(Some) Possible thesis research projects

One of the most abundant and yet understudied type of element in the human genome are transposable elements (TEs), also known as “jumping genes” because of their capacity to integrate in multiple sites of the genome. Many TEs are widely expressed throughout mammalian embryo development and afterwards kept inactive in somatic cells by epigenetic defence mechanisms such as DNA methylation or chromatin remodeling. However, it has been observed that these mechanisms sometimes fail to work as expected and the aberrant expression of TEs has been associated with the onset and progression of several diseases. TEs that integrate through an RNA intermediate, known as retrotransposons, can lead to multiple and nearly identical copies of the same TE across the genome. This results in a non-trivial amount of multimapping reads in RNA-seq experiments, which are typically discarded in standard analysis pipelines, requiring specialized software for reliably quantifying TE expression from those reads. We have developed atena (https://bioconductor.org/packages/atena), an R/Bioconductor package for the quantification of TE expression from bulk RNA-seq data. In this project we will extend the methodology and the software to quantify TE expression from single-cell and single-nucleus RNA-seq data, by integrating an empirical Bayes framework into the current expectation-maximization (EM) algorithm and/or combining it with pseudobulk approaches.