Julien Y. Dutheil

Evolutionary biologist. Likes statistics and hats, bioinformatics and pipes.

[Julien Y. Dutheil @jydutheil]

@DavidEnard @CastellanoED Did you manage to shift gears? This was quite tricky on a 4L...

[Julien Y. Dutheil @jydutheil]

@DavidEnard @CastellanoED This would be unfair not to mention the Citroen Acadiane here!

[Julien Y. Dutheil @jydutheil]

@DavidEnard @CastellanoED Unfortunately, Citroen stopped producing these suspensions after the C5. They were based on "hydrospheres" filled with nitrogen. I had a BX and then a Xantia, and I miss them!

[Julien Y. Dutheil @jydutheil]

@DavidEnard @afilipamoutinho @AdamEyreWalker This makes me think of this song, you know... Forever young 🎶... which was played by a band named "Alphaville"... how cool is that?

[Julien Y. Dutheil @jydutheil]

It is out! Thanks @afilipamoutinho and @AdamEyreWalker, this was a great adventure!

#PLOSBiology: Strong evidence for the adaptive walk model of gene evolution in Drosophila and Arabidopsis https://t.co/73leAdxV5u

[PLOS Biology @PLOSBiology]

Strong evidence that mol #evolution follows #AdaptiveWalk model across large timescales: Pop genomic datasets show that young genes adapt faster & are subject to mutations of larger fitness effects @afilipamoutinho @AdamEyreWalker @jydutheil #PLOSBiology https://t.co/3V8jqjfJKy

[Ana Filipa Moutinho @afilipamoutinho]

Here it is! Our latest work with @jydutheil and @AdamEyreWalker provides strong evidence for an adaptive walk of gene evolution: young genes adapt faster and accumulate mutations of larger effects than older ones. Check out the full story on @PLOSBiology: https://t.co/4Rl91pDCLG

[Damien de Vienne 🦋 damdevienne.bsky.social @damdevienne]

100,000 downloads and rated 4.5/5 !!! This is crazy🤯!!!
Thanks to all of you, curious people, teachers, researchers, to keep using and talking about Lifemap!

@CNRS @INEE_CNRS @INSB_CNRS it's not too late to start helping me with this project, still a lot to do to reach 200k 😉!

[Nataša Puzović @natashapuzovic]

This was work with the amazing Tanvi (@vvTanv) and Julien (@jydutheil)! Stay tuned for more noisy news...

[Nataša Puzović @natashapuzovic]

These results show that selection at the network level leads to differential selective pressure at the gene level, and local and global network characteristics are an essential component of gene-specific expression noise evolution. (5/5)

[Nataša Puzović @natashapuzovic]

Furthermore, we find that global network centrality measures such as network diameter, centralization and average degree affect average noise level and the average selective pressure acting on constituent genes. (4/5)

[Nataša Puzović @natashapuzovic]

We find that local network centrality measures have an effect on the evolution of gene-specific expression noise. Gene expression noise is more constrained in genes that are central in the network, i.e. genes that regulate other genes. (3/5)

[Nataša Puzović @natashapuzovic]

How does the gene network topology affect the selective pressure acting on gene-specific expression noise? We simulated the evolution of populations of model gene regulatory networks with different network structures under stabilizing selection on expression level. (2/5)

[Nataša Puzović @natashapuzovic]

A cell requires hundreds or thousands of gene products that interact with each other, but the expression of each gene is inherently noisy.
Here's our preprint where we study how gene-specific expression noise evolves in gene networks:
https://t.co/NiFX1NuHph
🧵(1/5)

[Julien Y. Dutheil @jydutheil]

Out of curiosity... do you think preprints should be formatted as...

[Julien Y. Dutheil @jydutheil]

@ThomasBataillon I was too lazy, I just did reverse-complement!

[Julien Y. Dutheil @jydutheil]

@ThomasBataillon ;)

[Julien Y. Dutheil @jydutheil]

@ras_nielsen Det bedste er ikke for godt… ;)

[Julien Y. Dutheil @jydutheil]

@ras_nielsen … which leads to the metaphysical question: when do we know that we really got the local Ne, that is, we have accounted for all demes that significantly contributed to the ancestry of the sample?

[Julien Y. Dutheil @jydutheil]

@ras_nielsen Phrased maybe a bit differently: with two demes, the method successfully recovers the local Ne from the coalescent Ne. But what happens if there is a third, unsampled deme? The inferred Ne should then be something between the real local Ne and the coalescent Ne, shouldn’t it?