Fishing with Two Lines: A Hybrid Approach to Spatial Transcriptomic Discovery Spatial transcriptomics faces a trade-off between the number of genes assayed and depth of per-gene sensitivity. We developed a 'dual chemistry' method that combines the high sensitivity of a 10X Geno...

A fun little project. We were curious if you could prep a single sample using both 10X Genomics Xenium V1 probes and Prime probes – allowing users to profile 480 genes at high sensitivity and 5,000 genes at lower sensitivity inline.
www.biorxiv.org/content/10.6...

The council is deciding your faith… #ashg25 @pacbio.bsky.social

Getting ready for our 8:30 session in room 252ABC. Join us to discuss genes, traits and identities, and navigating sex, gender, and sexuality in genomics. #ASHG25

World’s best PI! Couldn’t do it without all the support and laughs :)

This was such a great experience! I’m so excited to see how this work evolves 🫁

A very big thank you to all authors on this study, but especially to @jensucre.bsky.social, @jkropski.bsky.social, @davisjmcc.bsky.social, @premiepulmdoc.bsky.social, and many more people for making this work possible! Excited for what's to come 🫁🧬
(17/17)

Check out @saahimall.bsky.social's #skysplain of our latest work! Very proud of all her hard work on this study and REALLY excited for what she's got planned next!

#bpd #lungdevelopment #genomics #science

Our dataset is publicly available on GEO (GSE297945), and we have a spatial cell atlas to help visualize these data: lungcells.app.vumc.org/public/sucre...
(16/17)

Overall, this work establishes new frameworks for studying disease pathology in neonatal lung tissue, and can allow us to eventually identify targetable therapeutics to help premature infants bolster proper lung development!
(15/17)

Important to note - the above results are between cell types in the epithelial, endothelial, and mesenchymal lineages, excluding the immune lineage! Read the preprint to find out why!
(14/17)

When we intersected the results from all three terms (gestational age, life span, and DX score), we found 5 gene - cell type pairs overlapped between gestational age and life span; 2 are shared between gestational age and DX score; and 1 between life span and DX score.
(13/17)

Here, we found 18 gene expression changes associated with gestational age, 25 associated with life span, and 10 genes associated with disease severity (FDR < 0.1).
(12/17)

This regression model included terms for GA & LS. We then worked with Dr. Gail Deutsch at Seattle Children’s Hospital to assign a disease severity (DX) score for each tissue (represents the overall degree of damage observed) and used a similar regression framework with a term for DX score.
(11/17)

So, we established a framework that would account for spectrum of injury instead of using a ‘control vs. disease’ grouping schematic with linear regression to identify gene expression changes with gestational age (GA) and life span (LS) (LS = proxy for the degree of injury).
(10/17)

We then wanted to study the gene expression changes associated with both development and injury. However, every infant born prematurely experiences different levels of neonatal lung injury depending on a variety of factors (exposure to oxygen, mechanical ventilation, steroid treatments, etc).
(9/17)

One representative example is TNiche 1, which represents the alveolar niche and is composed of the key alveolar cell types, including AT1, AT2, and capillaries, and we can see that this niche increases in abundance across gestation, consistent with alveologenesis throughout lung development!
(8/17)

Then, we computationally identified 11 multicellular spatial “niches” using both Seurat v5 and an transcript-based approach developed by Dr. Ruqian Lyu in @davisjmcc.bsky.social’s group (www.biorxiv.org/content/10.1...). Both approaches found generally concordant results.
(7/17)

As an example, we find capillaries and alveolar type 1 (AT1) cells are unlikely to occur next to one another in samples from the early/late canalicular periods; but in samples from the alveolar stage of development and the adult BPD sample, they are more likely to be close to one another.
(6/17)

We then defined the cell-cell interactions across development, and to do this, we used cell proximity to quantify the likelihood that cell type pairs were in close proximity to one another within each developmental stage. This creates a map of cell interactions across the developing lung.
(5/17)

We were able to identify 40 unique cell populations across the 4 lineages, using canonical hallmarks established in previous studies. We noticed differences in cell type proportions as gestational age increased, reflecting different cell-specific patterns as development progressed.
(4/17)

With @10xgenomics.bsky.social, we profiled the expression of 343 genes from 17 human infant lung samples across a range of gestational ages and disease pathologies. We generated a ton of data (76 million transcripts in 1.2 million cells) - the largest spatial human neonatal lung dataset yet!
(3/17)

Human lung development requires carefully coordinated cellular communication to create sufficient surface area that can support gas exchange, and the exact molecular mechanisms and spatiotemporal relationships of various developmental pathways during lung development is unknown.
(2/17)

A spatial transcriptomic atlas of acute neonatal lung injury across development and disease severity A molecular understanding of lung organogenesis requires delineation of the timing and regulation of the cellular transitions that ultimately form and support a surface capable of gas exchange. While ...

I am so excited to share our most recent work & my first big project as a graduate student! We leveraged spatial transcriptomics to study the cell-cell communication involved in human lung development. Here’s the full study: www.biorxiv.org/content/10.1...
(1/17)

Congrats to @saahimall.bsky.social on her first study from her PhD! Also, science is always more fun when done with friends. Great to work as always with @jensucre.bsky.social and @jkropski.bsky.social!

best lab everrrrrrrrr

It's not every day your work is on the cover of a magazine. Congrats to first author and TGen post-doc, @annikavannan.bsky.social, @nebanovich.bsky.social, his team and collaborators on earning the cover of this month's publication of @naturegenet.bsky.social 🧬 🫁 👏 Photo courtesy of Nature Genetics

Protest sign with black text listing a subset of words that were flagged for further scrutiny by federal agencies (including “bias” “increase diversity” “disability” “racism” “trauma” “victim” and “women”). In large red letters over top, the words “These words kill fascists” is written, an homage to Woody Guthrie.

We will keep fighting and standing up for science.

Dynamic responses to rejection in the transplanted human heart revealed through spatial transcriptomics Allograft rejection following solid-organ transplantation is a major cause of graft dysfunction and mortality. Current approaches to diagnosis rely on histology, which exhibits wide diagnostic variabi...

I am excited to share our most recent work using spatial transcriptomics to uncover dynamic molecular responses to rejection in transplanted human hearts! 1/15
www.biorxiv.org/content/10.1...

Hi everyone, I’m the graduate student here. I’ve never felt a worse feeling than this moment. There is no way to justify what’s been happening.

I wasn’t even notified that my study section wasn’t meeting. I still haven’t been notified. I’ve effectively been ghosted by the NIH - make it make sense.