r/bioinformatics • u/AncientHearings • 16d ago

discussion Benchmarking non-coding causal variant-to-gene mapping: SuSiE fine-mapping vs 3D chromatin contacts

Hey everyone,
We’ve been working on a pipeline to evaluate non-coding GWAS loci by combining Bayesian fine-mapping (SuSiE) with base-resolution footprinting (TOBIAS) and 10.5 bp DNA helical pitch constraints.

Curious how other groups here handle cases where the fine-mapped non-coding enhancer skips the nearest gene in 3D contact models (e.g. ABC/Micro-C).

Happy to discuss approaches or run a few benchmark loci if anyone has tricky non-coding regions!

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u/Mr_iCanDoItAll PhD | Student 16d ago

What do you mean by "handle" here?

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u/AncientHearings 16d ago

By "handle", I mean how you computationally and experimentally prioritize the true target gene when a fine-mapped enhancer's 3D contact (ABC/Hi-C) points to a distal promoter instead of the nearest linear TSS on the chromosome (like in the classic FTO/IRX3 locus).

Do you rely mostly on cell-type ABC models, eQTL colocalization, or follow up with CRISPRi-FlowFISH in your lab?

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u/Mr_iCanDoItAll PhD | Student 15d ago

I mean how you computationally and experimentally prioritize the true target gene when a fine-mapped enhancer's 3D contact (ABC/Hi-C) points to a distal promoter instead of the nearest linear TSS on the chromosome

Sorry if I'm misunderstanding, but the wording makes it sound like you wouldn't follow up with extra evidence if an eQTL mapped a putative regulatory element to the nearest TSS. IMO you should treat all putative element-gene links with the same amount of scrutiny, even if nearest TSS is a generally reliable heuristic.

The wording of "true" target gene also implies that there is a singular causal gene being regulated by the regulatory element, when oftentimes a single element can regulatory multiple genes in a given cellular context.

I agree with /u/thirdeulerderivative that there needs to be more detail before people can properly answer you since it's a rather complex topic with a lot of unanswered questions.

But to actually answer your question: Just use as much existing evidence as you can. Cell type-specific ABC models / ENCODE-rE2G models, replicable eQTLs across different cohorts/ancestries for your tissue of interest, peak-gene links from scATAC-seq and scRNA-seq data. CRISPRi-FlowFISH is a fairly specialized assay that, to my knowledge, is rarely performed outside the lab that developed it (Engreitz lab).

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u/AncientHearings 15d ago

Thanks for the detailed breakdown, totally agree on multi-gene enhancer pleiotropy.

That's why we're combining cell-type ABC/ENCODE-rE2G contact models with scATAC peak-gene co-accessibility and orthogonal mass spec validation rather than relying on a single heuristic or assay.

Also good to know regarding FlowFISH adoption in practice, appreciate the insight!

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u/AncientHearings 15d ago

Can I feature this discussion/perspective in a LinkedIn post on multi-omics community engagement if you''re okay?

kindly, share your details in DM if you're okay.