Biology subjects

Wainberg, M.

Publications and source records attributed to Wainberg, M..

7 recordsLinked to original sources

bioRxiv2024

Perinatal Brain Injury Triggers Niche-Specific Changes to Cellular Biogeography

Preterm infants are at risk for brain injury and neurodevelopmental impairment due, in part, to white matter injury following chronic hypoxia exposure. However, the precise molecular mechanisms by which perinatal hypoxia disrupts early neurodevelopment are poorly understood. Here, we constructed a brain-wide map of the regenerative response to newborn brain injury using high-resolution imaging-based spatial transcriptomics to analyze over 1.3 million cells in a mouse model of chronic neonatal hypoxia. Additionally, we developed a new method for inferring condition-associated differences in cell type spatial proximity, enabling the identification of niche-specific changes in cellular architecture. We observed hypoxia-associated changes in region-specific cell states, cell type composition, and spatial organization. Importantly, our analysis revealed mechanisms underlying reparative neurogenesis and gliogenesis, while also nominating pathways that may impede circuit rewiring following perinatal hypoxia. Altogether, our work provides a comprehensive description of the molecular response to newborn brain injury.

neuroscience↗

bioRxiv2023

BrainRBPedia: a resource for RNA-binding proteins relevant to neurodevelopmental disorders

RNA-binding proteins (RBPs) are crucial players in the post-transcriptional regulation of mRNA and play major roles in ensuring proper neuronal development and function. Deficits in RBP function have been implicated in a number of neurodevelopmental disorders including autism spectrum disorder (ASD) and intellectual disability (ID), yet we lack resources that integrate current knowledge of RBP function, tissue expression, and disease association in one place to aid in their experimental characterization. Here we introduce BrainRBPedia - a database of 1072 RBPs with both disease annotations for neurodevelopmental disorders and functional annotations relevant to these disorders, including loss-of-function intolerance and expression specificity to the brain, neurons, and neuronal development. Using these functional annotations, we develop a machine learning model to prioritize RBPs likely to be involved in ASD and ID. Our model indicates that RBPs with high loss-of-function intolerance and those upregulated during neuronal differentiation are disproportionately likely to contribute to ASD and ID etiology. In summary, BrainRBPedia comprises a unique resource for researchers interested in the experimental characterization of RBPs in relation to neurodevelopmental disorders and suggests functional signatures of RBPs likely to play a role in neurodevelopment.

bioinformatics↗

bioRxiv2019

A genome-wide almanac of co-essential modules assigns function to uncharacterized genes

A central remaining question in the post-genomic era is how genes interact to form biological pathways. Measurements of gene dependency across hundreds of cell lines have been used to cluster genes into co-essential pathways, but this approach has been limited by ubiquitous false positives. Here, we develop a statistical method that enables robust identification of gene co-essentiality and yields a genome-wide set of functional modules. This almanac recapitulates diverse pathways and protein complexes and predicts the functions of 102 uncharacterized genes. Validating top predictions, we show that TMEM189 encodes plasmanylethanolamine desaturase, the long-sought key enzyme for plasmalogen synthesis. We also show that C15orf57 binds the AP2 complex, localizes to clathrin-coated pits, and enables efficient transferrin uptake. Finally, we provide an interactive web tool for the community to explore the results (coessentiality.net). Our results establish co-essentiality profiling as a powerful resource for biological pathway identification and discovery of novel gene functions.

genomics↗

bioRxiv2019

Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma

Protein-altering variants that are protective against human disease provide in vivo validation of therapeutic targets. Here we use genotyping data in UK Biobank and FinnGen to conduct a search for protein-altering variants conferring lower intraocular pressure (IOP) and protection against glaucoma. Through protein-altering variant association analysis we find a missense variant in UK Biobank (rs28991009 (MAF=0.8%) genotyped in 81,527 individuals with measured IOP and an independent set of 4,269 glaucoma patients and 251,355 controls) that significantly lowers IOP ({beta} = -0.73 mmHg for heterozygotes, -2.96 mmHg for homozygotes, P = 1 x 10-13) and is associated with 34% reduced risk of glaucoma (P = 0.005). In FinnGen, we identify an ANGPTL7 missense variant at a greater than 50-fold increased frequency in Finland compared with other populations (rs147660927, p.Arg220Cys, MAF Finland = 4.1%), which was genotyped in 5,177 glaucoma patients and 130,461 controls and is associated with 30% lower glaucoma risk (P = 1 x 10-9). We further find three rarer variants in UK Biobank, including a protein-truncating variant, which confer a strong composite lowering of IOP (P = 0.002), suggesting the protective mechanism likely resides in the loss of an interaction or function. Our results support inhibition or down-regulation of ANGPTL7 as a therapeutic strategy for glaucoma

genetics↗

bioRxiv2019

Genetics of 38 blood and urine biomarkers in the UK Biobank

Clinical laboratory tests are a critical component of the continuum of care and provide a means for rapid diagnosis and monitoring of chronic disease. In this study, we systematically evaluated the genetic basis of 38 blood and urine laboratory tests measured in 358,072 participants in the UK Biobank and identified 1,857 independent loci associated with at least one laboratory test, including 488 large-effect protein truncating, missense, and copy-number variants. We tested these loci for enrichment in specific single cell types in kidney, liver, and pancreas relevant to disease aetiology. We then causally linked the biomarkers to medically relevant phenotypes through genetic correlation and Mendelian randomization. Finally, we developed polygenic risk scores (PRS) for each biomarker and built multi-PRS models using all 38 PRSs simultaneously. We found substantially improved prediction of incidence in FinnGen (n=135,500) with the multi-PRS relative to single-disease PRSs for renal failure, myocardial infarction, liver fat percentage, and alcoholic cirrhosis. Together, our results show the genetic basis of these biomarkers, which tissues contribute to the biomarker function, the causal influences of the biomarkers, and how we can use this to predict disease.

genetics↗

bioRxiv2019

Identification and mitigation of pervasive off-target activity in CRISPR-Cas9 screens for essential non-coding elements

Pooled CRISPR-Cas9 screens have recently emerged as a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we conducted a genome-scale screen for essential CTCF loop anchors in the K562 leukemia cell line. Surprisingly, the primary drivers of signal in this screen were single guide RNAs (sgRNAs) with low specificity scores. After removing these guides, we found that there were no CTCF loop anchors critical for cell growth. We also observed this effect in an independent screen fine-mapping the core motifs in enhancers of the GATA1 gene. We then conducted screens in parallel with CRISPRi and CRISPRa, which do not induce DNA damage, and found that an unexpected and distinct set of off-targets also caused strong confounding growth effects with these epigenome-editing platforms. Promisingly, strict filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and allowed for the identification of essential enhancers, which we validated extensively. Together, our results show off-target activity can severely limit identification of essential functional motifs by active Cas9, while strictly filtered CRISPRi screens can be reliably used for assaying larger regulatory elements.

genomics↗

bioRxiv2017

Vulnerabilities of transcriptome-wide association studies

Transcriptome-wide association studies (TWAS) integrate GWAS and gene expression datasets to find gene-trait associations. In this Perspective, we explore properties of TWAS as a potential approach to prioritize causal genes, using simulations and case studies of literature-curated candidate causal genes for schizophrenia, LDL cholesterol and Crohns disease. We explore risk loci where TWAS accurately prioritizes the likely causal gene, as well as loci where TWAS prioritizes multiple genes, some of which are unlikely to be causal, because they share the same variants as eQTLs. We illustrate that TWAS is especially prone to spurious prioritization when using expression data from tissues or cell types that are less related to the trait, due to substantial variation in both expression levels and eQTL strengths across cell types. Nonetheless, TWAS prioritizes candidate causal genes at GWAS loci more accurately than simple baselines based on proximity to lead GWAS variant and expression in trait-related tissue. We discuss current strategies and future opportunities for improving the performance of TWAS for causal gene prioritization. Our results showcase the strengths and limitations of using expression variation across individuals to determine causal genes at GWAS loci and provide guidelines and best practices when using TWAS to prioritize candidate causal genes.

genetics↗