Today in @nature.com, we describe how discarded reads in biobank-scale WGS can help resolve the genetic predictors and consequences of Epstein-Barr Virus (EBV) infection.
Wonderful working with @ryandhindsa.bsky.social @sherrynyeo.bsky.social @erinmayc.bsky.social
www.nature.com/articles/s41...
Really elegant work, and something tells me the answer to the mammalian question is just around the corner 👏
Bravo 👏 @ryanlab.bsky.social - big moment for the lab and important findings re potential pathogenic mechanisms of mitochondrial disease
Now that’s the kind of reach we can only dream of! 😊 thanks
This made my day :) thank you
And finally - if you'd like to have our recent paper on functionally dominant mutations in mtDNA explained in podcast form, please see youtu.be/TY1hxrJzq5Q?...
p.s. thank you @albertosanzmon1.bsky.social :)
Thank you for your kind words Christian!
For those who’d like a high level summary of our paper today, please check out the accompanying research briefing:
www.nature.com/articles/s41...
Thank you Alexey, I think the functional data we generated bear out that point well.
Oof - a bunch of those images didn't come out at all! If you want to see them all the more reason to go check out the paper!
Huge thanks to all of our fantastic collaborators (many of whom are not on Bsky) within @cruk-si.bsky.social @mskcancercenter.bsky.social @helsinki.fi @uofglasgow.bsky.social and more - this was a team effort, supported by @cancerresearchuk.org and the NIH/National Cancer Institute.
Sidebar 2: they also appear to be something of an Achilles heel for therapy - another conversation for another day.
www.nature.com/articles/s43...
I'll leave it to the readers to make up their own minds.
But we think it's because the metabolic consequences of mtDNA mutation are powerful drivers of tumor initiation and progression.
www.cell.com/trends/cance...
Why this matters #2:
These mutations have never been seen in the human germline or in mito disease.
Clearly they are not compatible with life, but tumors are not only unfazed by this, they are happily selecting for the most deleterious mtDNA mutations observed on planet earth.
Why is that?
Why this matters #1:
Most mtDNA mutations in cancer have never been studied, and many are 5-50% heteroplasmy (VAF).
Because of the low heteroplasmy, they are often discounted as non-functional passengers.
The discoveries described in this paper establish that this is not a safe assumption.
rRNA hotspot mutations are clearly something else. Given their impact at very low heteroplasmy, we have termed these variants 'functionally dominant'.
As I said about 5000 posts back, canonical mtDNA mutations associated with mitochondrial disease need heteroplasmies over 50% to become penetrant -this makes them 'functionally recessive'.
This exemplar mutation we've been able to validate really matters, and not just because it's the first time anyone did it. Disease-associated mtDNA mutations having an impact below 50% heteroplasmy, and in this case quite a long way below, is very important for interpreting tumor genomics.
And in a final flourish, one of my favourite analyses, using the DOGMA output, Sonia was able to establish that the heteroplasmy threshold for a transcriptional phenotype of our example rRNA hotspot was somewhere ~20-30%.
Using the powerful DOGMA-seq method from Leif Ludwig (no Bsky) and @caleblareau.bsky.social, we were able to tease apart heteroplasmic dosage of m.1227G>A on cellular transcriptional phenotype, showing a clear effect on mitochondrial transcripts, but also (gasp) non-mitochondrial ribosomes...
This was coupled to a clearly perturbed mitoribosome assembly/translational profile, again from a low heteroplasmy (38%). If you're not seeing it immediately don't sweat - it took @mitogene.bsky.social ~5 years to teach me how to interpret these things
Interestingly, even after all that screening we couldn't get the bulk heteroplasmy of this recurrent mutation, m.1227G>A, above ~40%. And even more interesting, we saw massive effects of this mutation on metabolism, mitochondrial function and protein levels starting from heteroplasmy of ~10%.
(This was painful - introducing any old mutation somewhere in mtDNA is one thing, but trying to edit a single, specific position while avoiding off-targets is still a major challenge. In this case we had a 2% hit rate from candidate reagents to lead reagent. You have been warned!) #sorryjacqueline
Employing fantastic mitochondrial base editing tools developed in David Liu's lab @broadinstitute.org institute.org, we engineered in vitro models to bear recurrent rRNA mutations, which we then profiled extensively to see what was happening.
Now, because nobody has really had cause or means to study mutations in these positions, the impact of a 'low heteroplasmy' mutation in one of these positions was a total unknown. They seemed pretty likely to do something, but it was validation time.
However, the heteroplasmy of these genetically recurrent and structurally clustered rRNA mutations was pretty low - rarely rising over 30% in the bulk sequencing from tumor genomes (probably an underestimate, given how much of a tumor isn’t cancer cells, but still rather low).
With beautiful structures from @amunts.bsky.social nts.bsky.social lab as our roadmap, we were able to pin the most recurrent of these onto the structure - where they also appear to cluster in two regions where they are likely to impact ribosome function - but maybe not totally catastrophically.
We were intrigued by this, as recurrence suggests positive selection pressure. Going deeper, we found that these hotspot mutations were often in positions that do not tolerate variation in the germline, and were in regions likely to impact RNA folding (WC basepairs).
In this new superpowered dataset we found again that there are quite a lot of single nucleotide variant mutations in mitochondrial rRNA of tumors, but these are not randomly distributed - they fall into clearly recurrent hotspots, affecting 4% of all tumors.
