Reply to 'High prevalence of clonal monoallelic expression'

Extrinsic and intrinsic drivers of natural killer cell clonality

Clonal expansion of antigen-specific lymphocytes is the fundamental mechanism enabling potent adaptive immune responses and the generation of immune memory. Accompanied by pronounced epigenetic remodeling, the massive proliferation of individual cells generates a critical mass of effectors for the control of acute infections, as well as a pool of memory cells protecting against future pathogen encounters. Classically associated with the adaptive immune system, recent work has demonstrated that innate immune memory to human cytomegalovirus (CMV) infection is stably maintained as large clonal expansions of natural killer (NK) cells, raising questions on the mechanisms for clonal selection and expansion in the absence of re-arranged antigen receptors. Here, we discuss clonal NK cell memory in the context of the mechanisms underlying clonal competition of adaptive lymphocytes and propose alternative selection mechanisms that might decide on the clonal success of their innate counterparts. We propose that the integration of external cues with cell-intrinsic sources of heterogeneity, such as variegated receptor expression, transcriptional states, and somatic variants, compose a bottleneck for clonal selection, contributing to the large size of memory NK cell clones.

Random allelic expression in the adult human body

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

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.

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.

Perspectives on Allele-Specific Expression

Diploidy has profound implications for population genetics and susceptibility to genetic diseases. Although two copies are present for most genes in the human genome, they are not necessarily both active or active at the same level in a given individual. Genomic imprinting, resulting in exclusive or biased expression in favor of the allele of paternal or maternal origin, is now believed to affect hundreds of human genes. A far greater number of genes display unequal expression of gene copies due to cis-acting genetic variants that perturb gene expression. The availability of data generated by RNA sequencing applied to large numbers of individuals and tissue types has generated unprecedented opportunities to assess the contribution of genetic variation to allelic imbalance in gene expression. Here we review the insights gained through the analysis of these data about the extent of the genetic contribution to allelic expression imbalance, the tools and statistical models for gene expression imbalance, and what the results obtained reveal about the contribution of genetic variants that alter gene expression to complex human diseases and phenotypes.

Parental bias in expression and interaction of genes in the equine placenta

Most autosomal genes in the placenta show a biallelic expression pattern. However, some genes exhibit allele-specific transcription depending on the parental origin of the chromosomes on which the copy of the gene resides. Parentally expressed genes are involved in the reciprocal interaction between maternal and paternal genes, coordinating the allocation of resources between fetus and mother. One of the main challenges of studying parental-specific allelic expression (allele-specific expression [ASE]) in the placenta is the maternal cellular remnant at the fetomaternal interface. Horses (Equus caballus) have an epitheliochorial placenta in which both the endometrial epithelium and the epithelium of the chorionic villi are juxtaposed with minimal extension into the uterine mucosa, yet there is no information available on the allelic gene expression of equine chorioallantois (CA). In the current study, we present a dataset of 1,336 genes showing ASE in the equine CA (https://pouya-dini.github.io/equine-gene-db/) along with a workflow for analyzing ASE genes. We further identified 254 potentially imprinted genes among the parentally expressed genes in the equine CA and evaluated the expression pattern of these genes throughout gestation. Our gene ontology analysis implies that maternally expressed genes tend to decrease the length of gestation, while paternally expressed genes extend the length of gestation. This study provides fundamental information regarding parental gene expression during equine pregnancy, a species with a negligible amount of maternal cellular remnant in its placenta. This information will provide the basis for a better understanding of the role of parental gene expression in the placenta during gestation.

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.

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

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

Natural Genetic Variation Reveals Key Features of Epigenetic and Transcriptional Memory in Virus-Specific CD8 T Cells

Stable changes in chromatin states and gene expression in cells of the immune system form the basis for memory of infections and other challenges. Here, we used naturally occurring cis-regulatory variation in wild-derived inbred mouse strains to explore the mechanisms underlying long-lasting versus transient gene regulation in CD8 T cells responding to acute viral infection. Stably responsive DNA elements were characterized by dramatic and congruent chromatin remodeling events affecting multiple neighboring sites and required distinct transcription factor (TF) binding motifs for their accessibility. Specifically, we found that cooperative recruitment of T-box and Runx family transcription factors to shared targets mediated stable chromatin remodeling upon T cell activation. Our observations provide insights into the molecular mechanisms driving virus-specific CD8 T cell responses and suggest a general mechanism for the formation of transcriptional and epigenetic memory applicable to other immune and non-immune cells.

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

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

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