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Updated: Feb 8, 2026
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Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq
Published on: November 13, 2017
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Accesibilidad ampliada de la cromatina mapeada explica la variación genética asociada con rasgos complejos en el
Brandon M Wenz1, Max F Dudek2, Shweta Ramdas3
1Genetics and Epigenetics Program, Cell and Molecular Biology Graduate Group, Biomedical Graduate Studies, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, USA.
American journal of human genetics
|February 6, 2026
Resumen
Este estudio utiliza ATAC-seq para mapear la accesibilidad de la cromatina en hígados humanos, identificando miles de elementos reguladores y caQTL. La integración de estos datos con datos de GWAS proporciona mecanismos moleculares para rasgos complejos, revelando que el 20% de las señales de lípidos en sangre carecen de un vínculo genético claro.
Área de la Ciencia:
- Genomics
- Molecular Biology
- Human Genetics
Sus antecedentes:
- Genome-wide association studies (GWAS) identify genetic loci for complex traits.
- Chromatin accessibility studies aim to find regulatory elements influencing gene expression.
- Genetic variants affecting chromatin accessibility (caQTLs) can explain GWAS signals.
Objetivo del estudio:
- To investigate chromatin accessibility in human liver using ATAC-seq.
- To identify caQTLs and their colocalization with GWAS signals for liver-relevant traits.
- To assess the proportion of complex trait signals with proposed molecular mechanisms.
Principales métodos:
- Assay for transposase-accessible chromatin with sequencing (ATAC-seq) on 189 human liver samples.
- Identification of accessible chromatin regions and caQTLs.
- Integration of liver caQTLs, eQTLs, and blood lipid GWAS data.
Principales resultados:
- Over 2 million accessible chromatin regions and over 14,000 caQTLs identified.
- 157 loci showed colocalization between caQTLs, eQTLs, and GWAS signals.
- Approximately 20% of blood lipid GWAS signals lacked a statistically supported mechanism.
Conclusiones:
- Integrating multi-omic QTL data enhances understanding of GWAS signals.
- caQTLs provide mechanistic hypotheses for complex trait associations.
- Further experimental approaches are needed to fully elucidate complex trait mechanisms.
Palabras clave:
colesterolaccesibilidad de la cromatinacolocalizaciónarquitectura genéticahígadomapeo de locus de rasgos cuantitativosMás Videos Relacionados
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