<p>Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics<sup><CitationRef AdditionalCitationIDS="CR2 CR3 CR4" CitationID="CR1">1</CitationRef>–<CitationRef CitationID="CR5">5</CitationRef></sup>. Most of these variants individually have weak effects<sup><CitationRef CitationID="CR6">6</CitationRef></sup> and lie in non-coding gene-regulatory elements<sup><CitationRef AdditionalCitationIDS="CR8 CR9" CitationID="CR7">7</CitationRef>–<CitationRef CitationID="CR10">10</CitationRef></sup>, for which we lack a complete understanding of how single-nucleotide alterations modulate transcriptional processes to affect human phenotypes<sup><CitationRef CitationID="CR5">5</CitationRef>,<CitationRef AdditionalCitationIDS="CR12 CR13 CR14" CitationID="CR11">11</CitationRef>–<CitationRef CitationID="CR15">15</CitationRef></sup>. To address this problem, we measured the activity of 221,412 fine-mapped trait-associated variants using a massively parallel reporter assay<sup><CitationRef AdditionalCitationIDS="CR17 CR18 CR19" CitationID="CR16">16</CitationRef>–<CitationRef CitationID="CR20">20</CitationRef></sup> 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.</p>

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Functional dissection of complex trait variants at single-nucleotide resolution

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

摘要

Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics15. Most of these variants individually have weak effects6 and lie in non-coding gene-regulatory elements710, for which we lack a complete understanding of how single-nucleotide alterations modulate transcriptional processes to affect human phenotypes5,1115. To address this problem, we measured the activity of 221,412 fine-mapped trait-associated variants using a massively parallel reporter assay1620 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.