Discover and read the best of Twitter Threads about #transcriptomics

Most recents (5)

Excited to see my first co-first author paper of my PhD out in @NatureComms! Tweetorial:

In 2016 the Schwartz Lab @UWMDI_UWMed showed a single injection of FGF1 into the brain can permanently revert #Type2Diabetes in @justsaysinmice. We @tunepers lab asked: HOW? (1/9)
With the wet-lab superstar @mariebentsen, we replicated this experiment, but this time, collected hypothalami from these mice at several timepoints following drug injection for #singlecell #transcriptomics with @10xGenomics (2/9)
Our computational analyses found that FGF1 induced massive changes to non-neuronal cells, specifically tanycytes and astrocytes in the first week. Inspired by work from @LiddelowSA on glial reactivity, we asked if FGF1 induced an A2 or A1 state in astrocytes (3/9)
Read 9 tweets
📢🎉The work of #Bat1K is featured on the cover in the latest issue of @nature: “Six reference-quality #genomes reveal evolution of #bat adaptations” 🦇🧬 #bats Our thread 👇 on the paper:nature.com/articles/s4158… 📸: Olivier Farcy(1/n) Image
📢Have you ever wondered how 🦇 manage to do what they do? #bats have extraordinary adaptations, including powered #flight, laryngeal #echolocation, #vocal #learning and an exceptional #longevity with unique #immunity and resistance to #cancer! 📸: @DanielWhitby5 (2/n) Image
A #Bat1K team led by @Sonja_Vernes @EmmaTeeling1 @hillermich @TheGeneMyers has just published the raw genetic material that codes for these unique 🦇 adaptations and #superpowers in @nature! #bats #genomics #cool! (3/n) Image
Read 32 tweets
Time to catch up on some #Senescence papers, starting with beautiful work by @corina_amor_MD, Judith Freucht & @JosefLeibold. They used #CART #CellTherapy to clear #Senescent cells, and you'll never guess what happened next! nature.com/articles/s4158…
Just kidding, you guessed it: disease model mice got better. Props to the authors for A) inducing #Senescence in 3 different ways, B) using 2 models of #NASH/liver #Fibrosis, and C) validating their senescence observations in human samples of #Cancer and #Atherosclerosis.
The linchpin of the paper was identifying a specific membrane marker on #Senescent cells, uPAR. They used bulk #Transcriptomics to identify candidates, then narrowed down with #Proteomic data. Go #Omics!
They didn't explore whether uPAR is causative for the #Senescent phenotype.
Read 8 tweets
A true gem among #multiomics preprints: Integrative Network Fusion by @MarcoChierici, @nicole_bussola, @viperale, et al:

✓ 3 TCGA cancers & simulated data
✓ cross-validation described in detail
✓ flow diagram
✓ source code & data shared
✓ packages w/ version, cited

/n
- [the method description & comments follows]
- link: biorxiv.org/content/10.110…
- licence the above figures/tables: CC BY-NC-ND 4.0
- an earlier version of INF was previously presented in 2018: doi.org/10.1186/s13062…
- this is the first tweet in #SundayMultiOmics series
[[Introduction]]: Similarity network fusion (SNF, doi.org/10.1038/nmeth.…) is a popular technique (600+ citations, a lot for multi-omics!) for getting a sort of consensus signal from multiple omics; it requires the same patients (less commonly - observations) in each omic.
Read 24 tweets

Related hashtags

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3.00/month or $30.00/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!