A chromosome region linked to neurodevelopmental disorders influences locomotor behavior through sex-specific neural circuits

Domain: biology
Published: 2026-01-03
Editorial outcome: major_revision

Abstract
Biological sex shapes the manifestation and progression of neurodevelopmental disorders (NDDs), however, the underlying mechanisms remains unclear. Hemideletion of the 16p11.2 region (16p11.2 del/+) is associated with NDDs, and 16p11.2 del/+ mice exhibit sex-specific, striatum-related phenotypes relevant to NDDs. In this study, using snRNA-seq, we identify cell type- and sex-specific transcriptomic changes in D1- and D2-spiny projection neurons (SPNs), with greater impact in males. Fiber photometry recordings reveal reduced neuronal activity in the dorsal striatum of 16p11.2 del/+ males, but not females, with D2-SPNs identified as the primary contributors to this reduction. Behaviorally, we utilize conditional genetic approaches and find that selective hemideletion in D2-SPNs, but not D1-SPNs, induces male-specific hyperactivity, whereas cortical hemideletion increases hyperactivity in both sexes. Thus, a locus linked to NDDs acts in distinct striatal circuits, selectively impacting behavior in a sex- and cell type-specific manner.

Introduction
Male and female brains differ fundamentally in their reaction to genetic risk for brain disorders1. Sex differences in incidence, symptom presentation, and outcome have been found across biologically heterogeneous disorders, ranging from affective disorders to neurodegenerative diseases and primary brain tumors2–4. Neurodevelopmental disorders (NDDs), including autism spectrum disorders (ASD) and attention-deficit hyperactivity disorder (ADHD), provide a particularly striking example of sex-specific vulnerability, with male-to-female ratios of 4:1 ASD and 2:1 for ADHD5,6. Although the primary features of ASD are consistent across sexes, females can present differently than males, exhibiting fewer or harder-to-detect behavioral alterations7,8. This bias is most likely driven by a differential vulnerability of distinct neuronal circuits to genetic risk factors9,10, but identifying the exact underlying mechanisms remains a major challenge in the field.

Multiple lines of evidence have highlighted striatal circuits as key mediators of vulnerability to NDDs11,12. Neuroimaging studies in humans diagnosed with NDDs and in genetic mouse models have identified changes in striatal structure, function, and connectivity12–14. The striatum is a major hub that shapes an array of behaviors, including the regulation of locomotor activity11,15. Impairments in motor activity and stereotyped movements have been consistently observed in individuals diagnosed with NDDs11,16. The proper acquisition and execution of the locomotor behaviors demand a precisely honed interplay of striatal networks. In the striatum, two distinct neuronal circuits, the direct and indirect pathways, play a critical role in locomotion. The direct pathway is responsible for the initiation of actions and requires the activity of dopamine 1 receptor expressing spiny projection neurons (D1-SPNs), whereas the inhibitory indirect pathway recruits striatal dopamine 2 receptor expressing (D2-) SPNs17,18. Previous studies have suggested an imbalance between the direct and the indirect pathway in NDDs11,19; however, a comprehensive understanding of the role of these pathways in mediating sex-specific effects on behavior is lacking.

Here, we explore the mechanisms underlying the male preponderance of NDDs by mapping the sex-specific consequences of a copy number variation (CNV) linked to NDDs on the function of striatal circuits. We focus on 16p11.2 hemideletion (16p11.2 del/+), a rare genetic condition caused by a hemideletion within the chromosome 16p11.2 locus, as it is one of the most common genetic risk factors for NDDs20,21. Carriers of this CNV may receive a variety of diagnoses including ASD and ADHD22,23. Interestingly, female biological sex may be a protective factor for 16p11.2 del/+ carriers24. 16p11.2 del/+ model mice also show several sex-specific phenotypes25,26, including behaviors dependent upon striatal circuits. Male mice demonstrate impairments in reward learning and motivation27 and sleep26, whereas hyperactivity is observed in both sexes26. Although previous studies have provided an initial indication of striatal circuit dysregulation in 16p11.2 del/+ mice27,28, the exact underlying mechanisms of these phenotypes are not fully understood.

In this study, we examine the sex-specific impact of 16p11.2 del/+ on striatal circuits. High-throughput single-nucleus RNA sequencing (snRNA-seq) of neuronal nuclei from the striatum reveal that 16p11.2 del/+ induces distinct transcriptomic signatures in D1-SPNs and D2-SPNs between males and females. Furthermore, we observe sex- and cell type-specific changes in inhibitory synapse function of SPNs in 16p11.2 del/+ mice, supporting the selective impact of the mutation across distinct neuronal populations. GCaMP fiber photometry recordings reveal reduced dorsal striatal activity in 16p11.2 del/+ males, but not females, driven by D2-SPNs. Crucially, selective deletion of the 16p11.2 region in D2-SPNs induces hyperactivity in male but not in female mice indicating sexually dimorphic effects of the 16p11.2 region. Interestingly, 16p11.2 del/+ in the cortex is associated with hyperactivity in both sexes. Together, these results reveal that circuit level, sex-specific mechanisms mediate the behavioral alterations relevant to NDDs induced by 16p11.2 del/+.

Results
16p11.2 del/+ drives sex- and cell type-specific transcriptomic changes in SPNs
To delineate the impact of 16p11.2 del/+ on specific neuronal circuits in the striatum, we first examine the transcriptomic landscape at the single cell level using snRNA-seq (Fig. 1A). In a previous study, single-cell gene expression was analyzed using multiplex single cell-qPCR28. However, neonatal brains from 16p11.2 del/+ mice were studied, and sex information was not provided. Here, we investigate cell type-specific transcriptomic changes in the striatum of both male and female 16p11.2 del/+ and wild-type (wt) adult mice. Based on the transcriptional signature, we identify sub-populations of striatal neurons, including direct pathway spiny projection neurons (D1-SPNs), and indirect pathway spiny projection neurons (D2-SPNs), as well as various cortical neurons (Fig. 1B, S1, S2, S3). D1- and D2-SPNs exhibit marked transcriptional differences between 16p11.2 del/+ and wt mice that differ between the sexes. In D1-SPNs, we find 99 differentially expressed genes (DEGs) between 16p11.2 del/+ and wt males compared to 18 in females, whereas in D2-SPNs, we identify 114 DEGs in males compared to 20 in females (Fig. 1C–H, and supplementary data 1–4). These results suggest a differential impact of hemideletion of genes in 16p11.2 region on male and female SPNs, with a ~5-fold greater impact in males. In males, 58 DEGs are shared by both types of striatal neurons (Fig. 1I). Importantly, genes whose expression is altered by the 16p11.2 del/+ are enriched in genes associated with ASD. Using the SFARI gene database, we find that 21 DEGs in D1-SPNs of 16p11.2 del/+ male mice overlapped with ASD risk genes, and 21 DEGs in D2-SPNs overlapped with ASD risk genes, including 12 overlapping genes in both types of SPNs (Fig. 1I, S3). Among these 30 genes, several, such as Adcy5, Camk2b, Herc1, Grin2b, Ube3a, Lrp1, and Elavl3, have been reported to be associated with motor function29–35.

16p11.2 del/+ leads to distinct changes in synaptic properties in D1-SPNs and D2-SPNs
To characterize the molecular functions of the DEGs from D1- and D2-SPNs on male 16p11.2 mice, we perform pathway analysis. GO enrichment network analysis reveals that genes differentially expressed in both D1- and D2-SPNs (58 DEGs) are associated with regulation of excitatory postsynaptic organization (Fig. 2A). This is consistent with previous reports of increased miniature excitatory postsynaptic currents (mEPSC) frequency and increased AMPAR/NMDAR ratio in 16p11.2 del/+ SPNs28, suggesting both pre- and postsynaptic alterations at excitatory synapses. Interestingly, there is a substantial enrichment of genes associated with gamma-aminobutyric acid (GABA) synaptic transmission among the 41 exclusive D1-SPNs DEGs (Fig. 2A). To determine whether these molecular changes are reflected at the synaptic level, we investigate inhibitory synaptic function by recording inhibitory postsynaptic currents (IPSC). This reveals region- and sex-specific effects. In the dorsal striatum, we observe decreased spontaneous IPSC (sIPSC) frequency in D2-SPNs of 16p11.2 del/+ males (Fig. 2B–E) and increased sIPSC amplitude in D1-SPNs of 16p11.2 del/+ females (Fig. 2F–I). Additionally, miniature IPSC (mIPSC) recordings in the nucleus accumbens (NAc) reveal distinct alterations in D1- and D2-SPNs of 16p11.2 del/+ male mice. Comparison of mIPSC amplitudes shows a significant reduction in D1-SPNs of NAc in male 16p11.2 del/+ mice versus wt mice, indicating decreased postsynaptic GABAergic responsiveness (figure S4A-B). However, mIPSC frequency is significantly reduced in D2-SPNs of NAc in 16p11.2 del/+ males (figure S4C-D), similar to observations in D2-SPNs of the dorsal striatum. This suggests decreased presynaptic GABA release or fewer inhibitory inputs onto D2-SPNs across striatal subregions. Together, these results highlight the differential impact of the high-risk polygenic factor 16p11.2 del/+ on molecular pathways and inhibitory synaptic transmission within the two major neuronal circuits in the striatum, with region- and sex-specific alterations pointing to circuit-specific vulnerability.

Sex-specific transcriptomic changes in 16p11.2 del/+ male mice correlate with wild type gene expression differences between sexes
To explore the effects of baseline sex differences on gene expression changes in male 16p11.2 del/+ mice, we compare gene expression between wt males and wt females to gene expression between wt males and 16p11.2 del/+ males (figure S5A, B). As expected, there are substantial baseline transcriptional differences between wt males and females. Interestingly, differentially expressed genes in 16p11.2 del/+ male mice show a positive correlation with genes more highly expressed in wt females, suggesting that the deletion in males induces a partial shift toward a more female-like transcriptional profile. We perform the same analysis in 16p11.2 del/+ females using a quadrant plot approach (figure S5C, D). However, due to the smaller number of DEGs in females, the results were less conclusive. To investigate whether these gene expression patterns are specific to SPNs or observed more generally in the striatum, we analyze mRNA-seq data from a previous study (GSE224750) from the striatum of both male and female young adult 16p11.2 del/+ and wt mice (figure S5E, F). Consistent with our SPN-specific results, the transcriptomic changes in 16p11.2 del/+ males again positively correlate with baseline female-biased expression (figure S5E). In contrast, female gene expression changes induced by 16p11.2 del/+ appear less influenced by baseline sex differences (figure S5F). To ensure that each animal is treated as an independent replicate, we perform pseudobulk differential expression analysis by aggregating counts within each cell type and sample. This approach confirms the correlations between sex effects and 16p11.2 genotype effects (figure S5G, H), consistent with our single-cell results. Together, these findings highlight robust baseline transcriptional differences between wt males and females and suggest that 16p11.2 del/+ males may engage a compensatory transcriptional response, further supporting the idea that females possess a more resilient molecular baseline to the effects of the deletion.

Neuronal activity frequency in D2-SPNs is reduced in male 16p11.2 del/+ mice
To measure in vivo neuronal population activity within striatal circuits, we deliver AAV-syn-jGCaMP7f-WPRE to the dorsal striatum, a region associated with locomotor regulation. Two weeks after surgery, mice exhibit robust jGCaMP7f expression in the dorsal striatum (Fig. 3A). During open-field exploration, we record jGCaMP7f signals to monitor neuronal activity (Fig. 3B, C). Spike detection analysis reveals the frequency of striatal neuronal activity events (Fig. 3D). We observe a significant reduction in neuronal activity in male 16p11.2 del/+ mice compared to wt males (Fig. 3E), but not in female 16p11.2 del/+ mice (Fig. 3F). The AAV-ENK-CRE virus expresses CRE recombinase under the control of the enkephalin promoter, which is specific to D2-SPNs, while the AAV9-PPTA-CRE virus uses the preprotachykinin A promoter to drive CRE expression specifically in D1-SPNs36,37. By co-injecting AAV-ENK-CRE with either AAV-FLEX-tdTomato or AAV-FLEX-GFP, or AAV-PPTA-CRE with either AAV-FLEX-tdTomato or AAV-FLEX-GFP into D2-GFP or D1-tdTomato reporter mice, we confirm that AAV-ENK-CRE and AAV-PPTA-CRE drive expression exclusively in D2-SPNs and D1-SPNs, respectively (Fig. 3G–N). By applying AAV-ENK-CRE and AAV-PPTA-CRE in combination with AAV-syn-FLEX-jGCaMP8m-WPRE in 16p11.2 del/+ mice, we can monitor D2-SPN and D1-SPN activity simultaneously in each hemisphere of the brain (Fig. 3O). Two weeks after surgery, mice show robust jGCaMP8m expression with each CRE-expressing virus in the dorsal striatum (Fig. 3P, Q). We observe a significant reduction in D2-SPN activity in male 16p11.2 del/+ mice compared to wt males, while D1-SPN activity remains unchanged (Fig. 3R). These results demonstrate a sex-specific and circuit-specific impact of the 16p11.2 deletion on striatal neuronal activity.

16p11.2 del/+ in D2-SPNs leads to hyperactive behavior in male mice but not females
To determine the impact of 16p11.2 del/+ on behavior linked to distinct striatal circuits, we utilize conditional genetic approaches to introduce the hemideletion selectively in either D1- or D2-SPNs. We generate mice with 16p11.2 del/+ exclusively in D2-SPNs by crossing 16p11.2 flox/+ mice and A2A-CRE+/- mice (Fig. 4A). Double positive mice (flox/+:CRE+/-; A2A-CRE x 16p11.2 flox, D2-16p11.2 del/+ mice) are considered as the experimental group and the other three groups of mice (+/+:CRE-/-, flox/+:CRE-/-, +/+:CRE+/-) are combined as controls. Young adult (3–4-month-old) male and female D2-16p11.2 del/+ mice and littermate control mice are monitored in the home-cage using an infrared beam-break system across the 24-hour cycle, similar to previous studies26. We find increased activity in male (Fig. 4B, C, S6A) but not female (Fig. 4D, E, S6B) D2-16p11.2 del/+ mice, in contrast to our findings of hyperactivity in both sexes in the whole-organism 16p11.2 del/+ (figure S7)26. These results demonstrate that 16p11.2 del/+ in D2-SPNs induces hyperactive behavior specifically in male mice, revealing circuit level sex differences of the deletion of 16p11.2 region, consistent with our gene expression data.

To characterize the impact of 16p11.2 del/+ selectively in D1-SPNs, we generate mice with the hemideletion specifically in D1-SPNs by crossing 16p11.2 flox/+ mice and D1-CRE+/- mice (Fig. 4F). Again, double positive mice (flox/+:CRE+/-; sD1-CRE x 16p11.2 flox, D1-16p11.2 del/+ mice) are considered as the experimental group and the other three littermate genotypes (+/+:CRE-/-, flox/+:CRE-/-, +/+:CRE+/-) are categorized as the control group for behavioral tasks. Both male (Fig. 4G, H, S6C) and female (Fig. 4I, J, S6D) D1-16p11.2 del/+ mice exhibit similar locomotor activity to littermate controls. We confirm that neither 16p11.2 flox mice, D1-CRE mice, nor A2A-CRE mice exhibit hyperactive locomotion (figure S6, S8). Together, our results reveal that the sexually dimorphic effects of 16p11.2 del/+ on D2-SPNs mediates NDD-relevant increases in the locomotor activity of male animals.

Moreover, we find that sulpiride, a selective D2 receptor antagonist, alleviates hyperactivity in 16p11.2 del/+ male mice to levels comparable to those of wt males (Fig. 5A, B, S9). Although sulpiride also reduces locomotor activity or shows a trend toward reduction in wt males, wt females, and 16p11.2 del/+ females (Fig. 5C-H), effect size analysis reveals the strongest impact in 16p11.2 del/+ males (Cohen’s d=1.10), compared to smaller effects in wt males (d=0.58), wt females (d=0.64), and 16p11.2 del/+ females (d=0.64). Interestingly, risperidone, a potent antagonist of D2 and 5-HT receptors, alleviates hyperactivity in both male and female 16p11.2 del/+ mice (figure S10A–D), with a larger effect size observed in females. Effect size analysis shows the strongest impact in 16p11.2 del/+ females (Cohen’s d=0.80), compared to 16p11.2 del/+ males (d=0.60), wt males (d=0.26), and wt females (d=0.04), suggesting sexual dimorphism in the regulation of locomotor activity. In contrast, treatment with SCH39166, a D1 receptor antagonist, does not alleviate hyperactivity in either 16p11.2 del/+ males or wt males (figure S11), further supporting a key role for D2-SPNs in driving hyperactive behavior in 16p11.2 del/+ males. Together, these findings highlight D2-SPNs as a critical circuit component underlying hyperactivity in males, driving this behavioral phenotype.

16p11.2 del/+ in D2-SPNs in the dorsal lateral striatum drives hyperactive behavior in male mice
Distinct behavioral roles have been characterized for specific subregions within the striatum, with the dorsal medial striatum (DMS) supporting more cognitive functions and the dorsal lateral striatum (DLS) supporting motor output11,38. However, the conditional genetic approaches using D1-CRE and A2A-CRE mice lack the specificity necessary to target neuronal circuits within specific subregions of the striatum. To target specific subregions within the striatum, we deliver AAV-ENK-CRE virus to striatal subregions in 16p11.2 flox/+ male mice. Injecting this virus in 16p11.2 flox mice localizes the 16p11.2 hemideletion effects to D2-SPNs within specific striatal subregions. We co-inject a mix of AAV-ENK-CRE and AAV-flex-tdTomato in wt and 16p11.2 flox/+ male mice in three different striatal regions: the DMS, DLS, and NAc, and examine the impact on locomotor activity (Fig. 6A). Activity monitoring data shows that hyperactivity resulted from 16p11.2 del/+ in D2-SPNs in the DLS (Fig. 6C, D), but not in the DMS or NAc (Fig. 6F, G, I, J). Following behavioral testing, brains are collected, and we confirm hemideletion of the 16p11.2 region in the striatum using PCR and verify injection location and the extent of viral expression using fluorescent microscopy (Fig. 6B, E, H, S13). In sum, these results demonstrate that 16p11.2 del/+ in D2-SPNs, specifically of the DLS, induces hyperactive behavior in male mice.

16p11.2 del/+ in the cortex causes hyperactivity in both male and female mice
16p11.2 del/+ in D2-SPNs drives hyperactive behavior only in male mice, suggesting sexual dimorphism on the circuit level. However, the circuit basis for the hyperactivity observed in whole-organism 16p11.2 del/+ female mice (figure S7B26), remains unresolved. We hypothesize that a loss of the 16p11.2 region in neurons within the cortex, one of the main excitatory inputs into the striatum, contributes to hyperactivity in female 16p11.2 del/+ mice. To explore the functional role of genes in the 16p11.2 region in the cortex, we cross EMX1-CRE mice and 16p11.2 flox/+ mice (Fig. 7A). As before, double positive mice (flox/+:CRE+/-; EMX1-CRE x 16p11.2 flox, Ctx-16p11.2 del/+ mice) are considered as the experimental group and the other three genotypes (+/+:CRE-/-, flox/+:CRE-/-, +/+:CRE+/-) are combined as controls. Remarkably, both male (Fig. 7B, C) and female (Fig. 7D, E) Ctx-16p11.2 del/+ mice display hyperactive behavior compared to sex-matched control mice, phenocopying the 16p11.2 del/+ mice hyperactivity observed in both sexes (figure S7)26. These behavioral results demonstrate that deletion of the 16p11.2 region differentially impacts various hubs within cortico-striatal circuits, suggesting that circuit level sex differences mediate behavioral phenotypes of NDDs.

Methods
Animals
Mice were housed (2–5 per cage) in a room maintained on a 12-h light/dark cycle (20–25°C, 30–70% humidity) with ad libitum access to food and water. All procedures were approved by the University of Iowa Institutional Animal Care and Use Committee, and followed policies set forth by the National Institutes of Health Guide for the Care and Use of Laboratory Animals. 16p11.2 del/+ mice were produced by breeding male B6129S-Del(7Slx1b-Sept1)4Aam/J mice purchased from The Jackson Laboratory (Stock #013128) with female B6129SF1/J mice (Stock #101043), as previously described25. The 593kb CNV (chr6, 133.84-134.28Mb) conditioned mouse line was generated in the Mills laboratory to delete the causative region in specific neurons of the developing brain using chromosome engineering60. This conditional model has a floxed version of the region analogous to 16p11.2, and when crossed to a cell-type specific CRE mouse model, causes efficient deletion of the floxed region in vivo61. To generate mice with cell type-specific deletion of the region analogous to 16p11.2 (the 7F4 region in mice) specifically in D1- or D2-SPNs, we used the EY217 Drd1a-CRE line (purchased from GENSAT, B6.FVB(Cg)-Tg(Drd1a-re)EY217Gsat/Mmucd, Stock Number :034258-UCD) and KG139 A2A-CRE line (purchased from GENSAT, B6.FVB(Cg)-Tg(Adora2a-CRE)KG139Gsat/Mmucd, Stock Number 036158-UCD). These CRE lines were backcrossed at least 5 generations to 129S1 (purchased from The Jackson Laboratory, 129S1/SvImJ, Stock Number 002448) and bred to floxed 16p11.2 hemizygous mice created by our collaborator Alea Mills at Cold Spring Harbor Laboratory60. To selectively introduce the 16p11.2 del/+ in the cortex, we used the Emx1-CRE line (purchased from The Jackson Laboratory, B6.129S2-Emx1tm1(CRE)Krj/J, Stock Number 005628). Emx1-CRE mice express the CRE recombinase in cortical excitatory neurons and glia, but not GABAergic neurons62. To selectively introduce the 16p11.2 del/+ in D2-SPNs, we utilized A2a-CRE mice instead of D2-CRE mice because CRE recombinase is expressed in striatal cholinergic interneurons as well as D2-SPNs of D2-CRE mice63, unlike A2a-CRE mice, which drives expression in D2-SPNs but not cholinergic interneurons18. Experimental data was collected from littermate animals during the same time period. Mice aged between 10 and 16 weeks were randomly used for experiments to minimize any bias unless otherwise specified.

Genotyping. PCR-genotyping was done to identify founders with the intended mutation.

16p11.2 del/+
wtFwd GCTATGAAGATGCCCACCAT
wtRev GTGGTAACTCATGCGGTCCT
mutFwd CAAGCACTGGCTATGCATGT
mutRev AAGACAGAATGCTATGCAACCTT
sD1-CRE
Drd1aFwd GCTATGGAGATGCTCCTGATGGAA
CreGSRev CGGCAAACGGACAGAAGCATT
A2A-CRE
Adora2aFwd CGTGAGAAAGCCTTTGGGAAGCT
CreGSRev CGGCAAACGGACAGAAGCATT
EMX1-CRE
CommonFwd CAACGGGGAGGACATTGA
wtRev CAAAGACAGAGACATGGAGAGC
muRev TCGATAAGCCAGGGGTTC
16p11.2 flox
#1672(SF5’VectorS1) GCGCCCAATACGCAAACCGCC
#1673(SF216K12gapFor/Compl) TCCTCCACTGCTGGTAGGAG
#1674 (SF 135K15AFEO gap1 REV) GCATGTGTGCACTAACCTA TATCC
#1675(SF3’VectorS1) TGCGGGCCTCTTCGCTATTACG
16p11.2 df allele
dfFwd CCTCATGGACTAATTATGGAC
dfRev CCAGTTTCACTAATGACACA

Single-cell RNA-sequencing
Tissue processing for scRNA-seq. Mice were sacrificed at 14-16 weeks of age by live decapitation and the brain was rapidly removed. Using a mouse brain matrix, 1mm coronal sections were collected, and then tissue punches containing the striatum (-0.5~1.5mm AP from bregma; n=2 mice/genotype/sex) were rapidly frozen on dry ice. Tissue punches were preserved at -80°C until the day of single nuclei dissociation. Each snRNA-seq experimental set consisted of male wt, male 16p11.2 del/+, female wt, and female 16p11.2 del/+ littermates. Animals were selected from two separate litters originating from different breeding cages.

Single nuclei purification. For single nuclei dissociation, a protocol from a previous study was followed64. Briefly, frozen tissue punches were chopped and transferred to 450μl of chilled (4°C) homogenization buffer (250mM sucrose, 25mM KCl, 5mM MgCl2, 10mM Tris buffer (pH 8.0), 1μM DTT, 1x protease inhibitor, RNase In 0.4 U/μl, SUPERase-In 0.2 U/μl, 0.1% Triton X-100). After the Dounce homogenization and filtering (40μm), the nuclei were concentrated by centrifugation (1,000g for 8min at 4°C). For staining, anti-NeuN antibody (Millipore MAB377, 1:500), Hoechst, and Alexa 488 secondary antibody (Invitrogen A32723, 1:500) were treated and incubated on a rocker in a cold room for 30min. Then the nuclei were resuspended in 600μl FACS buffer (1% unacetylated BSA, RNase In 0.4 U/μl, PBS) for FACS to further purify the nuclei for sequencing. The nuclei were first sorted based on Hoechst signal and then based on Alexa 488 fluorophore, collecting 50,000 nuclei per mouse.

Single nuclear (snRNA) RNA sequencing and analysis. Libraries were constructed using the 3’ Expression-Single-Cell RNA-Seq using 10X Chromium System (v3.1), according to the manufacturer’s instructions. The nuclei were brought to a concentration of 500 nuclei/μl and 5000 nuclei were loaded to prepare libraries. Libraries were then sequenced (pair-end sequencing) on the Illumina NovaSeq 6000 at the Iowa Institute of Human Genetics at the University of Iowa. The depth of sequencing per flow cell was 50,000 reads per nuclei. FASTQ files were aligned to the pre-mRNA annotated Mus musculus reference genome version GRCm38 (refdata-cellranger-mm10-3.0.0). CellRanger Count v3.0.2 (10x Genomics, Pleasanton CA) was used on FASTQ data from each of the GEM wells individually for genome alignment and feature-barcode matrix counts generation. CellRanger Aggr v3.0.2 was then used to combine data from multiple samples of the same genotype (biological replicates) into an experiment-wide feature-barcode matrix and analysis, normalize those runs to the same sequencing depth, and then recompute the feature-barcode matrices and analysis on the combined data. This raw expression Unique Molecular Identifiers (UMI) counts matrix contains cells as rows and genes as columns and can be further used for downstream analysis such as normalization, clustering, differentially expressed genes, etc.

The clusters were then visualized with uniform manifold approximation and projection (UMAP) in two dimensions of UMI per cells (figure S1). The most significant gene markers corresponding to each cluster and conserved across the two genotypes (WT and 16p11.2 del/+) were used to identify the cell-types by correlating with previously published single-cell data65 and from the transcriptomic explorer of the Allen Brain Atlas (https://celltypes.brain-map.org/rnaseq/mouse_ctx-hip_10x). To obtain an observer-independent data-driven characterization of cell types, we computed the 2000 most variable genes in each cell, based on the assumption that these genes will distinguish best between different cell types and formed clusters of specific cell types based on similar transcriptomics signatures for each cell (Fig. 1B, S1, S2). Dot Plot representations show the normalized UMI expression of conserved gene markers across the two genotypes in the different cell types.

Raw single nuclei RNA-seq UMI count data was used for clustering analysis using the Seurat R analysis pipeline66. First, cells with more than 50,000 molecules (nUMI per cell) were filtered out to discard potential doublets. Post filtering, the raw UMI counts from the primary filtered dataset were used for log-normalization and scaled using a factor of 10,000 and regressed to covariates such as number as described in the Seurat analysis pipeline66. To further identify the top variable genes, the data was used to calculate principal components (PCs). Using Jackstraw analysis, statistically significant PCs were used to identify clusters within the data using original Louvain algorithm as described in the Seurat analysis pipeline, followed by visualizing the clusters with uniform manifold approximation and projection (UMAP) in two dimensions of UMI per cells67. Genes corresponding to each cluster were used to identify the cell-type by correlating to genes expressed in previously published adult mouse striatal single-cell data65 and analyzed for expression of top marker genes of known cell types.

Pairwise differential gene expression analysis tests were performed within each cluster-pair (wt vs. 16p11.2 del/+) using a Wilcoxon Rank Sum test (a two-sided test, with Benjamini–Hochberg correction to control the false discovery rate) from the Seurat R analysis pipeline66 to identify differentially expressed genes. Genes with an adjusted p-value under 0.05 and an absolute log2 fold change above 0.2 were considered significantly differentially expressed. Enrichment analysis of DEG-associated pathways and molecular functions from snRNA-seq was performed with a combination of Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Gene Ontology (GO-Molecular Function-EBI-Uniport-GOA-) databases. The analyses were done with Cytoscape (version. 3.8.0, https://cytoscape.org/)68 plug-in ClueGO (version 2.5.6)69. Only the pathways with a p-value < 0.05 and gene counts ≥ 3 were considered as significant and displayed. To connect the terms in the network, ClueGO utilizes kappa statistics which was set as ≥ 0.4.

Electrophysiology
Virus Injection and stereotaxic injections. For the cell-type–specific electrophysiology approach, we used AAV-ENK-CRE and AAV-PPTA-CRE viruses, kindly provided by Dr. Jocelyne Caboche (Sorbonne University). AAV-ENK-CRE targets D2-SPNs, and AAV-PPTA-CRE targets D1-SPNs, each driving CRE recombinase expression in those specific neurons36,37. pAAV-FLEX-tdTomato and pAAV-FLEX-GFP viruses (purchased from Addgene; catalog numbers 28306 and 28304, respectively) were used in combination with AAV-ENK-CRE or AAV-PPTA-CRE. 16p11.2 del/+ mice were injected with the virus mixture—10¹² vg/animal for AAV-ENK-CRE and 1×10¹¹ vg/animal for pAAV-FLEX-tdTomato, or 10¹² vg/animal for AAV-PPTA-CRE and 1×10¹¹ vg/animal for pAAV-FLEX-GFP—into each hemisphere of the dorsal striatum (AP: +0.65mm; ML: ±2.00mm; DV: –3.2mm from bregma). The rate of injection was 200nl/min with a total volume of 1μl per striatum. Injections were performed at ~2–3 months of age. Mice were prepared for recordings following 2–3 weeks of viral expression.

Brain slice preparation. Mice were decapitated, and brains were excised rapidly between zeitgeber time (ZT) 2 and ZT 4, relative to lights-off at ZT 12. Coronal brain slices 300-µm-thick were prepared using a Leica VT1200S (Leica Biosystems) vibrating blade microtome. During the brain slice preparation, the brain was immersed in an ice-cold, oxygenated (95% O2, 5% CO2) sucrose solution containing the following (in mM): 75.1 sucrose, 75 NaCl, 2.5 KCl, 1.2 NaHPO4, 30 NaHCO3, 20 HEPES, 25 glucose, 10 MgSO4 and 0.5 CaCl2. After slicing, the slices were immediately incubated in oxygenated artificial cerebrospinal fluid (ACSF) containing the following (in mM): 92 NaCl, 2.5 KCl, 1.2 NaHPO4, 30 NaHCO3, 20 HEPES, 25 glucose, 2 MgSO4 and 2 CaCl2, for 30min and transferred to room temperature for a minimum of 30min. Osmolarity of the solutions was kept between 298-300 mOsm.

Electrophysiological recording conditions and data acquisition. Slices were individually transferred to a recording chamber on the stage of an upright BX51WI microscope. The recording ACSF (containing the following (in mM): 124 NaCl, 2.5 KCl, 1.2 NaH2PO4, 24 NaHCO3, 5 HEPES, 12.5 glucose, 1.3 MgSO4 and 2.5 CaCl2) was heated to 28-30oC using a perfusion temperature controller and circulated at a rate of 1.5 ml/min using a peristaltic pump. Neurons expressing tdTomato/EGFP were identified using a combination of a SciCam Pro camera and fluorescence microscopy connected to a pE-400 illumination system. Data acquisition was done using a dPatch2 amplifier (Sutter Instruments) and Igor Pro 9. The intracellular pipette solution [containing the following (in mM): 130 Cs-methanesulfonate, 8 CsCl, 10 HEPES, 0.6 EGTA, 1 MgCl2, 5 QX-314 and 0.1 spermine; osmolarity ∼290-295 mOsm] was prepared and adjusted to a pH of 7.2 using CsOH. The current signals were acquired at 20 kHz and filtered at 4 kHz. Series resistance (Rs) was monitored using an access test analyzing the membrane current response to multiple 20 msec, 5 mV hyperpolarizing voltage steps from −65 mV. The access test was performed before and after each recording, and only cells with Rs < 20 MΩ and Rs changed during the recording <20% were used for subsequent analysis. Spontaneous inhibitory postsynaptic currents (sIPSCs) were pharmacologically isolated by using 50 µM D-APV and 20 µM NBQX and recorded at +10 mV.

Analysis. sIPSC analysis was done using custom Python scripts developed to extract and process the electrophysiological recordings stored in HDF5 (.h5) format and the metadata in notebook files. A minimum of 150 individual events per cell were included for analysis to ensure reliable estimation of synaptic parameters. Event detection used the scipy function find_peaks, applied to traces that were low pass filtered using a 4 pole butterworth filter with cutoff of 1000 Hz, and with prominence parameter of 15 pA, width parameter of 5 ms, and wlen parameter of 0.1. All the custom codes used for event detection, extraction, and synaptic parameter analysis are available from the GitHub repository: (https://github.com/neurord/ephys_anal/releases/tag/v2.0).

Fiber photometry and surgeries
Mice were injected with AAV-syn-jGCaMP7f-WPRE (10¹³ vg/mL, AAV9 #104488, Addgene) into the dorsal striatum (AP: +0.65mm; ML: ±2.0mm; DV: –3.2mm from bregma). The injection rate was 200 nL/min, with a total volume of 1 µL per hemisphere. For cell type-specific fiber photometry recordings, mice were co-injected with AAV-PPTA-CRE (10¹² vg/mL) or AAV-ENK-CRE (10¹² vg/mL) and AAV-syn-FLEX-jGCaMP8m-WPRE (10¹³ vg/mL, AAV9 #162378, Addgene). A 200-µm core, 1.25-mm ferrule, 0.37-NA optical fiber (Neurophotometrics) was implanted at the same location (AP: +0.65mm; ML: ±2.0mm; DV: –3.0mm from bregma) and secured with dental cement. Following two weeks of viral expression, fiber photometry recordings were performed using the FP3002 system (Neurophotometrics) and recorded with Bonsai software for 2–3min in the homecage. Two LED wavelengths were used: 415nm (isosbestic control) and 470nm (GCaMP excitation). GCaMP fluorescence signals were analyzed using MATLAB scripts adapted from the Neurophotometrics Data Analysis Manual. To calculate the percentage change in fluorescence (%ΔF/F), the isosbestic signal was first fitted with a biexponential decay curve. This fit was scaled to the calcium-dependent signal, which was then divided by the scaled fit. The %ΔF/F was computed using the fitted isosbestic signal (F) and the calcium-dependent signal (ΔF). Instantaneous spike frequency was estimated using spike detection MATLAB scripts (minimum peak prominence of 1), also adapted from the Neurophotometrics Data Analysis Manual.

Activity monitoring
An infrared beam-break system (Opto M3, Columbus Instruments, Columbus, OH) was used to measure mice locomotor activity, as previously described26. Behavior experiments were designed based on previous experience with an effect size of 0.7 in a power analysis. The mice were acclimatized to the monitoring chambers for one week before data collection to reduce the effect of a new environment. The data was collected for one week following the habituation period. ANOVAs followed by Fisher’s LSD post-hoc tests were performed using GraphPad 9 (La Jolla, CA), with genotype as the between-subjects factor and time as the within-subjects factor, as previously described26. After behavioral assessments, the striatum and adjacent cortices were dissected from D1- and D2-16p11.2 del/+ and control mice to confirm the hemideletion of the 16p11.2 region in the striatum using PCR (figure S12).

Drug treatment
For intraperitoneal injections (IP), sulpiride (50 mg/kg in a volume of 5 ml/kg, Sigma-Aldrich, Product No. S8010) was dissolved in 0.9% saline, 5% DMSO, and 1% acetic acid which was then neutralized using NaOH to pH 7. Vehicle treatment received 5 ml/kg of 5% DMSO in saline. The mice were acclimatized to the monitoring chambers for one week before data collection to reduce the effect of a new environment. In the second week, mice were injected with vehicle daily at the beginning of the dark cycle (total of 7 vehicle injections). In the third week, mice were injected with sulpiride at the beginning of the dark cycle every day (total of 7 drug injections). The data was collected for two weeks following the habituation period. The effect size was determined using Cohen’s d = (M2-M1)/SDpooled, where SDpooled = sqrt((SD1^2 + SD2^2)/2).

Virus Injection and stereotaxic injections
16p11.2 flox mice were injected with the virus mix (1012 vg/animal for AAV-ENK-CRE and 1×1011 vg/animal for either pAAV-FLEX-tdTomato and pAAV-FLEX-GFP) into the dorsal medial striatum (AP, +0.65mm; ML, ±1.70mm; DV, -3.2mm from bregma), dorsal lateral striatum (AP, +0.65mm; ML, ± 2.2mm; DV, -3.2mm from bregma) or NAc (AP, +1.2mm; ML, ±1.0mm; DV, -4.2mm from bregma). The rate of injection was 200 nl/min with a total volume of 1 μl per striatum. Following 2 weeks of virus expression, mice were tested in activity monitoring. After behavioral assessments, the striatum and cerebellum were dissected from 16p11.2 flox and control mice to confirm the hemideletion of the 16p11.2 region using PCR (figure S13).

Fluorescence imaging
After activity monitoring, mice were cervically dislocated and decapitated, and the whole brain removed on ice. Brain tissue was immersed in the 4% formaldehyde (PFA) at 4°C overnight. The tissue was transferred into 30% sucrose for 48h. Then, tissue was sliced into 40 µm thick sections using a cryostat at -20°C and mounted on slides. Fluorescence images were taken with a Leica DM6B Upright digital microscope using the software program NeuroLucida (Microbrightfield Inc). Placements were identified with reference to a mouse brain atlas70.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this manuscript Kim et al. provide an intriguing example of the potential utility of construct valid mouse models harboring mutations isolated from human patients with psychiatric disorders. The authors combine omics-based approaches with behavior and neurophysiology both localize the origin of key behavioral phenotypes in the 16p11.2 del/+ model and elucidate a potential mechanism driving altered locomotion in these mice, namely a shift in the excitatory/inhibitory input onto D2-SPNs in the DLS. The methods are sound, and conclusions supported by the experimental data. The integration of sex as a biological variable allows the authors to not only provide evidence of sex differences at the level of phenotypic outcomes, but to also begin tracing a potential mechanistic basis for these observations. Studies that provide cogent examples of how behavioral outcomes can be similar between the two sexes (e.g., hyperactivity in 16p11.2 del/+ mice of both sexes) but differ in the underlying neural substrates are rare and, thus, this study a refreshing deviation from the current standard. I believe the work to be appropriate for publication in Nature Communications but do have a few concerns that should be addressed by the authors prior to publication.\n1. It seems an oversight for the authors to present mIPSC data from D1/D2 SPNs in males only. A lack of impact of the 16p11.2 del/+ mutation on mIPSC frequency in females would further support the resilience of females to the detrimental impact of the 16p11.2 deletion on synaptic function and provide additional mechanistic insight into why the 16p11.2 mutation introduced into D2-SPNs triggers hyperactivity in males and not females. It would also bolster the authors claim that the transcriptional dataset reported reflects important functional consequences for SPN activity and circuit output.\n2. The section (lines 168-183; 380-399) describing supplementary figure 4 is difficult to follow. It could use a re-write to further clarify the main take-aways. I think the authors are trying to make 2 points here:\na. That there are baseline differences in transcriptional profiles between WT males and females. This is an important point and should be mentioned and discussed in the manuscript. It makes sense that baseline differences would translate to robust differences in susceptibility to 16p11.2 deletion.\nb. The transcriptional profile of the 16p11.2 females more closely overlaps with WT mice. Again, as this supports the idea of female resilience to the impacts of the 16p11.2 mutation, this is an important point that should be discussed in terms of implications and evidentiary support.\n3. The authors utilize home cage activity monitoring and specifically mention they habituated the mice to remove the impact of novelty on locomotor activity. Was there a rationale for this choice? The striatum is a known driver of novelty-induced locomotion, which has generally been attributed to SPNs in the nucleus accumbens. It is possible, therefore, that while 16p11.2 deletion in NAc MSNs does not impact home cage activity, it would impact novelty-induced hyperlocomotion.\n4. The authors should discuss how a reduction in mIPSC frequency (combined with the previously reported increase in mEPSC frequency) in D2 SPNs would result in increased locomotion in the context of altered output from basal ganglia circuitry. The same for a change in the mPFC.\na. What are the implications for sex differences in these circuits in the context of psychiatric disorders?\nb. Given the alteration in mIPSC frequency in D2-SPNs with the 16p11.2 deletion suggests a presynaptic origin, where could the alteration in inhibitory input originate? Possible sources could be local including Fast-spiking interneurons, D1-MSNs, or D2-D2 collaterals within the striatum or GABAergic inputs from cortical sub-regions (see: https://pubmed.ncbi.nlm.nih.gov/24304860/; https://pubmed.ncbi.nlm.nih.gov/27927785/; https://pubmed.ncbi.nlm.nih.gov/28467898/; and https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3899717/).\n5. The authors should acknowledge, as a limitation of the current study, that transcriptional analyses combine striatal neuron populations from both ventral (nucleus accumbens) and dorsal striatum. These circuits receive unique inputs and have been shown to differ in their transcriptional profiles (for example: https://pubmed.ncbi.nlm.nih.gov/35177825/ and https://pubmed.ncbi.nlm.nih.gov/37205475/ ). Clearly, given the authors were able to localize functional impacts of the 16p11.2 mutation to the DLS in males, there is likely to be a unique transcriptional profile in this sub-population of SPNs that might further narrow down the list of gene candidates driving altered locomotor behavior.\n6. Though undoubtedly useful in tracing circuits impacted by 16p11.2 deletion, hyperlocomotion, particularly in rodents, is not a translatable trait domain of clear relevance to human patients with 16p11.2 mutations and/or related conditions. The authors should discuss how a change in D2 MSN activity in the DLS might otherwise alter behavior (for example, habit formation). While directly testing altered phenotypes in the 16p11.2 del/+ model is undoubtedly beyond the scope of the current work, this discussion is nonetheless critical for understanding the potential clinical significance/implications of the authors findings. For example, prior work has shown that activity in D2-SPNs decreases in the DLS during consolidation of instrumental responding and D2-MSN inhibition strengthens consolidation but blocks the expression of previously learned habit-like responses (https://pubmed.ncbi.nlm.nih.gov/34433818/)", "reviewer_2": "The present study investigates the sex-specific impact on striatal circuits of a hemideletion within the chromosome 16p11.2 locus, building on previous work from the same and other research groups.\nIn particular, the present study analyzes:\ni) the differences in the transcriptomic signatures in D1 receptor-expressing striatal spiny neurons (D1-SPNs, direct striatonigral pathway) and D2-SPNs (indirect striatopallidal pathway) and in the locomotor activity in male and female 16p11.2 hemideletion (16p11.2del/+) mice;\nii) the expression of a hyperactive phenotype after selective 16p11.2 hemideletion in D1-SPNs or D2-SPNs of male mice, or in the cortex of male and female mice;\niii) the effect of a D1 receptor antagonist or a D2 receptor antagonist (risperidone) on the hyperactive phenotype of 16p11.2del/+ male mice;\niv) the specific involvement of 16p11.2 hemideletion in D2-SPNs of the dorsomedial, dorsolateral or ventral striatum in the expression of hyperactive behavior in male mice.\nA single nucleus RNA sequencing transcriptomic is performed on the whole striatum of 16p11.2 hemideletion male and female mice, and is correlated to the analysis of hyperactive behavior. The origin of the hyperactive behavior is investigated by introducing the 16p11.2 hemideletion selectively in D1-SPNs or D2-SPNs of male and female mice, in the cortex of male and female mice, and in three striatal subregions (dorsomedial, dorsolateral and ventral) of male mice. An electrophysiology analysis is performed to analyze spontaneous miniature GABAergic inhibitory transmission in the Nucleus accumbens (ventral striatum) of 16p11.2 hemideletion male mice.\nThe authors conclude that conditional 16p11.2 del/+ in specific striatal circuits (D2-SPNs) and in specific striatal subregions (dorsolateral striatum) induces hyperactivity in a sex-specific manner (males), indicating sexually dimorphic effects of the genes in the 16p11.2 region on the function of distinct neuronal circuits within the striatum, underlying hyperactivity in 16p11.2 del/+ mice.\nThe main novelty of the present work consists in the introduction of selective 16p11.2 hemideletion, to investigate the origin of the hyperactive phenotype in male mice.\nPrevious work described hyperactivity, circling, deficits in movement control and reward learning, and lack of habituation in 16p11.2 del/+ mice. Furthermore, increased numbers of D2+ and reduced numbers of D1+ neurons in deep layers of cortex, and defects at excitatory synapses of striatal D2-SPNs were also found. Notably, a study by Portmann and coll. (2014) reported lack of effect of risperidone on the hyperactivity of 16p11.2 del/+ mice. This difference should be discussed: do the authors believe it may depend on the fact that previous work did not discriminate between males and females? What was the effect of risperidone on wildtype male and female mice? Panels A and B of Fig. S8 suggest that a single animal showed a higher level of hyperactivity with respect to the others of the same experimental group and of the group shown in panel D. What happens if this animal is excluded from the analysis? Is the effect of risperidone still significant, or is it not – as reported in the work by Portmann and coll.?\nThe investigation on the consequences of genetic manipulations on striatal physiology is very limited and does not add much to the interpretation of the overall results, hence it could be omitted. Recordings have been performed only in the Nucleus accumbens, not in the dorsolateral striatum, despite the authors suggest that the latter region drives the hyperactive behavior in 16p11.2 hemideletion male mice. Furthermore, only spontaneous miniature GABAergic inhibitory transmission is evaluated, and it shows changes (despite different) in both D1-SPNs and D2-SPNs. Notably, previous work reported alterations in excitatory synaptic transmission. In order to correlate the hyperactive phenotype to alterations in striatal physiology, a more in depth analysis should be carried out in the dorsolateral striatum. It would be very interesting to analyze the changes induced by the different genetic manipulations in the physiology of the dorsolateral striatum, and correlate them to the observed behavioral and transcriptomic changes.", "reviewer_3": "This work by Kim and colleagues presents a clear and compelling study dissecting the effects of 16p11.2 deletion in striatal circuits on hyperactivity, electrophysiology, and gene expression in male and female mice. Results demonstrate a specific role for D2 spiny projection neurons in males’ hyperactivity, while deletion of the syntenic 16p11.2 region in cortex induces hyperactivity in both sexes. Single nucleus expression profiling finds a greater number of gene expression changes in male than female hets, and surprisingly finds that expression changes in hets parallel expression differences between females and males (changes in hets akin to female expression skews relative to males). This work presents compelling evidence for involvement of striatal circuitry in 16p11.2 deletion impacts and for sex-differential striatal circuit function, which may be important for understanding mechanisms for multiple neuropsychiatric conditions. The hyperactivity data are clear and straightforward to interpret. I primarily have questions about results from the snRNA-seq data:\nMajor comments\n(1) snRNA-seq data were generated from N=2 animals for each group. Were animals within each genotype-sex group from different litters, or were they littermates? As animals within a litter can be more similar to each other than animals from different litters, providing this information in the methods will help readers interpret the data.\n(2) Similarly, with N of 2 per group, it is possible that expression features from a single animal may drive some of the sex and genotype differences reported. This is especially a concern when differential expression methods that utilize cells as replicates are applied, since cells from the same animal are more similar to each other than cells from different animals. Methods that treat each animal as independent replicates, where expression measurements from cells from the same cluster and animal are combined (pseudobulk), are preferable. Can the authors confirm, was the Wilcoxon rank sum test from Seurat run such that cells are treated as replicates? If so, can a pseudobulk approach also be applied to confirm that the reported patterns are robust?\n(3) Is expression of genes within the deleted 16p11.2 region reduced in het males and females? Can these genes be marked in Fig 1C-F volcano plots? Can the highlighted ASD genes also be marked in these plots?\n(4) For gene set overlaps reported in Fig 1G,H,I and in text (lines 129-141), are the reported overlaps more or less than expected by chance? Can a Fisher’s exact or hypergeometric test be applied to assess the statistical likelihood of these overlaps?\n(5) Regarding differential expression of ASD risk genes in 16p11.2 hets, what is the direction of expression change for these genes? Many of the ASD risk genes are associated with ASD due to their haploinsufficiency, and protein-truncating variants that lead to reduced expression of these genes. Are ASD risk genes decreased or elevated in 16p11.2 hets?\n(6) Line 174 notes use of “quadrant plot analysis” which is not described in the Methods. Are the p-values in Fig S4 from a Pearson correlation test?\n(7) Does risperidone reduce hyperactivity to level of WT animals? Consider including WT animals’ activity in Fig S8 panels for a side-by-side comparison.\n(8) Discussion text ~line 385 notes the “unexpected shift of gene expression patterns in 16p11.2 del/+ males toward wt females”. Apart from a simple “molecular-level sex difference in the striatum”, I encourage the authors to think about what this might mean mechanistically. For example, is expression change for these genes in het males indicative of a disease-like process, or could it include a possible compensatory signature? Perhaps wt females express a compensatory-like expression program at baseline, which is then induced in 16p het males? (or other possibilities!)\nMinor comments\n(1) Fig 1C-F, please clarify and clearly label the direction of comparison. The plot titles on the figure say WT vs 16p, legend says 16p vs WT.\n(2) Fig 1G, H are fine as is but the comparison between DE gene lists is by definition dependent on significance threshold. A threshold-free test, e.g. rank-rank hypergenometric overlap, would give more thorough picture of shared changes across the transcriptome. But, if a point of these venn diagrams is that more genes are 16p-sensitive in males than females, maybe consider scaling size of circles to reflect this difference.\n(3) Fig S4G needs some clarification, is x-axis meant to represent gene expression level? I understand the hypothesis that 16p females’ phenotype may be intermediate between WTs and 16p males, but what is the rationale for the expectation that 16p females' expression would be so close to that of WTs?\n(4) Sentence at lines 287-290 seems fragmented, missing a few words? (or remove “that”?)\n(5) Lines 368-369, define what is meant by “enrichment” in this sentence. Often enrichment implies the use of a statistical test to assess likelihood of overlap or expression.", "reviewer_4": "This study employed single-nucleus RNA sequencing (snRNA-seq) to investigate the effects of the 16p11.2 del/+ genetic deletion within the striatum of mice. The researchers observed that the hemideletion induced distinct changes in gene expression profiles of D1 and D2 striatal projection neurons (SPNs). Notably, these effects were more pronounced in males compared to females. Interestingly, many of the genes impacted (DEGs) are associated with autism spectrum disorder (ASD). Additionally, the study suggests that the 16p11.2 del/+ hemideletion disrupts neuronal communication in male mice, particularly affecting GABA release and responsiveness.\nFinally, the authors demonstrated that the location of the deletion also influenced behavior. When specifically expressed in D2-SPNs of the dorsolateral striatum (DLS), the 16p11.2 del/+ deletion resulted in increased locomotor activity only in male mice. Conversely, deletion in the cortex caused hyperactivity in both sexes.\nWhile the research offers interesting findings, several issues require further exploration to strengthen the overall contribution.\n- While the manuscript presents interesting findings, for publication in a high-impact journal like Nature Communications, expanding the research scope and delving deeper into the mechanisms underlying the observed effects could significantly strengthen the overall impact.\n- While the authors report that 16p11.2 del/+ hemideletion disrupts synaptic properties in D1-SPNs and D2-SPNs of male mice, the analysis is limited to miniature currents measured in the nucleus accumbens. This contrasts with the transcriptomics data, which focused on the entire striatum.\n- While the nucleus accumbens is a relevant brain region, it would be helpful for the authors to elaborate on their reasons for focusing on this specific area for electrophysiological analysis, especially since the transcriptomic data covered the whole striatum.\n- Additionally, while they analyze miniature excitatory postsynaptic currents (mEPSCs), a previous study [54] reported increased mEPSC frequency and AMPAR/NMDAR ratio in 16p11.2 del/+ SPNs, suggesting alterations at both pre- and postsynaptic sites. Analyzing membrane properties and spontaneous activity of the cells could provide, for example, a more comprehensive picture of these potential changes.\n- The authors' focus on locomotor activity in the behavioral analysis provides a starting point for understanding the functional effects of the deletion. However, expanding the behavioral analysis to include additional relevant tests could provide a more comprehensive picture. For instance, since the electrophysiological experiments were conducted in the nucleus accumbens, a brain region known for its role in social behavior, exploring social interaction patterns in the mice could be particularly valuable.\n- The finding that 16p11.2 del/+ specifically in D2-SPNs of the DLS drives hyperactivity only in male mice is a key result. However, the lack of electrophysiological data from this specific brain region is a significant limitation. Understanding the electrophysiological changes associated with the deletion in DLS could provide crucial insights into the mechanisms underlying the observed sex-specific hyperactivity."}, "author_response": "NCOMMS-24-26009\nCorresponding Authors: Ted Abel\nResponse to Reviewer’s Critiques\nWe thank the reviewers for their time, effort, and thoughtful evaluation of our manuscript. We greatly appreciate the insightful and constructive comments, which have helped us to improve the quality and clarity of the work.\nIn response to the reviewers’ suggestions, we have substantially revised the manuscript. These revisions include new experiments, fiber photometry recordings, electrophysiological assessments, and pharmacological interventions that broaden the scope and strengthen the conclusions of our study. Fiber photometry recordings of GCaMP activity from the dorsal striatum reveal reduced neuronal activity frequency in 16p11.2 del/+ males, but not females, during open-field exploration. D2-SPNs were identified as the primary contributors to this reduction. Additional electrophysiology experiments in the dorsal striatum of both sexes further support the sex- and cell type-specific impact of the mutation. Pharmacological experiments using sulpiride and risperidone demonstrate sexually dimorphic effects on locomotor activity, highlighting the potential need for sex-specific therapeutic strategies. We believe these additional experiments have significantly enhanced the overall rigor and impact of the manuscript. In addition, we have revised the manuscript text to address specific concerns raised by the reviewers.\nBelow, we provide a point-by-point response to each of the reviewer’s comments (with our responses formatted in italic text). New or revised passages in the manuscript are indicated in bold italic text. We hope the reviewers will find that we have thoroughly addressed their concerns and substantially improved the manuscript as a result."}, {"round": 2, "reviewer_comments": {"reviewer_3": "I appreciate the authors’ thorough consideration of my previous questions about the single nucleus RNA-seq analyses and interpretations for this study. As several very interesting patterns and future hypotheses rest on the differential expression analyses of these data, I would ask that the authors include in supplements the pseudobulk DE analysis (currently in rebuttal only), and add a comment to the Discussion to note the limitations of DEG testing in single nuclei data sets with N=2 animals per group. The content and legends of Fig S5 can also be clarified.\n(1) It is encouraging that DESeq2 analysis of pseudobulked data from the Seurat AggregateExpression function also shows positive correlations between sex effects and het vs. wt effects in males, though these correlations appear to be potentially driven by a handful of genes with large sex differences (Rnf121, Gm26825, Tmem181a). Do the positive correlations remain if these genes are excluded? And/or if Spearman correlation is used instead of Pearson?\nFor full transparency as the field moves away from cell-based to sample-based DE analyses, I would strongly encourage the authors to include these pseudobulk DE results in the supplements. The plots provided in the rebuttal document can also be updated to mirror the other analyses presented in Fig S5: plot and test only DEGs with minimum log2FC magnitude 0.2, include number of genes per quadrant on the plots. With N=2 animals per group, these are admittedly underpowered tests, so weaker patterns here may be attributed to power, but will still provide important information and context for readers’ interpretation of these findings and for future study design.\n(2) Related, and as noted above, the limitations of DEG testing in single nuclei data sets with N=2 animals per group should be noted in the Discussion. That similar patterns are seen in bulk RNA data from striatum is reassuring, and should be emphasized while noting that larger sample sizes are needed in the future and/or independent replication of the D1 and D2 patterns at the snRNA level.\n(3) Fig S5, I apologize for not noting this in the first submission, but there are several inconsistencies across the panels in this figure that make it challenging to understand.\nFor panels A-D and F, sex diffs are on X axis and genotype diffs are on Y axis, but panel E is the opposite (genotype diffs on X, sex diffs on Y). It would be helpful to swap the axes in E for consistency.\nBased on the plot gaps around 0 logFC (0.2 logFC threshold for calling DEGs), it also appears that different DEG sets are plotted in different panels. Panels A-B appear to plot/test sex-DEGs, but panels C-F appear to plot/test genotype-DEGs. Consistency across tested gene sets would also be helpful, or rationale should be provided for why sex-DEGs are used for the male-anchored comparisons (A, B) vs. female-anchored comparisons (C, D).\nPanel labels and legend text do not agree for several panels. A, B, C, and D, image has sex-logFC on X, genotype-logFC on Y, but legend text says opposite (genotype-logFC on X, sex-logFC on Y). Panel E and F, image and legend do agree.\n(4) Discussion, lines 438-452 discuss the intersection between ASD risk genes and 16p11.2 del/+ DEGs, but the direction of effect is not mentioned here. It is likely of interest that a majority of these genes are up-regulated in 16p11.2 del/+ (exceptions for Grin2b and Ube3a), consistent with the hypothesis of a compensatory response, as opposed to compounding polygenic effects in the same direction. This pattern is noted in the next paragraph in the context of sex differences (lines 464-466), but seems also relevant here.\n(5) The updated text presents an intriguing hypothesis that females have elevated expression at baseline (vs. males) of genes potentially involved in compensatory mechanisms, and that het males increase expression of these same genes in the presence of a 16p11.2 del. It is implied that female hets then do not also exhibit a similar compensatory, further increase in expression of these genes (and the 5x smaller number of het DEGs in females is consistent with this). NOT REQUIRED, but this could be tested more directly – for example, by taking the genes elevated in wt females and het males (upper right quadrant), and using a sign test/binomial test to evaluate their direction of effect in del females (vs. wt females). Greater than 50% of genes with positive log2 FC (het > wt) and significance by binomial test may indicate that females also mount a (weaker) compensatory response by increasing expression of these genes, while a null result supports the hypothesis of male-specific compensation.", "reviewer_4": "This manuscript analyses the gender- and type-specific impact of the 16p11.2 haemideletion on striatal microcircuitry.\nI appreciate the authors' efforts in revising the manuscript. Most of my previous concerns have been adequately addressed and the revised version represents a substantial improvement. Especially interesting and valuable are the new experiments, including electrophysiological experiments in the dorsal striatum, fibre photometry and sulpiride treatment.\nHowever, a minor points require clarification.\n1) Spontaneous and miniaturised postsynaptic currents, either excitatory or inhibitory, differ in their origin and provide different information about the synapse. The authors employed spontaneous IPSCs in the dorsal striatum and miniature IPSCs in the nucleus accumbens. Can the authors discuss their choice?\n2) Ventral striatum and nucleus accumbens are close related but not the same area. The authors rifers to the nucleus accumbens regarding electrophysiological experiments and further to the ventral striatum for locomotion expeirments. If they refers to the same structure it should be better to use always the same name."}, "author_response": "NCOMMS-24-26009A\nCorresponding Authors: Ted Abel\nResponse to Reviewer’s Critiques\nWe thank the reviewers for their thoughtful evaluation and constructive comments, which have improved the clarity and quality of our manuscript.\nIn response to the reviewers’ suggestions, we have revised the manuscript. These revisions include additional analysis of the snRNA-seq results and updates to the supplementary figures for the quadrant plots. In addition, we have revised the text of the manuscript to address specific concerns raised by the reviewers, and we updated the manuscript title, abstract, and references to comply with the formatting requirements of Nature Communications. The revised version of the manuscript has been seen and approved by all authors.\nBelow, we provide a point-by-point response to each of the reviewer’s comments (with our responses formatted in blue italic). New or revised passages in the manuscript are indicated by blue bold italic text. We hope the reviewers will find that we have thoroughly addressed their concerns and improved the manuscript as a result."}, {"round": 3, "reviewer_comments": {"reviewer_3": "I appreciate the authors’ thoughtful responses to my remaining concerns. I have no further comments about this updated version of the manuscript.", "reviewer_4": "The authors have carefully revised the manuscript based on the reviewers’ comments. I greatly appreciate their dedication and attention to detail. All of my previous concerns have been satisfactorily addressed, and the manuscript has been greatly improved. I have no further comments to add."}, "author_response": "NCOMMS-24-26009B\nCorresponding Authors: Ted Abel\nResponse to Reviewer’s Comments\nWe sincerely thank the reviewers for their careful evaluation of our revised manuscript and for their positive comments. We appreciate their acknowledgement that all previous concerns have been fully addressed and have no further comments."}]

Decision letter