Stochastic choice of allelic expression in human neural stem cells

Inborn errors of immunity: an expanding universe of disease and genetic architecture

Inborn errors of immunity (IEIs) are generally considered to be rare monogenic disorders of the immune system that cause immunodeficiency, autoinflammation, autoimmunity, allergy and/or cancer. Here, we discuss evidence that IEIs need not be rare disorders or exclusively affect the immune system. Namely, an increasing number of patients with IEIs present with severe dysregulations of the central nervous, digestive, renal or pulmonary systems. Current challenges in the diagnosis of IEIs that result from the segregated practice of specialized medicine could thus be mitigated, in part, by immunogenetic approaches. Starting with a brief historical overview of IEIs, we then discuss the technological advances that are facilitating the immunogenetic study of IEIs, progress in understanding disease penetrance in IEIs, the expanding universe of IEIs affecting distal organ systems and the future of genetic, biochemical and medical discoveries in this field.

Population Epigenetics: The Extent of DNA Methylation Variation in Wild Animal Populations

Population epigenetics explores the extent of epigenetic variation and its dynamics in natural populations encountering changing environmental conditions. In contrast to population genetics, the basic concepts of this field are still in their early stages, especially in animal populations. Epigenetic variation may play a crucial role in phenotypic plasticity and local adaptation as it can be affected by the environment, it is likely to have higher spontaneous mutation rate than nucleotide sequences do, and it may be inherited via non-mendelian processes. In this review, we aim to bring together natural animal population epigenetic studies to generate new insights into ecological epigenetics and its evolutionary implications. We first provide an overview of the extent of DNA methylation variation and its autonomy from genetic variation in wild animal population. Second, we discuss DNA methylation dynamics which create observed epigenetic population structures by including basic population genetics processes. Then, we highlight the relevance of DNA methylation variation as an evolutionary mechanism in the extended evolutionary synthesis. Finally, we suggest new research directions by highlighting gaps in the knowledge of the population epigenetics field. As for our results, DNA methylation diversity was found to reveal parameters that can be used to characterize natural animal populations. Some concepts of population genetics dynamics can be applied to explain the observed epigenetic structure in natural animal populations. The set of recent advancements in ecological epigenetics, especially in transgenerational epigenetic inheritance in wild animal population, might reshape the way ecologists generate predictive models of the capacity of organisms to adapt to changing environments.

In Vivo Clonal Analysis Reveals Random Monoallelic Expression in Lymphocytes That Traces Back to Hematopoietic Stem Cells

Evaluating the epigenetic landscape in the stem cell compartment at the single-cell level is essential to assess the cells’ heterogeneity and predict their fate. Here, using a genome-wide transcriptomics approach in vivo, we evaluated the allelic expression imbalance in the progeny of single hematopoietic cells (HSCs) as a read-out of epigenetic marking. After 4 months of extensive proliferation and differentiation, we found that X-chromosome inactivation (XCI) is tightly maintained in all single-HSC derived hematopoietic cells. In contrast, the vast majority of the autosomal genes did not show clonal patterns of random monoallelic expression (RME). However, a persistent allele-specific autosomal transcription in HSCs and their progeny was found in a rare number of cases, none of which has been previously reported. These data show that: 1) XCI and RME in the autosomal chromosomes are driven by different mechanisms; 2) the previously reported high frequency of genes under RME in clones expanded in vitro (up to 15%) is not found in clones undergoing multiple differentiation steps in vivo; 3) prior to differentiation, HSCs have stable patterns of autosomal RME. We propose that most RME patterns in autosomal chromosomes are erased and established de novo during cell lineage differentiation.

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.

X-Chromosome Inactivation and Autosomal Random Monoallelic Expression as "Faux Amis"

X-chromosome inactivation (XCI) and random monoallelic expression of autosomal genes (RMAE) are two paradigms of gene expression regulation where, at the single cell level, genes can be expressed from either the maternal or paternal alleles. X-chromosome inactivation takes place in female marsupial and placental mammals, while RMAE has been described in mammals and also other species. Although the outcome of both processes results in random monoallelic expression and mosaicism at the cellular level, there are many important differences. We provide here a brief sketch of the history behind the discovery of XCI and RMAE. Moreover, we review some of the distinctive features of these two phenomena, with respect to when in development they are established, their roles in dosage compensation and cellular phenotypic diversity, and the molecular mechanisms underlying their initiation and stability.

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.

Genome-wide analysis of allele-specific expression of genes in the model diatom Phaeodactylum tricornutum

Recent advances in next generation sequencing technologies have allowed the discovery of widespread autosomal allele-specific expression (aASE) in mammals and plants with potential phenotypic effects. Extensive numbers of genes with allele-specific expression have been described in the diatom Fragilariopsis cylindrus in association with adaptation to external cues, as well as in Fistulifera solaris in the context of natural hybridization. However, the role of aASE and its extent in diatoms remain elusive. In this study, we investigate allele-specific expression in the model diatom Phaeodactylum tricornutum by the re-analysis of previously published whole genome RNA sequencing data and polymorphism calling. We found that 22% of P. tricornutum genes show moderate bias in allelic expression while 1% show nearly complete monoallelic expression. Biallelic expression associates with genes encoding components of protein metabolism while moderately biased genes associate with functions in catabolism and protein transport. We validated candidate genes by pyrosequencing and found that moderate biases in allelic expression were less stable than monoallelically expressed genes that showed consistent bias upon experimental validations at the population level and in subcloning experiments. Our approach provides the basis for the analysis of aASE in P. tricornutum and could be routinely implemented to test for variations in allele expression under different environmental conditions.

Autosomal Clonal Monoallelic Expression: Natural or Artifactual?

The prevalence of mitotically heritable clonal random monoallelic expression of autosomal genes (aRME) remains controversial. Specifically, presence of clonal aRME is well supported in vitro but remains elusive in vivo. Here, we provide critical insights into this matter and discuss whether prevalent clonal aRME is natural or artifactual.

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

CGGBP1-regulated cytosine methylation at CTCF-binding motifs resists stochasticity

Background

The human CGGBP1 binds to GC-rich regions and interspersed repeats, maintains homeostasis of stochastic cytosine methylation and determines DNA-binding of CTCF. Interdependence between regulation of cytosine methylation and CTCF occupancy by CGGBP1 remains unknown.

Results

By analyzing methylated DNA-sequencing data obtained from CGGBP1-depleted cells, we report that some transcription factor-binding sites, including CTCF, resist stochastic changes in cytosine methylation. By analysing CTCF-binding sites we show that cytosine methylation changes at CTCF motifs caused by CGGBP1 depletion resist stochastic changes. These CTCF-binding sites are positioned at locations where the spread of cytosine methylation in cis depends on the levels of CGGBP1.

Conclusion

Our findings suggest that CTCF occupancy and functions are determined by CGGBP1-regulated cytosine methylation patterns.

The influence of DNA methylation on monoallelic expression

Monoallelic gene expression occurs in diploid cells when only one of the two alleles of a gene is active. There are three main classes of genes that display monoallelic expression in mammalian genomes: (1) imprinted genes that are monoallelically expressed in a parent-of-origin dependent manner; (2) X-linked genes that undergo random X-chromosome inactivation in female cells; (3) random monoallelically expressed single and clustered genes located on autosomes. The heritability of monoallelic expression patterns during cell divisions implies that epigenetic mechanisms are involved in the cellular memory of these expression states. Among these, methylation of CpG sites on DNA is one of the best described modification to explain somatic inheritance. Here, we discuss the relevance of DNA methylation for the establishment and maintenance of monoallelic expression patterns among these three groups of genes, and how this is intrinsically linked to development and cellular states.

Incomplete penetrance in primary immunodeficiency: a skeleton in the closet

Primary immunodeficiencies (PIDs) comprise a diverse group of over 400 genetic disorders that result in clinically apparent immune dysfunction. Although PIDs are classically considered as Mendelian disorders with complete penetrance, we now understand that absent or partial clinical disease is often noted in individuals harboring disease-causing genotypes. Despite the frequency of incomplete penetrance in PID, no conceptual framework exists to categorize and explain these occurrences. Here, by reviewing decades of reports on incomplete penetrance in PID we identify four recurrent themes of incomplete penetrance, namely genotype quality, (epi)genetic modification, environmental influence, and mosaicism. For each of these principles, we review what is known, underscore what remains unknown, and propose future experimental approaches to fill the gaps in our understanding. Although the content herein relates specifically to inborn errors of immunity, the concepts are generalizable across genetic diseases.

Stochastic Gene Choice during Cellular Differentiation

Genes in higher eukaryotes are regulated by long-range interactions, which can determine what combination of genes is expressed in a chromosomal segment. The choice of the genes can display exclusivity, independence, or co-occurrence. We introduced a simple measure to quantify this interdependence in gene expression and differentiated mouse embryonic stem cells to neurons to measure the single-cell expression of the gene isoforms in the protocadherin (Pcdh) cluster, a key component of neuronal diversity. As the neuronal progenitors mature into neurons, expression of the gene isoforms in the Pcdh array is initially concurrent. Even though the number of the expressed genes is increasing during differentiation, the expression shifts toward exclusivity. The expression frequency correlates highly with CTCF binding to the promoters and follows dynamically the changes in the binding during the differentiation. These findings aid in understanding the interplay between cellular differentiation and stochastic gene choice.

Monoallelic expression in melanoma

BACKGROUND

Monoallelic expression (MAE) is a frequent genomic phenomenon in normal tissues, however its role in cancer is yet to be fully understood. MAE is defined as the expression of a gene that is restricted to one allele in the presence of a diploid heterozygous genome. Constitutive MAE occurs for imprinted genes, odorant receptors and random X inactivation. Several studies in normal tissues have showed MAE in approximately 5-20% of the cases. However, little information exists on the MAE rate in cancer. In this study we assessed the presence and rate of MAE in melanoma. The genetic basis of melanoma has been studied in depth over the past decades, leading to the identification of mutations/genetic alterations responsible for melanoma development.

METHODS

To examine the role of MAE in melanoma we used 15 melanoma cell lines and compared their RNA-seq data with genotyping data obtained by the parental TIL (tumor infiltrating lymphocytes). Genotyping was performed using the Illumina HumanOmni1 beadchip. The RNA-seq library preparation and sequencing was performed using the Illumina TruSeq Stranded Total RNA Human Kit and subsequently sequenced using a HiSeq 2500 according to manufacturer's guidelines. By comparing genotyping data with RNA-seq data, we identified SNPs in which DNA genotypes were heterozygous and corresponding RNA genotypes were homozygous. All homozygous DNA genotypes were removed prior to the analysis. To confirm the validity to detect MAE, we examined heterozygous DNA genotypes from X chromosome of female samples as well as for imprinted and olfactory receptor genes and confirmed MAE.

RESULTS

MAE was detected in all 15 cell lines although to a different rate. When looking at the B-allele frequencies we found a preferential pattern of complete monoallelic expression rather then differential monoallelic expression across the 15 melanoma cell lines. As some samples showed high differences in the homozygous and heterozygous call rate, we looked at the single chromosomes and showed that MAE may be explained by underlying large copy number imbalances in some instances. Interestingly these regions included genes known to play a role in melanoma initiation and progression. Nevertheless, some chromosome regions showed MAE without CN imbalances suggesting that additional mechanisms (including epigenetic silencing) may explain MAE in melanoma.

CONCLUSION

The biological implications of MAE are yet to be realized. Nevertheless, our findings suggest that MAE is a common phenomenon in melanoma cell lines. Further analyses are currently being undertaken to evaluate whether MAE is gene/pathway specific and to understand whether MAE can be employed by cancers to achieve a more aggressive phenotype.

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.

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.

Perspective: Is Random Monoallelic Expression a Contributor to Phenotypic Variability of Autosomal Dominant Disorders?

Several factors have been proposed as contributors to interfamilial and intrafamilial phenotypic variability in autosomal dominant disorders, including allelic variation, modifier genes, environmental factors and complex genetic and environmental interactions. However, regardless of the similarity of genetic background and environmental factors, asymmetric limb or trunk anomalies in a single individual and variable manifestation between monozygotic twins have been observed, indicating other mechanisms possibly involved in expressivity of autosomal dominant diseases. One such example is Holt-Oram syndrome (HOS), which is characterized by congenital cardiac defects and forelimb anomalies, mainly attributed to mutations in the TBX5 gene. We hypothesize that monoallelic expression of the TBX5 gene occurs during embryo development, and, in the context of a mutation, random monoallelic expression (RME) can create discrepant functions in a proportion of cells and thus contribute to variable phenotypes. A hybrid mouse model was used to investigate the occurrence of RME with the Tbx5 gene, and single-cell reverse transcription PCR and restriction digestion were performed for limb bud cells from developing embryos (E11.5) of the hybrid mice. RME of Tbx5 was observed in approximately two-thirds of limb bud cells. These results indicate that RME of the Tbx5 gene occurs frequently during embryo development, resulting in a mosaic expression signature (monoallelic, biallelic, or null) that may provide a potential explanation for the widespread phenotypic variability in HOS. This model will further provide novel insights into the variability of autosomal dominant traits and a better understanding of the complex expressivity of disease conditions.

Genome-wide identification of autosomal genes with allelic imbalance of chromatin state

In mammals, monoallelic gene expression can result from X-chromosome inactivation, genomic imprinting, and random monoallelic expression (RMAE). Epigenetic regulation of RMAE is not fully understood. Here we analyze allelic imbalance in chromatin state of autosomal genes using ChIP-seq in a clonal cell line. We identify approximately 3.7% of autosomal genes that show significant differences between chromatin states of two alleles. Allelic regulation is represented among several functional gene categories including histones, chromatin modifiers, and multiple early developmental regulators. Most cases of allelic skew are produced by quantitative differences between two allelic chromatic states that belong to the same gross type (active, silent, or bivalent). Combinations of allelic states of different types are possible but less frequent. When different chromatin marks are skewed on the same gene, their skew is coordinated as a result of quantitative relationships between these marks on each individual allele. Finally, combination of allele-specific densities of chromatin marks is a quantitative predictor of allelic skew in gene expression.

CD-tagging-MS2: detecting allelic expression of endogenous mRNAs and their protein products in single cells

Discriminating between the mRNA and protein outputs of each of the alleles of an endogenous gene in intact cells, is a difficult task. To examine endogenous transcripts originating from a specific allele, we applied Central Dogma tagging (CD-tagging), which is based on a tag insertion into an endogenous gene by creation of a new exon. Previously, CD-tagging was used to tag endogenous proteins. Here we developed a CD-tagging-MS2 approach in which two tags were inserted in tandem; a fluorescent protein tag in conjunction with the mRNA MS2 tag used for tagging mRNAs in cells. A cell clone library of CD-tagged-MS2 genes was generated, and protein and mRNA distributions were examined and characterized in single cells. Taking advantage of having one allele tagged, we demonstrate how the transcriptional activity of all alleles, tagged and untagged, can be identified using single molecule RNA fluorescence in situ hybridization (smFISH). Allele-specific mRNA expression and localization were quantified under normal and stress conditions. The latter generate cytoplasmic stress granules (SGs) that can store mRNAs, and the distribution of the mRNAs within and outside of the SGs was measured. Altogether, CD-tagging-MS2 is a robust and inexpensive approach for direct simultaneous detection of an endogenous mRNA and its translated protein product in the same cell.

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

Interactions between genetic and epigenetic effects shape brain function, behavior, and the risk for mental illness. Random X inactivation and genomic imprinting are epigenetic allelic effects that are well known to influence genetic architecture and disease risk. Less is known about the nature, prevalence, and conservation of other potential epigenetic allelic effects in vivo in the mouse and primate brain. Here we devise genomics, in situ hybridization, and mouse genetics strategies to uncover diverse allelic effects in the brain that are not caused by imprinting or genetic variation. We found allelic effects that are developmental stage and cell type specific, that are prevalent in the neonatal brain, and that cause mosaics of monoallelic brain cells that differentially express wild-type and mutant alleles for heterozygous mutations. Finally, we show that diverse non-genetic allelic effects that impact mental illness risk genes exist in the macaque and human brain. Our findings have potential implications for mammalian brain genetics. VIDEO ABSTRACT.

Landscape of monoallelic DNA accessibility in mouse embryonic stem cells and neural progenitor cells

We developed an allele-specific assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) to genotype and profile active regulatory DNA across the genome. Using a mouse hybrid F₁ system, we found that monoallelic DNA accessibility across autosomes was pervasive, developmentally programmed and composed of several patterns. Genetically determined accessibility was enriched at distal enhancers, but random monoallelically accessible (RAMA) elements were enriched at promoters and may act as gatekeepers of monoallelic mRNA expression. Allelic choice at RAMA elements was stable across cell generations and bookmarked through mitosis. RAMA elements in neural progenitor cells were biallelically accessible in embryonic stem cells but premarked with bivalent histone modifications; one allele was silenced during differentiation. Quantitative analysis indicated that allelic choice at the majority of RAMA elements is consistent with a stochastic process; however, up to 30% of RAMA elements may deviate from the expected pattern, suggesting a regulated or counting mechanism.

Erasure and reestablishment of random allelic expression imbalance after epigenetic reprogramming

Clonal level random allelic expression imbalance and random monoallelic expression provides cellular heterogeneity within tissues by modulating allelic dosage. Although such expression patterns have been observed in multiple cell types, little is known about when in development these stochastic allelic choices are made. We examine allelic expression patterns in human neural progenitor cells before and after epigenetic reprogramming to induced pluripotency, observing that loci previously characterized by random allelic expression imbalance (0.63% of expressed genes) are generally reset to a biallelic state in induced pluripotent stem cells (iPSCs). We subsequently neuralized the iPSCs and profiled isolated clonal neural stem cells, observing that significant random allelic expression imbalance is reestablished at 0.65% of expressed genes, including novel loci not found to show allelic expression imbalance in the original parental neural progenitor cells. Allelic expression imbalance was associated with altered DNA methylation across promoter regulatory regions, with clones characterized by skewed allelic expression being hypermethylated compared to their biallelic sister clones. Our results suggest that random allelic expression imbalance is established during lineage commitment and is associated with increased DNA methylation at the gene promoter.

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.

Random monoallelic expression of genes on autosomes: Parallels with X-chromosome inactivation

Genes are generally expressed from their two alleles, except in some particular cases such as random inactivation of one of the two X chromosomes in female mammals or imprinted genes which are expressed only from the maternal or the paternal allele. A lesser-known phenomenon is random monoallelic expression (RME) of autosomal genes, where genes can be stably expressed in a monoallelic manner, from either one of the parental alleles. Studies on autosomal RME face several challenges. First, RME that is based on epigenetic mechanisms has to be distinguished from biased expression of one allele caused by a DNA sequence polymorphism in a regulatory element. Second, RME should not be confused with transient monoallelic expression often observed in single cell analyses, and that often corresponds to dynamic bursting of expression. Thanks to analyses on clonal cell populations, the existence of RME in cultured cells is now well established. Future studies of RME in vivo will have to overcome tissue heterogeneity and certain technical limitations. Here, we discuss current knowledge on autosomal RME, as well as possible mechanisms controlling these expression patterns and potential implications for development and disease, drawing parallels with what is known for X-chromosome inactivation, a paradigm of random monoallelic expression.

Genes with monoallelic expression contribute disproportionately to genetic diversity in humans

An unexpectedly large number of human autosomal genes are subject to monoallelic expression (MAE). Our analysis of 4,227 such genes uncovers surprisingly high genetic variation across human populations. This increased diversity is unlikely to reflect relaxed purifying selection. Remarkably, MAE genes exhibit an elevated recombination rate and an increased density of hypermutable sequence contexts. However, these factors do not fully account for the increased diversity. We find that the elevated nucleotide diversity of MAE genes is also associated with greater allelic age: variants in these genes tend to be older and are enriched in polymorphisms shared by Neanderthals and chimpanzees. Both synonymous and nonsynonymous alleles of MAE genes have elevated average population frequencies. We also observed strong enrichment of the MAE signature among genes reported to evolve under balancing selection. We propose that an important biological function of widespread MAE might be the generation of cell-to-cell heterogeneity; the increased genetic variation contributes to this heterogeneity.

Transcriptomics analysis of iPSC-derived neurons and modeling of neuropsychiatric disorders

Induced pluripotent stem cell (iPSC)-derived neurons and neural progenitors are great resources for studying neural development and differentiation and their disruptions in disease conditions, and hold the promise of future cell therapy. In general, iPSC lines can be established either specifically from patients with neuropsychiatric disorders or from healthy subjects. The iPSCs can then be induced to differentiate into neural lineages and the iPSC-derived neurons are valuable for various types of cell-based assays that seek to understand disease mechanisms and identify and test novel therapies. In addition, it is an ideal system for gene expression profiling (i.e., transcriptomic analysis), an efficient and cost-effective way to explore the genetic programs regulating neurodevelopment. Moreover, transcriptomic comparison, which can be performed between patient-derived samples and controls, or in control lines in which the expression of specific genes has been disrupted, can uncover convergent gene targets and pathways that are downstream of the hundreds of candidate genes that have been associated with neuropsychiatric disorders. The results, especially after integration with spatiotemporal transcriptomic profiles of normal human brain development, have indeed helped to uncover gene networks, molecular pathways, and cellular signaling that likely play critical roles in disease development and progression. On the other hand, despite the great promise, many challenges remain in the usage of iPSC-derived neurons for modeling neuropsychiatric disorders, for example, how to generate relatively homogenous populations of specific neuronal subtypes that are affected in a particular disorder and how to better address the genetic heterogeneity that exists in the patient population.

Epigenome-Wide Association Study of Tic Disorders

Tic disorders are moderately heritable common psychiatric disorders that can be highly troubling, both in childhood and in adulthood. In this study, we report results obtained in the first epigenome-wide association study (EWAS) of tic disorders. The subjects are participants in surveys at the Netherlands Twin Register (NTR) and the NTR biobank project. Tic disorders were measured with a self-report version of the Yale Global Tic Severity Scale Abbreviated version (YGTSS-ABBR), included in the 8th wave NTR data collection (2008). DNA methylation data consisted of 411,169 autosomal methylation sites assessed by the Illumina Infinium HumanMethylation450 BeadChip Kit (HM450k array). Phenotype and DNA methylation data were available in 1,678 subjects (mean age = 41.5). No probes reached genome-wide significance (p < 1.2 × 10(-7)). The strongest associated probe was cg15583738, located in an intergenic region on chromosome 8 (p = 1.98 × 10(-6)). Several of the top ranking probes (p < 1 × 10(-4)) were in or nearby genes previously associated with neurological disorders (e.g., GABBRI, BLM, and ADAM10), warranting their further investigation in relation to tic disorders. The top significantly enriched gene ontology (GO) terms among higher ranking methylation sites included anatomical structure morphogenesis (GO:0009653, p = 4.6 × 10-(15)) developmental process (GO:0032502, p = 2.96 × 10(-12)), and cellular developmental process (GO:0048869, p = 1.96 × 10(-12)). Overall, these results provide a first insight into the epigenetic mechanisms of tic disorders. This first study assesses the role of DNA methylation in tic disorders, and it lays the foundations for future work aiming to unravel the biological mechanisms underlying the architecture of this disorder.

dbMAE: the database of autosomal monoallelic expression

Recently, data on ‘random’ autosomal monoallelic expression has become available for the entire genome in multiple human and mouse tissues and cell types, creating a need for better access and dissemination. The database of autosomal monoallelic expression (dbMAE; https://mae.hms.harvard.edu) incorporates data from multiple recent reports of genome-wide analyses. These include transcriptome-wide analyses of allelic imbalance in clonal cell populations based on sequence polymorphisms, as well as indirect identification, based on a specific chromatin signature present in MAE gene bodies. Currently, dbMAE contains transcriptome-wide chromatin identification calls for 8 human and 21 mouse tissues, and describes over 16 000 murine and ∼700 human cases of directly measured biased expression, compiled from allele-specific RNA-seq and genotyping array data. All data are manually curated. To ensure cross-publication uniformity, we performed re-analysis of transcriptome-wide RNA-seq data using the same pipeline. Data are accessed through an interface that allows for basic and advanced searches; all source references, including raw data, are clearly described and hyperlinked. This ensures the utility of the resource as an initial screening tool for those interested in investigating the role of monoallelic expression in their specific genes and tissues of interest.

Random monoallelic expression of autosomal genes: stochastic transcription and allele-level regulation

Random monoallelic expression (RME) of genes represents a striking example of how stochastic molecular processes can result in cellular heterogeneity. Recent transcriptome-wide studies have revealed both mitotically stable and cell-to-cell dynamic forms of autosomal RME, with the latter presumably resulting from burst-like stochastic transcription. Here, we discuss the distinguishing features of these two forms of RME and revisit literature on their nature, pervasiveness and regulation. Finally, we explore how RME may contribute to phenotypic variation, including the incomplete penetrance and variable expressivity often seen in genetic disease.

GABRA2 Alcohol Dependence Risk Allele is Associated with Reduced Expression of Chromosome 4p12 GABAA Subunit Genes in Human Neural Cultures

BACKGROUND

Genetic variation in a region of chromosome 4p12 that includes the GABAA subunit gene GABRA2 has been reproducibly associated with alcohol dependence (AD). However, the molecular mechanisms underlying the association are unknown. This study examined correlates of in vitro gene expression of the AD-associated GABRA2 rs279858*C-allele in human neural cells using an induced pluripotent stem cell (iPSC) model system.

METHODS

We examined mRNA expression of chromosome 4p12 GABAA subunit genes (GABRG1, GABRA2, GABRA4, and GABRB1) in 36 human neural cell lines differentiated from iPSCs using quantitative polymerase chain reaction and next-generation RNA sequencing. mRNA expression in adult human brain was examined using the BrainCloud and BRAINEAC data sets.

RESULTS

We found significantly lower levels of GABRA2 mRNA in neural cell cultures derived from rs279858*C-allele carriers. Levels of GABRA2 RNA were correlated with those of the other 3 chromosome 4p12 GABAA genes, but not other neural genes. Cluster analysis based on the relative RNA levels of the 4 chromosome 4p12 GABAA genes identified 2 distinct clusters of cell lines, a low-expression cluster associated with rs279858*C-allele carriers and a high-expression cluster enriched for the rs279858*T/T genotype. In contrast, there was no association of genotype with chromosome 4p12 GABAA gene expression in postmortem adult cortex in either the BrainCloud or BRAINEAC data sets.

CONCLUSIONS

AD-associated variation in GABRA2 is associated with differential expression of the entire cluster of GABAA subunit genes on chromosome 4p12 in human iPSC-derived neural cell cultures. The absence of a parallel effect in postmortem human adult brain samples suggests that AD-associated genotype effects on GABAA expression, although not present in mature cortex, could have effects on regulation of the chromosome 4p12 GABAA cluster during neural development.

Epigenetic events regulating monoallelic gene expression

In mammals, generally it is assumed that the genes inherited from each parent are expressed to similar levels. However, it is now apparent that in non-sex chromosomes, 6-10% of genes are selected for monoallelic expression. Monoallelic expression or allelic exclusion is established either in an imprinted (parent-of-origin) or a stochastic manner. The stochastic model explains random selection while the imprinted model describes parent-of-origin specific selection of alleles for expression. Allelic exclusion occurs during X chromosome inactivation, parent-of-origin expression of imprinted genes and stochastic monoallelic expression of cell surface molecules, clustered protocadherin (PCDH) genes. Mis-regulation or loss of allelic exclusion contributes to developmental diseases. Epigenetic mechanisms are fundamental players that determine this type of expression despite a homogenous genetic background. DNA methylation and histone modifications are two mediators of the epigenetic phenomena. The majority of DNA methylation is found on cytosines of the CpG dinucleotide in mammals. Several covalent modifications of histones change the electrostatic forces between DNA and histones modifying gene expression. Long-range chromatin interactions organize chromatin into transcriptionally permissive and prohibitive regions leading to simultaneous regulation of gene expression and repression. Non-coding RNAs (ncRNAs) are also players in regulating gene expression. Together, these epigenetic mechanisms fine-tune gene expression levels essential for normal development and survival. In this review, first we discuss what is known about monoallelic gene expression. Then, we focus on the molecular mechanisms that regulate expression of three monoallelically expressed gene classes: the X-linked genes, selected imprinted genes and PCDH genes.

The meta-epigenomic structure of purified human stem cell populations is defined at cis-regulatory sequences

The mechanism and significance of epigenetic variability in the same cell type between healthy individuals are not clear. Here, we purify human CD34+ hematopoietic stem and progenitor cells (HSPCs) from different individuals and find that there is increased variability of DNA methylation at loci with properties of promoters and enhancers. The variability is especially enriched at candidate enhancers near genes transitioning between silent and expressed states, and encoding proteins with leukocyte differentiation properties. Our findings of increased variability at loci with intermediate DNA methylation values, at candidate “poised” enhancers, and at genes involved in HSPC lineage commitment suggest that CD34+ cell subtype heterogeneity between individuals is a major mechanism for the variability observed. Epigenomic studies performed on cell populations, even when purified, are testing collections of epigenomes, or meta-epigenomes. Our findings show that meta-epigenomic approaches to data analysis can provide insights into cell subpopulation structure.

Clonal relationships impact neuronal tuning within a phylogenetically ancient vertebrate brain structure

Understanding how neurons acquire specific response properties is a major goal in neuroscience. Recent studies in mouse neocortex have shown that “sister neurons” derived from the same cortical progenitor cell have a greater probability of forming synaptic connections with one another [1, 2] and are biased to respond to similar sensory stimuli [3, 4]. However, it is unknown whether such lineage-based rules contribute to functional circuit organization across different species and brain regions [5]. To address this question, we examined the influence of lineage on the response properties of neurons within the optic tectum, a visual brain area found in all vertebrates [6]. Tectal neurons possess well-defined spatial receptive fields (RFs) whose center positions are retinotopically organized [7]. If lineage relationships do not influence the functional properties of tectal neurons, one prediction is that the RF positions of sister neurons should be no more (or less) similar to one another than those of neighboring control neurons. To test this prediction, we developed a protocol to unambiguously identify the daughter neurons derived from single tectal progenitor cells in Xenopus laevis tadpoles. We combined this approach with in vivo two-photon calcium imaging in order to characterize the RF properties of tectal neurons. Our data reveal that the RF centers of sister neurons are significantly more similar than would be expected by chance. Ontogenetic relationships therefore influence the fine-scale topography of the retinotectal map, indicating that lineage relationships may represent a general and evolutionarily conserved principle that contributes to the organization of neural circuits.

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We perform in vivo fate mapping of single progenitors in Xenopus laevis optic tectum

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Two-photon calcium imaging reveals similar receptive fields in sister tectal neurons

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Clonal relationships influence the fine-scale topography of the retinotectal map

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This supports a conserved influence of lineage on neuronal response properties

Epigenetic variation in monozygotic twins: a genome-wide analysis of DNA methylation in buccal cells

DNA methylation is one of the most extensively studied epigenetic marks in humans. Yet, it is largely unknown what causes variation in DNA methylation between individuals. The comparison of DNA methylation profiles of monozygotic (MZ) twins offers a unique experimental design to examine the extent to which such variation is related to individual-specific environmental influences and stochastic events or to familial factors (DNA sequence and shared environment). We measured genome-wide DNA methylation in buccal samples from ten MZ pairs (age 8–19) using the Illumina 450k array and examined twin correlations for methylation level at 420,921 CpGs after QC. After selecting CpGs showing the most variation in the methylation level between subjects, the mean genome-wide correlation (rho) was 0.54. The correlation was higher, on average, for CpGs within CpG islands (CGIs), compared to CGI shores, shelves and non-CGI regions, particularly at hypomethylated CpGs. This finding suggests that individual-specific environmental and stochastic influences account for more variation in DNA methylation in CpG-poor regions. Our findings also indicate that it is worthwhile to examine heritable and shared environmental influences on buccal DNA methylation in larger studies that also include dizygotic twins.

Random monoallelic expression: regulating gene expression one allele at a time

Monoallelic gene expression is a remarkable process in which transcription occurs from only one of two homologous alleles in a diploid cell. Interestingly, between 0.5% and 15% of autosomal genes exhibit random monoallelic gene expression, in which different cells express only one allele independently of the underlying genomic sequence, in a cell type-specific manner. Recently, genome-wide studies have increased our understanding of the cell type-specific incidence of random monoallelic gene expression, and how the imbalance in allelic expression is distinguished within the cell and potentially maintained across cell generations. Monoallelic gene expression is likely generated through stochastic independent regulation of the two alleles upon differentiation, and has varied implications for the cell and organism, in particular with respect to disease.

Random monoallelic gene expression increases upon embryonic stem cell differentiation

Random autosomal monoallelic gene expression refers to the transcription of a gene from one of two homologous alleles. We assessed the dynamics of monoallelic expression during development through an allele-specific RNA-sequencing screen in clonal populations of hybrid mouse embryonic stem cells (ESCs) and neural progenitor cells (NPCs). We identified 67 and 376 inheritable autosomal random monoallelically expressed genes in ESCs and NPCs, respectively, a 5.6-fold increase upon differentiation. Although DNA methylation and nuclear positioning did not distinguish the active and inactive alleles, specific histone modifications were differentially enriched between the two alleles. Interestingly, expression levels of 8% of the monoallelically expressed genes remained similar between monoallelic and biallelic clones. These results support a model in which random monoallelic expression occurs stochastically during differentiation and, for some genes, is compensated for by the cell to maintain the required transcriptional output of these genes.

Developmental dynamics and disease potential of random monoallelic gene expression

X chromosome inactivation (XCI) and allelic exclusion of olfactory receptors or immunoglobulin loci represent classic examples of random monoallelic expression (RME). RME of some single copy genes has also been reported, but the in vivo relevance of this remains unclear. Here we identify several hundred RME genes in clonal neural progenitor cell lines derived from embryonic stem cells. RME occurs during differentiation, and, once established, the monoallelic state can be highly stable. We show that monoallelic expression also occurs in vivo, in the absence of DNA sequence polymorphism. Several of the RME genes identified play important roles in development and have been implicated in human autosomal-dominant disorders. We propose that monoallelic expression of such genes contributes to the fine-tuning of the developmental regulatory pathways they control, and, in the context of a mutation, RME can predispose to loss of function in a proportion of cells and thus contribute to disease.

Allelic expression analysis in the brain suggests a role for heterogeneous insults affecting epigenetic processes in autism spectrum disorders

Monoallelic expression, including genomic imprinting, X-chromosome inactivation and random monoallelic expression of autosomal genes are epigenetic phenomena. Genes that are expressed in a monoallelic way may be more vulnerable to genetic or epigenetic mutations. Thus, comprehensive exploration of monoallelic expression in human brains may shed light on complex brain disorders. Autism-related disorders are known to be associated with imprinted genes on chromosome 15. However, it is not clear whether other imprinted regions or other types of monoallelic expression are associated with autism spectrum disorder (ASD). Here, we performed a genome-wide survey of allele expression imbalance (AEI) in the human brain using single-nucleotide polymorphisms (SNPs), in 18 individuals with ASD and 15 controls. Individuals with ASD had the most extreme number of monoallelic expressed SNPs in both the autosomes and the X chromosome. In two cases that were studied in detail, the monoallelic expression was confined to specific brain region or cell type. Using these data, we were also able to define the allelic expression status of known imprinted genes in the human brain and to identify abnormal imprinting in an individual with ASD. Lastly, we developed an analysis of individual-level expression, focusing on the difference of each individual from the mean. We found that individuals with ASD had more genes that were up- or down-regulated in an individual-specific manner. We also identified pathways perturbed in specific individuals. These results underline the heterogeneity in gene regulation in ASD, at the level of both allelic and total expression.

Chromatin signature of widespread monoallelic expression

In mammals, numerous autosomal genes are subject to mitotically stable monoallelic expression (MAE), including genes that play critical roles in a variety of human diseases. Due to challenges posed by the clonal nature of MAE, very little is known about its regulation; in particular, no molecular features have been specifically linked to MAE. In this study, we report an approach that distinguishes MAE genes in human cells with great accuracy: a chromatin signature consisting of chromatin marks associated with active transcription (H3K36me3) and silencing (H3K27me3) simultaneously occurring in the gene body. The MAE signature is present in ∼20% of ubiquitously expressed genes and over 30% of tissue-specific genes across cell types. Notably, it is enriched among key developmental genes that have bivalent chromatin structure in pluripotent cells. Our results open a new approach to the study of MAE that is independent of polymorphisms, and suggest that MAE is linked to cell differentiation.

DOI:http://dx.doi.org/10.7554/eLife.01256.001

Understanding how genes are activated and silenced is one of the central challenges in modern biology. These processes underpin the development of a fertilized egg into a complex organism, and they can also lead to life-threatening diseases when they go wrong. There are two copies of each gene in a human cell, a maternal copy and a paternal copy, and it is thought that both copies are usually regulated together. However, there are exceptions to this rule: for certain genes only the maternal copy is expressed as a protein in some cells, whereas the paternal copy is expressed in other cells.

This form of gene regulation, which is called monoallelic expression, can result in neighboring cells heading down very different paths. In extreme cases, depending on the differences between the two copies of the gene, cells that express one copy may function normally, while cells where the other copy is activated will start forming tumors. However, despite these potentially grave consequences, and early results which suggested that monoallelic expression affected a large number of human and mouse genes, it has proved to be a major technical challenge to identify these genes in most cell types.

Now, Nag, Savova et al. have discovered a molecular signature that can be used to detect monoallelic expression. The signature was found in chromatin, the densely packed structure formed by DNA and proteins inside the cell nucleus. Nag, Savova et al. discovered that the genes that are subject to monoallelic expression are bound with proteins that are modified in two contrasting ways. One modification, which is usually a sign of gene silencing, is prevalent on the inactive copy of the gene, and the other, which often marks active genes, is chiefly present on the active copy.

Nag, Savova et al. report that these modifications are found in different sets of genes in different cell types, indicating distinct genome-wide patterns of monoallelic expression. The chromatin signature approach lets them estimate the fraction of human genes that are subject to monoallelic expression. This number is surprisingly high: about 20% of commonly expressed genes and more than one-third of tissue-specific genes. In a particularly intriguing finding, almost all bivalent genes—a subset of genes that are involved in determining the fate of cell during development—are estimated to become monoallelic when they are activated.

In addition to these unexpected findings, the chromatin signature approach opens the door to exploring monoallelic expression as a form of gene regulation in all types of cells and, ultimately, to understanding how it is involved in both normal development and in disease.

DOI:http://dx.doi.org/10.7554/eLife.01256.002

Random or stochastic monoallelic expressed genes are enriched for neurodevelopmental disorder candidate genes

Random or stochastic monoallelic expressed genes (StMA genes) represent a unique form of monoallelic expression where allelic choice is made at random early in development. The consequential clonal diversity provides opportunity for functional heterozygosity in tissues such as the brain, and can impact on both development and disease. We investigate the relationship of StMA expressed genes previously identified in clonal neural stem cells with the neurodevelopmental disorders autism and schizophrenia. We found that StMA genes show an overrepresentation of schizophrenia risk candidates identified by genome wide association studies from the genetic association database. Similar suggestive enrichment was also found for genes from the NHGRI genome-wide association study catalog and a psychiatric genetics consortium schizophrenia dataset although these latter more robust gene lists did not achieve statistical significance. We also examined multiple sources of copy number variation (CNV) datasets from autism and schizophrenia cohorts. After taking into account total gene numbers and CNV size, both autism and schizophrenia associated CNVs appeared to show an enrichment of StMA genes relative to the control CNV datasets. Since the StMA genes were originally identified in neural stem cells, bias due to the neural transcriptome is possible. To address this, we randomly sampled neural stem cell expressed genes and repeated the tests. After a significant number of iterations, neural stem cell expressed genes did not show an overrepresentation in autism or schizophrenia CNV datasets. Therefore, irrespective of the neural derived transcriptome, StMA genes originally identified in neural stem cells show an overrepresentation in CNVs associated with autism and schizophrenia. If this association is functional, then the regulation (or dysregulation) of this form of allelic expression status within tissues such as the brain may be a contributory risk factor for neurodevelopmental disorders and may also influence disease discordance sometimes observed in monozygotic twins.

Autosomal monoallelic expression: genetics of epigenetic diversity?

In mammals, relative expression of the two parental alleles of many genes is controlled by one of three major epigenetic phenomena: X chromosome inactivation, imprinting, and mitotically stable autosomal monoallelic expression (MAE). MAE affects a large fraction of human autosomal genes and introduces enormous epigenetic heterogeneity in otherwise similar cell populations. Despite its prevalence, many functional and mechanistic aspects of MAE biology remain unknown. Several lines of evidence imply that MAE establishment and maintenance are controlled by a variety of genetic elements. Based on known genomic features regulating X-inactivation and imprinting, we outline likely features of MAE-controlling elements. We also assess implications of MAE for genotype-phenotype relationship, with a focus on haploinsufficiency.

From promises to practical strategies in epigenetic epidemiology

The epigenome has been heralded as a key 'missing piece' of the aetiological puzzle for complex phenotypes across the biomedical sciences. The standard research approaches developed for genetic epidemiology, however, are not necessarily appropriate for epigenetic studies of common disease. Here, we discuss the optimal execution of population-based studies of epigenetic variation, which will contribute to the emerging field of 'epigenetic epidemiology' and emphasize the importance of establishing a causal role in pathology for disease-associated epigenetic changes. We propose that improved understanding of the molecular mechanisms underlying human health and disease are best achieved through carrying out studies of epigenetics in populations as a part of an integrated functional genomics strategy.

Genetic basis of neuronal individuality in the mammalian brain

The mammalian brain is a complex multicellular system involving enormous numbers of neurons. The neuron is the basic functional unit of the brain, and neurons are organized by specialized intercellular connections into circuits with many other neurons. Physiological studies have revealed that individual neurons have remarkably selective response properties, and this individuality is a fundamental requirement for building complex and functionally diverse neural networks. Recent molecular biological studies have revealed genetic bases for neuronal individuality in the mammalian brain. For example, in the rodent olfactory epithelium, individual olfactory neurons express only one type of odorant receptor (OR) out of the over 1000 ORs encoded in the genome. The expressed OR determines the neuron's selective chemosensory response and specifies its axonal targeting to a particular olfactory glomerulus in the olfactory bulb. Neuronal diversity can also be generated in individual cells by the independent and stochastic expression of autosomal alleles, which leads to functional heterozygosity among neurons. Among the many genes that show autosomal stochastic monoallelic expression, approximately 50 members of the clustered protocadherins (Pcdhs) are stochastically expressed in individual neurons in distinct combinations. The clustered Pcdhs belong to a large subfamily of the cadherin superfamily of homophilic cell-adhesion proteins. Loss-of-function analyses show that the clustered Pcdhs have critical functions in the accuracy of axonal projections, synaptic formation, dendritic arborization, and neuronal survival. In addition, cis-tetramers, composed of heteromultimeric clustered Pcdh members, represent selective binding units for cell-cell interactions, and provide exponential numbers of possible cell-surface relationships between individual neurons. The extensive molecular diversity of neuronal cell-surface proteins affects neurons’ individual properties and connectivities. The molecular features of the diverse clustered Pcdh molecules suggest that they provide a genetic basis for neuronal individuality and appropriate neuronal wiring in the brain.