Humans are part of a group of animals called vertebrates, which are all the animals with backbones. Broadly, all vertebrates have a similar body shape with a head at one end and a left and right side that are similar to each other. Although this is not very obvious in humans, vertebrate bodies are derived from pairs of segments arranged from the head to the tail. Each of these segments or somites originates early in embryonic development. Cells from each somite then divide, grow and specialize to form bones such as the vertebrae of the vertebral column, muscles, skin, and other tissues that make up each segment.

Studying different animals during embryonic development has provided insights into how somites form and grow, but it is technically difficult to do and only provides an approximate model of how somites develop in humans. Being able to make and study somites using human cells in the lab would help scientists learn more about how somite formation in humans is regulated.

Budjan et al. grew human stem cells in the lab as three-dimensional structures called organoids, and used chemical signals similar to the ones produced in the embryo during development to make the cells form somites. Various combinations of signals were tested to find the best way to trigger somite formation. Once the somites formed, Budjan et al. measured them and studied their structure and the genes they used. They found that these lab-grown somites have the same size and structure as natural somites and use many of the same genes.

This new organoid model provides a way to study human somite formation and development in the lab for the first time. This can provide insights into the development and evolution of humans and other animals that could then help scientists understand diseases such as the development of abnormal spinal curvature that affects around 1 in 10,000 newborns.

Paraxial mesoderm (PM) development involves the formation of embryonic segments called somites, which are produced sequentially from the presomitic mesoderm (PSM) and arranged periodically along the anterior-posterior (AP) axis of the vertebrate embryo. Somites give rise and contribute to a variety of tissues including skeletal muscle, dermis, cartilage, and bone (Chal and Pourquié, 2017). Somite formation is controlled by a conserved molecular oscillator, the segmentation clock (Dequéant et al., 2006; Hubaud and Pourquié, 2014; Oates et al., 2012). Previous efforts have focused on how this oscillator controls somite formation using a variety of model systems such as mouse, zebrafish, and chick because of ethical and technical limitations of culturing human embryos. Recently, researchers were able to recapitulate PM development using human and mouse pluripotent stem cells cultured as 2D monolayers (Chu et al., 2019; Diaz-Cuadros et al., 2020; Matsuda et al., 2020). These cells undergo species-characteristic oscillations similar to their in vivo counterparts. However, final stages of somite development and vertebra formation were not observed in currently published human cell culture systems (Palla and Blau, 2020), suggesting that certain aspects of in vivo development are not recapitulated in these 2D systems. We reasoned that a 3D cell culture system may exhibit all the stages of PM development including morphogenetic processes associated with somite formation.

Here, we describe an organoid system derived from human induced pluripotent stem cells (hiPSCs) called Somitoids, which faithfully recapitulates functional, morphological, and molecular features of PM development, including formation of somite-like structures in vitro. To identify the culture conditions that reproducibly yielded formation of somite-like structures, we developed a quantitative image-based screening platform for individual organoids. Our screening approach identified the optimal parameter values for the culture conditions such as the initial cell number and the concentration of the chemical modulators. We show using single-cell RNA-sequencing (scRNA-seq), immunofluorescence, and qRT-PCR that Somitoids resemble their in vivo counterparts both transcriptionally and morphologically and can be differentiated into somite derivatives such as sclerotome and dermomyotome in vitro.

Our Somitoid system is reproducible and scalable, allowing for systematic and quantitative analysis of PM development and somite formation to study human spine development and disease in a dish. Finally, our approach can be used to systematically screen organoid cultures for desired phenotypes and reproducibility.

Recently, protocols have been developed to differentiate mouse or human pluripotent stem cells (hPSCs) towards PM using a combination of the WNT agonist CHIR and BMP inhibitor LDN (Chal et al., 2015; Diaz-Cuadros et al., 2020). To adapt the protocol for a 3D model of human somitogenesis, we first optimized the initial conditions of our cultures by generating pluripotent spheroids of defined cell numbers. hiPSCs were allowed to aggregate for 24 hr as suspension cultures in pluripotency media (mTeSR1) in the presence of ROCK inhibitor and polyvinyl alcohol (PVA) to promote aggregation (Figure 1A). These pluripotent spheroids resemble cavity-stage epiblast embryos as previously described for kidney organoid cultures (Freedman et al., 2015; Figure 1B, Figure 1—figure supplement 1A). Next, spheroids were cultured in media containing CHIR and LDN (CL), similarly as done for the monolayer cultures (Chal et al., 2015; Diaz-Cuadros et al., 2020), but with CHIR at a higher concentration (10 µM). After 24 hr in CL media, epiblast-stage cells transition to a neuromesodermal progenitor (NMp) or primitive streak cell fate, characterized by co-expression of T/BRA and SOX2 (Tzouanacou et al., 2009; Figure 1B). By 48 hr, cells rapidly downregulate SOX2 and express PSM markers, including TBX6 and MSGN1 (Figure 1B). This PSM state persists from day 2 to day 4 and is also characterized by the expression of segmentation clock genes such as HES7 (Figure 1C). On day 5, organoids showed expression of marker genes associated with somite fate as characterized by qPCR (Figure 1C, Figure 1—figure supplement 1B). Taken together, the order of activation of marker genes in the PM organoids followed the expected stages of differentiation observed during PM development.

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qPCR raw data of paraxial mesoderm (PM) organoid differentiation.

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We observed that following the above protocol resulted in a heterogeneous activation of somite marker genes across cells within the same organoid and across different replicates, as well as a low number of somite-like structures (Figure 1—figure supplement 2). To improve reproducibility, we set out to screen for the optimal initial cell number, the concentration of the signaling factors, and the timing of their additions during culture. For our primary screen, we compared organoids with an initial cell number of 500 and 1000 as well as combinations of modulators of candidate signaling pathways that have previously been involved in PM development and somite formation, including FGF, WNT, BMP, and TGF-β (Aulehla et al., 2008; Chal et al., 2015; Hubaud and Pourquié, 2014; Tonegawa et al., 1997; Xi et al., 2017). We primarily focused on the FGF and WNT signaling pathways since their critical role during somitogenesis is well established both in vivo (Aulehla et al., 2008; Aulehla et al., 2003; Delfini et al., 2005; Dubrulle et al., 2001; Dunty et al., 2008; Greco et al., 1996; Yamaguchi et al., 1999) and in vitro (Chal et al., 2015; Sakurai et al., 2012; Tan et al., 2013). Furthermore, dual inhibition of FGF and WNT signaling has been used with some success to generate PM derivatives in vitro (Loh et al., 2016; Matsuda et al., 2020). Finally, the BMP and TGF-β signaling pathways have been shown in vitro and in vivo to have a role in human somitogenesis (Loh et al., 2016; Xi et al., 2017).

PSM-stage organoids on day 3 were treated with signaling modulators for 24 and 48 hr, and somite fate and morphogenesis was assessed using PAX3, a somite fate marker, and F-ACTIN, a structural marker of somite formation (Figure 2A). We chose day 3 as a starting point for our systematic screen because PSM marker gene expression was more uniform compared to day 2 organoids (Figure 1B), and day 4 organoids are not significantly different from day 3 organoids based on a previous study and our own immunostaining and qPCR data (Figure 1B and C; Diaz-Cuadros et al., 2020). To quantitatively compare conditions, we developed an image analysis pipeline to determine organoid diameter and normalized average PAX3 expression intensity per organoid in an automated manner (Figure 2C and D, Figure 2—figure supplement 2B). We analyzed three organoids per condition. Strikingly, all organoids that were treated with any combination of FGF or WNT inhibitor reproducibly expressed PAX3 within 24 hr of treatment (Figure 2B and D). However, organoids that were initiated from 1000 cells displayed a higher fraction of PAX3-negative cells compared with organoids initiated from 500 cells, even though the average PAX3 expression levels across the entire organoid were comparable (Figure 2D, Figure 2—figure supplement 2A). Additional staining for SOX2, a neural marker, showed that PAX3-negative cells expressed SOX2, suggesting that our PM organoids derive from NMps (Figure 1B, Figure 2—figure supplement 2A). In addition, staining for F-ACTIN, together with nuclear expression of PAX3, more consistently revealed somite-like structures (radial arrangement of PAX3+ columnar cells with expression of apical F-ACTIN in the central cavity) in organoids made from 500 cells compared with organoids made from 1000 cells (Figure 2B, Figure 2—figure supplement 3A and B). Taken together, based on these observations, we used 500 cells as the initial cell number going forward.

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Quantification of organoid diameter from primary screen.

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Quantification of average PAX3 levels per organoid from primary screen.

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Organoids that were treated for 48 hr with signaling pathway modulators showed an overall decrease of PAX3 expression compared with organoids treated for only 24 hr across replicates, indicating that prolonged signaling manipulation does not improve the somite phenotype (Figure 2D). Additionally, organoids initiated from 500 cells and then treated for 48 hr had a smaller diameter compared with organoids of the same initial cell number that were treated for only 24 hr (Figure 2C). This suggests that long-term inhibition of WNT and/or FGF, known mitogenic signaling pathways, has detrimental effects on proliferation or cell survival. These results indicate that treatment of PSM-stage organoids with pathway modulators for 24 hr is sufficient to induce somite fate.

Next, we set out to optimize the culture conditions to increase the number of somite-like structures in addition to the expression levels of the somite marker genes. We looked for morphological hallmarks of somite formation, specifically the formation of rosette-like structures consisting of radially arranged bottle-shaped PAX3+ epithelial cells with their NCAD+ apical surface facing a central cavity (Figure 3—figure supplement 1A and B, Figure 3—video 1).

We used 500-cell spheroids as an initial starting point and compared two different inhibitor doses for FGF and WNT in addition to the other pathway modulators applied to PSM-stage organoids on day 3. We characterized the organoids after treating them for 24 hr, 48 hr, and 24 hr followed by culture in basal media without any added factor for an additional 24 hr (five organoids per condition, Figure 3A). In addition to quantifying PAX3 levels (Figure 3D, Figure 3—figure supplement 2B), we also counted the number of somite-like structures per organoid (Figure 3B and E, Figure 3—figure supplement 2A and B; see Materials and methods for a description of the scoring criteria). Comparing PAX3 expression levels in our treated organoids, we observed that somite fate can be broadly induced across a range of treatment regimes, concentrations, and types of WNT and/or FGF inhibitors (Figure 3C and D, Figure 3—figure supplement 2C). However, the number of somite-like structures is not necessarily correlated with average PAX3 expression levels. For example, the numbers of somite-like structures in several conditions (FGFRi^hi/PD173, WNTi^hi/C59, WNT^hi/C59+ FGFRi^lo, WNTi^hi/XAV) were lower in organoids treated for 24 hr followed by culture in basal media for 24 hr compared with organoids that were treated with the same inhibitors for 48 hr, even though they exhibited higher PAX3 expression levels on average (Figure 3D and E, Figure 3—figure supplement 2A). This suggests that marker gene expression alone may not be the best predictor when screening for morphologically complex phenotypes such as somite formation.

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Quantification of average PAX3 levels per organoid from secondary screen.

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Quantification of somite-like structures of secondary screen.

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Surprisingly, organoids that were cultured for an additional 24 hr (day 3 to day 4) in FGF, WNT pathway agonist, and BMP inhibitor, considered a treatment control, followed by culture in basal media only for another 24 hr, consistently exhibited the highest number of somite-like structures across all organoid replicates (Figure 3E, Figure 3—figure supplement 1A and B, Figure 3—figure supplement 2A and B, Figure 3—video 1) as well as technical replicates (Figure 3—figure supplement 3A). Additionally, the average PAX3 expression was among the highest of all conditions tested (Figure 3D). This suggests that simply removing FGF/WNT pathway agonists and BMP inhibitor, which maintain cells in a PSM state, is sufficient to reproducibly induce somite fate and morphological formation of somite-like structures (Figure 3—figure supplement 2A, Figure 3—figure supplement 3A). Computing the variation of the number of somite-like structures across the five organoids confirmed that this phenotype was highly reproducible (coefficient of variation = 11.1%; Figure 3—figure supplement 2B). Finally, our optimized protocol reproducibly yielded efficient induction of somite-like structures in multiple genetically independent hiPSC lines (Figure 3—figure supplement 3B). Taken together, we determined that initiating the protocol with 500 cells and treating day 3 organoids with CL + FGF for 24 hr followed by culture in basal media for an additional 24 hr yield the most robust induction of somite-like structures while minimizing variation between experiments (technical variation) and different cell lines (biological variation). This optimized differentiation protocol was therefore used for all subsequent experiments.

To further characterize the developmental trajectory and transcriptional states of our Somitoid system, we collected 15,558 cells (after postprocessing) over the course of the optimized 5-day differentiation protocol at timepoints that capture the key transition steps (day 1, day 2, day 3, day 5) and performed scRNA-seq (Figure 4A). Multiple organoids were used to obtain the required number of cells at each timepoint (see Materials and methods). We first combined all the cells across the timepoints and clustered them using the Leiden clustering algorithm (Traag et al., 2019). Predominantly, the four major clusters corresponded to cells from the four different timepoints. Therefore, cells at each timepoint have transcriptional states that are different compared with cells from the other timepoints. In addition, within each timepoint, cells exhibit similar transcriptional profiles as indicated by the uniformity of the expression levels of marker genes across individual cells (Figure 4E, Figure 4—figure supplements 1–3).

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Cells collected on day 1 exhibited gene expression profiles similar to primitive streak or NMps, expressing genes such as SOX2, T/BRA, MIXL1, and NODAL (Figure 4C and E, Figure 4—figure supplement 1). Starting on day 2, cells expressed canonical PSM marker genes such as TBX6, MSGN1, WNT3A, RSPO3, and clock genes of the Notch signaling pathway including HES7, LFNG, DLL1, and DLL3 (Figure 4C and E, Figure 4—figure supplement 2). Day 5 cells expressed somite marker genes such as TCF15, PAX3, FOXC2, and MEOX2 (Figure 4C and E, Figure 4—figure supplement 3). Interestingly, a subset of the day 5 cells also expressed somite polarity markers, UNCX and TBX18, which suggests faithful recapitulation of somite patterning in Somitoids (Figure 4C, Figure 4—figure supplement 3). Furthermore, two of the subclusters (‘PSM-to-somite,’ ‘early somite’), which are characterized by co-expression of PSM and somite marker genes, comprised both day 3 and day 5 cells, indicating that the PSM-to-somite transition is captured in our in vitro system (Figure 4A and B). Interestingly, one somite subcluster (‘late somite’) was enriched for myogenic genes (MYL4/6/7/9, TROPONIN L1) and sclerotome genes (TWIST1, COL1A1, COL11A1, COL7A1, ACTA2), suggesting that these cells represent more downstream fates of somite-derived cells (Figure 4B, Figure 4—figure supplement 4A). Finally, we observed the expected sequential activation pattern of the HOX genes in our Somitoid system starting with HOXA1 on day 1, followed by other cervical and thoracic HOX genes on days 2–3, to HOXD9, a lumbosacral HOX gene, in the somite-stage organoids (day 5; Figure 4D, Figure 4—figure supplement 4B). Taken together, our scRNA-seq analyses show that our Somitoid system faithfully recapitulates the gene regulatory programs of human PM development and generates mature somite-like cells, which express the full repertoire of known marker genes. Furthermore, we did not detect cells of different developmental origins, suggesting that we are generating homogeneous organoids containing only PM derivatives.

We next assessed whether our in vitro-derived somite-like structures show similar spatial organization and size distribution to their in vivo counterparts. To independently confirm some of the somite marker genes that we identified in our scRNA-seq dataset, we measured expression levels of TCF15/PARAXIS, PAX3, and F-ACTIN in day 5 Somitoids using whole-mount immunostaining (Figure 5A). Day 5 cells co-expressed both somite marker genes TCF15 and PAX3 throughout the Somitoid, and somite-like structures displayed apical localization of F-ACTIN. To determine whether in vitro-derived somite-like structures were similar in size to human embryonic segments, we compared them with Carnegie stage 9–11 early human somites (Figure 5B; see Materials and methods for a description of how somite sizes were quantified). Organoid-derived somite-like structures were similar in size (median area = 8892 µm², interquartile range [IQR] = 7698–10682 µm²) to Carnegie stage 11 somites (median area = 9681 µm², IQR = 8262–11493 µm²) but larger than earlier-stage human somites (Carnegie stage 9 somites, median area = 4399 µm², IQR = 4089–4433 µm²; Carnegie stage 10 somites, median area = 4704 µm², IQR = 4477–5343 µm²; see Figure 5B). Together, these results suggest that our organoid-derived somite-like structures share spatial and molecular features as well as overall size with their in vivo counterparts.

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Comparative somite size quantification of in vitro somite-like structures and human somites from the Carnegie collection.

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qPCR raw data of sclerotome differentiation.

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Finally, we assessed whether Somitoids can give rise to downstream PM derivatives of sclerotome and dermomyotome. First, we differentiated Somitoids to sclerotome by exposing day 5 organoids to SHH agonist and WNT inhibitor to mimic the signaling environment of ventral somites in vivo (Fan et al., 1995; Fan and Tessier-Lavigne, 1994; Loh et al., 2016). After 3 days, the organoids showed a robust induction of canonical sclerotome marker genes such as PAX1, SOX9, and COL2A1 (Figure 5C). Additionally, day 5 Somitoids were differentiated towards dermomyotome by exposing them to WNT/BMP agonists and SHH inhibitor for 48 hr followed by dissociation and culture on Matrigel as a monolayer in muscle differentiation medium (Loh et al., 2016; Matsuda et al., 2020) to further differentiate them to skeletal muscle. Immunostaining for myosin heavy chain (MYH1, a myocyte/myotube marker) confirmed that our Somitoid-derived cells can generate skeletal muscle derivatives in vitro (Figure 5—figure supplement 1). These data demonstrate that our in vitro-induced somite-like structures maintain their ability to differentiate further into somitic mesoderm derivatives of the sclerotome and dermomytome lineages.

Here, we reported the generation of human PM organoids from hPSCs that reproduce important features of somitogenesis not previously captured in conventional monolayer differentiation cultures, most notably formation of somite-like structures. Using a simple suspension culture that does not require manual matrix embedding, we identified optimal differentiation conditions by systematically screening initial cell numbers and modulating the signaling factors. Importantly, our culture conditions are compatible with high-throughput screening approaches. Many established organoid protocols currently have limited applications because they are not reproducible. Therefore, we set out to identify the optimal differentiation conditions that minimized the variability between organoids as quantified by automated image analysis.

One critical parameter we identified in our screens was the initial cell number used for aggregation. Our results suggest that if the initial cell number is above a certain threshold then somite fate cannot be induced in a homogeneous manner in our organoid system. This result is in line with previous findings in 3D models such as gastruloids, multi-axial self-organizing aggregates of mouse ES cells, which exhibit a higher degree of variability and multiple elongations when the number of initial cells exceeds a threshold (Beccari et al., 2018; van den Brink et al., 2014). Another important finding of our screens was that simply removing FGF, WNT pathway agonist as well as BMP inhibitor yielded the most reproducible and efficient somite-like structure-forming organoids. This treatment regime does not necessarily follow from applying prior in vivo and in vitro knowledge of somitogenesis. Previous protocols have used FGF and WNT inhibitors (Matsuda et al., 2020) or inhibition of all four candidate signaling pathways (FGF, WNT, BMP, and TGF-β) to induce somite fate (Loh et al., 2016) in monolayer cultured hiPSCs. While these conditions similarly induced somite fate marker genes in our 3D system, removal of FGF/WNT agonists and BMP inhibitor overall performed better as indicated by larger organoid diameters, higher average PAX3 expression levels, and higher number of somite-like structures. In line with these findings, our scRNA-seq analysis revealed that day 5 somite-like cells from our optimized protocol autonomously downregulate WNT target genes (DKK1, AXIN2, WNT3A, RSPO3; Figure 4—figure supplement 2) and FGF target genes (FGF8, FGF17, SPRY4, DUSP6/MKP3, SEF/IL17RD; Figure 4—figure supplement 5). Finally, our screening results also suggest that focusing on marker gene induction as a phenotypic readout alone is not sufficient to optimize culture conditions of more complex organoid models such as somitogenesis.

The scRNA-seq analysis of our hPSC-derived Somitoids independently confirmed our immunostaining and qRT-PCR results and showed that all major paraxial mesodermal cell types are generated, consistent with the cell types observed during PM development. Comparing our single-cell dataset with previously published in vitro-generated human PM transcriptomic data of monolayer cultures (Diaz-Cuadros et al., 2020; Matsuda et al., 2020) reveals a similar pattern of activation of marker genes. Diaz-Cuadros and colleagues did not generate bona fide somitic cells as their final timepoint cell population does not express canonical somitic markers. Matsuda et al. indeed show expression of several somitic marker genes including TCF15, MEOX1, and PAX3 based on bulk RNA-seq data. Interestingly, our own analysis of day 5 somitic cells revealed multiple distinct subclusters, suggesting transcriptional heterogeneity within this population, which could have not been inferred from bulk data (Figure 4B and C, Figure 4—figure supplement 4). Importantly, neither of these papers report formation of somite-like structures, suggesting that transcriptional similarity alone is not sufficient to predict morphological features, in line with our screening results showing that average marker gene expression is not a good predictor of in vitro induction efficiency of somite-like structures (Figure 3D and E, Figure 3—figure supplement 2A–C).

While expression patterns of canonical somitic marker genes seem to be conserved in humans, it will be interesting to perform detailed gene expression analysis to identify putative human-specific genes of somite differentiation. Since our Somitoid system is reproducible, it could serve as a versatile platform to perform functional screens of human-specific or disease-relevant genes using CRISPR/Cas9 or small-molecule inhibitor libraries. Somitoids thus provide a powerful in vitro system for studying the regulation and dynamics of human somitogenesis, including somite formation.

One limitation of this work is that the current protocol does not produce an AP axis and therefore does not generate somite-like structures in a bilaterally symmetric fashion as in the vertebrate embryo. A similar phenotype was recently reported in mouse gastruloids grown under similar signaling conditions that were embedded in Matrigel to promote self-organization into trunk-like structures (TLS; Veenvliet et al., 2020). Chemical modulation of BMP and WNT signaling pathways in Matrigel-embedded gastruloids resulted in the formation of somite-like structures arranged like a bunch of grapes, similar to what we observed in our system. In standard culture conditions, gastruloids and TLS recapitulate the axial organization of the embryo, which is missing in our Somitoids (Beccari et al., 2018; Moris et al., 2020; Veenvliet et al., 2020). To expand the patterning and morphogenetic potential of our Somitoid system, our approach could be combined with a microfluidics setup to generate spatio-temporally controlled morphogen gradients (Manfrin et al., 2019). In summary, Somitoids provide a scalable, reproducible, and easy to manipulate platform to study molecular networks underlying the differentiation of PM, as well as the morphogenetic processes of somite formation. Furthermore, Somitoids represent a promising in vitro system to study congenital diseases that are linked to the human segmentation clock and somite formation, such as congenital scoliosis.

Sequencing data has been deposited in GEO under accession code GSE194214; All data used to generate the figures are included in the manuscript as Source Data files.

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Author details

1. Christoph Budjan

   1. Department of Systems Biology, Harvard Medical School, Boston, United States
   2. Department of Data Science, Dana-Farber Cancer Institute, Boston, United States

   Contribution

   designed, optimized and performed the experiments; analyzed the experimental and single-cell RNA-sequencing data, Conceptualization, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1563-9750

2. Shichen Liu

   1. Department of Systems Biology, Harvard Medical School, Boston, United States
   2. Department of Data Science, Dana-Farber Cancer Institute, Boston, United States

   Contribution

   Methodology, assisted with single-cell sample collection and sequencing library preparation

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0964-6559

3. Adrian Ranga

   Laboratory of Bioengineering and Morphogenesis, Biomechanics Section, Department of Mechanical Engineering, Leuven, Belgium

   Contribution

   Methodology

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6400-9472

4. Senjuti Gayen

   1. Department of Systems Biology, Harvard Medical School, Boston, United States
   2. Department of Data Science, Dana-Farber Cancer Institute, Boston, United States

   Contribution

   Formal analysis

   Competing interests

   No competing interests declared

5. Olivier Pourquié

   1. Department of Genetics, Harvard Medical School, Boston, United States
   2. Department of Pathology, Brigham and Women's Hospital, Boston, United States

   Contribution

   Funding acquisition, Supervision

   Competing interests

   No competing interests declared

6. Sahand Hormoz

   1. Department of Systems Biology, Harvard Medical School, Boston, United States
   2. Department of Data Science, Dana-Farber Cancer Institute, Boston, United States
   3. Broad Institute of MIT and Harvard, Cambridge, United States

   Contribution

   Funding acquisition, Supervision, Writing – original draft, Writing – review and editing

   For correspondence

   sahand_hormoz@hms.harvard.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4384-4428

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