The Aarhus red giants challenge: II. Stellar oscillations in the red giant branch phase

[Contact] The large quantity of high-quality asteroseismic data that have been obtained from space-based photometric missions and the accuracy of the resulting frequencies motivate a careful consideration of the accuracy of computed oscillation frequencies of stellar models, when applied as diagnostics of the model properties.[Aims] Based on models of red-giant stars that have been independently calculated using different stellar evolution codes, we investigate the extent to which the differences in the model calculation affect the model oscillation frequencies and other asteroseismic diagnostics.[Methods] For each of the models, which cover four different masses and different evolution stages on the red-giant branch, we computed full sets of low-degree oscillation frequencies using a single pulsation code and, from these frequencies, typical asteroseismic diagnostics. In addition, we carried out preliminary analyses to relate differences in the oscillation properties to the corresponding model differences.[Results] In general, the differences in asteroseismic properties between the different models greatly exceed the observational precision of these properties. This is particularly true for the nonradial modes whose mixed acoustic and gravity-wave character makes them sensitive to the structure of the deep stellar interior and, hence, to details of their evolution. In some cases, identifying these differences led to improvements in the final models presented here and in Paper I; here we illustrate particular examples of this.[Conclusions] Further improvements in stellar modelling are required in order fully to utilise the observational accuracy to probe intrinsic limitations in the modelling and improve our understanding of stellar internal physics. However, our analysis of the frequency differences and their relation to stellar internal properties provides a striking illustration of the potential, in particular, of the mixed modes of red-giant stars for the diagnostics of stellar interiors.Funding for the Stellar Astrophysics Centre is provided by The Danish National Research Foundation (Grant agreement No. DNRF106). The research was supported by the ASTERISK project (ASTERoseismic Investigations with SONG and Kepler) funded by the European Research Council (Grant agreement No. 267864). This research was supported in part by the National Science Foundation under Grant No. NSF PHY-1748958. VSA acknowledges support from VILLUM FONDEN (research grant 10118) and the Independent Research Fund Denmark (Research grant 7027-00096B). DS is the recipient of an Australian Research Council Future Fellowship (project number FT1400147). SC acknowledges support from Premiale INAF MITiC, from INAF “Progetto mainstream” (PI: S. Cassisi), and grant AYA2013-42781P from the Ministry of Economy and Competitiveness of Spain. AMS is partially supported by grants ESP2017-82674-R (Spanish Government) and 2017-SGR-1131 (General-itat de Catalunya). TC acknowledges support from the European Research Council AdG No 320478-TOFU and the STFC Consolidated Grant ST/R000395/1. SH received funding for this research from the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no 338251 (StellarAges). AM acknowledges the support of the Government of India, Department of Atomic Energy, under Project No. 12-R&D-TFR-6.04-0600. DB is supported in the form of work contract FCT/MCTES through national funds and by FEDER through COMPETE2020 in connection to these grants: UID/FIS/04434/2019; PTDC/FIS-AST/30389/2017 & POCI-01-0145-FEDER-030389

The Aarhus red giants challenge: II. Stellar oscillations in the red giant branch phase

Contact. The large quantity of high-quality asteroseismic data that have been obtained from space-based photometric missions and the accuracy of the resulting frequencies motivate a careful consideration of the accuracy of computed oscillation frequencies of stellar models, when applied as diagnostics of the model properties. Aims. Based on models of red-giant stars that have been independently calculated using different stellar evolution codes, we investigate the extent to which the differences in the model calculation affect the model oscillation frequencies and other asteroseismic diagnostics. Methods. For each of the models, which cover four different masses and different evolution stages on the red-giant branch, we computed full sets of low-degree oscillation frequencies using a single pulsation code and, from these frequencies, typical asteroseismic diagnostics. In addition, we carried out preliminary analyses to relate differences in the oscillation properties to the corresponding model differences. Results. In general, the differences in asteroseismic properties between the different models greatly exceed the observational precision of these properties. This is particularly true for the nonradial modes whose mixed acoustic and gravity-wave character makes them sensitive to the structure of the deep stellar interior and, hence, to details of their evolution. In some cases, identifying these differences led to improvements in the final models presented here and in Paper I; here we illustrate particular examples of this. Conclusions. Further improvements in stellar modelling are required in order fully to utilise the observational accuracy to probe intrinsic limitations in the modelling and improve our understanding of stellar internal physics. However, our analysis of the frequency differences and their relation to stellar internal properties provides a striking illustration of the potential, in particular, of the mixed modes of red-giant stars for the diagnostics of stellar interiors. © ESO 2020

Droplet-based single-cell total RNA-seq reveals differential non-coding expression and splicing patterns during mouse development

In recent years, single-cell transcriptome sequencing has revolutionized biology, allowing for the unbiased characterization of cellular subpopulations. However, most methods amplify the termini of polyadenylated transcripts capturing only a small fraction of the total cellular transcriptome. This precludes the detection of many long non-coding, short non-coding and non-polyadenylated protein-coding transcripts. Additionally, most workflows do not sequence the full transcript hindering the analysis of alternative splicing. We therefore developed VASAseq to detect the total transcriptome in single cells. VASA-seq is compatible with both platebased formats and droplet microfluidics. We applied VASA-seq to over 30,000 single cells in the developing mouse embryo during gastrulation and early organogenesis. The dynamics of the total single-cell transcriptome result in the discovery of novel cell type markers, many based on non-coding RNA, an in vivo cell cycle analysis and an improved RNA velocity characterization. Moreover, it provides the first comprehensive analysis of alternative splicing during mammalian development.BBSRC studentship to Joachim de Jongh

High-throughput total RNA sequencing in single cells using VASA-seq.

Most methods for single-cell transcriptome sequencing amplify the termini of polyadenylated transcripts, capturing only a small fraction of the total cellular transcriptome. This precludes the detection of many long non-coding, short non-coding and non-polyadenylated protein-coding transcripts and hinders alternative splicing analysis. We, therefore, developed VASA-seq to detect the total transcriptome in single cells, which is enabled by fragmenting and tailing all RNA molecules subsequent to cell lysis. The method is compatible with both plate-based formats and droplet microfluidics. We applied VASA-seq to more than 30,000 single cells in the developing mouse embryo during gastrulation and early organogenesis. Analyzing the dynamics of the total single-cell transcriptome, we discovered cell type markers, many based on non-coding RNA, and performed in vivo cell cycle analysis via detection of non-polyadenylated histone genes. RNA velocity characterization was improved, accurately retracing blood maturation trajectories. Moreover, our VASA-seq data provide a comprehensive analysis of alternative splicing during mammalian development, which highlighted substantial rearrangements during blood development and heart morphogenesis

Trajectories of cell-cycle progression from fixed cell populations

An accurate dissection of sources of cell-to-cell variability is crucial for quantitative biology at the single-cell level but has been challenging for the cell cycle. We present Cycler, a robust method that constructs a continuous trajectory of cell-cycle progression from images of fixed cells. Cycler handles heterogeneous microenvironments and does not require perturbations or genetic markers, making it generally applicable to quantifying multiple sources of cell-to-cell variability in mammalian cells

Cell-intrinsic adaptation of lipid composition to local crowding drives social behaviour

Cells sense the context in which they grow to adapt their phenotype and allow multicellular patterning by mechanisms of autocrine and paracrine signalling. However, patterns also form in cell populations exposed to the same signalling molecules and substratum, which often correlate with specific features of the population context of single cells, such as local cell crowding. Here we reveal a cell-intrinsic molecular mechanism that allows multicellular patterning without requiring specific communication between cells. It acts by sensing the local crowding of a single cell through its ability to spread and activate focal adhesion kinase (FAK, also known as PTK2), resulting in adaptation of genes controlling membrane homeostasis. In cells experiencing low crowding, FAK suppresses transcription of the ABC transporter A1 (ABCA1) by inhibiting FOXO3 and TAL1. Agent-based computational modelling and experimental confirmation identified membrane-based signalling and feedback control as crucial for the emergence of population patterns of ABCA1 expression, which adapts membrane lipid composition to cell crowding and affects multiple signalling activities, including the suppression of ABCA1 expression itself. The simple design of this cell-intrinsic system and its broad impact on the signalling state of mammalian single cells suggests a fundamental role for a tunable membrane lipid composition in collective cell behaviour