Gregory E. Crawford

The paper assesses regulatory activity of cortical structure-associated variants using MPRA in human neural progenitor cells, identifying 918 variants with regulatory potential and showing condition-dependent effects.

The paper uses CRISPR-based functional genomics to identify noncoding regulatory elements and variants affecting schizophrenia-associated gene expression.

The paper investigates sex-specific molecular responses to early-life toxicant exposures in mice across multiple life stages using transcriptomic and epigenomic data.

This study quantifies intrinsic dCas9-DNA recognition using TANGO, identifying key factors affecting gRNA performance and revealing new aspects of dCas9 specificity.

The paper identifies multi-enhancer regulatory hubs critical for Th17 cell identity by analyzing chromatin accessibility and enhancer function in mouse CD4+ T cell subsets.

This paper shows that astrocytes reprogram neuronal gene expression and chromatin accessibility, affecting thousands of genes and regulatory elements, including those linked to schizophrenia and Alzheimer's disease.

The paper identifies a CRISPRa gRNA with broad off-target activity that enables genome-wide transcriptional reprogramming, showing that mismatch tolerance and PAM-proximal bases determine binding specificity.

This study identifies hundreds of new cis-regulatory element-gene connections in the MHC locus using CRISPR screens and single-cell transcriptomics, revealing cell type-specific regulatory mechanisms.

The paper identifies a non-coding variant causing GSD IX γ2, validates its splicing effects, and demonstrates reversal using antisense oligonucleotides.

The paper identifies transcription factors for reprogramming human astrocytes to neurons using CRISPRa screens and scRNA-seq, showing INSM1's broad neurogenic activity and cofactor interactions.

The paper identifies mechanoenhancers that regulate transcription in response to matrix stiffness and shows their potential for reprogramming cellular responses to mechanical cues.

This study compares the transcriptomic landscapes of Alzheimer's disease, Dementia with Lewy bodies, and Parkinson's disease using single-nucleus RNA sequencing to identify shared and distinct molecular features.

The paper develops CLEANSER, a model to filter ambient gRNAs in single-cell CRISPR screens, improving gRNA-cell assignment accuracy and differential gene expression analysis.

The paper identifies 46,802 enhancers and 164 psychiatric disorder variants with regulatory effects in the developing cortex and organoids using massively parallel reporter assays and deep learning.

The paper generates a molecular neuroanatomical map of the human prefrontal cortex using spatial transcriptomics and single nucleus RNA-sequencing, revealing novel spatial domains and cell-cell interactions linked to psychiatric disorders.

This paper introduces launch-dCas9, a machine learning framework to predict guide RNA effects in CRISPR epigenome editing, showing high accuracy and improved gRNA selection.

The paper uses MPRA in forebrain organoids to validate enhancer activity in early human neurodevelopment, identifying over 2,300 enhancers with temporal-specific activity.

The paper constructs an enhancer-driven gene regulatory network from human forebrain organoids with ASD and neurotypical controls, identifying key regulators of excitatory neuron specification in macrocephalic ASD.

This study uses single-nucleus multi-omics data to identify cis and trans regulatory networks and their target genes in Alzheimer's disease brains.

The paper introduces TOP, a Bayesian framework that quantifies TF occupancy across many conditions using a single DNase-seq experiment, showing changes in 1500 TF motifs across cell types, hormone exposure, and genetic backgrounds.

The paper identifies enhancer elements that regulate epicardial gene expression during zebrafish heart regeneration by analyzing transcriptomes and chromatin accessibility.

The paper identifies sex-dependent glial-specific chromatin accessibility changes in late-onset Alzheimer's disease brains using ATAC-seq and links them to LOAD-GWAS regions.

The paper identifies cell-type specific effects of genetic variation on chromatin accessibility during human neuronal differentiation and links these to regulatory mechanisms of neuropsychiatric disorder risk variants.

The paper screens non-coding regulatory elements in human cells to identify those affecting cell fitness and establishes connections between regulatory elements and target genes.

The paper integrates GWAS data with functional genomic annotations of decidual stromal cells to identify loci and target genes associated with gestational duration and preterm birth.

This study identifies traits associated with polygenic risk for depression using UK Biobank data and finds causal links between depression risk and brain structure, as well as environmental interactions.

The paper identifies genetic regulators of gene expression and chromatin accessibility across multiple tissues using a genetically diverse mouse population and proposes a causal model for gene regulation.

This study identifies 73 genome-wide significant loci for mood disorders, revealing shared and distinct genetic factors between major depressive disorder and bipolar disorder.

This study investigates whether genetic variation in the Major Histocompatibility Complex (MHC) is associated with depression risk, finding no significant associations at a conservative threshold.

The paper examines how genetic and environmental factors influence DNA methylation at variably methylated regions in neonatal blood, finding that combined effects best explain methylation variability.