Edinburgh Research Explorer

Biography

Grzegorz Kudla is a group leader at the MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland. He received his PhD in 2005, in the Maciej Zylicz lab, International Institute of Molecular and Cell Biology, Warsaw, Poland. He then worked as a postdoc with Joshua Plotkin at Harvard University and with David Tollervey at the University of Edinburgh, to study the influence of codon bias on gene expression. He is currently developing experimental and bioinformatic tools to study regulation of gene expression, protein-RNA interactions, and RNA-RNA interactions. Since 2008 he has served as Academic Editor of the open access journal PLoS ONE.

Qualifications

PhD in Biochemistry, 2005, International Institute of Molecular and Cell Biology, Warsaw, Poland

MSc in Animal Physiology, 2000, Warsaw University, Warsaw, Poland

Current Research Interests

I am interested in applying next-generation sequencing to study gene regulation, protein-RNA interactions, and RNA-RNA interactions.

Research Interests

A major goal of research in biology is to understand how DNA sequence mediates the regulation of gene expression. Historically, regulatory elements have been extensively studied in flanking regions of genes, but recent results point to an important role of coding sequences in regulation. We study the functional consequences of synonymous mutations in Eukaryotic genes. To characterize the influence of mutations on gene expression in human cells, we generate synthetic libraries of mutated genes, we use low- and high-throughput methods to measure the expression phenotypes of each mutant, and we apply bioinformatic analyses to disentangle the sequence features that influence gene expression at various stages. To study fitness effects of mutations, we mutagenize selected yeast genes and assay the fitness of each variant by deep sequencing the pooled mutants during competitive growth. This allows a comparison of fitness effects between synonymous and nonsynonymous mutations, and between specific classes of synonymous mutations.

In collaboration with other groups, we also use deep sequencing-based methods to investigate the interactions of regulatory proteins with RNA in yeast and human cells. We developed a new method for high-throughput mapping of RNA-RNA interactions, called CLASH. Our method is conceptually similar to the Chromosome Conformation Capture technique that has been widely used for the analysis of DNA structure. In collaboration with the Tollervey lab, we apply CLASH to the analysis of microRNA targets in human cells. This research will improve our understanding of gene regulation and molecular evolution, and may have practical applications in bio-medicine.

My research in a nutshell

In order to survive and grow, cells need to decode the information written in the genome. The "genetic code", which specifies how the information in the DNA is used to make different proteins, was solved in the 1960s. In contrast, the "regulatory code", which determines the amount of each protein produced, is still very poorly understood. If we can understand the regulatory code, we will be able to predict the effects of different DNA mutations on protein amounts in the cells. This information could be used, for example, to understand the mechanisms of various diseases, or to artificially manipulate the amounts of proteins made by genes.

 

We study the regulatory code, and how it differs between different organisms and different external conditions. We do that by measuring the amounts of proteins produced by thousands of mutant genes, and using computational methods to tell which mutations were most likely to produce an effect on protein production. We then confirm these statistical predictions experimentally. These experiments will increase our understanding of how the human genome works, and they may lead to practical applications in bio-medicine.

Highlighted research outputs

  1. Strand-specific, high-resolution mapping of modified RNA polymerase II

    Research output: Contribution to journalArticle

  2. Network of Epistatic Interactions Within a Yeast snoRNA

    Research output: Contribution to journalArticle

  3. Rate-limiting steps in yeast protein translation

    Research output: Contribution to journalArticle

  4. Transcriptome-wide analysis of exosome targets

    Research output: Contribution to journalArticle

  5. Synonymous but not the same: the causes and consequences of codon bias

    Research output: Contribution to journalLiterature review

  6. Coding-Sequence Determinants of Gene Expression in Escherichia coli

    Research output: Contribution to journalArticle

View all (27) »

Research projects

  1. RNA Genotype-Phenotype Mapping

    Project: Funded ProjectResearch

  2. Next generation gene optimisation

    Project: Funded ProjectResearch

View all (8) »

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