美国杰克逊实验室Ryan Tewhey小组研究出单核苷酸分辨率下复杂性状变异的功能解剖。该项研究成果发表在2026年2月25日出版的《自然》上。

这些变异中的大多数单独作用较弱，并且存在于非编码基因调控元件中，因此该课题组对单核苷酸改变如何调节转录过程从而影响人类表型缺乏完整的了解。为了解决这个问题，课题组在5种不同的细胞类型中测量了221412个精细定位的性状相关变异的活性，并进行了大规模并行报告分析。研究组表明，该分析有效地区分了可能的致病变体和对照，并以高精度确定了13121个调节变体。虽然这些变异的影响在很大程度上与功能的正交测量相一致，但只有69%的变异可以用已知转录因子结合基序的破坏来解释。

该课题组研究了136个变异的饱和诱变机制，并为91%的变异分配了受影响的转录因子，但没有明确的典型机制。最后，课题组在近距离检测到11%的被测调节变异的调控上位性，并在性状相关位点的一个小但重要的子集上发现了相同单倍型的多个功能变异。总的来说，他们的研究提供了一个系统的功能特征，可能是复杂和分子人类特征的基础，使人们能够对潜在疾病风险的调节语法有新的认识。

据悉，确定遗传变异和驱动复杂性状和疾病的机制仍然是人类遗传学的核心问题。

附：英文原文

Title: Functional dissection of complex trait variants at single-nucleotide resolution

Author: Siraj, Layla, Castro, Rodrigo I., Dewey, Hannah B., Kales, Susan, Butts, John C., Nguyen, Thanh Thanh L., Kanai, Masahiro, Berenzy, Daniel, Mouri, Kousuke, Wang, Qingbo S., Fiziev, Petko P., Tsuo, Kristin, McCaw, Zachary R., Gosai, Sager J., Aguet, Franois, Cui, Ran, Kassam, Irfahan, McRae, Jeremy, Vockley, Christopher M., Lareau, Caleb A., Abramov, Sergey, Boystov, Alexandr, Vierstra, Jeff, Okada, Yukinori, Gusev, Alexander, Jones, Thouis R., Lander, Eric S., Sabeti, Pardis C., Finucane, Hilary K., Reilly, Steven K., Ulirsch, Jacob C., Tewhey, Ryan

Issue&Volume: 2026-02-25

Abstract: Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics1,2,3,4,5. Most of these variants individually have weak effects6 and lie in non-coding gene-regulatory elements7,8,9,10, for which we lack a complete understanding of how single-nucleotide alterations modulate transcriptional processes to affect human phenotypes5,11,12,13,14,15. To address this problem, we measured the activity of 221,412 fine-mapped trait-associated variants using a massively parallel reporter assay16,17,18,19,20 in 5 diverse cell types. We show that this assay effectively discriminates between likely causal variants and controls, and identified 13,121 regulatory variants with high precision. Although the effects of these variants largely agree with orthogonal measures of function, only 69% of them can plausibly be explained by the disruption of a known transcription factor binding motif. We investigated the mechanisms of 136 variants using saturation mutagenesis and assigned affected transcription factors for 91% of variants without a clear canonical mechanism. Finally, we detected regulatory epistasis at 11% of tested regulatory variants in close proximity and identified multiple functional variants on the same haplotype at a small, but important, subset of trait-associated loci. Overall, our study provides a systematic functional characterization of likely causal common variants that underlie complex and molecular human traits, enabling new insights into the regulatory grammar underlying disease risk.

DOI: 10.1038/s41586-026-10121-6

Source: https://www.nature.com/articles/s41586-026-10121-6