BMSIP Projects 2021
2021
| Project Title | PI | Intern |
| Methods for detecting hybrid exons using RNA-Seq data | Ana Fiszbein, Department of Biology | Sana Majid |
| Molecular characterization of unstable antibody light chains in AL amyloidosis and multiple myeloma | Gareth Morgan, Department of Medicine/Amyloidosis Center | Allison Nau |
| Quorum Sensing Regulated Motility Genes in Roseovarius Strains | Melisa Osborne/Daniel Segrè, Department of Biology and Bioinformatics | Mae Rose Gott |
Methods for detecting hybrid exons using RNA-Seq data top
PI: Ana Fiszbein, Department of Biology
Intern: Sana Majid
Our lab uses a combination of high-throughput, functional genomics, bioinformatics and molecular approaches to study the co-transcriptional gene regulation of mammalian expression programs. We recently observed that alternative transcription start sites often arise close to annotated internal exons, creating “hybrid” exons that can be used as both terminal or internal exons. This project involves the development of statistical tools and algorithms to analyze RNA-sequencing data across different tissues, in order to characterize the features of hybrid exons. We will ask when and why hybrid exons become hybrid? And, in which tissues are they used as terminal exons or internal exons? We will use machine learning to investigate the sequences determinants of hybrid exons and single-cell RNA sequencing to explore whether hybrid exons can be used as terminal and internal in the same cells.
Molecular characterization of unstable antibody light chains in AL amyloidosis and multiple myeloma top
PI: Gareth Morgan, Department of Medicine/Amyloidosis Center
Intern: Allison Nau
AL amyloidosis and multiple myeloma are both cancers of antibody-secreting plasma cells. A subset of plasma cell cancers secrete unstable antibody light chains, which can aggregate as insoluble amyloid fibrils, leading to progressive and eventually fatal tissue damage. We are interested in understanding the differences between the antibody proteins that influence whether amyloidosis will occur, and the differences between the plasma cells that secrete them. We will use protein sequence analysis to look at the light chains, and high throughput gene expression data to look at the cells which secrete them. The intern will analyze Amyloidosis Center’s database of disease-associated antibody light chain sequences (~4000 unique antibody sequences) using the Observed Antibody Space repertoire sequencing database (~108 antibody sequences), and the Multiple Myeloma Research Foundation CoMMpass RNA-sequencing datasets.
Quorum Sensing Regulated Motility Genes in Roseovarius Strains top
PI: Melisa Osborne/Daniel Segrè, Department of Biology and Bioinformatics
Intern: Mae Rose Gott