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Determining protein structures and understanding biology using deep mutagenesis

  • Full or part time
  • Application Deadline
    Sunday, June 23, 2019
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

1 PhD position open to work in the Genetic Systems Lab at CRG, Barcelona.

Our lab has recently demonstrated that it is possible to determine the 3D structures of proteins by quantifying the effects of a very large number of mutations in parallel using selection and sequencing. This genetic approach to structure determination relies on the quantification of unexpected interactions (genetic interactions or epistasis) between mutations and provides a new experimental strategy for structure determination, with the exciting potential to reveal the in vivo structures of molecules (Schmiedel + Lehner, Nature Genetics, in press, https://www.biorxiv.org/content/10.1101/303875v2). We are currently developing generic assays to use this approach to solve protein structures and are applying it to diverse areas of biology. For example, we are using the approach to understand the mechanisms by which proteins involved in neurodegeneration kill cells as well as the in vivo conformations of these ‘unstructured’ proteins (https://www.biorxiv.org/content/10.1101/592121v1).

More generally, we are using deep mutagenesis to address fundamental questions in genetics and to understand how mutations affect diverse molecular processes, including individual proteins and RNAs (https://www.nature.com/articles/s41586-018-0170-7), physical interactions (https://elifesciences.org/articles/32472), regulatory interactions (https://www.biorxiv.org/content/10.1101/578419v2), alternative splicing (https://www.cell.com/cell/fulltext/S0092-8674(18)31624-6), and gene networks (https://www.biorxiv.org/content/10.1101/589606v1). We are particularly interested in how mutations interact, the causes of global and specific genetic interactions, how genetic interactions reveal molecular mechanisms, the problem of accurate genetic prediction, and the evolutionary implications of all of this. The other two main interests of the lab are mutation and selection in cancer genomes (Cell 2017, Nature 2015) and the importance of noise and inter-generational epigenetics in phenotypic variation (eLife 2019, Nature 2017, Science 2017).

We are looking for a new PhD student to join the lab to take on one of these exciting projects involving deep mutagenesis: Determining protein structures and understanding biology using deep mutagenesis. Candidates interested in and/or with experience in both molecular and computational biology are particularly encouraged to apply. The ideal candidate will be passionate about biology, motivated, organized and hard working with a ‘can do’ attitude.

The Genetic Systems lab is part of the CRG Systems Biology program, which is a unique centre of excellence in Europe for quantitative biology. The CRG and the other institutes of the PRBB including EMBL Barcelona provide an ideal ecosystem for this program, being very strong in both genomics and mechanistic molecular biology. The institute receives substantial core funding, has excellent core facilities, and a beautiful location on the seafront in Barcelona.

The lab (currently ~12 members) is highly collaborative with a flat structure and works with many different systems and approaches, including model organisms and human genetic data, choosing the system and approach for the question at hand. This creates a highly inter-disciplinary environment with many members of the lab using both experimental and computational approaches. All lab members lead their own projects. To date, 12 alumni from the lab have started their own labs, including in some of the most prestigious institutes in Europe and elsewhere.

The successful applicant will enrol in the very active CRG International PhD program, which includes science and practical courses, a wide range of complementary skills training, access to many courses, mentoring via a thesis committee, and active participation in the organization of seminars, symposia and retreats.

Applicants must have obtained a University Degree and a Masters Degree in a field of life sciences, engineering and/or physics within the European Higher Education System (minimum 300 ECTS) or equivalent by September 2019, and should have substantial research experience.

Applications are accepted exclusively online. Please, click the "Visit Website" button to access our online application system.
The deadline for the receipt of complete applications (including reference letters) is the 16th of June, 2019.
Proposals must be written in English.

Candidates may contact for informal enquiries regarding the application and academic enquiries, as well as address scientific enquiries to .

CRG offers and promotes a diverse and inclusive environment and welcomes applicants regardless of age, disability, gender, nationality, race, religion or sexual orientation.

All personal data requested by CRG from applicants will be treated in accordance with the principles of the Data Protection Act (15/13 December 1999).

Funding Notes

The selected PhD student will receive an annual work contract with a competitive salary and additional funding. Extramural funding of the group includes grants from the European Research Council as well as other national and international awards.

References

Baeza-Centurion P, Miñana B, Schmiedel JM, Valcárcel J*, Lehner B*. Combinatorial Genetics Reveals a Scaling Law for the Effects of Mutations on Splicing. Cell. 2019 24;176(3):549-563.
Domingo J, Diss, G, Lehner B. Pairwise and higher order genetic interactions during the evolution of a tRNA. Nature. 2018. 558(7708):117-121.
Perez MF*, Francesconi M*, Hidalgo-Carcedo C, Lehner B. Maternal age generates phenotypic variation in Caenorhabditis elegans. Nature. 2017 Dec 7;552(7683):106-109.
Klosin A, Casas E, Hidalgo-Carcedo C, Vavouri T, Lehner B. Transgenerational transmission of environmental information in C. elegans. Science. 2017 Apr 21;356(6335):320-323.

Full publications: https://www.ncbi.nlm.nih.gov/pubmed/?term=ben+lehner

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