Yael Mandel-Gutfreund Lab
Research Summary
Our lab studies the fundamental mechanisms of gene expression regulation in cells, during normal development and disease states. We combine computational and multi-omics approaches to investigate how transcriptional and post-transcriptional processes interact to control human pluripotency and cell fate decisions. Within this framework, we focus on the regulatory roles of long non-coding RNAs (lncRNAs) and their interactions with transcription factors and epigenetic regulators, aiming to uncover novel RNA-mediated mechanisms of gene control.
Studying the functional relationship between transcription factors and non-coding RNAs
We are currently developing a proteomic-based methodology to uncover the repertoire of dual binding DNA and RNA binding proteins (DRBPs) in human embryonic stem cells (hESCs), motivated by recent evidence demonstrating the ability of transcription factors to bind diverse types of RNA.
MKRN3 and puberty
Central precocious puberty (CPP - defined by premature initiation of puberty) is often associated with loss-of-function mutations in the putative RNA binding protein - Makorin Ring Finger Protein 3 (MKRN3). Moreover, hypothalamic MKRN3 mRNA levels decrease before puberty, suggesting its inhibitory role in puberty onset. Although this decrease is well established, the mechanisms that mediate MKRN3 downregulation is unclear. We are using a combination of high throughput sequencing analyses with experimental work to elucidate the mechanisms that regulate MKRN3 expression in the hypothalamus.
Detection of lncRNA-mediated transcription regulation networks in stem cell differentiation
The existence of a crosstalk between transcriptional and post-transcriptional regulation is well established. In recent years, long non-coding RNAs (lncRNAs) have emerged as key players in fine-tuning genetic expression, acting as a bridge between the different steps of the gene expression pathway. In this study we apply high-throughput methodologies, combining protein-centric and RNA-centric approaches to systematically identify lncRNAs that mediate transcriptional regulation networks.
Statistical algorithms for the detection of Biological insights in single-cell RNA-seq and spatial transcriptomics
We develop algorithms that rely on statistical assumptions or statistical tests to find statistically significant patterns of expression in high-throughput data. These patterns may be indicative of underlying active Biological processes in the studied tissue or cells.
The role of alternative poly-adenylation in gene regulation
The 3’ untranslated region (3’ UTR) of genes plays an important role in post-transcriptional regulation, affecting mRNA stability, localization and translation rate. The 3’ UTR length is determined by the site of poly-adenylation, Multiple sites can give rise to different 3’ UTR lengths (alternative poly-adenylation – APA), producing differentially regulated isoforms. In the lab, we use both bulk and single cell RNA-seq to determine the changes in APA during normal differentiation, or upon viral infection. Using our single cell data we are also studying the variability in isoform usage between cells in a uniform population - “biological noise”.
