Category: Publications

Postdoc Sean Alexander Bankier – new manuscript

We are please to announce that our postdoc Sean Alexander Bankier together with the co-authors published the manuscript: “Plasma cortisol-linked gene networks in hepatic and adipose tissues implicate corticosteroid-binding globulin in modulating tissue glucocorticoid action and cardiovascular risk”.

Frontiers | Plasma cortisol-linked gene networks in hepatic and adipose tissues implicate corticosteroid-binding globulin in modulating tissue glucocorticoid action and cardiovascular risk (frontiersin.org)

Probing the structure of individual RNA molecules

RNA molecules can form secondary and tertiary structures that can regulate their localization and function. These structures are rarely static and different copies of the same RNA can often adopt many different conformations. Despite this most methods are only capable of characterizing RNA at the consensus level, looking at the average over RNA molecules.

A new paper in Nucleic Acids Research from Teshome Bizuyaheu in the Valen group addresses this by developing a method to probe for structure on individual RNA molecules.  By introducing RNA modifications in a structure-dependent manner and using nanopore sequencing to decode the location of these modifications, the new method, Single Molecule Structure sequencing (SMS-seq), is able to create limited structural profiles from individual molecules.  Furthermore, since each RNA is probed at numerous places the discovery of dependencies and heterogeneity of structural features within a molecule is possible.

The paper can be found here.

CBU group leader, Markus Miettinen, together with the co-authors published a perspective paper “Emerging Era of Biomolecular Membrane Simulations: Automated Physically-Justifed Force Field Development and Quality-Evaluated Databanks” in which they discuss the current status of all-atom simulations of biomembranes, and outline their view on how these should be further developed by harnessing large databanks and automated data-driven approaches. Read the paper here: https://pubs.acs.org/doi/10.1021/acs.jpcb.2c01954

Our PhD student Muhammad Ammar Malik and Professor Tom Luk Michoel published a paper in which they analyse the mathematical structure of a class of statistical models for learning hidden factors influencing gene expression data and show that a new algorithm based on the analytical results is orders of magnitude faster than the standard algorithms for solving this class of models. Read the article here.