Biology subjects

Giusti-Rodriguez, P.

Publications and source records attributed to Giusti-Rodriguez, P..

12 recordsLinked to original sources

bioRxiv2026

3D-genome impacts of TAD-boundary-disrupting ultra-rare structural variants identified in schizophrenia

Schizophrenia is a complex and multifactorial brain disorder that impacts ~1% of the U.S. population. The genetic architecture of schizophrenia includes 10 large rare structural variants (SVs) ~10 exonic variants, and over 250 common variants. Previously we combined whole genome sequencing (WGS) with brain-specific epigenomic data and found an excess of ultrarare SVs in schizophrenia localizing to the boundaries of topologically associated domains (TADs). Alterations in TAD boundaries (TAD-b) may lead to disarrangement of enhancer-promoter contacts and dysregulation of gene expression and have been associated with several human diseases. Our study sought to functionally characterize two of these TAD-b SVs using chromatin conformation capture (e.g., Hi-C) and RNA sequencing, to unveil mechanistic insight into the effects of these variants on 3D-genome organization and gene expression. To achieve this, we genetically engineered these two TAD-b SVs in isogenic induced pluripotent stem cells (iPSCs) using CRISPR/Cas9. iPSCs were differentiated into neuronal precursor cells, excitatory glutamatergic neurons, and medium spiny neurons. We found that these TAD-boundary-disrupting SVs could reshape the 3D-genome and transcriptional networks in a cell-type-specific manner.

genomics↗

bioRxiv2026

Functional Annotation of the Major Histocompatibility Complex Locus

The human major histocompatibility complex (MHC) locus has the greatest density of disease-associations in the human genome, including links to over 100 polygenic disorders. Its complex haplotype structure, rich gene density, and high degree of linkage disequilibrium combine to make deciphering the gene regulatory logic of the MHC locus extremely challenging. Employing complementary high-throughput CRISPR interference (CRISPRi) and activation (CRISPRa) epigenetic screens coupled with single-cell transcriptome profiling across three distinct human cell types, we identified hundreds of new connections between cis-regulatory elements (CREs) and their target genes in this locus. These CRE-gene links are largely cell type-specific and act as enhancers. Additionally, some CREs have complex features, including harboring both active and repressive histone marks, lacking chromatin accessibility, targeting multiple genes, or acting as silencers. Computational methods fail to predict a majority of these CRE-gene connections. These findings emphasize the potential for functional perturbation experiments to dissect complex loci and reveal shared and cell type-specific regulatory mechanisms relevant to genomics of complex diseases. Collectively, this study provides a unique resource for understanding the complex regulatory landscape within the MHC locus and supports the need for creating new models that encompass CRE-gene interactions, cell type-specific gene expression, and disease genetics in the noncoding genome.

genomics↗

bioRxiv2025

Distinct patterns of de novo coding variants contribute to Tourette Syndrome etiology

Tourette syndrome (TS) is a highly heritable childhood-onset neuropsychiatric disorder characterized by persistent motor and vocal tics. While both common and rare variants contribute to TS susceptibility, the role of rare de novo mutations (DNMs) remains incompletely characterized. Here, we report findings from the largest TS whole-exome sequencing study to date, analyzing 1,466 TS trios alongside 6,714 autism spectrum disorder (ASD) trios and 5,880 unaffected sibling controls from the Simons Simplex Collection (SSC) and SPARK cohorts. Leveraging a trio-based design across these cohorts enabled calibrated assessment of DNM burden while controlling for background mutation rates. We observed a significant exome-wide enrichment of protein-truncating DNMs in TS probands, particularly within genes intolerant to loss-of-function variation (pLI [≥] 0.9), with little contribution from damaging missense variants. Notably, TS probands did not exhibit enrichment in previously implicated ASD or developmental delay (DD) genes, but elsewhere in the genome, suggesting a distinct rare variant architecture. Using a Bayesian statistical framework that integrates both de novo and rare inherited coding variants, we identified three candidate TS risk genes with FDR [≤] 0.05: PPP5C, EXOC1, and GXYLT1. Literature shows that they have prior links to neurodevelopmental and psychiatric disorders. These findings reveal a rare variant burden in TS that is genetically distinguishable from ASD, underscore the importance of loss-of-function mutations in TS risk, and nominate novel candidate genes for future functional investigation.

neuroscience↗

bioRxiv2025

MarkerMatch: A Proximity-Based Probe-Matching Algorithm for Joint Analysis of Copy-Number Variants from Different Genotyping Arrays

MotivationCopy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to call CNVs, which can be used in association tests, such as association between CNV number and disease status. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (the intersection encompassing the probes that occur in common on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has, however, led to excessive reduction in overall sensitivity of CNV calls as arrays can have an undesirably low overlap of probe sets. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision. ResultsBy analyzing CNV calls from 4,906 individuals genotyped across three different arrays (Global Screening Array, Omni2.5 array, and Omni Express Exome array), we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g., use of consensus probes only). We further demonstrate that MarkerMatch exceeds the output from current practice in terms of F1 score, Fowlkes-Mallows index, and Jaccard index. We also optimize MarkerMatch parameters, DMAX and Method, and find an optimal DMAX setting at 10kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis.

bioinformatics↗

bioRxiv2023

SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model

Harnessing the power of single-cell genomics technologies, single-cell Hi-C (scHi-C) and its derived technologies provide powerful tools to measure spatial proximity between regulatory elements and their target genes in individual cells. Using a global background model, we propose SnapHiC-G, a computational method to identify long-range enhancer-promoter interactions from scHi-C data. We applied SnapHiC-G to scHi-C datasets generated from mouse embryonic stem cells and human brain cortical cells and demonstrated that SnapHiC-G achieved high sensitivity in identifying long-range enhancer-promoter interactions. Moreover, SnapHiC-G can identify putative target genes for non-coding GWAS variants, and the genetic heritability of neuropsychiatric diseases is enriched for single nucleotide polymorphisms (SNPs) within SnapHiC-G-identified interactions in a cell-type-specific manner. In sum, SnapHiC-G is a powerful tool for characterizing cell-type-specific enhancer-promoter interactions from complex tissues and can facilitate the discovery of chromatin interactions important for gene regulation in biologically relevant cell types.

genetics↗

bioRxiv2020

Skewed X inactivation in genetically diverse mice is associated with recurrent copy number changes at the Xce locus

Female mammals are functional mosaics of their parental X-linked gene expression due to X chromosome inactivation (XCI). This process inactivates one copy of the X chromosome in each cell during embryogenesis and that state is maintained clonally through mitosis. In mice, the choice of which parental X chromosome remains active is determined by the X chromosome controlling element (Xce), which has been mapped to a 176 kb candidate interval. A series of functional Xce alleles has been characterized or inferred for classical inbred strains based on biased, or skewed, inactivation of the parental X chromosomes in crosses between strains. To further explore the function-structure basis and location of the Xce, we measured allele-specific expression of X-linked genes in a large population of F1 females generated from Collaborative Cross strains. Using published sequence data and applying a Bayesian "Polya urn" model of XCI skew, we report two major findings. First, inter-individual variability in XCI suggests mouse epiblasts contain on average 20-30 cells contributing to brain. Second, NOD/ShiLtJ has a novel and unique functional allele, Xcef, that is the weakest in the Xce allelic series. Despite phylogenetic analysis confirming that NOD/ShiLtJ carries a haplotype almost identical to the well-characterized C57BL/6J (Xceb), we observed unexpected patterns of XCI skewing in females carrying the NOD/ShiLtJ haplotype within the Xce. Copy number variation is common at the Xce locus and we conclude that the observed allelic series is a product of independent and recurring duplications shared between weak Xce alleles.

genetics↗

bioRxiv2019

Antipsychotic behavioral phenotypes in the mouse Collaborative Cross recombinant inbred inter-crosses (RIX)

Schizophrenia is an idiopathic disorder that affects approximately 1% of the human population, and presents with persistent delusions, hallucinations, and disorganized behaviors. Antipsychotics are the standard pharmacological treatment for schizophrenia, but are frequently discontinued by patients due to inefficacy and/or side effects. Chronic treatment with the typical antipsychotic haloperidol causes tardive dyskinesia (TD), which manifests as involuntary and often irreversible orofacial movements in around 30% of patients. Mice treated with haloperidol develop many of the features of TD, including jaw tremors, tongue protrusions, and vacuous chewing movements (VCMs). In this study, we used genetically diverse Collaborative Cross (CC) recombinant inbred inter-cross (RIX) mice to elucidate the genetic basis of antipsychotic-induced adverse drug reactions (ADRs). We performed a battery of behavioral tests in 840 mice from 73 RIX lines (derived from 62 CC strains) treated with haloperidol or placebo in order to monitor the development of ADRs. We used linear mixed models to test for strain and treatment effects. We observed highly significant strain effects for almost all behavioral measurements investigated (p<0.001). Further, we observed strong strain-by-treatment interactions for most phenotypes, particularly for changes in distance traveled, vertical activity, and extrapyramidal symptoms (EPS). Estimates of overall heritability ranged from 0.21 (change in body weight) to 0.4 (VCMs and change in distance traveled) while the portion attributable to the interactions of treatment and strain ranged from 0.01 (for change in body weight) to 0.15 (for change in EPS). Interestingly, close to 30% of RIX mice exhibited VCMs, a sensitivity to haloperidol exposure, approximately similar to the rate of TD in humans chronically exposed to haloperidol. Understanding the genetic basis for the susceptibility to antipsychotic ADRs may be possible in mouse, and extrapolation to humans could lead to safer therapeutic approaches for schizophrenia.

systems biology↗

bioRxiv2019

Shared Genetic Risk between Eating Disorder- and Substance-Use-Related Phenotypes: Evidence from Genome-Wide Association Studies

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa (BN) and problem alcohol use (genetic correlation [rg], twin-based=0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge-eating, AN without binge-eating, and a BN factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder (MDD). Total sample sizes per phenotype ranged from ~2,400 to ~537,000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg=0.18; false discovery rate q=0.0006), cannabis initiation and AN (rg=0.23; q<0.0001), and cannabis initiation and AN with binge-eating (rg=0.27; q=0.0016). Conversely, significant negative genetic correlations were observed between three non-diagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge-eating (rgs=-0.19 to -0.23; qs<0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for MDD loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships between these behaviors.

genetics↗

bioRxiv2019

Robust Hi-C chromatin loop maps in human neurogenesis and brain tissues at high-resolution

Genome-wide mapping of chromatin interactions at high resolution remains experimentally and computationally challenging. Here we used a low-input \"easy Hi-C\" (eHi-C) protocol to map the 3D genome architecture in neurogenesis and brain tissues, and also developed an improved Hi-C bias-correction pipeline (HiCorr) enabling better identification of enhancer loops or aggregates at sub-TAD level. We compared ultra-deep 3D genome maps from 10 human tissue- or cell types, with a focus on stem cells and neural development. We found several large loci in skin-derived human iPSC lines showing recurrent 3D compartmental memory of somatic heterochromatin. Chromatin loop interactions, but not genome compartments, are hallmarks of neural differentiation. Interestingly, we observed many cell type- or differentiation-specific enhancer aggregates spanning large neighborhoods, supporting a phase-separation mechanism that stabilizes enhancer contacts during development. Finally, we demonstrated that chromatin loop outperforms eQTL in explaining neurological GWAS results, revealing a unique value of high-resolution 3D genome maps in elucidating the disease etiology.\n\nHighlightsO_LILow input \"easy Hi-C\" protocol compatible with 50-100K cells\nC_LIO_LIImproved Hi-C bias correction allows direct observation and accurate identification of sub-TAD chromatin loops and enhancer aggregates\nC_LIO_LIRecurrent architectural memory of somatic heterochromatin at compartment level in skin-derived hiPSCs\nC_LIO_LIChromatin loop, but not genome compartment, marks neural differentiation\nC_LIO_LIChromatin loop outperforms eQTL in defining brain GWAS target genes\nC_LI

genomics↗

bioRxiv2017

Genetic Identification Of Brain Cell Types Underlying Schizophrenia

With few exceptions, the marked advances in knowledge about the genetic basis for schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. Applying knowledge of the cellular taxonomy of the brain from single-cell RNA-sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. The common variant genomic results consistently mapped to pyramidal cells, medium spiny neurons, and certain interneurons but far less consistently to embryonic, progenitor, or glial cells. These enrichments were due to distinct sets of genes specifically expressed in each of these cell types. Many of the diverse gene sets associated with schizophrenia (including antipsychotic targets) implicate the same brain cell types. Our results provide a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. While some of the genetic risk is associated with GABAergic interneurons, this risk largely does not overlap with that from projecting cells.

genomics↗

bioRxiv2017

Evaluation Of Chromatin Accessibility In Prefrontal Cortex Of Schizophrenia Cases And Controls

Schizophrenia genome-wide association (GWA) studies have identified over 150 regions of the genome that are associated with disease risk, yet there is little evidence that coding mutations contribute to this disorder. To explore the mechanism of non-coding regulatory elements in schizophrenia, we performed ATAC-seq on adult prefrontal cortex brain samples from 135 individuals with schizophrenia and 137 controls, and identified 118,152 ATAC-seq peaks. These accessible chromatin regions in brain are highly enriched for SNP-heritability for schizophrenia (10.6 fold enrichment, P=2.4x10-4, second only to genomic regions conserved in Eutherian mammals) and replicated in an independent dataset (9.0 fold enrichment, P=2.7x10-4). This degree of enrichment of schizophrenia heritability was higher than in open chromatin found in 138 different cell and tissue types. Brain open chromatin regions that overlapped highly conserved regions exhibited an even higher degree of heritability enrichment, indicating that conservation can identify functional subsets within regulatory elements active in brain. However, we did not identify chromatin accessibility differences between schizophrenia cases and controls, nor did we find an interaction of chromatin QTLs with case-control status. This indicates that although causal variants map within regulatory elements, mechanisms other than differential chromatin may govern the contribution of regulatory element variation to schizophrenia risk. Our results strongly implicate gene regulatory processes involving open chromatin in the pathogenesis of schizophrenia, and suggest a strategy to understand the hundreds of common variants emerging from large genomic studies of complex brain diseases.

genomics↗

bioRxiv2017

Common Variant Associations with Fragile X Syndrome

Fragile X syndrome is a common cause of intellectual disability. It is usually caused by a de novo mutation which often occur on multiple haplotypes and should not be detectible using genome-wide association (GWA). We conducted GWA 89 male FXS cases and 266 male controls, and detected multiple genome-wide significant signals near FMR1 (odds ratio=8.10, P=2.5x10-10). These findings withstood robust attempts at falsification. Fine-mapping did not serve to narrow the interval (minimum P=1.13xl0-14), and functional genomic integration (including 5C data we generated for this region) did not provide a mechanistic hypothesis. Controls carrying a risk haplotype had significantly longer and more variable FMR1 CGG repeats than controls with the protective haplotype (P=4.75x10-5) which may predispose toward increases in CGG number to the pre-mutation range over many generations. This is a salutary reminder of the complexity of even \"simple\" monogenetic disorders.

genetics↗