Biology subjects

Rink, J.

Publications and source records attributed to Rink, J..

8 recordsLinked to original sources

bioRxiv2026

Divergent evolution of the Wnt signaling system in flatworms

Regenerative capacity varies widely across flatworms (Platyhelminthes). Whereas catenulids, microstomids and planarians can regenerate a complete head de novo, other flatworms cannot. This striking diversity raises a longstanding evolutionary question: does whole-body regeneration represent an ancestral trait that was subsequently lost in multiple lineages, or did it evolve convergently? Addressing this question requires comparative analyses of the molecular mechanisms underlying regeneration across phylogenetically diverse flatworms. Here, we focus on Wnt signaling, a deeply conserved regulator of antero-posterior (A-P) patterning and a central determinant of head-versus-tail identity during planarian regeneration, to establish a mechanistic framework for such comparisons. Although Wnt signaling has been studied extensively in planarians and parasitic neodermatans, its evolution and deployment in other flatworm clades remain poorly characterized. To address this gap, we characterized the complement of Wnt signaling components in two early-diverging flatworm clades, Catenulida and Macrostomorpha, with particular emphasis on expression and function in the catenulid Stenostomum brevipharyngium. Phylogenetic analyses reveal the ancient loss of six Wnt families and one secreted Frizzled-related protein (sFRP) family in the last common ancestor of flatworms, followed by additional lineage-specific gene losses and expansions. Moreover, several Wnt pathway components display markedly divergent expression patterns between catenulids and other flatworms, while functional analyses indicate corresponding differences in their regenerative deployment. Together, our findings reveal a dynamic evolutionary history of the flatworm Wnt signaling toolkit and establish a comparative framework for testing whether the molecular circuitry underlying head regeneration is ancestrally conserved or has evolved independently in distinct flatworm lineages.

evolutionary biology↗

bioRxiv2026

Cave-dwelling Planariidae in Croatia exhibit differing levels of cave trait evolution

The Dinaric karst of Croatia encompasses a network of over 10,000 caves and represents one of the worlds most important subterranean biodiversity hotspots. It is inhabited by remarkably diverse and often endemic species, including planarian flatworms, which are among the rarest macroinvertebrates encountered in cave habitats. Although the presence of cave planarians has long been known, no integrative research on this group has been conducted to date, and the evolutionary relationships between these animals and their surface water counterparts are currently unresolved. To address these gaps, we combined field sampling, phylogenetic analysis based on COI and 18S genes, and phenotypic characterization. Our results show that cave planariids in Croatia belong to at least three genera and are more widespread and diverse across both Croatia, and the broader Dinaric karst, than previously assumed. We increased the number of cave records in the Dinaric karst from 26 to 37 and documented cf. Atrioplanaria and Phagocata in Croatian caves for the first time. Phylogenetic reconstructions suggest numerous independent cave colonization events, including multiple instances within the genera Crenobia and cf. Atrioplanaria. Variation in pigmentation and eye reduction, both within and between populations, further reveal heterogeneous evolutionary trajectories of cave-associated phenotypes. The biogeographical patterns and high genetic diversity we report here point to a complex evolutionary history of planariids in the Dinarides. Our newly generated molecular phylogenies and systematic documentation of trait variability establish Planariidae as a valuable model for studying mechanisms underlying convergent evolution of pigment loss and eye reduction in cave environments.

zoology↗

bioRxiv2025

Single-Cell Epigenomics Uncovers Heterochromatin Instability and Transcription Factor Dysfunction during Mouse Brain Aging

The mechanisms regulating transcriptional changes in brain aging remain poorly understood. Here, we use single-cell epigenomics to profile chromatin accessibility and gene expression across eight brain regions in the mouse brain at 2, 9, and 18 months of age. In addition to a significant decline in progenitor cell populations involved in neurogenesis and myelination, we observed widespread and concordant changes of transcription and chromatin accessibility during aging in glial and neuronal cell types. These alterations are accompanied by dysregulation of master transcription factors and a shift toward stress-responsive programs driven by AP-1, indicating a progressive loss of cell identity with aging. We also identify region- and cell-type-specific heterochromatin decay, characterized by increased accessibility at H3K9me3-marked domains, activation of transposable elements, and upregulation of long non-coding RNAs, particularly in glutamatergic neurons. Together, these results reveal age-related disruption of heterochromatin maintenance and transcriptional programs, identify vulnerable brain regions and cell types, and pinpoint key molecular pathways altered in brain aging. HighlightsO_LISingle-cell multimodal profiling across eight brain regions reveals coordinated chromatin and transcriptional shifts during aging C_LIO_LIAge-related depletion of progenitor cells coincides with dysregulation of key developmental transcription factors C_LIO_LICell identity maintenance is compromised with the decline of master transcription factors C_LIO_LIHeterochromatin destabilization accompanied by activation of AP-1, transposable elements, pseudogene families, and long non-coding RNAs C_LI

genomics↗

bioRxiv2025

Cell-type-specific transposable element demethylation and TAD remodeling in the aging mouse brain

Aging is a major risk factor for neurodegenerative diseases, yet underlying epigenetic mechanisms remain unclear. Here, we generated a comprehensive single-nucleus cell atlas of brain aging across multiple brain regions, comprising 132,551 single-cell methylomes and 72,666 joint chromatin conformation-methylome nuclei. Integration with companion transcriptomic and chromatin accessibility data yielded a cross-modality taxonomy of 36 major cell types. We observed that age-related methylation changes were more pronounced in non-neuronal cells. Transposable element methylation alone distinguished age groups, showing cell-type-specific genome-wide demethylation. Chromatin conformation analysis demonstrated age-related increases in TAD boundary strength with enhanced accessibility at CTCF binding sites. Spatial transcriptomics across 895,296 cells revealed regional heterogeneity during aging within identical cell types. Finally, we developed novel deep-learning models that accurately predict age-related gene expression changes using multi-modal epigenetic features, providing mechanistic insights into gene regulation. This dataset advances our understanding of brain aging and offers potential translational applications. HighlightsO_LISingle-cell multi-omic profiling maps the epigenetic and spatial transcriptomic landscape of brain aging across multiple regions. C_LIO_LICell-type-specific genome-wide demethylation of retrotransposable elements correlates with increased chromatin accessibility and expression. C_LIO_LIElevated TAD boundary strength emerges as a unique marker of brain aging associated with CTCF gaining accessibility. C_LIO_LIA novel deep-learning model reveals the significance of epigenetic features on age-related transcriptomic changes across genes. C_LI

genomics↗

bioRxiv2023

Brain-wide Correspondence Between Neuronal Epigenomics and Long-Distance Projections

Single-cell genetic and epigenetic analyses parse the brains billions of neurons into thousands of "cell-type" clusters, each residing in different brain structures. Many of these cell types mediate their unique functions by virtue of targeted long-distance axonal projections to allow interactions between specific cell types. Here we have used Epi-Retro-Seq to link single cell epigenomes and associated cell types to their long-distance projections for 33,034 neurons dissected from 32 different source regions projecting to 24 different targets (225 source [->]target combinations) across the whole mouse brain. We highlight uses of this large data set for interrogating both overarching principles relating projection cell types to their transcriptomic and epigenomic properties and for addressing and developing specific hypotheses about cell types and connections as they relate to genetics. We provide an overall synthesis of the data set with 926 statistical comparisons of the discriminability of neurons projecting to each target for every dissected source region. We integrate this dataset into the larger, annotated BICCN cell type atlas composed of millions of neurons to link projection cell types to consensus clusters. Integration with spatial transcriptomic data further assigns projection-enriched clusters to much smaller source regions than afforded by the original dissections. We exemplify these capabilities by presenting in-depth analyses of neurons with identified projections from the hypothalamus, thalamus, hindbrain, amygdala, and midbrain to provide new insights into the properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription factor binding motifs, and neurotransmitter usage.

neuroscience↗

bioRxiv2023

Single-cell DNA Methylome and 3D Multi-omic Atlas of the Adult Mouse Brain

Cytosine DNA methylation is essential in brain development and has been implicated in various neurological disorders. A comprehensive understanding of DNA methylation diversity across the entire brain in the context of the brains 3D spatial organization is essential for building a complete molecular atlas of brain cell types and understanding their gene regulatory landscapes. To this end, we employed optimized single-nucleus methylome (snmC-seq3) and multi-omic (snm3C-seq1) sequencing technologies to generate 301,626 methylomes and 176,003 chromatin conformation/methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell type taxonomy that contains 4,673 cell groups and 261 cross-modality-annotated subclasses. We identified millions of differentially methylated regions (DMRs) across the genome, representing potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide multiplexed error-robust fluorescence in situ hybridization (MERFISH2) data validated the association of this spatial epigenetic diversity with transcription and allowed the mapping of the DNA methylation and topology information into anatomical structures more precisely than our dissections. Furthermore, multi-scale chromatin conformation diversities occur in important neuronal genes, highly associated with DNA methylation and transcription changes. Brain-wide cell type comparison allowed us to build a regulatory model for each gene, linking transcription factors, DMRs, chromatin contacts, and downstream genes to establish regulatory networks. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a companion whole-brain SMART-seq3 dataset. Our study establishes the first brain-wide, single-cell resolution DNA methylome and 3D multi-omic atlas, providing an unparalleled resource for comprehending the mouse brains cellular-spatial and regulatory genome diversity.

genomics↗

bioRxiv2022

Epigenomic complexity of the human brain revealed by single-cell DNA methylomes and 3D genome structures

Delineating the gene regulatory programs underlying complex cell types is fundamental for understanding brain functions in health and disease. Here, we comprehensively examine human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in over 500,000 cells from 46 brain regions. We identified 188 cell types and characterized their molecular signatures. Integrative analyses revealed concordant changes in DNA methylation, chromatin accessibility, chromatin organization, and gene expression across cell types, cortical areas, and basal ganglia structures. With these resources, we developed scMCodes that reliably predict brain cell types using their methylation status at select genomic sites. This multimodal epigenomic brain cell atlas provides new insights into the complexity of cell type-specific gene regulation in the adult human brain.

neuroscience↗

bioRxiv2017

Content-Aware Image Restoration: Pushing the Limits of Fluorescence Microscopy

Fluorescence microscopy is a key driver of discoveries in the life-sciences, with observable phenomena being limited by the optics of the microscope, the chemistry of the fluorophores, and the maximum photon exposure tolerated by the sample. These limits necessitate trade-offs between imaging speed, spatial resolution, light exposure, and imaging depth. In this work we show how image restoration based on deep learning extends the range of biological phenomena observable by microscopy. On seven concrete examples we demonstrate how microscopy images can be restored even if 60-fold fewer photons are used during acquisition, how near isotropic resolution can be achieved with up to 10-fold under-sampling along the axial direction, and how tubular and granular structures smaller than the diffraction limit can be resolved at 20-times higher frame-rates compared to state-of-the-art methods. All developed image restoration methods are freely available as open source software in Python, FO_SCPLOWIJIC_SCPLOW, and KO_SCPLOWNIMEC_SCPLOW.

bioinformatics↗