Tim Warwick

Read the preprint @ biorxiv.org/content/10.110… and let us know how to improve RADIAnT, send feature requests, get help with problem-solving and more @ github.com/si-ze/RADIAnT

This project is the hard work of Simonida Zehr, with massive input from @TheMarcelSchulz in the frame of @trr267 (funded by @dfg_public), with major contributions from many people from @BrandesLab (@goetheuni) and @AstraZeneca / @Cambridge_Uni (Alessandro Bonetti + Emma Walsh)

and finally, we generated RADICL-seq libraries from control endothelial cells and #EndMT-stimulated cells, and show that RADIAnT can be used to identify dynamic #chromatin-associated #lncRNAs

In a benchmarking experiment using #Malat1 RAP-DNA data as a positive dataset, we found that RADIAnT outperformed previously proposed methods in the accurate recall of Malat1-DNA interactions

Using published data from mESCs, we show that RADIAnT detects consistent RNA-DNA interactions across different ligation methods and experiments. RADIAnT uses a genomic binning approach which can be scaled to the quality and depth of the data to maximise statistical power

RADIAnT makes up the final step of reads-to-interactions pipeline, built with #Snakemake, which is customisable by the user with regard to species, method and more, enabling parallelised and reproducible analysis of RNA-DNA ligation data

Do you want to detect #RNA-#DNA interactions from RADICL-seq, Red-C or GRID-seq, but lack a reliable method? Then try RADIAnT, our new statistical framework for calling robust, consistent interactions from RNA-DNA ligation methods biorxiv.org/content/10.110…

Therefore, we developed a statistical approach that accounts for these factors - RADIAnT. RADIAnT builds a dataset-specific background model from the input data, against which RNA-DNA interactions can be called in a manner that accounts for gene locus proximity and RNA expression

Whilst working with these data types, we noted that they were hugely influenced by nascent transcription and RNA expression levels, leading to potential overrepresentation of close-range interactions and underrepresentation of long-range interactions

@EVanNostrandLab dive into the new mysteries of snoRNAs in this exciting article. Includes: -chimeric eCLiP to map snoRNA-target RNA interactions - SNORD89 guided 2'-O methylation of U2 leading to splicing regulation - SNORD3-rRNA processing biorxiv.org/content/10.110… 👏👏👏👏👏

Did you know that there is a second glutamine metabolism pathway that generates α-ketoglutarate? Check out our new pre-print from @FlaviaRezendeF describing the pathway, now on bioRxiv: biorxiv.org/content/10.110… (1/4)

It was a pleasure to be involved in the project, supported by @CPI_ExStra @trr267 @goetheuni @dfg_public and @dzhk_germany, conducted at @BrandesLab here in Frankfurt! (4/4)

Using Hi-C data, we could show that these enhancers are functionally required for the expression of linked genes in endothelial cells (3/4)

How do ubiquitous chromatin remodeling complexes alter accessibility of cell-type specific enhancers? We analysed genome-wide #RNA-#DNA interactions and found enrichments in RNA binding at SWI/SNF-bound enhancers (1/4)

Final poster day #ISMBECCB2023 ! 308 : @tim_warwick presents a method to predict RNA:DNA:DNA interactions using novel RNA:DNA interaction codes. TriplexAligner is able to predict triplex targets for RNAs using local alignments. @trr267 @dzhk_germany @BrandesLab @iRnaCosi 1/3

and in case you can’t make the talk I’ll also have a poster later on (no. 308) where we can talk in more detail (if the paper is still on the board)!

Read the manuscript here: academic.oup.com/bib/article/23…

For anybody at #ISMBECCB2023 interested in mechanisms of regulatory #RNA, I’ll be giving a talk on our recently published method on prediction of RNA-DNA interactions at 12:20 TODAY in the iRNA session! @BrandesLab @TheMarcelSchulz @trr267 @CPI_ExStra

Come and see our science in 4 talks over the next three days at #ISMBECCB2023 in #Lyon @dzhk_germany @CPI_ExStra @InstCardReg_FFM