Single-cell measurement of higher-order 3D genome organization with scSPRITE

Single-cell measurement of higher-order 3D genome organization with scSPRITE

Abstract

Although three-dimensional (3D) genome company is main to lots of elements of nuclear function, it has actually been challenging to determine at the single-cell level. To resolve this, we established ‘single-cell split-pool acknowledgment of interactions by tag extension’ (scSPRITE). scSPRITE utilizes split-and-pool barcoding to tag DNA pieces in the exact same nucleus and their 3D spatial plan. Due to the fact that scSPRITE steps multiway DNA contacts, it produces higher-resolution maps within a private cell than can be accomplished by distance ligation. We used scSPRITE to countless mouse embryonic stem cells and found recognized genome structures, consisting of chromosome areas, active and non-active compartments, and topologically associating domains (TADs) in addition to long-range inter-chromosomal structures arranged around different nuclear bodies. We observe that these structures show various levels of heterogeneity throughout the population, with TADs representing vibrant systems of genome company throughout cells. We anticipate that scSPRITE will be a vital tool for studying genome structure within heterogeneous populations.

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Data accessibility

The datasets (Figs. 1 5 and Extended Data Figs. 1 − 5) produced and examined in the present research study are offered in the Gene Expression Omnibus repository under accession number GSE154353( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE154353).

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Acknowledgements

We want to thank F. Gao from Caltech’s Bioinformatics Resource Center and I. Antoshechkin from Caltech’s Millard and Muriel Jacobs Genetics and Genomics Laboratory for support. We would likewise like to thank C. Chen, V. Trinh, E. Detmar, E. Soehalim, A. Narayanan and I. Goronzy for their contributions in assisting establish scSPRITE and analysis. We wish to thank M. Thompson’s lab for permitting us to utilize their MiSeq instrument and the ENCODE Consortium and the ENCODE production lab of B. Ren (University of California, San Diego) for making their information openly offered. We likewise thank N. Shelby and S. Hiley for contributions to the writing and modifying this manuscript and I.-M. Strazhnik for aiding with illustrations. Financing: This work was moneyed by the National Institutes of Health 4DN Program (U01 DA040612 and U01 HL130007), the National Human Genome Research Institute Genomics of Gene Regulation Program (U01 HG007910), the New York Stem Cell Foundation (NYSCF-R-I13), the Sontag Foundation and funds from Caltech. M.V.A. and S.A.Q. were moneyed by a National Science Foundation Graduate Research Fellowship Program fellowship. M.V.A. was furthermore moneyed by the Earle C. Anthony Fellowship (Caltech). M. Guttman is an NYSCF-Robertson Investigator.

Author details

Author notes

  1. These authors contributed similarly: Mary V. Arrastia, Joanna W. Jachowicz.

Affiliations

  1. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA

    Mary V. Arrastia, Matthew S. Curtis, David A. Selck & Rustem F. Ismagilov

  2. Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA

    Joanna W. Jachowicz, Noah Ollikainen, Charlotte Lai, Sofia A. Quinodoz, Rustem F. Ismagilov & Mitchell Guttman

Contributions

M.V.A. performed the experiments to establish and verify the approach, conceived and carried out the analyses and composed the manuscript. J.W.J. added to and monitored the experiments to establish and verify the technique, conceived and carried out the analyses and composed the manuscript. N.O. conceived and carried out analysis to confirm the technique, established the pipeline for the workup of scSPRITE sequencing information and added to composing the manuscript. M.S.C. added to the experiments to establish the technique. C.A.L. established a pipeline to sort cells by cell-specific barcodes. S.A.Q. added to the experiments to establish and verify the approach. D.A.S. added to conceive scSPRITE and to the experiments to establish the approach. R.F.I. conceived scSPRITE and monitored the experiments and the analysis to establish the technique. M.G. conceived scSPRITE, monitored the experiments and the analysis to confirm the technique and composed the manuscript. For comprehensive author contributions, please see Supplementary Note 5

Corresponding authors

Correspondence to.
Rustem F. Ismagilov or Mitchell Guttman

Ethics statements

Competing interests

This paper is the topic of a patent application submitted by Caltech. R.F.I. has a monetary interest in Talis Biomedical Corp. S.A.Q. and M.G. are innovators on a patent owned by Caltech on SPRITE. The staying authors state no contending monetary interests.

Additional details

Peer evaluation details Nature Biotechnology thanks Andrew Adey and the other, confidential, customer( s) for their contribution to the peer evaluation of this work.

Publisher’s note Springer Nature stays neutral with regard to jurisdictional claims in released maps and institutional associations.

Extended information

Extended Data Fig. 1 scSPRITE create single cell maps with high genomic protection.

a Metrology of cell aggregation. Leading: variety of cells in clumps pre- and post-filtration (singlets, doublets, triplets, and so on). Bottom: microscopic lense images (10 x) of cells pre- and post-filtration action, scale bar 100 µm. b Recognition of In-nuclei barcoding action of the procedure on blended cell population (human-mouse cells): no blending (leading middle and leading right), blending prior to crosslinking (bottom left), blending after crosslinking (bottom middle), and blending after in-nuclei constraint absorb (bottom right). c Schematic of the computational analysis pipeline for processing scSPRITE information. d Theoretical variety of contacts determined by SPRITE-derived approaches and Hi-C-derived techniques over increasing varieties of DNA particles per complex. e Optimum variety of pairwise interactions that can be acquired from distance ligation (Hi-C-derived techniques) and intricate barcoding (SPRITE-derived techniques). f Genome-wide protection for the filtered 1,00 0 cells: the typical (black triangular points) and average outright variance (MAD) (green circular points) worths were computed per cell utilizing the variety of checks out per 1 Mb bin genome-wide (chr1-19). g Genomic protection of 20 random cell barcodes; 1 Mb bin per chromosome.

Extended Data Fig. 2 Known chromosomal structures can be determined genome-wide in numerous single mESCs by scSPRITE.

a Extra single cell examples of chromosome area structure in between chr1 and chr2; outlined as variety of DNA clusters at 1 Mb resolution. Box plot represents stabilized detection ratings in between chr1 and chr2, where hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the mean, red dots represent single cell examples (n = 1000 cells). b Chromosome area ratings throughout 1000 cells (clustered based upon resemblance pattern). Columns represent chromosome area detection ratings for all sets of chromosomes with the referral chromosome. Arrows represent chromosome area ratings in between chr1 and chr2, which were evaluated in this paper. c Metrology of chromosome area ratings with regard to each chromosome. Boxplots reveal the variety of chromosome area ratings, the typical rating (black line), and private sets of chromosome area ratings (grey dots). d Box plot represents average chromosome area detection ratings from all genome-wide (chr1-19) chromosome pairs., where hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the typical, red dots represent single cell examples (n = 1000 cells) (left). Extra single cell examples of genome-wide (chr1-19) chromosome areas (right). e Extra single cell examples of A/B compartments found within 0-55 Mb in chr2; outlined variety of DNA clusters at 1 Mb resolution (right). Box plot represents stabilized detection ratings in between 0-55 Mb in chr2, where hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the typical, red dots represent single cell examples (n = 1000 cells). f Representation of compartment changing ratings throughout 1,00 0 cells (clustered based upon rating resemblance pattern). Columns represent the strength of compartment changing detection ratings for compartments that changed from “B-to-A-to-B” or “A-to-B-to-A” genome-wide (chr1-19). Arrows represent compartment changing ratings for chr2 1-55 Mb, chr8 22-37 Mb, chr1058-70 Mb, and chr17 8-45 Mb, all of which were evaluated in this paper. g Extra single cell examples of compartment changing from Region 1, Region 2, and Region 3 (right). For each area’s box plot: hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the mean, red dots represent single cell examples (n = 1000 cells). h Anticipated (right) and observed (left) protection of checks out in the A and B compartment.

Extended Data Fig. 3 Higher-order structures are recognized genome-wide in numerous single mESC by scSPRITE approach.

a Extra single cell examples of nucleolar interactions found in between chr18 and chr19; outlined variety of DNA clusters at 1 Mb resolution; detection ratings listed below contact map (right). Box plot represents stabilized detection ratings in between chr18 and chr19, where hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the typical, red dots represent single cell examples (n = 1000 cells). b Nucleolar interaction in between chr12 and chr19: detection ratings for 1000 cells (middle). Box plot where hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the typical, red dots represent single cell examples (n = 1000 cells). Representation of structures with max rating ( 1) and minutes. rating (-1) (left) and ensemble scSPRITE heatmap (middle); contact map at 1 Mb resolution. Single cell examples (right); outlined variety of DNA clusters at 1 Mb resolution. c Relative connection of the percent of cells from scSPRITE vs DNA-FISH consisting of inter-chromosomal interactions at defined 1 Mb areas targeted by DNA-FISH probes. Control chromosomes (grey points) and nucleolar associating chromosomes (black dots) are outlined. d Relative connection of the contact frequency from scSPRITE vs the contact frequency from SPRITE consisting of inter-chromosomal interactions targeted by DNA-FISH probes. Control chromosomes (grey points) and nucleolar associating chromosomes (black dots) are outlined. e Frequency of cells consisting of inter-chromosomal nucleolar contacts (stabilized to variety of checks out per area) for each set of nucleolar associating chromosomes. f Single cell examples of speckle interaction discovered in between chr2 and chr5; outlined variety of DNA clusters at 1 Mb resolution. Box plot represents stabilized detection ratings in between chr2 and chr5, where hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the typical, red dots represent single cell examples (n = 1000 cells). g Extra single cell examples of speckle interactions discovered in between chr2 and chr4; outlined variety of DNA clusters at 1 Mb resolution. Box plot represents stabilized detection ratings in between chr2 and chr4, where hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the mean, red dots represent single cell examples (n = 1000 cells). h Frequency of cells consisting of inter-chromosomal speckle contacts (stabilized to variety of checks out per area) for each set of speckle associating chromosomes. i Extra single cell examples of centromere-proximal interactions spotted in between chr1 and chr11; outlined variety of DNA clusters at 1 Mb resolution. Box plot represents stabilized detection ratings in between chr1 and chr11, where hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the average, red dots represent single cell examples (n = 1000 cells). j Single cell examples of chr4 and chr11 centromere-proximal areas engaging together; outlined variety of DNA clusters at 1 Mb resolution. Box plot represents stabilized detection ratings in between chr4 and chr11, where hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the average, red dots represent single cell examples (n = 1000 cells). k Frequency of cells consisting of inter-chromosomal centromeric contacts (stabilized to variety of checks out per area) for each set of chromosomes. l Higher-order structures representation from scHi-C information16— centromere-proximal interactions, speckle interactions, and nucleolar interactions; Pairwise contact map from ensemble 1,00 0 cells (left), pairwise contact map from their finest single cell (right).

Extended Data Fig. 4 TADs are heterogeneous systems present in the genomes of private mESCs.

a Genome-wide connection of insulation ratings in between ensemble scSPRITE and Hi-C 3 from mouse ES cells at 40 kb resolution. b Insulation rating profile of ensemble scSPRITE (red) and Hi-C 3(blue) at 40 kb resolution at chr1 65-95 Mb. c Extra single cell examples of TAD-like structures in between 124.8-1267 Mb of chr4; outlined variety of DNA clusters at 40 kb resolution; detection ratings listed below contact map. Box plot represents stabilized detection ratings in between 124.8-1267 Mb of chr4, where hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the mean, red dots represent single cell examples (n = 1000 cells). d Little detection ratings throughout 1,00 0 cells (clustered based upon rating resemblance pattern) in chr2 (left) and chr18(right). Columns represent the strength of TAD detection ratings for all TADs spotted throughout chr2 or chr18, respectively, in ensemble scSPRITE. e Little detection ratings throughout 1,00 0 cells in between 38.5-4856 Mb of chr4. Each line represents the strength of TAD detection ratings in this offered area from a single cell. Cells are either in Group 1 or 2 in Fig. 4f or not utilized. f Ensemble heatmap from all 1000 cells in between 39.4-414 Mb of chr4 representing strong TADs spotted wholesale (blue lines), and weak emerging TADs (green line) over the A/B limit. g Portion of cells in each cell cycle stage from the set of single cells including (left) or doing not have (right) the contact in between the border area (Fig. 4f). h Distinction contact map throughout a control area 84.8-884 Mb of chr4 made by deducting the stabilized contacts from cells in Group II from Group I (Fig. 4f). Insulation ratings for cells in Group I (dark grey) and Group II (light grey) are outlined.

Extended Data Fig. 5 Structural heterogeneity in long-range interactions is exposed by scSPRITE.

a Ensemble heatmaps throughout 122.2-1228 Mb area in chr6 representing cells including (top) or doing not have (bottom) the contact in between the Nanog locus and the -300 Kb SE. Blue square reveals the contact. b Variety of genome-wide checks out (left) and variety of genome-wide contacts (right) for groups of cells with and without the Nanog– SE interaction. For each box plot, hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the typical (with = 159 cells, without = 149 cells). No analytical significance in between the 2 groups were seen based upon the Kolmogorov– Smirnov two-sided test. c Portion of cells in each cell cycle stage from the set of single cells including (left) or doing not have (right) the contact in between the Nanog locus and the SE 300 kb upstream of Nanog d Heatmaps in between 119.24-12128 Mb in chr5 of pooled cells either consisting of (top) or doing not have (bottom) the contact in between the Tbx3 locus and Lhx5 Blue square reveals the contact. e Variety of genome-wide checks out (left) and variety of genome-wide contacts (right) for groups of cells with and without the Tbx3-Lhx5 interaction. For each box plot, hairs represent the 10 th and 90 th percentiles, box limitations represent the 25 th and 75 th percentiles, black line represents the average (with = 152 cells, without = 149 cells). No analytical significance in between the 2 groups were seen based upon the Kolmogorov– Smirnov two-sided test. f Portion of cells in each cell cycle stage from the set of single cells including (left) or doing not have (right) the contact in between the Tbx3 locus and the Lhx5

Supplementary info

Supplementary Tables

Table 1: Metrics for each set of chromosome area stabilized detection ratings. Table 2: Metrics for each area of A/B compartment stabilized detection ratings. Table 3: Metrics for each TAD stabilized detection rating.

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Arrastia, M.V., Jachowicz, J.W., Ollikainen, N. et al. Single-cell measurement of higher-order 3D genome company with scSPRITE.
Nat Biotechnol(2021). https://doi.org/101038/ s41587-021-00998 -1

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