The model nematode Caenorhabditis elegans has been a champion of genetics since the 1970s. A vast body of knowledge exists that links genes of this nematode to homologous in humans and hence, this nematode is often used to understand the basics of human genetic regulation.
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.