Detection of Imprinted Genes by Single-Cell Allele-Specific Gene Expression

Mom genes and dad genes: genomic imprinting in the regulation of social behaviors

Genomic imprinting is an epigenetic phenomenon in mammals that affects brain development and behavior. Imprinting involves the regulation of allelic expression for some genes in offspring that depends on whether alleles are inherited from mothers compared to fathers, and is thought to provide parental control over offspring social behavior phenotypes. Imprinted gene expression is prevalent in the mammalian brain, and human imprinted gene mutations are associated with neurodevelopmental disorders and neurodivergent social behavior in Prader-Willi Syndrome, Angelman Syndrome, and autism. Here, we provide a review of the evidence that imprinted genes influence social behaviors across major neurodevelopmental stages in humans and mouse animal models that include parent-infant interactions, juvenile sociability, and adult aggression, dominance, and sexual behavior.

A compendium of methods: Searching allele specific expression via RNA sequencing

Diploid mammalian genome has paired alleles for each gene; typically allowing for equal expression of the two alleles within the cell/tissue. However, genetic regulatory elements and epigenetic modifications can disrupt this equality, leading to preferential expression of one allele. Examining high-confidence allele-specific expression (ASE) is vital for understanding genetic variations and their impact on major diseases like cancers and diabetes. ASE analysis not only aids in disease prognosis and diagnosis but also helps to identify regulatory mechanisms operating within the genome. While advances in sequencing technologies have greatly improved our understanding of ASE, challenges remain in estimating it accurately. In this article, we reviewed methods for detecting ASE using both bulk RNASeq and single-cell RNASeq data to provide deeper insights beyond the mere prediction of ASE genes. Fundamentally, ASE detection methods are data-driven and can be classified according to type of data used. Some methods utilize both, DNA genotyping information and RNASeq while others rely solely on RNASeq data. This article offers a comparative analysis of these methods and compilation of repositories providing valuable insights.

Characterization of Loss-of-Imprinting in Breast Cancer at the Cellular Level by Integrating Single-Cell Full-Length Transcriptome with Bulk RNA-Seq Data

Genomic imprinting, the parent-of-origin-specific gene expression, plays a pivotal role in growth regulation and is often dysregulated in cancer. However, screening for imprinting is complicated by its cell-type specificity, which bulk RNA-seq cannot capture. On the other hand, large-scale single-cell RNA-seq (scRNA-seq) often lacks transcript-level detail and is cost-prohibitive. Here, we address this gap by integrating bulk RNA-seq with full-length transcript scRNA-seq to investigate imprinting dynamics in breast cancer. By analyzing scRNA-seq data from 486 cancer cells across subtypes, we identified multiple SNPs in imprinted genes, including HM13, MEST (PEG1), SNHG14 and PEG10, showing consistent biallelic expression. Bulk RNA-seq, however, revealed that this biallelic expression arises from transcript-specific imprinting, rather than loss-of-imprinting (LOI). The imprinted SNPs identified in bulk RNA-seq predominantly demonstrate proper monoallelic expression in scRNA-seq. As a clear exception, an HER2+ breast cancer sample exhibited distinct LOI of MEST. Previous bulk RNA-seq-based observations about MEST LOI in breast cancer could not exclude a non-cancer cell impact, but our results validate that MEST LOI is cancer-specific. This study demonstrates the complementary utility of bulk and scRNA-seq in imprinting studies, confirming MEST LOI as a genuine event in breast cancer.

Computational methods for allele-specific expression in single cells

Allele-specific expression (ASE) is a powerful signal that can be used to investigate multiple molecular mechanisms, such as cis-regulatory effects and imprinting. Single-cell RNA-sequencing (scRNA-seq) enables ASE characterization at the resolution of individual cells. In this review, we highlight the computational methods for processing and analyzing single-cell ASE data. We first describe a bioinformatics pipeline to obtain ASE counts from raw reads synthesized from previous literature. We then discuss statistical methods for detecting allelic imbalance and its variability across conditions using scRNA-seq data. In addition, we describe other methods that use single-cell ASE to address specific biological questions. Finally, we discuss future directions and emphasize the need for an integrated, optimized bioinformatics pipeline, and further development of statistical methods for different technologies.

Z-DNA formation in promoters conserved between human and mouse are associated with increased transcription reinitiation rates

A long-standing question concerns the role of Z-DNA in transcription. Here we use a deep learning approach DeepZ that predicts Z-flipons based on DNA sequence, structural properties of nucleotides and omics data. We examined Z-flipons that are conserved between human and mouse genomes after generating whole-genome Z-flipon maps and then validated them by orthogonal approaches based on high resolution chemical mapping of Z-DNA and the transformer algorithm Z-DNABERT. For human and mouse, we revealed similar pattern of transcription factors, chromatin remodelers, and histone marks associated with conserved Z-flipons. We found significant enrichment of Z-flipons in alternative and bidirectional promoters associated with neurogenesis genes. We show that conserved Z-flipons are associated with increased experimentally determined transcription reinitiation rates compared to promoters without Z-flipons, but without affecting elongation or pausing. Our findings support a model where Z-flipons engage Transcription Factor E and impact phenotype by enabling the reset of preinitiation complexes when active, and the suppression of gene expression when engaged by repressive chromatin complexes.

Detection of allele-specific expression in spatial transcriptomics with spASE

Spatial transcriptomics technologies permit the study of the spatial distribution of RNA at near-single-cell resolution genome-wide. However, the feasibility of studying spatial allele-specific expression (ASE) from these data remains uncharacterized. Here, we introduce spASE, a computational framework for detecting and estimating spatial ASE. To tackle the challenges presented by cell type mixtures and a low signal to noise ratio, we implement a hierarchical model involving additive mixtures of spatial smoothing splines. We apply our method to allele-resolved Visium and Slide-seq from the mouse cerebellum and hippocampus and report new insight into the landscape of spatial and cell type-specific ASE therein.

Genetic/epigenetic effects in NF1 microdeletion syndrome: beyond the haploinsufficiency, looking at the contribution of not deleted genes

NF1 microdeletion syndrome, accounting for 5-11% of NF1 patients, is caused by a deletion in the NF1 region and it is generally characterized by a severe phenotype. Although 70% of NF1 microdeletion patients presents the same 1.4 Mb type-I deletion, some patients may show additional clinical features. Therefore, the contribution of several pathogenic mechanisms, besides haploinsufficiency of some genes within the deletion interval, is expected and needs to be defined. We investigated an altered expression of deletion flanking genes by qPCR in patients with type-1 NF1 deletion, compared to healthy donors, possibly contributing to the clinical traits of NF1 microdeletion syndrome. In addition, the 1.4-Mb deletion leads to changes in the 3D chromatin structure in the 17q11.2 region. Specifically, this deletion alters DNA-DNA interactions in the regions flanking the breakpoints, as demonstrated by our 4C-seq analysis. This alteration likely causes position effect on the expression of deletion flanking genes.Interestingly, 4C-seq analysis revealed that in microdeletion patients, an interaction was established between the RHOT1 promoter and the SLC6A4 gene, which showed increased expression. We performed NGS on putative modifier genes, and identified two "likely pathogenic" rare variants in RAS pathway, possibly contributing to incidental phenotypic features.This study provides new insights into understanding the pathogenesis of NF1 microdeletion syndrome and suggests a novel pathomechanism that contributes to the expression phenotype in addition to haploinsufficiency of genes located within the deletion.This is a pivotal approach that can be applied to unravel microdeletion syndromes, improving precision medicine, prognosis and patients' follow-up.

The role of imprinting genes' loss of imprints in cancers and their clinical implications

Genomic imprinting plays an important role in the growth and development of mammals. When the original imprint status of these genes is lost, known as loss of imprinting (LOI), it may affect growth, neurocognitive development, metabolism, and even tumor susceptibility. The LOI of imprint genes has gradually been found not only as an early event in tumorigenesis, but also to be involved in progression. More than 120 imprinted genes had been identified in humans. In this review, we summarized the most studied LOI of two gene clusters and 13 single genes in cancers. We focused on the roles they played, that is, as growth suppressors and anti-apoptosis agents, sustaining proliferative signaling or inducing angiogenesis; the molecular pathways they regulated; and especially their clinical significance. It is notable that 12 combined forms of multi-genes' LOI, 3 of which have already been used as diagnostic models, achieved good sensitivity, specificity, and accuracy. In addition, the methods used for LOI detection in existing research are classified into detection of biallelic expression (BAE), differentially methylated regions (DMRs), methylation, and single-nucleotide polymorphisms (SNPs). These all indicated that the detection of imprinting genes' LOI has potential clinical significance in cancer diagnosis, treatment, and prognosis.

Epigenomic states contribute to coordinated allelic transcriptional bursting in iPSC reprogramming

Two alleles of a gene can be transcribed independently or coordinatedly, which can lead to temporal expression heterogeneity with potentially distinct impacts on cell fate. Here, we profiled genome-wide allelic transcriptional burst kinetics during the reprogramming of MEF to induced pluripotent stem cells. We show that the degree of coordination of allelic bursting differs among genes, and alleles of many reprogramming-related genes burst in a highly coordinated fashion. Notably, we show that the chromatin accessibility of the two alleles of highly coordinated genes is similar, unlike the semi-coordinated or independent genes, suggesting the degree of coordination of allelic bursting is linked to allelic chromatin accessibility. Consistently, we show that many transcription factors have differential binding affinity between alleles of semi-coordinated or independent genes. We show that highly coordinated genes are enriched with chromatin accessibility regulators such as H3K4me3, H3K4me1, H3K36me3, H3K27ac, histone variant H3.3, and BRD4. Finally, we demonstrate that enhancer elements are highly enriched in highly coordinated genes. Our study demonstrates that epigenomic states contribute to coordinated allelic bursting to fine-tune gene expression during induced pluripotent stem cell reprogramming.

A novel imprinted locus on bovine chromosome 18 homologous with human chromosome 16q24.1

Genomic imprinting is an epigenetic regulation mechanism in mammals resulting in the parentally dependent monoallelic expression of genes. Imprinting disorders in humans are associated with several congenital syndromes and cancers and remain the focus of many medical studies. Cattle is a better model organism for investigating human embryo development than mice. Imprinted genes usually cluster on chromosomes and are regulated by different methylation regions (DMRs) located in imprinting control regions that control gene expression in cis. There is an imprinted locus on human chromosome 16q24.1 associated with congenital lethal developmental lung disease in newborns. However, genomic imprinting on bovine chromosome 18, which is homologous with human chromosome 16 has not been systematically studied. The aim of this study was to analyze the allelic expressions of eight genes (CDH13, ATP2C2, TLDC1, COTL1, CRISPLD2, ZDHHC7, KIAA0513, and GSE1) on bovine chromosome 18 and to search the DMRs associated gene allelic expression. Three transcript variants of the ZDHHC7 gene (X1, X2, and X5) showed maternal imprinting in bovine placentas. In addition, the monoallelic expression of X2 and X5 was tissue-specific. Five transcripts of the KIAA0513 gene showed tissue- and isoform-specific monoallelic expression. The CDH13, ATP2C2, and TLDC1 genes exhibited tissue-specific imprinting, however, COTL1, CRISLPLD2, and GSE1 escaped imprinting. Four DMRs, established after fertilization, were found in this region. Two DMRs were located between the ZDHHC7 and KIAA0513 genes, and two were in exon 1 of the CDH13 and ATP2C2 genes, respectively. The results from this study support future studies on the molecular mechanism to regulate the imprinting of candidate genes on bovine chromosome 18.

Imprinted genes and the manipulation of parenting in mammals

Genomic imprinting refers to the parent-of-origin expression of genes, which originates from epigenetic events in the mammalian germ line. The evolution of imprinting may reflect a conflict over resource allocation early in life, with silencing of paternal genes in offspring soliciting increased maternal provision and silencing of maternal genes limiting demands on the mother. Parental caregiving has been identified as an area of potential conflict, with several imprinted genes serendipitously found to directly influence the quality of maternal care. Recent systems biology approaches, based on single-cell RNA sequencing data, support a more deliberate relationship, which is reinforced by the finding that imprinted genes expressed in the offspring influence the quality of maternal caregiving. These bidirectional, reiterative relationships between parents and their offspring are critical both for short-term survival and for lifelong wellbeing, with clear implications for human health.

Prenatal exposure to triclosan assessed in multiple urine samples and placental DNA methylation

A previous study reported positive associations of maternal urinary concentrations of triclosan, a synthetic phenol with widespread exposure in the general population, with placental DNA methylation of male fetuses. Given the high number of comparisons performed in -omic research, further studies were needed to validate and extend on these findings. Using a cohort of male and female fetuses with repeated maternal urine samples to assess exposure, we studied the associations between triclosan and placental DNA methylation. We assessed triclosan concentrations in two pools of 21 urine samples collected among 395 women from the SEPAGES cohort. We used Infinium Methylation EPIC arrays to measure DNA methylation in placental biopsies collected at delivery. We performed a candidate study restricted to a set of candidate CpGs (n = 500) identified in a previous work as well as an exploratory epigenome-wide association study to investigate the associations between triclosan and differentially methylated probes and regions. Analyses were conducted on the whole population and stratified by child's sex. Mediation analysis was performed to test whether heterogeneity of placental tissue may mediate the observed associations. In the candidate approach, we confirmed 18 triclosan-associated genes when both sexes were considered. After stratification for child's sex, triclosan was associated with 72 genes in females and three in males. Most of the associations were positive and several CpGs mapped to imprinted genes: FBRSL1, KCNQ1, RHOBTB3, and SMOC1. A mediation effect by placental tissue heterogeneity was identified for most of the observed associations. In the exploratory analysis, we identified a few isolated associations in the sex-stratified analysis. In line with a previous study on male placentas, our approach revealed several positive associations between triclosan exposure and placental DNA methylation. Several identified loci mapped to imprinted genes.

Epigenetic Reprogramming in Mice and Humans: From Fertilization to Primordial Germ Cell Development

In this review, advances in the understanding of epigenetic reprogramming from fertilization to the development of primordial germline cells in a mouse and human embryo are discussed. To gain insights into the molecular underpinnings of various diseases, it is essential to comprehend the intricate interplay between genetic, epigenetic, and environmental factors during cellular reprogramming and embryonic differentiation. An increasing range of diseases, including cancer and developmental disorders, have been linked to alterations in DNA methylation and histone modifications. Global epigenetic reprogramming occurs in mammals at two stages: post-fertilization and during the development of primordial germ cells (PGC). Epigenetic reprogramming after fertilization involves rapid demethylation of the paternal genome mediated through active and passive DNA demethylation, and gradual demethylation in the maternal genome through passive DNA demethylation. The de novo DNA methyltransferase enzymes, Dnmt3a and Dnmt3b, restore DNA methylation beginning from the blastocyst stage until the formation of the gastrula, and DNA maintenance methyltransferase, Dnmt1, maintains methylation in the somatic cells. The PGC undergo a second round of global demethylation after allocation during the formative pluripotent stage before gastrulation, where the imprints and the methylation marks on the transposable elements known as retrotransposons, including long interspersed nuclear elements (LINE-1) and intracisternal A-particle (IAP) elements are demethylated as well. Finally, DNA methylation is restored in the PGC at the implantation stage including sex-specific imprints corresponding to the sex of the embryo. This review introduces a novel perspective by uncovering how toxicants and stress stimuli impact the critical period of allocation during formative pluripotency, potentially influencing both the quantity and quality of PGCs. Furthermore, the comprehensive comparison of epigenetic events between mice and humans breaks new ground, empowering researchers to make informed decisions regarding the suitability of mouse models for their experiments.

Imprinted Genes: Genomic Conservation, Transcriptomic Dynamics and Phenomic Significance in Health and Diseases

Since its discovery in 1991, genomic imprinting has been the subject of numerous studies into its mechanisms of establishment and regulation, evolution and function, and presence in multiple genomes. Disturbance of imprinting has been implicated in a range of diseases, ranging from debilitating syndromes to cancers to fetal deficiencies. Despite this, studies done on the prevalence and relevance of imprinting on genes have been limited in scope, tissue types available, and focus, by both availability and resources. This has left a gap in comparative studies. To address this, we assembled a collection of imprinted genes available in current literature covering five species. Here we sought to identify trends and motifs in the imprinted gene set (IGS) in three distinct arenas: evolutionary conservation, across-tissue expression, and health phenomics. Overall, we found that imprinted genes displayed less conservation and higher proportions of non-coding RNA while maintaining synteny. Maternally expressed genes (MEGs) and paternally expressed genes (PEGs) occupied distinct roles in tissue expression and biological pathway use, while imprinted genes collectively showed a broader tissue range, notable preference for tissue specific expression and limited gene pathways than comparable sex differentiation genes. Both human and murine imprinted genes showed the same clear phenotypic trends, that were distinct from those displayed by sex differentiation genes which were less involved in mental and nervous system disease. While both sets had representation across the genome, the IGS showed clearer clustering as expected, with PEGs significantly more represented than MEGs.

FOXI3 pathogenic variants cause one form of craniofacial microsomia

Craniofacial microsomia (CFM; also known as Goldenhar syndrome), is a craniofacial developmental disorder of variable expressivity and severity with a recognizable set of abnormalities. These birth defects are associated with structures derived from the first and second pharyngeal arches, can occur unilaterally and include ear dysplasia, microtia, preauricular tags and pits, facial asymmetry and other malformations. The inheritance pattern is controversial, and the molecular etiology of this syndrome is largely unknown. A total of 670 patients belonging to unrelated pedigrees with European and Chinese ancestry with CFM, are investigated. We identify 18 likely pathogenic variants in 21 probands (3.1%) in FOXI3. Biochemical experiments on transcriptional activity and subcellular localization of the likely pathogenic FOXI3 variants, and knock-in mouse studies strongly support the involvement of FOXI3 in CFM. Our findings indicate autosomal dominant inheritance with reduced penetrance, and/or autosomal recessive inheritance. The phenotypic expression of the FOXI3 variants is variable. The penetrance of the likely pathogenic variants in the seemingly dominant form is reduced, since a considerable number of such variants in affected individuals were inherited from non-affected parents. Here we provide suggestive evidence that common variation in the FOXI3 allele in trans with the pathogenic variant could modify the phenotypic severity and accounts for the incomplete penetrance.

Widespread allele-specific topological domains in the human genome are not confined to imprinted gene clusters

BACKGROUND

There is widespread interest in the three-dimensional chromatin conformation of the genome and its impact on gene expression. However, these studies frequently do not consider parent-of-origin differences, such as genomic imprinting, which result in monoallelic expression. In addition, genome-wide allele-specific chromatin conformation associations have not been extensively explored. There are few accessible bioinformatic workflows for investigating allelic conformation differences and these require pre-phased haplotypes which are not widely available.

RESULTS

We developed a bioinformatic pipeline, "HiCFlow," that performs haplotype assembly and visualization of parental chromatin architecture. We benchmarked the pipeline using prototype haplotype phased Hi-C data from GM12878 cells at three disease-associated imprinted gene clusters. Using Region Capture Hi-C and Hi-C data from human cell lines (1-7HB2, IMR-90, and H1-hESCs), we can robustly identify the known stable allele-specific interactions at the IGF2-H19 locus. Other imprinted loci (DLK1 and SNRPN) are more variable and there is no "canonical imprinted 3D structure," but we could detect allele-specific differences in A/B compartmentalization. Genome-wide, when topologically associating domains (TADs) are unbiasedly ranked according to their allele-specific contact frequencies, a set of allele-specific TADs could be defined. These occur in genomic regions of high sequence variation. In addition to imprinted genes, allele-specific TADs are also enriched for allele-specific expressed genes. We find loci that have not previously been identified as allele-specific expressed genes such as the bitter taste receptors (TAS2Rs).

CONCLUSIONS

This study highlights the widespread differences in chromatin conformation between heterozygous loci and provides a new framework for understanding allele-specific expressed genes.

Genetics of mitochondrial diseases: Current approaches for the molecular diagnosis

Mitochondrial diseases are a genetically and phenotypically variable set of monogenic disorders. The main characteristic of mitochondrial diseases is a defective oxidative phosphorylation. Both nuclear and mitochondrial DNA encode the approximately 1500 mitochondrial proteins. Since identification of the first mitochondrial disease gene in 1988 a total of 425 genes have been associated with mitochondrial diseases. Mitochondrial dysfunctions can be caused both by pathogenic variants in the mitochondrial DNA or the nuclear DNA. Hence, besides maternal inheritance, mitochondrial diseases can follow all modes of Mendelian inheritance. The maternal inheritance and tissue specificity distinguish molecular diagnostics of mitochondrial disorders from other rare disorders. With the advances made in the next-generation sequencing technology, whole exome sequencing and even whole-genome sequencing are now the established methods of choice for molecular diagnostics of mitochondrial diseases. They reach a diagnostic rate of more than 50% in clinically suspected mitochondrial disease patients. Moreover, next-generation sequencing is delivering a constantly growing number of novel mitochondrial disease genes. This chapter reviews mitochondrial and nuclear causes of mitochondrial diseases, molecular diagnostic methodologies, and their current challenges and perspectives.

Inference of putative cell-type-specific imprinted regulatory elements and genes during human neuronal differentiation

Genomic imprinting results in gene expression bias caused by parental chromosome of origin and occurs in genes with important roles during human brain development. However, the cell-type and temporal specificity of imprinting during human neurogenesis is generally unknown. By detecting within-donor allelic biases in chromatin accessibility and gene expression that are unrelated to cross-donor genotype, we inferred imprinting in both primary human neural progenitor cells and their differentiated neuronal progeny from up to 85 donors. We identified 43/20 putatively imprinted regulatory elements (IREs) in neurons/progenitors, and 133/79 putatively imprinted genes in neurons/progenitors. Although 10 IREs and 42 genes were shared between neurons and progenitors, most putative imprinting was only detected within specific cell types. In addition to well-known imprinted genes and their promoters, we inferred novel putative IREs and imprinted genes. Consistent with both DNA methylation-based and H3K27me3-based regulation of imprinted expression, some putative IREs also overlapped with differentially methylated or histone-marked regions. Finally, we identified a progenitor-specific putatively imprinted gene overlapping with copy number variation that is associated with uniparental disomy-like phenotypes. Our results can therefore be useful in interpreting the function of variants identified in future parent-of-origin association studies.

Promising therapeutic aspects in human genetic imprinting disorders

Genomic imprinting is an epigenetic phenomenon of monoallelic gene expression pattern depending on parental origin. In humans, congenital imprinting disruptions resulting from genetic or epigenetic mechanisms can cause a group of diseases known as genetic imprinting disorders (IDs). Genetic IDs involve several distinct syndromes sharing homologies in terms of genetic etiologies and phenotypic features. However, the molecular pathogenesis of genetic IDs is complex and remains largely uncharacterized, resulting in a lack of effective therapeutic approaches for patients. In this review, we begin with an overview of the genomic and epigenomic molecular basis of human genetic IDs. Notably, we address ethical aspects as a priority of employing emerging techniques for therapeutic applications in human IDs. With a particular focus, we delineate the current field of emerging therapeutics for genetic IDs. We briefly summarize novel symptomatic drugs and highlight the key milestones of new techniques and therapeutic programs as they stand today which can offer highly promising disease-modifying interventions for genetic IDs accompanied by various challenges.

Airpart: interpretable statistical models for analyzing allelic imbalance in single-cell datasets

MOTIVATION

Allelic expression analysis aids in detection of cis-regulatory mechanisms of genetic variation, which produce allelic imbalance (AI) in heterozygotes. Measuring AI in bulk data lacking time or spatial resolution has the limitation that cell-type-specific (CTS), spatial- or time-dependent AI signals may be dampened or not detected.

RESULTS

We introduce a statistical method airpart for identifying differential CTS AI from single-cell RNA-sequencing data, or dynamics AI from other spatially or time-resolved datasets. airpart outputs discrete partitions of data, pointing to groups of genes and cells under common mechanisms of cis-genetic regulation. In order to account for low counts in single-cell data, our method uses a Generalized Fused Lasso with Binomial likelihood for partitioning groups of cells by AI signal, and a hierarchical Bayesian model for AI statistical inference. In simulation, airpart accurately detected partitions of cell types by their AI and had lower Root Mean Square Error (RMSE) of allelic ratio estimates than existing methods. In real data, airpart identified differential allelic imbalance patterns across cell states and could be used to define trends of AI signal over spatial or time axes.

AVAILABILITY AND IMPLEMENTATION

The airpart package is available as an R/Bioconductor package at https://bioconductor.org/packages/airpart.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genomic Imprinting in the New Omics Era: A Model for Systems-Level Approaches

Genomic imprinting represents a noteworthy inheritance mechanism leading to allele-specific regulations dependent of the parental origin. Imprinted loci are especially involved in essential mammalian functions related to growth, development and behavior. In this mini-review, we first offer a summary of current representations associated with genomic imprinting through key results of the three last decades. We then outline new perspectives allowed by the spread of new omics technologies tackling various interacting levels of imprinting regulations, including genomics, transcriptomics and epigenomics. We finally discuss the expected contribution of new omics data to unresolved big questions in the field.

BrewerIX enables allelic expression analysis of imprinted and X-linked genes from bulk and single-cell transcriptomes

Genomic imprinting and X chromosome inactivation (XCI) are two prototypical epigenetic mechanisms whereby a set of genes is expressed mono-allelically in order to fine-tune their expression levels. Defects in genomic imprinting have been observed in several neurodevelopmental disorders, in a wide range of tumours and in induced pluripotent stem cells (iPSCs). Single Nucleotide Variants (SNVs) are readily detectable by RNA-sequencing allowing the determination of whether imprinted or X-linked genes are aberrantly expressed from both alleles, although standardised analysis methods are still missing. We have developed a tool, named BrewerIX, that provides comprehensive information about the allelic expression of a large, manually-curated set of imprinted and X-linked genes. BrewerIX does not require programming skills, runs on a standard personal computer, and can analyze both bulk and single-cell transcriptomes of human and mouse cells directly from raw sequencing data. BrewerIX confirmed previous observations regarding the bi-allelic expression of some imprinted genes in naive pluripotent cells and extended them to preimplantation embryos. BrewerIX also identified misregulated imprinted genes in breast cancer cells and in human organoids and identified genes escaping XCI in human somatic cells. We believe BrewerIX will be useful for the study of genomic imprinting and XCI during development and reprogramming, and for detecting aberrations in cancer, iPSCs and organoids. Due to its ease of use to non-computational biologists, its implementation could become standard practice during sample assessment, thus raising the robustness and reproducibility of future studies.

Analysis of Transcriptomic Data Generated from Drug-Treated Cancer Cell Line

Resistance to chemotherapy is one major obstacle in current cancer treatment. Therefore, understanding the molecular basis of the acquisition of resistance is vital for the design and development of appropriate cancer therapy. Importantly, acquisition of resistance is not a single-step process, and the molecular signature of cells dynamically changes during this process. With the advent of next-generation omic technologies, today one can precisely map the molecular alterations not only in a population of tumor cells but also at the single-cell level as they attain chemo-resistance. In this chapter, we describe a detailed transcriptomic pipeline following next-generation sequencing for mapping alteration in expression during the process of attainment of resistance. We provide comprehensive information on the process to (1) track the differential expression of transcripts, (2) understand the gene ontology functions, (3) filter out candidate key genes, (4) identify the pathways regulated by them, and (5) generate a map of their probable interactions. We assume that our analytical method will be useful for research in this direction.

Functional organization of the maternal and paternal human 4D Nucleome

Every human somatic cell inherits a maternal and a paternal genome, which work together to give rise to cellular phenotypes. However, the allele-specific relationship between gene expression and genome structure through the cell cycle is largely unknown. By integrating haplotype-resolved genome-wide chromosome conformation capture, mature and nascent mRNA, and protein binding data from a B lymphoblastoid cell line, we investigate this relationship both globally and locally. We introduce the maternal and paternal 4D Nucleome, enabling detailed analysis of the mechanisms and dynamics of genome structure and gene function for diploid organisms. Our analyses find significant coordination between allelic expression biases and local genome conformation, and notably absent expression bias in universally essential cell cycle and glycolysis genes. We propose a model in which coordinated biallelic expression reflects prioritized preservation of essential gene sets.

Semicoordinated allelic-bursting shape dynamic random monoallelic expression in pregastrulation embryos

Recently, allele-specific single-cell RNA-seq analysis has demonstrated widespread dynamic random monoallelic expression of autosomal genes (aRME) in different cell types. However, the prevalence of dynamic aRME during pregastrulation remains unknown. Here, we show that dynamic aRME is widespread in different lineages of pregastrulation embryos. Additionally, the origin of dynamic aRME remains elusive. It is believed that independent transcriptional bursting from each allele leads to dynamic aRME. Here, we show that allelic burst is not perfectly independent; instead it happens in a semicoordinated fashion. Importantly, we show that semicoordinated allelic bursting of genes, particularly with low burst frequency, leads to frequent asynchronous allelic bursting, thereby contributing to dynamic aRME. Furthermore, we found that coordination of allelic bursting is lineage specific and genes regulating the development have a higher degree of coordination. Altogether, our study provides significant insights into the prevalence and origin of dynamic aRME and their developmental relevance during early development.

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Dynamic aRME is widespread in different lineages of pregastrulation embryos

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Semicoordinated bursting of genes with low burst frequency leads to dynamic aRME

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Degree of coordination of allelic bursting is lineage specific

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Developmental genes have higher degree of coordination of allelic bursting

SCReadCounts: estimation of cell-level SNVs expression from scRNA-seq data

BACKGROUND

Recent studies have demonstrated the utility of scRNA-seq SNVs to distinguish tumor from normal cells, characterize intra-tumoral heterogeneity, and define mutation-associated expression signatures. In addition to cancer studies, SNVs from single cells have been useful in studies of transcriptional burst kinetics, allelic expression, chromosome X inactivation, ploidy estimations, and haplotype inference.

RESULTS

To aid these types of studies, we have developed a tool, SCReadCounts, for cell-level tabulation of the sequencing read counts bearing SNV reference and variant alleles from barcoded scRNA-seq alignments. Provided genomic loci and expected alleles, SCReadCounts generates cell-SNV matrices with the absolute variant- and reference-harboring read counts, as well as cell-SNV matrices of expressed Variant Allele Fraction (VAFRNA) suitable for a variety of downstream applications. We demonstrate three different SCReadCounts applications on 59,884 cells from seven neuroblastoma samples: (1) estimation of cell-level expression of known somatic mutations and RNA-editing sites, (2) estimation of cell- level allele expression of biallelic SNVs, and (3) a discovery mode assessment of the reference and each of the three alternative nucleotides at genomic positions of interest that does not require prior SNV information. For the later, we applied SCReadCounts on the coding regions of KRAS, where it identified known and novel somatic mutations in a low-to-moderate proportion of cells. The SCReadCounts read counts module is benchmarked against the analogous modules of GATK and Samtools. SCReadCounts is freely available ( https://github.com/HorvathLab/NGS ) as 64-bit self-contained binary distributions for Linux and MacOS, in addition to Python source.

CONCLUSIONS

SCReadCounts supplies a fast and efficient solution for estimation of cell-level SNV expression from scRNA-seq data. SCReadCounts enables distinguishing cells with monoallelic reference expression from those with no gene expression and is applicable to assess SNVs present in only a small proportion of the cells, such as somatic mutations in cancer.

Canonical and Non-canonical Genomic Imprinting in Rodents

Genomic imprinting is an epigenetic phenomenon that results in unequal expression of homologous maternal and paternal alleles. This process is initiated in the germline, and the parental epigenetic memories can be maintained following fertilization and induce further allele-specific transcription and chromatin modifications of single or multiple neighboring genes, known as imprinted genes. To date, more than 260 imprinted genes have been identified in the mouse genome, most of which are controlled by imprinted germline differentially methylated regions (gDMRs) that exhibit parent-of-origin specific DNA methylation, which is considered primary imprint. Recent studies provide evidence that a subset of gDMR-less, placenta-specific imprinted genes is controlled by maternal-derived histone modifications. To further understand DNA methylation-dependent (canonical) and -independent (non-canonical) imprints, this review summarizes the loci under the control of each type of imprinting in the mouse and compares them with the respective homologs in other rodents. Understanding epigenetic systems that differ among loci or species may provide new models for exploring genetic regulation and evolutionary divergence.

How Machine Learning and Statistical Models Advance Molecular Diagnostics of Rare Disorders Via Analysis of RNA Sequencing Data

Rare diseases, although individually rare, collectively affect approximately 350 million people worldwide. Currently, nearly 6,000 distinct rare disorders with a known molecular basis have been described, yet establishing a specific diagnosis based on the clinical phenotype is challenging. Increasing integration of whole exome sequencing into routine diagnostics of rare diseases is improving diagnostic rates. Nevertheless, about half of the patients do not receive a genetic diagnosis due to the challenges of variant detection and interpretation. During the last years, RNA sequencing is increasingly used as a complementary diagnostic tool providing functional data. Initially, arbitrary thresholds have been applied to call aberrant expression, aberrant splicing, and mono-allelic expression. With the application of RNA sequencing to search for the molecular diagnosis, the implementation of robust statistical models on normalized read counts allowed for the detection of significant outliers corrected for multiple testing. More recently, machine learning methods have been developed to improve the normalization of RNA sequencing read count data by taking confounders into account. Together the methods have increased the power and sensitivity of detection and interpretation of pathogenic variants, leading to diagnostic rates of 10-35% in rare diseases. In this review, we provide an overview of the methods used for RNA sequencing and illustrate how these can improve the diagnostic yield of rare diseases.

Features and mechanisms of canonical and noncanonical genomic imprinting

Genomic imprinting is the monoallelic expression of a gene based on parent of origin and is a consequence of differential epigenetic marking between the male and female germlines. Canonically, genomic imprinting is mediated by allelic DNA methylation. However, recently it has been shown that maternal H3K27me3 can result in DNA methylation-independent imprinting, termed "noncanonical imprinting." In this review, we compare and contrast what is currently known about the underlying mechanisms, the role of endogenous retroviral elements, and the conservation of canonical and noncanonical genomic imprinting.

Inducible uniparental chromosome disomy to probe genomic imprinting at single-cell level in brain and beyond

Genomic imprinting is an epigenetic mechanism that results in parental allele-specific expression of ~1% of all genes in mouse and human. Imprinted genes are key developmental regulators and play pivotal roles in many biological processes such as nutrient transfer from the mother to offspring and neuronal development. Imprinted genes are also involved in human disease, including neurodevelopmental disorders, and often occur in clusters that are regulated by a common imprint control region (ICR). In extra-embryonic tissues ICRs can act over large distances, with the largest surrounding Igf2r spanning over 10 million base-pairs. Besides classical imprinted expression that shows near exclusive maternal or paternal expression, widespread biased imprinted expression has been identified mainly in brain. In this review we discuss recent developments mapping cell type specific imprinted expression in extra-embryonic tissues and neocortex in the mouse. We highlight the advantages of using an inducible uniparental chromosome disomy (UPD) system to generate cells carrying either two maternal or two paternal copies of a specific chromosome to analyze the functional consequences of genomic imprinting. Mosaic Analysis with Double Markers (MADM) allows fluorescent labeling and concomitant induction of UPD sparsely in specific cell types, and thus to over-express or suppress all imprinted genes on that chromosome. To illustrate the utility of this technique, we explain how MADM-induced UPD revealed new insights about the function of the well-studied Cdkn1c imprinted gene, and how MADM-induced UPDs led to identification of highly cell type specific phenotypes related to perturbed imprinted expression in the mouse neocortex. Finally, we give an outlook on how MADM could be used to probe cell type specific imprinted expression in other tissues in mouse, particularly in extra-embryonic tissues.

Single-cell RNA-seq analysis of mouse preimplantation embryos by third-generation sequencing

The development of next generation sequencing (NGS) platform-based single-cell RNA sequencing (scRNA-seq) techniques has tremendously changed biological researches, while there are still many questions that cannot be addressed by them due to their short read lengths. We developed a novel scRNA-seq technology based on third-generation sequencing (TGS) platform (single-cell amplification and sequencing of full-length RNAs by Nanopore platform, SCAN-seq). SCAN-seq exhibited high sensitivity and accuracy comparable to NGS platform-based scRNA-seq methods. Moreover, we captured thousands of unannotated transcripts of diverse types, with high verification rate by reverse transcription PCR (RT-PCR)–coupled Sanger sequencing in mouse embryonic stem cells (mESCs). Then, we used SCAN-seq to analyze the mouse preimplantation embryos. We could clearly distinguish cells at different developmental stages, and a total of 27,250 unannotated transcripts from 9,338 genes were identified, with many of which showed developmental stage-specific expression patterns. Finally, we showed that SCAN-seq exhibited high accuracy on determining allele-specific gene expression patterns within an individual cell. SCAN-seq makes a major breakthrough for single-cell transcriptome analysis field.

This study describes a novel single-cell RNA-seq technology called SCAN-seq which can capture the full-length transcripts in single cells based on the third-generation Nanopore sequencing platform, and demonstrates its performance on mouse preimplantation embryos.

Cell-Type Specificity of Genomic Imprinting in Cerebral Cortex

In mammalian genomes, a subset of genes is regulated by genomic imprinting, resulting in silencing of one parental allele. Imprinting is essential for cerebral cortex development, but prevalence and functional impact in individual cells is unclear. Here, we determined allelic expression in cortical cell types and established a quantitative platform to interrogate imprinting in single cells. We created cells with uniparental chromosome disomy (UPD) containing two copies of either the maternal or the paternal chromosome; hence, imprinted genes will be 2-fold overexpressed or not expressed. By genetic labeling of UPD, we determined cellular phenotypes and transcriptional responses to deregulated imprinted gene expression at unprecedented single-cell resolution. We discovered an unexpected degree of cell-type specificity and a novel function of imprinting in the regulation of cortical astrocyte survival. More generally, our results suggest functional relevance of imprinted gene expression in glial astrocyte lineage and thus for generating cortical cell-type diversity.

Quantifying Genomic Imprinting at Tissue and Cell Resolution in the Brain

Imprinted genes are a group of ~150 genes that are preferentially expressed from one parental allele owing to epigenetic marks asymmetrically distributed on inherited maternal and paternal chromosomes. Altered imprinted gene expression causes human brain disorders such as Prader-Willi and Angelman syndromes and additional rare brain diseases. Research data principally obtained from the mouse model revealed how imprinted genes act in the normal and pathological brain. However, a better understanding of imprinted gene functions calls for building detailed maps of their parent-of-origin-dependent expression and of associated epigenetic signatures. Here we review current methods for quantifying genomic imprinting at tissue and cell resolutions, with a special emphasis on methods to detect parent-of-origin dependent expression and their applications to the brain. We first focus on bulk RNA-sequencing, the main method to detect parent-of-origin-dependent expression transcriptome-wide. We discuss the benefits and caveats of bulk RNA-sequencing and provide a guideline to use it on F1 hybrid mice. We then review methods for detecting parent-of-origin-dependent expression at cell resolution, including single-cell RNA-seq, genetic reporters, and molecular probes. Finally, we provide an overview of single-cell epigenomics technologies that profile additional features of genomic imprinting, including DNA methylation, histone modifications and chromatin conformation and their combination into sc-multimodal omics approaches, which are expected to yield important insights into genomic imprinting in individual brain cells.

MeCP2 is involved in random mono-allelic expression for a subset of human autosomal genes

Widespread random monoallelic gene expression (RMAE) effects influence about 10% of human genes. However, the mechanisms by which RME of autosomal genes is established and those by which it is maintained both remain open questions. Because the choice of allelic expression is randomly performed cell-by-cell, the RMAE mechanism is not observable in non-clonal cell populations or in whole tissues. Several target genes of MeCP2, the gene involved in Rett syndrome (RTT), have been previously described as subject to RMAE, suggesting that MeCP2 may be involved in the establishment and/or maintenance of RME of autosomal genes. To improve our knowledge on this largely unknown phenomenon, and to study the role of MeCP2 in RMAE, we compared RMA gene expression profiles in clonal cell cultures expressing wild-type MeCP2 versus mutant MeCP2 from a RTT patient carrying a pathogenic non-sense variant. Our data clearly demonstrated that MeCP2 deficiency does not affect significantly allelic gene expression of X-linked genes, imprinted genes as well as the RMAE profile in the majority of genes. However, the functional deficiency in MeCP2 appeared to disrupt the mono-allelic or the bi-allelic expression of at least 49 genes allowing us to define a specific signature of MECP2 mutated clones.

Loss of Imprinting in Human Placentas Is Widespread, Coordinated, and Predicts Birth Phenotypes

Genomic imprinting leads to mono-allelic expression of genes based on parent of origin. Therian mammals and angiosperms evolved this mechanism in nutritive tissues, the placenta, and endosperm, where maternal and paternal genomes are in conflict with respect to resource allocation. We used RNA-seq to analyze allelic bias in the expression of 91 known imprinted genes in term human placentas from a prospective cohort study in Mali. A large fraction of the imprinted exons (39%) deviated from mono-allelic expression. Loss of imprinting (LOI) occurred in genes with either maternal or paternal expression bias, albeit more frequently in the former. We characterized LOI using binomial generalized linear mixed models. Variation in LOI was predominantly at the gene as opposed to the exon level, consistent with a single promoter driving the expression of most exons in a gene. Some genes were less prone to LOI than others, particularly lncRNA genes were rarely expressed from the repressed allele. Further, some individuals had more LOI than others and, within a person, the expression bias of maternally and paternally imprinted genes was correlated. We hypothesize that trans-acting maternal effect genes mediate correlated LOI and provide the mother with an additional lever to control fetal growth by extending her influence to LOI of the paternally imprinted genes. Limited evidence exists to support associations between LOI and offspring phenotypes. We show that birth length and placental weight were associated with allelic bias, making this the first comprehensive report of an association between LOI and a birth phenotype.

Pervasive Inter-Individual Variation in Allele-Specific Expression in Monozygotic Twins

Despite being developed from one zygote, heterokaryotypic monozygotic (MZ) co-twins exhibit discordant karyotypes. Epigenomic studies in biological samples from heterokaryotypic MZ co-twins are of the most significant value for assessing the effects on gene- and allele-specific expression of an extranumerary chromosomal copy or structural chromosomal disparities in otherwise nearly identical germline genetic contributions. Here, we use RNA-Seq data from existing repositories to establish within-pair correlations for the breadth and magnitude of allele-specific expression (ASE) in heterokaryotypic MZ co-twins discordant for trisomy 21 and maternal 21q inheritance, as well as homokaryotypic co-twins. We show that there is a genome-wide disparity at ASE sites between the heterokaryotypic MZ co-twins. Although most of the disparity corresponds to changes in the magnitude of biallelic imbalance, ASE sites switching from either strictly monoallelic to biallelic imbalance or the reverse occur in few genes that are known or predicted to be imprinted, subject to X-chromosome inactivation or A-to-I(G) RNA edited. We also uncovered comparable ASE differences between homokaryotypic MZ twins. The extent of ASE discordance in MZ twins (2.7%) was about 10-fold lower than the expected between pairs of unrelated, non-twin males or females. The results indicate that the observed within-pair dissimilarities in breadth and magnitude of ASE sites in the heterokaryotypic MZ co-twins could not solely be attributable to the aneuploidy and the missing allelic heritability at 21q.

The effects of placental long noncoding RNA H19 polymorphisms and promoter methylation on H19 expression in association with preeclampsia susceptibility

The effect of DNA methylation on gene expression triggered it as a susceptibility factor in various diseases including preeclampsia (PE). The pathogenesis of PE is closely associated with the methylation status and genetic variants of relevant genes. Therefore, the aim of the study was to investigate the possible impacts of the placental DNA methylation and rs3741219, rs217727, and rs2107425 polymorphisms of the H19 gene on the PE susceptibility as well as the its mRNA expression. Moreover, eight haplotypes of three loci in the H19 gene were analyzed. In this case-control study, the placentas of 107 preeclamptic and 113 non-preeclamptic women were collected after delivery. The methylation status was assessed by methylation-specific polymerase chain reaction (PCR). The H19 polymorphisms were genotyped using polymerase chain reaction-restriction fragment length polymorphism or amplification refractory mutation system-polymerase chain reaction methods. The quantitative real time PCR was used for mRNA expression assay. The placental H19 rs3741219 and rs2107425 polymorphisms were not associated with PE. However, H19 rs217727CT and TT genotypes might be associated with a 9.2- and 17.7-fold increased risk of PE, respectively. The T_rs3741219 C_rs217727 C_rs2107425 and T_rs3741219 C_rs217727 T_rs2107425 haplotypes were significantly lower, whereas the T_rs3741219 T_rs217727 C_rs2107425 and C_rs3741219 T_rs217727 C_rs2107425 haplotypes were significantly higher in PE women. Promoter but not upstream region hypermethylation of H19 gene could be led to decreased risk of PE (MM vs. UM + UU). No significant difference was observed in the placental mRNA expression between two groups. The H19 expression was significantly higher in women with unmethylated (UU), compared to methylated promoter (MM). The H19 expression was 17- and 15-fold higher in H19-rs2107425 CC and CT genotypes in PE women. In conclusion, the H19 rs2107425 polymorphism was associated with a higher risk of PE and increased H19 mRNA expression. The promoter hypermethylation of H19 gene was associated with a lower risk of PE and decreased H19 mRNA expression.

A Bayesian mixture model for the analysis of allelic expression in single cells

Allele-specific expression (ASE) at single-cell resolution is a critical tool for understanding the stochastic and dynamic features of gene expression. However, low read coverage and high biological variability present challenges for analyzing ASE. We demonstrate that discarding multi-mapping reads leads to higher variability in estimates of allelic proportions, an increased frequency of sampling zeros, and can lead to spurious findings of dynamic and monoallelic gene expression. Here, we report a method for ASE analysis from single-cell RNA-Seq data that accurately classifies allelic expression states and improves estimation of allelic proportions by pooling information across cells. We further demonstrate that combining information across cells using a hierarchical mixture model reduces sampling variability without sacrificing cell-to-cell heterogeneity. We applied our approach to re-evaluate the statistical independence of allelic bursting and track changes in the allele-specific expression patterns of cells sampled over a developmental time course.

Single cell transcriptome in aneuploidies reveals mechanisms of gene dosage imbalance

Aneuploidy is a major source of gene dosage imbalance due to copy number alterations (CNA), and viable human trisomies are model disorders of altered gene expression. We study gene and allele-specific expression (ASE) of 9668 single-cell fibroblasts from trisomy 21 (T21) discordant twins and from mosaic T21, T18, T13 and T8. We examine 928 single cells with deep scRNAseq. Expected and observed overexpression of trisomic genes in trisomic vs. diploid bulk RNAseq is not detectable in trisomic vs. diploid single cells. Instead, for trisomic genes with low-to-average expression, their altered gene dosage is mainly due to the higher fraction of trisomic cells simultaneously expressing these genes, in agreement with a stochastic 2-state burst-like model of transcription. These results, confirmed in a further analysis of 8740 single fibroblasts with shallow scRNAseq, suggest that the specific transcriptional profile of each gene contributes to the phenotypic variability of trisomies. We propose an improved model to understand the effects of CNA and, generally, of gene regulation on gene dosage imbalance.

Genome imprinting in stem cells: A mini-review

Genomic imprinting is an epigenetic process result in silencing of one of the two alleles (maternal or paternal) based on the parent of origin. Dysregulation of imprinted genes results in detectable developmental and differential abnormalities. Epigenetics erasure is required for resetting the cell identity to a ground state during the production of induced pluripotent stem (iPS) cells from somatic cells. There are some contradictory reports regarding the status of the imprinting marks in the genome of iPS cells. Additionally, many studies highlighted the existence of subtle differences in the imprinting loci between different types of iPS cells and embryonic stem (ES) cells. These observations could ultimately undermine the use of patient-derived iPS cells for regenerative medicine.

How Does Reprogramming to Pluripotency Affect Genomic Imprinting?

Human induced Pluripotent Stem Cells (hiPSCs) have the capacity to generate a wide range of somatic cells, thus representing an ideal tool for regenerative medicine. Patient-derived hiPSCs are also used for in vitro disease modeling and drug screenings. Several studies focused on the identification of DNA mutations generated, or selected, during the derivation of hiPSCs, some of which are known to drive cancer formation. Avoiding such stable genomic aberrations is paramount for successful use of hiPSCs, but it is equally important to ensure that their epigenetic information is correct, given the critical role of epigenetics in transcriptional regulation and its involvement in a plethora of pathologic conditions. In this review we will focus on genomic imprinting, a prototypical epigenetic mechanism whereby a gene is expressed in a parent-of-origin specific manner, thanks to the differential methylation of specific DNA sequences. Conventional hiPSCs are thought to be in a pluripotent state primed for differentiation. They display a hypermethylated genome with an unexpected loss of DNA methylation at imprinted loci. Several groups recently reported the generation of hiPSCs in a more primitive developmental stage, called naïve pluripotency. Naïve hiPSCs share several features with early human embryos, such as a global genome hypomethylation, which is also accompanied by a widespread loss of DNA methylation at imprinted loci. Given that loss of imprinting has been observed in genetic developmental disorders as well as in a wide range of cancers, it is fundamental to make sure that hiPSCs do not show such epigenetic aberrations. We will discuss what specific imprinted genes, associated with human pathologies, have been found commonly misregulated in hiPSCs and suggest strategies to effectively detect and avoid such undesirable epigenetic abnormalities.

Transcriptional profiling at the DLK1/MEG3 domain explains clinical overlap between imprinting disorders

Imprinting disorders (IDs) often affect growth in humans, leading to diseases with overlapping features, regardless of the genomic region affected. IDs related to hypomethylation of the human 14q32.2 region and its DLK1/MEG3 domain are associated with Temple syndrome (TS14). TS14 is a rare type of growth retardation, the clinical signs of which overlap considerably with those of Silver-Russell syndrome (SRS), another ID related to IGF2 down-regulation at 11p15.5 region. We show that 14q32.2 hypomethylation affects expression, not only for genes at this locus but also for other imprinted genes, and especially lowers IGF2 levels at 11p15.5. Furthermore, expression of nonimprinted genes is also affected, some of which are also deregulated in SRS patients. These findings highlight the epigenetic regulation of gene expression at the DLK1/MEG3 domain. Expression profiling of TS14 and SRS patients highlights common signatures, which may account for the clinical overlap observed between TS14 and SRS.

Extensive cellular heterogeneity of X inactivation revealed by single-cell allele-specific expression in human fibroblasts

X-chromosome inactivation (XCI) provides a dosage compensation mechanism where, in each female cell, one of the two X chromosomes is randomly silenced. However, some genes on the inactive X chromosome and outside the pseudoautosomal regions escape from XCI and are expressed from both alleles (escapees). We investigated XCI at single-cell resolution combining deep single-cell RNA sequencing with whole-genome sequencing to examine allelic-specific expression in 935 primary fibroblast and 48 lymphoblastoid single cells from five female individuals. In this framework we integrated an original method to identify and exclude doublets of cells. In fibroblast cells, we have identified 55 genes as escapees including five undescribed escapee genes. Moreover, we observed that all genes exhibit a variable propensity to escape XCI in each cell and cell type and that each cell displays a distinct expression profile of the escapee genes. A metric, the Inactivation Score-defined as the mean of the allelic expression profiles of the escapees per cell-enables us to discover a heterogeneous and continuous degree of cellular XCI with extremes represented by "inactive" cells, i.e., cells exclusively expressing the escaping genes from the active X chromosome and "escaping" cells expressing the escapees from both alleles. We found that this effect is associated with cell-cycle phases and, independently, with the XIST expression level, which is higher in the quiescent phase (G0). Single-cell allele-specific expression is a powerful tool to identify novel escapees in different tissues and provide evidence of an unexpected cellular heterogeneity of XCI.

Maximizing the Utility of Cancer Transcriptomic Data

Transcriptomic profiling has been applied to large numbers of cancer samples, by large-scale consortia, including The Cancer Genome Atlas, International Cancer Genome Consortium, and Cancer Cell Line Encyclopedia. Advances in mining cancer transcriptomic data enable us to understand the endless complexity of the cancer transcriptome and thereby to discover new biomarkers and therapeutic targets. In this paper, we review computational resources for deep mining of transcriptomic data to identify, quantify, and determine the functional effects and clinical utility of transcriptomic events, including noncoding RNAs, post-transcriptional regulation, exogenous RNAs, and transcribed genetic variants. These approaches can be applied to other complex diseases, thereby greatly leveraging the impact of this work.

Parent of origin gene expression in a founder population identifies two new candidate imprinted genes at known imprinted regions

Genomic imprinting is the phenomena that leads to silencing of one copy of a gene inherited from a specific parent. Mutations in imprinted regions have been involved in diseases showing parent of origin effects. Identifying genes with evidence of parent of origin expression patterns in family studies allows the detection of more subtle imprinting. Here, we use allele specific expression in lymphoblastoid cell lines from 306 Hutterites related in a single pedigree to provide formal evidence for parent of origin effects. We take advantage of phased genotype data to assign parent of origin to RNA-seq reads in individuals with gene expression data. Our approach identified known imprinted genes, two putative novel imprinted genes, PXDC1 and PWAR6, and 14 genes with asymmetrical parent of origin gene expression. We used gene expression in peripheral blood leukocytes (PBL) to validate our findings, and then confirmed imprinting control regions (ICRs) using DNA methylation levels in the PBLs.

Epigenetic regulation in development: is the mouse a good model for the human?

BACKGROUND

Over the past few years, advances in molecular technologies have allowed unprecedented mapping of epigenetic modifications in gametes and during early embryonic development. This work is allowing a detailed genomic analysis, which for the first time can answer long-standing questions about epigenetic regulation and reprogramming, and highlights differences between mouse and human, the implications of which are only beginning to be explored.

OBJECTIVE AND RATIONALE

In this review, we summarise new low-cell molecular methods enabling the interrogation of epigenetic information in gametes and early embryos, the mechanistic insights these have provided, and contrast the findings in mouse and human.

SEARCH METHODS

Relevant studies were identified by PubMed search.

OUTCOMES

We discuss the levels of epigenetic regulation, from DNA modifications to chromatin organisation, during mouse gametogenesis, fertilisation and pre- and post-implantation development. The recently characterised features of the oocyte epigenome highlight its exceptionally unique regulatory landscape. The chromatin organisation and epigenetic landscape of both gametic genomes are rapidly reprogrammed after fertilisation. This extensive epigenetic remodelling is necessary for zygotic genome activation, but the mechanistic link remains unclear. While the vast majority of epigenetic information from the gametes is erased in pre-implantation development, new insights suggest that repressive histone modifications from the oocyte may mediate a novel mechanism of imprinting. To date, the characterisation of epigenetics in human development has been almost exclusively limited to DNA methylation profiling; these data reinforce that the global dynamics are conserved between mouse and human. However, as we look closer, it is becoming apparent that the mechanisms regulating these dynamics are distinct. These early findings emphasise the importance of investigations of fundamental epigenetic mechanisms in both mouse and humans.

WIDER IMPLICATIONS

Failures in epigenetic regulation have been implicated in human disease and infertility. With increasing maternal age and use of reproductive technologies in countries all over the world, it is becoming ever more important to understand the necessary processes required to establish a developmentally competent embryo. Furthermore, it is essential to evaluate the extent to which these epigenetic patterns are sensitive to such technologies and other adverse environmental exposures.

Longitudinal Effects of Developmental Bisphenol A Exposure on Epigenome-Wide DNA Hydroxymethylation at Imprinted Loci in Mouse Blood

BACKGROUND

Epigenetic machinery plays an important role in genomic imprinting, a developmental process that establishes parent-of-origin-specific monoallelic gene expression. Although a number of studies have investigated the role of 5-methylcytosine in imprinting control, the contribution of 5-hydroxymethylcytosine (5-hmC) to this epigenetic phenomenon remains unclear.

OBJECTIVES

Using matched mouse blood samples (from mice at 2, 4, and 10 months of age), our objective was to examine the effects of perinatal bisphenol A (BPA) exposure (50 μg/kg diet) on longitudinal 5-hmC patterns at imprinted regions. We also aimed to test the hypothesis that 5-hmC would show defined patterns at imprinted genes that persist across the life course.

METHODS

Genome-wide 5-hmC levels were measured using hydroxymethylated DNA immunoprecipitation sequencing (HMeDIP-seq). Modeling of differential hydroxymethylation by BPA exposure was performed using a pipeline of bioinformatics tools, including the csaw R package.

RESULTS

Based on BPA exposure, we identified 5,950 differentially hydroxymethylated regions (DHMRs), including 12 DHMRs that were annotated to murine imprinted genes—Gnas, Grb10, Plagl1, Klf14, Pde10a, Snrpn, Airn, Cmah, Ppp1r9a, Kcnq1, Phactr2, and Pde4d. When visualized, these imprinted gene DHMRs showed clear, consistent patterns of differential 5-hmC by developmental BPA exposure that persisted throughout adulthood.

CONCLUSIONS

These data show long-term establishment of 5-hmC marks at imprinted loci during development. Further, the effect of perinatal BPA exposure on 5-hmC at specific imprinted loci indicates that developmental exposure to environmental toxicants may alter long-term imprinted gene regulation via an epigenetic mechanism. https://doi.org/10.1289/EHP3441.