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Jobs

PhD students

Elucidating the role of upstream open reading frame-encoded micropeptides in cardiac biology

Summary

Small proteins of less than 100 amino acids are known as micropeptides. They are important contributors to cardiac biology. Most of these peptides have been identified on long non-coding RNAs. Biologically relevant micropeptides encoded by upstream open reading frames (uORFs) have only recently been described in cardiac cells. Using parallel transcriptome and ribosome profiling of mouse cardiomyocytes coupled to analysis of published mass spectrometry data we have identified potential uORF-encoded micropeptides. Building on this preliminary data we want to further confirm the importance of these uORFs during cardiomyocyte stress as well as deepen our understanding on the encoded micropeptides.

In this PhD project, we will study three micropeptides identified in our preliminary analysis. We want to understand the impact these small peptides have on cell physiology and how they impact cardiac function during stress. As our in vitro model system, we use human induced pluripotent stem cell-derived cardiomyocytes.

We offer an excellent scientific infrastructure, strong integration into bioinformatics workflow and a vibrant community of research labs.

Reference

https://pubmed.ncbi.nlm.nih.gov/?term=%22Dieterich+C%22%5BAU%5D&sort=date

Methods that will be used

Differentiation and culturing human induced stem cell-derived cardiomyocytes, next generation RNA-sequencing, mass spectrometry, microscopy, co-immunoprecipitation studies

Cooperation partners

Rebecca Wade, ZMBH & HITS
Jeroen Krijgsveld, DKFZ

Keywords

Cardiology, induced-pluripotent stem cells, micropeptides, RNA translation, RNA sequencing,
Computational RNA Biology


PhD students

CircTools 2.0 – one stop solution for circular RNA research

Summary

Circular RNAs (circRNAs) originate through back-splicing events from linear primary transcripts, are resistant to exonucleases, are not polyadenylated and have been shown to be highly specific for cell type and developmental stage. CircRNA detection starts from high-throughput sequencing data and is a multi-stage bioinformatics process yielding sets of potential circRNA candidates that require further analyses.
Our current circtools solution provides researchers with a harmonized workflow that covers different stages of in silico circRNA analyses, from prediction to first functional insights. Circtools is an open source software suite that encourages users to contribute new modules, which they might find helpful in their own research. Within this project, we aim to address three key objectives, that we hope will further increase the impact circtools has on the circRNA community.

Circtools in its current version (https://github.com/dieterich-lab/circtools ) covers all major steps of computational circRNA analysis using Illumina RNA-seq data. However, from own experiments as well as valuable feedback from collaborators, it will be necessary to add new functionality the workflow (objective 1). Thus, we intent to extend the module repertoire of circtools with additional algorithms and the capability to handle new data types such as long read, single molecule and single cell sequencing approaches. Automatic code tests performed via continuous integration (CI) methods are a fundamental part of these efforts.

Although we provide a detailed step-by-step documentation and built-in help of circtools, our command line-based approach is still an inhibiting factor for researchers with limited experience of command line tools. As a first step, the primer as well as the KnockDown design module will be turned into an additional web application (objective 2), that allows researchers to easily use both function without the need of command line work or any kind of installation.

Additionally, the circtools workflow itself will be frequently used in our own projects, which are mostly in the cardiovascular setting, and you will drive the advancement of this endeavor (objective 3).
In this PhD project, the successful bioinformatics applicant will be based in the Dieterich Lab (www.dieterichlab.org) and will be funded through DFG grant DI 1501/13-1 (Qualitätssicherung von Forschungssoftware durch ihre nachhaltige Nutzbarmachung)
We offer an excellent scientific infrastructure, strong integration into bioinformatics workflow and a vibrant community of research labs.

Reference

Jakobi T, Siede D, Eschenbach J, Heumüller AW, Busch M, Nietsch R, Meder B, Most P, Dimmeler S, Backs J, Katus HA, Dieterich C. Deep Characterization of Circular RNAs from Human Cardiovascular Cell Models and Cardiac Tissue. Cells. 2020 Jul 4;9(7):1616. doi: 10.3390/cells9071616. PMID: 32635460; PMCID: PMC7407233.

Jakobi T, Uvarovskii A, Dieterich C. circtools-a one-stop software solution for circular RNA research. Bioinformatics. 2019 Jul 1;35(13):2326-2328. doi: 10.1093/bioinformatics/bty948. PMID: 30462173; PMCID: PMC6596886.

Methods that will be used

see github.com/dieterich-lab/circtools

Cooperation partners

Tobias Jakobi, Ph.D.
Assistant Professor of Medicine
Translational Cardiovascular Research Center
THE UNIVERSITY OF ARIZONA
COLLEGE OF MEDICINE PHX

Personal qualifications

Proven competence in handling high-throughput data sets and good understanding of the underlying statistical challenges. A proven competence in scripting/programming (i.e. at least two out of C/C++, R, Python, Java) is essential. Other relevant qualifications include a good understanding of RNA Biology. Moreover, you are happy to work in a highly interdisciplinary team.

Keywords

Circular RNA, Bioinformatics, Computational RNA Biology, Cardiovascular research


PhD students

Long Non-coding RNAs in podocyte disorders

Summary

Non-coding RNAs play an important role both in cellular biology and physiology of numerous tissues and have been linked to several renal pathologies. Large-scale datasets generated by novel sequencing technologies have shown that the majority of transcripts does indeed not possess any coding potential. Among these non-coding transcripts, long non-coding RNAs (lncRNAs) have gained increasing attention due to numerous studies underlining their importance in organ development and disease. However, a large gap has remained between the growing knowledge on lncRNA expression and the question how these transcripts impact on organ function and disease on the molecular level. It is in fact this knowledge which would be crucial for a better understanding of their contribution to human disease as well as their exploitation as potential therapeutic targets. As to the role of lncRNAs in kidney disease in general only very little is known; regarding podocyte cell biology and associated diseases such as FSGS we lack virtually any insight at all. As a consequence, the emerging field of lncRNAs bears a great potential for identifying novel diagnostic and therapeutic targets by unraveling associated regulatory processes and their impact on renal pathologies. To reach this goal, we have established a bioinformatic pipeline (CALINCA) which allows for the automated identification of lncRNAs that are podocyte-specific, conserved in evolution and dysregulated in FSGS models. Based on these analyses, we have selected several lncRNAs as promising candidates in the pathogenesis of FSGS and have both created novel knockout mouse lines as well as identified optimal cell culture models for these genes.
In this PhD project, the successful bioinformatics applicant will be based in the Dieterich Lab (www.dieterichlab.org) and be part of the DFG-funded clinical research unit 329 on Disease Pathways in Podocyte injury. He/She will help to advance our understanding of the molecular function of ncRNAs in focal-segmental glomerulosclerosis through innovate computational approaches. Along these lines, He/She will enhance and improve our bioinformatic workflow (CALINCA).
We offer an excellent scientific infrastructure, strong integration into a highly interdisciplinary team and a vibrant community of research labs.

Reference

Talyan S, Filipów S, Ignarski M, Smieszek M, Chen H, Kühne L, Butt L, Göbel H, Hoyer-Allo KJR, Koehler FC, Altmüller J, Brinkkötter P, Schermer B, Benzing T, Kann M, Müller RU, Dieterich C. CALINCA-A Novel Pipeline for the Identification of lncRNAs in Podocyte Disease. Cells. 2021 Mar 20;10(3):692. doi: 10.3390/cells10030692. PMID: 33804736; PMCID: PMC8003990.

Methods that will be used

Computational sequence analyses, subcellular localization prediction, Co-expression networks, Predictions and Identification of interaction partners, Interpretation of loss-of-function and gain-of-function assays. Analysis of Single Cell / Nuclei Assays and Sequencing. Support of RNA-imaging approaches.

Cooperation partners

Prof. Dr. med. Roman-Ulrich Müller
University Hospital Cologne
Department II of Internal Medicine, Center for Molecular Medicine Cologne (CMMC),
Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD)

Prof. Dr. Andreas Beyer
University Cologne
Cellular networks and Systems Biology
Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD)

Personal qualifications

Proven competence in handling high-throughput data sets and good understanding of the underlying


We are always looking for talented students and job application.

Contact & Application
Please upload a covering letter/supporting statement, including a brief statement of research interests, CV and the details of two referees as part of your online application.
Applications should be sent by email in ONE pdf-file to sekretariat.dieterich(at)med.uni-heidelberg.de

Please do not hesitate to contact us if you have any further questions.

University Hospital Heidelberg
Department of Internal Medicine III
Section of Bioinformatics & Systems Cardiology
Prof. Dr. rer. nat. Christoph Dieterich
Im Neuenheimer Feld 669
69120 Heidelberg
sekretariat.dieterich(at)med.uni-heidelberg.de

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