dbMAE: the database of autosomal monoallelic expression

Simultaneous brain cell type and lineage determined by scRNA-seq reveals stereotyped cortical development

Mutations are acquired frequently, such that each cell's genome inscribes its history of cell divisions. Common genomic alterations involve loss of heterozygosity (LOH). LOH accumulates throughout the genome, offering large encoding capacity for inferring cell lineage. Using only single-cell RNA sequencing (scRNA-seq) of mouse brain cells, we found that LOH events spanning multiple genes are revealed as tracts of monoallelically expressed, constitutionally heterozygous single-nucleotide variants (SNVs). We simultaneously inferred cell lineage and marked developmental time points based on X chromosome inactivation and the total number of LOH events while identifying cell types from gene expression patterns. Our results are consistent with progenitor cells giving rise to multiple cortical cell types through stereotyped expansion and distinct waves of neurogenesis. This type of retrospective analysis could be incorporated into scRNA-seq pipelines and, compared with experimental approaches for determining lineage in model organisms, is applicable where genetic engineering is prohibited, such as humans.

RNA sequencing-based screen for reactivation of silenced alleles of autosomal genes

In mammalian cells, maternal and paternal alleles usually have similar transcriptional activity. Epigenetic mechanisms such as X-chromosome inactivation (XCI) and imprinting were historically viewed as rare exceptions to this rule. Discovery of autosomal monoallelic autosomal expression (MAE) a decade ago revealed an additional allele-specific mode regulating thousands of mammalian genes. Despite MAE prevalence, its mechanistic basis remains unknown. Using an RNA sequencing-based screen for reactivation of silenced alleles, we identified DNA methylation as key mechanism of MAE mitotic maintenance. In contrast with the all-or-nothing allelic choice in XCI, allele-specific expression in MAE loci is tunable, with exact allelic imbalance dependent on the extent of DNA methylation. In a subset of MAE genes, allelic imbalance was insensitive to DNA demethylation, implicating additional mechanisms in MAE maintenance in these loci. Our findings identify a key mechanism of MAE maintenance and provide basis for understanding the biological role of MAE.

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.

Chromosomal coordination and differential structure of asynchronous replicating regions

Stochastic asynchronous replication timing (AS-RT) is a phenomenon in which the time of replication of each allele is different, and the identity of the early allele varies between cells. By taking advantage of stable clonal pre-B cell populations derived from C57BL6/Castaneous mice, we have mapped the genome-wide AS-RT loci, independently of genetic differences. These regions are characterized by differential chromatin accessibility, mono-allelic expression and include new gene families involved in specifying cell identity. By combining population level mapping with single cell FISH, our data reveal the existence of a novel regulatory program that coordinates a fixed relationship between AS-RT regions on any given chromosome, with some loci set to replicate in a parallel and others set in the anti-parallel orientation. Our results show that AS-RT is a highly regulated epigenetic mark established during early embryogenesis that may be used for facilitating the programming of mono-allelic choice throughout development.

Most regions of the mammalian genome replicate both alleles in a synchronous manner, but some loci have been found to replicate asynchronously and the time of replication of each allele is different. Here the authors, by employing clonal mouse cells from a hybrid strain chart replication timing over the entire genome, using polymorphisms to distinguish between the paternal and maternal alleles.

scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets

BACKGROUND

Recently, pioneering expression quantitative trait loci (eQTL) studies on single cell RNA sequencing (scRNA-seq) data have revealed new and cell-specific regulatory single nucleotide variants (SNVs). Here, we present an alternative QTL-related approach applicable to transcribed SNV loci from scRNA-seq data: scReQTL. ScReQTL uses Variant Allele Fraction (VAFRNA) at expressed biallelic loci, and corelates it to gene expression from the corresponding cell.

RESULTS

Our approach employs the advantage that, when estimated from multiple cells, VAFRNA can be used to assess effects of SNVs in a single sample or individual. In this setting scReQTL operates in the context of identical genotypes, where it is likely to capture RNA-mediated genetic interactions with cell-specific and transient effects. Applying scReQTL on scRNA-seq data generated on the 10 × Genomics Chromium platform using 26,640 mesenchymal cells derived from adipose tissue obtained from three healthy female donors, we identified 1272 unique scReQTLs. ScReQTLs common between individuals or cell types were consistent in terms of the directionality of the relationship and the effect size. Comparative assessment with eQTLs from bulk sequencing data showed that scReQTL analysis identifies a distinct set of SNV-gene correlations, that are substantially enriched in known gene-gene interactions and significant genome-wide association studies (GWAS) loci.

CONCLUSION

ScReQTL is relevant to the rapidly growing source of scRNA-seq data and can be applied to outline SNVs potentially contributing to cell type-specific and/or dynamic genetic interactions from an individual scRNA-seq dataset.

AVAILABILITY

https://github.com/HorvathLab/NGS/tree/master/scReQTL.

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.

Functional effects of protein variants

Genetic and other variations frequently affect protein functions. Scientific articles can contain confusing descriptions about which function or property is affected, and in many cases the statements are pure speculation without any experimental evidence. To clarify functional effects of protein variations of genetic or non-genetic origin, a systematic conceptualisation and framework are introduced. This framework describes protein functional effects on abundance, activity, specificity and affinity, along with countermeasures, which allow cells, tissues and organisms to tolerate, avoid, repair, attenuate or resist (TARAR) the effects. Effects on abundance discussed include gene dosage, restricted expression, mis-localisation and degradation. Enzymopathies, effects on kinetics, allostery and regulation of protein activity are subtopics for the effects of variants on activity. Variation outcomes on specificity and affinity comprise promiscuity, specificity, affinity and moonlighting. TARAR mechanisms redress variations with active and passive processes including chaperones, redundancy, robustness, canalisation and metabolic and signalling rewiring. A framework for pragmatic protein function analysis and presentation is introduced. All of the mechanisms and effects are described along with representative examples, most often in relation to diseases. In addition, protein function is discussed from evolutionary point of view. Application of the presented framework facilitates unambiguous, detailed and specific description of functional effects and their systematic study.

ReQTL: identifying correlations between expressed SNVs and gene expression using RNA-sequencing data

MOTIVATION

By testing for associations between DNA genotypes and gene expression levels, expression quantitative trait locus (eQTL) analyses have been instrumental in understanding how thousands of single nucleotide variants (SNVs) may affect gene expression. As compared to DNA genotypes, RNA genetic variation represents a phenotypic trait that reflects the actual allele content of the studied system. RNA genetic variation at expressed SNV loci can be estimated using the proportion of alleles bearing the variant nucleotide (variant allele fraction, VAFRNA). VAFRNA is a continuous measure which allows for precise allele quantitation in loci where the RNA alleles do not scale with the genotype count. We describe a method to correlate VAFRNA with gene expression and assess its ability to identify genetically regulated expression solely from RNA-sequencing (RNA-seq) datasets.

RESULTS

We introduce ReQTL, an eQTL modification which substitutes the DNA allele count for the variant allele fraction at expressed SNV loci in the transcriptome (VAFRNA). We exemplify the method on sets of RNA-seq data from human tissues obtained though the Genotype-Tissue Expression (GTEx) project and demonstrate that ReQTL analyses are computationally feasible and can identify a subset of expressed eQTL loci.

AVAILABILITY AND IMPLEMENTATION

A toolkit to perform ReQTL analyses is available at https://github.com/HorvathLab/ReQTL.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Complex Autoinflammatory Syndrome Unveils Fundamental Principles of JAK1 Kinase Transcriptional and Biochemical Function

Autoinflammatory disease can result from monogenic errors of immunity. We describe a patient with early-onset multi-organ immune dysregulation resulting from a mosaic, gain-of-function mutation (S703I) in JAK1, encoding a kinase essential for signaling downstream of >25 cytokines. By custom single-cell RNA sequencing, we examine mosaicism with single-cell resolution. We find that JAK1 transcription was predominantly restricted to a single allele across different cells, introducing the concept of a mutational “transcriptotype” that differs from the genotype. Functionally, the mutation increases JAK1 activity and transactivates partnering JAKs, independent of its catalytic domain. S703I JAK1 is not only hypermorphic for cytokine signaling but also neomorphic, as it enables signaling cascades not canonically mediated by JAK1. Given these results, the patient was treated with tofacitinib, a JAK inhibitor, leading to the rapid resolution of clinical disease. These findings offer a platform for personalized medicine with the concurrent discovery of fundamental biological principles.

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Janus kinase (JAK1) mutation underlies monogenic autoinflammatory disease

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S703I mutation enhances downstream signaling by transactivation of partnering JAKs

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Mosaicism and monoallelic expression shape JAK1 transcription patterns

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JAK inhibitor therapy resolves clinical disease

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.

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.

Developmental conservation of microRNA gene localization at the nuclear periphery

microRNAs are of vital importance for the regulation of the adaptive and innate immune responses, modulating gene expression at the post transcriptional level. Although there is cumulative information regarding the steady state mature microRNA levels and their respective targets, little is known about the effect of the three-dimensional chromatin architecture on the transcriptional regulation of microRNA gene loci. Here, we sought to investigate the effect of subnuclear localization on the transcriptional activation of eight murine microRNA loci in the immune system. Our results show that microRNA genes display a preferential monoallelic gene expression profile accompanied with perinuclear localization irrespectively of their transcription status or differentiation state. The expression profile and perinuclear localization are developmentally conserved while microRNA gene loci localization outside constitutive lamin associated domains is cross-species conserved. Our findings provide support for an active nuclear periphery and its role in chromatin organization of the non-coding genome.

Pathogenesis of hypertension in a mouse model for human CLCN2 related hyperaldosteronism

Human primary aldosteronism (PA) can be caused by mutations in several ion channel genes but mouse models replicating this condition are lacking. We now show that almost all known PA-associated CLCN2 mutations markedly increase ClC-2 chloride currents and generate knock-in mice expressing a constitutively open ClC-2 Cl⁻ channel as mouse model for PA. The Clcn2^op allele strongly increases the chloride conductance of zona glomerulosa cells, provoking a strong depolarization and increasing cytoplasmic Ca²⁺ concentration. Clcn2^op mice display typical features of human PA, including high serum aldosterone in the presence of low renin activity, marked hypertension and hypokalemia. These symptoms are more pronounced in homozygous Clcn2^op/op than in heterozygous Clcn2^+/op mice. This difference is attributed to the unexpected finding that only ~50 % of Clcn2^+/op zona glomerulosa cells are depolarized. By reproducing essential features of human PA, Clcn2^op mice are a valuable model to study the pathological mechanisms underlying this disease.

Mutations in the chloride channel ClC-2 have been found in primary aldosteronism (PA). Here, Göppner et al. generate transgenic mice expressing a mutant form of ClC-2 that displays increased chloride currents like patient mutations, and find it recapitulates the key pathological features of PA.

Genome-Wide Analysis of Allele-Specific Expression Patterns in Seventeen Tissues of Korean Cattle (Hanwoo)

The functional hemizygosity could be caused by the MAE of a given gene and it can be one of the sources to affect the phenotypic variation in cattle. We aimed to identify MAE genes across the transcriptome in Korean cattle (Hanwoo). For three Hanwoo family trios, the transcriptome data of 17 tissues were generated in three offspring. Sixty-two MAE genes had a monoallelic expression in at least one tissue. Comparing genotypes among each family trio, the preferred alleles of 18 genes were identified (maternal expression, n = 9; paternal expression, n = 9). The MAE genes are involved in gene regulation, metabolic processes, and immune responses, and in particular, six genes encode transcription factors (FOXD2, FOXM1, HTATSF1, SCRT1, NKX6-2, and UBN1) with tissue-specific expression. In this study, we report genome-wide MAE genes in seventeen tissues of adult cattle. These results could help to elucidate epigenetic effects on phenotypic variation in Hanwoo.

Clinical sequencing: From raw data to diagnosis with lifetime value

High-throughput sequencing (HTS) has revolutionized genetics by enabling the detection of sequence variants at hitherto unprecedented large scale. Despite these advances, however, there are still remaining challenges in the complete coverage of targeted regions (genes, exome or genome) as well as in HTS data analysis and interpretation. Moreover, it is easy to get overwhelmed by the plethora of available methods and tools for HTS. Here, we review the step-by-step process from the generation of sequence data to molecular diagnosis of Mendelian diseases. Highlighting advantages and limitations, this review addresses the current state of (1) HTS technologies, considering targeted, whole-exome, and whole-genome sequencing on short- and long-read platforms; (2) read alignment, variant calling and interpretation; as well as (3) regulatory issues related to genetic counseling, reimbursement, and data storage.

Profiling allele-specific gene expression in brains from individuals with autism spectrum disorder reveals preferential minor allele usage

One fundamental but understudied mechanism of gene regulation in disease is allele-specific expression (ASE), the preferential expression of one allele. We leveraged RNA-sequencing data from human brain to assess ASE in autism spectrum disorder (ASD). When ASE is observed in ASD, the allele with lower population frequency (minor allele) is preferentially more highly expressed than the major allele, opposite to the canonical pattern. Importantly, genes showing ASE in ASD are enriched in those downregulated in ASD postmortem brains and in genes harboring de novo mutations in ASD. Two regions, 14q32 and 15q11, containing all known orphan C/D box small nucleolar RNAs (snoRNAs), are particularly enriched in shifts to higher minor allele expression. We demonstrate that this allele shifting enhances snoRNA-targeted splicing changes in ASD-related target genes in idiopathic ASD and 15q11-q13 duplication syndrome. Together, these results implicate allelic imbalance and dysregulation of orphan C/D box snoRNAs in ASD pathogenesis.

Abnormal Cell Sorting Underlies the Unique X-Linked Inheritance of PCDH19 Epilepsy

X-linked diseases typically exhibit more severe phenotypes in males than females. In contrast, protocadherin 19 (PCDH19) mutations cause epilepsy in heterozygous females but spare hemizygous males. The cellular mechanism responsible for this unique pattern of X-linked inheritance is unknown. We show that PCDH19 contributes to adhesion specificity in a combinatorial manner such that mosaic expression of Pcdh19 in heterozygous female mice leads to striking sorting between cells expressing wild-type (WT) PCDH19 and null PCDH19 in the developing cortex, correlating with altered network activity. Complete deletion of PCDH19 in heterozygous mice abolishes abnormal cell sorting and restores normal network activity. Furthermore, we identify variable cortical malformations in PCDH19 epilepsy patients. Our results highlight the role of PCDH19 in determining cell adhesion affinities during cortical development and the way segregation of WT and null PCDH19 cells is associated with the unique X-linked inheritance of PCDH19 epilepsy.

Regulated Capture of Vκ Gene Topologically Associating Domains by Transcription Factories

Expression of vast repertoires of antigen receptors by lymphocytes, with each cell expressing a single receptor, requires stochastic activation of individual variable (V) genes for transcription and recombination. How this occurs remains unknown. Using single-cell RNA sequencing (scRNA-seq) and allelic variation, we show that individual pre-B cells monoallelically transcribe divergent arrays of Vκ genes, thereby opening stochastic repertoires for subsequent Vκ-Jκ recombination. Transcription occurs upon translocation of Vκ genes to RNA polymerase II arrayed on the nuclear matrix in transcription factories. Transcription is anchored by CTCF-bound sites or E2A-loaded Vκ promotors and continues over large genomic distances delimited only by topological associating domains (TADs). Prior to their monoallelic activation, Vκ loci are transcriptionally repressed by cyclin D3, which prevents capture of Vκ gene containing TADs by transcription factories. Cyclin D3 also represses protocadherin, olfactory, and other monoallelically expressed genes, suggesting a widely deployed mechanism for coupling monoallelic gene activation with cell cycle exit.

Systematic pan-cancer analysis of somatic allele frequency

Imbalanced expression of somatic alleles in cancer can suggest functional and selective features, and can therefore indicate possible driving potential of the underlying genetic variants. To explore the correlation between allele frequency of somatic variants and total gene expression of their harboring gene, we used the unique data set of matched tumor and normal RNA and DNA sequencing data of 5523 distinct single nucleotide variants in 381 individuals across 10 cancer types obtained from The Cancer Genome Atlas (TCGA). We analyzed the allele frequency in the context of the variant and gene functional features and linked it with changes in the total gene expression. We documented higher allele frequency of somatic variants in cancer-implicated genes (Cancer Gene Census, CGC). Furthermore, somatic alleles bearing premature terminating variants (PTVs), when positioned in CGC genes, appeared to be less frequently degraded via nonsense-mediated mRNA decay, indicating possible favoring of truncated proteins by the tumor transcriptome. Among the genes with multiple PTVs with high allele frequency, ARID1, TP53 and NSD1 were known key cancer genes. All together, our analyses suggest that high allele frequency of tumor somatic variants can indicate driving functionality and can serve to identify potential cancer-implicated genes.

Risk alleles of genes with monoallelic expression are enriched in gain-of-function variants and depleted in loss-of-function variants for neurodevelopmental disorders

Over 3000 human genes can be expressed from a single allele in one cell, and from the other allele-or both-in neighboring cells. Little is known about the consequences of this epigenetic phenomenon, monoallelic expression (MAE). We hypothesized that MAE increases expression variability, with a potential impact on human disease. Here, we use a chromatin signature to infer MAE for genes in lymphoblastoid cell lines and human fetal brain tissue. We confirm that across clones MAE status correlates with expression level, and that in human tissue data sets, MAE genes show increased expression variability. We then compare mono- and biallelic genes at three distinct scales. In the human population, we observe that genes with polymorphisms influencing expression variance are more likely to be MAE (P<1.1 × 10-6). At the trans-species level, we find gene expression differences and directional selection between humans and chimpanzees more common among MAE genes (P<0.05). Extending to human disease, we show that MAE genes are under-represented in neurodevelopmental copy number variants (CNVs) (P<2.2 × 10-10), suggesting that pathogenic variants acting via expression level are less likely to involve MAE genes. Using neuropsychiatric single-nucleotide polymorphism (SNP) and single-nucleotide variant (SNV) data, we see that genes with pathogenic expression-altering or loss-of-function variants are less likely MAE (P<7.5 × 10-11) and genes with only missense or gain-of-function variants are more likely MAE (P<1.4 × 10-6). Together, our results suggest that MAE genes tolerate a greater range of expression level than biallelic expression (BAE) genes, and this information may be useful in prediction of pathogenicity.

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.

Gene expression allelic imbalance in ovine brown adipose tissue impacts energy homeostasis

Heritable trait variation within a population of organisms is largely governed by DNA variations that impact gene transcription and protein function. Identifying genetic variants that affect complex functional traits is a primary aim of population genetics studies, especially in the context of human disease and agricultural production traits. The identification of alleles directly altering mRNA expression and thereby biological function is challenging due to difficulty in isolating direct effects of cis-acting genetic variations from indirect trans-acting genetic effects. Allele specific gene expression or allelic imbalance in gene expression (AI) occurring at heterozygous loci provides an opportunity to identify genes directly impacted by cis-acting genetic variants as indirect trans-acting effects equally impact the expression of both alleles. However, the identification of genes showing AI in the context of the expression of all genes remains a challenge due to a variety of technical and statistical issues. The current study focuses on the discovery of genes showing AI using single nucleotide polymorphisms as allelic reporters. By developing a computational and statistical process that addressed multiple analytical challenges, we ranked 5,809 genes for evidence of AI using RNA-Seq data derived from brown adipose tissue samples from a cohort of late gestation fetal lambs and then identified a conservative subgroup of 1,293 genes. Thus, AI was extensive, representing approximately 25% of the tested genes. Genes associated with AI were enriched for multiple Gene Ontology (GO) terms relating to lipid metabolism, mitochondrial function and the extracellular matrix. These functions suggest that cis-acting genetic variations causing AI in the population are preferentially impacting genes involved in energy homeostasis and tissue remodelling. These functions may contribute to production traits likely to be under genetic selection in the population.

Monoallelic Gene Expression in Mammals

Monoallelic expression not due to cis-regulatory sequence polymorphism poses an intriguing problem in epigenetics because it requires the unequal treatment of two segments of DNA that are present in the same nucleus and that can indeed have absolutely identical sequences. Here, I focus on a few recent developments in the field of monoallelic expression that are of particular interest and raise interesting questions for future work. One development is regarding analyses of imprinted genes, in which recent work suggests the possibility that intriguing networks of imprinted genes exist and are important for genetic and physiological studies. Another issue that has been raised in recent years by a number of publications is the question of how skewed allelic expression should be for it to be designated as monoallelic expression and, further, what methods are appropriate or inappropriate for analyzing genomic data to examine allele-specific expression. Perhaps the most exciting recent development in mammalian monoallelic expression is a clever and carefully executed analysis of genetic diversity of autosomal genes subject to random monoallelic expression (RMAE), which provides compelling evidence for distinct evolutionary forces acting on random monoallelically expressed genes.

Analysis of allelic expression patterns in clonal somatic cells by single-cell RNA-seq

Cellular heterogeneity can emerge from the expression of only one parental allele. However, it has remained controversial whether, or to what degree, random monoallelic expression of autosomal genes (aRME) is mitotically inherited (clonal) or stochastic (dynamic) in somatic cells, particularly in vivo. Here we used allele-sensitive single-cell RNA-seq on clonal primary mouse fibroblasts and freshly isolated human CD8⁺ T cells to dissect clonal and dynamic monoallelic expression patterns. Dynamic aRME affected a considerable portion of the cells' transcriptomes, with levels dependent on the cells' transcriptional activity. Notably, clonal aRME was detected, but it was surprisingly scarce (<1% of genes) and mainly affected the most weakly expressed genes. Consequently, the overwhelming majority of aRME occurs transiently within individual cells, and patterns of aRME are thus primarily scattered throughout somatic cell populations rather than, as previously hypothesized, confined to patches of clonally related cells.

The 2016 database issue of Nucleic Acids Research and an updated molecular biology database collection

The 2016 Database Issue of Nucleic Acids Research starts with overviews of the resources provided by three major bioinformatics centers, the U.S. National Center for Biotechnology Information (NCBI), the European Bioinformatics Institute (EMBL-EBI) and Swiss Institute for Bioinformatics (SIB). Also included are descriptions of 62 new databases and updates on 95 databases that have been previously featured in NAR plus 17 previously described elsewhere. A number of papers in this issue deal with resources on nucleic acids, including various kinds of non-coding RNAs and their interactions, molecular dynamics simulations of nucleic acid structure, and two databases of super-enhancers. The protein database section features important updates on the EBI's Pfam, PDBe and PRIDE databases, as well as a variety of resources on pathways, metabolomics and metabolic modeling. This issue also includes updates on popular metagenomics resources, such as MG-RAST, EBI Metagenomics, and probeBASE, as well as a newly compiled Human Pan-Microbe Communities database. A significant fraction of the new and updated databases are dedicated to the genetic basis of disease, primarily cancer, and various aspects of drug research, including resources for patented drugs, their side effects, withdrawn drugs, and potential drug targets. A further six papers present updated databases of various antimicrobial and anticancer peptides. The entire Database Issue is freely available online on the Nucleic Acids Research website (http://nar.oxfordjournals.org/). The NAR online Molecular Biology Database Collection, http://www.oxfordjournals.org/nar/database/c/, has been updated with the addition of 88 new resources and removal of 23 obsolete websites, which brought the current listing to 1685 databases.