Biology subjects

Dahl, A.

Publications and source records attributed to Dahl, A..

At least 55 records · Page 3Linked to original sources

bioRxiv2020

Filaggrin deficient mice have a lower threshold for cutaneous allergen sensitization but do not develop spontaneous skin inflammation or atopy

Defects of filaggrin (FLG) compromise epidermal barrier function and represent an important known genetic risk factor for atopic dermatitis (AD), but also for systemic atopy, including allergic sensitization and asthma. The flaky tail mouse model, widely used to address mechanisms of atopy induction by barrier-defective skin, harbors two mutations that affect the skin barrier, the mutation Flgft, resulting in near-complete loss of FLG expression, and the matted mutation inactivating transmembrane protein 79 (Tmem79). Upon separation of the two mutant loci, which are closely linked on chromosome 3, mice defective only for Tmem79 featured pronounced dermatitis and systemic atopy. Upon extensive backcross to BALB/c, also Flgft/ft mice (assumed to be wild type for Tmem79), developed AD-like dermatitis and reproduced the human atopic march, with high IgE levels and spontaneous asthma, suggesting a key role for functional Flg in protection from atopy also in mice. In contrast, BALB/c mice congenic for a targeted Flg knock out mutation did not develop skin inflammation or atopy. To resolve this discrepancy, we generated Flg-deficient mice on a pure BALB/c background by inactivating the Flg gene in BALB/c embryos. These animals feature an ichthyosis phenotype, but do not develop spontaneous dermatitis or systemic atopy. We sequenced the genome of the atopic Flgft BALB/c congenics and discovered that they were unexpectedly homozygous for the atopy-causing Tmem79matted mutation. In summary, we show that Flg-deficiency does not cause atopy in mice. This finding is in line with lack of atopic disease in a fraction of Ichthyosis vulgaris patients carrying two FLG null alleles. However, absence of FLG may promote and modulate dermatitis caused by other genetic barrier defects, as skin inflammation in Tmem79ma/maFlgft/ft BALB/c congenics is qualitatively different compared to Tmem79ma/ma mice.

immunology↗

bioRxiv2020

Hematopoietic lineages diverge within the stem cell compartment

Hematopoietic stem cells (HSCs) produce a highly diverse array of cell lineages. To assay hematopoietic differentiation with minimal experimental perturbation, non-invasive methods for heritable labeling1-3 or barcoding4-7 of HSCs in vivo have recently been developed and used to study lineage fate of HSCs in physiological conditions. However, the differentiation pathways leading from HSCs to mature cells remain controversial8, with suggested models ranging from gradual lineage restriction in a branching cascade of progenitors to HSCs already making ultimate lineage decisions. Here we show, by iterating HSC fate-mapping, mitotic history tracking, single-cell RNA-sequencing and computational inference, that the major differentiation routes to megakaryocytes, erythro-myeloid cells and lymphocytes split within HSCs. We identify the hitherto elusive self-renewing source of physiological hematopoiesis as an HSC subpopulation co-expressing high levels of Sca-1 and CD201. Downstream, HSCs reduce Sca-1 expression and enter into either thrombopoiesis or erythro-myelopoiesis, or retain high Sca-1 levels and the ability to generate lymphocytes. Moreover, we show that a distinct population of CD48-/lo megakaryocyte progenitors links HSCs to megakaryocytes. This direct thrombopoiesis pathway is independent of the classical pathway of megakaryocyte differentiation via multipotent progenitors and becomes the dominant platelet production line upon enhanced thrombopoietin signaling. Our results define a hierarchy of self-renewal and lineage decisions within HSCs in native hematopoiesis. Methodologically, we provide a blueprint for mapping physiological differentiation pathways of stem cells and probing their regulation.

systems biology↗

bioRxiv2020

Coordinated Interaction: A model and test for globally signed epistasis in complex traits

Interactions between genetic variants - epistasis - is pervasive in model systems and can profoundly impact evolutionary adaption, population disease dynamics, genetic mapping, and precision medicine efforts. In this work we develop a model for structured polygenic epistasis, called Coordinated Interaction (CI), and prove that several recent theories of genetic architecture fall under the formal umbrella of CI. Unlike standard polygenic epistasis models that assume interaction and main effects are independent, in the CI model, sets of SNPs broadly interact positively or negatively, on balance skewing the penetrance of main genetic effects. To test for the existence of CI we propose the even-odd (EO) test and prove it is calibrated in a range of realistic biological models. Applying the EO test in the UK Biobank, we find evidence of CI in 14 of 26 traits spanning disease, anthropometric, and blood categories. Finally, we extend the EO test to tissue-specific enrichment and identify several plausible tissue-trait pairs. Overall, CI is a new dimension of genetic architecture that can capture structured, systemic interactions in complex human traits.

genetics↗

bioRxiv2020

Estimating the rate of cell type degeneration from epigenetic sequencing of cell-free DNA

Circulating cell-free DNA (cfDNA) in the bloodstream originates from dying cells and is a promising non-invasive biomarker for cell death. Here, we develop a method to accurately estimate the relative abundances of cell types contributing to cfDNA. We leverage the distinct DNA methylation profile of each cell type throughout the body. Decomposing the cfDNA mixture is difficult, as fragments from relevant cell types may only be present in a small amount. We propose an algorithm, CelFiE, that estimates cell type proportion from both whole genome cfDNA input and reference data. CelFiE accommodates low coverage data, does not rely on CpG site curation, and estimates contributions from multiple unknown cell types that are not available in reference data. In simulations we show that CelFiE can accurately estimate known and unknown cell type of origin of cfDNA mixtures in low coverage and noisy data. Simulations also demonstrate that we can effectively estimate cfDNA originating from rare cell types composing less than 0.01% of the total cfDNA. To validate CelFiE, we use a positive control: cfDNA extracted from pregnant and non-pregnant women. CelFiE estimates a large placenta component specifically in pregnant women (p = 9.1 x 10-5). Finally, we use CelFiE to decompose cfDNA from ALS patients and age matched controls. We find increased cfDNA concentrations in ALS patients (p = 3.0 x 10-3). Specifically, CelFiE estimates increased skeletal muscle component in the cfDNA of ALS patients (p = 2.6 x 10-3), which is consistent with muscle impairment characterizing ALS. Quantification of skeletal muscle death in ALS is novel, and overall suggests that CelFiE may be a useful tool for biomarker discovery and monitoring of disease progression.

genomics↗

bioRxiv2019

Epigenetic rejuvenation of the hippocampus by environmental enrichment

The decline of brain function during aging is associated with epigenetic changes, including DNA methylation. Lifestyle interventions can improve brain function during aging, but their influence on age-related epigenetic changes is unknown. Using genome-wide DNA methylation sequencing, we here show that environmental enrichment counteracted age-related DNA methylation changes in the hippocampal dentate gyrus of mice. Specifically, environmental enrichment prevented the aging-induced CpG hypomethylation at target sites of the methyl-CpG-binding protein Mecp2, which is known to control neuronal functions. The genes at which environmental enrichment counteracted aging effects have described roles in neuronal plasticity, neuronal cell communication and adult hippocampal neurogenesis and are dysregulated with age-related cognitive decline in the human brain. Our results highlight the rejuvenating effects of environmental enrichment at the level of DNA methylation and give molecular insights into the specific aspects of brain aging that can be counteracted by lifestyle interventions.

neuroscience↗

bioRxiv2019

Proliferative behavior of hematopoietic stem cells revisited: No evidence for mitotic memory

The proliferative activity of adult hematopoietic stem cells (HSCs) is controversially discussed. Inducible fluorescent histone 2B fusion protein (H2B-FP) transgenic mice are important tools for tracking the mitotic history of murine HSCs in label dilution experiments. A recent study proposed that the most primitive HSCs divide only four times, to then enter permanent quiescence. We observed that background fluorescence due to leaky H2B-FP expression, occurring in all H2B-FP transgenes independent of label induction, accumulated with age in primitive HSCs with high repopulation potential. We argue that this background had been misinterpreted as retention of induced label and permanent quiescence. We found cell division-independent half-lives of H2B-FPs to be short, which had led to overestimation of HSC divisional activity. Our data do not support HSC mitotic memory and entry into permanent quiescence after few divisions, but show that primitive HSCs of adult mice continue to cycle rarely.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC=\"FIGDIR/small/745729v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (30K):\norg.highwire.dtl.DTLVardef@1b97626org.highwire.dtl.DTLVardef@fbc702org.highwire.dtl.DTLVardef@1c66b60org.highwire.dtl.DTLVardef@1b38f69_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2019

Gene expression-based identification of antigen-responsive CD8+ T cells on a single-cell level

CD8+ T cells are important effectors of adaptive immunity against pathogens, tumors and self antigens. Here, we asked how human cognate antigen-responsive CD8+ T cells and their receptors could be identified in unselected single-cell gene expression data. Single-cell RNA sequencing and qPCR of dye-labelled antigen-specific cells identified large gene sets that were congruently up- or downregulated in virus-responsive CD8+ T cells under different antigen presentation conditions. Combined expression of TNFRSF9, XCL1, XCL2, and CRTAM was the most distinct marker of virus-responsive cells on a single-cell level. Using transcriptomic data, we developed a machine learning-based classifier that provides sensitive and specific detection of virus-responsive CD8+ T cells from unselected populations. Gene response profiles of CD8+ T cells specific for the autoantigen islet-specific glucose-6-phosphatase catalytic subunit-related protein differed markedly from virus-specific cells. These findings provide single-cell gene expression parameters for comprehensive identification of rare antigen-responsive cells and T cell receptors.\n\nOne-sentence summaryIdentification of genes, gene sets, and development of a machine learning-based classifier that distinguishes antigen-responsive CD8+ T cells on a single-cell level.

immunology↗

bioRxiv2019

Universal continuous severity traits underlying hundreds of Parkinson’s disease clinical features

The generation of deeply phenotyped patient cohorts offers an enormous potential to identify disease subtypes but are currently limited by the cohort size and the heterogeneity of the clinical assessments collected across different cohorts. Identifying the universal axes of clinal severity and progression is key to accelerating our understanding of how disease manifests and progresses. These universal axes would accelerate our understanding of how Parkinsons disease (PD) manifests and progresses through which patients may be appropriately compared appropriately stratified, and personalised therapeutic strategies and treatments can be developed and targeted. We developed a Bayesian multiple phenotype mixed model incorporating the genetic relationships between individuals which is able to reduce a wide-array of different clinical measurements into a smaller number of continuous underlying factors named phenotypic axis. We identify three principal axes of PD patient phenotypic variation which are reproducibly found across three independent, deeply and diversely phenotyped cohorts. Together they explain over 75% of the observed clinical variation and remain robustly captured with a fraction of the clinically-recorded features. The most influential axis was associated with the genetic risk of Alzheimers disease (AD) and involves genetic pathways associated with neuroinflammation. Our results suggest PD patients with a high genetic risk for AD are more likely to develop a more aggressive form of PD including, but not limited to, dementia.

neuroscience↗

bioRxiv2019

Redox potential defines functional states of adult hippocampal stem cells

Intracellular redox states regulate the balance between stem cell maintenance and activation. Increased levels of reactive oxygen species (ROS) are linked to proliferation and lineage specification. In contrast to this general principle, we show that in the hippocampus of adult mice it is the quiescent neural stem cells (NSCs) that maintain the highest ROS levels (hiROS). Classifying NSCs based on intracellular ROS content identified subpopulations with distinct molecular profiles, corresponding to functional states. Shifts in ROS content primed cells for a subsequent transition of cellular state, with lower cellular ROS content marking activity and differentiation. Physical activity, a known physiological activator of adult hippocampal neurogenesis, recruited the quiescent hiROS NSCs into proliferation via a transient Nox2-dependent ROS surge. In the absence of Nox2, baseline neurogenesis was unaffected, but the activity-induced increase in proliferation disappeared. These results describe a novel mechanism linking the modulation of cellular ROS by behavioral cues to the maintenance and activation of adult NSCs.\n\nHighlightsO_LIQuiescent adult hippocampal stem cells are characterized by high intracellular ROS\nC_LIO_LIChanges in intracellular ROS content precede changes in cellular state\nC_LIO_LIAcute physical activity recruits quiescent cells into active proliferation\nC_LIO_LIThis recruitment is marked by a Nox2-dependent ROS spike in hiROS stem cells and represents an independent mode of cell cycle entry\nC_LI\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC=\"FIGDIR/small/606186_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (65K):\norg.highwire.dtl.DTLVardef@1bbb7ddorg.highwire.dtl.DTLVardef@1241536org.highwire.dtl.DTLVardef@1ec9c32org.highwire.dtl.DTLVardef@102d527_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2019

A smart polymer for sequence-selective binding, pulldown and release of DNA targets

Selective isolation of DNA is crucial for applications in biology, bionanotechnology, clinical diagnostics and forensics. We herein report a smart methanol-responsive polymer (MeRPy) that can be programmed to bind and separate single- as well as double-stranded DNA targets. Captured targets are quickly isolated and released back into solution by denaturation (sequence-agnostic) or toehold-mediated strand displacement (sequence-selective). The latter mode allows 99.8% efficient removal of unwanted sequences and 79% recovery of highly pure target sequences. We applied MeRPy for the depletion of insulin, glucagon, and transthyretin cDNA from clinical next-generation sequencing (NGS) libraries. This step improved data quality for low-abundance transcripts in expression profiles of pancreatic tissues. Its low cost, scalability, high stability and ease of use make MeRPy suitable for diverse applications in research and clinical laboratories, including enhancement of NGS libraries, extraction of DNA from biological samples, preparative-scale DNA isolations, and sorting of DNA-labeled non-nucleic acid targets.

molecular biology↗

bioRxiv2019

Comprehensive Assessment of Sequence and Expression of Circular-RNAs in Progenitor Cell Types of the Developing Mammalian Cortex

ABSRTRACTCircular (circ) RNAs have recently emerged as a novel class of non coding transcripts whose identification and function remain elusive. Among many tissues and species, the mammalian brain is the organ in which circRNAs are more abundant and first evidence of their functional significance started to emerge. Yet, even within this well studied organ, annotation of circRNAs remains fragmentary, their sequence is unknown and their expression in specific cell types was never investigated. Overcoming these limitations, here we provide the fist comprehensive identification of circRNAs and their expression patterns in proliferating neural stem cells, neurogenic progenitors and newborn neurons of the developing mouse cortex. Extending the current knowledge about the diversity of this class of transcripts by the identification of nearly 4,000 new circRNAs, our study is the first to provide the full sequence information and expression patterns of circRNAs in cell types representing the lineage of neurogenic commitment. We further exploited our data by evaluating the coding potential, evolutionary conservation and biogenesis of circRNAs that we found to arise from a specific sub-class of linear mRNAs. Our study provides the arising field of circRNA biology with a powerful new resource to address the complexity and potential biological significance of this new class of transcripts.

developmental biology↗

bioRxiv2018

Comparative RNAi Screens in Isogenic Human Stem Cells Reveal SMARCA4 as a Differential Regulator

Large-scale RNAi screens are a powerful approach to identify functions of genes in a cell-type specific manner. For model organisms, genetically identical (isogenic) cells from different cell-types are readily available, making comparative studies meaningful. For humans, however, screening isogenic cells is not straightforward. Here, we show that RNAi screens are possible in genetically identical human stem cells, employing induced pluripotent stem cell as intermediates. The screens revealed SMARCA4 (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily A member 4) as a stemness regulator, while balancing differentiation distinctively for each cell type. SMARCA4 knockdown in hematopoietic stem progenitor cells (HSPC) caused impaired self-renewal in-vitro and in-vivo with skewed myeloid differentiation; whereas in neural stem cells (NSC), it impaired selfrenewal while biasing differentiation towards neural lineage, through combinatorial SWI/SNF subunit assembly. Our findings pose a powerful approach for deciphering human stem cell biology and attribute distinct roles to SMARCA4 in stem cell maintenance.

molecular biology↗

bioRxiv2018

Reverse GWAS: Using Genetics to Identify and Model Phenotypic Subtypes

Recent and classical work has revealed biologically and medically significant subtypes in complex diseases and traits. However, relevant subtypes are often unknown, unmeasured, or actively debated, making automatic statistical approaches to subtype definition particularly valuable. We propose reverse GWAS (RGWAS) to identify and validate subtypes using genetics and multiple traits: while GWAS seeks the genetic basis of a given trait, RGWAS seeks to define trait subtypes with distinct genetic bases. Unlike existing approaches relying on off-the-shelf clustering methods, RGWAS uses a bespoke decomposition, MFMR, to model covariates, binary traits, and population structure. We use extensive simulations to show these features can be crucial for power and calibration. We validate RGWAS in practice by recovering known stress subtypes in major depressive disorder. We then show the utility of RGWAS by identifying three novel subtypes of metabolic traits. We biologically validate these metabolic subtypes with SNP-level tests and a novel polygenic test: the former recover known metabolic GxE SNPs; the latter suggests genetic heterogeneity may explain substantial missing heritability. Crucially, statins, which are widely prescribed and theorized to increase diabetes risk, have opposing effects on blood glucose across metabolic subtypes, suggesting potential have potential translational value.\n\nAuthor summaryComplex diseases depend on interactions between many known and unknown genetic and environmental factors. However, most studies aggregate these strata and test for associations on average across samples, though biological factors and medical interventions can have dramatically different effects on different people. Further, more-sophisticated models are often infeasible because relevant sources of heterogeneity are not generally known a priori. We introduce Reverse GWAS to simultaneously split samples into homogeneoues subtypes and to learn differences in genetic or treatment effects between subtypes. Unlike existing approaches to computational subtype identification using high-dimensional trait data, RGWAS accounts for covariates, binary disease traits and, especially, population structure; these features are each invaluable in extensive simulations. We validate RGWAS by recovering known genetic subtypes of major depression. We demonstrate RGWAS is practically useful in a metabolic study, finding three novel subtypes with both SNP- and polygenic-level heterogeneity. Importantly, RGWAS can uncover differential treatment response: for example, we show that statin, a common drug and potential type 2 diabetes risk factor, may have opposing subtype-specific effects on blood glucose.

genetics↗

bioRxiv2018

Existence and implications of population variance structure

Identifying the genetic and environmental factors underlying phenotypic differences between populations is fundamental to multiple research communities. To date, studies have focused on the relationship between population and phenotypic mean. Here we consider the relationship between population and phenotypic variance, i.e., \"population variance structure.\" In addition to gene-gene and gene-environment interaction, we show that population variance structure is a direct consequence of natural selection. We develop the ancestry double generalized linear model (ADGLM), a statistical framework to jointly model population mean and variance effects. We apply ADGLM to several deeply phenotyped datasets and observe ancestry-variance associations with 12 of 44 tested traits in ~113K British individuals and 3 of 14 tested traits in ~3K Mexican, Puerto Rican, and African-American individuals. We show through extensive simulations that population variance structure can both bias and reduce the power of genetic association studies, even when principal components or linear mixed models are used. ADGLM corrects this bias and improves power relative to previous methods in both simulated and real datasets. Additionally, ADGLM identifies 17 novel genotype-variance associations across six phenotypes.

genetics↗

bioRxiv2018

GxEMM: Extending linear mixed models to general gene-environment interactions

Gene-environment interaction (GxE) is a well-known source of non-additive inheritance. GxE can be important in applications ranging from basic functional genomics to precision medical treatment. Further, GxE effects elude inherently-linear LMMs and may explain missing heritability. We propose a simple, unifying mixed model for polygenic interactions (GxEMM) to capture the aggregate effect of small GxE effects spread across the genome. GxEMM extends existing LMMs for GxE in two important ways. First, it extends to arbitrary environmental variables, not just categorical groups. Second, GxEMM can estimate and test for environment-specific heritability. In simulations where the assumptions of existing methods do not hold, we show that GxEMM improves estimates of ordinary and GxE heritability and increases power to test for polygenic GxE. We then use GxEMM to prove that the heritability of major depression (MD) is reduced by stress, which we previously conjectured but could not prove with prior methods, and that a tail of polygenic GxE effects remains unexplained by MD GWAS.

genetics↗

bioRxiv2018

GBAT: a gene-based association method for robust trans-gene regulation detection

Identification of trans-eQTLs has been limited by a heavy multiple testing burden, read-mapping biases, and hidden confounders. To address these issues, we developed GBAT, a powerful gene-based method that allows robust detection of trans gene regulation. Using simulated and real data, we show that GBAT drastically increases detection of trans-gene regulation over standard trans-eQTL analyses.

genetics↗

bioRxiv2017

On negative heritability and negative estimates of heritability

AO_SCPLOWBSTRACTC_SCPLOWWe consider the problem of interpreting negative maximum likelihood estimates of heritability that sometimes arise from popular statistical models of additive genetic variation. These may result from random noise acting on estimates of genuinely positive heritability, but we argue that they may also arise from misspecification of the standard additive mechanism that is supposed to justify the statistical procedure. Researchers should be open to the possibility that negative heritability estimates could reflect a real physical feature of the biological process from which the data were sampled.

genetics↗

bioRxiv2017

Instructive starPEG-Heparin biohybrid 3D cultures for modeling human neural stem cell plasticity, neurogenesis, and neurodegeneration

Three-dimensional models of human neural development and neurodegeneration are crucial when exploring stem-cell-based regenerative therapies in a tissue-mimetic manner. However, existing 3D culture systems are not sufficient to model the inherent plasticity of NSCs due to their ill-defined composition and lack of controllability of the physical properties. Adapting a glycosaminoglycan-based, cell-responsive hydrogel platform, we stimulated primary and induced human neural stem cells (NSCs) to manifest neurogenic plasticity and form extensive neuronal networks in vitro. The 3D cultures exhibited neurotransmitter responsiveness, electrophysiological activity, and tissue-specific extracellular matrix (ECM) deposition. By whole transcriptome sequencing, we identified that 3D cultures express mature neuronal markers, and reflect the in vivo make-up of mature cortical neurons compared to 2D cultures. Thus, our data suggest that our established 3D hydrogel culture supports the tissue-mimetic maturation of human neurons. We also exemplarily modeled neurodegenerative conditions by treating the cultures with A{beta}42 peptide and observed the known human pathological effects of Alzheimers disease including reduced NSC proliferation, impaired neuronal network formation, synaptic loss and failure in ECM deposition as well as elevated Tau hyperphosphorylation and formation of neurofibrillary tangles. We determined the changes in transcriptomes of primary and induced NSC-derived neurons after A{beta}42, providing a useful resource for further studies. Thus, our hydrogel-based human cortical 3D cell culture is a powerful platform for studying various aspects of neural development and neurodegeneration, as exemplified for A{beta}42 toxicity and neurogenic stem cell plasticity.\n\nSignificanceNeural stem cells (NSC) are reservoir for new neurons in human brains, yet they fail to form neurons after neurodegeneration. Therefore, understanding the potential use of NSCs for stem cell-based regenerative therapies requires tissue-mimetic humanized experimental systems. We report the adaptation of a 3D bio-instructive hydrogel culture system where human NSCs form neurons that later form networks in a controlled microenvironment. We also modeled neurodegenerative toxicity by using Amyloid-beta4 peptide, a hallmark of Alzheimers disease, observed phenotypes reminiscent of human brains, and determined the global gene expression changes during development and degeneration of neurons. Thus, our reductionist humanized culture model will be an important tool to address NSC plasticity, neurogenicity, and network formation in health and disease.

neuroscience↗