Tandem repeat variation shapes immune cell type-specific gene expression

Key numbers

• 30.7% of which are specific
• 6.1% of tested genes

Tandem repeats (TRs)-highly polymorphic, repetitive sequences across the human genome-are important regulators of gene expression but remain underexplored due to challenges in accurate genotyping and analysis1. Here we generate whole-genome and single-cell RNA sequencing from more than 5.4 million blood-derived cells across 1,925 individuals in two cohorts2, and perform meta-analysis to characterize the impact of variation in more than 1.7 million TR loci on immune cell type-specific gene expression. We identify more than 69,000 single-cell expression quantitative trait loci, 30.7% of which are specific to 1 of 28 immune cell types, and reveal dynamic regulatory effects using cell-state inference. Matched single-cell assay for transposase-accessible chromatin with high-throughput sequencing profiles from more than 3.4 million nuclei in 922 individuals3 uncover chromatin accessibility quantitative trait loci for nearly one-third of expression-associated TRs, supporting coordinated effects on cis-regulatory architecture. Fine-mapping implicates 1,490 TRs as candidate causal drivers of gene expression in 6.1% of tested genes, and colocalization analyses highlight more than 200 genes in which TRs likely mediate genetic associations with immune and haematological traits. Together, these results provide a genome-wide, multiomic view of TR-mediated regulation in the human immune system, establishing TRs as key contributors to cell type-specific regulatory variation and complex trait architecture.

Hope A Tanudisastro, Anna S E Cuomo, Ben Weisburd, Matthew Welland, Eleanor Spenceley, Michael Franklin, Angli Xue, Hao Lawrence Huang, Blake Bowen, Jianan Fan, Oscar A Dong, Albert Henry, Peter C Allen, Kristof Wing, Owen Tang, Michael Gray, Andre L M Reis, Jonathan Margoliash, Nehir E Kurtas, Jeffrey M Pullin, Arthur S Lee, Harrison Brand, Michael Harper, Katalina Bobowik, Michael Silk, Amy Miniter, John Marshall, Vivian Bakiris, Bindu Swapna Madala, Caitlin Uren, et al.

Leverage3 / 5

A method or resource many groups across the field will adopt within a year.

10% of this desk’s rubric

Magnitude3 / 5

Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.

20% of this desk’s rubric

Evidence3 / 5

Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.

32% of this desk’s rubric

Novelty3 / 5

A genuinely new approach to an open problem.

8% of this desk’s rubric

Trajectory2 / 5

Some room to improve with obvious engineering.

5% of this desk’s rubric

Stakes2 / 5

Benefits a professional community (practitioners, clinicians, engineers).

25% of this desk’s rubric

• Citations3 (reference 20, via openalex, Oct 30, 2026, 05:48 UTC)

• Reviewed by heuristic-v10 on Oct 30, 2026, 06:17 UTC. Paper type: empirical.
• Categories: Journal Article
• BRIEF, No.2 in the Biology edition of October 30, 2026.