The Mendelian disorders of the epigenetic machinery

Björnsson, Hans T.

doi:10.1101/gr.190629.115

Cited by 159 publications

(182 citation statements)

References 65 publications

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“…The most frequent clinical manifestations thereof are intellectual disability, disorders of the neuronal migration, immune dysfunction, growth impairment, and skeletal anomalies. Craniosynostosis is a consistent, albeit rare feature in 4 out of 44 mendelian disorders of the epigenetic machinery [Bjornsson, 2015]. Conceivably, the phenotypic outcome in individual patients may reflect not only disruption of the compartments of the epigenetic machinery, but also the molecular constitution of the target genes [Paro, 1995;Law et al, 2010].…”

Section: Genotype-phenotype Relationshipsmentioning

confidence: 99%

Structural Genome Variations Related to Craniosynostosis

Poot¹

2018

Mol Syndromol

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Craniosynostosis refers to a condition during early development in which one or more of the fibrous sutures of the skull prematurely fuse by turning into bone, which produces recognizable patterns of cranial shape malformations depending on which suture(s) are affected. In addition to cases with isolated cranial dysmorphologies, craniosynostosis appears in syndromes that include skeletal features of the eyes, nose, palate, hands, and feet as well as impairment of vision, hearing, and intellectual development. Approximately 85% of the cases are nonsyndromic sporadic and emerge after de novo structural genome rearrangements or single nucleotide variation, while the remainders consist of syndromic cases following mendelian inheritance. By karyotyping, genome wide linkage, and CNV analyses as well as by whole exome and whole genome sequencing, numerous candidate genes for craniosynostosis belonging to the FGF, Wnt, BMP, Ras/ERK, ephrin, hedgehog, STAT, and retinoic acid signaling pathways have been identified. Many of the craniosynostosis-related candidate genes form a functional network based upon protein-protein or protein-DNA interactions. Depending on which node of this craniosynostosis-related network is affected by a gene mutation or a change in gene expression pattern, a distinct craniosynostosis syndrome or set of phenotypes ensues. Structural variations may alter the dosage of one or several genes or disrupt the genomic architecture of genes and their regulatory elements within topologically associated chromatin domains. These may exert dominant effects by either haploinsufficiency, dominant negative partial loss of function, gain of function, epistatic interaction, or alteration of levels and patterns of gene expression during development. Molecular mechanisms of dominant modes of action of these mutations may include loss of one or several binding sites for cognate protein partners or transcription factor binding sequences. Such losses affect interactions within functional networks governing development and consequently result in phenotypes such as craniosynostosis. Many of the novel variants identified by genome wide CNV analyses, whole exome and whole genome sequencing are incorporated in recently developed diagnostic algorithms for craniosynostosis.

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Section: Genotype-phenotype Relationshipsmentioning

confidence: 99%

Structural Genome Variations Related to Craniosynostosis

Poot¹

2018

Mol Syndromol

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“…It has been identified that there is a high mutational load in chromatin-modifying genes in developmental disorders [25]. These monogenic disorders strongly indicate the importance of chromatin dynamics and the associated phenotypes commonly including significant behavioural and intellectual disabilities [26]. It is also of note that these genes have also been observed as somatic hotspots in cancers [27].…”

Section: Chromatin Modificationsmentioning

confidence: 98%

Insights in human epigenomic dynamics through comparative primate analysis

Bell

2016

Genomics

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Epigenomic analysis gives a molecular insight into cell-specific genomic activity. It provides a detailed functional plan to dissect an organism, tissue by tissue.Therefore comparative epigenomics may increase understanding of human-acquired traits, by revealing regulatory changes in systems such as the neurological, musculoskeletal, and immunological.Enhancer loci evolve fast by hijacking elements from other tissues or rewiring and amplifying existing units for human-specific function. Promoters by contrast often require a CpG dense genetic infrastructure. Specific interplay occurs between the two, but also a shared modality of function, with coordination from global chromatin-modifying enzymes. Changes in specific transcription factor binding sites also facilitate the local epigenetic state. In the case of CTCF, these may further influence 3-dimensional structure and interaction.How these mechanistic units are modulated between tissue and species enables more comprehensive understanding of human processes and pathology.With this, precise therapeutic targeting of these epigenetic modifications may become possible.

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“…Mutations in epigenetic enzymes are frequently observed in cancer [42], intellectual disability [43], neurological disorders such as Alzheimer’s, Parkinson’s, and Huntington’s disease [44], and autoimmune diseases such as rheumatoid arthritis [45–47] and type 1 diabetes [48]. Most studies have been performed in cancer: ~30% of all driver genes characterized in cancer are related to chromatin structure and function [42].…”

Section: Main Textmentioning

confidence: 99%

Genome-wide epigenomic profiling for biomarker discovery

2016

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A myriad of diseases is caused or characterized by alteration of epigenetic patterns, including changes in DNA methylation, post-translational histone modifications, or chromatin structure. These changes of the epigenome represent a highly interesting layer of information for disease stratification and for personalized medicine. Traditionally, epigenomic profiling required large amounts of cells, which are rarely available with clinical samples. Also, the cellular heterogeneity complicates analysis when profiling clinical samples for unbiased genome-wide biomarker discovery. Recent years saw great progress in miniaturization of genome-wide epigenomic profiling, enabling large-scale epigenetic biomarker screens for disease diagnosis, prognosis, and stratification on patient-derived samples. All main genome-wide profiling technologies have now been scaled down and/or are compatible with single-cell readout, including: (i) Bisulfite sequencing to determine DNA methylation at base-pair resolution, (ii) ChIP-Seq to identify protein binding sites on the genome, (iii) DNaseI-Seq/ATAC-Seq to profile open chromatin, and (iv) 4C-Seq and HiC-Seq to determine the spatial organization of chromosomes. In this review we provide an overview of current genome-wide epigenomic profiling technologies and main technological advances that allowed miniaturization of these assays down to single-cell level. For each of these technologies we evaluate their application for future biomarker discovery. We will focus on (i) compatibility of these technologies with methods used for clinical sample preservation, including methods used by biobanks that store large numbers of patient samples, and (ii) automation of these technologies for robust sample preparation and increased throughput.

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The Mendelian disorders of the epigenetic machinery

Cited by 159 publications

References 65 publications

Structural Genome Variations Related to Craniosynostosis

Structural Genome Variations Related to Craniosynostosis

Insights in human epigenomic dynamics through comparative primate analysis

Genome-wide epigenomic profiling for biomarker discovery

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