Biology subjects

Banks, E.

Publications and source records attributed to Banks, E..

At least 19 recordsLinked to original sources

bioRxiv2024

Differential roles of NaV1.2 and NaV1.6 in neocortical pyramidal cell excitability

Mature neocortical pyramidal cells functionally express two sodium channel (NaV) isoforms: NaV1.2 and NaV1.6. These isoforms are differentially localized to pyramidal cell compartments, and as such are thought to contribute to different aspects of neuronal excitability. But determining their precise roles in pyramidal cell excitability has been hampered by a lack of tools that allow for selective, acute block of each isoform individually. Here, we leveraged aryl sulfonamide-based molecule (ASC) inhibitors of NaV channels that exhibit state-dependent block of both NaV1.2 and NaV1.6, along with knock-in mice with changes in NaV1.2 or NaV1.6 structure that prevents ASC binding. This allowed for acute, potent, and reversible block of individual isoforms that permitted dissection of the unique contributions of NaV1.2 and NaV1.6 in pyramidal cell excitability. Remarkably, block of each isoform had contrasting--and in some situations, opposing--effects on neuronal action potential output, with NaV1.6 block decreasing and NaV1.2 block increasing output. Thus, NaV isoforms have unique roles in regulating different aspects of pyramidal cell excitability, and our work may help guide development of therapeutics designed to temper hyperexcitability through selective NaV isoform blockade.

neuroscience↗

bioRxiv2024

Blended Length Genome Sequencing (blend-seq): Combining Short Reads with Low-Coverage Long Reads to Maximize Variant Discovery

We introduce blend-seq, a workflow for combining data from traditional short-read sequencing pipelines with low-coverage long reads, to improve variant discovery for single samples without the full cost of high-coverage long reads. We demonstrate that with only 4x long-read coverage augmenting 30x short reads, we can improve SNP discovery across the genome, exceeding performance beyond even high-coverage short reads (60x). For genotype-agnostic discovery of structural variants, we see a threefold improvement in recall while maintaining precision by using the low-coverage long reads on their own, and show how we can improve genotyping accuracy by adding in the short-read data. In addition, we demonstrate how the long reads can better phase these variants, incorporating long-context information in the genome to substantially outperform phasing with short reads alone. Our experiments highlight the complementary nature of short- and long-read technologies: the former contributing higher depth for genotyping and the latter better resolution of larger events or those in difficult regions.

genomics↗

bioRxiv2024

An enhancer-AAV toolbox to target and manipulate distinct interneuron subtypes

In recent years, we and others have identified a number of enhancers that, when incorporated into rAAV vectors, can restrict the transgene expression to particular neuronal populations. Yet, viral tools to access and manipulate specific neuronal subtypes are still limited. Here, we performed systematic analysis of single cell genomic data to identify enhancer candidates for each of the telencephalic interneuron subtypes. We established a set of enhancer-AAV tools that are highly specific for distinct cortical interneuron populations and striatal cholinergic interneurons. These enhancers, when used in the context of different effectors, can target (fluorescent proteins), observe activity (GCaMP) and manipulate (opto-genetics) specific neuronal subtypes. We also validated our enhancer-AAV tools across species. Thus, we provide the field with a powerful set of tools to study neural circuits and functions and to develop precise and targeted therapy.

neuroscience↗

bioRxiv2023

Entorhinal cortex vulnerability to human APP expression promotes hyperexcitability and tau pathology

Preventative treatment for Alzheimers Disease is of dire importance, and yet, cellular mechanisms underlying early regional vulnerability in Alzheimers Disease remain unknown. In human patients with Alzheimers Disease, one of the earliest observed pathophysiological correlates to cognitive decline is hyperexcitability. In mouse models, early hyperexcitability has been shown in the entorhinal cortex, the first cortical region impacted by Alzheimers Disease. The origin of hyperexcitability in early-stage disease and why it preferentially emerges in specific regions is unclear. Using cortical-region and cell-type-specific proteomics coupled with ex vivo and in vivo electrophysiology, we uncovered differential susceptibility to human-specific amyloid precursor protein (hAPP) in a model of sporadic Alzheimers. Unexpectedly, our findings reveal that early entorhinal hyperexcitability may result from intrinsic vulnerability of parvalbumin (PV) interneurons, rather than the suspected layer II excitatory neurons. This vulnerability of entorhinal PV interneurons is specific to hAPP, as it could not be recapitulated with increased murine APP expression. However, partial replication of the findings could be seen after introduction of a murine APP chimera containing a humanized amyloid-beta sequence. Surprisingly, neurons in the Somatosensory Cortex showed no such vulnerability to adult-onset hAPP expression. hAPP-induced hyperexcitability in entorhinal cortex could be ameliorated by enhancing PV interneuron excitability in vivo. Co-expression of human Tau with hAPP decreased circuit hyperexcitability, but at the expense of increased pathological tau species. This study suggests early disease interventions targeting non-excitatory cell types may protect regions with early vulnerability to pathological symptoms of Alzheimers Disease and downstream cognitive decline.

neuroscience↗

bioRxiv2023

A dual hit of α-synuclein internalization and immune challenge leads to formation and maintenance of Lewy body-like inclusions in human dopaminergic neurons

Lewy bodies (LBs), rich in -synuclein, are a hallmark of Parkinsons disease (PD). Understanding their biogenesis is likely to provide insight into the pathophysiology of PD, yet a cellular model for LB formation remains elusive. The realization that the immune challenge is a trigger for neurodegenerative diseases has been a breakthrough in the understanding of PD. Here, iPSC-derived human dopaminergic (DA) neurons from multiple healthy donors were found to form LB-like inclusions following treatment with - synuclein preformed fibrils, but only when coupled to an immune challenge (interferon-gamma or interleukin-1 beta) or when co-cultured with activated microglia. Human cortical neurons derived from the same iPSC lines did not form LB-like inclusions. Exposure to interferon-gamma impairs autophagy in a lysosomal-specific manner in vitro, similar to the disruption of proteostasis pathways that contribute to PD. We find that lysosomal membrane proteins LAMP1 and LAMP2 and transcription factors regulating lysosomal biogenesis and function are downregulated in DA but not cortical neurons. Finally, due to the excellent sample preservation afforded by cells compared to post-mortem PD brain tissue, we conclude that the LB-like inclusions in DA neurons are membrane-bound, suggesting they are not limited to the cytoplasmic compartment. In Brief O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=170 SRC="FIGDIR/small/542776v3_figabs.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@1f41855org.highwire.dtl.DTLVardef@69798dorg.highwire.dtl.DTLVardef@ab55bdorg.highwire.dtl.DTLVardef@8a16b8_HPS_FORMAT_FIGEXP M_FIG C_FIG Bayati et al. identify that iPSC-derived dopaminergic neurons undergoing a dual hit treatment of exogenous -synuclein fibrils and proinflammatory cytokines form Lewy body-like inclusions. The dual hit treatment also led to the downregulation of lysosomal proteins. Characterization of inclusions revealed that inclusions were membrane-bound and LC3B-positive, suggesting they are dysfunctional autophagosomes. HighlightsO_LI-synuclein preformed fibril administration coupled with Interferon-gamma exposure leads dopaminergic neurons to form Lewy body-like inclusions C_LIO_LIInclusions are filamentous, membranous, and filled with aberrant organelles C_LIO_LIImpaired autophagic flux and downregulation of TFEB, NRF2, LAMP1, and LAMP2 correlated with inclusion formation C_LIO_LIActivation of NRF2 through the treatment of neurons with the antioxidant perillaldehyde, prevents inclusion formation C_LI

neuroscience↗

bioRxiv2023

A novel enhancer-AAV approach selectively targeting dentate granule cells

The mammalian brain contains the most diverse array of cell types of any organ, including dozens of neuronal subtypes with distinct anatomical and functional characteristics. The brain leverages these neuron-type-specializations to perform diverse circuit operations and thus execute different behaviors properly. Through the use of Cre lines, access to specific neuron types has steadily improved over past decades. Despite their extraordinary utility, development and cross-breeding of Cre lines is time-consuming and expensive, presenting a significant barrier to entry for many investigators. Furthermore, cell-based therapeutics developed in Cre mice are not clinically translatable. Recently, several AAV vectors utilizing neuron-type-specific regulatory transcriptional sequences (enhancer-AAVs) were developed which overcome these limitations. Using a publicly available RNAseq dataset, we evaluated the potential of several candidate enhancers for neuron-type-specific targeting in the hippocampus. Here we identified a promising enhancer-AAV for targeting dentate granule cells and validated its selectivity in wild-type adult mice.

neuroscience↗

bioRxiv2023

DENND2B activates Rab35 at the intercellular bridge regulating cytokinetic abscission and tetraploidy

Cytokinesis is the final stage of cell division. Successful cytokinesis requires membrane trafficking pathways regulated by Rabs, molecular switches activated by guanine nucleotide exchange factors (GEFs). Late in cytokinesis, an intercellular cytokinetic bridge (ICB) connecting the two daughter cells undergoes abscission, which requires depolymerization of actin. Rab35 recruits MICAL1 to oxidate and depolymerize actin filaments. We report that DENND2B, a protein previously implicated in cancer, mental retardation and multiple congenital disorders functions as a GEF for Rab35 and recruits and activates the GTPase at the ICB. Unexpectedly, the N-terminal region of DENND2B interacts with an active mutant of Rab35, suggesting that DENND2B is both a Rab35 GEF and effector. Knockdown of DENND2B delays abscission resulting in increased multinucleated cells and overaccumulation of F-actin at the ICB. F-actin accumulation leads to formation of a chromatin bridge, a process known to activate the NoCut/abscission checkpoint, and DENND2B knockdown actives Aurora B kinase, a hallmark of checkpoint activation. This study identifies DENND2B as a crucial player in cytokinetic abscission and provides insight into the multisystem disorder associated with DENND2B mutation.

cell biology↗

bioRxiv2022

GATK-gCNV: A Rare Copy Number Variant Discovery Algorithm and Its Application to Exome Sequencing in the UK Biobank

Copy number variants (CNVs) are major contributors to genetic diversity and disease. To date, exome sequencing (ES) has been generated for millions of individuals in international biobanks, human disease studies, and clinical diagnostic screening. While standardized methods exist for detecting short variants (single nucleotide and insertion/deletion variants) using tools such as the Genome Analysis ToolKit (GATK), technical challenges have confounded similarly uniform large-scale CNV analyses from ES data. Given the profound impact of rare and de novo coding CNVs on genome organization and human disease, the lack of widely-adopted and robustly benchmarked rare CNV discovery tools has presented a barrier to routine exome-wide assessment of this critical class of variation. Here, we introduce GATK-gCNV, a flexible algorithm to discover rare CNVs from genome sequencing read-depth information, which we distribute as an open-source tool packaged in GATK. GATK-gCNV uses a probabilistic model and inference framework that accounts for technical biases while simultaneously predicting CNVs, which enables self-consistency between technical read-depth normalization and variant calling. We benchmarked GATK-gCNV in 7,962 exomes from individuals in quartet families with matched genome sequencing and microarray data. These analyses demonstrated 97% recall of rare ([≤]1% site frequency) coding CNVs detected by microarrays and 95% recall of rare coding CNVs discovered by genome sequencing at a resolution of more than two exons. We applied GATK-gCNV to generate a reference catalog of rare coding CNVs in 197,306 individuals with ES from the UK Biobank. We observed strong correlations between CNV rates per gene and measures of mutational constraint, as well as rare CNV associations with multiple traits. In summary, GATK-gCNV is a tunable approach for sensitive and specific CNV discovery in ES, which can easily be applied across trait association and clinical screening.

genomics↗

bioRxiv2022

Cost-efficient whole genome-sequencing using novel mostly natural sequencing-by-synthesis chemistry and open fluidics platform

We introduce a massively parallel novel sequencing platform that combines an open flow cell design on a circular wafer with a large surface area and mostly natural nucleotides that allow optical end-point detection without reversible terminators. This platform enables sequencing billions of reads with longer read length ([~]300bp) and fast runs times (<20hrs) with high base accuracy (Q30 > 85%), at a low cost of $1/Gb. We establish system performance by whole-genome sequencing of the Genome-In-A-Bottle reference samples HG001-7, demonstrating high accuracy for SNPs (99.6%) and Indels in homopolymers up to length 10 (96.4%) across the vast majority (>98%) of the defined high-confidence regions of these samples. We demonstrate scalability of the whole-genome sequencing workflow by sequencing an additional 224 selected samples from the 1000 Genomes project achieving high concordance with reference data.

genomics↗

bioRxiv2022

A genome-wide mutational constraint map quantified from variation in 76,156 human genomes

The depletion of disruptive variation caused by purifying natural selection (constraint) has been widely used to investigate protein-coding genes underlying human disorders, but attempts to assess constraint for non-protein-coding regions have proven more difficult. Here we aggregate, process, and release a dataset of 76,156 human genomes from the Genome Aggregation Database (gnomAD), the largest public open-access human genome reference dataset, and use this dataset to build a mutational constraint map for the whole genome. We present a refined mutational model that incorporates local sequence context and regional genomic features to detect depletions of variation across the genome. As expected, proteincoding sequences overall are under stronger constraint than non-coding regions. Within the non-coding genome, constrained regions are enriched for known regulatory elements and variants implicated in complex human diseases and traits, facilitating the triangulation of biological annotation, disease association, and natural selection to non-coding DNA analysis. More constrained regulatory elements tend to regulate more constrained protein-coding genes, while non-coding constraint captures additional functional information underrecognized by gene constraint metrics. We demonstrate that this genome-wide constraint map provides an effective approach for characterizing the non-coding genome and improving the identification and interpretation of functional human genetic variation.

genetics↗

bioRxiv2022

A novel form of macropinocytosis mediates ultra-rapid transfer of pathological alpha- synuclein to lysosomes

The nervous system spread of alpha-synuclein fibrils is thought to cause Parkinsons disease (PD) and other synucleinopathies, yet the mechanisms underlying internalization and cellular spread are enigmatic. Here we use confocal and super-resolution microscopy, subcellular fractionation and electron microscopy (EM) of immunogold labelled alpha-synuclein preformed fibrils (PFF) to demonstrate that this fibril form of alpha-synuclein undergoes rapid internalization and is targeted directly to lysosomes in as little as 2 minutes. Uptake of PFF is disrupted by macropinocytic inhibitors and circumvents classical endosomal pathways. Immunogold-labelled PFF are seen at the highly curved inward edge of membrane ruffles, in newly formed macropinosomes, in multivesicular bodies and in lysosomes. While most fibrils remain in lysosomes, a portion is transferred to neighboring naive cells along with markers of exosomes. These data indicate that PFF use a unique internalization mechanism as a component of cell-to-cell propagation.

cell biology↗

bioRxiv2021

High-throughput RNA isoform sequencing using programmable cDNA concatenation

Alternative splicing is a core biological process that enables profound and essential diversification of gene function. Short-read RNA sequencing approaches fail to resolve RNA isoforms and therefore primarily enable gene expression measurements - an isoform unaware representation of the transcriptome. Conversely, full-length RNA sequencing using long-read technologies are able to capture complete transcript isoforms, but their utility is deeply constrained due to throughput limitations. Here, we introduce MAS-ISO-seq, a technique for programmably concatenating cDNAs into single molecules optimal for long-read sequencing, boosting the throughput >15 fold to nearly 40 million cDNA reads per run on the Sequel IIe sequencer. We validated unambiguous isoform assignment with MAS-ISO-seq using a synthetic RNA isoform library and applied this approach to single-cell RNA sequencing of tumor-infiltrating T cells. Results demonstrated a >30 fold boosted discovery of differentially spliced genes and robust cell clustering, as well as canonical PTPRC splicing patterns across T cell subpopulations and the concerted expression of the associated hnRNPLL splicing factor. Methods such as MAS-ISO-seq will drive discovery of novel isoforms and the transition from gene expression to transcript isoform expression analyses.

genetics↗

bioRxiv2021

Mitochondrial DNA variation across 56,434 individuals in gnomAD

Databases of allele frequency are extremely helpful for evaluating clinical variants of unknown significance; however, until now, genetic databases such as the Genome Aggregation Database (gnomAD) have ignored the mitochondrial genome (mtDNA). Here we present a pipeline to call mtDNA variants that addresses three technical challenges: (i) detecting homoplasmic and heteroplasmic variants, present respectively in all or a fraction of mtDNA molecules, (ii) circular mtDNA genome, and (iii) misalignment of nuclear sequences of mitochondrial origin (NUMTs). We observed that mtDNA copy number per cell varied across gnomAD cohorts and influenced the fraction of NUMT-derived false-positive variant calls, which can account for the majority of putative heteroplasmies. To avoid false positives, we excluded samples prone to NUMT misalignment (few mtDNA copies per cell), cell line artifacts (many mtDNA copies per cell), or with contamination and we reported variants with heteroplasmy greater than 10%. We applied this pipeline to 56,434 whole genome sequences in the gnomAD v3.1 database that includes individuals of European (58%), African (25%), Latino (10%), and Asian (5%) ancestry. Our gnomAD v3.1 release contains population frequencies for 10,850 unique mtDNA variants at more than half of all mtDNA bases. Importantly, we report frequencies within each nuclear ancestral population and mitochondrial haplogroup. Homoplasmic variants account for most variant calls (98%) and unique variants (85%). We observed that 1/250 individuals carry a pathogenic mtDNA variant with heteroplasmy above 10%. These mitochondrial population allele frequencies are publicly available at gnomad.broadinstitute.org and will aid in diagnostic interpretation and research studies.

genomics↗

bioRxiv2021

Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL)

The traditional model of genomic data analysis - downloading data from centralized warehouses for analysis with local computing resources - is increasingly unsustainable. Not only are transfers slow and cost prohibitive, but this approach also leads to redundant and siloed compute infrastructure that makes it difficult to ensure security and compliance of protected data. The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) inverts this model, providing a unified cloud computing environment for data storage, management, and analysis. AnVIL eliminates the need for data movement, allows for active threat detection and monitoring, and provides scalable, shared computing resources that can be acquired by researchers as needed. This presents many new opportunities for collaboration and data sharing that will ultimately lead to scientific discoveries at scales not previously possible.

bioinformatics↗

bioRxiv2019

Somatic Truth Data from Cell Lineage

Existing somatic benchmark datasets for human sequencing data use germline variants, synthetic methods, or expensive validations, none of which are satisfactory for providing a large collection of true somatic variation across a whole genome. Here we propose a dataset of short somatic mutations, that are validated using a known cell lineage. The dataset contains 56,974 (2,687 unique) Single Nucleotide Variations (SNV), 6,370 (316 unique) small Insertions and Deletions (Indels), and 144 (8 unique) Copy Number Variants (CNV) across 98 in silico mixed truth sets with a high confidence region covering 2.7 gigabases per mixture. The data is publicly available for use as a benchmarking dataset for somatic short mutation discovery pipelines.

bioinformatics↗

bioRxiv2019

Variation across 141,456 human exomes and genomes reveals the spectrum of loss-of-function intolerance across human protein-coding genes

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes critical for an organisms function will be depleted for such variants in natural populations, while non-essential genes will tolerate their accumulation. However, predicted loss-of-function (pLoF) variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes1. Here, we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence pLoF variants in this cohort after filtering for sequencing and annotation artifacts. Using an improved human mutation rate model, we classify human protein-coding genes along a spectrum representing tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve gene discovery power for both common and rare diseases.

genomics↗

bioRxiv2018

Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects

Hundreds of thousands of human whole genome sequencing (WGS) datasets will be generated over the next few years to interrogate a broad range of traits, across diverse populations. These data are more valuable in aggregate: joint analysis of genomes from many sources increases sample size and statistical power for trait mapping, and will enable studies of genome biology, population genetics and genome function at unprecedented scale. A central challenge for joint analysis is that different WGS data processing and analysis pipelines cause substantial batch effects in combined datasets, necessitating computationally expensive reprocessing and harmonization prior to variant calling. This approach is no longer tenable given the scale of current studies and data volumes. Here, in a collaboration across multiple genome centers and NIH programs, we define WGS data processing standards that allow different groups to produce \"functionally equivalent\" (FE) results suitable for joint variant calling with minimal batch effects. Our approach promotes broad harmonization of upstream data processing steps, while allowing for diverse variant callers. Importantly, it allows each group to continue innovating on data processing pipelines, as long as results remain compatible. We present initial FE pipelines developed at five genome centers and show that they yield similar variant calling results - including single nucleotide (SNV), insertion/deletion (indel) and structural variation (SV) - and produce significantly less variability than sequencing replicates. Residual inter-pipeline variability is concentrated at low quality sites and repetitive genomic regions prone to stochastic effects. This work alleviates a key technical bottleneck for genome aggregation and helps lay the foundation for broad data sharing and community-wide \"big-data\" human genetics studies.

bioinformatics↗

bioRxiv2017

Scaling accurate genetic variant discovery to tens of thousands of samples

Comprehensive disease gene discovery in both common and rare diseases will require the efficient and accurate detection of all classes of genetic variation across tens to hundreds of thousands of human samples. We describe here a novel assembly-based approach to variant calling, the GATK HaplotypeCaller (HC) and Reference Confidence Model (RCM), that determines genotype likelihoods independently per-sample but performs joint calling across all samples within a project simultaneously. We show by calling over 90,000 samples from the Exome Aggregation Consortium (ExAC) that, in contrast to other algorithms, the HC-RCM scales efficiently to very large sample sizes without loss in accuracy; and that the accuracy of indel variant calling is superior in comparison to other algorithms. More importantly, the HC-RCM produces a fully squared-off matrix of genotypes across all samples at every genomic position being investigated. The HC-RCM is a novel, scalable, assembly-based algorithm with abundant applications for population genetics and clinical studies.

genomics↗