Cicero predicts cis-regulatory DNA interactions from single cell chromatin accessibility data

By Hannah A. Pliner, Jonathan S. Packer, J. McFaline-Figueroa, D. Cusanovich, R. Daza, Delasa Aghamirzaie, S. Srivatsan, Xiaojie Qiu, Dana L. Jackson, A. Minkina and 4 more. Molecules and Cells, 2018

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Summary Linking regulatory DNA elements to their target genes, which may be located hundreds of kilobases away, remains challenging. Here we introduce Cicero, an algorithm that identifies coaccessible pairs of DNA elements using single-cell chromatin accessibility data, and so connects regulatory elements to their putative target genes. We apply Cicero to investigate how dynamically accessible elements orchestrate gene regulation in differentiating myoblasts. Groups of Cicero-linked regulatory elements meet criteria of "chromatin hubs" — they are enriched for physical proximity, interact with a common set of transcription factors, and undergo coordinated changes in histone marks that are predictive of changes in gene expression. Pseudotemporal analysis revealed that most DNA elements remain in chromatin hubs throughout differentiation. A subset of elements bound by MYOD in myoblasts exhibit early opening in a PBX1- and MEIS1-dependent manner. This strategy can be applied to dissect the architecture, sequence determinants, and mechanisms of cis-regulation on a genome-wide scale.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ec764e5b62efa4f4d0266a41346978bcdf8a1d2e

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In Molecular Biology

Citations in the corpus

Benchmarking atlas-level data integration in single-cell genomics (2020, background): “While alternative choices of gene activity scoring may improve this feature space 33,34 , our results indicate that peaks or windows are better suited to integrate and analyze scATAC-seq data.”
Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion (2019, neutral): “f g NK cells (18-20) B cells (14-16) CD4+ T cells (21-25) Basophils (17)”
A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility. (2018, methodology): “Cicero assigns a regularized co-accessibility score to each pair of ‘‘open’’ sites in each cluster using Graphical Lasso model, penalized by genomic distance (Pliner et al., 2018).”
Multi-omics single-cell data integration and regulatory inference with graph-linked embedding (2022, methodology): “4b), as well as LASSO and Cicero 43 , the coaccessibility-based regulatory prediction method (Fig.”