Interpreting the impact of noncoding structural variation in neurodevelopmental disorders

Structural genomic variation and behavioral interactions underpin a balanced sexual mimicry polymorphism

How phenotypic diversity originates and persists within populations are classic puzzles in evolutionary biology. While balanced polymorphisms segregate within many species, it remains rare for both the genetic basis and the selective forces to be known, leading to an incomplete understanding of many classes of traits under balancing selection. Here, we uncover the genetic architecture of a balanced sexual mimicry polymorphism and identify behavioral mechanisms that may be involved in its maintenance in the swordtail fish Xiphophorus birchmanni. We find that ∼40% of X. birchmanni males develop a "false gravid spot," a melanic pigmentation pattern that mimics the "pregnancy spot" associated with sexual maturity in female live-bearing fish. Using genome-wide association mapping, we detect a single intergenic region associated with variation in the false gravid spot phenotype, which is upstream of kitlga, a melanophore patterning gene. By performing long-read sequencing within and across populations, we identify complex structural rearrangements between alternate alleles at this locus. The false gravid spot haplotype drives increased allele-specific expression of kitlga, which provides a mechanistic explanation for the increased melanophore abundance that causes the spot. By studying social interactions in the laboratory and in nature, we find that males with the false gravid spot experience less aggression; however, they also receive increased attention from other males and are disdained by females. These behavioral interactions may contribute to the maintenance of this phenotypic polymorphism in natural populations. We speculate that structural variants affecting gene regulation may be an underappreciated driver of balanced polymorphisms across diverse species.

Re-analysis of whole genome sequencing ends a diagnostic odyssey: Case report of an RNU4-2 related neurodevelopmental disorder

Despite increasing knowledge of disease-causing genes in human genetics, approximately half of the individuals affected by neurodevelopmental disorders remain genetically undiagnosed. Part of this missing heritability might be caused by genetic variants outside of protein-coding genes, which are not routinely diagnostically investigated. A recent preprint identified de novo variants in the non-coding spliceosomal snRNA gene RNU4-2 as a cause of a frequent novel syndromic neurodevelopmental disorder. Here we mined 164 whole genome sequencing (WGS) trios from individuals with neurodevelopmental or multiple congenital anomaly disorders that received diagnostic genomic investigations at our clinic. We identify a recurrent de novo RNU4-2 variant (NR_003137.2(RNU4-2):n.64_65insT) in a 5-year-old girl with severe global developmental delay, hypotonia, microcephaly, and seizures that likely explains her phenotype, given that extensive previous genetic investigations failed to identify an alternative cause. We present detailed phenotyping of the individual obtained during a 5-year follow-up. This includes photographs showing recognizable facial features for this novel disorder, which might allow prioritizing other currently unexplained affected individuals sharing similar facial features for targeted investigations of RNU4-2. This case illustrates the power of re-analysis to solve previously unexplained cases even when a diagnostic genome remains negative.

Facing the challenges to shorten the diagnostic odyssey: first Whole Genome Sequencing experience of a Colombian cohort with suspected rare diseases

Exome and genome sequencing (ES/GS) are routinely used for the diagnosis of genetic diseases in developed countries. However, their implementation is limited in countries from Latin America. We aimed to describe the results of GS in patients with suspected rare genetic diseases in Colombia. We studied 501 patients from 22 healthcare sites from January to December 2022. GS was performed in the index cases using dried blood spots on filtercards. Ancestry analysis was performed under iAdmix. Multiomic testing was performed when needed (biomarker, enzymatic activity, RNA-seq). All tests were performed at an accredited genetic laboratory. Ethnicity prediction data confirmed that 401 patients (80%) were mainly of Amerindian origin. A genetic diagnosis was established for 142 patients with a 28.3% diagnostic yield. The highest diagnostic yield was achieved for pathologies with a metabolic component and syndromic disorders (p < 0.001). Young children had a median of 1 year of diagnostic odyssey, while the median time for adults was significantly longer (15 years). Patients with genetic syndromes have spent more than 75% of their life without a diagnosis, while for patients with neurologic and neuromuscular diseases, the time of the diagnostic odyssey tended to decrease with age. Previous testing, specifically karyotyping or chromosomal microarray were significantly associated with a longer time to reach a definitive diagnosis (p < 0.01). Furthermore, one out of five patients that had an ES before could be diagnosed by GS. The Colombian genome project is the first Latin American study reporting the experience of systematic use of diagnostic GS in rare diseases.

Potential clinical applications of advanced genomic analysis in cerebral palsy

Cerebral palsy (CP) has historically been attributed to acquired insults, but emerging research suggests that genetic variations are also important causes of CP. While microarray and whole-exome sequencing based studies have been the primary methods for establishing new CP-gene relationships and providing a genetic etiology for individual patients, the cause of their condition remains unknown for many patients with CP. Recent advancements in genomic technologies offer additional opportunities to uncover variations in human genomes, transcriptomes, and epigenomes that have previously escaped detection. In this review, we outline the use of these state-of-the-art technologies to address the molecular diagnostic challenges experienced by individuals with CP. We also explore the importance of identifying a molecular etiology whenever possible, given the potential for genomic medicine to provide opportunities to treat patients with CP in new and more precise ways.

A de novo ARIH2 gene mutation was detected in a patient with autism spectrum disorders and intellectual disability

E3 ubiquitin protein ligase encoded by ARIH2 gene catalyses the ubiquitination of target proteins and plays a crucial role in posttranslational modifications across various cellular processes. As prior documented, mutations in genes involved in the ubiquitination process are often associated with autism spectrum disorder (ASD) and/or intellectual disability (ID). In the current study, a de novo heterozygous mutation was identified in the splicing intronic region adjacent to the last exon of the ARIH2 gene using whole exome sequencing (WES). We hypothesize that this mutation, found in an ASD/ID patient, disrupts the protein Ariadne domain which is involved in the autoinhibition of ARIH2 enzyme. Predictive analyses elucidated the implications of the novel mutation in the splicing process and confirmed its autosomal dominant inheritance model. Nevertheless, we cannot exclude the possibility that other genetic factors, undetectable by WES, such as mutations in non-coding regions and polygenic risk in inter-allelic complementation, may contribute to the patient's phenotype. This work aims to suggest potential relationship between the detected mutation in ARIH2 gene and both ASD and ID, even though functional studies combined with new sequencing approaches will be necessary to validate this hypothesis.

Chromosomal structural rearrangements implicate long non-coding RNAs in rare germline disorders

In recent years, there has been increased focus on exploring the role the non-protein-coding genome plays in Mendelian disorders. One class of particular interest is long non-coding RNAs (lncRNAs), which has recently been implicated in the regulation of diverse molecular processes. However, because lncRNAs do not encode protein, there is uncertainty regarding what constitutes a pathogenic lncRNA variant, and thus annotating such elements is challenging. The Developmental Genome Anatomy Project (DGAP) and similar projects recruit individuals with apparently balanced chromosomal abnormalities (BCAs) that disrupt or dysregulate genes in order to annotate the human genome. We hypothesized that rearrangements disrupting lncRNAs could be the underlying genetic etiology for the phenotypes of a subset of these individuals. Thus, we assessed 279 cases with BCAs and selected 191 cases with simple BCAs (breakpoints at only two genomic locations) for further analysis of lncRNA disruptions. From these, we identified 66 cases in which the chromosomal rearrangements directly disrupt lncRNAs. In 30 cases, no genes of any other class aside from lncRNAs are directly disrupted, consistent with the hypothesis that lncRNA disruptions could underly the phenotypes of these individuals. Strikingly, the lncRNAs MEF2C-AS1 and ENSG00000257522 are each disrupted in two unrelated cases. Furthermore, we experimentally tested the lncRNAs TBX2-AS1 and MEF2C-AS1 and found that knockdown of these lncRNAs resulted in decreased expression of the neighboring transcription factors TBX2 and MEF2C, respectively. To showcase the power of this genomic approach for annotating lncRNAs, here we focus on clinical reports and genetic analysis of seven individuals with likely developmental etiologies due to lncRNA disruptions.

Mapping enhancer and chromatin accessibility landscapes charts the regulatory network of Alzheimer's disease

BACKGROUND

Enhancers are regulatory elements that target and modulate gene expression and play a role in human health and disease. However, the roles of enhancer regulatory circuit abnormalities driven by epigenetic alterations in Alzheimer's disease (AD) are unclear.

METHODS

In this study, a multiomic integrative analysis was performed to map enhancer and chromatin accessibility landscapes and identify regulatory network abnormalities in AD. We identified differentially methylated enhancers and constructed regulatory networks across brain regions using AD brain tissue samples. Through the integration of snATAC-seq and snRNA-seq datasets, we mapped enhancers with DNA methylation alterations (DMA) and chromatin accessibility landscapes. Core regulatory triplets that contributed to AD neuropathology in specific cell types were further prioritized.

RESULTS

We revealed widespread DNA methylation alterations (DMA) in the enhancers of AD patients across different brain regions. In addition, the genome-wide transcription factor (TF) binding profiles showed that enhancers with DMA are pervasively regulated by TFs. The TF-enhancer-gene regulatory network analysis identified core regulatory triplets that are associated with brain and immune cell proportions and play important roles in AD pathogenesis. Enhancer regulatory circuits with DMA exhibited distinct chromatin accessibility patterns, which were further characterized at single-cell resolutions.

CONCLUSIONS

Our study comprehensively investigated DNA methylation-mediated regulatory circuit abnormalities and provided novel insights into the potential pathogenesis of AD.

Methods of Detection and Mechanisms of Origin of Complex Structural Genome Variations

Based on classical karyotyping, structural genome variations (SVs) have generally been considered to be either "simple" (with one or two breakpoints) or "complex" (with more than two breakpoints). Studying the breakpoints of SVs at nucleotide resolution revealed additional, subtle structural variations, such that even "simple" SVs turned out to be "complex." Genome-wide sequencing methods, such as fosmid and paired-end mapping, short-read and long-read whole genome sequencing, and single-molecule optical mapping, also indicated that the number of SVs per individual was considerably larger than expected from karyotyping and high-resolution chromosomal array-based studies. Interestingly, SVs were detected in studies of cohorts of individuals without clinical phenotypes. The common denominator of all SVs appears to be a failure to accurately repair DNA double-strand breaks (DSBs) or to halt cell cycle progression if DSBs persist. This review discusses the various DSB response mechanisms during the mitotic cell cycle and during meiosis and their regulation. Emphasis is given to the molecular mechanisms involved in the formation of translocations, deletions, duplications, and inversions during or shortly after meiosis I. Recently, CRISPR-Cas9 studies have provided unexpected insights into the formation of translocations and chromothripsis by both breakage-fusion-bridge and micronucleus-dependent mechanisms.

Solving the unsolved genetic epilepsies: Current and future perspectives

Many patients with epilepsy undergo exome or genome sequencing as part of a diagnostic workup; however, many remain genetically unsolved. There are various factors that account for negative results in exome/genome sequencing for patients with epilepsy: (1) the underlying cause is not genetic; (2) there is a complex polygenic explanation; (3) the illness is monogenic but the causative gene remains to be linked to a human disorder; (4) family segregation with reduced penetrance; (5) somatic mosaicism or the complexity of, for example, a structural rearrangement; or (6) limited knowledge or diagnostic tools that hinder the proper classification of a variant, resulting in its designation as a variant of unknown significance. The objective of this review is to outline some of the diagnostic options that lie beyond the exome/genome, and that might become clinically relevant within the foreseeable future. These options include: (1) re-analysis of older exome/genome data as knowledge increases or symptoms change; (2) looking for somatic mosaicism or long-read sequencing to detect low-complexity repeat variants or specific structural variants missed by traditional exome/genome sequencing; (3) exploration of the non-coding genome including disruption of topologically associated domains, long range non-coding RNA, or other regulatory elements; and finally (4) transcriptomics, DNA methylation signatures, and metabolomics as complementary diagnostic methods that may be used in the assessment of variants of unknown significance. Some of these tools are currently not integrated into standard diagnostic workup. However, it is reasonable to expect that they will become increasingly available and improve current diagnostic capabilities, thereby enabling precision diagnosis in patients who are currently undiagnosed.

PhenoSV: interpretable phenotype-aware model for the prioritization of genes affected by structural variants

Structural variants (SVs) represent a major source of genetic variation associated with phenotypic diversity and disease susceptibility. While long-read sequencing can discover over 20,000 SVs per human genome, interpreting their functional consequences remains challenging. Existing methods for identifying disease-related SVs focus on deletion/duplication only and cannot prioritize individual genes affected by SVs, especially for noncoding SVs. Here, we introduce PhenoSV, a phenotype-aware machine-learning model that interprets all major types of SVs and genes affected. PhenoSV segments and annotates SVs with diverse genomic features and employs a transformer-based architecture to predict their impacts under a multiple-instance learning framework. With phenotype information, PhenoSV further utilizes gene-phenotype associations to prioritize phenotype-related SVs. Evaluation on extensive human SV datasets covering all SV types demonstrates PhenoSV's superior performance over competing methods. Applications in diseases suggest that PhenoSV can determine disease-related genes from SVs. A web server and a command-line tool for PhenoSV are available at https://phenosv.wglab.org .

Identification of a robust DNA methylation signature for Fanconi anemia

Fanconi anemia (FA) is a clinically variable and genetically heterogeneous cancer-predisposing disorder representing the most common bone marrow failure syndrome. It is caused by inactivating predominantly biallelic mutations involving >20 genes encoding proteins with roles in the FA/BRCA DNA repair pathway. Molecular diagnosis of FA is challenging due to the wide spectrum of the contributing gene mutations and structural rearrangements. The assessment of chromosomal fragility after exposure to DNA cross-linking agents is generally required to definitively confirm diagnosis. We assessed peripheral blood genome-wide DNA methylation (DNAm) profiles in 25 subjects with molecularly confirmed clinical diagnosis of FA (FANCA complementation group) using Illumina's Infinium EPIC array. We identified 82 differentially methylated CpG sites that allow to distinguish subjects with FA from healthy individuals and subjects with other genetic disorders, defining an FA-specific DNAm signature. The episignature was validated using a second cohort of subjects with FA involving different complementation groups, documenting broader genetic sensitivity and demonstrating its specificity using the EpiSign Knowledge Database. The episignature properly classified DNA samples obtained from bone marrow aspirates, demonstrating robustness. Using the selected probes, we trained a machine-learning model able to classify EPIC DNAm profiles in molecularly unsolved cases. Finally, we show that the generated episignature includes CpG sites that do not undergo functional selective pressure, allowing diagnosis of FA in individuals with reverted phenotype due to gene conversion. These findings provide a tool to accelerate diagnostic testing in FA and broaden the clinical utility of DNAm profiling in the diagnostic setting.

Reappraisal of the Concept of Accelerated Aging in Neurodegeneration and Beyond

BACKGROUND

Genetic and epigenetic changes, oxidative stress and inflammation influence the rate of aging, which diseases, lifestyle and environmental factors can further accelerate. In accelerated aging (AA), the biological age exceeds the chronological age.

OBJECTIVE

The objective of this study is to reappraise the AA concept critically, considering its weaknesses and limitations.

METHODS

We reviewed more than 300 recent articles dealing with the physiology of brain aging and neurodegeneration pathophysiology.

RESULTS

(1) Application of the AA concept to individual organs outside the brain is challenging as organs of different systems age at different rates. (2) There is a need to consider the deceleration of aging due to the potential use of the individual structure-functional reserves. The latter can be restored by pharmacological and/or cognitive therapy, environment, etc. (3) The AA concept lacks both standardised terminology and methodology. (4) Changes in specific molecular biomarkers (MBM) reflect aging-related processes; however, numerous MBM candidates should be validated to consolidate the AA theory. (5) The exact nature of many potential causal factors, biological outcomes and interactions between the former and the latter remain largely unclear.

CONCLUSIONS

Although AA is commonly recognised as a perspective theory, it still suffers from a number of gaps and limitations that assume the necessity for an updated AA concept.

Structural variation of the coding and non-coding human pharmacogenome

Genetic variants in drug targets and genes encoding factors involved in drug absorption, distribution, metabolism and excretion (ADME) can have pronounced impacts on drug pharmacokinetics, response, and toxicity. While the landscape of genetic variability at the level of single nucleotide variants (SNVs) has been extensively studied in these pharmacogenetic loci, their structural variation is only poorly understood. Thus, we systematically analyzed the genetic structural variability across 908 pharmacogenes (344 ADME genes and 564 drug targets) based on publicly available whole genome sequencing data from 10,847 unrelated individuals. Overall, we extracted 14,984 distinct structural variants (SVs) ranging in size from 50 bp to 106 Mb. Each individual harbored on average 10.3 and 1.5 SVs with putative functional effects that affected the coding regions of ADME genes and drug targets, respectively. In addition, by cross-referencing pharmacogenomic SVs with experimentally determined binding data of 224 transcription factors across 130 cell types, we identified 1276 non-coding SVs that overlapped with gene regulatory elements. Based on these data, we estimate that non-coding structural variants account for 22% of the genetically encoded pharmacogenomic variability. Combined, these analyses provide the first comprehensive map of structural variability across pharmacogenes, derive estimates for the functional impact of non-coding SVs and incentivize the incorporation of structural genomic data into personalized drug response predictions.

Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

MOTIVATION

A growing amount of noncoding genetic variants, including single-nucleotide polymorphisms, are found to be associated with complex human traits and diseases. Their mechanistic interpretation is relatively limited and can use the help from computational prediction of their effects on epigenetic profiles. However, current models often focus on local, 1D genome sequence determinants and disregard global, 3D chromatin structure that critically affects epigenetic events.

RESULTS

We find that noncoding variants of unexpected high similarity in epigenetic profiles, with regards to their relatively low similarity in local sequences, can be largely attributed to their proximity in chromatin structure. Accordingly, we have developed a multimodal deep learning scheme that incorporates both data of 1D genome sequence and 3D chromatin structure for predicting noncoding variant effects. Specifically, we have integrated convolutional and recurrent neural networks for sequence embedding and graph neural networks for structure embedding despite the resolution gap between the two types of data, while utilizing recent DNA language models. Numerical results show that our models outperform competing sequence-only models in predicting epigenetic profiles and their use of long-range interactions complement sequence-only models in extracting regulatory motifs. They prove to be excellent predictors for noncoding variant effects in gene expression and pathogenicity, whether in unsupervised "zero-shot" learning or supervised "few-shot" learning.

AVAILABILITY AND IMPLEMENTATION

Codes and data can be accessed at https://github.com/Shen-Lab/ncVarPred-1D3D and https://zenodo.org/record/7975777.

Detection of trait-associated structural variations using short-read sequencing

Genomic structural variation (SV) affects genetic and phenotypic characteristics in diverse organisms, but the lack of reliable methods to detect SV has hindered genetic analysis. We developed a computational algorithm (MOPline) that includes missing call recovery combined with high-confidence SV call selection and genotyping using short-read whole-genome sequencing (WGS) data. Using 3,672 high-coverage WGS datasets, MOPline stably detected ∼16,000 SVs per individual, which is over ∼1.7-3.3-fold higher than previous large-scale projects while exhibiting a comparable level of statistical quality metrics. We imputed SVs from 181,622 Japanese individuals for 42 diseases and 60 quantitative traits. A genome-wide association study with the imputed SVs revealed 41 top-ranked or nearly top-ranked genome-wide significant SVs, including 8 exonic SVs with 5 novel associations and enriched mobile element insertions. This study demonstrates that short-read WGS data can be used to identify rare and common SVs associated with a variety of traits.

POSTRE: a tool to predict the pathological effects of human structural variants

Understanding the pathological impact of non-coding genetic variation is a major challenge in medical genetics. Accumulating evidences indicate that a significant fraction of genetic alterations, including structural variants (SVs), can cause human disease by altering the function of non-coding regulatory elements, such as enhancers. In the case of SVs, described pathomechanisms include changes in enhancer dosage and long-range enhancer-gene communication. However, there is still a clear gap between the need to predict and interpret the medical impact of non-coding variants, and the existence of tools to properly perform these tasks. To reduce this gap, we have developed POSTRE (Prediction Of STRuctural variant Effects), a computational tool to predict the pathogenicity of SVs implicated in a broad range of human congenital disorders. By considering disease-relevant cellular contexts, POSTRE identifies SVs with either coding or long-range pathological consequences with high specificity and sensitivity. Furthermore, POSTRE not only identifies pathogenic SVs, but also predicts the disease-causative genes and the underlying pathological mechanism (e.g, gene deletion, enhancer disconnection, enhancer adoption, etc.). POSTRE is available at https://github.com/vicsanga/Postre.

Molecular hallmarks of long non-coding RNAs in aging and its significant effect on aging-associated diseases

Aging is linked to the deterioration of many physical and cognitive abilities and is the leading risk factor for Alzheimer's disease. The growing aging population is a significant healthcare problem globally that researchers must investigate to better understand the underlying aging processes. Advances in microarrays and sequencing techniques have resulted in deeper analyses of diverse essential genomes (e.g., mouse, human, and rat) and their corresponding cell types, their organ-specific transcriptomes, and the tissue involved in aging. Traditional gene controllers such as DNA- and RNA-binding proteins significantly influence such programs, causing the need to sort out long non-coding RNAs, a new class of powerful gene regulatory elements. However, their functional significance in the aging process and senescence has yet to be investigated and identified. Several recent researchers have associated the initiation and development of senescence and aging in mammals with several well-reported and novel long non-coding RNAs. In this review article, we identified and analyzed the evolving functions of long non-coding RNAs in cellular processes, including cellular senescence, aging, and age-related pathogenesis, which are the major hallmarks of long non-coding RNAs in aging.

The non-coding genome in Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) are a group of neurodevelopmental disorders (NDDs) characterized by difficulties in social interaction and communication, repetitive behavior, and restricted interests. While ASD have been proven to have a strong genetic component, current research largely focuses on coding regions of the genome. However, non-coding DNA, which makes up for ∼99% of the human genome, has recently been recognized as an important contributor to the high heritability of ASD, and novel sequencing technologies have been a milestone in opening up new directions for the study of the gene regulatory networks embedded within the non-coding regions. Here, we summarize current progress on the contribution of non-coding alterations to the pathogenesis of ASD and provide an overview of existing methods allowing for the study of their functional relevance, discussing potential ways of unraveling ASD's "missing heritability".

Disruption of the gene regulatory programme in neurodevelopmental disorders

Cortical development consists of a series of synchronised events, including fate transition of cortical progenitors, neuronal migration, specification and connectivity. It is becoming clear that gene expression programs governing these events rely on the interplay between signalling molecules, transcription factors and epigenetic mechanisms. When genetic or environmental factors disrupt expression of genes involved in important brain development processes, neurodevelopmental disorders can occur. This review aims to highlight how recent advances in technologies have helped uncover and imitate the gene regulatory mechanisms commonly disrupted in neurodevelopmental disorders.

Evolution and dysfunction of human cognitive and social traits: A transcriptional regulation perspective

Evolutionary changes in brain and craniofacial development have endowed humans with unique cognitive and social skills, but also predisposed us to debilitating disorders in which these traits are disrupted. What are the developmental genetic underpinnings that connect the adaptive evolution of our cognition and sociality with the persistence of mental disorders with severe negative fitness effects? We argue that loss of function of genes involved in transcriptional regulation represents a crucial link between the evolution and dysfunction of human cognitive and social traits. The argument is based on the haploinsufficiency of many transcriptional regulator genes, which makes them particularly sensitive to loss-of-function mutations. We discuss how human brain and craniofacial traits evolved through partial loss of function (i.e. reduced expression) of these genes, a perspective compatible with the idea of human self-domestication. Moreover, we explain why selection against loss-of-function variants supports the view that mutation-selection-drift, rather than balancing selection, underlies the persistence of psychiatric disorders. Finally, we discuss testable predictions.

Focus on your locus with a massively parallel reporter assay

A growing number of variants associated with risk for neurodevelopmental disorders have been identified by genome-wide association and whole genome sequencing studies. As common risk variants often fall within large haplotype blocks covering long stretches of the noncoding genome, the causal variants within an associated locus are often unknown. Similarly, the effect of rare noncoding risk variants identified by whole genome sequencing on molecular traits is seldom known without functional assays. A massively parallel reporter assay (MPRA) is an assay that can functionally validate thousands of regulatory elements simultaneously using high-throughput sequencing and barcode technology. MPRA has been adapted to various experimental designs that measure gene regulatory effects of genetic variants within cis- and trans-regulatory elements as well as posttranscriptional processes. This review discusses different MPRA designs that have been or could be used in the future to experimentally validate genetic variants associated with neurodevelopmental disorders. Though MPRA has limitations such as it does not model genomic context, this assay can help narrow down the underlying genetic causes of neurodevelopmental disorders by screening thousands of sequences in one experiment. We conclude by describing future directions of this technique such as applications of MPRA for gene-by-environment interactions and pharmacogenetics.

TADeus2: a web server facilitating the clinical diagnosis by pathogenicity assessment of structural variations disarranging 3D chromatin structure

In recent years great progress has been made in identification of structural variants (SV) in the human genome. However, the interpretation of SVs, especially located in non-coding DNA, remains challenging. One of the reasons stems in the lack of tools exclusively designed for clinical SVs evaluation acknowledging the 3D chromatin architecture. Therefore, we present TADeus2 a web server dedicated for a quick investigation of chromatin conformation changes, providing a visual framework for the interpretation of SVs affecting topologically associating domains (TADs). This tool provides a convenient visual inspection of SVs, both in a continuous genome view as well as from a rearrangement’s breakpoint perspective. Additionally, TADeus2 allows the user to assess the influence of analyzed SVs within flaking coding/non-coding regions based on the Hi-C matrix. Importantly, the SVs pathogenicity is quantified and ranked using TADA, ClassifyCNV tools and sampling-based P-value. TADeus2 is publicly available at https://tadeus2.mimuw.edu.pl.

Investigation of Chromosomal Structural Abnormalities in Patients With Undiagnosed Neurodevelopmental Disorders

Background: Structural variations (SVs) are various types of the genomic rearrangements encompassing at least 50 nucleotides. These include unbalanced gains or losses of DNA segments (copy number changes, CNVs), balanced rearrangements (such as inversion or translocations), and complex combinations of several distinct rearrangements. SVs are known to play a significant role in contributing to human genomic disorders by disrupting the protein-coding genes or the interaction(s) with cis-regulatory elements. Recently, different types of genome sequencing-based tests have been introduced in detecting various types of SVs other than CNVs and regions with absence of heterozygosity (AOH) with clinical significance.

Method: In this study, we applied the mate-pair low pass (∼4X) genome sequencing with large DNA-insert (∼5 kb) in a cohort of 100 patients with neurodevelopmental disorders who did not receive informative results from a routine CNV investigation. Read-depth-based CNV analysis and chimeric-read-pairs analysis were used for CNV and SV analyses. The region of AOH was indicated by a simultaneous decrease in the rate of heterozygous SNVs and increase in the rate of homozygous SNVs.

Results: First, we reexamined the 25 previously reported CNVs among 24 cases in this cohort. The boundaries of these twenty-five CNVs including 15 duplications and 10 deletions detected were consistent with the ones indicated by the chimeric-read-pairs analysis, while the location and orientation were determined in 80% of duplications (12/15). Particularly, one duplication was involved in complex rearrangements. In addition, among all the 100 cases, 10% of them were detected with rare or complex SVs (&gt;10 Kb), and 3% were with multiple AOH (≥5 Mb) locating in imprinting chromosomes identified. In particular, one patient with an overall value of 214.5 Mb of AOH identified on 13 autosomal chromosomes suspected parental consanguinity.

Conclusion: In this study, mate-pair low-pass GS resolved a significant proportion of CNVs with inconclusive significance, and detected additional SVs and regions of AOH in patients with undiagnostic neurodevelopmental disorders. This approach complements the first-tier CNV analysis for NDDs, not only by increasing the resolution of CNV detection but also by enhancing the characterization of SVs and the discovery of potential causative regions (or genes) contributory to could be complex in composition NDDs.

Further Delineation of Duplications of ARX Locus Detected in Male Patients with Varying Degrees of Intellectual Disability

The X-linked gene encoding aristaless-related homeobox (ARX) is a bi-functional transcription factor capable of activating or repressing gene transcription, whose mutations have been found in a wide spectrum of neurodevelopmental disorders (NDDs); these include cortical malformations, paediatric epilepsy, intellectual disability (ID) and autism. In addition to point mutations, duplications of the ARX locus have been detected in male patients with ID. These rearrangements include telencephalon ultraconserved enhancers, whose structural alterations can interfere with the control of ARX expression in the developing brain. Here, we review the structural features of 15 gain copy-number variants (CNVs) of the ARX locus found in patients presenting wide-ranging phenotypic variations including ID, speech delay, hypotonia and psychiatric abnormalities. We also report on a further novel Xp21.3 duplication detected in a male patient with moderate ID and carrying a fully duplicated copy of the ARX locus and the ultraconserved enhancers. As consequences of this rearrangement, the patient-derived lymphoblastoid cell line shows abnormal activity of the ARX-KDM5C-SYN1 regulatory axis. Moreover, the three-dimensional (3D) structure of the Arx locus, both in mouse embryonic stem cells and cortical neurons, provides new insight for the functional consequences of ARX duplications. Finally, by comparing the clinical features of the 16 CNVs affecting the ARX locus, we conclude that—depending on the involvement of tissue-specific enhancers—the ARX duplications are ID-associated risk CNVs with variable expressivity and penetrance.

The non-coding genome in genetic brain disorders: new targets for therapy?

The non-coding genome, consisting of more than 98% of all genetic information in humans and once judged as ‘Junk DNA’, is increasingly moving into the spotlight in the field of human genetics. Non-coding regulatory elements (NCREs) are crucial to ensure correct spatio-temporal gene expression. Technological advancements have allowed to identify NCREs on a large scale, and mechanistic studies have helped to understand the biological mechanisms underlying their function. It is increasingly becoming clear that genetic alterations of NCREs can cause genetic disorders, including brain diseases. In this review, we concisely discuss mechanisms of gene regulation and how to investigate them, and give examples of non-coding alterations of NCREs that give rise to human brain disorders. The cross-talk between basic and clinical studies enhances the understanding of normal and pathological function of NCREs, allowing better interpretation of already existing and novel data. Improved functional annotation of NCREs will not only benefit diagnostics for patients, but might also lead to novel areas of investigations for targeted therapies, applicable to a wide panel of genetic disorders. The intrinsic complexity and precision of the gene regulation process can be turned to the advantage of highly specific treatments. We further discuss this exciting new field of ‘enhancer therapy’ based on recent examples.

Comprehensive multi-omics integration identifies differentially active enhancers during human brain development with clinical relevance

BACKGROUND

Non-coding regulatory elements (NCREs), such as enhancers, play a crucial role in gene regulation, and genetic aberrations in NCREs can lead to human disease, including brain disorders. The human brain is a complex organ that is susceptible to numerous disorders; many of these are caused by genetic changes, but a multitude remain currently unexplained. Understanding NCREs acting during brain development has the potential to shed light on previously unrecognized genetic causes of human brain disease. Despite immense community-wide efforts to understand the role of the non-coding genome and NCREs, annotating functional NCREs remains challenging.

METHODS

Here we performed an integrative computational analysis of virtually all currently available epigenome data sets related to human fetal brain.

RESULTS

Our in-depth analysis unravels 39,709 differentially active enhancers (DAEs) that show dynamic epigenomic rearrangement during early stages of human brain development, indicating likely biological function. Many of these DAEs are linked to clinically relevant genes, and functional validation of selected DAEs in cell models and zebrafish confirms their role in gene regulation. Compared to enhancers without dynamic epigenomic rearrangement, DAEs are subjected to higher sequence constraints in humans, have distinct sequence characteristics and are bound by a distinct transcription factor landscape. DAEs are enriched for GWAS loci for brain-related traits and for genetic variation found in individuals with neurodevelopmental disorders, including autism.

CONCLUSION

This compendium of high-confidence enhancers will assist in deciphering the mechanism behind developmental genetics of human brain and will be relevant to uncover missing heritability in human genetic brain disorders.

How does genetic variation modify ND-CNV phenotypes?

Rare copy-number variants (CNVs) associated with neurodevelopmental disorders (NDDs), i.e., ND-CNVs, provide an insight into the neurobiology of NDDs and, potentially, a link between biology and clinical outcomes. However, ND-CNVs are characterised by incomplete penetrance resulting in heterogeneous carrier phenotypes, ranging from non-affected to multimorbid psychiatric, neurological, and physical phenotypes. Recent evidence indicates that other variants in the genome, or 'other hits', may partially explain the variable expressivity of ND-CNVs. These may be other rare variants or the aggregated effects of common variants that modify NDD risk. Here we discuss the recent findings, current questions, and future challenges relating to other hits research in the context of ND-CNVs and their potential for improved clinical diagnostics and therapeutics for ND-CNV carriers.

Biological implications of genetic variations in autism spectrum disorders from genomics studies

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental condition characterized by atypical social interaction and communication together with repetitive behaviors and restricted interests. The prevalence of ASD has been increased these years. Compelling evidence has shown that genetic factors contribute largely to the development of ASD. However, knowledge about its genetic etiology and pathogenesis is limited. Broad applications of genomics studies have revealed the importance of gene mutations at protein-coding regions as well as the interrupted non-coding regions in the development of ASD. In this review, we summarize the current evidence for the known molecular genetic basis and possible pathological mechanisms as well as the risk genes and loci of ASD. Functional studies for the underlying mechanisms are also implicated. The understanding of the genetics and genomics of ASD is important for the genetic diagnosis and intervention for this condition.

A Reassessment of Copy Number Variations in Congenital Heart Defects: Picturing the Whole Genome

Copy number variations (CNVs) can modulate phenotypes by affecting protein-coding sequences directly or through interference of gene expression. Recent studies in cancer and limb defects pinpointed the relevance of non-coding gene regulatory elements such as long non-coding RNAs (lncRNAs) and topologically associated domain (TAD)-related gene-enhancer interactions. The contribution of such non-coding elements is largely unexplored in congenital heart defects (CHD). We performed a retrospective analysis of CNVs reported in a cohort of 270 CHD patients. We reviewed the diagnostic yield of pathogenic CNVs, and performed a comprehensive reassessment of 138 CNVs of unknown significance (CNV-US), evaluating protein-coding genes, lncRNA genes, and potential interferences with TAD-related gene-enhancer interactions. Fifty-two of the 138 CNV-US may relate to CHD, revealing three candidate CHD regions, 19 candidate CHD genes, 80 lncRNA genes of interest, and six potentially CHD-related TAD interferences. Our study thus indicates a potential relevance of non-coding gene regulatory elements in CNV-related CHD pathogenesis. Shortcomings in our current knowledge on genomic variation call for continuous reporting of CNV-US in international databases, careful patient counseling, and additional functional studies to confirm these preliminary findings.

Novel Compound Heterozygous Mutation in TRAPPC9 Gene: The Relevance of Whole Genome Sequencing

Advances in high-throughput technologies and its implementation worldwide have had a considerable impact on the elucidation of the molecular causes underlying neurodevelopmental psychiatric disorders, especially for autism spectrum disorder and intellectual disability (ID). Nevertheless, etiology remains elusive in close to 50% of cases, even in those families with multiple affected individuals, strongly hinting at a genetic cause. Here we present a case report of two siblings affected with severe ID and other comorbidities, who embarked on a genetic testing odyssey until diagnosis was reached by using whole genome sequencing (WGS). WGS identified a maternally inherited novel missense variant (NM_031466.7:c.1037G > A; p.Gly346Glu) and a paternally inherited 90 kb intragenic deletion in TRAPPC9 gene. This report demonstrates the clinical utility of WGS in patients who remain undiagnosed after whole exome sequencing.

De novo variants in neurodevelopmental disorders-experiences from a tertiary care center

Up to 40% of neurodevelopmental disorders (NDDs) such as intellectual disability, developmental delay, autism spectrum disorder, and developmental motor abnormalities have a documented underlying monogenic defect, primarily due to de novo variants. Still, the overall burden of de novo variants as well as novel disease genes in NDDs await discovery. We performed parent-offspring trio exome sequencing in 231 individuals with NDDs. Phenotypes were compiled using human phenotype ontology terms. The overall diagnostic yield was 49.8% (n = 115/231) with de novo variants contributing to more than 80% (n = 93/115) of all solved cases. De novo variants affected 72 different-mostly constrained-genes. In addition, we identified putative pathogenic variants in 16 genes not linked to NDDs to date. Reanalysis performed in 80 initially unsolved cases revealed a definitive diagnosis in two additional cases. Our study consolidates the contribution and genetic heterogeneity of de novo variants in NDDs highlighting trio exome sequencing as effective diagnostic tool for NDDs. Besides, we illustrate the potential of a trio-approach for candidate gene discovery and the power of systematic reanalysis of unsolved cases.

Parallel functional testing identifies enhancers active in early postnatal mouse brain

Enhancers are cis-regulatory elements that play critical regulatory roles in modulating developmental transcription programs and driving cell-type-specific and context-dependent gene expression in the brain. The development of massively parallel reporter assays (MPRAs) has enabled high-throughput functional screening of candidate DNA sequences for enhancer activity. Tissue-specific screening of in vivo enhancer function at scale has the potential to greatly expand our understanding of the role of non-coding sequences in development, evolution, and disease. Here, we adapted a self-transcribing regulatory element MPRA strategy for delivery to early postnatal mouse brain via recombinant adeno-associated virus (rAAV). We identified and validated putative enhancers capable of driving reporter gene expression in mouse forebrain, including regulatory elements within an intronic CACNA1C linkage disequilibrium block associated with risk in neuropsychiatric disorder genetic studies. Paired screening and single enhancer in vivo functional testing, as we show here, represents a powerful approach towards characterizing regulatory activity of enhancers and understanding how enhancer sequences organize gene expression in the brain.

Diagnostic Utility of Genome-Wide DNA Methylation Analysis in Mendelian Neurodevelopmental Disorders

Mendelian neurodevelopmental disorders customarily present with complex and overlapping symptoms, complicating the clinical diagnosis. Individuals with a growing number of the so-called rare disorders exhibit unique, disorder-specific DNA methylation patterns, consequent to the underlying gene defects. Besides providing insights to the pathophysiology and molecular biology of these disorders, we can use these epigenetic patterns as functional biomarkers for the screening and diagnosis of these conditions. This review summarizes our current understanding of DNA methylation episignatures in rare disorders and describes the underlying technology and analytical approaches. We discuss the computational parameters, including statistical and machine learning methods, used for the screening and classification of genetic variants of uncertain clinical significance. Describing the rationale and principles applied to the specific computational models that are used to develop and adapt the DNA methylation episignatures for the diagnosis of rare disorders, we highlight the opportunities and challenges in this emerging branch of diagnostic medicine.