Colleen A. McClung

This study investigates diurnal variations in cholinergic interneuron activity and nicotinic signaling in the nucleus accumbens using electrophysiological recordings in rodents.

This study performs a single-nucleus transcriptome-wide association study to identify gene-trait associations in brain disorders, revealing cell-type-specific genetic regulation and ancestry-specific patterns.

The paper constructs a single-nucleus atlas of genetic regulation in the human brain, identifying cell-type-specific regulatory effects and disease-associated genes.

This paper develops a zwitterionic polymer coating to enable chronic dopamine sensing and electrophysiology recording in freely moving mice over four weeks.

The paper introduces gecco, a gene-specific normalization method for bulk RNA-seq that reduces library size bias while preserving biological signal, improving differential expression and pathway analysis.

This study shows that prenatal circadian rhythm disruption in mice leads to sex-specific behavioral changes in adulthood, with females showing mood-related issues and males showing substance use-like behaviors.

The paper identifies genomic loci associated with cellular rhythms in Diversity Outbred mice using QTL mapping and connects them to circadian regulation and complex traits.

This study identifies tissue-specific molecular signatures and convergent pathways in suicide by analyzing transcriptomic data from blood and brain tissues.

This study identifies cell-type and sex-specific gene expression and electrophysiological rhythms in mouse prefrontal cortex neurons, showing differences in rhythmic transcripts and biological processes between excitatory pyramidal cells and inhibitory PV interneurons.

This study compares circadian transcriptomic rhythms in mouse and human prefrontal cortex subregions, finding conserved signaling with sex-specific phase shifts and species-specific rhythmic transcript identities.

This study creates a single-nucleus transcriptomic atlas of the human DLPFC across the lifespan, revealing three transcriptomic phases and ten age-related trajectories linked to neurodevelopmental and neurodegenerative disease risk.

The paper identifies a multi-region brain network that encodes anxiety in healthy and depressive states using electrical recordings and machine learning in mice.

This study shows that microbial circadian rhythms influence sex differences in host gene expression and metabolism, with diet affecting these sex-specific patterns.

The paper develops a sparse negative binomial classifier for RNA-seq data that adjusts for covariates and improves prediction accuracy and feature selection.

The paper identifies 12-hour ultradian rhythms in the human prefrontal cortex and shows disruptions in schizophrenia affecting genes related to protein processing and mitochondrial function.

This study shows that manipulating SCN neural activity in mice affects anxiety-like behavior but not depressive-like behavior, with dampened activity rhythms correlating with increased anxiety.

This paper introduces CircaPower, a statistical method for power calculation in circadian rhythmicity detection, validated through simulations and real data.

This paper introduces likelihood-based methods to detect circadian rhythmicity and differential circadian patterns in transcriptomic data, showing improved error control and power in simulations and real data.

This study investigates how NPAS2 mutations affect cocaine self-administration in mice, showing sex- and time-of-day-dependent changes in reward and motivation.

This study shows that including genetic and sex differences in mice improves the alignment of addiction-related traits with human studies.