Genetic regulation of the transcriptome

The basis of many responses lies in modifying gene expression. One way of understanding how genetic regulation works at a  is by crossing two (or more) genetically diverse strains and creating a so-called segregated population. Subsequently, strains of this population can be exposed to different types of environments and the whole transcriptome can be measured (e.g. by RNA-sequencing).

In this project, we have measured over 300 transcriptomes over various environments and want to map the genetic regulators of transcript levels. In this way, we can identify regulatory hot-spots. Identification and characterization of these hot-spots can lead to finding the important regulators affecting the expression of many genes. There are several thesis opportunities related to this research:

-      Conducting an eQTL experiment: design and execute an eQTL experiment in C. elegans. This research is a mix between bioinformatics and labwork. It would include learning to analyze and use recombinant inbred population or introgression line populations (either in R or excel), power analysis, how to work with the model nematode C. elegans, experimental design, RNA isolation, transcriptomics (either RNA-sequencing, microarray, and/or qPCR).

-      Bioinformatic analysis: analyze a large transcriptomics dataset, plus follow-up analyses to understand the biology of transcriptional differences. This includes learning how to program in R, understand and exploit genomic databases, and cutting-edge analytical methods for gene-expression analysis.

-      Experimental follow-up: verifying the existence of regulatory hot-spots and test candidate genes. This would include learning how to work with the model nematode C. elegans, experimental design, RNA isolation, conducting genetic crosses, Crispr/CAS9 gene-editing, working with genetic markers (DNA-isolation, PCR), transcriptomics (either RNA-sequencing, microarray, and/or qPCR), and data-analysis.