Mike Clark

Australian Science & Biomedical Research in Crisis Please use this form to share the impact of Australia's historically low success rates for major competitive research grants on your research, your team, and your mental health. Researchers do researc...

Share your stories here docs.google.com/forms/d/e/1F... #SaveOzScience

If your #NHMRC ideas grant was unsuccessful and you have a story to share about the impact of this on your #biomedicalresearch, career, team - get in touch. Federal DOH have asked #NARF to collect stories of impact of low funding. #SaveOzScience #DiscoveriesNeedDollars #EMCRs

The success rate for NHMRC Ideas Grants announced yesterday was just over 8%. That means 11 of every 12 people who applied got rejected. This is a culture changing level of rejection and frankly a point of national shame. This is a crisis for research.
I will not rest until we see this resolved.

Be kind to each other.. bad news for most coming in under embargo. We need more funding in the system...

Hard to know for sure until NHMRC releases funding details. From the grants I reviewed I think requested funds have increased as cost of research has gone up. Clearly funding available hasn't kept pace to even maintain the poor success rate we previously had.

this is unsustainable, the $600M underspend of the #MRFF could be funnelled, or at least partially funnelled, to supporting excellent #NHMRC applications that fall below the funding cut off because there is too little money in the pot #DiscoveriesNeedDollars #SaveOzScience

It's an all time low in both the percentage and number of #NHMRC #IdeasGrant funded. Previous lowest percentage was 9.8% in the 2020. However 283 grants were funded that year, this year it's under 200.

Individual outcomes aren't publicly released yet, but all applicants have been told if they were successful or not

Australian #NHMRC Ideas grants are out. 8.1% success rate. Lowest since the scheme began. Congrats to the successful few, as it looks like less than 200 were funded. 🧪

Chelsea Mayoh gave one of the most inspiring talks of the conference. Performing RNA-seq on kids with cancer in Australia has been highly successful in generating reportable findings, treatment recommendations, correcting diagnoses and mostly importantly, improving survival. #abacbs2025

This project was led by the talented @jakobschuster.bsky.social in colab with @qgouil.bsky.social & @mritchieau.bsky.social

As an example of the power of Matchbox, Jakob’s last tool was Restrander. A 17 line matchbox script achieved the same result as 1400 lines of C++ in Restrander!

We’ve demonstrated Matchbox for demultiplexing long-read scRNA-seq data with 10X or SPLiT-seq barcodes; restranding RNA-seq reads; assessing CRISPR editing efficiency; and haplotyping repeat regions.

Matchbox is implemented in rust and available from github.com/jakob-schust....

Sequencing data requires read processing. Some tasks are common (trimming, de-multiplexing, filtering) & others bespoke, especially if you have non-standard read-structures.

Introducing Matchbox: a fast and incredibly versatile read processor that can do all this & more 🧪
doi.org/10.1101/2025...

Publicly available, reference datasets are a bioinformatician's best friend! Find out more about the LongBench resource at poster 17 #abacbs2025 from @mritchieau.bsky.social @wehi-research.bsky.social

Ami Bhatt taking us through the wild world of bacterial mobile elements. Jumping insertion sequences that can cause antibiotic resistance; DNA invertons that flip in orientation (including in coding seqs); and the huge abundance of phages integrated into bacterial genomes in our guts. #abacbs2025

Agreed. And thanks for giving such a clear and engaging talk. Not my field but I definitely learnt a few things.

@zaminiqbal.bsky.social sequencing 765 historical plasmids (Murray collection) vs modern plasmids. 3 outcomes. 1. plasmid survive in same/similar form. 2. Now found embedded in modern massive plasmids. 3. Go extinct. ~1/2 of the types remain only as small fragments in other plasmids. #abacbs2025

@zaminiqbal.bsky.social on studying the evolution of plasmids in bacteria. How do we model evolution and understand something that jumps around between cells and species? Totally different biological system and investigatory mindset to studying vertically inherited chromosomes. #abacbs2025

@jovmaksimovic.bsky.social – On how to “easily“ detect fusions in single-cells. 1. Identify fusions with bulk RNA seq. 2. Use Flexify to design fusion detection probes for 10x Flex. 3. Detect fusions and their expression in each cell with scRNA-seq. #abacbs2025

Ruining Dong from @unimelb.bsky.social explaining how the ability to detect methylation in circulating tumor DNA (ctDNA) improves ability to determine tumor tissue of origin. Matching methylation profiles of tissues to ctDNA sounds simple, but spoiler alert, it’s actually pretty complex. #abacbs2025

First up in the #abacbs2025 Gene Regulation & Epigenetics session is Feng Yan from @nadia-davidson.bsky.social lab evaluating different long-read methods for de-novo transcriptome analysis. TLDR: Still a way to go to reduce false postives, but RNA-bloom2 generally works best.

View of Adelaide from just by the Australian Bioinformatics and Computational Biology Society conference.

Very excited to be in Adelaide to attend #ABACBS2025 . Australia is a powerhouse of microbial genomics, and indeed of bioinformatics, so am very much looking forward to meeting everyone, old friends and new, and speaking tomorrow!

Excited to share matchbox. It’s super fast and versatile to search for patterns in reads, I’m curious to see all the uses it will find!
Congrats to @jakobschuster.bsky.social , co-supervisors @michaelbclark.bsky.social @mritchieau.bsky.social and team!
www.biorxiv.org/content/10.1...

Looking for scientists working with long-read transcriptomics technologies to join a COST action proposal. Contact us!!! @nanoporetech.com @pacbio.bsky.social

This study reflects years of work, a big thanks to everyone involved, including Ricardo De Paoli-Iseppi who co-led the work and the many graduate and undergrad students who took on some of the genes for their projects or worked on IsoLamp including @josiegleeson.bsky.social & @youyupei.bsky.social

Research has shown genetic risk for disease can be imparted at the isoform level, as well as the gene level. Therefore, understanding which isoforms genes express is essential to correctly determining the disease-associated isoforms and the molecular mechanisms behind disease aetiology.

We developed a new analysis pipeline, IsoLamp, to discover and quantify isoforms from long-read amplicon sequencing. While much of the analysis and visualisation used IsoVis.
IsoVis: isomix.org/isovis/
IsoLamp: github.com/ClarkLaborat...

Overall we found more than 300 previously unreported RNA isoforms from 31 genes in brain. Some were highly abundant or even the dominant isoform, and we could show translation of novel RNAs into novel proteoforms, including new isoforms of the depression risk gene ITIH4 (see image).

Long-read sequencing reveals the RNA isoform repertoire of neuropsychiatric risk genes in human brain - Genome Biology Background Neuropsychiatric disorders are highly complex conditions and the risk of developing a disorder has been tied to hundreds of genomic variants that alter the expression and/or RNA isoforms made by risk genes. However, how these genes contribute to disease risk and onset through altered expression and RNA splicing is not well understood. Results Combining our new bioinformatic pipeline IsoLamp with nanopore long-read amplicon sequencing, we deeply profile the RNA isoform repertoire of 31 high-confidence neuropsychiatric disorder risk genes in Human brain. We show most risk genes are more complex than previously reported, identifying 363 novel isoforms and 28 novel exons, including isoforms which alter protein domains, and genes such as ATG13 and GATAD2A where most expression was from previously undiscovered isoforms. The greatest isoform diversity is detected in the schizophrenia risk gene ITIH4. Mass spectrometry of brain protein isolates confirms translation of a novel exon skipping event in ITIH4, suggesting a new regulatory mechanism for this gene in the brain. Conclusions Our results emphasize the widespread presence of previously undetected RNA and protein isoforms in the human brain and provide an effective approach to address this knowledge gap. Uncovering the isoform repertoire of candidate neuropsychiatric risk genes will underpin future analyses of the functional impact these isoforms have on neuropsychiatric disorders, enabling the translation of genomic findings into a pathophysiological understanding of disease.

🧪Happy to share our latest paper in Genome Biology.

We profiled #RNA isoforms from 31 neuropsychiatric risk genes in the human brain using long-read sequencing. Unannotated isoforms commonly made up a significant proportion of a gene's expression.

genomebiology.biomedcentral.com/articles/10....

Long-read transcriptomics is advancing quickly, we benchmarked leading bulk and single-cell protocols in this awesome collaborative effort!
We hope it will be a valuable resource for the community.
Congrats @youyupei.bsky.social @mritchieau.bsky.social @michaelbclark.bsky.social and all!