When and where?
Mi 14-16 055/T9 Seminarraum
Contact:
marsico@molgen.mpg.de
Annalisa.Marsico@fu-berlin.de
Content and goal of the seminar
Recent technological developments have brought forth a new era of RNA research in which large sets of data are collected rapidly using high-throughput next generation sequencing technologies. Growing evidence suggests that only around 5% of the mammalian genomes are transcribed into protein-coding RNAs, and a large amount of transcripts are non-coding RNAs (ncRNAs). Few discoveries have recognized that several species of ncRNAs (e.g. microRNAs or circular RNAs) have a much wider spectrum of functions than anticipated. For example, the discovery of microRNAs has changed our view of how genes are regulated at post-transcriptional level.
Bioinformatics is a pivotal component of this new RNA research revolution. It utilizes mathematical models and computer simulations to extract and analyze RNA data, search new ncRNA genes, predict their targets and their protein-binding partners.
This seminar is meant for master students and the goal is to look deeper at some selected papers describing algorithms and statistical methods for ncRNA-protein interaction prediction, lncRNA function prediction (both evolutionary-based and network analysis methods). We will also have a deeper look into new experimental high-throughput technologies and challenges in the data produced by such technologies. Such methods include CLIP-seq data for detecting RNA-RNA and RNA-RBP interactions/motifs, CRISPR/Cas9 high-throughput genome editing (a technique candidate to the next nobel price!) and single-cell transcriptomic, as an alternative to bulk RNA-seq. The aim will be to use these articles as starting point to critically assess the presented methodologies, understand their context of applicability and critically assess the results. A group discussion about each paper will be essential part of the seminar (see below).
Format of this seminar
The seminar will be held in English language. The format of this seminar will be a bit different from what you have seen so far, in the sense that there will not be paper assignments followed by a 30 minutes presentation.
Every Wednesday you will all be assigned a paper from the (fixed) list below. Everyone is required to carefully read the paper, but only one person each time will be reponsible to:
- pitch the paper content, meaning prepare three key slides (Introduction, Method, Results) about the paper, in order to introduce it to the class. The paper pitch should last 5 minutes. During the first lecture I will give you some example on how to do that.
- steer a group discussion about the paper (e.g. discuss about the method in detail, is it useful? is it novel? which kind of biological questions it allows to answer? is it an advancement with respect to other methods? what is the most interesting result of the paper? Is the conclusion supported by the data?). More details about how to steer this kind of discussion will be given in the first lecture. The discussion should last about 30 minutes.
In addition, at the end of each class I will always give a short introduction (~15 minutes) to the topic of week after, to place next paper into context.
Basically, in this seminar you will learn four important skills, useful for your future job in both academia or industry:
- How to give a short pitch about a topic
- How to effectively read a paper
- How to chair a discussion
- How to critically access a topic in a group
Important: please select 3 papers you would like to pitch from the list below, ranked according to your preference. First-come, first-served.
The dates for the papers are fixed, choosing a paper means choosing a date!
Send your list to me until October 18, 21:00 Uhr (after the first lecture). I will try to make sure that everybody is assigned one of its favorite papers.
I hope you will enjoy this kind of seminar (it is a bit unusual) and hopefully learn a lot!
Completing the seminar
- Attend all classes. You can miss up to one class. If you miss more than one class you will be asked to write a report about a topic of your choice discussed in the seminar.
- Give the paper pitch and chair a discussion at least once
- Participate actively to the group discussion
Papers' list
[18.10.2017] Annalisa: introduction pptx
RNA-RNA bindingin protein (RBP) interactions, sequence-structure motifs
1. [25.10.2017] Annalisa Marsico ssHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data (Heller et al. NAR 2017) pdf
2. [01.11.2017] Jacob Gora A deep boosting based approach for capturing the sequence binding preferences of RNA-binding proteins from high-throughput CLIP-seq data (Li et al. NAR 2017) pdf
3. [08.11.2017] Kristian Reinhart Modeling the combined effect of RNA-binding proteins and microRNAs in post-transcriptional regulation (HafezQorani et al. NAR 2016) pdf
4. [15.11.2017] Paula Junge, Bonian Riebe Motif independent identification of potential RNA G-quadruplexes by G4RNA screener (Garant et al., Bioinformatics 2017) pdf
Target prediction of small bacterial RNAs (sRNAs)
[22.11.2017] No seminar - Annalisa not in Berlin
1. [29.11.2017] Miriam Sieg Global Mapping of Small RNA-Target Interactions in Bacteria (Melamed et al. Molecular Cell 2016) pdf
2. [06.12.2017] Ben Wulf Comparative genomics boosts target prediction for bacterial small RNAs (Wright et al. PNAS 2013) pdf
Detection of circular RNAs
1. [13.12.2017] Anika Novikov CIRI: an efficient and unbiased algorithm for de novo circular RNA identification (Gao et al. Genome Biology 2015) pdf
In silico prediction of long non-coding RNA functions
1. [20.12.2018] Anja Seidel In silico prediction of lncRNA function using tissue specific and evolutionary conserved expression (Perron et al. BMC Bioinformatics 2017) pdf
2. [11.01.2018] Marc Horlacher Global network random walk for predicting potential human lncRNA-disease associations (Gu et al. Scientific Reports 2017) pdf
Yufei Zhang IntNetLncSim: an integrative network analysis method to infer lncRNA functional similarity (Cheng et al. Oncotarget 2017) pdf
3. [17.01.2018] Anthony Wolf A subset of conserved mammalian long non-coding RNAs are fossils of ancestral protein-coding genes (Hezroni et al. Genome Biology 2017) pdf
Single cell transcriptomics
1. [24.01.2018] Lie Hong Design and computational analysis of single-cell RNA-sequencing experiments (Bacher et al. Genome Biology 2016) pdf
2. [31.01.2018] Alexander Lüttringhaus Normalizing single-cell RNA sequencing data: challenges and opportunities (Vallejos et al., Nature Methods 2017) pdf
CRISPR/Cas9 - prediction of efficiency
1. [07.02.2018] Sebastian Proft CRISPR library designer (CLD): software for multispecies design of single guide RNA libraries (Heigwer et al., Genome Biology 2016) pdf
Javier Macho Rendon CRISPRscan: designing highly efficient sgRNAs for CRISPR-Cas9 targeting in vivo (Moreno-Mateos et al., Nature Methods 2015) pdf
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