An in vitro model of early anteroposterior organization during human development.

The body plan of the mammalian embryo is shaped through the process of gastrulation, an early developmental event that transforms an isotropic group of cells into an ensemble of tissues that is ordered with reference to three orthogonal axes1. Although model organisms have provided much insight into this process, we know very little about gastrulation in humans, owing to the difficulty of obtaining embryos at such early stages of development and the ethical and technical restrictions that limit the feasibility of observing gastrulation ex vivo2. Here we show that human embryonic stem cells can be used to generate gastruloids-three-dimensional multicellular aggregates that differentiate to form derivatives of the three germ layers organized spatiotemporally, without additional extra-embryonic tissues. Human gastruloids undergo elongation along an anteroposterior axis, and we use spatial transcriptomics to show that they exhibit patterned gene expression. This includes a signature of somitogenesis that suggests that 72-h human gastruloids show some features of Carnegie-stage-9 embryos3. Our study represents an experimentally tractable model system to reveal and examine human-specific regulatory processes that occur during axial organization in early development

Ultrathin graphene-based membrane with precise molecular sieving and ultrafast solvent permeation

Graphene oxide (GO) membranes continue to attract intense interest due to their unique molecular sieving properties combined with fast permeation. However, their use is limited to aqueous solutions because GO membranes appear impermeable to organic solvents, a phenomenon not yet fully understood. Here, we report efficient and fast filtration of organic solutions through GO laminates containing smooth two-dimensional (2D) capillaries made from large (10-20 μm) flakes. Without modification of sieving characteristics, these membranes can be made exceptionally thin, down to â 1/410 nm, which translates into fast water and organic solvent permeation. We attribute organic solvent permeation and sieving properties to randomly distributed pinholes interconnected by short graphene channels with a width of 1 nm. With increasing membrane thickness, organic solvent permeation rates decay exponentially but water continues to permeate quickly, in agreement with previous reports. The potential of ultrathin GO laminates for organic solvent nanofiltration is demonstrated by showing >99.9% rejection of small molecular weight organic dyes dissolved in methanol. Our work significantly expands possibilities for the use of GO membranes in purification and filtration technologies

A new tool called DISSECT for analyzing large genomic datasets using a Big Data approach

Large-scale genetic and genomic data are increasingly available and the major bottleneck in their analysis is a lack of sufficiently scalable computational tools. To address this problem in the context of complex traits analysis, we present DISSECT. DISSECT is a new and freely available software that is able to exploit the distributed-memory parallel computational architectures of compute clusters, to perform a wide range of genomic and epidemiologic analyses, which currently can only be carried out on reduced sample sizes or under restricted conditions. We demonstrate the usefulness of our new tool by addressing the challenge of predicting phenotypes from genotype data in human populations using mixed-linear model analysis. We analyse simulated traits from 470,000 individuals genotyped for 590,004 SNPs in ∼4 h using the combined computational power of 8,400 processor cores. We find that prediction accuracies in excess of 80% of the theoretical maximum could be achieved with large sample sizes

Genetic Divergence between Freshwater and Marine Morphs of Alewife (Alosa pseudoharengus): A ‘Next-Generation’ Sequencing Analysis

Alewife Alosa pseudoharengus, a small clupeid fish native to Atlantic Ocean, has recently (∼150 years ago) invaded the North American Great Lakes and despite challenges of freshwater environment its populations exploded and disrupted local food web structures. This range expansion has been accompanied by dramatic changes at all levels of organization. Growth rates, size at maturation, or fecundity are only a few of the most distinct morphological and life history traits that contrast the two alewife morphs. A question arises to what extent these rapidly evolving differences between marine and freshwater varieties result from regulatory (including phenotypic plasticity) or structural mutations. To gain insights into expression changes and sequence divergence between marine and freshwater alewives, we sequenced transcriptomes of individuals from Lake Michigan and Atlantic Ocean. Population specific single nucleotide polymorphisms were rare but interestingly occurred in sequences of genes that also tended to show large differences in expression. Our results show that the striking phenotypic divergence between anadromous and lake alewives can be attributed to massive regulatory modifications rather than coding changes

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

NPR-A regulates self-renewal and pluripotency of embryonic stem cells

Self-renewal and pluripotency of embryonic stem (ES) cells are maintained by several signaling cascades and by expression of intrinsic factors, such as Oct4, Nanog and Sox2. The mechanism regulating these signaling cascades in ES cells is of great interest. Recently, we have demonstrated that natriuretic peptide receptor A (NPR-A), a specific receptor for atrial and brain natriuretic peptides (ANP and BNP, respectively), is expressed in pre-implantation embryos and in ES cells. Here, we examined whether NPR-A is involved in the maintenance of ES cell pluripotency. RNA interference-mediated knockdown of NPR-A resulted in phenotypic changes, indicative of differentiation, downregulation of pluripotency factors (such as Oct4, Nanog and Sox2) and upregulation of differentiation genes. NPR-A knockdown also resulted in a marked downregulation of phosphorylated Akt. Furthermore, NPR-A knockdown induced accumulation of ES cells in the G1 phase of the cell cycle. Interestingly, we found that ANP was expressed in self-renewing ES cells, whereas its level was reduced after ES cell differentiation. Treatment of ES cells with ANP upregulated the expression of Oct4, Nanog and phosphorylated Akt, and this upregulation depended on NPR-A signaling, because it was completely reversed by pretreatment with either an NPR-A antagonist or a cGMP-dependent protein kinase inhibitor. These findings provide a novel role for NPR-A in the maintenance of self-renewal and pluripotency of ES cells

Hybridization thermodynamics of NimbleGen Microarrays

Background While microarrays are the predominant method for gene expression profiling, probe signal variation is still an area of active research. Probe signal is sequence dependent and affected by probe-target binding strength and the competing formation of probe-probe dimers and secondary structures in probes and targets. Results We demonstrate the benefits of an improved model for microarray hybridization and assess the relative contributions of the probe-target binding strength and the different competing structures. Remarkably, specific and unspecific hybridization were apparently driven by different energetic contributions: For unspecific hybridization, the melting temperature Tm was the best predictor of signal variation. For specific hybridization, however, the effective interaction energy that fully considered competing structures was twice as powerful a predictor of probe signal variation. We show that this was largely due to the effects of secondary structures in the probe and target molecules. The predictive power of the strength of these intramolecular structures was already comparable to that of the melting temperature or the free energy of the probe-target duplex. Conclusions This analysis illustrates the importance of considering both the effects of probe-target binding strength and the different competing structures. For specific hybridization, the secondary structures of probe and target molecules turn out to be at least as important as the probe-target binding strength for an understanding of the observed microarray signal intensities. Besides their relevance for the design of new arrays, our results demonstrate the value of improving thermodynamic models for the read-out and interpretation of microarray signals

Improved genetic profiling of anthropometric traits using a big data approach

Genome-wide association studies (GWAS) promised to translate their findings into clinically beneficial improvements of patient management by tailoring disease management to the individual through the prediction of disease risk. However, the ability to translate genetic findings from GWAS into predictive tools that are of clinical utility and which may inform clinical practice has, so far, been encouraging but limited. Here we propose to use a more powerful statistical approach, the use of which has traditionally been limited due to computational requirements and lack of sufficiently large individual level genotyped cohorts, but which improve the prediction of multiple medically relevant phenotypes using the same panel of SNPs. As a proof of principle, we used a shared panel of 319,038 common SNPs with MAF > 0.05 to train the prediction models in 114,264 unrelated White-British individuals for height and four obesity related traits (body mass index, basal metabolic rate, body fat percentage, and waist-to-hip ratio). We obtained prediction accuracies that ranged between 46% and 75% of the maximum achievable given the captured heritable component. For height, this represents an improvement in prediction accuracy of up to 68% (184% more phenotypic variance explained) over SNPs reported to be robustly associated with height in a previous GWAS meta-analysis of similar size. Across-population predictions in White non-British individuals were similar to those in White-British whilst those in Asian and Black individuals were informative but less accurate. We estimate that the genotyping of circa 500,000 unrelated individuals will yield predictions between 66% and 82% of the SNP-heritability captured by common variants in our array. Prediction accuracies did not improve when including rarer SNPs or when fitting multiple traits jointly in multivariate models

Evolutionarily Conserved Transcriptional Co-Expression Guiding Embryonic Stem Cell Differentiation

Understanding the molecular mechanisms controlling pluripotency in embryonic stem cells (ESCs) is of central importance towards realizing their potentials in medicine and science. Cross-species examination of transcriptional co-expression allows elucidation of fundamental and species-specific mechanisms regulating ESC self-renewal or differentiation.We examined transcriptional co-expression of ESCs from pathways to global networks under the framework of human-mouse comparisons. Using generalized singular value decomposition and comparative partition around medoids algorithms, evolutionarily conserved and divergent transcriptional co-expression regulating pluripotency were identified from ESC-critical pathways including ACTIVIN/NODAL, ATK/PTEN, BMP, CELL CYCLE, JAK/STAT, PI3K, TGFbeta and WNT. A set of transcription factors, including FOX, GATA, MYB, NANOG, OCT, PAX, SOX and STAT, and the FGF response element were identified that represent key regulators underlying the transcriptional co-expression. By transcriptional intervention conducted in silico, dynamic behavior of pathways was examined, which demonstrate how much and in which specific ways each gene or gene combination effects the behavior transition of a pathway in response to ESC differentiation or pluripotency induction. The global co-expression networks of ESCs were dominated by highly connected hub genes such as IGF2, JARID2, LCK, MYCN, NASP, OCT4, ORC1L, PHC1 and RUVBL1, which are possibly critical in determining the fate of ESCs.Through these studies, evolutionary conservation at genomic, transcriptomic, and network levels is shown to be an effective predictor of molecular factors and mechanisms controlling ESC development. Various hypotheses regarding mechanisms controlling ESC development were generated, which could be further validated by in vitro experiments. Our findings shed light on the systems-level understanding of how ESC differentiation or pluripotency arises from the connectivity or networks of genes, and provide a "road-map" for further experimental investigation