Deleterious, protein-altering variants in the transcriptional coregulator ZMYM3 in 27 individuals with a neurodevelopmental delay phenotype

Integrative genomic analyses identify neuroblastoma risk genes involved in neuronal differentiation

Genome-Wide Association Studies (GWAS) have been decisive in elucidating the genetic predisposition of neuroblastoma (NB). The majority of genetic variants identified in GWAS are found in non-coding regions, suggesting that they can be causative of pathogenic dysregulations of gene expression. Nonetheless, pinpointing the potential causal genes within implicated genetic loci remains a major challenge. In this study, we integrated NB GWAS and expression Quantitative Trait Loci (eQTL) data from adrenal gland to identify candidate genes impacting NB susceptibility. We found that ZMYM1, CBL, GSKIP and WDR81 expression was dysregulated by NB predisposing variants. We further investigated the functional role of the identified genes through computational analysis of RNA sequencing (RNA-seq) data from single-cell and whole-tissue samples of NB, neural crest, and adrenal gland tissues, as well as through in vitro differentiation assays in NB cell cultures. Our results indicate that dysregulation of ZMYM1, CBL, GSKIP, WDR81 may lead to malignant transformation by affecting early and late stages of normal program of neuronal differentiation. Our findings enhance the understanding of how specific genes contribute to NB pathogenesis by highlighting their influence on neuronal differentiation and emphasizing the impact of genetic risk variants on the regulation of genes involved in critical biological processes.

Identifying the "stripe" transcription factors and cooperative binding related to DNA methylation

DNA methylation plays a critical role in gene regulation by modulating the DNA binding of transcription factors (TFs). This study integrates TFs' ChIP-seq profiles with WGBS profiles to investigate how DNA methylation affects protein interactions. Statistical methods and a 5-letter DNA motif calling model have been developed to characterize DNA sequences bound by proteins, while considering the effects of DNA modifications. By employing these methods, 79 significant universal "stripe" TFs and cofactors (USFs), 2360 co-binding protein pairs, and distinct protein modules associated with various DNA methylation states have been identified. The USFs hint a regulatory hierarchy within these protein interactions. Proteins preferentially bind to non-CpG sites in methylated regions, indicating binding affinity is not solely CpG-dependent. Proteins involved in methylation-specific USFs and cobinding pairs play essential roles in promoting and sustaining DNA methylation through interacting with DNMTs or inhibiting TET binding. These findings underscore the interplay between protein binding and methylation, offering insights into epigenetic regulation in cellular biology.

Preclinical alternative drug discovery programs for monogenic rare diseases. Should small molecules or gene therapy be used? The case of hereditary spastic paraplegias

Patients diagnosed with rare diseases and their and families search desperately to organize drug discovery campaigns. Alternative models that differ from default paradigms offer real opportunities. There are, however, no clear guidelines for the development of such models, which reduces success rates and raises costs. We address the main challenges in making the discovery of new preclinical treatments more accessible, using rare hereditary paraplegia as a paradigmatic case. First, we discuss the necessary expertise, and the patients' clinical and genetic data. Then, we revisit gene therapy, de novo drug development, and drug repurposing, discussing their applicability. Moreover, we explore a pool of recommended in silico tools for pathogenic variant and protein structure prediction, virtual screening, and experimental validation methods, discussing their strengths and weaknesses. Finally, we focus on successful case applications.

Zinc finger proteins: guardians of genome stability

Zinc finger proteins (ZNF), a unique yet diverse group of proteins, play pivotal roles in fundamental cellular mechanisms including transcription regulation, chromatin remodeling, protein/RNA homeostasis, and DNA repair. Consequently, the mis regulation of ZNF proteins can result in a variety of human diseases, ranging from neurodevelopmental disorders to several cancers. Considering the promising results of DNA damage repair (DDR) inhibition in the clinic, as a therapeutic strategy for patients with homologous recombination (HR) deficiency, identifying other potential targetable DDR proteins as emerged vulnerabilities in resistant tumor cells is essential, especially when considering the burden of acquired drug resistance. Importantly, there are a growing number of studies identifying new ZNFs and revealing their significance in several DDR pathways, highlighting their great potential as new targets for DDR-inhibition therapy. Although, there are still many uncharacterized ZNF-containing proteins with unknown biological function. In this review, we highlight the major classes and observed biological functions of ZNF proteins in mammalian cells. We briefly introduce well-known and newly discovered ZNFs and describe their molecular roles and contributions to human health and disease, especially cancer. Finally, we discuss the significance of ZNFs in DNA repair mechanisms, their potential in cancer therapy and advances in exploiting ZNF proteins as future therapeutic targets for human disease.

Transposable elements-mediated recruitment of KDM1A epigenetically silences HNF4A expression to promote hepatocellular carcinoma

Transposable elements (TEs) contribute to gene expression regulation by acting as cis-regulatory elements that attract transcription factors and epigenetic regulators. This research aims to explore the functional and clinical implications of transposable element-related molecular events in hepatocellular carcinoma, focusing on the mechanism through which liver-specific accessible TEs (liver-TEs) regulate adjacent gene expression. Our findings reveal that the expression of HNF4A is inversely regulated by proximate liver-TEs, which facilitates liver cancer cell proliferation. Mechanistically, liver-TEs are predominantly occupied by the histone demethylase, KDM1A. KDM1A negatively influences the methylation of histone H3 Lys4 (H3K4) of liver-TEs, resulting in the epigenetic silencing of HNF4A expression. The suppression of HNF4A mediated by KDM1A promotes liver cancer cell proliferation. In conclusion, this study uncovers a liver-TE/KDM1A/HNF4A regulatory axis that promotes liver cancer growth and highlights KDM1A as a promising therapeutic target. Our findings provide insight into the transposable element-related molecular mechanisms underlying liver cancer progression.

Probabilistic association of differentially expressed genes with cis-regulatory elements

Differential gene expression in response to perturbations is mediated at least in part by changes in binding of transcription factors (TFs) and other proteins at specific genomic regions. Association of these cis-regulatory elements (CREs) with their target genes is a challenging task that is essential to address many biological and mechanistic questions. Many current approaches rely on chromatin conformation capture techniques or single-cell correlational methods to establish CRE-to-gene associations. These methods can be effective but have limitations, including resolution, gaps in detectable association distances, and cost. As an alternative, we have developed DegCre, a nonparametric method that evaluates correlations between measurements of perturbation-induced differential gene expression and differential regulatory signal at CREs to score possible CRE-to-gene associations. It has several unique features, including the ability to use any type of CRE activity measurement, yield probabilistic scores for CRE-to-gene pairs, and assess CRE-to-gene pairings across a wide range of sequence distances. We apply DegCre to six data sets, each using different perturbations and containing a variety of regulatory signal measurements, including chromatin openness, histone modifications, and TF occupancy. To test their efficacy, we compare DegCre associations to Hi-C loop calls and CRISPR-validated CRE-to-gene associations, establishing good performance by DegCre that is comparable or superior to competing methods. DegCre is a novel approach to the association of CREs to genes from a perturbation-differential perspective, with strengths that are complementary to existing approaches and allow for new insights into gene regulation.

Skewed X-chromosome inactivation in unsolved neurodevelopmental disease cases can guide re-evaluation For X-linked genes

Despite major advances in genome technology and analysis, >50% of patients with a neurodevelopmental disorder (NDD) remain undiagnosed after extensive evaluation. A point in case is our clinically heterogeneous cohort of NDD patients that remained undiagnosed after FRAXA testing, chromosomal microarray analysis and trio exome sequencing (ES). In this study, we explored the frequency of non-random X chromosome inactivation (XCI) in the mothers of male patients and affected females, the rationale being that skewed XCI might be masking previously discarded genetic variants found on the X chromosome. A multiplex fluorescent PCR-based assay was used to analyse the pattern of XCI after digestion with HhaI methylation-sensitive restriction enzyme. In families with skewed XCI, we re-evaluated trio-based ES and identified pathogenic variants and a deletion on the X chromosome. Linkage analysis and RT-PCR were used to further study the inactive X chromosome allele, and Xdrop long-DNA technology was used to define chromosome deletion boundaries. We found skewed XCI (>90%) in 16/186 (8.6%) mothers of NDD males and in 12/90 (13.3%) NDD females, far beyond the expected rate of XCI in the normal population (3.6%, OR = 4.10; OR = 2.51). By re-analyzing ES and clinical data, we solved 7/28 cases (25%) with skewed XCI, identifying variants in KDM5C, PDZD4, PHF6, TAF1, OTUD5 and ZMYM3, and a deletion in ATRX. We conclude that XCI profiling is a simple assay that targets a subgroup of patients that can benefit from re-evaluation of X-linked variants, thus improving the diagnostic yield in NDD patients and identifying new X-linked disorders.

Allele biased transcription factor binding across human brain regions gives mechanistic insight into eQTLs

Transcription Factors (TFs) influence gene expression by facilitating or disrupting the formation of transcription initiation machinery at particular genomic loci. Because genomic localization of TFs is in part driven by TF recognition of DNA sequence, variation in TF binding sites can disrupt TF-DNA associations and affect gene regulation. To identify variants that impact TF binding in human brain tissues, we quantified allele bias for 93 TFs analyzed with ChIP-seq experiments of multiple structural brain regions from two donors. Using graph genomes constructed from phased genomic sequence data, we compared ChIP-seq signal between alleles at heterozygous variants within each tissue sample from each donor. Comparison of results from different brain regions within donors and the same regions between donors provided measures of allele bias reproducibility. We identified thousands of DNA variants that show reproducible bias in ChIP-seq for at least one TF. We found that alleles that are rarer in the general population were more likely than common alleles to exhibit large biases, and more frequently led to reduced TF binding. Combining ChIP-seq with RNA-seq, we identified TF-allele interaction biases with RNA bias in a phased allele linked to 6,709 eQTL variants identified in GTEx data, 3,309 of which were found in neural contexts. Our results provide insights into the effects of both common and rare variation on gene regulation in the brain. These findings can facilitate mechanistic understanding of cis-regulatory variation associated with biological traits, including disease.