Unbalanced allele expression associated with mutation and disease

HA person carries two copies of most genes, with one copy, or allele, coming from each parent. Although these copies tend to be functionally redundant, traditional genetic theory dictates that biallelic expression, in which both alleles are equally transcribed when a gene is expressed, is nearly universal. But a study published in Cell Reports January assumes something different: that it may be fairly common for cells to preferentially express only one allele of a gene.

Using a model that distinguishes patterns in allele expression from RNA-sequencing data, the researchers found that both alleles in some genes were equally active across all tissues — but for nearly 3,000 genes, cells preferred one allele or the other, showing what the authors call random. . allelic expression (RAE). The authors say that these genes are more likely to acquire harmful mutations, and thus can serve as biomarkers to predict or diagnose disease.

The study was “very interesting,” says McGill University biologist Brian Chen, adding, “I definitely thought this approach was really smart.” Although Chen was not alone in praising the work, the results generated some controversy.

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Biased allele expression is a well-known genetic phenomenon, but it is believed to be rare. However, there are some more common exceptions, such as how cells with two X chromosomes inactivate one of them during development in order to measure the level of expression of X-linked genes that can be toxic in double doses. Scientists have described cases of random monoallelic expression, in which cells only express one allele and suppress the other, but experts disagree about the prevalence of the phenomenon. Some studies They suggested that it occurs in up to 10 percent of genes, Richard SandburgThe geneticist at Karolinska Institutet in Sweden says his experiments indicated that unbalanced expression likely occurs in less than one percent of genes.

Christopher Gregg, a neuroscientist and geneticist at the University of Utah School of Medicine, suspects that biased allele activity is more common than the literature suggests. his former lab have found Widespread evidence of allelic imbalance in mouse brains and cultured cells. “[We] He discovered that there were some genes where the two alleles were quite similar to each other,” Gregg explains. “But there were other genes that just broke off completely.”

Wanting to extend the findings to human tissues, he enlisted former postdoctoral researcher Stephanie Kravitz to analyze a large RNAseq dataset from the Genetic Tissue Expression Consortium (GTEx) that included sequences from more than 15,000 genes in 54 tissues from 832 human donors. From these data, Kravitz calculated the abundance of each allele across tissues.

The researchers then compared the relative gene expression levels of each allele across different tissues within each individual, with the assumption that if two alleles were expressed in a binary fashion, the ratio of total allelic expression should fit a binomial distribution, while randomly expressed alleles would not. As a control, they tested whether the method could distinguish X-linked genes from somatic genes, and indeed, the model described X-linked genes as RAE, validating the model’s ability to discriminate biased expression of alleles.

In all, the analysis selected 2,762 non-X-linked genes that fit the RAE pattern. If accurate, that number represents roughly 10 percent of known human genes. By performing an ontogenetic analysis, which explains the molecular targets and biological processes associated with a group of genes, the researchers found that RAE genes were more susceptible to immune adaptation and cellular plasticity than biallelic genes. On the other hand, biallelic genes are more evolutionarily conserved and are more likely to be related to cell survival, Gregg explains, meaning they are less likely to carry mutations. The researchers also found that biallelic genes tend to be located near the centromere, indicating that they are less prone to recombination, while random allelic genes are more likely to cluster near the ends of the telomere.

An ontology analysis also revealed that RAE genes are linked to the disease, Gregg says. “They are preferentially enriched around the genes present [associated with] It posits that age-related diseases such as cardiovascular disease, cancer, and heart disease” and thus, understanding where and why one allele is expressed more than its counterpart can lead to more accurate health risk assessments or even prognosis.

Moreover, Gregg says, the findings challenge the notion that all a person’s cells function with the same set of genetic blueprints. “If it is the case that there are some cells that express this allele and other cells that express this allele, then they really do have different genotypes,” he explains. “That’s really kind of amazing.”

Chen says that, as an experimentalist, it “makes sense” to him that some genes are tougher than others. He adds that such studies may help scientists narrow down potential disease-causing genes, which could then become targets for future study.

Alexander Mendenhalla geneticist at the University of Washington, writes in an e-mail to the scientist That the study is “wonderful” and that the authors have a “good positive control with inactivated X,” an exciting finding. He agrees with Greg that the study has translational potential. “It suggests that part of a patient’s personalized medicine profile may need to be their gene expression profile, at a level that includes these allelic biases.”

However, not everyone was convinced. Sandberg points out that there is still no mechanistic basis behind what the authors call random allelic expression. “It has not been established on well-established concepts, such as imprinting, X chromosome inactivation, allelic imbalance, or random monoallelic expression,” he notes, thus wondering whether the findings are meaningful. “We don’t know if it would be appropriate to use” the mathematical model used by the authors in the paper, speculating that it might capture unrelated expression phenomena that could be explained by cell-to-cell variation, such as variant cell-specific binding. He says other methods, such as single-cell RNAseq, can give researchers more information about the types of cells they are looking for, and thus help distinguish between phenomena.

Gregg admits that the mechanisms behind random allelic expression are not known, but he sticks with the methodology the team used. He argues that single-cell methods are useful, but have “limited applications” for shaping tissues throughout the body, and can produce “technically muddled data”. He adds that because RAE genes are more susceptible to mutation and associated with disease, they show “important new links” between RAE and the factors that drive differences in humans and are targets for future studies.

Gregg also argues that there are likely multiple mechanics at play. For example, it indicates transcriptional overlap, where neighboring genes with overlapping sequences cannot be active simultaneously. Another possibility is enhancer overlap, where two jinans compete to use the same enhancer. “The truth is, we don’t know the cause” of RAE, says Gregg. “There probably won’t be one solution that explains the whole thing.”

In addition to discovering the mechanisms of RAE, Gregg says he hopes to continue studying the phenomenon in human tissues and its relationship to diseases such as cancer. He hypothesized that RAE could be a biomarker of how dangerous tumors are or how well our body copies DNA as we age.

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