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TOM 05.04.2017

Venue: Biomedicum 1, Meeting room 5-6, 3rd Floor

Timing: 16:00 onwards

Presenter: Alok Jaiswal, PhD student, FIMM

Methods for analyzing genome-wide loss-of-function screening data

Loss-of-function techniques, such as RNAi and CRISPR, are widely used for gene silencing. These experimental methods have been extensively applied in establishing gene function in biological processes, identification of therapeutic drug targets and vulnerabilities of cancer cells. In this talk, I will describe about statistical methods that are used to analyse genome-wide loss-of-function datasets.

TOM 08.03.2017

Venue: Biomedicum 1, Meeting room 8-9, P floor

Timing: 15:30 onwards

Presenter: Dr. Ari Löytynoja, Group Leader, Institute of Biotechnology

Generalised model of local template switch mutations

Replication-related template switch mutations are known to create short,
perfect inverted repeats in bacteria. We developed a generalised model
(the four point mutation model; 4PM) that describes local template
switches in DNA replication. Using this model, we studied the mutation
clusters in human and primate sequence data and found that large numbers
of these are caused by template switch events. The 1000 Genomes data
show that 4PM events segregate in human populations and the Icelandic
trio data contain de novo 4PM events. I describe the 4PM alignment
algorithm and the computational analyses involved in the study
(http://biorxiv.org/content/early/2016/09/27/038380). I will then
discuss what the findings mean for reference-based sequencing studies
and for the evolution of genomes.

TOM 08.02.2017

Venue: Biomedicum 1, Meeting room 5-6, 3rd Floor

Timing: 15:30 onwards

Presenter: Dr. Matti Kankainen, Bioinformatics Team, FIMM

Best practices in RNA-seq data analysis

RNA sequencing (RNA-seq) has become an indispensable tool to characterize transcriptomes and understand the molecular indicators of disease and treatment. It is a powerful technology to study gene expression and discover novel isoforms, in addition to which RNA-seq has proven to be highly useful technique to discover expressed coding variants, deep intronic mutations, and fusion-transcripts. In this talk, I will describe how we at the FIMM sequencing center process RNA-seq data from model organisms and will give a sneak preview to the upcoming new analysis features we are developing at the moment.

TOM Spring schedule 2017

Tentative schedule for Spring session 2017

Date Presenter       Title of presentation
08.02 Matti Kankainen Best practices in RNA-seq data analysis
08.03

Ari Löytynoja

Generalised model of local template switch mutations

05.04 Alok Jaiswal

Methods for analyzing loss-of-function screening data

10.05 Julia Casado

Single-cell data analysis framework

 

TOM – 14.12.2016

Venue: Biomedicum 1, Seminar room 1-2

Timing: 15:30 onwards

Presenter: Boris Vassilev, Ikonen Lab, Department of Anatomy, Biomedicum Helsinki

Document, automate, and share your data analysis with Lir

Lir is a software tool for documenting, automating, and sharing computational work. We have demonstrated that Lir can improve the reproducibility of a complex data analysis. With Lir, it takes less effort to document the analysis, while the generation of all results is automated. Importantly, Lir supports the use of multiple programming languages and approaches in the same data analysis. This allows the user to employ whatever tool is best suited for each step of the analysis

See more details from the publication: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0164023

Student in Spotlight – Petra Tauscher

For the month of November 2016

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Petra Tauscher is a PhD student at the Institute of Biotechnology, Developmental Biology Program with Group Leader Dr. Osamu Shimmi. She is studying the post-transcriptional regulation of TGF-beta type signaling in Drosophila development, and has recently published an article on this topic. Congratulations Petra!

Developmental patterning and intrinsic properties of BMP ligands

Research Digest:

A fascinating area of research in biology is to understand how animals transform from a single-cell zygote to a fully-grown adult with sophisticated organ systems. Previous studies have shown that the genetic mechanisms of a huge variety of animal species during development is conserved, i.e. a similar group of genes carry out a conserved set of molecular functions. How is it possible that animals look so different, despite using the same mechanisms?

Because the developmental processes are conserved, it allows researchers to conduct studies in model organisms. For instance, invertebrates like fruit flies, as well as vertebrates use the same set of molecules for dorsal/ventral patterning (DV) during embryogenesis which ultimately determines the back/belly in adult form. The Bone Morphogenetic Protein (BMP) signaling pathway is one such conserved signaling that plays a crucial role during this process. It is also important for the posterior cross-vein (PCV) formation during pupal stage, which develops into the wings in flies. So how does the BMP signaling pathway result in DV patterning in one, and PCV in another context of development?

Previous studies suggest that changes in gene regulation affect BMP signaling in a spatiotemporal manner. Petra’s experiments [1] add a new aspect to this idea. She compared the protein sequences of BMP-type ligands from various species and found that the BMP-type ligands contain a highly conserved N-glycosylation motif. However, Screw, a BMP-type ligand in fly, carries an additional unique N-glycosylation motif that is not present in other BMP-type ligands. While Screw is critical and exclusively found in the context of dorsal/ventral patterning, Glass bottom boat, a paralog of Screw plays a role during PCV formation in fly. Petra et al. found that Screw, if expressed artificially in the wing can replace the function of Glass Bottom Boat during PCV formation, but vice-versa is not true. Furthermore, BMP-type ligands lacking N-glycosylation motifs were more efficient in the context of PCV formation, whereas lack of N-glycosylation in the Screw ligand led to a reduced viability. This suggests that N-glycosylations provide an advantage for DV patterning, i.e. during early stages of embryogenesis but are detrimental during PCV formation. Hence, N-glycosylation motifs affect BMP function in a context dependent manner.

Petra thereby concludes that apart from the spatial and temporal changes in gene expression, post-translational modifications may be one way how evolutionarily conserved molecules and signaling pathways adapt to different developmental processes.

  1. Tauscher PM, Gui J, Shimmi O. Adaptive protein divergence of BMP ligands takes place under developmental and evolutionary constraints. Development. 2016 Oct 15;143(20):3742-3750.

 

TOM – 16.11.2016

Venue: Biomedicum 1, Seminar room 1-2

Timing: 15:30 onwards

Presenter: Teemu Kivioja, Taipale Lab, Genome-Scale Biology Program

Utilizing integer linear programming in experiment design and analysis

Many tasks in bioinformatics involve choosing the best combination
from a vast number of different alternatives, for example the optimal
set of molecular probes from a large number of candidate probes. Many
such discrete optimization problems can be conveniently expressed in
Integer Linear Programming (ILP) or more generally Mixed Integer
Linear Programming (MILP) framework. The improvement of general ILP
solvers together with the increase in computing power has made it
possible to optimally solve many problem instances of small to medium
sizes without developing a task-specific algorithm or resorting to
heuristics. I will introduce how one can use ILP to solve experiment
design and analysis problems through simple examples taken from my own
research including molecular barcode design, CRISPR/Cas9 guide RNA
selection, and selecting a representative set of transcription factor
binding motifs.

Battle de suprême: CRISPR vs. RNAi based screening

Written by: An Uncharacterized ORF

genome_editing

(Commentators speech log)

Dear XXs and XYs, Welcome to the LoF Screening Championship hosted by the World Federation for Functional Genomics (WFFG). We’re having a gloriously sunny day and a more perfect stage couldn’t be asked for an ultimate entertaining extravaganza. LoF, sounds eerily like ‘laugh’ so you may think that this is a competition for the king of comedy of sorts, the one who can leave you Laughing-on-Floor, but sadly it stands for Loss-of-Function.

Loss-of-function screens are concerned with understanding the function of genes by quintessentially removing them from a cell and observing the consequences. For instance, it has been applied in identifying genes that are essential for survival of cancer cells, with the intention to pick out diagnostic markers and targets for drugs, giving them the ability to kill cancer cells. Similar to other functional genomic tools like transcriptome and proteome profiling, LoF screens have also been adapted to high-throughput settings. By nullifying the function of many genes in one go, these techniques can produce a copious amount of data leaving the analyst melancholically overwhelmed.

Today on stage, we have two contestants both of whom have been adapted for high-throughput LoF screens. While one works by knocking down the mRNAs to suppress gene expression, the other works by knocking the gene out. On this sombre thought of gene annihilation, let’s watch this crown battle for the favourite toolkit of natural philosophers, aka scientists.

But first, here’s a quick look at their bios.

 

RNAi:

Popularly known as RNAi, Ribonucleic Acid interference is the veteran here. Make no mistake, despite the nominal reference to a recreational drug, RNAi’s character remains unblemished by any doping scandals, and most likely is a scornful quip on the scandalous.

Brought out from obscurity by Andrew Fire and Craig Mello in 1998, RNAi generated a huge fire, ahem, fan following and swiftly became the poster child of the Silencer movement that rose to its prominence post-millennium. The arrival of RNAi to the scene provided immense psychological boost to her fans, who could then use it to write their own stories of explorations on suppressing their favourite genes. No wonder RNAi became a heartthrob; for it empowered the people for targeted gene suppression and gave rise to a democratic wave of explorations.

RNAi’s prime strengths are its dicing and slicing abilities that it derives from the adventuring Argonautes. RNAi’s two avatars, siRNA and shRNA, have been successfully deployed by her fans for quite some time. However, as they grew familiar with the technique, RNAi has fallen prey to the old maxim, “familiarity breeds contempt”. Sufficient time has already been devoted to expose RNAi’s shortcomings, inefficient knockdown and off-target effects, that has MELLO-wed the FIRE in RNAi.

 

CRISPR:

on the other side is a new kid on the block. Clustered Regularly Interspaced Short Palindromic Repeats (catches breath) under the nom de guerre CRISPR has ascended to stellar heights within a very short term. Legend has it that, when CRISPR was young and still hadn’t realised his full potential, he was found protecting bacteria in yogurt from viruses. It was Emanuelle Charpentier, Jennifer Doudna and Feng Zhang who trained CRISPR and helped unleash his capabilities.

CRISPR’s strengths come from its Cas9 arm with which it can break DNA at any address directed by the Guide RNA. CRISPR has become a sensational star and has found a cult fan following in the Genome Editors. Ever since CRISPR came into the scene, the Genome Editing community has been very gung-ho about it, almost to the level that their infectious enthusiasm has raised eyebrows of the Human Germline Ethical Brigade.

Like RNAi, CRISPR has also been morphed to perform high-throughput LoF screens. The question remains, who is better at it? Let’s hope we will get the answer today.

 

… Continued …

Originally published at: FIMMSights Blog!

TOM – 19.10.2016

Venue: Biomedicum 1, Seminar room 1-2

Timing: 15:30 onwards

Presenter: Gopal Peddinti, Senior Researcher, FIMM

Genome scale metabolic modeling of cancer cells

Genome based research in cancer has identified a plethora of mutational events involved in the initiation and progression of cancers. Surprisingly, the huge diversity of genomic alterations appear to converge in altering the tumor metabolism. Therefore, “starving the tumor cells of their energy supplies” (i.e. targeting tumor metabolism) appears to be a universal bullet to treat cancers. To explore the therapeutic potential of metabolism, genome scale metabolic models (GSMM) emerged as powerful in silico tools in cancer systems biology research for predicting biomarkers, therapeutic targets, and treatment side effects.

GSMMs are stoichiometric models providing a comprehensive view of cell metabolism. Reconstruction and simulation of GSMMs is achieved by constraint based modeling framework. COnstraints Based Reconstruction and Analysis (COBRA) is a comprehensive toolbox used widely in metabolic modeling. I will briefly review the GSMM approach, some of its successful applications, and show the COBRA matlab toolbox (https://opencobra.github.io/cobratoolbox/).

Dance your PhD – Maarja Laos

“Creativity is a great motivator because it makes people interested in what they are doing. Creativity gives hope that there can be a worthwhile idea. Creativity gives the possibility of some sort of achievement to everyone. Creativity makes life more fun and more interesting.”   –   Edward de Bono

 

Here’s a submission from Maarja Laos, an ILS PhD Student and Student Council member, for the Dance your PhD contest organised by the Science magazine. No talk, only Dance! Kudos to Maarja for being able to put all the hard work to get it done and inspiring us fellow students to look at our projects from a creative perspective and add fun in our journey as scientists. Enjoy!

 

Description:

The cochlea of the inner ear functions to enable us to hear sounds. It contains hair cells that via the hair bundles on their apical surface detect sound waves and transmit them to the brain to generate hearing.

Human hair cells are very sensitive and die easily due to loud noise and other insults (e.g. some antibiotics, chemotherapy drugs). Unfortunately, following injury the surviving hair cells in mammals, including in humans, are unable to divide leading to a gradual deterioration of hearing.

Scientists are trying to restore human hearing by designing strategies to replace lost hair cells either by forcing the surviving hair cells to divide, by repairing the damaged essential parts of the hair cell, such as the hair bundle or by making the surrounding supporting cells to convert into hair cells. The cochlear auditory sensory epithelium containing the hair cells and supporting cells can be grown in culture on a filter membrane. The filter membrane is placed on top of a metal mesh so that the cells are located at the interface of the culturing media and air, allowing both nutrients from the culturing media and oxygen from the air to reach them.

Scientists face many difficulties trying to make these regenerative strategies to work. When mammalian hair cells are forced to divide, the cell division often fails, resulting in death of a cell or daughter hair cells with abnormal number of chromosomes. The strategies aiming to repair the damaged hair bundle of a hair cell are not able to fully restore the hair bundle, resulting in hair cells that are unable to properly detect sound. The strategies that convert supporting cells into hair cells usually produce hair cells that are not fully functional and retain characteristics of supporting cells. In my PhD project I have tried to understand the reasons why these regenerative strategies are not successful.