Evidence map›Paper›PMID 35951677›Full record

ArticleScience (New York, N.Y.)2022

Nested epistasis enhancer networks for robust genome regulation.

Xueqiu Lin, Yanxia Liu, Shuai Liu, Xiang Zhu, Lingling Wu, Yanyu Zhu, Dehua Zhao, Xiaoshu Xu, Augustine Chemparathy, Haifeng Wang and 7 more

Abstract read
In one paragraph

Article in Science (New York, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

81 citing papers in PubMed.

  1. Article
  2. Testing for Genetic Interactions in Complex Disease With Distance Correlation.Biometrical journal. Biometrische Zeitschrift · 2026
    Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Locus-Scale Massively Parallel Reporter Assays.bioRxiv : the preprint server for biology · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Remodeling ofScience advances · 2026
    Article
  20. Article

21 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Xueqiu Lin *Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0001-8706-9657
Yanxia Liu *Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-6550-3624
Shuai Liu *Laboratory of Epigenome Biology, Systems Biology Center, National Heart, Lung and Blood Institute NIH, Bethesda, MD 20892, USA.ORCID 0000-0002-6069-4900
Xiang ZhuDepartment of Statistics, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0003-1134-6413
Lingling WuDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-6921-1127
Yanyu ZhuDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0001-8681-976X
Dehua ZhaoDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Xiaoshu XuDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Augustine ChemparathySchool of Medicine, Stanford University, Stanford, CA 94305, USA.
Haifeng WangDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0003-4792-2005
Yaqiang CaoLaboratory of Epigenome Biology, Systems Biology Center, National Heart, Lung and Blood Institute NIH, Bethesda, MD 20892, USA.ORCID 0000-0002-4665-1517
Muneaki NakamuraDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0003-2441-5211
Jasprina N NoordermeerDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Marie La RussaDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-1758-313X
Wing Hung WongDepartment of Statistics, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0001-7466-2339
Keji ZhaoLaboratory of Epigenome Biology, Systems Biology Center, National Heart, Lung and Blood Institute NIH, Bethesda, MD 20892, USA.
Lei S QiDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-3965-3223

Funding

COG FOREIGN ACCRUALU10CA098543 · NCI · NATIONAL CHILDHOOD CANCER FOUNDATION · PI ADAMSON, PETER C. · 2003 to 2013
$335.5M
Viral Vector Technology (VVTSR)P30CA021765 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI CHARLES ROBERTS · 1985 to 2026
$166.9M
Support for Human Specimen Banking in NCI-Supported Cancer Clinical TrialsU24CA114766 · NCI · RESEARCH INST NATIONWIDE CHILDREN'S HOSP · PI RAMIREZ MILAN, NILSA DEL CARMEN · 2005 to 2014
$14.5M
PHARMACOGENOMICS OF CHILDHOOD LEUKEMIA (ALL)R37CA036401 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI EVANS, WILLIAM E · 1987 to 2014
$9.7M
PAARK4Kids-Pharmacogenomics of Anticancer Agents Research in ChildrenU01GM092666 · NIGMS · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI RELLING, MARY V · 2010 to 2014
$8.9M
Drug Resistant Pathways in Relapsed Acute Lymphoblastic Leukemia(ALL)R01CA140729 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI CARROLL, WILLIAM L. · 2010 to 2020
$4.8M
Glucocorticoids in Lymphoblastic LeukemiaR01CA142665 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI RELLING, MARY V · 2010 to 2020
$4.6M
Pharmacogenomics of Childhood Leukemia ALLR01CA036401 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI EVANS, WILLIAM E · 1985 to 2019
$3.6M
High resolution dissection of oncogene enhancer networks via CRISPR screening and live-cell imaging.R01CA266470 · NCI · STANFORD UNIVERSITY · PI Lei Stanley Qi · 2022 to 2026
$1.9M
Pharmacogenomics of Racial Disparities in Childhood Leukemia OutcomesRC4CA156449 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI RELLING, MARY V · 2010 to 2010
$1.7M
Statistical methods for gene regulatory analysis and single cell genomicsR01HG010359 · NHGRI · STANFORD UNIVERSITY · PI WONG, WING H. · 2019 to 2022
$1.5M
PDE4B and pharmacoethnicity of childhood leukemiaR21CA158568 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI YANG, JUN J. · 2011 to 2012
$422k
NCI NIH HHS P30 CA021765NCI NIH HHS R01 CA036401NCI NIH HHS R01 CA140729NCI NIH HHS R01 CA142665NCI NIH HHS R01 CA266470NCI NIH HHS R21 CA158568NCI NIH HHS R37 CA036401NCI NIH HHS RC4 CA156449NCI NIH HHS U10 CA098543NCI NIH HHS U24 CA114766NHGRI NIH HHS R01 HG010359NIGMS NIH HHS U01 GM092666Wellcome Trust
6 · The paper itself

Abstract

Mammalian genomes have multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, but it is unclear how these enhancers coordinate to achieve this task. We combine multiplexed CRISPRi screening with machine learning to define quantitative enhancer-enhancer interactions. We find that the ultralong distance enhancer network has a nested multilayer architecture that confers functional robustness of gene expression. Experimental characterization reveals that enhancer epistasis is maintained by three-dimensional chromosomal interactions and BRD4 condensation. Machine learning prediction of synergistic enhancers provides an effective strategy to identify noncoding variant pairs associated with pathogenic genes in diseases beyond genome-wide association studies analysis. Our work unveils nested epistasis enhancer networks, which can better explain enhancer functions within cells and in diseases.

Indexed as

DiseaseEnhancer Elements, GeneticEpistasis, GeneticMachine LearningBromodomain Containing ProteinsCell Cycle ProteinsGenome-Wide Association StudyHumansK562 CellsNuclear ProteinsTranscription FactorsBRD4 protein, humanBromodomain Containing ProteinsCell Cycle ProteinsNuclear ProteinsTranscription Factors

Identifiers

PMID35951677
PMCPMC10259245

What OpenQuestion holds

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Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.