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Results for “developmental biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 433 records · Page 24Linked to original sources

bioRxiv2019

Pan-cancer classifications of tumor histological images using deep learning

Histopathological images are a rich but incompletely explored data type for studying cancer. Manual inspection is time consuming, making it challenging to use for image data mining. Here we show that convolutional neural networks (CNNs) can be systematically applied across cancer types, enabling comparisons to reveal shared spatial behaviors. We develop CNN architectures to analyze 27,815 hematoxylin and eosin slides from The Cancer Genome Atlas for tumor/normal, cancer subtype, and mutation classification. Our CNNs are able to classify tumor/normal status of whole slide images (WSIs) in 19 cancer types with consistently high AUCs (0.995{+/-}0.008), as well as subtypes with lower but significant accuracy (AUC 0.87{+/-}0.1). Remarkably, tumor/normal CNNs trained on one tissue are effective in others (AUC 0.88{+/-}0.11), with classifier relationships also recapitulating known adenocarcinoma, carcinoma, and developmental biology. Moreover, classifier comparisons reveal intra-slide spatial similarities, with average tile-level correlation of 0.45{+/-}0.16 between classifier pairs. Breast cancers, bladder cancers, and uterine cancers have spatial patterns that are particularly easy to detect, suggesting these cancers can be canonical types for image analysis. Patterns for TP53 mutations can also be detected, with WSI self- and cross-tissue AUCs ranging from 0.65-0.80. Finally, we comparatively evaluate CNNs on 170 breast and colon cancer images with pathologist-annotated nuclei, finding that both cellular and intercellular regions contribute to CNN accuracy. These results demonstrate the power of CNNs not only for histopathological classification, but also for cross-comparisons to reveal conserved spatial biology.

bioinformatics↗

bioRxiv2019

Distinct modes of cell competition are governed by entropic and energetic properties of mixed cell populations

How cells with different genetic makeups compete in tissues is an outstanding question in developmental biology and cancer research. Studies in recent years have revealed that cell competition can either be driven by short-range biochemical signalling or by long-range mechanical stresses in the tissue. To date, cell competition has generally been characterised at the population-scale, leaving the single-cell level mechanisms of competition elusive. Here, we use high time-resolution experimental data to construct a multi-scale agent-based model for epithelial cell competition, and use it to gain a conceptual understanding of the cellular factors that governs competition in cell populations within tissues. We find that a key determinant of mechanical competition is the difference in homeostatic density between winners and losers, while differences in growth rates and tissue organisation do not affect competition end-result. In contrast, the outcome and kinetics of biochemical competition is strongly influenced by local tissue organisation. Indeed, when loser cells are homogenously mixed with winners at the onset of competition, they are eradicated; however, when they are spatially separated, winner and loser cells coexist for long times. These findings suggest distinct biophysical origins for mechanical and biochemical modes of cell competition.

biophysics↗

bioRxiv2019

Chytrid rhizoid morphogenesis is adaptive and resembles hyphal development in ‘higher’ fungi

Fungi are major components of the Earths biosphere [1], sustaining many critical ecosystem processes [2, 3]. Key to fungal prominence is their characteristic cell biology, our understanding of which has been principally based on higher dikaryan hyphal and yeast forms [4-6]. The early-diverging Chytridiomycota (chytrids) are ecologically important [2, 7, 8] and a significant component of fungal diversity [9-11], yet their cell biology remains poorly understood. Unlike dikaryan hyphae, chytrids typically attach to substrates and feed osmotrophically via anucleate rhizoids [12]. The evolution of fungal hyphae appears to have occurred from lineages exhibiting rhizoidal growth [13] and it has been hypothesised that a rhizoid-like structure was the precursor to multicellular hyphae and mycelial feeding in fungi [14]. Here we show in a unicellular chytrid, Rhizoclosmatium globosum, that rhizoid development has equivalent features to dikaryan hyphae and is adaptive to resource availability. Rhizoid morphogenesis exhibits analogous properties with growth in hyphal forms, including tip production, branching and decreasing fractal geometry towards the growing edge, and is controlled by {beta}-glucan-dependent cell wall synthesis and actin polymerisation. Chytrid rhizoids from individual cells also demonstrate adaptive morphological plasticity in response to substrate availability, developing a searching phenotype when carbon starved and exhibiting spatial differentiation when interacting with particulate substrates. Our results show striking similarities between unicellular early-diverging and dikaryan fungi, providing insights into chytrid cell biology, ecological prevalence and fungal evolution. We demonstrate that the sophisticated cell biology and developmental plasticity previously considered characteristic of hyphal fungi are shared more widely across the Kingdom Fungi and therefore could be conserved from their most recent common ancestor.

developmental biology↗

bioRxiv2019

Embryonic and foetal expression patterns of the ciliopathy gene CEP164

Nephronophthisis-related ciliopathies (NPHP-RC) are a group of inherited genetic disorders that share a defect in the formation, maintenance or functioning of the primary cilium complex, causing progressive kidney failure and other clinical manifestations. Mutations in centrosomal protein 164 kDa (CEP164), also known as NPHP15, have been identified as a cause of NPHP-RC. Here we have utilised the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) to perform immunohistochemistry studies on human embryonic and foetal tissues to determine the expression patterns of CEP164 during development. Notably expression is widespread, yet defined, in multiple organs including the kidney, retina and cerebellum. Murine studies demonstrated an almost identical Cep164 expression pattern. Taken together, this data supports conserved roles for CEP164 throughout the development of numerous organs, which we suggest accounts for the multi-system disease phenotype of CEP164 mediated NPHP-RC.

genetics↗

bioRxiv2019

Comparative single-cell transcriptomics of complete insect nervous systems

Molecular profiles of neurons influence information processing, but bridging the gap between genes, circuits, and behavior has been very difficult. Furthermore, the behavioral state of an animal continuously changes across development and as a result of sensory experience. How behavioral state influences molecular cell state is poorly understood. Here we present a complete atlas of the Drosophila larval central nervous system composed of over 200,000 single cells across four developmental stages. We develop polyseq, a python package, to perform cell-type analyses. We use single-molecule RNA-FISH to validate our scRNAseq findings. To investigate how internal state affects cell state, we optogentically altered internal state with high-throughput behavior protocols designed to mimic wasp sting and over activation of the memory system. We found nervous system-wide and neuron-specific gene expression changes. This resource is valuable for developmental biology and neuroscience, and it advances our understanding of how genes, neurons, and circuits generate behavior.

neuroscience↗

bioRxiv2019

High-Spatial-Resolution Multi-Omics Atlas Sequencing of Mouse Embryos via Deterministic Barcoding in Tissue

We present DBiT-seq -Deterministic Barcoding in Tissue for spatial omics sequencing - for co-mapping of mRNAs and proteins in a formaldehyde-fixed tissue slide via NGS sequencing. Parallel microfluidic channels were used to deliver DNA barcodes to the surface of a tissue slide and crossflow of two sets of barcodes A1-50 and B1-50 followed by ligation in situ yielded a 2D mosaic of tissue pixels, each containing a unique full barcode AB. Application to mouse embryos revealed major tissue types in early organogenesis as well as fine features like microvasculature in a brain and pigmented epithelium in an eye field. Gene expression profiles in 10m pixels conformed into the clusters of single-cell transcriptomes, allowing for rapid identification of cell types and spatial distributions. DBiT-seq can be adopted by researchers with no experience in microfluidics and may find applications in a range of fields including developmental biology, cancer biology, neuroscience, and clinical pathology. In BriefMicrofluidic deterministic barcoding of mRNAs and proteins in tissue slides followed by high-throughput sequencing enables the construction of a high-spatial-resolution multi-omics atlas at the genome scale. Application to mouse embryos (E10-12) identified major tissue types in early organogenesis and revealed fine tissue features such as retinal pigmented epithelium and endothelial microvasculature at the cellular level. HighlightsO_LIDeterministic barcoding in tissue enables NGS-based spatial multi-omics mapping. C_LIO_LIDBiT-seq identified spatial patterning of major tissue types in mouse embryos. C_LIO_LIDBiT-seq revealed fine features such as retinal pigmented epithelium and microvascular endothelium at the cellular level. C_LIO_LIDirect integration with scRNA-seq data allows for rapid cell type identification. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/788992v2_ufig1.gif" ALT="Figure 1"> View larger version (77K): org.highwire.dtl.DTLVardef@41d937org.highwire.dtl.DTLVardef@11bdc46org.highwire.dtl.DTLVardef@1aa143org.highwire.dtl.DTLVardef@51755c_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2019

GAL4/GFP enhancer-trap lines for identification and manipulation of cells and tissues in developing Arabidopsis leaves

Understanding developmental processes requires the unambiguous identification of cells and tissues, and the selective manipulation of the properties of those cells and tissues. Both requirements can most efficiently be satisfied through the use of GAL4/GFP enhancer-trap lines. No such lines are available, however, for the study of leaf development in the Columbia-0 reference genotype of Arabidopsis. Here we address this limitation by identifying and characterizing a set of GAL4/GFP enhancer-trap lines in the Columbia-0 background for the specific labeling of cells and tissues during leaf development, and for the targeted expression of genes of interest in those cells and tissues. By using one line in our set to resolve outstanding problems in leaf vein patterning, we show that these lines can be used to address key questions in plant developmental biology.

plant biology↗

bioRxiv2019

Integrative analyses of the RNA modification machinery reveal tissue- and cancer-specific signatures

BackgroundRNA modifications play central roles in cellular fate and differentiation. These features have placed the epitranscriptome in the forefront of developmental biology and cancer research. However, the machinery responsible for placing, removing and recognizing more than 170 RNA modifications remains largely uncharacterized and poorly annotated, and we currently lack integrative studies that identify which RNA modification-related proteins (RMPs) may be dysregulated in each cancer type. ResultsHere we have performed a comprehensive annotation and evolutionary analysis of human RMPs as well as an integrative analysis of their expression patterns across 32 tissues, 10 species and 13,358 paired tumor-normal human samples. Our analysis reveals an unanticipated heterogeneity of RMP expression patterns across mammalian tissues, with a vast proportion of duplicated enzymes displaying testis-specific expression, suggesting a key role for RNA modifications in sperm formation and possibly intergenerational inheritance. Moreover, through the analysis of paired tumor-normal human samples we uncover many RMPs that are dysregulated in various types of cancer, and whose expression levels are predictive of cancer progression. Surprisingly, we find that several commonly studied RNA modification enzymes such as METTL3 or FTO, are not significantly up-regulated in most cancer types, once the sample is properly scaled and normalized to the full dataset, whereas several less-characterized RMPs, such as LAGE3 and HENMT1, are dysregulated in many cancers. ConclusionsOur analyses reveal an unanticipated heterogeneity in the expression patterns of RMPs across mammalian tissues, and uncover a large proportion of dysregulated RMPs in multiple cancer types. We provide novel targets for future cancer research studies targeting the human epitranscriptome, as well as foundations to understand cell type-specific behaviours that are orchestrated by RNA modifications.

molecular biology↗

bioRxiv2019

Regeneration comes for free with biological development in a generative Boolean model

BackgroundMulticellular organisms are characterized by a wide diversity of forms and complexity despite a restricted set of key molecules and mechanisms at the base of organismal development. Development combines three basic processes -- asymmetric cell division, signaling and gene regulation -- in a multitude of ways to create this overwhelming diversity of multicellular life-forms. Here, we use a generative model to test the limits to which such processes can be combined to generate multiple differentiation paths during development, and attempt to chart the diversity of multicellular organisms generated. ResultsWe sample millions of biologically feasible developmental schemes, allowing us to comment on the statistical properties of cell-differentiation trajectories they produce. We characterize model-generated organisms using the graph topology of their cell-type lineage maps. Remarkably, tree-type lineage differentiation maps are the rarest in our data. Additionally, a majority of the organisms generated by our model appear to be endowed with the ability to regenerate using pluripotent cells. ConclusionsOur results indicate that, in contrast to common views, cell-type lineage graphs are unlikely to be tree-like. Instead, they are more likely to be directed acyclic graphs, with multiple lineages converging on the same terminal cell-type. Furthermore, the high incidence of pluripotent cells in model-generated organisms stands in line with the long-standing hypothesis that whole body regeneration is an epiphenomenon of development. We discuss experimentally testable predictions of our model, and some ways to adapt the generative framework to test additional hypotheses about general features of development.

developmental biology↗

bioRxiv2025

Harnessing anti-CRISPR to suppress, subtract, and segregate Cas9 activity for precision CRISPR in Drosophila

Tissue-specific CRISPR (ts-CRISPR) is a powerful approach for studying cell and developmental biology by restricting mutagenesis to specific tissues. However, the precision of this approach is often compromised by non-specific, "leaky" Cas9 activity that confounds phenotypic analysis and destabilizes Cas9/gRNA stocks. To address these limitations in Drosophila, we developed a toolkit based on the Anti-CRISPR (Acr) protein AcrIIA4. We first identified AcrIIA4 as a potent in vivo Cas9 inhibitor with high stability and established the temporal requirements for its function. Based on these findings, we generated three classes of Acr tools. First, a collection of AcrIIA4-bearing balancers robustly suppresses Cas9 and enables the stable maintenance of complex Cas9/gRNA stocks. Importantly, maternal deposition of AcrIIA4 from these balancers provides a means of temporal control, delaying Cas9 activity until metamorphosis. Second, tissue-specific AcrIIA4 transgenes refine leaky Cas9 drivers in a "tissue-subtraction" strategy. Finally, germline-specific and soma-specific Acr tools efficiently segregate Cas9 activity, solving bidirectional leakiness between these two compartments. This comprehensive AcrIIA4 toolkit provides new levels of precision, versatility, and temporal control for Drosophila CRISPR applications.

genetics↗

bioRxiv2026

Rethinking yield stability through phenotypic plasticity and its link to modern statistical methods

In the context of advocacy for yield stability, trade-offs between yield and yield stability, the frequent lack of definitions, and the variation in methods when they are explicit, we connect two perspectives: phenotypic plasticity and factor analytics. Phenotypic plasticity brings over a century of research in developmental biology, ecology and evolution, and is gaining traction in crop science. Factor analytics is an advanced linear mixed model of multi-environment data with factor analytic variance structures for the variety-by-environment interaction effect. We (1) review phenotypic plasticity, define agronomically adaptive plasticity where varieties (or practices) consistently return superior yield (or other traits) across environments with no trade-off, and describe percentile-plasticity plots to assess the agronomic value of plasticity; (2) outline factor analytic models, and (3) link plasticity and factor analytic models mathematically and empirically. We show that phenotypic plasticity of cereal yield correlates positively with overall performance obtained from factor analytic models when plasticity is adaptive and negatively when it is maladaptive. We conclude that phenotypic plasticity contributes biological meaning to opaque analytical approaches, and that biologically grounded statistics are needed to challenge weak agronomic narratives, such as advocacy for stability that might reflect decision biases rather than critical consideration of its benefits. HighlightUncritical advocacy for crop yield stability is common. Here we advance a biological-statistical synthesis of yield stability and test theoretical predictions with actual wheat and oat yield data.

plant biology↗

bioRxiv2026

Intracellular crowding links dimensionality to cell fate through a mechano-metabolic signalling axis

Three-dimensional (3D) cell culture systems exhibit more native-like cell behaviour compared to conventional two-dimensional (2D) cell culture systems. However, it remains largely unknown how dimensionality alters cell behaviour. Here, we identify intracellular crowding as a key biophysical parameter altered by cell culture dimensionality, which directs cell fate over a mechano-metabolic axis. Specifically, culture dimensionality controlled intracellular crowding by altering cell volume, which was confirmed across multiple cell types and cell culture platforms. Using chondrogenesis as a model system, we demonstrated that dimensionality-induced intracellular changes lead to improved chondrogenic stem cell differentiation in microtissue culture via a FOXO1 signalling axis. Our findings highlight intracellular crowding as an important parameter of cell culture systems, and present a novel strategy for engineering biomimetic cell culture systems, which has implications for a multitude of applications including disease modelling, in vitro drug screening models, developmental biology, and cell-based therapies.

cell biology↗

bioRxiv2026

Establishing genetically controlled, closed 1 colonies of an ascidian

Recent technological advances have made many "non-model" organisms accessible for experimental studies. However, reference inbred strains were not necessarily available, especially in marine invertebrates, and genetic background of organisms used for experiments are often non-uniform. This situation potentially affects experimental reproducibility. Although ascidians, Ciona intestinalis (type A, or C. robusta), are a widely used marine animal for many areas of experimental biology including developmental studies, no reference strains have been obtained despite extensive efforts. As an alternative way to improve reproducibility, we have established and maintained ascidian colonies through intra-population breeding every year from 2016 to 2020, and monitored genomic variants of these colonies. This method does not reduce genetic variations but instead manages and monitors genetic variations in the colonies, providing an easy and cost-effective way of increasing experimental reproducibility. Furthermore, we recently upgraded these genetically isolated, closed colonies that were re-established every year, and have maintained them for more than three years only through intra-population breeding and occasional back-cross using cryopreserved sperm. Genetic variants that we revealed using 3.7 tera-bases of sequence data will help to design future experiments in this species. Our data also show that two wild-populations, which were used to establish the colonies, have maintained distinct genetic backgrounds, although their habitats are directly linked to the Pacific Ocean and only 170 km apart. More importantly, genetic information regarding these colonies will undoubtedly improve experimental reproducibility and traceability, and our method will provide a realistic solution for performing reproducible experiments using non-model organisms.

developmental biology↗

bioRxiv2026

LineageSim: A Single-Cell Lineage Simulator with Fate-Aware Gene Expression

Single-cell lineage data paired with gene expression are critical for developing computational methods in developmental biology. Since experimental lineage tracing is often technically limited, robust simulations are necessary to provide the ground truth for rigorous validation. However, existing simulators generate largely Markovian gene expression, failing to encode the fate bias observed in real biological systems, where progenitor states exhibit early signatures of future commitment. Consequently, they cannot support the training and evaluation of computational methods that model long-range temporal dependencies. We present LineageSim, a generative framework that introduces fate-aware gene expression, where progenitor states carry latent signals of their descendants terminal fates. This framework establishes a new class of benchmarks for cell fate prediction algorithms. We validate the presence of these temporal signals by training a logistic regression baseline, which achieves 68.3% balanced accuracy. This confirms that the generated data contain subtle but recoverable fate information, in contrast to existing simulators, where such predictive signals are systematically absent.

bioinformatics↗

bioRxiv2026

Bistability to Quad-stability: Emergence of Hybrid Phenotypes & Enhanced Spatio-temporal Plasticity in Presence of Host-Circuit Coupling

In the context of multistability-driven diseases, like cancer, spatio-temporal plasticity plays a significant role to achieve a spectrum of phenotypic variations. The interplay between gene regulatory networks and environmental factors, such as resource competition and spatial diffusion, plays a crucial role in determining cellular behaviour and phenotypic heterogeneity. Though reaction-diffusion frameworks have been widely applied in developmental biology, less attention has been paid to the simultaneous effects of resource competition and growth feedback on spatial organization. In this paper, we observed that a bistable genetic circuit under high resource competition due to growth feedback gives rise to multiple emergent phenotypes, as observed in cancer systems. Furthermore, we observed how spatial diffusion coupled with intrinsic nonlinearity can drive the emergence of distinct spatial dynamics over time. The observed spatiotemporal plasticity can also be driven by the comparative stability of the fixed points, diffusivity, and asymmetry of diffusion. Our findings highlight that growth-induced resource competition combined with diffusion can provide deeper insights into metastasis and cancer progression.

cancer biology↗

bioRxiv2026

Studies of mice with a large deletion of the ARPKD-associated Pkhd1 locus likely explain its GWAS association with glaucoma in humans

PKHD1, the gene primarily mutated in human autosomal recessive polycystic kidney disease, is one of the top 20 genes associated with primary open angle glaucoma (POAG) and associated endophenotypes in Genome-Wide Association Studies. Here, we show that Pkhd1del3-67/del3-67 mutant mice develop congenital glaucoma due to anterior segment dysgenesis. Using a combination of genetic, epigenetic, bioinformatics and mouse developmental biology approaches, we show that Pkhd1del3-67/del3-67 mice lack Tfap2b and AP-2{beta} expression in a subset of periocular mesenchymal cells at E13.5 and its derivatives. Our data suggest that the Pkhd1del3-67 deletion disrupts features of the Pkhd1-Tfap2b genomic architecture essential for Tfap2b cell-specific activities. Consistent with this model, Pkhd1del3-67/+;Tfap2bko/+trans-heterozygotes lack Tfap2b and AP-2{beta} in relevant cell-types and have similar eye abnormalities as neural crest cell-specific Tfap2bko mutants. These findings provide a likely causal explanation for how SNPs associated with PKHD1 are functionally linked to POAG and add insight into understanding the complexity of disease-causing SNP associations and gene regulatory mechanisms.

genetics↗

bioRxiv2026

Title: Optogenetic WNT signaling drives germ layer self-organization in a human gastruloid model

In vitro stem cell models of human gastrulation have been an advance for developmental biology, though elucidating mechanisms of germ layer formation remains challenging. While investigating whether spatially-patterned signaling is required for germ layer formation, we tested a "salt-and-pepper" signaling strategy in which WNT was optogenetically activated in a subset of human pluripotent stem cells (hPSC) uniformly mixed into an aggregate. Following mesendodermal specification, WNT-activated cells spatially segregated into a hemisphere, then underwent further differentiation and organization into mesoderm and endoderm. RNAseq-based lineage analysis revealed that WNT activation non-autonomously induced TGF{beta}/BMP signaling, leading to robust emergence of an anterior visceral endoderm-like population that patterned adjacent neural and mesendodermal fates. Transcriptional profiles and trajectories closely mirrored those observed during human gastrulation. Moreover, TGF{beta} or cadherin perturbation disrupted germ layer formation or spatial organization, respectively. This simple model thus enables mechanistic dissection of complex human lineage specifications and organization during gastrulation.

bioengineering↗

bioRxiv2026

Decomap-seq enables efficient and reliable retrieval of spatial transcripts

Spatial transcriptomics (ST) has emerged as a transformative tool for resolving the molecular heterogeneity of complex tissues within their native anatomical context. However, next-generation sequencing (NGS)-based ST platforms frequently encounter sensitivity bottlenecks arising from sub-optimal probe architectures on solid substrates. Conventional single-stranded DNA coupling methods often lead to disordered interfacial molecular conformations due to non-specific nucleobase-mediated surface tethering, which creates steric hindrance and inhibits the enzymatic efficiency of in situ library preparation. Here, we present Decomap (double-strand protected combinatorial barcoding microarray chip), a high-performance ST platform utilizing a triple-segment (dsZ-X-Y) fabrication strategy to achieve superior transcript capture efficiency. This structural optimization significantly enhances DNA ligation kinetics and subsequent polymerase-mediated extension, overcoming the fundamental limitations of traditional single-stranded coupling strategies. Decomap-seq achieved a median detection of 7,200 genes and 29,097 UMIs per 50 m-spot at a sequencing saturation of 50.1%. These results validate Decomap as a highly sensitive and robust tool for spatial transcriptomics, offering a powerful platform for advancing research in histopathology, developmental biology, and neuroscience.

biochemistry↗