Ruprecht-Karls-Universität Heidelberg
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Knop0119 - Scientist (f/m) / PhD position
Project no:

Project leader:

Project supervisor:
Knop, Michael
Application deadline:
31. May 2019
Start of PhD project:
1. Jul 2019

Project description:

Impact of local gene environment and 3D organisation of the cell nucleus on single gene transcriptome dynamics
Protein homeostasis is crucially influenced by the dynamics of gene expression. In this project we continue our systematic work where we explored the impact of antisense ncRNAs on gene regulation and gene expression noise, and where we showed that individual antisense RNAs can impact gene regulation in a major way (Huber et al., 2016, Bunina et al., 2017). In this PhD project we will continue the work by systematic exploration of the contribution of the local gene neighbourhood as well as the 3D organisation of the genome on gene expression and on stochastic gene expression (noise). The project will involve high throughput yeast genetics, high content microscopy, Hi-C related methods and nextGen sequencing to study chromatin organisation, and it will require bioinformatics analysis to correlate own datasets with data from literature. Work will be conducted in a small team of experienced researcher. The project is based on previous work in the lab and it will involve methods, resources and database technology developed in the lab (Meurer et al., Dubreil et al., 2018).
Bunina D, Stefl M, Huber F, Khmelinskii A, Meurer M, Barry JD, Kats I, Kirrmaier D, Huber W & Knop M (2017) Upregulation of SPS100 gene expression by an antisense RNA via a switch of mRNA isoforms with different stabilities. Nucleic Acids Res. 45: 11144–11158

Huber F, Bunina D, Gupta I, Khmelinskii A, Meurer M, Theer P, Steinmetz LM & Knop M (2016) Protein Abundance Control by Non-coding Antisense Transcription. Cell Rep 15: 2625–2636

Meurer M, Duan Y, Sass E, Kats I, Herbst K, Buchmuller BC, Dederer V, Huber F, Kirrmaier D, Stefl M, Van Laer K, Dick TP, Lemberg MK, Khmelinskii A, Levy ED & Knop M (2018) Genome-wide C-SWAT library for high-throughput yeast genome tagging. Nat Methods 15: 598–600

Dubreuil B, Sass E, Nadav Y, Heidenreich M, Georgeson JM, Weill U, Duan Y, Meurer M, Schuldiner M, Knop M & Levy ED (2018) YeastRGB: comparing the abundance and localization of yeast proteins across cells and libraries. Nucleic Acids Res. 425: 737
Methods that will be used:
High content microscopy, FACS, Hi-C, ChipSeq, next Gen sequencing and statistical data analysis, yeast genetics using robotics, various molecular biology techniques (oligoarrays, qPCR, standard cloning techniques, etc…).
Cooperation partners:
Emmanuel Levy – Weizmann
Lars Steinmetz - EMBL
Personal qualifications:
We are looking for outstanding candidates that combine excellent wet lab skills in molecular biology with theoretical and bioinformatics knowledge and very good coding skills (image analysis using ImageJ and Matlab, DNA sequence analysis and statistical bioinformatics using R and python). The candidate needs to be well organized and able to handle complex tasks.

We offer an interdisciplinary environment that allows a talented candidate to rapidly complement his skills and knowledge and to discuss solutions of upcoming challenges during the project.