Owen Marshall

damidBind (development version) The damidBind package provides a straightforward formal analysis pipeline to analyse and explore differential DamID binding, gene transcription or chromatin accessibility between two conditions. The p...

damidBind is open-source (GPLv3) and live on Bioconductor.

If you have TaDa or CATaDa data waiting for differential analysis, the wait is over.

bioconductor.org/packages/dam...

damidBind's volcano plotting in action

There's also the usual suite of GO enrichment analysis tools and Venn diagrams.

And I've added a few needed tweaks to that old analysis stalwart, the volcano plot, with deeper labelling in dense regions of plots, and as many highlighted gene groups as you like.

Tired of manually pasting peak coordinates into a genome browser?

damidBind includes an interactive Shiny/IGV interface. Just click a differentially-bound region in your results table to instantly view the raw tracks and peaks in their genomic context.

Just two commands from data to analysis ...

But all that stuff happens under the hood. For the end user, you can move from raw data to differential calls in just two commands.

Sensible defaults are provided for common experiment types, while there's plenty of options and flexibility for power users.

The package accounts for the unique nature of DamID data - that pesky uneven distribution of GATC sites.

It links peaks with nearby genes, integrates limma and NOIseq to handle both log-ratio binding and count-based data, and brings much-needed updates to RNA Pol TaDa gene expression profiling.

The damidBind workflow (under-the-hood details)

DamID has become a staple for cell-type specific profiling, but moving from binding profiles to biological insights is often still a bespoke script affair.

damidBind formalises this for:

TF binding (TaDa/NanoDam)
Chromatin accessibility (CATaDa)
RNA Pol II occupancy (proxy for gene expression)

damidBind: an R/Bioconductor package for differential DamID analysis and data exploration Summary: DamID, and its cell-type specific adaptations, including Targeted DamID (TaDa), Chromatin Accessibility TaDa (CATaDa) and NanoDam, are now widely-adopted as techniques for the genome-wide pro...

I'm thrilled to announce damidBind, our new R/Bioconductor package for analysing differential binding in DamID datasets, and its accompanying preprint.

www.biorxiv.org/content/10.6...

marshall-lab.org/damidBind/

8/ We're excited to share this resource with the Drosophila community.

We hope it sparks further research into GAL4 driver dynamics, and inspires the development of better tools for studying aging and neurodegeneration.

7/ TL;DR:
- Common neuronal and glial GAL4 drivers change spatially & decline in activity with age.
- nSyb[R57C10]-GAL4 is the most stable for adult studies, but even it weakens after two weeks of adult life
- Aging Drosophila research needs better tools for consistent late-life expression.

6/ We're not the only ones to have noticed a global age-related decline with drivers.

A big shout-out to the @seroude.bsky.social lab, whose work has led the way here.

5/ Our findings highlight a critical issue for the Drosophila community:

GAL4 drivers are powerful tools, but their spatiotemporal activity must be carefully characterised for each experiment—especially in aging studies.

4/ And it's not just neurons!

The pan-glial driver repo-GAL4 also shows significant declines in activity as flies age.

This suggests a global transcriptional decline in aging brains, consistent with earlier fly and mammalian RNA-seq studies.

3/ The biggest surprise? GAL4 driver activity plummets during the first 1–2 weeks of adult life.

By 30 days at 18°C (~15 days at 25°C), activity is barely detectable in many brain regions.

This raises concerns for long-term studies of aging & neurodegeneration.

2/ Expression patterns of "pan-neuronal" drivers aren't as uniform as you'd think.

- elav[C155]-GAL4: Strong bias for mushroom body, weak in optic lobes.
- nSyb[R57C10]-GAL4: More consistent, but still regionally biased.
- ChAT-GAL4: Highly dynamic early on.

1/ The GAL4/UAS system is a cornerstone of Drosophila neuroscience. But how stable are GAL4 drivers during aging?

We found that all tested drivers—elav[C155]-GAL4, nSyb[R57C10]-GAL4, ChAT-GAL4, and repo-GAL4—show rapid declines in activity over time.

Dynamic changes in neuronal and glial GAL4 driver expression during Drosophila aging Abstract. Understanding how diverse cell types come together to form a functioning brain relies on the ability to specifically target these cells. This is

Excited to share our latest work, just out in #GENETICS.

We show that neuronal & glial GAL4 driver activity changes dramatically over adult life, raising key questions for aging & neurodegeneration research.

academic.oup.com/genetics/art...

(Oh, and, hello Bluesky! So nice to finally be here :)

New features include:

* Automatic handling of multiple experiments and replicates
* Automatic handling of PE and SE sequencing data
* Ability to set a separate --datadir for input FASTQs and BAMs
... and a few other neat features and bugfixes. Enjoy :)

damidseq_pipeline An automated pipeline for processing DamID-seq datasets

I've just released version v1.6 of damidseq_pipeline to GitHub:

owenjm.github.io/damidseq_pip...