Biology subjects

Michaelson, J. J.

Publications and source records attributed to Michaelson, J. J..

10 recordsLinked to original sources

bioRxiv2025

Rapidly evolved genomic regions shape individual language abilities in present-day humans

Language is a defining feature of our species, yet the genomic changes enabling it remain poorly understood. Despite decades of work since FOXP2s discovery, we still lack a clear picture of which regions shaped language evolution and how variation contributes to present-day phenotypic differences. Using a novel evolutionary stratified polygenic score approach in nearly 40,000 individuals, we find that Human Ancestor Quickly Evolved Regions (HAQERs) are specifically associated with language but not general cognition. HAQERs evolved before the human-Neanderthal split, giving hominins increased binding of Forkhead and Homeobox transcription factors, and show balancing selection across the past 20,000 years. Remarkably, language variants in HAQERs appear more prevalent in Neanderthals and have convergently evolved across vocal-learning mammals. Our results reveal how ancient innovations continue shaping human language.

evolutionary biology↗

bioRxiv2024

Long-term, cell type-specific effects of prenatal stress on dorsal striatum and relevant behaviors in mice

Maternal stress during pregnancy, or prenatal stress, is a risk factor for neurodevelopmental disorders in offspring, including autism spectrum disorder (ASD). In ASD, dorsal striatum displays abnormalities correlating with symptom severity, but there is a gap in knowledge about dorsal striatal cellular and molecular mechanisms that may contribute. Using a mouse model, we investigated how prenatal stress impacted striatal-dependent behavior in adult offspring. We observed enhanced motor learning and earlier response times on an interval timing task, with accompanying changes in time-related medium spiny neuron (MSN) activity. We performed adult dorsal striatal single-cell RNA sequencing following prenatal stress which revealed differentially expressed genes (DEGs) in multiple cell types; downregulated DEGs were enriched for ribosome and translational pathways consistently in MSN subtypes, microglia, and somatostatin neurons. DEGs in MSN subtypes over-represented ASD risk genes and were enriched for synapse-related processes. These results provide insights into striatal alterations relevant to neurodevelopmental disorders.

neuroscience↗

bioRxiv2023

Activity-induced gene expression in the human brain

Direct electrical stimulation (eSTIM) is widely used clinically, from neurosurgical mapping to therapeutic interventions for neurological and neuropsychiatric disorders1-10. Despite over a century of application, its molecular and cellular underpinnings remain unknown. Here, using state-of-the-art single-nuclei multiomic profiling, we map changes in cell-type-specific gene expression and chromatin accessibility in vivo in the human cortex following eSTIM of neurosurgery patients. eSTIM impacts a network of cells that extends beyond excitatory neurons to include inhibitory neurons, astrocytes, oligodendrocytes and microglia. We observed an upregulation of canonical immediate-early genes (IEGs: FOS, NPAS4, EGR4) in excitatory and inhibitory neurons and induction of cytokine-related genes CCL3 and CCL4 in microglia. The cross-species conservation of this gene signature, together with our examination of a cohort of both epilepsy and cancer patients, underscores the fundamental role of these changes in stimulation-driven plasticity while controlling for disease and environmental confounds. Our study of changes in chromatin accessibility reveals a common code that involves a cell-type specific signature of transcription factor binding motifs for members of the EGR family. By addressing these previously unexplored questions about activity-induced gene expression in vivo in the human brain, our findings challenge the long-standing neuron-centric view of eSTIM, highlighting the broader role of non-neuronal cells, including microglia, in mediating the impact of brain stimulation.

neuroscience↗

bioRxiv2023

Cerebellar Morphological Differences in Bipolar Disorder Type I

BackgroundThe neural underpinnings of bipolar disorder (BD) remain poorly understood. The cerebellum is ideally positioned to modulate emotional regulation circuitry yet has been understudied in BD. Previous studies have suggested differences in cerebellar activity and metabolism in BD, however findings on cerebellar structural differences remain contradictory. MethodsWe collected 3T anatomical MRI scans from participants with (N = 131) and without (N = 81) BD type I. Differences in cerebellar volumes were assessed along with factors that influence the results. ResultsThe cerebellar cortex was smaller bilaterally in participants with BD. Polygenic propensity score (bipolar N = 103, control N = 64) did not predict any cerebellar volumes, suggesting that non-genetic factors may have greater influence on the cerebellar volume difference we observed in BD. Cerebellar white matter volumes increased with more adverse childhood events, but we did not observe any associations with parental psychiatric illness. We also evaluated time from onset and symptom burden and found no associations with cerebellar volumes, suggesting neurodevelopment may differ prior to onset. Finally, we found taking sedatives was associated with larger cerebellar white matter and non-significantly larger cortical volume. LimitationsThis study was cross-sectional, limiting interpretation of possible mechanisms. Most of our participants were White, which could limit the generalizability. Additionally, we did not account for potential polypharmacy interactions. ConclusionsThese findings suggest that external influences, such as medications, may influence cerebellum structure in BD and may mask underlying differences. Accounting for medication may be critical for consistent findings in future studies.

neuroscience↗

bioRxiv2023

Mapping the spatial transcriptomic signature of the hippocampus during memory consolidation

Memory consolidation involves discrete patterns of transcriptional events in the hippocampus. Despite the emergence of single-cell transcriptomic profiling techniques, defining learning-responsive gene expression across subregions of the hippocampus has remained challenging. Here, we utilized unbiased spatial sequencing to elucidate transcriptome-wide changes in gene expression in the hippocampus following learning, enabling us to define molecular signatures unique to each hippocampal subregion. We find that each subregion of the hippocampus exhibits distinct yet overlapping transcriptomic signatures. Although the CA1 region exhibited increased expression of genes related to transcriptional regulation, the DG showed upregulation of genes associated with protein folding. We demonstrate the functional relevance of subregion-specific gene expression by genetic manipulation of a transcription factor selectively in the CA1 hippocampal subregion, leading to long-term memory deficits. This work demonstrates the power of using spatial molecular approaches to reveal transcriptional events during memory consolidation.

neuroscience↗

bioRxiv2021

Altered hippocampal transcriptome dynamics following sleep deprivation

Widespread sleep deprivation is a continuing public health problem in the United States and worldwide affecting adolescents and adults. Acute sleep deprivation results in decrements in spatial memory and cognitive impairments. The hippocampus is vulnerable to acute sleep deprivation with changes in gene expression, cell signaling, and protein synthesis. Sleep deprivation also has long lasting effects on memory and performance that persist after recovery sleep, as seen in behavioral studies from invertebrates to humans. Although previous research has shown that acute sleep deprivation impacts gene expression, the extent to which sleep deprivation affects gene regulation remains unknown. Using an unbiased deep RNA sequencing approach, we investigated the effects of acute sleep deprivation on gene expression in the hippocampus. We identified 1,146 genes that were significantly dysregulated following sleep deprivation with 507 genes upregulated and 639 genes downregulated, including protein coding genes and long non-coding RNAs not previously identified as impacted by sleep deprivation. Notably, genes significantly upregulated after sleep deprivation were associated with RNA splicing and the nucleus. In contrast, downregulated genes were associated with cell adhesion, dendritic localization, the synapse, and postsynaptic membrane. These results clearly demonstrate that sleep deprivation differentially regulates gene expression on multiple transcriptomic levels to impact hippocampal function. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=180 HEIGHT=200 SRC="FIGDIR/small/445021v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1e611eborg.highwire.dtl.DTLVardef@1a26aa2org.highwire.dtl.DTLVardef@6e8e2org.highwire.dtl.DTLVardef@1a388f0_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

The CBP KIX domain regulates long-term memory and circadian activity

CREB-dependent transcription necessary for long-term memory is driven by interactions with CREB-binding protein (CBP), a multi-domain protein that binds numerous transcription factors. Identifying specific domain functions for multi-action proteins is essential to understand processes necessary for healthy living including cognitive function and a robust circadian clock. We investigated the function of the CBP KIX domain in hippocampal memory and gene expression using CBPKIX/KIX mice with mutations that prevent phospho-CREB (Ser133) binding. We found that CBPKIX/KIX mice were impaired in long-term, but not short-term spatial memory in the Morris water maze. Using an unbiased analysis of gene expression after training for hippocampus-dependent memory, we discovered dysregulation of CREB and CLOCK target genes and downregulation of circadian genes in CBPKIX/KIX mice. With our finding that the CBP KIX domain was important for transcription of circadian genes, we profiled circadian activity in CBPKIX/KIX mice. CBPKIX/KIX mice exhibited delayed activity peaks after light offset and longer free-running periods in constant dark, although phase resetting to light was comparable to wildtype. These studies provide insight into the significance of the CBP KIX domain by defining targets of CBP transcriptional co-activation in memory and the role of the CBP KIX domain in vivo on circadian rhythms.

neuroscience↗

bioRxiv2019

Genetic research at the intersection of gender identity, sexual orientation, and mental health: community attitudes and recommendations for researchers

Biological sex is an important factor in mental health, and a non-binary view of how variation in sex and gender influence mental health represents a new research frontier that may yield new insights. The recent acceleration of research into sexual orientation, gender identity, and mental health has generally been conducted without sufficient understanding of the opinions of sexual and gender minorities (SGM) toward this research. We surveyed 768 individuals, with an enrichment of LGBTQ+ stakeholders, for their opinions regarding genetic research of SGM and mental health. We found that the key predictors of attitudes toward genetic research specifically on SGM are 1) general attitudes toward genetic and mental health research 2) tolerance of SGM and associated behaviors 3) non-cisgender stakeholder status and 4) age of the respondent. Non-heterosexual stakeholder status was significantly associated with increased willingness to participate in genetic research if a biological basis for gender identity were discovered. We also found that non-stakeholders with a low tolerance for SGM indicated their SGM views would be positively updated if science showed a biological basis for their behaviors and identities. These findings represent an important first step in understanding and engaging the LGBTQ+ stakeholder community in the context of genetic research.

scientific communication and education↗

bioRxiv2018

Calculating the Effects of Autism Risk Gene Variants on Dysfunction of Biological Processes Identifies Clinically-Useful Information

Autism spectrum disorders (ASD) are neurodevelopmental conditions that are influenced by genetic factors and encompass a wide-range and severity of symptoms. The details of how genetic variation contributes to variable symptomatology are unclear, creating a major challenge for translating vast amounts of data into clinically-useful information. To determine if variation in ASD risk genes correlates with symptomatology differences among individuals with ASD, thus informing treatment, we developed an approach to calculate the likelihood of genetic dysfunction in Gene Ontology-defined biological processes that have significant overrepresentation of known risk genes. Using whole-exome sequence data from 2,381 individuals with ASD included in the Simons Simplex Collection, we identified likely damaging variants and conducted a clustering analysis to define subgroups based on scores reflecting genetic dysfunction in each process of interest to ASD etiology. Dysfunction in cognition-related genes distinguished a distinct subset of individuals with increased social deficits, lower IQs, and reduced adaptive behaviors when compared to individuals with no evidence of cognition-related gene dysfunction. In particular, a stop-gain variant in the pharmacogene encoding cycloxygenase-2 was associated with having an IQ<70 (i.e. intellectual disability), a key comorbidity in ASD. We expect that screening genes involved in cognition for deleterious variants in ASD cases may be useful for identifying clinically-informative factors that should be prioritized for functional follow-up. This has implications in designing more comprehensive genetic testing panels and may help provide the basis for more informed treatment in ASD.

genetics↗

bioRxiv2017

TiSAn: Tissue Specific Variant Annotation

Measures of general deleteriousness, like CADD or PolyPhen, have become indispensable tools in the interpretation of genetic variants. However, these measures say little about where in the organism these deleterious effects will be most apparent. An additional, complementary measure is needed to link deleterious variants (as determined by e.g., CADD) to tissues in which their effect will be most meaningful. Here, we introduce TiSAn (Tissue Specific Annotation), a tool that predicts how related a genomic position is to a given tissue (http://github.com/kevinVervier/TiSAn). TiSAn uses machine learning on genome-scale, tissue-specific data to discriminate variants relevant to a tissue from those having no bearing on the development or function of that tissue. Predictions are then made genome-wide, and these scores can then be used to contextualize and filter variants of interest in whole genome sequencing or genome wide association studies (GWAS). We demonstrate the accuracy and versatility of TiSAn by introducing predictive models for human heart and human brain, and detecting tissue-relevant variations in large cohorts for autism spectrum disorder (TiSAn-brain) and coronary artery disease (TiSAn-heart). We find that TiSAn is better able to prioritize genetic variants according to their tissue-specific action than the current state of the art method, GenoSkyLine.

bioinformatics↗