Diverse Non-genetic, Allele-Specific Expression Effects Shape Genetic Architecture at the Cellular Level in the Mammalian Brain

Genomic Imprinting and Random Monoallelic Expression

The review discusses the mechanisms of monoallelic expression, such as genomic imprinting, in which gene transcription depends on the parental origin of the allele, and random monoallelic transcription. Data on the regulation of gene activity in the imprinted regions are summarized with a particular focus on the areas controlling imprinting and factors influencing the variability of the imprintome. The prospects of studies of the monoallelic expression are discussed.

The counterpart congenital overgrowth syndromes Beckwith-Wiedemann Syndrome in human and large offspring syndrome in bovine involve alterations in DNA methylation, transcription, and chromatin configuration

Beckwith-Wiedemann Syndrome (BWS, OMIM #130650) is a congenital epigenetic disorder in humans which affects approximately 1 in 10,340 children. The incidence is likely an underestimation as the condition is usually recognized based on observable phenotypes at birth. BWS children have up to a 28% risk of developing tumors and currently, only 80% of patients can be corroborated molecularly (epimutations/variants). It is unknown how the subtypes of this condition are molecularly similar/dissimilar globally, therefore there is a need to deeply characterize the syndrome at the molecular level. Here we characterize the methylome, transcriptome and chromatin configuration of 18 BWS individuals together with the animal model of the condition, the bovine large offspring syndrome (LOS). Sex specific comparisons are performed for a subset of the BWS patients and LOS. Given that this epigenetic overgrowth syndrome has been characterized as a loss-of-imprinting condition, parental allele-specific comparisons were performed using the bovine animal model. In general, the differentially methylated regions (DMRs) detected in BWS and LOS showed significant enrichment for CTCF binding sites. Altered chromosome compartments in BWS and LOS were positively correlated with gene expression changes, and the promoters of differentially expressed genes showed significant enrichment for DMRs, differential topologically associating domains, and differential A/B compartments in some comparisons of BWS subtypes and LOS. We show shared regions of dysregulation between BWS and LOS, including several HOX gene clusters, and also demonstrate that altered DNA methylation differs between the clinically epigenetically identified BWS patients and those identified as having DNA variants (i.e. CDKN1C microdeletion). Lastly, we highlight additional genes and genomic regions that have the potential to serve as targets for biomarker development to improve current molecular methodologies. In summary, our results suggest that genome-wide alternation of chromosome architecture, which is partially caused by DNA methylation changes, also contribute to the development of BWS and LOS.

Random allelic expression in the adult human body

Genes are typically assumed to express both parental alleles similarly, yet cell lines show random allelic expression (RAE) for many autosomal genes that could shape genetic effects. Thus, understanding RAE in human tissues could improve our understanding of phenotypic variation. Here, we develop a methodology to perform genome-wide profiling of RAE and biallelic expression in GTEx datasets for 832 people and 54 tissues. We report 2,762 autosomal genes with some RAE properties similar to randomly inactivated X-linked genes. We found that RAE is associated with rapidly evolving regions in the human genome, adaptive signaling processes, and genes linked to age-related diseases such as neurodegeneration and cancer. We define putative mechanistic subtypes of RAE distinguished by gene overlaps on sense and antisense DNA strands, aggregation in clusters near telomeres, and increased regulatory complexity and inputs compared with biallelic genes. We provide foundations to study RAE in human phenotypes, evolution, and disease.

Differential Allele-Specific Expression Revealed Functional Variants and Candidate Genes Related to Meat Quality Traits in B. indicus Muscle

Traditional transcriptomics approaches have been used to identify candidate genes affecting economically important livestock traits. Regulatory variants affecting these traits, however, remain under covered. Genomic regions showing allele-specific expression (ASE) are under the effect of cis-regulatory variants, being useful for improving the accuracy of genomic selection models. Taking advantage of the better of these two methods, we investigated single nucleotide polymorphisms (SNPs) in regions showing differential ASE (DASE SNPs) between contrasting groups for beef quality traits. For these analyses, we used RNA sequencing data, imputed genotypes and genomic estimated breeding values of muscle-related traits from 190 Nelore (Bos indicus) steers. We selected 40 contrasting unrelated samples for the analysis (N = 20 animals per contrasting group) and used a beta-binomial model to identify ASE SNPs in only one group (i.e., DASE SNPs). We found 1479 DASE SNPs (FDR ≤ 0.05) associated with 55 beef-quality traits. Most DASE genes were involved with tenderness and muscle homeostasis, presenting a co-expression module enriched for the protein ubiquitination process. The results overlapped with epigenetics and phenotype-associated data, suggesting that DASE SNPs are potentially linked to cis-regulatory variants affecting simultaneously the transcription and phenotype through chromatin state modulation.

Variable allelic expression of imprinted genes at the Peg13, Trappc9, Ago2 cluster in single neural cells

Genomic imprinting is an epigenetic process through which genes are expressed in a parent-of-origin specific manner resulting in mono-allelic or strongly biased expression of one allele. For some genes, imprinted expression may be tissue-specific and reliant on CTCF-influenced enhancer-promoter interactions. The Peg13 imprinting cluster is associated with neurodevelopmental disorders and comprises canonical imprinted genes, which are conserved between mouse and human, as well as brain-specific imprinted genes in mouse. The latter consist of Trappc9, Chrac1 and Ago2, which have a maternal allelic expression bias of ∼75% in brain. Findings of such allelic expression biases on the tissue level raise the question of how they are reflected in individual cells and whether there is variability and mosaicism in allelic expression between individual cells of the tissue. Here we show that Trappc9 and Ago2 are not imprinted in hippocampus-derived neural stem cells (neurospheres), while Peg13 retains its strong bias of paternal allele expression. Upon analysis of single neural stem cells and in vitro differentiated neurons, we find not uniform, but variable states of allelic expression, especially for Trappc9 and Ago2. These ranged from mono-allelic paternal to equal bi-allelic to mono-allelic maternal, including biased bi-allelic transcriptional states. Even Peg13 expression deviated from its expected paternal allele bias in a small number of cells. Although the cell populations consisted of a mosaic of cells with different allelic expression states, as a whole they reflected bulk tissue data. Furthermore, in an attempt to identify potential brain-specific regulatory elements across the Trappc9 locus, we demonstrate tissue-specific and general silencer activities, which might contribute to the regulation of its imprinted expression bias.

DNA Methylation Analysis of Imprinted Genes in the Cortex and Hippocampus of Cross-Fostered Mice Selectively Bred for Increased Voluntary Wheel-Running

We have previously shown that high runner (HR) mice (from a line genetically selected for increased wheel-running behavior) have distinct, genetically based, neurobiological phenotypes as compared with non-selected control (C) mice. However, developmental programming effects during early life, including maternal care and parent-of-origin-dependent expression of imprinted genes, can also contribute to variation in physical activity. Here, we used cross-fostering to address two questions. First, do HR mice have altered DNA methylation profiles of imprinted genes in the brain compared to C mice? Second, does maternal upbringing further modify the DNA methylation status of these imprinted genes? To address these questions, we cross-fostered all offspring at birth to create four experimental groups: C pups to other C dams, HR pups to other HR dams, C pups to HR dams, and HR pups to C dams. Bisulfite sequencing of 16 imprinted genes in the cortex and hippocampus revealed that the HR line had altered DNA methylation patterns of the paternally imprinted genes, Rasgrf1 and Zdbf2, as compared with the C line. Both fostering between the HR and C lines and sex modified the DNA methylation profiles for the paternally expressed genes Mest, Peg3, Igf2, Snrpn, and Impact. Ig-DMR, a gene with multiple paternal and maternal imprinted clusters, was also affected by maternal upbringing and sex. Our results suggest that differential methylation patterns of imprinted genes in the brain could contribute to evolutionary increases in wheel-running behavior and are also dependent on maternal upbringing and sex.

Introns control stochastic allele expression bias

Monoallelic expression (MAE) or extreme allele bias can account for incomplete penetrance, missing heritability and non-Mendelian diseases. In cancer, MAE is associated with shorter patient survival times and higher tumor grade. Prior studies showed that stochastic MAE is caused by stochastic epigenetic silencing, in a gene and tissue-specific manner. Here, we used C. elegans to study stochastic MAE in vivo. We found allele bias/MAE to be widespread within C. elegans tissues, presenting as a continuum from fully biallelic to MAE. We discovered that the presence of introns within alleles robustly decreases MAE. We determined that introns control MAE at distinct loci, in distinct cell types, with distinct promoters, and within distinct coding sequences, using a 5'-intron position-dependent mechanism. Bioinformatic analysis showed human intronless genes are significantly enriched for MAE. Our experimental evidence demonstrates a role for introns in regulating MAE, possibly explaining why some mutations within introns result in disease.

Locus specific epigenetic modalities of random allelic expression imbalance

Most autosomal genes are thought to be expressed from both alleles, with some notable exceptions, including imprinted genes and genes showing random monoallelic expression (RME). The extent and nature of RME has been the subject of debate. Here we investigate the expression of several candidate RME genes in F1 hybrid mouse cells before and after differentiation, to define how they become persistently, monoallelically expressed. Clonal monoallelic expression is not present in embryonic stem cells, but we observe high frequencies of monoallelism in neuronal progenitor cells by assessing expression status in more than 200 clones. We uncover unforeseen modes of allelic expression that appear to be gene-specific and epigenetically regulated. This non-canonical allelic regulation has important implications for development and disease, including autosomal dominant disorders and opens up therapeutic perspectives.

Starvation and Climate Change—How to Constrain Cancer Cell Epigenetic Diversity and Adaptability to Enhance Treatment Efficacy

Advanced metastatic cancer is currently not curable and the major barrier to eliminating the disease in patients is the resistance of subpopulations of tumor cells to drug treatments. These resistant subpopulations can arise stochastically among the billions of tumor cells in a patient or emerge over time during therapy due to adaptive mechanisms and the selective pressures of drug therapies. Epigenetic mechanisms play important roles in tumor cell diversity and adaptability, and are regulated by metabolic pathways. Here, I discuss knowledge from ecology, evolution, infectious disease, species extinction, metabolism and epigenetics to synthesize a roadmap to a clinically feasible approach to help homogenize tumor cells and, in combination with drug treatments, drive their extinction. Specifically, cycles of starvation and hyperthermia could help synchronize tumor cells and constrain epigenetic diversity and adaptability by limiting substrates and impairing the activity of chromatin modifying enzymes. Hyperthermia could also help prevent cancer cells from entering dangerous hibernation-like states. I propose steps to a treatment paradigm to help drive cancer extinction that builds on the successes of fasting, hyperthermia and immunotherapy and is achievable in patients. Finally, I highlight the many unknowns, opportunities for discovery and that stochastic gene and allele level epigenetic mechanisms pose a major barrier to cancer extinction that warrants deeper investigation.

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.

aScan: A Novel Method for the Study of Allele Specific Expression in Single Individuals

In diploid organisms, two copies of each allele are normally inherited from parents. Paternal and maternal alleles can be regulated and expressed unequally, which is referred to as allele-specific expression (ASE). In this work, we present aScan, a novel method for the identification of ASE from the analysis of matched individual genomic and RNA sequencing data. By performing extensive analyses of both real and simulated data, we demonstrate that aScan can correctly identify ASE with high accuracy and sensitivity in different experimental settings. Additionally, by applying our method to a small cohort of individuals that are not included in publicly available databases of human genetic variation, we outline the value of possible applications of ASE analysis in single individuals for deriving a more accurate annotation of "private" low-frequency genetic variants associated with regulatory effects on transcription. All in all, we believe that aScan will represent a beneficial addition to the set of bioinformatics tools for the analysis of ASE. Finally, while our method was initially conceived for the analysis of RNA-seq data, it can in principle be applied to any quantitative NGS assay for which matched genotypic and expression data are available. AVAILABILITY: aScan is currently available in the form of an open source standalone software package at: https://github.com/Federico77z/aScan/. aScan version 1.0.3, available at https://github.com/Federico77z/aScan/releases/tag/1.0.3, has been used for all the analyses included in this manuscript. A Docker image of the tool has also been made available at https://github.com/pmandreoli/aScanDocker.

CTCF-Mediated Genome Architecture Regulates the Dosage of Mitotically Stable Mono-allelic Expression of Autosomal Genes

The mechanisms that guide the clonally stable random mono-allelic expression of autosomal genes remain enigmatic. We show that (1) mono-allelically expressed (MAE) genes are assorted and insulated from bi-allelically expressed (BAE) genes through CTCF-mediated chromatin loops; (2) the cell-type-specific dynamics of mono-allelic expression coincides with the gain and loss of chromatin insulator sites; (3) dosage of MAE genes is more sensitive to the loss of chromatin insulation than that of BAE genes; and (4) inactive alleles of MAE genes are significantly more insulated than active alleles and are de-repressed upon CTCF depletion. This alludes to a topology wherein the inactive alleles of MAE genes are insulated from the spatial interference of transcriptional states from the neighboring bi-allelic domains via CTCF-mediated loops. We propose that CTCF functions as a typical insulator on inactive alleles, but facilitates transcription through enhancer-linking on active allele of MAE genes, indicating widespread allele-specific regulatory roles of CTCF.

Complex Economic Behavior Patterns Are Constructed from Finite, Genetically Controlled Modules of Behavior

Complex ethological behaviors could be constructed from finite modules that are reproducible functional units of behavior. Here, we test this idea for foraging and develop methods to dissect rich behavior patterns in mice. We uncover discrete modules of foraging behavior reproducible across different strains and ages, as well as nonmodular behavioral sequences. Modules differ in terms of form, expression frequency, and expression timing and are expressed in a probabilistically determined order. Modules shape economic patterns of feeding, exposure, activity, and perseveration responses. The modular architecture of foraging changes developmentally, and different developmental, genetic, and parental effects are found to shape the expression of specific modules. Dissecting modules from complex patterns is powerful for phenotype analysis. We discover that both parental alleles of the imprinted Prader-Willi syndrome gene Magel2 are functional in mice but regulate different modules. Our study found that complex economic patterns are built from finite, genetically controlled modules.

The principles and mechanisms involved in constructing complex behavior patterns are not well defined. Stacher Hörndli et al. find that complex foraging patterns in mice are constructed from finite modules, defined as significantly reproducible behavioral sequences. Modules are expressed in a probabilistically defined order to construct complex patterns and controlled by genetic mechanisms.

Signatures of sex: Sex differences in gene expression in the vertebrate brain

Women and men differ in disease prevalence, symptoms, and progression rates for many psychiatric and neurological disorders. As more preclinical studies include both sexes in experimental design, an increasing number of sex differences in physiology and behavior have been reported. In the brain, sex-typical behaviors are thought to result from sex-specific patterns of neural activity in response to the same sensory stimulus or context. These differential firing patterns likely arise as a consequence of underlying anatomic or molecular sex differences. Accordingly, gene expression in the brains of females and males has been extensively investigated, with the goal of identifying biological pathways that specify or modulate sex differences in brain function. However, there is surprisingly little consensus on sex-biased genes across studies and only a handful of robust candidates have been pursued in the follow-up experiments. Furthermore, it is not known how or when sex-biased gene expression originates, as few studies have been performed in the developing brain. Here we integrate molecular genetic and neural circuit perspectives to provide a conceptual framework of how sex differences in gene expression can arise in the brain. We detail mechanisms of gene regulation by steroid hormones, highlight landmark studies in rodents and humans, identify emerging themes, and offer recommendations for future research. This article is categorized under: Nervous System Development > Vertebrates: General Principles Gene Expression and Transcriptional Hierarchies > Regulatory Mechanisms Gene Expression and Transcriptional Hierarchies > Sex Determination.

Elimination of Reference Mapping Bias Reveals Robust Immune Related Allele-Specific Expression in Crossbred Sheep

Pervasive allelic variation at both gene and single nucleotide level (SNV) between individuals is commonly associated with complex traits in humans and animals. Allele-specific expression (ASE) analysis, using RNA-Seq, can provide a detailed annotation of allelic imbalance and infer the existence of cis-acting transcriptional regulation. However, variant detection in RNA-Seq data is compromised by biased mapping of reads to the reference DNA sequence. In this manuscript, we describe an unbiased standardized computational pipeline for allele-specific expression analysis using RNA-Seq data, which we have adapted and developed using tools available under open license. The analysis pipeline we present is designed to minimize reference bias while providing accurate profiling of allele-specific expression across tissues and cell types. Using this methodology, we were able to profile pervasive allelic imbalance across tissues and cell types, at both the gene and SNV level, in Texel×Scottish Blackface sheep, using the sheep gene expression atlas data set. ASE profiles were pervasive in each sheep and across all tissue types investigated. However, ASE profiles shared across tissues were limited, and instead, they tended to be highly tissue-specific. These tissue-specific ASE profiles may underlie the expression of economically important traits and could be utilized as weighted SNVs, for example, to improve the accuracy of genomic selection in breeding programs for sheep. An additional benefit of the pipeline is that it does not require parental genotypes and can therefore be applied to other RNA-Seq data sets for livestock, including those available on the Functional Annotation of Animal Genomes (FAANG) data portal. This study is the first global characterization of moderate to extreme ASE in tissues and cell types from sheep. We have applied a robust methodology for ASE profiling to provide both a novel analysis of the multi-dimensional sheep gene expression atlas data set and a foundation for identifying the regulatory and expressed elements of the genome that are driving complex traits in livestock.

New subtypes of allele-specific epigenetic effects: implications for brain development, function and disease

Typically, it is assumed that the maternal and paternal alleles for most genes are equally expressed. Known exceptions include canonical imprinted genes, random X-chromosome inactivation, olfactory receptors and clustered protocadherins. Here, we highlight recent studies showing that allele-specific expression is frequent in the genome and involves subtypes of epigenetic allelic effects that differ in terms of heritability, clonality and stability over time. Different forms of epigenetic allele regulation could have different roles in brain development, function, and disease. An emerging area involves understanding allelic effects in a cell-type and developmental stage-specific manner and determining how these effects influence the impact of genetic variants and mutations on the brain. A deeper understanding of epigenetics at the allele and cellular level in the brain could help clarify the mechanisms underlying phenotypic variance.

Allele-specific RNA imaging shows that allelic imbalances can arise in tissues through transcriptional bursting

Extensive cell-to-cell variation exists even among putatively identical cells, and there is great interest in understanding how the properties of transcription relate to this heterogeneity. Differential expression from the two gene copies in diploid cells could potentially contribute, yet our ability to measure from which gene copy individual RNAs originated remains limited, particularly in the context of tissues. Here, we demonstrate quantitative, single molecule allele-specific RNA FISH adapted for use on tissue sections, allowing us to determine the chromosome of origin of individual RNA molecules in formaldehyde-fixed tissues. We used this method to visualize the allele-specific expression of Xist and multiple autosomal genes in mouse kidney. By combining these data with mathematical modeling, we evaluated models for allele-specific heterogeneity, in particular demonstrating that apparent expression from only one of the alleles in single cells can arise as a consequence of low-level mRNA abundance and transcriptional bursting.

In mammals, most cells of the body contain two genetic datasets: one from the mother and one from the father, and—in theory—these two sets of information could contribute equally to produce the molecules in a given cell. In practice, however, this is not always the case, which can have dramatic implications for many traits, including visible features (such as fur color) and even disease outcomes. However, it remains difficult to measure the parental origin of individual molecules in a given cell and thus to assess what processes lead to an imbalance of the maternal and paternal contribution. We adapted a microscopy technique—called allele-specific single molecule RNA FISH—that uses a combination of fluorescent tags to specifically label one type of molecule, RNA, depending on its origin, for use in mouse kidney sections. Focusing on RNAs that were previously reported to show imbalance, we performed measurements and combined these with mathematical modeling to quantify imbalance in tissues and explain how these can arise. We found that we could recapitulate the observed imbalances using models that only take into account the random processes that produce RNA, without the need to invoke special regulatory mechanisms to create unequal contributions.

Epigenetic and Cellular Diversity in the Brain through Allele-Specific Effects

The benefits of diploidy are considered to involve masking partially recessive mutations and increasing genetic diversity. Here, we review new studies showing evidence for diverse allele-specific expression and epigenetic states in mammalian brain cells, which suggest that diploidy expands the landscape of gene regulatory and expression programs in cells. Allele-specific expression has been thought to be restricted to a few specific classes of genes. However, new studies show novel genomic imprinting effects that are brain-region-, cell-type- and age-dependent. In addition, novel forms of random monoallelic expression that impact many autosomal genes have been described in vitro and in vivo. We discuss the implications for understanding the benefits of diploidy, and the mechanisms shaping brain development, function, and disease.

CIS-Acting Allele-Specific Expression Differences Induced by Alcohol and Impacted by Sex as Well as Parental Genotype of Origin

BACKGROUND

Alcohol use disorders (AUDs) are influenced by complex interactions between the genetics of the individual and their environment. We have previously identified hundreds of polygenic genetic variants between the selectively bred high- and low-alcohol drinking (HAD and LAD) rat lines. Here, we report allele-specific expression (ASE) differences, between the HAD2 and LAD2 rat lines.

METHODS

The HAD2 and LAD2 rats, which have been sequenced, were reciprocally crossed to generate 10 litters of F1 progeny. For 5 of these litters, the sire was HAD2, and for the other 5 litters, the sire was a LAD2. From these 10 litters, 2 males and 2 females were picked from each F1 litter (N = 40 total). The F1 pups were divided, balancing for sex and direction of cross, into an alcohol (15%) versus a water control group. Alcohol drinking started in the middle of adolescence (~postnatal day 35) and lasted 9 weeks. At the end of these treatments, rats were euthanized, the nucleus accumbens was dissected, and RNA was processed for RNA-sequencing and ASE analyses.

RESULTS

Analyses revealed that adolescent ethanol (EtOH) drinking, individual EtOH drinking levels, parentage, and sex-of-animal affected ASEs of about 300 genes. The identified genes included those associated with EtOH metabolism (e.g., Aldh2); neuromodulatory function (e.g., Cckbr, Slc6a7, and Slc1a1); ion channel activity (e.g., Kcnc3); and other synaptic and epigenetic functions.

CONCLUSIONS

These data indicate that EtOH drinking differentially amplified paternal versus maternal allelic contribution to the transcriptome. We hypothesize that this was due, at least in part, to EtOH-induced changes in cis-regulation of polymorphisms previously identified between the HAD2 and LAD2 rat lines. This report highlights the complexity of gene-by-environment interactions mediating a genetic predisposition for, and/or the active development of, AUDs.

The Oxytocin Receptor: From Intracellular Signaling to Behavior

The many facets of the oxytocin (OXT) system of the brain and periphery elicited nearly 25,000 publications since 1930 (see FIGURE 1 , as listed in PubMed), which revealed central roles for OXT and its receptor (OXTR) in reproduction, and social and emotional behaviors in animal and human studies focusing on mental and physical health and disease. In this review, we discuss the mechanisms of OXT expression and release, expression and binding of the OXTR in brain and periphery, OXTR-coupled signaling cascades, and their involvement in behavioral outcomes to assemble a comprehensive picture of the central and peripheral OXT system. Traditionally known for its role in milk let-down and uterine contraction during labor, OXT also has implications in physiological, and also behavioral, aspects of reproduction, such as sexual and maternal behaviors and pair bonding, but also anxiety, trust, sociability, food intake, or even drug abuse. The many facets of OXT are, on a molecular basis, brought about by a single receptor. The OXTR, a 7-transmembrane G protein-coupled receptor capable of binding to either Gαior Gαqproteins, activates a set of signaling cascades, such as the MAPK, PKC, PLC, or CaMK pathways, which converge on transcription factors like CREB or MEF-2. The cellular response to OXT includes regulation of neurite outgrowth, cellular viability, and increased survival. OXTergic projections in the brain represent anxiety and stress-regulating circuits connecting the paraventricular nucleus of the hypothalamus, amygdala, bed nucleus of the stria terminalis, or the medial prefrontal cortex. Which OXT-induced patterns finally alter the behavior of an animal or a human being is still poorly understood, and studying those OXTR-coupled signaling cascades is one initial step toward a better understanding of the molecular background of those behavioral effects.

A UNIFIED STATISTICAL FRAMEWORK FOR SINGLE CELL AND BULK RNA SEQUENCING DATA

Recent advances in technology have enabled the measurement of RNA levels for individual cells. Compared to traditional tissue-level bulk RNA-seq data, single cell sequencing yields valuable insights about gene expression profiles for different cell types, which is potentially critical for understanding many complex human diseases. However, developing quantitative tools for such data remains challenging because of high levels of technical noise, especially the "dropout" events. A "dropout" happens when the RNA for a gene fails to be amplified prior to sequencing, producing a "false" zero in the observed data. In this paper, we propose a Unified RNA-Sequencing Model (URSM) for both single cell and bulk RNA-seq data, formulated as a hierarchical model. URSM borrows the strength from both data sources and carefully models the dropouts in single cell data, leading to a more accurate estimation of cell type specific gene expression profile. In addition, URSM naturally provides inference on the dropout entries in single cell data that need to be imputed for downstream analyses, as well as the mixing proportions of different cell types in bulk samples. We adopt an empirical Bayes' approach, where parameters are estimated using the EM algorithm and approximate inference is obtained by Gibbs sampling. Simulation results illustrate that URSM outperforms existing approaches both in correcting for dropouts in single cell data, as well as in deconvolving bulk samples. We also demonstrate an application to gene expression data on fetal brains, where our model successfully imputes the dropout genes and reveals cell type specific expression patterns.

The emerging landscape of in vitro and in vivo epigenetic allelic effects

Epigenetic mechanisms that cause maternally and paternally inherited alleles to be expressed differently in offspring have the potential to radically change our understanding of the mechanisms that shape disease susceptibility, phenotypic variation, cell fate, and gene expression. However, the nature and prevalence of these effects in vivo have been unclear and are debated. Here, I consider major new studies of epigenetic allelic effects in cell lines and primary cells and in vivo. The emerging picture is that these effects take on diverse forms, and this review attempts to clarify the nature of the different forms that have been uncovered for genomic imprinting and random monoallelic expression (RME). I also discuss apparent discrepancies between in vitro and in vivo studies. Importantly, multiple studies suggest that allelic effects are prevalent and can be developmental stage- and cell type-specific. I propose some possible functions and consider roles for allelic effects within the broader context of gene regulatory networks, cellular diversity, and plasticity. Overall, the field is ripe for discovery and is in need of mechanistic and functional studies.

Characteristics of allelic gene expression in human brain cells from single-cell RNA-seq data analysis

Background

Monoallelic expression of autosomal genes has been implicated in human psychiatric disorders. However, there is a paucity of allelic expression studies in human brain cells at the single cell and genome wide levels.

Results

In this report, we reanalyzed a previously published single-cell RNA-seq dataset from several postmortem human brains and observed pervasive monoallelic expression in individual cells, largely in a random manner. Examining single nucleotide variants with a predicted functional disruption, we found that the “damaged” alleles were overall expressed in fewer brain cells than their counterparts, and at a lower level in cells where their expression was detected. We also identified many brain cell type-specific monoallelically expressed genes. Interestingly, many of these cell type-specific monoallelically expressed genes were enriched for functions important for those brain cell types. In addition, function analysis showed that genes displaying monoallelic expression and correlated expression across neuronal cells from different individual brains were implicated in the regulation of synaptic function.

Conclusions

Our findings suggest that monoallelic gene expression is prevalent in human brain cells, which may play a role in generating cellular identity and neuronal diversity and thus increasing the complexity and diversity of brain cell functions.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4261-x) contains supplementary material, which is available to authorized users.

Knockout of the epilepsy gene Depdc5 in mice causes severe embryonic dysmorphology with hyperactivity of mTORC1 signalling

DEPDC5 mutations have recently been shown to cause epilepsy in humans. Evidence from in vitro studies has implicated DEPDC5 as a negative regulator of mTORC1 during amino acid insufficiency as part of the GATOR1 complex. To investigate the role of DEPDC5 in vivo we generated a null mouse model using targeted CRISPR mutagenesis. Depdc5 homozygotes display severe phenotypic defects between 12.5-15.5 dpc, including hypotrophy, anaemia, oedema, and cranial dysmorphology as well as blood and lymphatic vascular defects. mTORC1 hyperactivity was observed in the brain of knockout embryos and in fibroblasts and neurospheres isolated from knockout embryos and cultured in nutrient deprived conditions. Heterozygous mice appeared to be normal and we found no evidence of increased susceptibility to seizures or tumorigenesis. Together, these data support mTORC1 hyperactivation as the likely pathogenic mechanism that underpins DEPDC5 loss of function in humans and highlights the potential utility of mTORC1 inhibitors in the treatment of DEPDC5-associated epilepsy.