Biology subjects

Sanders, S. J.

Publications and source records attributed to Sanders, S. J..

At least 19 recordsLinked to original sources

bioRxiv2026

A unified framework for quantitative splicing and transcript prediction

RNA splicing is frequently disrupted by genetic variation, contributing to a wide range of human diseases. Identifying the variants responsible for altered splicing is therefore crucial but has long been challenging. Deep learning models that predict splicing from genomic sequence have substantially advanced their detection, but accurately resolving their quantitative effects on splicing and the resulting transcripts remains an unmet need. Here we introduce SpliceAI2, a deep learning model trained end-to-end on splice site, splice junction, and transcript usage across multiple mammalian species. SpliceAI2 reconstructs complete transcripts directly from genomic sequence and considerably improves identification of splice-altering variants and quantification of their effects in diverse benchmarks spanning cryptic splicing, splicing quantitative trait loci, and massively parallel reporter assays. Human population datasets provide independent validation of these predicted functional effects through evidence of natural selection and associated changes in plasma protein abundance. Application to a rare disease cohort reveals that predicted splice-altering variants are highly enriched in disease-associated genes and account for 15% of the excess genetic burden, with approximately half residing in deep intronic regions likely missed by exome sequencing. Together, these findings establish SpliceAI2 as a major step forward in interpreting splice-altering variants across the human genome.

genomics↗

bioRxiv2026

Machine learning-assisted directed evolution yields dramatic improvement on novel AAV engineering task

Directed evolution enables the discovery of protein mutants with improved fitness through iterative rounds of selection and has been widely applied to adeno-associated virus (AAV) capsid engineering. Machine learning (ML) can augment this process by prioritising mutants for experimental validation, but whether its benefits outweigh the added cost of ML-designed library construction remains unclear. Here, we address this question by considering improvements in manufacturing efficiency of AAV capsids in the context of exosomal encapsulation, which is a technique for improving AAV immunogenicity. We generated a directed evolution dataset comprising 53,974 mutants across three rounds of selection and an independent assessment dataset of 472 ML-designed mutants with detailed profiling. Directed evolution alone yielded a 3-fold improvement, while ML-assisted directed evolution yielded a 41-fold improvement in manufacturing efficiency, demonstrating that ML-assisted directed evolution outperforms directed evolution alone. We show that data quality - specifically the number of selection rounds and the statistical power of mutant counts - has a greater impact on model performance than model architecture. Finally, we provide practical guidance on experimental design and implementation of ML tuning strategies that can augment model performance in protein engineering applications.

bioengineering↗

bioRxiv2026

Spatial transcriptomics implicates the thalamus and cortex in autism and schizophrenia

The past decade has seen tremendous progress in the identification of genes associated with complex neuropsychiatric disorders, including autism spectrum disorder (ASD) and schizophrenia. Expression patterns of these genes in single cell data strongly implicate excitatory and inhibitory neurons; however, there are limited data on the brain regions involved - a critical question for neurobiology. Spatial transcriptomics provide an opportunity to perform systematic multiregional analyses to provide insights into this question. Here, we have generated a spatial transcriptomics dataset encompassing the diverse anatomical territories of the adult mouse brain sagittal midsection. We compare neuropsychiatric gene enrichment by applying Gene Fraction Enrichment Score (GFES), a novel statistic method that controls for differing neuronal proportions across regions. ASD-associated genes identified by exome sequencing were most enriched in the thalamus followed by the cortex. Schizophrenia genes from genome-wide association studies were also enriched in the thalamus, along with the hippocampus and cortex. These findings add to the evidence that the thalamus plays a major role in neuropsychiatric disorders whilst supporting roles for the cortex and hippocampus. The results highlight shared and distinct patterns for pleiotropic brain disorders that could elucidate common underlying mechanisms and circuitry.

neuroscience↗

bioRxiv2026

Spatiotemporal analysis of autism gene enrichment implicates cortex, thalamus, and hypothalamus

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder. Sequencing analyses have identified 185 ASD-associated genes, which implicate neurons, but the specific brain regions through which these neurons influence neurodevelopment remain unclear. Here, we integrate over one million single-cell RNA sequencing profiles from 20 regions of the developing human brain (4-23 post-conceptual weeks) using a new framework, STARMAPS (Sparse Task-specific Analysis for Revealing Molecular Associations in Particular Single-cell datasets). STARMAPS accounts for coordinated regional and developmental perturbations in gene expression, enabling robust cross-region comparison. We replicate prior findings that ASD-associated genes are enriched in excitatory neurons during mid-fetal development, and we extend these results to reveal distinct spatial signatures. Across 26 excitatory neuron subtypes, six clusters showed significant enrichment for ASD-associated genes. These clusters localize to both cortical and subcortical regions, including the motor, temporal, and visual cortex, as well as the thalamus and hypothalamus. Our findings support a major role for excitatory neurons across distributed brain circuits, implicating previously underappreciated subcortical structures in ASD etiology. By providing a statistically rigorous framework for spatiotemporal integration of single-cell data, STARMAPS enables refined mapping of molecular vulnerability across the developing human brain.

genomics↗

bioRxiv2026

Molecular dynamics of Brodmann Area 22 in development and autism

Challenges in verbal communication are a prominent feature of autism. However, gene regulatory programs in speech-related cortical regions remain poorly characterized. In parallel, it remains unclear whether the heterogeneous genetic factors underlying autism converge on shared neurobiological mechanisms. To address these gaps, we generated paired transcriptomic and epigenomic data from post-mortem human brain tissue across 100 donors. Here, we show that transcriptional differences in the speech-related Brodmann Area 22 in individuals with neurodevelopmental conditions, including autism, are strongest among those with a known genetic diagnosis. A similar but attenuated signature is observed in those without a genetic diagnosis. These transcriptional differences are most pronounced in neurons, with glutamatergic L4/5 intratelencephalic neurons affected across multiple modalities. Finally, multimodal analysis implicates altered RFX3-dependent networks as a central hub in autism, particularly among L4/5 intratelencephalic neurons in non-verbal individuals. Together, our study identifies regulatory architecture linking chromatin state, transcriptional output, and variation in verbal ability in autism.

neuroscience↗

bioRxiv2026

Genome-scale functional mapping of the mammalian whole brain with in vivo Perturb-seq

Functional genomics studies have provided critical insights into cell type-specific gene regulatory programs, but to date most have been conducted in wild-type tissues or cell cultures. Here, we present a gene expression functional atlas across the mouse brain. We use an enhanced in vivo Perturb-seq platform to analyze transcriptome-wide responses to loss of 1,947 disease-associated genes, profiling over 7.7 million cells spanning major brain regions and neuronal populations. We find striking cell-type-specific essentiality and transcriptional programs and show that closely related disease genes such as two NMDA receptor subunits can drive opposing transcriptional programs. Together, this work reveals insights into the genetics and mechanisms of neurodevelopmental, psychiatric, and neurodegenerative diseases in vivo, paving the way for the design of future genetic medicine.

genomics↗

bioRxiv2025

A Retinoic Acid Autoregulatory Loop Governing Prefrontal-Motor Arealization

The frontal lobe comprises the prefrontal association cortex (PFC), which supports complex cognition and goal-directed behavior, and the motor cortex (MC), which executes movement. A hallmark of primate brain evolution is PFC expansion accompanied by a posterior displacement of the MC. Retinoic acid (RA) signaling has emerged as a key regulator of PFC specification and expansion. However, the mechanisms that spatially confine RA signaling within the developing PFC, and the downstream RA-responsive gene networks, remain poorly understood. Here we defined an RA-associated gene regulatory network (RA-GRN) in the developing human PFC and identified MEIS2, which encodes a transcription factor linked to intellectual disability and autism spectrum disorder (ASD), as its key hub of this network. Conditional deletion of Meis2 in postmitotic cortical excitatory neurons in mice results in a partial respecification of prospective prefrontal association territories toward motor-like molecular and connectional features, highlighting a critical role of postmitotic neurons in establishing and maintaining cortical areal identities. Concomitant with Meis2 loss, the population of excitatory neurons expressing the RA-synthesizing enzyme ALDH1A3, and consequently RA signaling itself, is markedly reduced in the developing medial prefrontal cortex (mPFC). These findings revealed a conserved autoregulatory loop: RA [->] MEIS2 [->] ALDH1A3 [->] RA that reinforces a PFC-enriched RA gradient and organizes the MC-PFC axis. Together, our findings reveal a postmitotic mechanism by which specific features of neuronal identity reinforce RA signaling to define key features of prefrontal and motor cortical territories, linking a classic morphogen to transcriptional identity, neural circuit formation and function, and potentially to psychiatric disorders.

neuroscience↗

bioRxiv2025

Engineered AAV Capsids with Enhanced Extracellular Vesicle Loading via Rational Design and Directed Evolution

Overcoming immune responses and ensuring efficient delivery remain key obstacles to advancing adeno-associated virus (AAV)-based genetic medicines into the clinic. Encapsulating AAVs within naturally secreted extracellular vesicles (EV-AAV) can shield them from neutralising antibodies and increase transduction efficiency; however, wild-type AAV capsids are incorporated into EVs inefficiently, with the percentage of total AAV genomes in the EV-AAV fraction ranging from 0.5% to 12%, depending on AAV serotype. Here, we establish a high-throughput screening platform that links AAV capsid genotype to EV encapsulation phenotype to improve encapsulation efficiency. We combined rational design with directed evolution to engineer AAV9 variants that preferentially sort into EVs. A library of 392,550 AAV9 capsid mutants was generated by inserting Late (L) domains, established EV-sorting motifs, and fully random amino acid inserts in a surface-exposed region of the AAV9 capsid protein. Screening data were analysed using a statistical model-assisted protein selection (SMAPS) workflow - developed as a novel quantitative modelling and selection strategy for protein engineering challenges of this kind. SMAPS functions as a digital twin of the protein variants in our high-throughput screen, allowing us to monitor uncertainty in copy numbers over multiple steps in the experimental workflow. Using SMAPS, we identified five lead hits, which showed up to threefold increased EV-AAV yield compared to wild-type, without altering particle size. Moreover, in vitro transduction experiments demonstrated that the lead AAV9 capsid exhibits substantially higher transduction efficiency compared to wild-type AAV9 and retained functional activity in the presence of neutralising anti-AAV9 antibodies. Collectively, our study: (i) delivers a scalable high-throughput screen for EV-AAV engineering, (ii) introduces the fields first statistical model-guided quality-control framework for directed evolution, and (iii) provides best-in-class capsids for EV encapsulation.

synthetic biology↗

bioRxiv2025

Modulating splicing in five prime untranslated regions to treat rare haploinsufficient disease

Rare genetic disorders collectively impact over 300 million people worldwide, yet around 95% have no specific treatments. For the many rare disorders caused by haploinsufficiency, effective therapies need to upregulate protein expression. However, therapeutic upregulation is often not straightforward. Increasing protein translation of the wildtype allele through inhibiting repressive upstream open reading frames (uORFs) has been proposed as a therapeutic approach for a few specific genes. The widespread success of steric-block antisense oligonucleotides (ASOs) for this purpose is, however, debated. Here, we explore an alternative approach, using splice-switching to exclude uORF-containing exons from the mRNA. Through a genome-wide computational screening approach, we identified 79 uORF-containing 5UTR exons in haploinsufficient monogenic disease genes as candidate exon skipping targets. We demonstrate that removing the target exon significantly increased protein translation (between 1.4-5.5 fold) in a luciferase reporter assay for four of six prioritised target 5UTR exons in neurodevelopmental disorder genes (CTCF, GRIN2B, KRIT1, and TSC1). Overall, this work supports the widespread application of 5UTR exon skipping to boost translation of clinically relevant haploinsufficient genes.

genomics↗

bioRxiv2025

Disruption of Cell-Type-Specific Molecular Programs of Medium Spiny Neurons in Autism

Autism spectrum disorders (ASD) are highly heritable neurodevelopmental conditions with major contributions from rare genetic variants. Most studies have focused on cortical mechanisms; even growing evidence implicates subcortical circuits in ASD etiology. To systematically map developmental and molecular alterations beyond the cortex, we profiled lineage relationships across five brain regions in an ASD mouse model. Most prominent changes emerged in the striatum, a hub for learning and motor control. Furthermore, we performed single-nucleus multiomic profiling of human putamen from ASD and neurotypical donors revealed cell-type-specific transcriptomic and regulatory alterations. Differential expression converged on synaptic and energy metabolic dysfunctions in D1 striosome medium spiny neurons (MSNs), coupled with astrocytic remodeling of synaptic support. Gene regulatory network analysis identified EGR3 and EGR1 as key transcriptional regulators of ASD-associated programs of D1 MSNs. Together, these results establish the striatum as a central node of ASD convergence and provide a multiomic resource for dissecting its subcortical mechanisms.

neuroscience↗

bioRxiv2025

Large-scale discovery of neural enhancers for cis-regulation therapies

CRISPR-based gene activation (CRISPRa) has emerged as a promising therapeutic approach for neurodevelopmental disorders (NDD) caused by haploinsufficiency. However, scaling this cis-regulatory therapy (CRT) paradigm requires pinpointing which candidate cis-regulatory elements (cCREs) are active in human neurons, and which can be targeted with CRISPRa to yield specific and therapeutic levels of target gene upregulation. Here, we combine Massively Parallel Reporter Assays (MPRAs) and a multiplex single cell CRISPRa screen to discover functional human neural enhancers whose CRISPRa targeting yields specific upregulation of NDD risk genes. First, we tested 5,425 candidate neuronal enhancers with MPRA, identifying 2,422 that are active in human neurons. Selected cCREs also displayed specific, autonomous in vivo activity in the developing mouse central nervous system. Next, we applied multiplex single-cell CRISPRa screening with 15,643 gRNAs to test all MPRA-prioritized cCREs and 761 promoters of NDD genes in their endogenous genomic contexts. We identified hundreds of promoter- and enhancer-targeting CRISPRa gRNAs that upregulated 200 of the 337 NDD genes in human neurons, including 91 novel enhancer-gene pairs. Finally, we confirmed that several of the CRISPRa gRNAs identified here demonstrated selective and therapeutically relevant upregulation of SCN2A, CHD8, CTNND2 and TCF4 when delivered virally to patient cell lines, human cerebral organoids, and a humanized mouse model of hTcf4. Our results provide a comprehensive resource of active, target-linked human neural enhancers for NDD genes and corresponding gRNA reagents for CRT development. More broadly, this work advances understanding of neural gene regulation and establishes a generalizable strategy for discovering CRT gRNA candidates across cell types and haploinsufficient disorders.

genomics↗

bioRxiv2025

Accurately modelling RNase H-mediated antisense oligonucleotide efficacy

Antisense oligonucleotides (ASOs) are a powerful class of drugs with the potential to treat a wide range of human diseases. However, the prediction of ASO efficacy remains challenging, as large-scale and costly experimental screens are typically required to identify optimal candidates for a specific therapeutic target. To address this challenge, we compiled ASO Atlas, a database comprising 188,521 RNase H-mediated ASO sequences targeting 334 unique genes with corresponding knockdown efficacy measurements extracted from published patents. Using ASO Atlas, we trained OligoAI, a deep learning model capable of jointly modelling RNA target context, ASO sequence, sugar and backbone chemistries, and dosage to predict in vitro efficacy. We experimentally validated OligoAI by targeting KCNT2, achieving a 5.72-fold reduction in screening effort compared to random selection. ASO Atlas provides the first systematic resource to rigorously evaluate hypotheses regarding key parameters in ASO design, including sequence composition, chemical modifications, and target region selection. Both ASO Atlas and OligoAI have been made freely accessible through an online web-tool with the aim of facilitating the accelerated optimisation of ASO design.

bioinformatics↗

bioRxiv2025

Targeted BDNF upregulation via upstream open reading frame disruption

To understand the relative contributions of 5' UTR elements to translation, we performed a comprehensive analysis of upstream open reading frames (uORFs) across a representative 5' UTR. We selected the neurotrophin BDNF (Brain derived neurotrophic factor) as an exemplar as upregulation of this protein is a potential therapeutic approach for a plethora of neurodevelopmental, neurodegenerative, and neuropsychiatric disorder indications. Predicted uORFs were identified in 14 out of 17 BDNF RefSeq transcript isoforms, and experimentally confirmed to be exerting translation repression effects for five of these transcripts. These findings suggest that uORF elements play an important role in shaping the protein output from this locus. We explored several approaches to disrupt BDNF uORF function. Deletion of a 5' UTR exon in BDNF v11 (containing eight predicted uORFs), in order to simulate an exon skipping outcome, resulted in pronounced upregulation in a reporter construct system. This effect was found to be partially uORF-dependent, but was also dependent on the disruption of an RNA secondary structure element. However, this transcript variant was found to not be expressed in human brain. Conversely, direct disruption of a single uORF start codon in the widely expressed BDNF v4 transcript variant using an adenine base editing approach resulted in a [~]1.8-fold upregulation of endogenous BDNF protein expression in cell culture. This study describes novel BDNF regulatory mechanisms, and potential uORF-targeted modalities for therapeutic gene activation.

molecular biology↗

bioRxiv2024

Massively parallel reporter assays and mouse transgenic assays provide complementary information about neuronal enhancer activity

Genetic studies find hundreds of thousands of noncoding variants associated with psychiatric disorders. Massively parallel reporter assays (MPRAs) and in vivo transgenic mouse assays can be used to assay the impact of these variants. However, the relevance of MPRAs to in vivo function is unknown and transgenic assays suffer from low throughput. Here, we studied the utility of combining the two assays to study the impact of non-coding variants. We carried out an MPRA on over 50,000 sequences derived from enhancers validated in transgenic mouse assays and from multiple fetal neuronal ATAC-seq datasets. We also tested over 20,000 variants, including synthetic mutations in highly active neuronal enhancers and 177 common variants associated with psychiatric disorders. Variants with a high impact on MPRA activity were further tested in mice. We found a strong and specific correlation between MPRA and mouse neuronal enhancer activity including changes in neuronal enhancer activity in mouse embryos for variants with strong MPRA effects. Mouse assays also revealed pleiotropic variant effects that could not be observed in MPRA. Our work provides a large catalog of functional neuronal enhancers and variant effects and highlights the effectiveness of combining MPRAs and mouse transgenic assays.

genomics↗

bioRxiv2023

AlphaMissense is better correlated with functional assays of missense impact than earlier prediction algorithms

Missense variants that alter a single amino acid in the encoded protein contribute to many human disorders but pose a substantial challenge in interpretation. Though these variants can be reliably identified through sequencing, distinguishing the clinically significant ones remains difficult, such that "Variants of Unknown Significance" outnumber those classified as "Pathogenic" or "Likely Pathogenic." Numerous in silico approaches have been developed to predict the functional impact of missense variants to inform clinical interpretation, the latest being AlphaMissense, which uses artificial intelligence methods trained on predicted protein structure. To independently assess the performance of AlphaMissense and 38 other predictors of missense severity, we compared predictions to data from multiplexed assays of variant effect (MAVE). MAVE experiments generate almost every possible individual amino acid change in a gene and measure their functional impact using a high-throughput assay. Assessing 17,696 variants across five genes (DDX3X, MSH2, PTEN, KCNQ4, and BRCA1), we find that AlphaMissense is consistently one of the top five algorithms based on correlation with functional impact and is the best-correlated algorithm for two genes. We conclude that AlphaMissense represents the current best-in-class predictor by this metric; however, the improvement over other algorithms is modest. We note that multiple missense predictors, including AlphaMissense, appear to overcall variants as pathogenic despite minimal functional impact and that substantially more high-quality training data, including consistently analyzed patient cohorts and MAVE analyses, are required to improve accuracy.

genetics↗

bioRxiv2023

Multiplex, single-cell CRISPRa screening for cell type specific regulatory elements

CRISPR-based gene activation (CRISPRa) is a promising therapeutic approach for gene therapy, upregulating gene expression by targeting promoters or enhancers in a tissue/cell-type specific manner. Here, we describe an experimental framework that combines highly multiplexed perturbations with single-cell RNA sequencing (sc-RNA-seq) to identify cell-type-specific, CRISPRa-responsive cis-regulatory elements and the gene(s) they regulate. Random combinations of many gRNAs are introduced to each of many cells, which are then profiled and partitioned into test and control groups to test for effect(s) of CRISPRa perturbations of both enhancers and promoters on the expression of neighboring genes. Applying this method to a library of 493 gRNAs targeting candidate cis-regulatory elements in both K562 cells and iPSC-derived excitatory neurons, we identify gRNAs capable of specifically upregulating intended target genes and no other neighboring genes within 1 Mb, including gRNAs yielding upregulation of six autism spectrum disorder (ASD) and neurodevelopmental disorder (NDD) risk genes in neurons. A consistent pattern is that the responsiveness of individual enhancers to CRISPRa is restricted by cell type, implying a dependency on either chromatin landscape and/or additional trans-acting factors for successful gene activation. The approach outlined here may facilitate large-scale screens for gRNAs that activate therapeutically relevant genes in a cell type-specific manner.

genomics↗

bioRxiv2022

Autism-associated transcriptional regulators target shared loci proximal to brain-expressed genes.

Many autism spectrum disorder (ASD)-associated genes act as transcriptional regulators (TRs). ChIP-seq was used to identify the regulatory targets of ARID1B, BCL11A, FOXP1, TBR1, and TCF7L2, ASD-associated TRs in the developing human and mouse cortex. These TRs shared substantial overlap in the binding sites, especially within open chromatin. The overlap within a promoter region, 1-2,000bp upstream of transcription start site, was highly predictive of brain expressed genes. This signature was observed at 96 out of 102 ASD-associated genes. In vitro CRISPRi against ARID1B and TBR1 delineated downstream convergent biology in mouse cortical cultures. After eight days, NeuN+ and CALB+ cells were decreased, GFAP+ cells were increased, and transcriptomic signatures correlated with the postmortem brain samples from individuals with ASD. We suggest functional convergence across five ASD-associated TRs leads to shared neurodevelopmental outcomes of haploinsufficient disruption.

genomics↗

bioRxiv2022

Physical and functional convergence of the autism risk genes Scn2a and Ank2 in neocortical pyramidal cell dendrites

Dysfunction in sodium channels and their ankyrin scaffolding partners have both been implicated in neurodevelopmental disorders, including autism spectrum disorder (ASD). In particular, the genes SCN2A, which encodes the sodium channel NaV1.2, and ANK2, which encodes ankyrin-B, have strong ASD association. Recent studies indicate that ASD-associated haploinsufficiency in Scn2a impairs dendritic excitability and synaptic function in neocortical pyramidal cells, but how NaV1.2 is anchored within dendritic regions is unknown. Here, we show that ankyrin-B is essential for scaffolding NaV1.2 to the dendritic membrane of mouse neocortical neurons, and that haploinsufficiency of Ank2 phenocopies intrinsic dendritic excitability and synaptic deficits observed in Scn2a+/- conditions. Thus, these results establish a direct, convergent link between two major ASD risk genes and reinforce an emerging framework suggesting that neocortical pyramidal cell dendritic dysfunction can be etiological to neurodevelopmental disorder pathophysiology.

neuroscience↗