection of eRNAs in enhancer regions could be a consequence of the RNA-seq strategy used in our study. Although this hypothesis is not completely ruled out, in our study we detected very consistent differences in the chromatin organization structure between the enhancer with transcription of clear eRNA and enhancer without transcription of eRNA, suggesting that eRNAs are transcribed from certain enhancer regions active in the genome of each cell. It is noteworthy that those enhancer or super-enhancer regions with an eRNA transcription featured higher enrichment for activating histone modifications and 3D contacts (more DNAse and HiC contacts) than enhancer regions without eRNA transcription. This suggests that these enhancer regions need more chromatin accessibility and interactivity and eRNAs transcription to fulfill their regulatory functions. Additionally, the enhancer or super-enhancer regions with eRNA transcription were associated with protein-coding genes that play an essential role in B cell differentiation, such as BCL6 in the case of GC cells. Based on these observations, our studies suggest that eRNAs are key components of the chromatin regulatory machinery essential for the transcriptional control of cell key context-specific protein-coding genes. Perhaps, these eRNAs are important for contributing to the bridging or looping between regulatory enhancer regions of the genome32 that are crucial to establish the GC phenotype during the humoral immune response.Our studies showed that the expression of lncRNAs in B cell subpopulations strongly correlated with chromatin features such as histone modifications, chromatin architecture, and transcription factors, similar to previously reported studies33. In this sense, our results suggest that, like the coding genes regulated by CTCF, those lncRNA enriched by CTCF in GC cells could play a relevant role in the regulation of essential genes or pathways implicated directly in the initiation and proliferation reaction of GC cells. In the opposite way, we also identified a novel functional group of bivalent lncRNAs, enriched by H3K4me3 and H3K27me3. EZH2, H3K27 methyltransferase, mediates the GC proliferation and somatic hypermutation through the formation of bivalent chromatin domains in critical coding gene promoters, leading to a transient silencing of B cell differentiation and cell cycle checkpoint genes13. All these results globally indicate that there are different functional groups of lncRNAs that would be involved in the initiation, activation, regulation of essential genes, and routes for the correct human humoral immune response.Another interesting group of novel functional lncRNAs defined in our study were those enriched by CTCF in GC cells. Recently, it has been shown that CTCF orchestrates the GC transcriptome and that it plays a very important role in the initiation and maintenance of the GC reaction29, we found a negative correlation between the expression of the circRNAs and the expression of RNA-binding proteins ADAR1, DHX9, and HNRNPL. Since depletion of these genes was previously shown to increase the expression of specific circRNAs29, it raises the possibility that ADAR1, DHX9, and HNRNPL might also be an important regulator of circRNAs' biogenesis during terminal B cell differentiation. Interestingly, our studies demonstrated that the explosive and cell-specific expression of circRNAs in human plasma cells predominantly occurred from the Ig genes, which are the Achilles heel of the plasma cells that serve as cellular factories for Ig synthesis. In the case of plasma cells obtained from healthy donors, we detected distinct lengths of the junction region of Ig-circRNAs. However, we found a single predominant sequence from the junction region of circRNA derived from Ig locus in monoclonal gammopathy like MM. These results have allowed us to hypothesize that the tight expression of the circRNAs derived from the Ig locus could occur, as described in the case of circRNAs derived from chromosomal translocations34, as a consequence of the massive and exquisitely controlled rearrangement of the Ig that occurs during the humoral immune response culminating in the plasma cell. Therefore, the Ig locus leads to a high expression of both linear mRNAs as circular non-coding RNAs in human plasma cells. This raises the possibility that Ig-derived circRNAs may in some way play an important role in the identity and function of plasma cells. CircRNAs have been previously shown to be transcribed from key genes with high expression, participating in the regulation of the expression of its host gene36. In the case of the Ig locus, the expression of the circRNAs may represent a novel regulatory mechanism for the Ig locus during the humoral immune response.We also identified 1356 novel putative circRNAs expressed during the humoral immune response, showing the highest mean expression values in human plasma cells (TPCs and BMPCs). As in the case of neuronal differentiation, the expression of circRNAs was found to increase during terminal B cell differentiation. However, we believe that it is unlikely that the high expression of the circRNAs can be attributed solely to a process of accumulation as consequence of a low rate of cell proliferation. As reported previouslyTaken together, our studies mapping the full non-coding transcriptome during the humoral immune response show these to be tightly linked to the various transitions that B cells undergo upon immune activation and suggest that lncRNAs contribute to the regulation of essential genes during this process. Although the exact function and implication of each of the lncRNAs detected in B cell subpopulations is unknown, our studies provide the basis for future studies to explore the function and contribution of lncRNAs during the human humoral immune response, especially in two of the essential steps of terminal B cell differentiation: the B cell activation when the NB cells enter the GC and the final establishment of long-lived plasma cells. In this way, our atlas of long non-coding RNAs could provide valuable insights on the role that lncRNAs play in each of the steps of B cell differentiation and whether their alteration have implications as a non-coding oncogenes or tumor suppressors in human tumors derived from these cells, such as diffuse large B cell lymphomas or MM.37. Healthy donor samples were provided by the Biobank of the University of Navarra and were processed following standard operating procedures approved by the local Ethics and Scientific Committee. The following monoclonal antibody combination was used for the cell isolation from tonsils: CD45-OC515 ; CD20-Pacific Blue ; CD44-APCH7 . CD10 PE-Cy7 ; CD38-FITC ; CXCR4-PE ; CD27-APC  and CD3-PerCP-Cy5.5 . BMPCs were FACS  from human bone marrow of healthy donors using CD38-FITC ; CD138-BV421  and CD27-BV510 . Monitoring of instrument performance was performed daily using the Cytometer SetupTracking  after laser stabilization.NB cells, CBs, CCs, MEM cells, and plasma cells (TPCs) were isolated from human tonsils of healthy donors and (BMPCs) from bone marrow of healthy donors by multiparameter FACS using the expression level of nine different surface antigens as previously describedTotal RNA from all B cell subpopulations was isolated using Trizol extraction method (Life Technologies), purified by RNeasy MinElute spin column (Qiagen) and treated with DNase I (Thermo Fisher) following the manufacturer’s instructions. Total RNA was quantified using NanoDrop Specthophotometer (NanoDrop Technologies). High-quality purified total RNA (300–600 ng) from each sample was used for library preparation according to the user's manual of Truseq Stranded Total ribo-depleted RNA sample preparation kit (Illumina). Library quality was assessed using Agilent 2100 Bioanalyzer (Agilent Technologies) and the quantity was determined using Qubit (Life Technologies). Strand-specific RNA libraries were multiplexed (four samples per lane) and the sequencing was done with Illumina HiSeq 2500 (Illumina) as 50 base paired-end runs.(−ΔΔCt) method using the gene GAPDH as an endogenous control. All results are shown as the average of three independent experiments. Quantitative RT-PCR (Q-RT-PCR) primers for specific novel and annotated lncRNAs, eRNAs, and circRNAs are listed in Supplementary Table RNA was prepared as previously described. Complementary DNA (cDNA) was synthesized using Verso cDNA kit (Thermo Fisher) following the manufacturer’s instructions. Detection was done using Fast SyberGreen on 7900HT Fast Real-Time PCR System with 384-Well Block Module thermal cycler from Applied Biosystems and using the following conditions: initial step of 20 s at 95 °C followed by 40 cycles of 1 s at 95 °C and 20 s at 60 °C. The relative expression of each gene was quantified by the Log 2® 4-TOPO® plasmid using TOPO-TA Cloning® Kit for Sequencing (Life Technologies) and transformed into Escherichia coli according to the manufacturer’s recommendations. Colonies with recombinant plasmids containing the described PCR products were screened by digestion with EcoRI (Amersham Biosciences). Candidate plasmid clones were sequenced using T7 and T3 universal forward and reverse primers.Amplification product obtained by Q-RT-PCR for circRNA-3 in three new samples of TPCs and plasma cells from two patients with MM were subcloned into pCR38 to remove any potential ribosomal RNA leftover from the ribodepletion step. A first pass alignment was done against human ribosomal sequences allowing multi-mapping. Unmapped reads from the first step were then aligned to hg19 human reference using GENCODE v1939 junction points. Cufflinks v2.2.116,40 was run on the resulting alignment files to create de novo transcriptome assembly specific to each sample using strand-specific settings and GENCODE v19 as a database. Cufflinks outputs for all of the samples were then merged with themselves and GENCODE database using cuffmerge. The resulting assembly was then filtered to only novel intergenic and antisense transcripts, removing isoforms for known genes as well as novel intronic sense-overlapping transcripts due to challenges in separating them from transcription artifacts. R41 and GNU parallel42 was used to facilitate the analysis.A two-step alignment procedure was performed with STAR v2.417 on all three ORFs of the transcript strand. Maximum score along the length of the transcript across all three ORFs was used as the maximum coding potential, and novel transcripts that had a coding potential score >0 were filtered out.The novel transcripts were then filtered for minimum length of 200. Coding potential of each transcript was checked using phyloCSF43 was used to annotate each sample to the merged transcript annotation. Resulting counts were normalized to library size using number of mapped reads to each sample by DESeq244, and converted into Transcripts-pre-million (TPM)45. Any transcript  that was expressed in at least three samples with ⩾1 TPM was included for the study.Subread featureCountsWe have used Human BodyMap v2, Human lincRNA, and GENCODE v28 references to annotate the transcribed elements for Fig. 47. Both distances resulted in similar trees, and Supplementary Figure Unsupervised clustering of the samples was done by PCA and phylogenetic analysis. PCA included in the manuscript were performed using the TPM values of the top 10% most variable genes (standard deviation across the samples). PCA on all genes without filtering yielded similar results (data not shown). Phylogenetic analysis was performed on a distance matrix created by log transforming the TPM values and calculating pairwise Euclidean and Pearson’s distance between each sample. The character matrix was generated using neighbor joining algorithm on the distance matrix and bootstrapping the result 100 times on resampled values using the ape package in Rq value of <0.01.Differential expression was calculated with DESeq2 by pairwise comparisons of all cell types. Differentially expressed genes were selected by taking the genes with an absolute log 2(Fold Change) (log 2FC) of 1.5 and 48 to align to hg19 reference. CIRI25 was run on the pooled sample to discover circRNAs. circRNA expression was quantified by matching the junction reads in the pooled data to their original sample. circRNAs that had ⩾5 junction points in at least three samples were included for study.circRNA discovery was performed by pooling all the samples and using BWA-MEM49 for each gene. This many-to-many lncRNA-coding gene association was used for all of the following analyses.Each lncRNA was associated to nearby coding genes by intersecting the lncRNA coordinates by the regulatory region of the coding genes. Regulatory region coordinates were defined by basal plus extension association in GREATk-means clustering50 with k = 8 using the group medians  for each cluster. Top cell-type-specific signatures as calculated by tissue specificity index18 are shown in Fig. Gene expression was averaged by taking the median of TPM values for each cell type. lncRNAs were then clustered by ans Fig. . EnrichmFlanking region of coding genes (+−250 kb) that are differentially expressed between cell type transitions was intersected with the lncRNAs genomic coordinates. Mean log 2FC of lncRNA expression changes in the same comparison were plotted as a function of distance for both upregulated and downregulated coding genes Fig. .54 by the FC enrichment of the binding compared to the input. For each lncRNA, a summary value of each signal track was calculated by taking the 90th percentile value in a window of +−1000 bp from the TSS. This was done to remove potential outliers and normalize for length.ChIP-seq data for histone modifications and transcription factors mentioned in the Results section were aligned to hg19 genome with BWA-MEM. Peaks and signal tracks were calculated using MACS v2t-SNE23. lncRNAs were separated into 10 clusters using spectral clustering with SamSPECTRAL55. For heatmap visualizations, the signal values for each feature were colored by mapping the feature value to a 0–1 range after removing the top and bottom 1%.Dimensionality reduction on the ChIP-seq data matrix was performed using 57 on H3K27ac data. Highly active enhancer regions that were merged together in a bigger region with ROSE are annotated as “super-enhancer regions”, whereas the specific enhancer peaks that lie within the general region are called “super-enhancer constituent peaks”.Enhancers were called for NB cells and GCs separately using the H3K4me1 marks that were at least 2500 bp away from a coding gene TSS. H3K4me1 peaks that also contained an H3K27ac peak were annotated as “active enhancers”, whereas H3K4me1 peaks that did not overlap with H3K27ac peak were called as “poised enhancers”. Super-enhancer regions were called using the ROSE algorithmeRNAs were called by taking the TSS+−1000 bp of single-exon intergenic lncRNAs and intersecting them with the enhancer peaks. Any eRNA within 2500 bp of a coding gene TSS was excluded. Activity of an eRNA was matched to the activity level of the enhancer  for NB cells and GCs separately.G, window size of w and window count of l, two regions that flank G to the left (5′ of + strand) or right (3′ of + strand) excluding the center window were created as follows:For a genomic coordinate Gleft or Gright from forward and reverse strands were summed up to give Fleft, Fright for forward strand, and Rleft, Rright for reverse strand. A dummy count ε was added to remove the exaggerating effects of very small counts on ratios. Bidirectionality score B was calculated asThe number of aligned reads that fall into either B was calculated with w = 100 and l = 7; lncRNAs with B > 0.5 were annotated as bidirectional.For each intergenic lncRNA the bidirectionality score Further information on experimental design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Reporting Summary


Mutations in the gene Adenomatous Polyposis Coli or APC appear in most sporadic cases of colorectal cancer and it is the most frequent mutation causing hereditary Familial Adenomatous Polyposis. The detailed molecular mechanism by which APC mutations predispose to the development of colorectal cancer is not completely understood. This is in part due to the lack of accessibility to appropriate models that recapitulate the early events associated with APC mediated intestinal transformation. We have established a novel platform utilizing human induced Pluripotent Stem cells or iPSC from normal or FAP-specific APC mutant individuals and evaluated the effect of the mutation in the cells before and after differentiation into intestinal organoids. In order to minimize genetic background effects, we also established an isogenic platform using TALEN-mediated gene editing. Comparison of normal and APC mutant iPSC revealed a significant defect in cell identity and polarity due to the presence of APC in heterozygosity as well as chromosomal aberrations including abnormal anaphases and centrosome numbers. Importantly, upon specification into intestinal progeny, APC heterozygosity was responsible for a major change in the transcriptional identity of the cells with dysregulation of key signaling pathways, including metabolic reprogramming, abnormal lipid metabolism and intestinal-specific cadherin expression. In conclusion, we have developed a novel iPSC/intestinal model of APC mutagenesis and provide strong evidence that APC in heterozygosity imparts a clear phenotypic and molecular defect, affecting basic cellular functions and integrity, providing novel insights in the earlier events of APC-mediated tumorigenesis. Colorectal cancer (CRC) is the second leading cause of cancer-related death in America. Ten to 30% of CRC have a major hereditary component providing unique opportunities to study specific genes and pathways associated with intestinal tumorigenesis. Among them, one of the most important drivers of CRC is Adenomatous Polyposis Coli (APC) as more than 50% of hypermutated tumors and more than 80% of non-hypermutated tumors have mutations in APC , 2. FurtWe sought to develop a novel approach based on the generation of induced pluripotent stem cells (iPSC) from normal individuals or from patients with familial adenomatous polyposis (FAP), the second most highly penetrant form of hereditary CRC, which is caused mainly by APC mutations. The ability of these pluripotent cells to differentiate into intestinal organoids provided us with a readily accessible platform in which to evaluate the effect of APC mutations on the cellular and molecular phenotype of iPSC and their intestinal progeny. Indeed, by comparing isogenic cells expressing either the wild-type or a truncated version of APC, mimicking the germline mutation commonly found in FAP patients, we detected surprising defects in cell identity and chromosomal integrity. Importantly, upon specification into intestinal progeny, APC heterozygosity was responsible for a major change in the transcriptional identity of the cells with dysregulation of key signaling pathways, including metabolic reprogramming, abnormal lipid metabolism and cadherin overexpression, providing novel insights in the earlier events of APC-mediated tumorigenesis.Reprogramming of fibroblasts from normal and FAP patients was performed as previously described using the excisable STEMCCA lentiviral reprogramming system . Twenty-Pluripotency marker expression of reprogrammed iPSC was tested using the ES Characterization Kit (Millipore # SCR001) by following manufacture’s recommendations for AP, TRA-1-80, and SSEA4 staining. Colonies were analyzed with the inverted microscope Nikon Eclipse TS100. Karyotype analysis was done by Cell Line Genetics.https://tale-nt.cac.cornell.edu. We selected six combinations of TALEN pairs that bind close to the sequence encoding amino acid 1309 of the APC protein. The APC1309 mutation is one of the most common APC germline mutations leading to severe intestinal phenotypes. Custom TALEN arrays were assembled as described[Targeting of the human APC locus in iPSC was achieved by transient delivery of plasmid vectors encoding TALENs. TALEN arrays specific for the APC gene were designed using the TAL Effector Nucleotide Targeter 2.0 software, available at Puro gene would increase the probability to pick colonies carrying frameshift mutations resulting in premature stop codons. To achieve this, we followed a transfection/selection protocol that we had developed previously for the excision of lentiviral cassettes from the genome of iPSC [In order to target the APC gene in iPSC, APC TALENs 1320-L and 1320-R3 were subcloned into the pHAGE2 EF1α IRES Puro vector for co-expression of a TALEN monomer and the Puro resistance gene. We reasoned that transient puromycin selection of iPSC expressing high levels of the TALENs and the  of iPSC . In brie of iPSC . Clone sProtein extraction and Western blot was performed as described elsewhere. For APCIn vitro differentiation of iPSC into fibroblasts was done as follows. iPSC were harvested and allowed to form embryoid bodies (EBs) in DMEM media containing 20% KSR. Seven days later, EBs were transferred to 10-cm gelatin-coated culture dishes containing DMEM media with 10% fetal calf serum (FCS). 50–60% confluency cultures were maintained in absence of bFGF and Matrigel and split weekly with trypsin-EDTA for at least 5 passages until achieving uniform fibroblast-like morphology, loss of Tra-1-81, expression of CD90 and normalized G0-G1 cell cycle accumulation. Confluent iPSC-derived fibroblasts were scratched with a pipette tip and allowed to polarize and migrate into the wound space. Cells were fixed in 4% PFA and stained with Phalloidin and pericentrin antibody followed by specific secondary antibody detection. Finally, nuclei were counterstained with DAPI and cells photographed with an inverted fluorescence microscope (See detailed antibody list and working dilutions in iPSC were expanded in feeder-free conditions using mTeSR™1 medium (Stemcell technologies) following the manufacturer’s recommendations. Upon reaching 80% confluence, iPSC colonies were fixed in 4% PFA for 5 min, washed in PBS and stained with DAPI (1μg/mL) for 5 minutes. Stained cells were imaged with a fluorescence microscope and anaphase bridge indexes (ABI) were scored as described. For cenDifferentiation of control and mutant iPSC lines into intestinal tissue was performed as described with theAt day 3 of the differentiation protocol, cells were harvested with Gentle Cell Dissociation Reagent (STEMCELL Technologies Inc.), washed with PBS containing 0.2% of Bovin Serum Albumin (BSA) and stained using conjugated antibodies against markers CXCR4 and c-KIT . The effIn the same way, flow cytometry analysis was used to quantify differences on the proliferation rates between iPSC and HIOs samples from controls and FAP patients following the recommendations of the Click-iT EdU Alexa Fluor 488 Imaging Kit (Life Technologies).At day 8 of differentiation, cultured cell layers containing three-dimensional (3D) emerging structures were fixed with 4% paraformaldehyde (PFA) in PBS during 15 minutes and washed 3X for 5 minutes with TBST buffer. Cells were permeabilized with 1% Triton X-100 for 10 minutes. After washing with TBST, cells were blocked with 4% Normal Donkey Serum  during 30 minutes and stained with specific antibodies for CDX2 and SOX17. After 1hour of incubation, cells were washed with TBST, followed by incubation with appropriate antibodies conjugated to Alexa Fluor 488 and Cy3 during 45 minutes. DNA was detected with DAPI. All the steps were performed at room temperature (RT). Well images were taken with the Keyence BZ-X710 fluorescence microscope.At day 21, 3D matrigel containing developed organoids was pipetted into a 15 ml Falcon tube and fixed with fresh 4% PFA in PBS at 4°C overnight. The next day, organoids were recovered from the diluted matrigel, washed on PBS, and stained following the steps as previously indicated for cultured cells, with specific primary antibodies against the intestinal markers CDX2 and VILLIN, and Hoechst for DNA detection. Whole organoids were mounted on cavity slides (Eisco) and imaged with a Zeiss LSM 700 confocal microscope.After 40 days, organoids were fixed in 4% PFA in PBS at 4°C overnight. Samples were washed in cold PBS, rinsed six times in 7.5% sucrose in PBS (10 minutes each) and incubated in 30% sucrose on the rotor at 4°C overnight. Next day, samples were embedded in O.C.T and frozen with liquid nitrogen. Frozen sections were permeabilized and blocked as described before and stained with the intestinal markers CDX2, villin and lysozyme as well as antibodies against β-catenin and EdU for proliferation analysis  following the manufacturer’s recommendations. Reversed transcription of 1μg of total RNA from each sample was carried out with the SuperScript™ III First-Strand Synthesis System (Invitrogen). The resulting cDNA was diluted to a final concentration of 50 ng/μl and gene expression was detected with specific taqMan Probes (Thermo Fisher Scientific)  with thehttps://cran.r-project.org/) and Bioconductor (https://www.bioconductor.org/). Pairwise differential expression analysis between samples was performed using the edgeR package (https://bioconductor.org/packages/release/bioc/html/edgeR.html). Multiplicity correction was performed by applying the Benjamini-Hochberg method on p-values to control the false discovery rate (FDR), with top genes sorted by FDR and called as significantly differentially expressed when meeting thresholds of p value<0.05. Heatmaps were generated using gplots(http://www.inside-r.org/packages/cran/gplots/docs/heatmap.2) and RColorBrewer(https://cran.r-project.org/web/packages/RColorBrewer/index.html). Expression data of significant genes was log2 adjusted and samples were clustered via Pearson correlation and average linkage. All raw and processed data has been deposited in GEO (GSE99821).Gene expression data was generated via a 3' DGE protocol for high-throughput single cell RNA barcoding and sequencing, run andwww.qiagen.com/ingenuity) software  was used to generate functional networks and analyze signal transduction pathways. The functional networks and signal transduction pathways of IPA are predicted on the basis of known gene–gene (protein–protein) and functional interactions based on information contained in the Ingenuity Pathway Knowledge Base.IPA®, QIAGEN Redwood City, Student's t-tests were performed for statistical analysis. Statistically significant differences from the wild-type control are indicated by asterisks: *p< 0.05; **P < 0.01.APC gene at position 1621 and the other two (FAP 6965–1 and FAP 6888–1) contain a AG deletion at position 4611  to be variable between iPSC lines from different donors. This inter-individual variability was confirmed by comparing iPSC lines derived from three healthy donors  and performed a classic “wound repair assay”. First, iPSC-derived fibroblasts were grown to confluence and then a mechanical “scratch” was induced with a pipette tip. Fibroblasts then tend to grow towards the “wound” by polarizing the cells and then migrating to cover the defect. Staining the cells with phalloidin, pericentrin and DAPI enables the quantification of the location of the microtubule-organizing center (MTOC) relative to the nucleus as a measurement of cell polarity. As shown in APC mutant cells showed a significant decrease in the percentage of polarized MTOC. As APC has also been implicated in the regulation of chromosomal segregation and the formation of the mitotic spindle, with APC mutations causing chromosomal abnormalities [APC mutant cells showed a significant increase in abnormal anaphases  with alal cells .APC+/+ and APC+/- into intestinal organoids, following the protocol described above. As shown in APC mutant line, first into endoderm . Similarly to SAGE, DGE allows sequencing of most RNA transcripts , includited iPSC . Indeed,ted iPSC . Furtherted iPSC .CDH17), was the number 13 most highly dysregulated among the 2124 misexpressed genes in HIOs . Cadherin 17, also known as IL Cadherin or Intestinal-Liver Cadherin is a member of the cadherin superfamily that appears to be expressed primarily in the intestinal tract and its protein may play a role in the morphological organization of the intestine and liver. Remarkably, abnormal CDH17 expression has been described as a diagnostic marker of adenocarcinomas of the digestive system [APC mutant HIO was Isocitrate dehydrogenase 1 (IDH1) . One of the top 5 canonical pathways that was found by Gen Set Enrichment Analysis (See below) within the HIO gene set was oxidative phosphorylation  is overexpressed in several cancers including gastrointestinal cancers and correlates with poor prognosis and accelerated growth and invasion of cancer cells. In addition, VIMENTIN is a marker for epithelial-mesenchymal transition (EMT) and is currently being evaluated as a potential target for anti-cancer therapy [Upon analysis of each set of differentially expressed genes for potential differences in epithelial or signaling programs, we observed that Cadherin 17 , Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (IPA) and all showed similar results. Among the dysregulated KEGG pathways associated with the list . Indeed,O family . Validatfunction .APC+/- HIO, Ingenuity® Pathway Analysis (IPA) was used. A total of 2124 differentially expressed genes were uploaded to IPA for core analysis. Out of those, 2113 genes IDs were successfully mapped. As shown in In order to further validate the pathways affected in APC heterozygous, we sought to recapitulate the primordial developmental state of gut epithelia and study the cellular and molecular “milieu” that may provide a bona fide environment for the development of intestinal tumors. We demonstrated that FAP patient iPSC were able to differentiate into gut organoids, although many differences found in the intestinal-like tissues developed from normal or heterozygous APC iPSC were certainly blurred by the inter-patient variability. Once we moved into the isogenic system, we were able to find robust and significant differences between normal and APC mutant intestinal epithelial cells. It is relevant to emphasize that studies with the FAP lines were also limited by the unstable nature of the APC mutant lines. Spontaneous differentiation was always evident in our cultures requiring extra care in the maintenance and passaging of the lines, and was further supported by the faster induction of markers such as SOX17 and CDX2 in the APC mutant cells.The recent establishment of in vitro 3D culture approaches to model intestinal morphogenesis, either from intestinal crypts  or from APC mutant cells. As mentioned above, even though we had a relatively high efficiency of TALEN induced DNA double strand breaks (~15–25%), the overall efficiency of obtaining non-conserved mutations bearing truncated versions of APC was very low (~6%). As a matter of fact, after screening more than 400 colonies we were never able to recover a line with homozygous mutations in both APC alleles, strongly suggesting that APC is a key factor in the maintenance of iPSC lines in their pluripotent state. Our findings that APC in heterozygosity was enough to induce spontaneous differentiation of the iPSC could indicate that even if our TALENs were able to create homozygous APC mutant lines, they were lost to spontaneous differentiation before forming colonies. This is supported by the existence of a limited number of reports describing APC mutant lines, which were all done on mouse ESC expressing either hypomorphic mutant variants of APC [APC mutations [APC heterozygous human iPSC line. Interestingly, recent studies describing a novel differentiation protocol to derive colonic organoids from human iPSC found that FAP-specific iPSC had a significant increase in proliferation as measured by percentage of ki67 positive cells [Another interesting finding relates to the gene editing approach to create the s of APC  or speciutations . These sve cells . WhetherAPC in heterozygosity has such an impact on the phenotypic and molecular characteristics of our iPSC and their intestinal progeny is not completely unexpected. Several studies have previously shown that changes in APC dosage can affect cellular motility, migration and polarity [The finding that polarity , 38, 39,polarity . Our datIDH1 and IDH2 along with succinate dehydrogenase (SDH), fumarate hydratase (FH), and pyruvate kinase M2 (PKM2) [IDH1/2 mutations have been observed in several solid and blood cancers including colon cancer. The metabolic activity of IDH1/2 has been tied to cancer epigenetic mechanisms. Several ongoing studies have started targeting these IDH1/2 metabolic genes as selective targets for new anticancer therapeutics [There is a renewed interest in the area of cancer metabolism with metabolic reprogramming coined as a hallmark of cancer based on the discovery of mutations and alterations in 2 (PKM2) , 42. IDHapeutics . MetabolOur studies show that a truncated form of APC induces a significant effect on the cellular and molecular features of iPSC and their differentiated progeny. This effect is exacerbated upon differentiation into intestinal organoids with a major impact on the gene expression profile of the cells, and the emergence of a molecular signature resembling several features of intestinal tumorigenesis and abnormal metabolism. Further studies using cells with homozygous mutations mimicking the correspondent loss of heterozygosity (LOH) present in advanced intestinal tumors is warranted.S1 FigRepresentative micrographs showing bright field (top rows) and Alkaline Phosphatase staining (bottom rows) evidence abnormal colony growth pattern in APC+/- colonies compared to the WT isogenic line (BU1).(PDF)Click here for additional data file.S2 FigExpression of endodermal genes measured by qRT-PCR comparing WT vs FAP iPSC lines (top graph) or three independent control lines (bottom graph).(PDF)Click here for additional data file.S3 Fig(A) Expression of APC measured by qRT-PCR in WT (black) vs FAP (red) iPSC before (d0) and after differentiation into intestinal organoids (d40). (B) Expression of Wnt target genes in intestinal organoids. Data are mean ± SE from two independent WT and FAP lines.(PDF)Click here for additional data file.S4 FigExpression of the endodermal marker Sox17 overtime during differentiation of control (black) vs FAP (red) iPSC into intestinal organoids. DE: definitive endoderm. Data are mean ± SE of two independent lines.(PDF)Click here for additional data file.S5 FigqRT-PCR data of selected genes in WT vs FAP iPSC upon intestinal differentiation. Data are mean ± SE of two independent lines.(PDF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 TableTop genes sorted by FDR and called as significantly differentially expressed when meeting thresholds of p value<0.05.(XLSX)Click here for additional data file.


Aplysia californica (Aplysia) allows for detailed studies of physiological and molecular changes in small sets of neurons. Sensory neurons of the biting and tail withdrawal reflexes are glutamatergic and show reduced L-Glutamate current density in aged animals, making them a good candidate to study age-related changes in glutamatergic responses. To examine if changes in ionotropic L-Glu receptor (iGluR) transcription underlie reduced physiology, mRNA expression of iGluR was quantified in two sensory neuron clusters of two cohorts of Aplysia at both sexual maturity (~8 months) and advanced age (~12 months). Sensory neuron aging resulted in a significant overall decrease in expression of iGluR subunits in both sensory neuron clusters and cohorts. Although the individual subunits differentially expressed varied between sensory neuron clusters and different cohorts of animals, all differentially expressed subunits were downregulated, with no subunits showing significantly increased expression with age. Overall declines in transcript expression suggest that age-related declines in L-Glu responsiveness in Aplysia sensory neurons could be linked to overall declines in iGluR expression, rather than dysregulation of specific subunits. In both sensory neuron clusters tested the N-methyl-D-aspartate receptor subtype was expressed at significantly greater levels than other iGluR subtypes, suggesting an in vivo role for NMDAR-like receptors in Aplysia sensory neurons.The simplified nervous system of  Aplysia californica (Aplysia) has been used extensively as a model for studying the effects of aging due to a relatively simple nervous system, easily identifiable neurons, and short life span of ~12 months. Well-mapped neural circuits in the Aplysia nervous system have allowed researchers to more closely correlate age-related changes in reflex behaviors with physiological and molecular changes in the relevant underlying neurons [Aging is associated with impairments in neuronal function that result in declines in cognitive function and reflex systems of aged animals. A reduced number of synaptic contacts and reduced dendritic spine density can alter the strength of synaptic connections, leading to diminished excitatory postsynaptic potential amplitude in aged neurons –3. The m neurons –9.Aplysia, the majority of fast synaptic transmission in the central nervous system is mediated by ionotropic glutamate receptors (iGluR) [Aplysia are glutamatergic, and show reduced L-Glu current density and fewer neurons responding to L-Glu in animals of advanced age [Throughout much of the animal kingdom, including  (iGluR) , 11. Agi (iGluR) , 13. In nced age . Althougnced age .Aplysia, with varying degrees of relatedness to their vertebrate counterparts [Aplysia iGluR tetramers, if indeed its functional iGluR are formed as in vertebrates, is unknown.Vertebrate iGluR are classified into three subtypes based on selective agonists in vertebrates: N-methyl-D-aspartate (NMDA), α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), and kainate. Functional iGluR are formed as heterotetramers, consisting of iGluR subunits belonging to the same subtype. There is evidence that analogues of each of these vertebrate subtypes exists in terparts . The comAplysia [Aplysia sensory neurons [2+ [Aplysia sensory neurons or in motoneurons of the abdominal ganglion [Aplysia, similar to L-Glu-induced effects in these neurons [NMDAR are the most well-conserved iGluR subtype across bilaterian species, including Aplysia , thus th neurons , 18 and  neurons , making rons [2+ , which arons [2+ . AMPAR mganglion , 22, it  neurons . KainateAplysia. To provide context for vertebrate species, Aplysia iGluR subunits were classified as NMDAR or AMPAR based on homology with vertebrate subunits in a previous phylogenetics study [To test the hypothesis that changes in iGluR transcription may underlie reduced iGluR current amplitude in aged sensory neurons, this study used qPCR to examine changes in iGluR transcription in mature and aged PVC and BSC sensory neurons in 2 cohorts of cs study .Subunits with unclear phylogenetic relationships to vertebrate iGluR were not classified into a particular subtype.Aplysia from the University of Miami National Resource for Aplysia were reared from egg masses of wild-caught animals. Two cohorts were reared and maintained throughout their lifespan at a temperature of 13–15°C. Once the animals reached age 4 months they were held at 5 per cage to reach sexual maturity. Animals were fed an ad lib diet of Agardhiella subulata as previously described [escribed . Mass waAplysia have previously been defined as Aged I (AI) or Aged II (AII) based on progressively diminished reflexes and reductions in iGluR physiology of sensory neurons [Aplysia. Mean reflex completion times were compared to Kempsell and Fieber (2014) and determined that age 12 month animals in these two cohorts were stage Aged II (AII).Sexual maturity for each cohort was designated as the first day an egg mass was laid. Reflex completion times were measured in animals at sexual maturity  and near the end of life (age 12 months) to quantify behavioral changes with age. Aged  neurons . Times tRighting was measured at M and then again at AII in 8 animals from each cohort per time point. An individual was placed in a 48x27x20 cm polycarbonate cage with flowing seawater and acclimated for five minutes before measurements of righting. The animal was picked up from the bottom of the cage and rolled off the palm of the hand at the top of the water column. Time was recorded from the moment the animal reached the cage bottom. It then righted itself and adhered to the bottom of the cage. The reflex was completed as it began to take its first crawling step. The measurement was recorded 3 times per individual, with a minimum of 5 minutes between trials, and the times averaged. Data were combined for all animals at each time point and a Student’s t-test was used to determine significant differences in righting between age groups.TWR was measured at M and AII in the same individuals that were analyzed for the righting reflex. After righting measurements, animals were allowed to rest for 5 minutes. The animal was then placed on its foot in the center of the cage, allowed to adhere to the bottom, and was lightly held in place to measure initial resting length. TWR was initiated by pressing a blunted 21-gauge needle to the tip of the animal’s tail for approximately 1 sec to initiate withdrawal of the tail. Time was recorded from the initiation of the reflex until the animal relaxed the tail approximately 30%. Retracted length was recorded to calculate percent tail withdrawn. Measurements of duration and amplitude of TWR were recorded 3 times, with a minimum of 5 minutes between trials, and the measurements averaged. A Student’s t-test was used to calculate differences in TWR time and fraction of body length withdrawn between age groups.th body weight (by volume) of isotonic MgCl2. The animal was euthanized by severing the connectives and removal of all nervous system ganglia. Ganglia were immediately rinsed in artificial seawater  after removal.RNA was extracted from a six-animal subset tested for TWR and righting from each cohort at M, and 6 from each cohort at AII. An animal was first anesthetized by injection of 1/6PVC neurons were separated from the remainder of the pleural ganglia and immediately placed in Qiagen lysis buffer, with both left and right PVC clusters pooled into a single sample. The same procedure was used to harvest BSC neurons from the buccal ganglia. Total RNA from PVC and BSC neurons was extracted with the Qiagen RNeasy Micro Kit following the manufacturer’s instructions. Genomic DNA contamination was removed during RNA extraction according to manufacturer’s instructions (Qiagen).Quantity of RNA from all tissues was analyzed using a NanoDrop (Model ND-1000). One hundred ng of total RNA from each sample was reverse transcribed into cDNA using SuperScript III reverse transcriptase (Invitrogen) with random hexamer primers following the manufacturer’s suggestions. The resulting cDNA was diluted 1:5 with nuclease free water to provide a final concentration equivalent to 1 ng RNA/1 μl cDNA for qPCR.qPCR reactions were executed on a Stratagene Mx3005P with SYBR Green master mix (Invitrogen). Each reaction consisted of 10 μl of SYBR Green master mix, 2 μl of cDNA and 0.2 μM of forward and reverse primers in a total volume of 20 μl. Thermal cycler conditions were as follows: 95°C for 10 minutes, followed by 40 cycles of 95°C for 15 sec, 58°C for 30 sec, 72°C for 30 sec. All 12 iGluR subunits and the splice variant of Grin1 previously identified were tested. Primer sequences and amplicon lengths for each transcript can be found in Table A in E coli cells using a TOPO TA cloning kit (ThermoFisher). Plasmids were purified with a Qiagen mini-prep plasmid kit and quantified on a Nanodrop to determine plasmid concentration. Plasmids were linearized by restriction digest and serial dilutions prepared from 106−100 plasmid copies that were run in triplicate on each plate to calculate a standard curve for absolute copy number calculation.For cohort 1, sensory neuron clusters from 6 animals at M and at AII were analyzed with qPCR to quantify changes in iGluR expression. Two technical replicates were performed for each biological replicate. Absolute copy number for each replicate was calculated using serial dilutions of a known quantity of plasmid containing the target amplicon. PCR products for each gene were gel purified with a Qiagen gel purification kit and transfected into electrocompetent T Difference (GED) formula [T method [T was calculated for the gene of interest (GOI) in each biological sample using the formula ΔCT = CT (GOI)–CT (GOI:reference), where the reference is an independent sample not used for other analyses. The same reference sample used was for each plate and contained PVC neurons from a sexually mature animal. Relative expression ratio (rER) was then calculated using the rER formula described by Schefe and Lehmann [T values used for all qPCR analysis are available in For cohort 2, PVC and BSC neuron clusters from 4 animals were tested at each time point. These samples were run in technical triplicate instead of duplicates as were run for cohort 1. In this cohort, we tested the expression of several of the most highly expressed iGluR subunits from Cohort 1: Grin1-1, Grin1-2, Grin2, GluR1, GluR5, and GluR7. For cohort 2 quantification, target transcripts were normalized to GAPDH using the Gene Expression’s C formula , which iT method  that acc Lehmann . qPCR ef Lehmann . RelativFor cohort 1, differential expression of each gene was calculated using a two-way analysis of variance (ANOVA) on absolute copy numbers, followed by Tukey’s HSD post hoc test for each subunit. Differential expression in cohort 2 was determined using a two-way ANOVA on the calculated rER values (described above), followed by Tukey’s HSD post-hoc test. Significance was defined at p ≤ 0.05 following multiple testing correction, and all p-values presented throughout are following multiple testing correction.Aplysia. Average mass declined beginning approximately two months prior to AII measurements in both cohorts  were not assigned a subtype designation.To determine whether reduced L-Glu current density is correlated with altered expression of iGluR subunits, expression of each subunit was compared in PVC neurons of M and AII animals. To further characterize the effects of aging on iGluR subtypes, individual subunits were categorized into NMDA  or AMPA  vertebrate receptor subtypes based on a previous phylogenetic study . PredictF1,12 = 14.53, p < 0.05), as well as downregulation of 3 individual subunits in aged animals: Grin1-1, KA1, and GluR6  and GluR1 and Grin1-1 subunits were significantly downregulated in aged neurons of cohort 2. Similar to cohort 1, significantly increased expression was not observed for any iGluR subunits.In PVC neurons of cohort 1 there was a statistically significant effect of aging on overall iGluR expression , and NMDA receptor subunits Grin1-1 and Grin1-2 were significantly downregulated in aged animals . The AMPAR subunit GluR1 had significantly decreased expression in cohort 2  Animal mass estimated from wet weight decreased beginning approximately 2 months before AII measurements (n = 15). Dotted lines represent time points animals were sacrificed for qPCR. B) Time to right increased significantly in AII. C) Tail withdrawal time increased significantly in AII. D) Amplitude of tail withdrawal decreased significantly in AII, calculated as fraction of the initial length withdrawn.(DOCX)Click here for additional data file.S1 File(XLSX)Click here for additional data file.