Tuuli Lappalainen
@tuuliel.bsky.social
Professor at KTH, NY Genome Center, SciLifeLab, working on functional genomics and human genetics.
....tai sitten ei. @villeniinisto.vihreat.fi ei antanut ihan oikeaa kokonaiskuvaa mikäli ao. lähde pitää paikkansa. Lakimuutokset on enemmistön takana, mutta puolueiden välinen sopimusta voi muuttaa vain 3/4 enemmistöllä.
puheenvuoro.uusisuomi.fi/villekalervo...
puheenvuoro.uusisuomi.fi/villekalervo...
October 14, 2025 at 4:10 PM
....tai sitten ei. @villeniinisto.vihreat.fi ei antanut ihan oikeaa kokonaiskuvaa mikäli ao. lähde pitää paikkansa. Lakimuutokset on enemmistön takana, mutta puolueiden välinen sopimusta voi muuttaa vain 3/4 enemmistöllä.
puheenvuoro.uusisuomi.fi/villekalervo...
puheenvuoro.uusisuomi.fi/villekalervo...
Neither approach does a stellar job, but I'm an optimist: Our works points to future potential, with larger and more diverse studies. The genes detected in these 1st gen CRISPRi work look pretty similar to eQTL data from 15 years ago (I was there). There is much to discover!
May 6, 2025 at 5:01 PM
Neither approach does a stellar job, but I'm an optimist: Our works points to future potential, with larger and more diverse studies. The genes detected in these 1st gen CRISPRi work look pretty similar to eQTL data from 15 years ago (I was there). There is much to discover!
Overall, this provides important insights in cis-target gene discovery from eQTLs and CRISPRi. I think we're ultimately going to need both tools, as both have fundamental weaknesses: eQTL's bias against constrained genes, and difficulty of applying CRISPR to diverse cell types.
May 6, 2025 at 5:01 PM
Overall, this provides important insights in cis-target gene discovery from eQTLs and CRISPRi. I think we're ultimately going to need both tools, as both have fundamental weaknesses: eQTL's bias against constrained genes, and difficulty of applying CRISPR to diverse cell types.
The analysis of gold-standard genes in these GWAS loci shows how much you'd miss using only one approach, and how startlingly orthogonal the discoveries are. The patterns are highly variable between the loci. It depends on your downstream application if you prefer higher sensitivity vs specificity.
May 6, 2025 at 5:01 PM
The analysis of gold-standard genes in these GWAS loci shows how much you'd miss using only one approach, and how startlingly orthogonal the discoveries are. The patterns are highly variable between the loci. It depends on your downstream application if you prefer higher sensitivity vs specificity.
Analysis of the loci where the gold-standard gene was missed looks pretty grim: eQTLs find other i.e. misleading genes, while CRISPRi often lacks power. "Wow they both suck, but in totally different ways" was my first reaction to this plot.
May 6, 2025 at 5:01 PM
Analysis of the loci where the gold-standard gene was missed looks pretty grim: eQTLs find other i.e. misleading genes, while CRISPRi often lacks power. "Wow they both suck, but in totally different ways" was my first reaction to this plot.
The 💰 question: what about “true” causal gene discovery? We compiled a list of 421 gold-standard genes, of which 53 were discovered as eGenes and 23 as cGenes - and only 9 with both! A higher proportion of cGenes are gold-standard genes, compared to eGenes or Hi-C targets.
May 6, 2025 at 5:01 PM
The 💰 question: what about “true” causal gene discovery? We compiled a list of 421 gold-standard genes, of which 53 were discovered as eGenes and 23 as cGenes - and only 9 with both! A higher proportion of cGenes are gold-standard genes, compared to eGenes or Hi-C targets.
eGenes and cGenes have different properties too: cGenes are fewer, proximal, more constrained and more buffered, while eQTL mapping (especially across many cell types) finds more genes per locus, including distal ones. This is consistent with previous empirical work and theoretical work on eQTLs.
May 6, 2025 at 5:01 PM
eGenes and cGenes have different properties too: cGenes are fewer, proximal, more constrained and more buffered, while eQTL mapping (especially across many cell types) finds more genes per locus, including distal ones. This is consistent with previous empirical work and theoretical work on eQTLs.
Target genes do overlap, but not so much. This is partly due to power: sc-eQTLs contribute little, eQTLs struggle with low-freq variants, CRISPRi with low expr genes. CRISPRi (but not eQTL) power is low in non-overlapping loci, indicating that bigger CRISPRi studies -> better convergence.
May 6, 2025 at 5:01 PM
Target genes do overlap, but not so much. This is partly due to power: sc-eQTLs contribute little, eQTLs struggle with low-freq variants, CRISPRi with low expr genes. CRISPRi (but not eQTL) power is low in non-overlapping loci, indicating that bigger CRISPRi studies -> better convergence.
Briefly, we analyzed blood trait GWAS, eQTLs from blood cell types, and CRE (enhancer) CRISPRi+scRNA-seq data from K562s, primarily from Gasperini et al. and our own Morris et al. (with @johnomix.bsky.social). We were then able to analyze the overlap of discoveries in 882 GWAS CREs.
May 6, 2025 at 5:01 PM
Briefly, we analyzed blood trait GWAS, eQTLs from blood cell types, and CRE (enhancer) CRISPRi+scRNA-seq data from K562s, primarily from Gasperini et al. and our own Morris et al. (with @johnomix.bsky.social). We were then able to analyze the overlap of discoveries in 882 GWAS CREs.
We've worked on eQTLs and CRISPR for 10+ years now, and 4 years ago I hypothesized about their orthogonal strengths and weaknesses, for a review paper with @dgmacarthur.bsky.social. It’s exciting to finally have enough empirical data for a systematic analysis.
www.science.org/doi/10.1126/...
www.science.org/doi/10.1126/...
May 6, 2025 at 5:01 PM
We've worked on eQTLs and CRISPR for 10+ years now, and 4 years ago I hypothesized about their orthogonal strengths and weaknesses, for a review paper with @dgmacarthur.bsky.social. It’s exciting to finally have enough empirical data for a systematic analysis.
www.science.org/doi/10.1126/...
www.science.org/doi/10.1126/...
Our new contribution to the quest to find causal GWAS genes! Sam Ghatan from my lab at @nygenome.org led a systematic comparison of eQTLs and CRISPRi+scRNA-seq screens. TL;DR: they provide highly complementary insights, with ortogonal pros and cons. 🧵👇
www.biorxiv.org/content/10.1...
www.biorxiv.org/content/10.1...
May 6, 2025 at 5:01 PM
Our new contribution to the quest to find causal GWAS genes! Sam Ghatan from my lab at @nygenome.org led a systematic comparison of eQTLs and CRISPRi+scRNA-seq screens. TL;DR: they provide highly complementary insights, with ortogonal pros and cons. 🧵👇
www.biorxiv.org/content/10.1...
www.biorxiv.org/content/10.1...
Drug target genes for a given disease share enrichments with genetically implicated genes. We also show vignettes of genes that are genetically associated to a disease, expressed in disease-enriched structures, and targets for known drugs.
May 5, 2025 at 3:40 PM
Drug target genes for a given disease share enrichments with genetically implicated genes. We also show vignettes of genes that are genetically associated to a disease, expressed in disease-enriched structures, and targets for known drugs.
But what about spatial vs cell type data? Analyzing sc/sn data from the brain suggests that some diseases could arise from dysfunction in a particular cell type that may or may not be spatially enriched, while others may derive from dysfunction of multiple cell types in a given tissue structure.
May 5, 2025 at 3:40 PM
But what about spatial vs cell type data? Analyzing sc/sn data from the brain suggests that some diseases could arise from dysfunction in a particular cell type that may or may not be spatially enriched, while others may derive from dysfunction of multiple cell types in a given tissue structure.
The brain is particularly cool, with its well-defined substructure. We see the expected neuropsych enrichment in cortex, while Alzheimer’s genes are enriched in white matter, thalamus and choroid plexus. Spatial correlation shows subclusters of disease genes in distinct spatial domains.
May 5, 2025 at 3:40 PM
The brain is particularly cool, with its well-defined substructure. We see the expected neuropsych enrichment in cortex, while Alzheimer’s genes are enriched in white matter, thalamus and choroid plexus. Spatial correlation shows subclusters of disease genes in distinct spatial domains.
While genes often showed a broad enrichment across a tissue, in about 20% of disease-tissue pairs only a subset of tissue structures were enriched, highlighting the value of spatial data. Cool patterns across many diseases/tissues - and a big resource for domain specialists to explore!
May 5, 2025 at 3:40 PM
While genes often showed a broad enrichment across a tissue, in about 20% of disease-tissue pairs only a subset of tissue structures were enriched, highlighting the value of spatial data. Cool patterns across many diseases/tissues - and a big resource for domain specialists to explore!
We processed 31 published 🐭 & 🙂 spatial datasets from 8 organs with genetically implicated (and drug target) genes in 32 human diseases from @opentargets.org. We then mapped the tissue structures where disease genes are higher expressed than the null, using our new approach STEAM.
May 5, 2025 at 3:40 PM
We processed 31 published 🐭 & 🙂 spatial datasets from 8 organs with genetically implicated (and drug target) genes in 32 human diseases from @opentargets.org. We then mapped the tissue structures where disease genes are higher expressed than the null, using our new approach STEAM.
This vision is a result of a true community effort, extending even beyond this long list of co-authors. Many thanks to everyone who's contributed. Now we’re gearing up for implementation - so stay tuned!
April 7, 2025 at 11:48 AM
This vision is a result of a true community effort, extending even beyond this long list of co-authors. Many thanks to everyone who's contributed. Now we’re gearing up for implementation - so stay tuned!
Streamlining data access - in an ethically sustainable way - is the key to data-driven science, and recent technical and regulatory advances will facilitate this. We want to pursue PROMISE in partnerships between academia, healthcare and industry for not just cool science but society-wide impact.
April 7, 2025 at 11:48 AM
Streamlining data access - in an ethically sustainable way - is the key to data-driven science, and recent technical and regulatory advances will facilitate this. We want to pursue PROMISE in partnerships between academia, healthcare and industry for not just cool science but society-wide impact.
We all know and love UKBB, FinnGen etc - and Sweden has some catching up to do. But we want to seek further gains in data-driven precision omics with Sweden's longitudinal records, multi-omics capabilities at @scilifelab.se, and translational approaches pioneered by Genomic Medicine Sweden.
April 7, 2025 at 11:48 AM
We all know and love UKBB, FinnGen etc - and Sweden has some catching up to do. But we want to seek further gains in data-driven precision omics with Sweden's longitudinal records, multi-omics capabilities at @scilifelab.se, and translational approaches pioneered by Genomic Medicine Sweden.
They don't provide an explicit definition of "transcriptotype", but I don't see how it couldn't be replaced with "gene expression level".
March 19, 2025 at 10:24 AM
They don't provide an explicit definition of "transcriptotype", but I don't see how it couldn't be replaced with "gene expression level".
Works for me. I don't know why they'd be under particularly heavy traffic though...
February 18, 2025 at 7:11 PM
Works for me. I don't know why they'd be under particularly heavy traffic though...
One month to go until the CSHL Biology of Genomes abstract deadline! My all-time fav meeting, and one of the few covering genomics broadly. We have a ✨🤩 lineup of speakers, but it's the abstract talks & posters that really make the meeting - send us your best work! meetings.cshl.edu/meetings.asp...
January 14, 2025 at 1:57 PM
One month to go until the CSHL Biology of Genomes abstract deadline! My all-time fav meeting, and one of the few covering genomics broadly. We have a ✨🤩 lineup of speakers, but it's the abstract talks & posters that really make the meeting - send us your best work! meetings.cshl.edu/meetings.asp...
🌟 Exciting news: The Leena Peltonen School of Human Genetics returns in 2025!
We're excited to bring PhD students together with an all-star list of leaders in human genetics.
📅 July 27-31, 2025
📍 Wellcome Genome Campus, UK
📝 Apply by March 7 at www.lpshg.com
We're excited to bring PhD students together with an all-star list of leaders in human genetics.
📅 July 27-31, 2025
📍 Wellcome Genome Campus, UK
📝 Apply by March 7 at www.lpshg.com
December 18, 2024 at 12:42 PM
🌟 Exciting news: The Leena Peltonen School of Human Genetics returns in 2025!
We're excited to bring PhD students together with an all-star list of leaders in human genetics.
📅 July 27-31, 2025
📍 Wellcome Genome Campus, UK
📝 Apply by March 7 at www.lpshg.com
We're excited to bring PhD students together with an all-star list of leaders in human genetics.
📅 July 27-31, 2025
📍 Wellcome Genome Campus, UK
📝 Apply by March 7 at www.lpshg.com
Endorsement from Elsa!
November 29, 2024 at 7:55 AM
Endorsement from Elsa!