Local and global chromatin interactions are altered by large genomic deletions associated with human brain development

Resolving the 22q11.2 deletion using CTLR-Seq reveals chromosomal rearrangement mechanisms and individual variance in breakpoints

We developed a generally applicable method, CRISPR/Cas9-targeted long-read sequencing (CTLR-Seq), to resolve, haplotype-specifically, the large and complex regions in the human genome that had been previously impenetrable to sequencing analysis, such as large segmental duplications (SegDups) and their associated genome rearrangements. CTLR-Seq combines in vitro Cas9-mediated cutting of the genome and pulse-field gel electrophoresis to isolate intact large (i.e., up to 2,000 kb) genomic regions that encompass previously unresolvable genomic sequences. These targets are then sequenced (amplification-free) at high on-target coverage using long-read sequencing, allowing for their complete sequence assembly. We applied CTLR-Seq to the SegDup-mediated rearrangements that constitute the boundaries of, and give rise to, the 22q11.2 Deletion Syndrome (22q11DS), the most common human microdeletion disorder. We then performed de novo assembly to resolve, at base-pair resolution, the full sequence rearrangements and exact chromosomal breakpoints of 22q11.2DS (including all common subtypes). Across multiple patients, we found a high degree of variability for both the rearranged SegDup sequences and the exact chromosomal breakpoint locations, which coincide with various transposons within the 22q11.2 SegDups, suggesting that 22q11DS can be driven by transposon-mediated genome recombination. Guided by CTLR-Seq results from two 22q11DS patients, we performed three-dimensional chromosomal folding analysis for the 22q11.2 SegDups from patient-derived neurons and astrocytes and found chromosome interactions anchored within the SegDups to be both cell type-specific and patient-specific. Lastly, we demonstrated that CTLR-Seq enables cell-type specific analysis of DNA methylation patterns within the deletion haplotype of 22q11DS.

Genomic, molecular, and cellular divergence of the human brain

While many core biological processes are conserved across species, the human brain has evolved with unique capacities. Current understanding of the neurobiological mechanisms that endow human traits as well as associated vulnerabilities remains limited. However, emerging data have illuminated species divergence in DNA elements and genome organization, in molecular, morphological, and functional features of conserved neural cell types, as well as temporal differences in brain development. Here, we summarize recent data on unique features of the human brain and their complex implications for the study and treatment of brain diseases. We also consider key outstanding questions in the field and discuss the technologies and foundational knowledge that will be required to accelerate understanding of human neurobiology.

Abnormal developmental trajectory and vulnerability to cardiac arrhythmias in tetralogy of Fallot with DiGeorge syndrome

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease. Ventricular dysfunction and cardiac arrhythmias are well-documented complications in patients with repaired TOF. Whether intrinsic abnormalities exist in TOF cardiomyocytes is unknown. We establish human induced pluripotent stem cells (hiPSCs) from TOF patients with and without DiGeorge (DG) syndrome, the latter being the most commonly associated syndromal association of TOF. TOF-DG hiPSC-derived cardiomyocytes (hiPSC-CMs) show impaired ventricular specification, downregulated cardiac gene expression and upregulated neural gene expression. Transcriptomic profiling of the in vitro cardiac progenitors reveals early bifurcation, as marked by ectopic RGS13 expression, in the trajectory of TOF-DG-hiPSC cardiac differentiation. Functional assessments further reveal increased arrhythmogenicity in TOF-DG-hiPSC-CMs. These findings are found only in the TOF-DG but not TOF-with no DG (ND) patient-derived hiPSC-CMs and cardiac progenitors (CPs), which have implications on the worse clinical outcomes of TOF-DG patients.

The impact of 22q11.2 copy-number variants on human traits in the general population

While extensively studied in clinical cohorts, the phenotypic consequences of 22q11.2 copy-number variants (CNVs) in the general population remain understudied. To address this gap, we performed a phenome-wide association scan in 405,324 unrelated UK Biobank (UKBB) participants by using CNV calls from genotyping array. We mapped 236 Human Phenotype Ontology terms linked to any of the 90 genes encompassed by the region to 170 UKBB traits and assessed the association between these traits and the copy-number state of 504 genotyping array probes in the region. We found significant associations for eight continuous and nine binary traits associated under different models (duplication-only, deletion-only, U-shape, and mirror models). The causal effect of the expression level of 22q11.2 genes on associated traits was assessed through transcriptome-wide Mendelian randomization (TWMR), revealing that increased expression of ARVCF increased BMI. Similarly, increased DGCR6 expression causally reduced mean platelet volume, in line with the corresponding CNV effect. Furthermore, cross-trait multivariable Mendelian randomization (MVMR) suggested a predominant role of genuine (horizontal) pleiotropy in the CNV region. Our findings show that within the general population, 22q11.2 CNVs are associated with traits previously linked to genes in the region, and duplications and deletions act upon traits in different fashions. We also showed that gain or loss of distinct segments within 22q11.2 may impact a trait under different association models. Our results have provided new insights to help further the understanding of the complex 22q11.2 region.

Abnormal Chromatin Folding in the Molecular Pathogenesis of Epilepsy and Autism Spectrum Disorder: a Meta-synthesis with Systematic Searching

How DNA is folded and packaged in nucleosomes is an essential regulator of gene expression. Abnormal patterns of chromatin folding are implicated in a wide range of diseases and disorders, including epilepsy and autism spectrum disorder (ASD). These disorders are thought to have a shared pathogenesis involving an imbalance in the number of excitatory-inhibitory neurons formed during neurodevelopment; however, the underlying pathological mechanism behind this imbalance is poorly understood. Studies are increasingly implicating abnormal chromatin folding in neural stem cells as one of the candidate pathological mechanisms, but no review has yet attempted to summarise the knowledge in this field. This meta-synthesis is a systematic search of all the articles on epilepsy, ASD, and chromatin folding. Its two main objectives were to determine to what extent abnormal chromatin folding is implicated in the pathogenesis of epilepsy and ASD, and secondly how abnormal chromatin folding leads to pathological disease processes. This search produced 22 relevant articles, which together strongly implicate abnormal chromatin folding in the pathogenesis of epilepsy and ASD. A range of mutations and chromosomal structural abnormalities lead to this effect, including single nucleotide polymorphisms, copy number variants, translocations and mutations in chromatin modifying. However, knowledge is much more limited into how abnormal chromatin organisation subsequently causes pathological disease processes, not yet showing, for example, whether it leads to abnormal excitation-inhibitory neuron imbalance in human brain organoids.

The 22q11.2 Low Copy Repeats

LCR22s are among the most complex loci in the human genome and are susceptible to nonallelic homologous recombination. This can lead to a variety of genomic disorders, including deletions, duplications, and translocations, of which the 22q11.2 deletion syndrome is the most common in humans. Interrogating these phenomena is difficult due to the high complexity of the LCR22s and the inaccurate representation of the LCRs across different reference genomes. Optical mapping techniques, which provide long-range chromosomal maps, could be used to unravel the complex duplicon structure. These techniques have already uncovered the hypervariability of the LCR22-A haplotype in the human population. Although optical LCR22 mapping is a major step forward, long-read sequencing approaches will be essential to reach nucleotide resolution of the LCR22s and map the crossover sites. Accurate maps and sequences are needed to pinpoint potential predisposing alleles and, most importantly, allow for genotype-phenotype studies exploring the role of the LCR22s in health and disease. In addition, this research might provide a paradigm for the study of other rare genomic disorders.

Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p

The canonical paradigm for converting genetic association to mechanism involves iteratively mapping individual associations to the proximal genes through which they act. In contrast, in the present study we demonstrate the feasibility of extracting biological insights from a very large region of the genome and leverage this strategy to study the genetic influences on autism. Using a new statistical approach, we identified the 33-Mb p-arm of chromosome 16 (16p) as harboring the greatest excess of autism's common polygenic influences. The region also includes the mechanistically cryptic and autism-associated 16p11.2 copy number variant. Analysis of RNA-sequencing data revealed that both the common polygenic influences within 16p and the 16p11.2 deletion were associated with decreased average gene expression across 16p. The transcriptional effects of the rare deletion and diffuse common variation were correlated at the level of individual genes and analysis of Hi-C data revealed patterns of chromatin contact that may explain this transcriptional convergence. These results reflect a new approach for extracting biological insight from genetic association data and suggest convergence of common and rare genetic influences on autism at 16p.

3D Genome Plasticity in Normal and Diseased Neurodevelopment

Non-random spatial organization of the chromosomal material inside the nuclei of brain cells emerges as an important regulatory layer of genome organization and function in health and disease. Here, we discuss how integrative approaches assessing chromatin in context of the 3D genome is providing new insights into normal and diseased neurodevelopment. Studies in primate (incl. human) and rodent brain have confirmed that chromosomal organization in neurons and glia undergoes highly dynamic changes during pre- and early postnatal development, with potential for plasticity across a much wider age window. For example, neuronal 3D genomes from juvenile and adult cerebral cortex and hippocampus undergo chromosomal conformation changes at hundreds of loci in the context of learning and environmental enrichment, viral infection, and neuroinflammation. Furthermore, locus-specific structural DNA variations, such as micro-deletions, duplications, repeat expansions, and retroelement insertions carry the potential to disrupt the broader epigenomic and transcriptional landscape far beyond the boundaries of the site-specific variation, highlighting the critical importance of long-range intra- and inter-chromosomal contacts for neuronal and glial function.

Loss of function of OTUD7A in the schizophrenia- associated 15q13.3 deletion impairs synapse development and function in human neurons

Identifying causative gene(s) within disease-associated large genomic regions of copy-number variants (CNVs) is challenging. Here, by targeted sequencing of genes within schizophrenia (SZ)-associated CNVs in 1,779 SZ cases and 1,418 controls, we identified three rare putative loss-of-function (LoF) mutations in OTU deubiquitinase 7A (OTUD7A) within the 15q13.3 deletion in cases but none in controls. To tie OTUD7A LoF with any SZ-relevant cellular phenotypes, we modeled the OTUD7A LoF mutation, rs757148409, in human induced pluripotent stem cell (hiPSC)-derived induced excitatory neurons (iNs) by CRISPR-Cas9 engineering. The mutant iNs showed a ∼50% decrease in OTUD7A expression without undergoing nonsense-mediated mRNA decay. The mutant iNs also exhibited marked reduction of dendritic complexity, density of synaptic proteins GluA1 and PSD-95, and neuronal network activity. Congruent with the neuronal phenotypes in mutant iNs, our transcriptomic analysis showed that the set of OTUD7A LoF-downregulated genes was enriched for those relating to synapse development and function and was associated with SZ and other neuropsychiatric disorders. These results suggest that OTUD7A LoF impairs synapse development and neuronal function in human neurons, providing mechanistic insight into the possible role of OTUD7A in driving neuropsychiatric phenotypes associated with the 15q13.3 deletion.

The 22q11.2 region regulates presynaptic gene-products linked to schizophrenia

It is unclear how the 22q11.2 deletion predisposes to psychiatric disease. To study this, we generated induced pluripotent stem cells from deletion carriers and controls and utilized CRISPR/Cas9 to introduce the heterozygous deletion into a control cell line. Here, we show that upon differentiation into neural progenitor cells, the deletion acted in trans to alter the abundance of transcripts associated with risk for neurodevelopmental disorders including autism. In excitatory neurons, altered transcripts encoded presynaptic factors and were associated with genetic risk for schizophrenia, including common and rare variants. To understand how the deletion contributed to these changes, we defined the minimal protein-protein interaction network that best explains gene expression alterations. We found that many genes in 22q11.2 interact in presynaptic, proteasome, and JUN/FOS transcriptional pathways. Our findings suggest that the 22q11.2 deletion impacts genes that may converge with psychiatric risk loci to influence disease manifestation in each deletion carrier.

Structural Variation at a Disease Mutation Hotspot: Strategies to Investigate Gene Regulation and the 3D Genome

A rare form of X-linked Charcot-Marie-Tooth neuropathy, CMTX3, is caused by an interchromosomal insertion occurring at chromosome Xq27.1. Interestingly, eight other disease phenotypes have been associated with insertions (or insertion-deletions) occurring at the same genetic locus. To date, the pathogenic mechanism underlying most of these diseases remains unsolved, although local gene dysregulation has clearly been implicated in at least two phenotypes. The challenges of accessing disease-relevant tissue and modelling these complex genomic rearrangements has led to this research impasse. We argue that recent technological advancements can overcome many of these challenges, particularly induced pluripotent stem cells (iPSC) and their capacity to provide access to patient-derived disease-relevant tissue. However, to date these valuable tools have not been utilized to investigate the disease-associated insertions at chromosome Xq27.1. Therefore, using CMTX3 as a reference disease, we propose an experimental approach that can be used to explore these complex mutations, as well as similar structural variants located elsewhere in the genome. The mutational hotspot at Xq27.1 is a valuable disease paradigm with the potential to improve our understanding of the pathogenic consequences of complex structural variation, and more broadly, refine our knowledge of the multifaceted process of long-range gene regulation. Intergenic structural variation is a critically understudied class of mutation, although it is likely to contribute significantly to unsolved genetic disease.

Deciphering the Retinal Epigenome during Development, Disease and Reprogramming: Advancements, Challenges and Perspectives

Retinal neurogenesis is driven by concerted actions of transcription factors, some of which are expressed in a continuum and across several cell subtypes throughout development. While seemingly redundant, many factors diversify their regulatory outcome on gene expression, by coordinating variations in chromatin landscapes to drive divergent retinal specification programs. Recent studies have furthered the understanding of the epigenetic contribution to the progression of age-related macular degeneration, a leading cause of blindness in the elderly. The knowledge of the epigenomic mechanisms that control the acquisition and stabilization of retinal cell fates and are evoked upon damage, holds the potential for the treatment of retinal degeneration. Herein, this review presents the state-of-the-art approaches to investigate the retinal epigenome during development, disease, and reprogramming. A pipeline is then reviewed to functionally interrogate the epigenetic and transcriptional networks underlying cell fate specification, relying on a truly unbiased screening of open chromatin states. The related work proposes an inferential model to identify gene regulatory networks, features the first footprinting analysis and the first tentative, systematic query of candidate pioneer factors in the retina ever conducted in any model organism, leading to the identification of previously uncharacterized master regulators of retinal cell identity, such as the nuclear factor I, NFI. This pipeline is virtually applicable to the study of genetic programs and candidate pioneer factors in any developmental context. Finally, challenges and limitations intrinsic to the current next-generation sequencing techniques are discussed, as well as recent advances in super-resolution imaging, enabling spatio-temporal resolution of the genome.

Meta-analysis of transcriptional regulatory networks for lipid metabolism in neural cells from schizophrenia patients based on an open-source intelligence approach

There have been a number of reports about the transcriptional regulatory networks in schizophrenia. However, most of these studies were based on a specific transcription factor or a single dataset, an approach that is inadequate to understand the diverse etiology and underlying common characteristics of schizophrenia. Here we reconstructed and compared the transcriptional regulatory network for lipid metabolism enzymes using 15 public transcriptome datasets of neural cells from schizophrenia patients. Since many of the well-known schizophrenia-related SNPs are in enhancers, we reconstructed a network including enhancer-dependent regulation and found that 53.3 % of the total number of edges (7,577 pairs) involved regulation via enhancers. By examining multiple datasets, we found common and unique transcriptional modes of regulation. Furthermore, enrichment analysis of SNPs that were connected with genes in the transcriptional regulatory networks by eQTL suggested an association with hematological cell counts and some other traits/diseases, whose relationship to schizophrenia was either not or insufficiently reported in previous studies. Based on these results, we suggest that in future studies on schizophrenia, information on genotype, comorbidities and hematological cell counts should be included, along with the transcriptome, for a more detailed genetic stratification and mechanistic exploration of schizophrenia.

Integration of genetic, transcriptomic, and clinical data provides insight into 16p11.2 and 22q11.2 CNV genes

BACKGROUND

Deletions and duplications of the multigenic 16p11.2 and 22q11.2 copy number variant (CNV) regions are associated with brain-related disorders including schizophrenia, intellectual disability, obesity, bipolar disorder, and autism spectrum disorder (ASD). The contribution of individual CNV genes to each of these identified phenotypes is unknown, as well as the contribution of these CNV genes to other potentially subtler health implications for carriers. Hypothesizing that DNA copy number exerts most effects via impacts on RNA expression, we attempted a novel in silico fine-mapping approach in non-CNV carriers using both GWAS and biobank data.

METHODS

We first asked whether gene expression level in any individual gene in the CNV region alters risk for a known CNV-associated behavioral phenotype(s). Using transcriptomic imputation, we performed association testing for CNV genes within large genotyped cohorts for schizophrenia, IQ, BMI, bipolar disorder, and ASD. Second, we used a biobank containing electronic health data to compare the medical phenome of CNV carriers to controls within 700,000 individuals in order to investigate the full spectrum of health effects of the CNVs. Third, we used genotypes for over 48,000 individuals within the biobank to perform phenome-wide association studies between imputed expressions of individual 16p11.2 and 22q11.2 genes and over 1500 health traits.

RESULTS

Using large genotyped cohorts, we found individual genes within 16p11.2 associated with schizophrenia (TMEM219, INO80E, YPEL3), BMI (TMEM219, SPN, TAOK2, INO80E), and IQ (SPN), using conditional analysis to identify upregulation of INO80E as the driver of schizophrenia, and downregulation of SPN and INO80E as increasing BMI. We identified both novel and previously observed over-represented traits within the electronic health records of 16p11.2 and 22q11.2 CNV carriers. In the phenome-wide association study, we found seventeen significant gene-trait pairs, including psychosis (NPIPB11, SLX1B) and mood disorders (SCARF2), and overall enrichment of mental traits.

CONCLUSIONS

Our results demonstrate how integration of genetic and clinical data aids in understanding CNV gene function and implicates pleiotropy and multigenicity in CNV biology.

Combinatorial patterns of gene expression changes contribute to variable expressivity of the developmental delay-associated 16p12.1 deletion

BACKGROUND

Recent studies have suggested that individual variants do not sufficiently explain the variable expressivity of phenotypes observed in complex disorders. For example, the 16p12.1 deletion is associated with developmental delay and neuropsychiatric features in affected individuals, but is inherited in > 90% of cases from a mildly-affected parent. While children with the deletion are more likely to carry additional "second-hit" variants than their parents, the mechanisms for how these variants contribute to phenotypic variability are unknown.

METHODS

We performed detailed clinical assessments, whole-genome sequencing, and RNA sequencing of lymphoblastoid cell lines for 32 individuals in five large families with multiple members carrying the 16p12.1 deletion. We identified contributions of the 16p12.1 deletion and "second-hit" variants towards a range of expression changes in deletion carriers and their family members, including differential expression, outlier expression, alternative splicing, allele-specific expression, and expression quantitative trait loci analyses.

RESULTS

We found that the deletion dysregulates multiple autism and brain development genes such as FOXP1, ANK3, and MEF2. Carrier children also showed an average of 5323 gene expression changes compared with one or both parents, which matched with 33/39 observed developmental phenotypes. We identified significant enrichments for 13/25 classes of "second-hit" variants in genes with expression changes, where 4/25 variant classes were only enriched when inherited from the noncarrier parent, including loss-of-function SNVs and large duplications. In 11 instances, including for ZEB2 and SYNJ1, gene expression was synergistically altered by both the deletion and inherited "second-hits" in carrier children. Finally, brain-specific interaction network analysis showed strong connectivity between genes carrying "second-hits" and genes with transcriptome alterations in deletion carriers.

CONCLUSIONS

Our results suggest a potential mechanism for how "second-hit" variants modulate expressivity of complex disorders such as the 16p12.1 deletion through transcriptomic perturbation of gene networks important for early development. Our work further shows that family-based assessments of transcriptome data are highly relevant towards understanding the genetic mechanisms associated with complex disorders.

Spatial genome architecture and the emergence of malignancy

Human chromosomes are large spatially and hierarchically structured entities, the integrity of which needs to be preserved throughout the lifespan of the cell and in conjunction with cell cycle progression. Preservation of chromosomal structure is important for proper deployment of cell type-specific gene expression programs. Thus, aberrations in the integrity and structure of chromosomes will predictably lead to disease, including cancer. Here, we provide an updated standpoint with respect to chromatin misfolding and the emergence of various cancer types. We discuss recent studies implicating the disruption of topologically associating domains, switching between active and inactive compartments, rewiring of promoter-enhancer interactions in malignancy as well as the effects of single nucleotide polymorphisms in non-coding regions involved in long-range regulatory interactions. In light of these findings, we argue that chromosome conformation studies may now also be useful for patient diagnosis and drug target discovery.

Chromatin Modifications in 22q11.2 Deletion Syndrome

PURPOSE

Chromosome 22q11.2 deletion syndrome is a common inborn error of immunity. The early consequences of thymic hypoplasia are low T cell numbers. Later in life, atopy, autoimmunity, inflammation, and evolving hypogammaglobulinemia can occur and the causes of these features are not understood. This study utilized an unbiased discovery approach to define alterations in histone modifications. Our goal was to identify durable chromatin changes that could influence cell behavior.

METHODS

CD4 T cells and CD19 B cells underwent ChIP-seq analysis using antibodies to H3K4me3, H3K27ac, and H4ac. RNA effects were defined in CD4 T cells by RNA-seq. Serum cytokines were examined by Luminex.

RESULTS

Histone marks of transcriptional activation at CD4 T cell promoters and enhancers were globally increased. The promoter activation signature had elements related to T cell activation and inflammation, concordant with effects seen in the transcriptome. B cells, in contrast, had a minimally altered epigenetic landscape in 22q11.2. Both cell types had an "edge" effect with markedly altered chromatin adjacent to the deletion.

CONCLUSIONS

People with 22q11.2 deletion have altered CD4 T cell chromatin and a transcriptome concordant with the changes in the epigenome. These effects support a disease model where qualitative changes to T cells occur in addition to quantitative defects that have been well characterized. This study offers unique insight into qualitative differences in the T cells in 22q11.2 deletion, an aspect that has received limited attention.

Structural Variations of the 3D Genome Architecture in Cervical Cancer Development

Human papillomavirus (HPV) integration is the major contributor to cervical cancer (CC) development by inducing structural variations (SVs) in the human genome. SVs are directly associated with the three-dimensional (3D) genome structure leading to cancer development. The detection of SVs is not a trivial task, and several genome-wide techniques have greatly helped in the identification of SVs in the cancerous genome. However, in cervical cancer, precise prediction of SVs mainly translocations and their effects on 3D-genome and gene expression still need to be explored. Here, we have used high-throughput chromosome conformation capture (Hi-C) data of cervical cancer to detect the SVs, especially the translocations, and validated it through whole-genome sequencing (WGS) data. We found that the cervical cancer 3D-genome architecture rearranges itself as compared to that in the normal tissue, and 24% of the total genome switches their A/B compartments. Moreover, translocation detection from Hi-C data showed the presence of high-resolution t(4;7) (q13.1; q31.32) and t(1;16) (q21.2; q22.1) translocations, which disrupted the expression of the genes located at and nearby positions. Enrichment analysis suggested that the disrupted genes were mainly involved in controlling cervical cancer-related pathways. In summary, we detect the novel SVs through Hi-C data and unfold the association among genome-reorganization, translocations, and gene expression regulation. The results help understand the underlying pathogenicity mechanism of SVs in cervical cancer development and identify the targeted therapeutics against cervical cancer.

Three-dimensional genome organization in the central nervous system, implications for neuropsychological disorders

Chromosomes in eukaryotic cell nuclei are highly compacted and finely organized into hierarchical three-dimensional (3D) configuration. In recent years, scientists have gained deeper understandings of 3D genome structures and revealed novel evidence linking 3D genome organization to various important cell events on the molecular level. Most importantly, alteration of 3D genome architecture has emerged as an intriguing higher order mechanism that connects disease-related genetic variants in multiple heterogenous and polygenic neuropsychological disorders, delivering novel insights into the etiology. In this review, we provide a brief overview of the hierarchical structures of 3D genome and two proposed regulatory models, loop extrusion and phase separation. We then focus on recent Hi-C data in the central nervous system and discuss 3D genome alterations during normal brain development and in mature neurons. Most importantly, we make a comprehensive review on current knowledge and discuss the role of 3D genome in multiple neuropsychological disorders, including schizophrenia, repeat expansion disorders, 22q11 deletion syndrome, and others.

Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning

Over the past years, large consortia have been established to fuel the sequencing of whole genomes of many cancer patients. Despite the increased abundance in tools to study the impact of SNVs, non-coding SVs have been largely ignored in these data. Here, we introduce svMIL2, an improved version of our Multiple Instance Learning-based method to study the effect of somatic non-coding SVs disrupting boundaries of TADs and CTCF loops in 1646 cancer genomes. We demonstrate that svMIL2 predicts pathogenic non-coding SVs with an average AUC of 0.86 across 12 cancer types, and identifies non-coding SVs affecting well-known driver genes. The disruption of active (super) enhancers in open chromatin regions appears to be a common mechanism by which non-coding SVs exert their pathogenicity. Finally, our results reveal that the contribution of pathogenic non-coding SVs as opposed to driver SNVs may highly vary between cancers, with notably high numbers of genes being disrupted by pathogenic non-coding SVs in ovarian and pancreatic cancer. Taken together, our machine learning method offers a potent way to prioritize putatively pathogenic non-coding SVs and leverage non-coding SVs to identify driver genes. Moreover, our analysis of 1646 cancer genomes demonstrates the importance of including non-coding SVs in cancer diagnostics.

DSCAM/PAK1 pathway suppression reverses neurogenesis deficits in iPSC-derived cerebral organoids from patients with Down syndrome

Down syndrome (DS), caused by trisomy of chromosome 21, occurs in 1 of every 800 live births. Early defects in cortical development likely account for the cognitive impairments in DS, although the underlying molecular mechanism remains elusive. Here, we performed histological assays and unbiased single-cell RNA-Seq (scRNA-Seq) analysis on cerebral organoids derived from 4 euploid cell lines and from induced pluripotent stem cells (iPSCs) from 3 individuals with trisomy 21 to explore cell-type-specific abnormalities associated with DS during early brain development. We found that neurogenesis was significantly affected, given the diminished proliferation and decreased expression of layer II and IV markers in cortical neurons in the subcortical regions; this may have been responsible for the reduced size of the organoids. Furthermore, suppression of the DSCAM/PAK1 pathway, which showed enhanced activity in DS, using CRISPR/Cas9, CRISPR interference (CRISPRi), or small-molecule inhibitor treatment reversed abnormal neurogenesis, thereby increasing the size of organoids derived from DS iPSCs. Our study demonstrates that 3D cortical organoids developed in vitro are a valuable model of DS and provide a direct link between dysregulation of the DSCAM/PAK1 pathway and developmental brain defects in DS.

Insulator foci distance correlates with cellular and nuclear morphology in early Drosophila embryos

The three-dimensional (3D) organization of the genome is highly dynamic, changing during development and varying across different tissues and cell types. Recent studies indicate that these changes alter regulatory interactions, leading to changes in gene expression. Despite its importance, the mechanisms that influence genomic organization remain poorly understood. We have previously identified a network of chromatin boundary elements, or insulators, in the Drosophila Antennapedia homeotic complex (ANT-C). These genomic elements interact with one another to tether chromatin loops that could block or promote enhancer-promoter interactions. To understand the function of these insulators, we assessed their interactions by measuring their 3D nuclear distance in developing animal tissues. Our data suggest that the ANT-C Hox complex might be in a folded or looped configuration rather than in a random or extended form. The architecture of the ANT-C complex, as read out by the pair-wise distance between insulators, undergoes a strong compression during late embryogenesis, coinciding with the reduction of cell and nuclear diameters due to continued cell divisions in post-cleavage cells. Our results suggest that genomic architecture and gene regulation may be influenced by cellular morphology and movement during development.

The hierarchical folding dynamics of topologically associating domains are closely related to transcriptional abnormalities in cancers

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The hierarchical levels of TAD boundaries were tissue- and cell type-specific.

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The TAD nesting level of genes in tumors is different from that in normal tissue.

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Hierarchical TAD level of genes is related to abnormal transcription and prognosis in cancers.

Recent studies have shown that the three-dimensional (3D) structure of chromatin is associated with cancer progression. However, the roles of the 3D genome structure and its dynamics in cancer remains largely unknown. In this study, we investigated hierarchical topologically associating domain (TAD) structures in cancers and defined a “TAD hierarchical score (TH score)” for genes, which allowed us to assess the TAD nesting level of all genes in a simplified way. We demonstrated that the TAD nesting levels of genes in a tumor differ from those in normal tissue. Furthermore, the hierarchical TAD level dynamics were related to transcriptional changes in cancer, and some of the genes in which the hierarchical level was altered were significantly related to the prognosis of cancer patients. Overall, the results of this study suggest that the folding dynamics of TADs are closely related to transcriptional abnormalities in cancers, emphasizing that the function of hierarchical chromatin organization goes beyond simple chromatin packaging efficiency.

svMIL: predicting the pathogenic effect of TAD boundary-disrupting somatic structural variants through multiple instance learning

Motivation

Despite the fact that structural variants (SVs) play an important role in cancer, methods to predict their effect, especially for SVs in non-coding regions, are lacking, leaving them often overlooked in the clinic. Non-coding SVs may disrupt the boundaries of Topologically Associated Domains (TADs), thereby affecting interactions between genes and regulatory elements such as enhancers. However, it is not known when such alterations are pathogenic. Although machine learning techniques are a promising solution to answer this question, representing the large number of interactions that an SV can disrupt in a single feature matrix is not trivial.

Results

We introduce svMIL: a method to predict pathogenic TAD boundary-disrupting SV effects based on multiple instance learning, which circumvents the need for a traditional feature matrix by grouping SVs into bags that can contain any number of disruptions. We demonstrate that svMIL can predict SV pathogenicity, measured through same-sample gene expression aberration, for various cancer types. In addition, our approach reveals that somatic pathogenic SVs alter different regulatory interactions than somatic non-pathogenic SVs and germline SVs.

Availability and implementation

All code for svMIL is publicly available on GitHub: https://github.com/UMCUGenetics/svMIL.

Supplementary information

Supplementary data are available at Bioinformatics online.

Inferring chromosome radial organization from Hi-C data

BACKGROUND

The nonrandom radial organization of eukaryotic chromosome territories (CTs) inside the nucleus plays an important role in nuclear functional compartmentalization. Increasingly, chromosome conformation capture (Hi-C) based approaches are being used to characterize the genome structure of many cell types and conditions. Computational methods to extract 3D arrangements of CTs from this type of pairwise contact data will thus increase our ability to analyze CT organization in a wider variety of biological situations.

RESULTS

A number of full-scale polymer models have successfully reconstructed the 3D structure of chromosome territories from Hi-C. To supplement such methods, we explore alternative, direct, and less computationally intensive approaches to capture radial CT organization from Hi-C data. We show that we can infer relative chromosome ordering using PCA on a thresholded inter-chromosomal contact matrix. We simulate an ensemble of possible CT arrangements using a force-directed network layout algorithm and propose an approach to integrate additional chromosome properties into our predictions. Our CT radial organization predictions have a high correlation with microscopy imaging data for various cell nucleus geometries (lymphoblastoid, skin fibroblast, and breast epithelial cells), and we can capture previously documented changes in senescent and progeria cells.

CONCLUSIONS

Our analysis approaches provide rapid and modular approaches to screen for alterations in CT organization across widely available Hi-C data. We demonstrate which stages of the approach can extract meaningful information, and also describe limitations of pairwise contacts alone to predict absolute 3D positions.

Robust Hi-C Maps of Enhancer-Promoter Interactions Reveal the Function of Non-coding Genome in Neural Development and Diseases

Genome-wide mapping of chromatin interactions at high resolution remains experimentally and computationally challenging. Here we used a low-input "easy Hi-C" protocol to map the 3D genome architecture in human neurogenesis and brain tissues and also demonstrated that a rigorous Hi-C bias-correction pipeline (HiCorr) can significantly improve the sensitivity and robustness of Hi-C loop identification at sub-TAD level, especially the enhancer-promoter (E-P) interactions. We used HiCorr to compare the high-resolution maps of chromatin interactions from 10 tissue or cell types with a focus on neurogenesis and brain tissues. We found that dynamic chromatin loops are better hallmarks for cellular differentiation than compartment switching. HiCorr allowed direct observation of cell-type- and differentiation-specific E-P aggregates spanning large neighborhoods, suggesting a mechanism that stabilizes enhancer contacts during development. Interestingly, we concluded that Hi-C loop outperforms eQTL in explaining neurological GWAS results, revealing a unique value of high-resolution 3D genome maps in elucidating the disease etiology.

Copy number variants (CNVs): a powerful tool for iPSC-based modelling of ASD

Patients diagnosed with chromosome microdeletions or duplications, known as copy number variants (CNVs), present a unique opportunity to investigate the relationship between patient genotype and cell phenotype. CNVs have high genetic penetrance and give a good correlation between gene locus and patient clinical phenotype. This is especially effective for the study of patients with neurodevelopmental disorders (NDD), including those falling within the autism spectrum disorders (ASD). A key question is whether this correlation between genetics and clinical presentation at the level of the patient can be translated to the cell phenotypes arising from the neurodevelopment of patient induced pluripotent stem cells (iPSCs).Here, we examine how iPSCs derived from ASD patients with an associated CNV inform our understanding of the genetic and biological mechanisms underlying the aetiology of ASD. We consider selection of genetically characterised patient iPSCs; use of appropriate control lines; aspects of human neurocellular biology that can capture in vitro the patient clinical phenotype; and current limitations of patient iPSC-based studies. Finally, we consider how future research may be enhanced to maximise the utility of CNV patients for research of pathological mechanisms or therapeutic targets.

Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective

Genome-wide association studies (GWAS) have been performed for many psychiatric disorders and revealed a complex polygenic architecture linking mental and physical health phenotypes. Psychiatric diagnoses are often heterogeneous, and several layers of trait heterogeneity may contribute to detection of genetic risks per disorder or across multiple disorders. In this review, we discuss these heterogeneities and their consequences on the discovery of risk loci using large-scale genetic data. We primarily highlight the ways in which sex and diagnostic complexity contribute to risk locus discovery in schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, autism spectrum disorder, posttraumatic stress disorder, major depressive disorder, obsessive-compulsive disorder, Tourette’s syndrome and chronic tic disorder, anxiety disorders, suicidality, feeding and eating disorders, and substance use disorders. Genetic data also have facilitated discovery of clinically relevant subphenotypes also described here. Collectively, GWAS of psychiatric disorders revealed that the understanding of heterogeneity, polygenicity, and pleiotropy is critical to translate genetic findings into treatment strategies.

Using GARDEN-NET and ChAseR to explore human haematopoietic 3D chromatin interaction networks

We introduce an R package and a web-based visualization tool for the representation, analysis and integration of epigenomic data in the context of 3D chromatin interaction networks. GARDEN-NET allows for the projection of user-submitted genomic features on pre-loaded chromatin interaction networks, exploiting the functionalities of the ChAseR package to explore the features in combination with chromatin network topology properties. We demonstrate the approach using published epigenomic and chromatin structure datasets in haematopoietic cells, including a collection of gene expression, DNA methylation and histone modifications data in primary healthy myeloid cells from hundreds of individuals. These datasets allow us to test the robustness of chromatin assortativity, which highlights which epigenomic features, alone or in combination, are more strongly associated with 3D genome architecture. We find evidence for genomic regions with specific histone modifications, DNA methylation, and gene expression levels to be forming preferential contacts in 3D nuclear space, to a different extent depending on the cell type and lineage. Finally, we examine replication timing data and find it to be the genomic feature most strongly associated with overall 3D chromatin organization at multiple scales, consistent with previous results from the literature.

Structural variation in the sequencing era

Identifying structural variation (SV) is essential for genome interpretation but has been historically difficult due to limitations inherent to available genome technologies. Detection methods that use ensemble algorithms and emerging sequencing technologies have enabled the discovery of thousands of SVs, uncovering information about their ubiquity, relationship to disease and possible effects on biological mechanisms. Given the variability in SV type and size, along with unique detection biases of emerging genomic platforms, multiplatform discovery is necessary to resolve the full spectrum of variation. Here, we review modern approaches for investigating SVs and proffer that, moving forwards, studies integrating biological information with detection will be necessary to comprehensively understand the impact of SV in the human genome.

Modeling Down syndrome in animals from the early stage to the 4.0 models and next

The genotype-phenotype relationship and the physiopathology of Down Syndrome (DS) have been explored in the last 20 years with more and more relevant mouse models. From the early age of transgenesis to the new CRISPR/CAS9-derived chromosomal engineering and the transchromosomic technologies, mouse models have been key to identify homologous genes or entire regions homologous to the human chromosome 21 that are necessary or sufficient to induce DS features, to investigate the complexity of the genetic interactions that are involved in DS and to explore therapeutic strategies. In this review we report the new developments made, how genomic data and new genetic tools have deeply changed our way of making models, extended our panel of animal models, and increased our understanding of the neurobiology of the disease. But even if we have made an incredible progress which promises to make DS a curable condition, we are facing new research challenges to nurture our knowledge of DS pathophysiology as a neurodevelopmental disorder with many comorbidities during ageing.

TAD fusion score: discovery and ranking the contribution of deletions to genome structure

Deletions that fuse two adjacent topologically associating domains (TADs) can cause severe developmental disorders. We provide a formal method to quantify deletions based on their potential disruption of the three-dimensional genome structure, denoted as the TAD fusion score. Furthermore, we show that deletions that cause TAD fusion are rare and under negative selection in the general population. Finally, we show that our method correctly gives higher scores to deletions reported to cause various disorders, including developmental disorders and cancer, in comparison to the deletions reported in the 1000 Genomes Project. The TAD fusion score tool is publicly available at https://github.com/HormozdiariLab/TAD-fusion-score .

Downregulation of genes outside the deleted region in individuals with 22q11.2 deletion syndrome

The 22q11.2 deletion syndrome (22q11.2DS) is caused by recurrent hemizygous deletions of chromosome 22q11.2. The phenotype of the syndrome is complex and varies widely among individuals. Little is known about the role of the different genes located in 22q11.2, and we hypothesized that genetic risk factors lying elsewhere in the genome might contribute to the phenotype. Here, we present the whole-genome gene expression data of 11 patients with approximately 3 Mb deletions. Apart from the hemizygous genes mapped to the 22q11.2 region, the TUBA8 and GNAZ genes, neighboring the deleted interval but in normal copy number, showed altered expression. When genes mapped to other chromosomes were considered in the gene expression analysis, a genome-wide dysregulation was observed, with increased or decreased expression levels. The enriched pathways of these genes were related to immune response, a deficiency that is frequently observed in 22q11.2DS patients. We also used the hypothesis-free weighted gene co-expression network analysis (WGCNA), which revealed the co-expression gene network modules with clear connection to mechanisms associated with 22q11.2DS such as immune response and schizophrenia. These findings, combined with the traditional gene expression profile, can be used for the identification of potential pathways and genes not previously considered to be related to the 22q11.2 deletion syndrome.