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Published January 2022 | Supplemental Material
Journal Article Open

SPRITE: a genome-wide method for mapping higher-order 3D interactions in the nucleus using combinatorial split-and-pool barcoding

Abstract

A fundamental question in gene regulation is how cell-type-specific gene expression is influenced by the packaging of DNA within the nucleus of each cell. We recently developed Split-Pool Recognition of Interactions by Tag Extension (SPRITE), which enables mapping of higher-order interactions within the nucleus. SPRITE works by cross-linking interacting DNA, RNA and protein molecules and then mapping DNA–DNA spatial arrangements through an iterative split-and-pool barcoding method. All DNA molecules within a cross-linked complex are barcoded by repeatedly splitting complexes across a 96-well plate, ligating molecules with a unique tag sequence, and pooling all complexes into a single well before repeating the tagging. Because all molecules in a cross-linked complex are covalently attached, they will sort together throughout each round of split-and-pool and will obtain the same series of SPRITE tags, which we refer to as a barcode. The DNA fragments and their associated barcodes are sequenced, and all reads sharing identical barcodes are matched to reconstruct interactions. SPRITE accurately maps pairwise DNA interactions within the nucleus and measures higher-order spatial contacts occurring among up to thousands of simultaneously interacting molecules. Here, we provide a detailed protocol for the experimental steps of SPRITE, including a video (https://youtu.be/6SdWkBxQGlg). Furthermore, we provide an automated computational pipeline available on GitHub that allows experimenters to seamlessly generate SPRITE interaction matrices starting with raw fastq files. The protocol takes ~5 d from cell cross-linking to high-throughput sequencing for the experimental steps and 1 d for data processing.

Additional Information

© 2022 Nature Publishing Group. Received 09 December 2019; Accepted 13 September 2021; Published 10 January 2022. We thank all members of the Guttman Laboratory for input on the SPRITE protocol; M. Blanco, I. Goronzy and P. Vangala for helpful comments; B. Tabak for insights on cluster size analysis and weighting; C. Lai and P. Russell for initial support with the SPRITE pipeline; I.-M. Strazhnik and S. Knemeyer for illustrations; and G. Napolitan-Witz for producing and editing the SPRITE video. S.Q. is supported by the HHMI Gilliam Fellowship and NSF GRFP Fellowship. P.B. is supported by the UCLA-Caltech MSTP, NIH F30CA247447, the Josephine de Kármán Fellowship Trust and a Caltech Chen Graduate Innovator Grant. N.O. is supported by the American Cancer Society Postdoctoral Fellowship grant number PF-17-240-01. This work was funded by the NIH 4DN (U01 DA040612 and U01 HL130007), the NYSCF, NIH Director's Early Independence Award (DP5OD012190), CZI Ben Barres Early Career Acceleration Award, Sontag Foundation, Searle Scholars Program, Pew-Steward Scholars program, and funds from Caltech. M.G. is a NYSCF-Robertson Investigator. Data availability: Example DNA SPRITE datasets have been deposited on the 4DN Data Portal24 under accession numbers 4DNFI8ZROQ87 and 4DNFIY9HL35V. Code availability: The DNA SPRITE software is available for download on the Guttman Laboratory github page at https://github.com/GuttmanLab/sprite-pipeline/. Version v0.2 is explained in detail within this paper. Author Contributions: S.A.Q. and M.G. conceptualized the experimental method; S.A.Q., P.B., J.J., E.S. and E.D. developed the experimental method and generated data; P.C., N.O. and M.G. developed the computational method and data analysis tools; S.A.Q, P.B., P.C. and M.G. wrote the manuscript. Competing interests: S.A.Q. and M.G. are inventors of a patent on the SPRITE method. Peer review information: Nature Protocols thanks Xiaohua Shen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Additional details

Created:
August 22, 2023
Modified:
December 22, 2023