Addiction-Associated Genetic Variants Implicate Brain Cell Type- and Region-Specific Cis-Regulatory Elements in Addiction Neurobiology

Srinivasan, Chaitanya; Phan, BaDoi N.; Lawler, Alyssa J.; Ramamurthy, Easwaran; Kleyman, Michael; Brown, Ashley R.; Kaplow, Irene M.; Wirthlin, Morgan; Pfenning, Andreas

doi:10.1523/jneurosci.2534-20.2021

Cited by 24 publications

(21 citation statements)

References 136 publications

(329 reference statements)

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“…Finally, our conditional hereditability enrichment analysis identified associations between several striatal cell types to a broad panel of human neurological and psychiatric diseases as well as several psychosocial domains. Our heritability enrichment analyses are consistent with previous studies that linked SPNs to human diseases 54,59–61 . Notably, these earlier studies were limited by the resolution of their annotations since they did not differentiate SPN cell types.…”

Section: Discussionsupporting

confidence: 91%

Integrative multi-dimensional characterization of striatal projection neuron heterogeneity in adult brain

Gayden

Puig

Srinivasan

et al. 2023

Preprint

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Striatal dopamine (DA) neurotransmission is critical for an array of reward-related behaviors and goal-directed motor control. In rodents, 95% of striatal neurons are GABAergic medium spiny neurons (MSNs) that have been traditionally segregated into two subpopulations based on the expression of stimulatory DA D1-like receptors versus inhibitory D2-like receptors. However, emerging evidence suggests that striatal cell composition is anatomically and functionally more heterogenous than previously appreciated. The presence of MSNs that co-express multiple DA receptors offers a means to more accurately understand this heterogeneity. To dissect the precise nature of MSN heterogeneity, here we used multiplex RNAscope to identify expression of three predominantly expressed DA receptors in the striatum: DA D1 (D1R), D2 (D2R), and D3 (D3R) receptors. We report heterogenous subpopulations of MSNs that are distinctly distributed across the dorsal-ventral and rostral-caudal axes of the adult mouse striatum. These subpopulations include MSNs that co-express D1R and D2R (D1/2R), D1R and D3R (D1/3R), and D2R and D3R (D2/3R). Overall, our characterization of distinct MSN subpopulations informs our understanding of region-specific striatal cell heterogeneity.

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Section: Discussionsupporting

confidence: 91%

Integrative multi-dimensional characterization of striatal projection neuron heterogeneity in adult brain

Gayden

Puig

Srinivasan

et al. 2023

Preprint

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“…Genes implicated in schizophrenia are expressed specifically in MSNs, rather than interneurons, astrocytes, or glia 4 . With respect to reward pathophysiology, a robust literature implicates A2a- and D1-MSN specific connectivity 5 , gene expression 6 and chromatin accessibility 7 . In addition to cell-type specificity, transcriptomic profiling underscores individual subject variation in pathogenic gene expression associated with several brain disorders 8 .…”

Section: Introductionmentioning

confidence: 99%

Cell-type specific profiling of histone post-translational modifications in the adult mouse striatum

et al. 2022

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Epigenetic gene regulation in the heterogeneous brain remains challenging to decipher with current strategies. Bulk tissue analysis from pooled subjects reflects the average of cell-type specific changes across cell-types and individuals, which obscures causal relationships between epigenetic modifications, regulation of gene expression, and complex pathology. To address these limitations, we optimized a hybrid protocol, ICuRuS, for the isolation of nuclei tagged in specific cell-types and histone post translational modification profiling from the striatum of a single mouse. We combined affinity-based isolation of the medium spiny neuron subtypes, Adenosine 2a Receptor or Dopamine Receptor D1, with cleavage of histone-DNA complexes using an antibody-targeted micrococcal nuclease to release DNA complexes for paired end sequencing. Unlike fluorescence activated cell sorting paired with chromatin immunoprecipitation, ICuRuS allowed for robust epigenetic profiling at cell-type specific resolution. Our analysis provides a framework to understand combinatorial relationships between neuronal-subtype-specific epigenetic modifications and gene expression.

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“…To demonstrate the ability to predict OCR differences across species, we curated publicly available data to create a dataset of brain OCRs and their orthologs across dozens of species (Methods). Specifically, we created two positive sets: The first consisted of brain OCRs from Mus musculus [ 66 ], which we used to evaluate the ability of a model trained in one species to generalize to species not used in training. The second consisted of brain OCRs from Homo sapiens [ 41 , 67 , 68 ], Macaca Mulatta [ 64 ], Mus musculus [ 66 ], and Rattus norvegicus [ 64 ].…”

Section: Resultsmentioning

confidence: 99%

“…Specifically, we created two positive sets: The first consisted of brain OCRs from Mus musculus [ 66 ], which we used to evaluate the ability of a model trained in one species to generalize to species not used in training. The second consisted of brain OCRs from Homo sapiens [ 41 , 67 , 68 ], Macaca Mulatta [ 64 ], Mus musculus [ 66 ], and Rattus norvegicus [ 64 ]. Rather than focus on longer regions, which have been shown to work well in some previous studies [ 57 , 59 ], we used 500 bp regions for multiple reasons.…”

Section: Resultsmentioning

confidence: 99%

Inferring mammalian tissue-specific regulatory conservation by predicting tissue-specific differences in open chromatin

et al. 2022

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Background Evolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation of many enhancers, distal regulatory elements that control spatial and temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high. Results We present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that can predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Next, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss of regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity have a stronger tendency than the general population to have predicted lineage-specific open chromatin. Conclusion The framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements.

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Addiction-Associated Genetic Variants Implicate Brain Cell Type- and Region-Specific Cis-Regulatory Elements in Addiction Neurobiology

Abstract: We would like to thank members of the Eric Yttri lab and Aryn Gittis lab at Carnegie Mellon University for providing Drd1-cre, Adora2a-cre, and PValb-2a-Cre mice for cell type-specific ATAC-seq experiments.

Cited by 24 publications

References 136 publications

Integrative multi-dimensional characterization of striatal projection neuron heterogeneity in adult brain

Integrative multi-dimensional characterization of striatal projection neuron heterogeneity in adult brain

Cell-type specific profiling of histone post-translational modifications in the adult mouse striatum

Inferring mammalian tissue-specific regulatory conservation by predicting tissue-specific differences in open chromatin

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