Project description
To code or not to code, that is the evolutionary question
Expressing a gene (manufacturing its corresponding protein) requires transcription and translation. During transcription, the information in DNA is transferred to a messenger RNA (mRNA) molecule. During translation, the mRNA sequence is used to assemble amino acids that form the protein. In some genes, not all of the DNA sequence codes the protein. These introns are spliced out after transcription, leaving only the exons in the mature RNA molecule to make the protein. Splicing is critical to sequence evolution but the underlying mechanisms are unclear. EvolSpliceKinetics is conducting the first genome-wide study of exon and intron definition. Pioneering sequencing in a model organism combined with machine learning and population genetics should provide unprecedented insight into the evolutionary role of splicing kinetics.
Objective
The need to preserve correct splicing is a major source of constraint on sequence evolution. This includes selection on the splice sites as well as on regulatory elements in exons and introns. Are all exons and introns constrained similarly by splicing related pressures? This is a crucial problem not only for understanding genome evolution but also for predicting where disease-causing mutations occur.
Any variation in the prevalence of splicing information most likely reflects mechanistic variation in how the splicing process unfolds at different introns. Notably, it is often assumed that the relative importance of intronic and exonic splicing information depends on whether the splicing machinery recognizes introns or exons as the initial unit. However, this common model has never been tested directly because it is currently not possible to investigate splicing mechanism at this level of detail genome-wide. Existing studies on the distribution of splicing information are therefore based on proxies of unclear mechanistic significance, such as intron size.
My host lab has developed a nascent RNA sequencing technique that allows unprecedented insight into splicing dynamics transcriptome-wide. They have recently applied this method to Drosophila melanogaster, a species thought to use a diversity of splicing strategies. I propose to use this data, combined with a machine learning approach, to conduct the first genome-wide study into exon and intron definition based on direct kinetic evidence. I will then use population genetics methods to determine how the prevalence and strength of selection on different types of splicing information covaries with splicing dynamics.
Fields of science
Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
1649 028 Lisboa
Portugal