Multi-species atlas resolves an axolotl limb development and regeneration paradox

Zhong, Junyan; Aires, Rita; Tsissios, Georgios; Skoufa, Evangelia; Brandt, Kerstin; Sandoval-Guzmán, Tatiana; Aztekin, Can

doi:10.1101/2023.03.01.530572

Cited by 2 publications

(2 citation statements)

References 64 publications

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“…One of the key features in spVIPES is its ability to integrate datasets with non-matching features. Transcriptomics datasets from different species are integrated based on their shared feature space, inferred from ortholog relationships between the genes 25 . Incorporating more complex relationships between genes across different species has been shown to improve cell type matching 19 .…”

Section: Resultsmentioning

confidence: 99%

Integrative learning of disentangled representations from single-cell RNA-sequencing datasets

Novella-Rausell,

Peters,

Mahfouz

2023

Preprint

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Single-cell RNA-sequencing is instrumental in studying cellular diversity in biological systems. Using batch correction methods, cell identities are often jointly defined across multiple conditions, individuals, or modalities. These approaches overlook group-specific information and require either paired data or matching features across datasets. Here we present shared-private Variational Inference via Product of Experts with Supervision (spVIPES), a framework to analyze the shared and private components of unpaired groups of cells with non-matching features. spVIPES represents the cells from the different groups as a composite of private and shared factors of variation using a probabilistic latent variable model. We evaluate the performance of spVIPES with a simulated dataset and apply our model in three different scenarios: (i) cross-species comparisons, (ii) regeneration following long and short acute kidney injury, and (iii) IFN-βstimulation of PMBCs. In our study, we demonstrate that spVIPES accurately disentangles distinct sources of variation into private and shared representations while matching current state-of-the-art methods for batch correction. Furthermore, spVIPES’ shared space outperforms alternatives models at learning cell identities across datasets with non-matching features. We implemented spVIPES using thescvi-toolsframework and release it as an open-source software athttps://github.com/nrclaudio/spVIPES.

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Section: Resultsmentioning

confidence: 99%

Integrative learning of disentangled representations from single-cell RNA-sequencing datasets

Novella-Rausell,

Peters,

Mahfouz

2023

Preprint

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“…Efforts to regenerate mammalian limbs or digits have focused on transplanting limb bud mesoderm with limited success 9,38 . Meanwhile, the effectiveness of specialized signaling centers 39 , and particularly AER cells 40,41 , has been emphasized in amphibian regeneration. Therefore, our methods robustly forming specialized signaling center AER-like cells, and other limb cell types could be foundational in fundamental regeneration research, as well as transplantation studies aimed at inducing blastema for mammalian regeneration.…”

Section: Discussionmentioning

confidence: 99%

Specialized signaling centers direct cell fate and spatial organization in a limb organoid model

Skoufa,

Zhong,

Kahre

et al. 2024

Preprint

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Specialized signaling centers orchestrate robust development and regeneration. Limb morphogenesis, for instance, requires interactions between the mesoderm and the signaling center apical-ectodermal ridge (AER), whose properties and role in cell fate decisions have remained challenging to dissect. To tackle this, we developed mouse embryonic stem cells (mESCs)-based heterogeneous cultures and a limb organoid model, termed budoids, comprising cells with AER, surface ectoderm, and mesoderm properties. mESCs were first induced into heterogeneous cultures that self-organized into domes in 2D. Aggregating these cultures resulted in formation of limb bud-like structures in 3D, exhibiting chondrogenesis-based symmetry breaking and elongation. Using our organoids and quantitative in situ expression profiling, we uncovered that AER-like cells support nearby limb mesoderm and fibroblast identities while enhancing tissue polarization that permits distant cartilage formation. Together, our findings provide a powerful model to study aspects of limb morphogenesis, and reveal the ability of signaling center AER cells to concurrently modulate cell fate and spatial organization.

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Multi-species atlas resolves an axolotl limb development and regeneration paradox

Cited by 2 publications

References 64 publications

Integrative learning of disentangled representations from single-cell RNA-sequencing datasets

Integrative learning of disentangled representations from single-cell RNA-sequencing datasets

Specialized signaling centers direct cell fate and spatial organization in a limb organoid model

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