Tianxiong (Bear) Yu
@tianxiong-bear-yu.bsky.social
78 followers 150 following 14 posts
Instructor in UMass Chan Medical School. Focus on using Computational Methods to study transposons in human and koala genomes.
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tianxiong-bear-yu.bsky.social
As we age, our brains change at both the genomic and transcriptomic levels. 🧠✨
In our new Nature @nature.com paper, we map these changes at single-cell resolution in the human prefrontal cortex from infancy to centenarian.
Honored to lead the data analysis and be co-first author on this work!
Single-cell transcriptomic and genomic changes in the ageing human brain - Nature
Sequencing analyses of human prefrontal cortex from donors ranging in age from 0.4 to 104 years show that ageing correlates with an accumulation of somatic mutations in short housekeeping genes a...
www.nature.com
Reposted by Tianxiong (Bear) Yu
tianxiong-bear-yu.bsky.social
5/5. I’m deeply grateful to my amazing co-first author Ailsa Jeffries — it was a joy to work together on this project. Special thanks to my mentors Michael Lodato and Zhiping Weng for their guidance and support throughout this work.
tianxiong-bear-yu.bsky.social
4/5. Finally, a linear model showed that high basal expression and short gene length are linked to decreased expression with ageing.
Housekeeping genes are short and highly active. Our analysis suggests they are prone to damage, mutation, and disrupted expression and function during ageing.
a, Mixed-effects linear model identifying determinants of downregulation in excitatory neurons (model performance R2=0.54). Gene and exon length positively correlated with ageing-related fold change (FC) in expression. Length-normalized expression in excitatory neurons and frontal cortex expression (GTEx database) negatively correlated with ageing-related fold change. Significance of linear model correlations was determined by two-sided t-test. b, Density plots of the length of downregulated genes (solid lines) and all expressed genes (dashed lines) for each cell type. Mean lengths for downregulated genes are shown; asterisks denote significant differences from the mean neuronal downregulated length. c, Expression of topoisomerase complex genes across cell types. Asterisks denote significant differences in the percentage of cells expressing between neurons and non-neurons (two-sided Wilcoxon rank-sum test). d, Housekeeping genes (n=1,802) are significantly shorter than neuron-specific genes (n=288). e, Short (decile 1) housekeeping and neuron-specific genes showed differential expression in adult excitatory neurons CPKM, counts per kilobase per million. f,g, Fold change (elderly/adult) of housekeeping genes (f) and neuron-specific genes (g) by length decile in excitatory neurons.
tianxiong-bear-yu.bsky.social
3/5. Using scWGS, we identified somatic SNVs in neurons. Signature analysis revealed a predominant age-related mutation signature (A1; mainly C>T and T>C). Signature A1 mutations accumulate at ~12.1 per neuron per year and are likely driven by transcriptional activity.
a, De novo mutational signature analysis of sSNVs in human neurons revealed two signatures: A1 dominated by T>C mutations and A2 dominated by C>T mutations. b, Number of signature A1 sSNVs in each neuron plotted by age. Signature A1 strongly correlates with age (R2 = 0.88) with an extrapolated mutation rate of 12.1 SNVs per year. c, sSNV enrichment of signature A1 in coding regions plotted by neuron expression quantile (left) and genic versus intergenic regions (right). Signature A1 is enriched in the highest-expressed genes and genic regions (chi-squared test). d, Percentage of total sSNVs derived from the transcribed strand broken down by expression quantile. T>C and C>T strand bias increases with expression. e, Number of signature A2 sSNVs in each neuron plotted by age. Signature A2 correlates with age (R2 = 0.42) with an extrapolated mutation rate of 3 SNVs per year. f, sSNV enrichment of signature A2 in coding regions plotted by neuron expression quantile (left) and genic versus intergenic regions (right). Signature A2 is depleted in the highest-expressed genes and enriched in the lowest-expressed genes as well as intergenic regions.
tianxiong-bear-yu.bsky.social
2/5. We further found that housekeeping genes (involved in ribosomes, transport, and metabolism) show a common decrease in expression across both neurons and glia. Conversely, neuron-specific gene expression generally remains stable throughout life.
a, Number of downregulated (blue) and upregulated (red) genes for each cell type in elderly donors. DEGs, differentially expressed genes. b, Heat map of significantly downregulated differentially expressed genes in elderly donors. Genes not differentially expressed are in white. The leftmost genes are defined as common across cell types (down in one or more excitatory, one or more inhibitory and two or more non-neuronal cell types). c, GO terms of genes downregulated in ageing plotted as general categories. Housekeeping functions (shades of blue) are commonly downregulated. d, Housekeeping genes are significantly downregulated in elderly relative to adult brains in all neuron types. e, Mean gene effect score for all of the downregulated (blue) and upregulated (red) genes (in elderly versus adult donors) in the DepMap database. The downregulated genes for both neurons (left) and microglia (right) are more essential than the upregulated genes.
tianxiong-bear-yu.bsky.social
1/5. Using snRNA-seq, we found no differences in the overall ratios of neurons to glia or excitatory to inhibitory neurons. However, we identified subtypes of excitatory neurons and astrocytes unique to the infant PFC. These infant-specific cells are enriched for neurodevelopmental genes.
Clusters plotted by donor contribution as a percentage of total cells in the cluster. L2/3-2 and Ast-3 are composed nearly completely of nuclei from infant donors
tianxiong-bear-yu.bsky.social
As we age, our brains change at both the genomic and transcriptomic levels. 🧠✨
In our new Nature @nature.com paper, we map these changes at single-cell resolution in the human prefrontal cortex from infancy to centenarian.
Honored to lead the data analysis and be co-first author on this work!
Single-cell transcriptomic and genomic changes in the ageing human brain - Nature
Sequencing analyses of human prefrontal cortex from donors ranging in age from 0.4 to 104 years show that ageing correlates with an accumulation of somatic mutations in short housekeeping genes a...
www.nature.com
Reposted by Tianxiong (Bear) Yu
twigtechnology.bsky.social
New study led by Joanna Baker shows bigger brains and relatively longer thumbs coevolved in primates. Humans have huge thumbs, but only what our brain size (esp. neocortex) would predict. It’s NOT driven by tool use.

A fantastic paper with a huge amount of work, and superb data presentation 🧪🏺👍🧠💀🐒🦧
Human dexterity and brains evolved hand in hand - Communications Biology
Thumbs and brains coevolved in primates. Across living and extinct species, longer thumbs predict bigger brains, highlighting the neural cost of dexterity.
www.nature.com
Reposted by Tianxiong (Bear) Yu
juliusbrennecke.bsky.social
Pls. share widely

Calling all transposon fans & lovers of genetic innovation

MOBILE GENOME welcomes you in Heidelberg, Nov. 4–7 2025

→ Vibrant & friendly community
→ Cutting-edge talks from mechanisms to physiology
→ Plenty of surprises (TEs never stop innovating)

submit abstract by July 29
events.embl.org
⏰ Abstract deadline for 'The mobile genome' is 29 July!

👉 https://s.embl.org/mge25-01-bl

Join us 4–7 Nov 2025 at EMBL Heidelberg (or online) to explore the impact of TEs across biology. 🧬🔍

⭐🧑🏼‍🔬 24 talks + 15 flash talks from posters – don't miss out!

#EMBOMobileGenome
tianxiong-bear-yu.bsky.social
Finally got my personal academia website done. I am glad it looks well-organized for both laptop and phone.
Big shout to "Academia Pages" GitHub pages template.
tianxiongbb.github.io
About me
tianxiongbb.github.io
Reposted by Tianxiong (Bear) Yu
Reposted by Tianxiong (Bear) Yu
cp-cell.bsky.social
The new issue is out! 👉 cell.com/cell/current

In this issue of Cell, Yu et al. capture evolution of KoRV-A transcriptional silencing as the virus transitions from a pathogen to a stable endogenous retrovirus. The cover features an adult koala with a joey.

📷 Credit: Currumbin Wildlife Sanctuary
Reposted by Tianxiong (Bear) Yu
juliusbrennecke.bsky.social
We are seeking a new colleague to join us at the Vienna BioCenter, specifically at my beloved home institution, IMBA @imbavienna.bsky.social

we value collegiality and a passion for curiosity driven science. Being a great and fun human being also helps!
imbavienna.bsky.social
IMBA is recruiting a Junior Group Leader! Are you interested in starting your own lab, pursuing curiosity-driven basic research in the life sciences? Apply now to our group leader position. The deadline is May 28. Link is below.
Reposted by Tianxiong (Bear) Yu
juliusbrennecke.bsky.social
In the ‘90s, Pelisson et al. found that gypsy retrotransposons in flies can go viral—literally—thanks to an envelope gene. Now, @mayavoichek.bsky.social uncovers a wild new path to retrotransposon infectivity. A fascinating story—see Maya's thread
www.biorxiv.org/content/10.1101/2025.03.14.642691v2
Reposted by Tianxiong (Bear) Yu
umasschan.bsky.social
Working with a team at the University of Queensland, UMass Chan scientists have discovered that a population of koalas has evolved genomic immunity to a retrovirus: direc.to/mDfy

#koalas @lubanlab.bsky.social @tianxiong-bear-yu.bsky.social
William E. Theurkauf, PhD; Jeremy Luban, MD; Tianxiong Yu, PhD; and Zhiping Weng, PhD A koala
Reposted by Tianxiong (Bear) Yu
saezlab.bsky.social
📄 Update on our preprint about Gene Regulatory Net (GRN) benchmarking 📄
We have included the original and decoupled version of SCENIC+, added a new metric and two more databases. Dictys and SCENIC+ outperformed others, but still performed poorly in causal mechanistic tasks.
doi.org/10.1101/2024... 👇
Performance of multimodal GRN inference methods. SCENIC+ and Dictys outperform others.
Reposted by Tianxiong (Bear) Yu
wayomayo.bsky.social
New preprint of my postdoc work! We found a novel group of zinc-finger proteins that rapidly evolved in a lineage-specific manner to repress regulatory activities of transposon-derived sequences through anchoring nucleosomes. #TEsky

biorxiv.org/content/10.110…
tianxiong-bear-yu.bsky.social
6/6. The two-phased response mirrors the innate and adaptive immunity: first recognize the pattern then the sequence of a new invader. Analyzing 400+ published koala DNA-seq data revealed the second phase response trigger – MAP4K4 KoRV-A provirus – is under selection and sweeping to fixation.
tianxiong-bear-yu.bsky.social
5/6. The antisense piRNAs directs its binding partner PIWI to recruit DNA methylation machinery co-transcriptionally at KoRV-A proviruses genome wide, leading to a 10–fold decreasing of KoRV-A expression compared to koalas without the MAP4K4 provirus.
K94276 (green): koala with the MAP4K4 provirus.
K98224 (blue): koala without the MAP4K4 provirus
tianxiong-bear-yu.bsky.social
4/6. We identified the second phase in koalas north of the River. It was triggered when the KoRV-A sequence was captured by a genic (i.e. MAP4K4) 3´UTR. Transcripts antisense to KoRV-A are made, as well as antisense piRNAs processed from these transcripts.