Mike Clark
@michaelbclark.bsky.social
63 followers 48 following 10 posts
Genetics, transcriptomics, RNA and neuroscience. Lab head at the University of Melbourne, Australia. View own.
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Reposted by Mike Clark
anaconesa.bsky.social
Looking for scientists working with long-read transcriptomics technologies to join a COST action proposal. Contact us!!! @nanoporetech.com @pacbio.bsky.social
michaelbclark.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
michaelbclark.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.
michaelbclark.bsky.social
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...
isomix
isomix.org
michaelbclark.bsky.social
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).
michaelbclark.bsky.social
🧪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 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.
genomebiology.biomedcentral.com
Reposted by Mike Clark
qgouil.bsky.social
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!
Reposted by Mike Clark
ewanbirney.bsky.social
Bioinformaticians / computational biologists take note - know where you should take your OS tool chain from and do not introduce backdoors.
jbonfield.bsky.social
Heads up: ignore samtools dot org, similarly minimap2 dot com and likely others. It's owned by a known phishing site and while the binaries they offer look valid currently (but note they may be serving us different binaries to others), that could change.

Ie: it's not us (Samtools team)! Be warned
Reposted by Mike Clark
youyupei.bsky.social
🔹 What’s inside
• Bulk, single-cell & single-nucleus RNA-seq from 8 lung-cancer cell lines spanning 3 cancer types for realistic DE analysis
• Three long-read protocols (ONT PCR-cDNA, ONT direct RNA, PacBio Kinnex) and Illumina short-read sequencing
• Synthetic spike-in controls for ground truth
michaelbclark.bsky.social
If you want to explore the data check out the Shiny App: clarklaboratory.shinyapps.io/human_brain_...

Big thanks to Josie Gleeson and Ric De Paoli-Iseppi for leading this work.
michaelbclark.bsky.social
- Different RNA isoforms from the same gene can have different modification rates at the same m6A site. Distance to a splice site, transcript 3' end, and the CDS versus UTR status of a nucleotide all exert influence.
michaelbclark.bsky.social
We identified 57,000 m6A sites in 15,000 isoforms.

Some of the key results were:
- highest m6A levels in the cerebellum.
- Pre-frontal cortex had the most unique m6A profile, associated with excitatory neurons and synaptic genes.
- Some RNAs are hyper-modified. The lncRNA TUG1 had 37 m6A sites!
Reposted by Mike Clark
science.org
The appearance of large language models caused a drastic shift in the vocabulary of academic writing, according to an analysis in #ScienceAdvances of more than 15 million biomedical abstracts published from 2010 to 2024.

Learn more:
Delving into LLM-assisted writing in biomedical publications through excess vocabulary
Large language models (LLMs) like ChatGPT can generate and revise text with human-level performance. These models come with clear limitations, can produce inaccurate information, and reinforce existing biases.
scim.ag