Research fellow, Harvard Medical School


I study mechanism of allele specific expression at the level of a cell, a tissue or a whole organism

My main project aims to understand the role of allele specific expression (ASE) in the genotype-phenotype relationship. We hypothesize that a significant yet unappreciated source of phenotypic variability is clonally-stable allelic silencing. To compare expression variability between MAE genes and genes with biallelic expression (BAE), we use tissue specific genes classification by chromatin signature (co-occurrence of H3K27me3 silencing mark and H3K36me3 active mark on the gene body), and expression data (RNA-seq). We predict MAE or BAE status in a tissue and then assess the variance in RNA abundance between MAE and BAE genes in hundreds of GTEx donors. For each gene in a given tissue, we assess variability between GTEx samples. At all expression levels, MAE genes have more variable levels of expression compared to BAE genes. This means that MAE genes contribute disproportionally to expression variation in humans, potentially increasing phenotypic variability. Moreover, our observations may generally be useful in interpreting genetic variation in the context of human 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.

Abstract: 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.Molecular Psychiatry advance online publication, 7 March 2017; doi:10.1038/mp.2017.13.

Pub.: 08 Mar '17, Pinned: 29 Jun '17