Biology subjects

Stein, J. L.

Publications and source records attributed to Stein, J. L..

35 records · Page 2Linked to original sources

bioRxiv2021

Genetic variations within human gained enhancer elements affect human brain sulcal morphology.

The expansion of the cerebral cortex is one of the most distinctive changes in the evolution of the human brain. Cortical expansion and related increases in cortical folding may have contributed to emergence of our capacities for high-order cognitive abilities. Molecular analysis of humans, archaic hominins, and non-human primates has allowed identification of chromosomal regions showing evolutionary changes at different points of our phylogenetic history. In this study, we assessed the contributions of genomic annotations spanning 30 million years to human sulcal morphology measured via MRI in more than 18,000 participants from the UK Biobank. We found that variation within brain-expressed human gained enhancers, regulatory genetic elements that emerged since our last common ancestor with Old World monkeys, explained more trait heritability than expected for the left and right calloso-marginal posterior fissures and the right central sulcus. Intriguingly, these are sulci that have been previously linked to the evolution of locomotion in primates and later on bipedalism in our hominin ancestors.

neuroscience↗

bioRxiv2021

The breast pre-cancer atlas illustrates the molecular and micro-environmental diversity of ductal carcinoma in situ

Micro-environmental and molecular factors mediating the progression of Breast Ductal Carcinoma In Situ (DCIS) are not well understood, impeding the development of prevention strategies and the safe testing of treatment de-escalation. We addressed methodological barriers and characterized the mutational, transcriptional, histological and microenvironmental landscape across 85 multiple micro-dissected regions from 39 cases. Most somatic alterations, including whole genome duplications, were clonal, but genetic divergence increased with physical distance. Phenotypic and subtype heterogeneity frequently associated with underlying genetic heterogeneity and regions with low-risk features preceded those with high-risk features according to the inferred phylogeny. B- and T-lymphocytes spatial analysis identified 3 immune states, including an epithelial excluded state located preferentially at DCIS regions, and characterized by histological and molecular features of immune escape, independently from molecular subtypes. Such breast pre-cancer atlas with uniquely integrated observations will help scope future expansion studies and build finer models of outcomes and progression risk.

genomics↗

bioRxiv2021

ToxCast chemical library screen identifies diethanolamine as an activator of Wnt signaling

Numerous autism spectrum disorder (ASD) risk genes are associated with Wnt signaling, suggesting that brain development may be especially sensitive to genetic perturbation of this pathway. Additionally, valproic acid, which modulates Wnt signaling, increases risk for ASD when taken during pregnancy. We previously found that an autism-linked gain-of-function UBE3AT485A mutant construct hyperactivated canonical Wnt signaling, providing a genetic means to elevate Wnt signaling above baseline levels. To identify environmental use chemicals that enhance or suppress Wnt signaling, we screened the ToxCast Phase I and II libraries in cells expressing this autism linked UBE3AT485 gain-of-function mutant construct. Using structural comparisons, we identify classes of chemicals that stimulated Wnt signaling, including ethanolamines, as well as chemicals that inhibited Wnt signaling, such as agricultural pesticides, and synthetic hormone analogs. To prioritize chemicals for follow-up, we leveraged predicted human exposure data, and identified diethanolamine (DEA) as a chemical that both stimulates Wnt signaling in UBE3AT485A-transfected cells and has a high potential for prenatal exposure in humans. DEA also enhanced proliferation in two primary human neural progenitor cell lines. Overall, this study identifies chemicals with the potential for human exposure that influence Wnt signaling in human cells.

molecular biology↗

bioRxiv2021

Segmentor: A tool for manual refinement of 3D microscopy annotations

BackgroundRecent advances in tissue clearing techniques, combined with high-speed image acquisition through light sheet microscopy, enable rapid three-dimensional (3D) imaging of biological specimens, such as whole mouse brains, in a matter of hours. Quantitative analysis of such 3D images can help us understand how changes in brain structure lead to differences in behavior or cognition, but distinguishing features of interest, such as nuclei, from background can be challenging. Recent deep learning-based nuclear segmentation algorithms show great promise for automated segmentation, but require large numbers of manually and accurately labeled nuclei as training data. ResultsWe present Segmentor, an open-source tool for reliable, efficient, and user-friendly manual annotation and refinement of objects (e.g., nuclei) within 3D light sheet microscopy images. Segmentor employs a hybrid 2D-3D approach for visualizing and segmenting objects and contains features for automatic region splitting, designed specifically for streamlining the process of 3D segmentation of nuclei. We show that editing simultaneously in 2D and 3D using Segmentor significantly decreases time spent on manual annotations without affecting accuracy. ConclusionsSegmentor is a tool for increased efficiency of manual annotation and refinement of 3D objects that can be used to train deep learning segmentation algorithms, and is available at https://www.nucleininja.org/ and https://github.com/RENCI/Segmentor.

neuroscience↗

bioRxiv2020

Genetic influences on cell type specific gene expression and splicing during neurogenesis elucidate regulatory mechanisms of brain traits

Interpretation of the function of non-coding risk loci for neuropsychiatric disorders and brain-relevant traits via gene expression and alternative splicing is generally performed in bulk post-mortem adult tissue. However, genetic risk loci are enriched in regulatory elements active during neocortical differentiation, and regulatory effects of risk variants may be masked by heterogeneity in bulk tissue. Here, we map expression quantitative trait loci (eQTLs), splicing QTLs (sQTLs), and allele specific expression in primary human neural progenitors (n=85) and their sorted neuronal progeny (n=74), identifying numerous loci not detected in either bulk developing cortical wall or adult cortex. Using colocalization and genetic imputation via transcriptome wide association, we uncover cell-type specific regulatory mechanisms underlying risk for brain-relevant traits that are active during neocortical differentiation. Specifically, we identified a progenitor-specific eQTL for CENPW co-localized with common variant associations of cortical area and educational attainment.

genetics↗

bioRxiv2020

NuMorph: tools for cellular phenotyping in tissue cleared whole brain images

Tissue clearing methods allow every cell in the mouse brain to be imaged without physical sectioning. However, the computational tools currently available for cell quantification in cleared tissue images have been limited to counting sparse cell populations in stereotypical mice. Here we introduce NuMorph, a group of image analysis tools to quantify all nuclei and nuclear markers within the mouse cortex after tissue clearing and imaging by a conventional light-sheet microscope. We applied NuMorph to investigate two distinct mouse models: a Topoisomerase 1 (Top1) conditional knockout model with severe neurodegenerative deficits and a Neurofibromin 1 (Nf1) conditional knockout model with a more subtle brain overgrowth phenotype. In each case, we identified differential effects of gene deletion on individual cell-type counts and distribution across cortical regions that manifest as alterations of gross brain morphology. These results underline the value of 3D whole brain imaging approaches and the tools are widely applicable for studying 3D structural deficits of the brain at cellular resolution in animal models of neuropsychiatric disorders.

neuroscience↗

bioRxiv2020

MRLocus: identifying causal genes mediating a trait through Bayesian estimation of allelic heterogeneity

Expression quantitative trait loci (eQTL) studies are used to understand the regulatory function of non-coding genome-wide association study (GWAS) risk loci, but colocalization alone does not demonstrate a causal relationship of gene expression affecting a trait. Evidence for mediation, that perturbation of gene expression in a given tissue or developmental context will induce a change in the downstream GWAS trait, can be provided by two-sample Mendelian Randomization (MR). Here, we introduce a new statistical method, MRLocus, for Bayesian estimation of the gene-to-trait effect from eQTL and GWAS summary data for loci displaying allelic heterogeneity, that is, containing multiple LD-independent eQTLs. MRLocus makes use of a colocalization step applied to each eQTL, followed by an MR analysis step across eQTLs. Additionally, our method involves estimation of allelic heterogeneity through a dispersion parameter, indicating variable mediation effects from each individual eQTL on the downstream trait. Our method is evaluated against state-of-the-art methods for estimation of the gene-to-trait mediation effect, using an existing simulation framework. In simulation, MRLocus often has the highest accuracy among competing methods, and in each case provides more accurate estimation of uncertainty as assessed through interval coverage. MRLocus is then applied to five causal candidate genes for mediation of particular GWAS traits, where gene-to-trait effects are concordant with those previously reported. We find that MRLocus estimation of the causal effect across eQTLs within a locus provides useful information for determining how perturbation of gene expression or individual regulatory elements will affect downstream traits. The MRLocus method is implemented as an R package available at https://mikelove.github.io/mrlocus.

bioinformatics↗

bioRxiv2020

Common variants contribute to intrinsic functional architecture of human brain

The human brain remains active in the absence of explicit tasks and forms networks of correlated activity. Resting-state functional magnetic resonance imaging (rsfMRI) measures brain activity at rest, which has been linked with both cognitive and clinical outcomes. The genetic variants influencing human brain function are largely unknown. Here we utilized rsfMRI from 44,190 individuals of multiple ancestries (37,339 in the UK Biobank) to discover and validate the common genetic variants influencing intrinsic brain activity. We identified hundreds of novel genetic loci associated with intrinsic functional signatures (P < 2.8 x 10-11), including associations to the central executive, default mode, and salience networks involved in the triple network model of psychopathology. A number of intrinsic brain activity associated loci colocalized with brain disorder GWAS (e.g., Alzheimers disease, Parkinsons disease, schizophrenia) and cognition, such as 19q13.32, 17q21.31, and 2p16.1. Particularly, we detected a colocalization between one (rs429358) of the two variants in the APOE {varepsilon}4 locus and function of the default mode, central executive, attention, and visual networks. Genetic correlation analysis demonstrated shared genetic influences between brain function and brain structure in the same regions. We also detected significant genetic correlations with 26 other complex traits, such as ADHD, major depressive disorder, schizophrenia, intelligence, education, sleep, subjective well-being, and neuroticism. Common variants associated with intrinsic brain activity were enriched within regulatory element in brain tissues.

genetics↗

bioRxiv2020

Evaluating brain structure traits as endophenotypes using polygenicity and discoverability

Human brain structure traits have been hypothesized to be broad endophenotypes for neuropsychiatric disorders, implying that brain structure traits are comparatively closer to the underlying biology. Genome-wide association studies from large sample sizes allow for the comparison of common variant genetic architectures between traits to test the evidence supporting this claim. Endophenotypes, compared to neuropsychiatric disorders, are hypothesized to have less polygenicity, with greater effect size of each susceptible SNP, requiring smaller sample sizes to discover them. Here, we compare polygenicity and discoverability of brain structure traits, neuropsychiatric disorders, and other traits (89 in total) to directly test this hypothesis. We found reduced polygenicity (FDR = 0.01) and increased discoverability of cortical brain structure traits, as compared to neuropsychiatric disorders (FDR = 3.68x10-9). We predict that ~8M samples will be required to explain the full heritability of cortical surface area by genome-wide significant SNPs, whereas sample sizes over 20M will be required to explain the full heritability of major depressive disorder. In conclusion, we find reduced polygenicity and increased discoverability of cortical structure compared to neuropsychiatric disorders, which is consistent with brain structure satisfying the higher power criterion of endophenotypes.

genetics↗

bioRxiv2020

The comprehensive genetic architecture of brain white matter

Brain regions communicate with each other via tracts of myelinated axons, commonly referred to as white matter. White matter microstructure can be measured in the living human brain using diffusion based magnetic resonance imaging (dMRI), and has been found to be altered in patients with neuropsychiatric disorders. Although under strong genetic control, few genetic variants influencing white matter microstructure have ever been identified. Here we identified common genetic variants influencing white matter microstructure using dMRI in 42,919 individuals (35,741 in the UK Biobank). The dMRIs were summarized into 215 white matter microstructure traits, including 105 measures from tract-specific functional principal component analysis. Genome-wide association analysis identified many novel white matter microstructure associated loci (P < 2.3 x 10-10). We identified shared genetic influences through genetic correlations between white matter tracts and 62 other complex traits, including stroke, neuropsychiatric disorders (e.g., ADHD, bipolar disorder, major depressive disorder, schizophrenia), cognition, neuroticism, chronotype, as well as non-brain traits. Common variants associated with white matter microstructure alter the function of regulatory elements in glial cells, particularly oligodendrocytes. White matter associated genes were enriched in pathways involved in brain disease pathogenesis, neurodevelopment process, and repair of white matter damage (P < 1.5 x 10-8). In summary, this large-scale tract-specific study provides a big step forward in understanding the genetic architecture of white matter and its genetic links to a wide spectrum of clinical outcomes.

genetics↗

bioRxiv2020

Cell-type specific effects of genetic variation on chromatin accessibility during human neuronal differentiation

Common genetic risk for neuropsychiatric disorders is enriched in regulatory elements active during cortical neurogenesis. However, the mechanisms mediating the effects of genetic variants on gene regulation are poorly understood. To determine the functional impact of common genetic variation on the non-coding genome longitudinally during human cortical development, we performed a chromatin accessibility quantitative trait loci (caQTL) analysis in neural progenitor cells and their differentiated neuronal progeny from 92 donors. We identified 8,111 caQTLs in progenitors and 3,676 caQTLs in neurons, with highly temporal, cell-type specific effects. A subset ([~]20%) of caQTLs were also associated with changes in gene expression. Motif-disrupting alleles of transcriptional activators generally led to decreases in chromatin accessibility, whereas motif-disrupting alleles of repressors led to increases in chromatin accessibility. By integrating cell-type specific caQTLs and brain-relevant genome-wide association data, we were able to fine-map loci and identify regulatory mechanisms underlying non-coding neuropsychiatric disorder risk variants. HighlightsO_LIGenetic variation alters chromatin architecture during human cortical development C_LIO_LIGenetic effects on chromatin accessibility are highly cell-type specific C_LIO_LIAlleles disrupting TF motifs generally decrease accessibility, except for repressors C_LIO_LIcaQTLs facilitate fine-mapping and inference of regulatory mechanisms of GWAS loci C_LI

genetics↗

bioRxiv2019

Mitotic gene bookmarking by RUNX1 contributes to stabilization of the normal mammary epithelial phenotype

RUNX1 has recently been shown to play an important role in determination of mammary epithelial cell identity. However, mechanisms by which loss of the RUNX1 transcription factor in mammary epithelial cells leads to epithelial-to-mesenchymal transition (EMT) are not known. Here, we report mitotic bookmarking of genes by RUNX1 as a potential mechanism to convey regulatory information through successive cell divisions for coordinate control of mammary cell proliferation, growth, and identity. Genome-wide RUNX1 occupancy profiles for asynchronous, mitotically enriched, and early G1 breast epithelial cells reveal RUNX1 is retained during the mitosis to G1 transition on protein coding and long non-coding RNA genes critical for mammary epithelial proliferation, growth, and phenotype maintenance. Disruption of RUNX1 DNA binding and association with mitotic chromosomes alters cell morphology, global protein synthesis, and phenotype-related gene expression. Together, these findings show for the first time that RUNX1 bookmarks a subset of epithelial-related genes during mitosis that remain occupied as cells enter the next cell cycle. Compromising RUNX1 DNA binding initiates EMT, an essential first step in the onset of breast cancer. SignificanceThis study elucidates mitotic gene bookmarking as a potential epigenetic mechanism that impacts breast epithelial cell growth and phenotype and has potential implications in breast cancer onset.

cancer biology↗

bioRxiv2018

Genetic control of gene expression and splicing in the developing human brain

Most genetic risk for human diseases lies within non-coding regions of the genome, which is predicted to regulate gene expression, often in a tissue and stage specific manner. This has motivated building of extensive eQTL resources to understand how human allelic variation affects gene expression and splicing throughout the body, focusing primarily on adult tissue. Given the importance of regulatory pathways during brain development, we characterize the genetic control of the developing human cerebral cortical transcriptome, including expression and splicing, in 201 mid-gestational human brains, to understand how common allelic variation affects gene regulation during development. We leverage expression and splice quantitative trait loci to identify genes and isoforms relevant to neuropsychiatric disorders and brain volume. These findings demonstrate genetic mechanisms by which early developmental events have a striking and widespread influence on adult anatomical and behavioral phenotypes, as well as the evolution of the human cerebral cortex.\n\nHighlightsO_LIGenome wide map of human fetal brain eQTLs and sQTLs provides a new view of genetic control of expression and splicing.\nC_LIO_LIThere is substantial contrast between genetic control of transcript regulation in mature versus developing brain.\nC_LIO_LIWe identify novel regulatory regions specific to fetal brain development.\nC_LIO_LIIntegration of eQTLs and GWAS reveals specific relationships between expression and disease risk for neuropsychiatric diseases and relevant human brain phenotypes.\nC_LI

neuroscience↗

bioRxiv2018

A single cell transcriptomic analysis of human neocortical development

Defining the number, proportion, or lineage of distinct cell types in the developing human brain is an important goal of modern brain research. We defined single cell transcriptomic profiles for 40,000 cells at mid-gestation to identify cell types in the developing human neocortex. We define expression profiles corresponding to all known major cell types at this developmental period and identify multiple transcription factors and co-factors expressed in specific cell types, providing an unprecedented resource for understanding human neocortical development including the first single-cell characterization of human subplate neurons. We characterize major developmental trajectories during early neurogenesis, showing that cell type differentiation occurs on a continuum that involves transitions that tie cell cycle progression with early cell fate decisions. We use these data to deconvolute regulatory networks and map neuropsychiatric disease genes to specific cell types, implicating dysregulation of specific cell types, as the mechanistic underpinnings of several neurodevelopmental disorders. Together these results provide an extensive catalog of cell types in human neocortex and extend our understanding of early cortical development, human brain evolution and the cellular basis of neuropsychiatric disease.\n\nOne Sentence SummaryComprehensive single cell transcriptomes in developing human cortex inform models of cell diversity, differentiation and disease risk.

neuroscience↗

bioRxiv2018

RUNX1 suppresses breast cancer stemness and tumor growth

Recent studies have revealed that mutations in the transcription factor Runx1 are prevalent in breast tumors. Yet, how loss of Runx1 contributes to breast cancer (BCa) remains unresolved. We demonstrate for the first time that Runx1 represses the breast cancer stem cell (BCSC) phenotype and consequently, functions as a tumor suppressor in breast cancer. Runx1 ectopic expression in MCF10AT1 and MCF10CA1a BCa cells reduces (60%) migration, invasion and in vivo tumor growth in mouse mammary fat pad (P<0.05). Runx1 is decreased in BCSCs, and overexpression of Runx1 suppresses tumorsphere formation and reduces the BCSC population. Furthermore, Runx1 inhibits Zeb1 expression, while Runx1 depletion activates Zeb1 and the epithelial-mesenchymal transition. Mechanistically Runx1 functions as a tumor suppressor in breast cancer through repression of cancer stem cell activity. This key regulation of BCSCs by Runx1 may be shared in other epithelial carcinomas, highlighting the importance of Runx1 in solid tumors.

cancer biology↗

bioRxiv2017

Genetic markers of ADHD-related variations in intracranial volume

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common and highly heritable neurodevelopmental disorder with a complex pathophysiology, where genetic risk is hypothesized to be mediated by alterations in structure and function of diverse brain networks. We tested one aspect of this hypothesis by investigating the genetic overlap between ADHD (n=55,374) and (mainly subcortical) brain volumes (n=11,221-24,704), using the largest publicly available studies. At the level of common variant genetic architecture, we discovered a significant negative genetic correlation between ADHD and intracranial volume (ICV). Meta-analysis of individual variants found significant loci associated with both ADHD risk and ICV; additional loci were identified for ADHD and amygdala, caudate nucleus, and putamen volumes. Gene-set analysis in the ADHD-ICV meta-analytic data showed significant association with variation in neurite outgrowth-related genes. In summary, our results suggest new hypotheses about biological mechanisms involved in ADHD etiology and highlight the need to study additional brain parameters.

genetics↗

bioRxiv2017

Genetic Architecture of Subcortical Brain Structures in Over 40,000 Individuals Worldwide

Subcortical brain structures are integral to motion, consciousness, emotions, and learning. We identified common genetic variation related to the volumes of nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen, and thalamus, using genome-wide association analyses in over 40,000 individuals from CHARGE, ENIGMA and the UK-Biobank. We show that variability in subcortical volumes is heritable, and identify 25 significantly associated loci (20 novel). Annotation of these loci utilizing gene expression, methylation, and neuropathological data identified 62 candidate genes implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

genetics↗