Lef1 expression in fibroblasts maintains developmental potential in adult skin to regenerate wounds

1Understanding how to induce skin regeneration instead of scarring will have broad implications clinically and cosmetically. One of the main characteristics of scars is the absence of hair follicles, indicating that their regeneration in a wound may be a critical step in achieving scar-less skin repair. Interestingly, human embryonic skin has the capacity to regenerate without scars. Similarly, neonatal and adult mouse skin has the capacity to regenerate small non-functional hair follicles under specific conditions (Figure 1c–d;;; ). These insights have prompted efforts in the field to define the molecular triggers that promote hair development in skin, with the ultimate goal of devising a way to regenerate fully functional hairs in adult skin wounds as a therapeutic modality.

2Human and mouse skin are similar in their overall structural complexity, indicating that mouse skin can be a useful model to study skin development and wound repair. Murine hair follicle and skin development primarily occurs between embryonic day 12.5 (E12.5) to post-natal day 21 (P21). During this time, different fibroblast lineages are established that respond to the changes in the environment to support hair follicle and skin development. Fibroblasts that support hair follicle development differentiate from the papillary fibroblast lineage, into dermal papilla (DP), dermal sheath (DS), and arrector pili (AP) cells. Reticular fibroblasts, which cannot differentiate into papillary fibroblast lineages, secrete extra-cellular-matrix (ECM) and form adipocytes. By post-natal day 2 (P2) fibroblast heterogeneity is fully established with the presence of the defined layers of the dermis (Figure 1a; ). Skin maturation occurs after P2 with the formation of the AP and the completion of the first hair follicle cycle, which results in the loss of a defined papillary fibroblast layer (Figure 1b;;; ). We have previously shown that papillary fibroblasts are the primary source of de-novo dermal papilla during skin development, which are required for hair formation. Furthermore, it has been suggested that adult murine skin form scars due to the lack of a defined papillary layer. Consequently, expanding this fibroblast layer in adult skin might support skin regeneration in adult mice.

3The use of scRNA-seq in the murine skin has established useful cell atlases of the skin during development and homeostasis. In addition, scRNA-seq studies investigating wound healing have so far focused on comparing scarring, non-scarring, or regenerating conditions. These studies have helped to identified key markers of the newly discovered skin fascia, including Gpx3, Plac8, and Mest, which recently has been shown to contribute to scar formation. These, scRNA-seq studies have revealed that transgenic activation of the Shh pathway in the alpha-smooth-actin cells in scarring wounds, which includes pericytes, blood vessels, and myofibroblasts, can support small non-functional hair regeneration. However, activation of Shh pathway in dermal fibroblasts is associated with malignant phenotypes and may perturb development and homeostasis such that it may not be a safe target to support human skin regeneration clinically. Altogether, these findings suggest that an overall comparison of developing, homeostatic, scarring, and regenerating skin conditions will yield important discoveries for molecular factors that can safely support skin regeneration without harmful side effects.

4The Wnt signaling pathway is involved in regulating development, wound healing, disease and cancer. Studies that activated Wnt and beta-catenin in skin have led to important discoveries for wound healing but have produced contrasting results in the context of fibroblast biology and hair follicle formation. Wnts are a group of secreted protein that activates a cascade of events that stabilizes nuclear beta-catenin, which operates as a powerful co-transcription factor of gene expression. Importantly, beta-catenin alone cannot activate the expression of Wnt target genes without co-transcription factors. There are four Wnt co-transcription factors Tcf7 (Tcf1), Lef1, Tcf3 (Tcf7l1), and Tcf4 (Tcf7l2). These co-transcription factors modulate the functional outcome of Wnt signaling by binding to different target genes. In the context of wound healing and regeneration, it is not known how differential expression of Tcf/Lef can modulate fibroblast activity via Wnt signaling.

5Since it has been shown that embryonic and neonatal skin have the potential to regenerate hair follicles upon wounding, we set out to identify the cell types and molecular factors that define this ability in order to transfer this regenerative potential to adult tissue. Our work has identified Lef1, as the factor in fibroblast of developing skin, that can transform adult tissue to regenerate.

6We and others have previously shown that there are differences between neonatal and adult skin in terms of their cellular and biological properties. These differences influence how skin can repair or if it can regenerate hair follicles in a wound. We showed that neonatal developing skin at P2 (Figure 1a) can regenerate small hair follicles 7 days after wounding (7dpw) (Figure 1c), while adult homeostatic skin at P21 (Figure 1b) heals by scarring 7dpw (Figure 1d). In order to identify the cell types and molecular pathways that define the ability of developing skin to regenerate, we performed a comparison of unsorted cells from four conditions using scRNA-seq (Figure 1e). A total of 66,407 cells from 12 libraries (n = 3 for each condition) met the preprocessing threshold, showed little batch variation (Figure 1—figure supplement 2), and were used for downstream analysis. Each condition was represented as different colors (Figure 1e–f). UMAP plotting of the 66,407 sequenced cells revealed distinct clusters (Figure 1f–g). To identify cell clusters, we used Louvain modulating analysis, which resulted in 18 distinct clusters (Figure 1g). We assigned seven main classes of cells to the clusters. Keratinocytes represented the largest portion of cell types in the analysis (blue clusters - 0, 1, 2, 5, 8, 9, 11, 12, 17) (Figure 1h). We identified three distinct fibroblast clusters (green clusters - 3, 4, 16). These clusters expressed Twist2, Pdgfra, and En1 (Figure 1h). We also identified other clusters based on their distinct gene expression profile (Figure 1h; Supplementary file 1), such as immune cells (cluster 6), vasculature (clusters - 7, 15), Schwann cells (cluster 10), melanocytes (cluster 13), and a pericyte population (cluster 14).

7To identify a unique cell type that supports the ability to regenerate hair follicles, we quantified the number of cells for each condition within a cluster and graphed them as a percentage of cell condition within a cluster (Figure 1i). Unexpectedly, there was no cluster exclusively defined by over-representation of the regenerating condition. Regenerating (green) and scarring (red) conditions were found in similar proportions amongst Keratinocytes, lymphocytes/blood, melanocytes, Schwann cells, blood vessels and fibroblasts (Figure 1i). However, there were two clusters that were distinct based on the percentage of cell types from a specific condition. Cluster 16 consisted of 99.9% of fibroblasts from homeostatic skin, while Cluster 3 consisted of 67.8% of developing fibroblasts (Figure 1i). In addition, cluster 4 consisted of 25.7% of regenerating condition, 57.6% of the scarring conditions. Since fibroblasts are known to play a critical role in regulating hair follicle reformation in wounds by differentiating into de-novo DP, we chose to further analyze clusters 3, 4, and 16.

8We subset the fibroblast clusters 3, 4, 16 and re-clustered them by performing an integration analysis. This allowed us to test if different fibroblast subtypes, such as the papillary and reticular/hypodermal/fascia lineages, would be represented uniquely within a condition (Figure 1j–l). UMAP plotting of the integrated analysis revealed 10 distinct clusters (Figure 1k). The largest cluster (cluster 0) expressed markers of the papillary fibroblast lineage (Figure 1e–g). Four clusters (clusters 1, 2, 3, 4) distinctly expressed markers of the reticular/hypodermal/fascia layers of the dermis (Figure 1k; Figure 1—figure supplement 1a–b; Supplementary file 1;; ). Three clusters (clusters 6, 7, 8) expressed markers of the dermal papilla and dermal sheath (Figure 1e–g). One cluster was distinctly represented by Acta2 indicating a myofibroblast subtype (cluster 9).

9To identify conditions that are represented within specific fibroblast subtypes, we quantified the percentage of cells from each condition within the sub-clusters (Figure 1l). Our results revealed that four clusters were uniquely represented by four conditions. The myofibroblast sub-cluster (cluster 9) contained 69% of cells from the regenerating condition, while a hypodermal fascia cluster (cluster 1) contained 92.2% of cells from the scarring condition. Cluster 4, identified by the high expression of Cochlin (Coch), an inner ear ECM protein, contained 80.8% of cells from the homeostasis condition and a DP/DS sub-clusters (cluster 6) contained 95.0% of cells from the homeostasis condition. The papillary fibroblast cluster (cluster 0) contained 98.1% of cells from the developing skin condition. The DP sub-cluster (cluster 7) consisted of 56.5% cells from the developing condition and 37.1% cells from the regenerating condition. These results indicate that there is a distinct separation based on condition between fibroblast sub-types neonatal papillary fibroblasts versus reticular/hypodermal/fascia. Moreover, regenerating, and scarring conditions were present in similar proportions across multiple fibroblasts subtypes, besides clusters of hypodermal and fascia cells that were mainly composed of the scarring condition. This suggested that both wounding conditions shared similar cellular and molecular signatures that may be driven by the wound healing process.

10Since our goal was to identify a cell type that uniquely represented the ability to support hair follicle formation that does not include a wound induced signature, we focused on cluster 0 which are developing fibroblasts. Developing fibroblasts migrate into wounds and support the reformation of hair follicles. In homeostatic skin DP and DS are critical for hair follicle growth and cycling. However, they do not migrate into wounds to support hair follicle reformation. Myofibroblasts are a major contributor to scar formation but may not normally differentiate into dermal papilla during hair follicle regeneration. Furthermore, reticular and fascia fibroblasts contribute to scar formation but do not differentiate into dermal papilla. We conclude that the developing fibroblasts are unique and might harbor the potential to support hair follicle regeneration in wounds.

11Neonatal developing skin has been extensively studied in the context of functional fibroblasts heterogeneity. To identify fibroblasts lineages in scRNA-seq data, we isolated cell clusters from developing skin using pan fibroblast marker Pdgfra and Twist2 (Figure 2d, Figure 2—figure supplement 1; ) and then overlaid previously identified molecular markers of different lineages including papillary (Dpp4+/Dlk1-/Ly6a-), reticular (Dpp4-/Dlk1+/Ly6a+/-) and hypodermal fibroblasts (Dpp4-/Dlk1-/Ly6a+) on the developing scRNA-seq UMAP (Figure 2a–e). We also identified small populations of fascia utilizing the new marker Gpx3 (Figure 2d; ). Furthermore, the dermal sheath cluster was identified by expression of Acan and Acta2 (; Figure 2d, Figure 2—figure supplement 1), which is plotted between the dermal papilla (DP) and papillary fibroblasts clusters (Figure 2d–e). The DP clusters were defined by expression of Corin, a well-established marker for DP. Interestingly, we also found novel heterogeneity within papillary fibroblast clusters. Besides the Dpp4+ clusters, Lef1 and Dkk1 expressions marked distinct papillary fibroblast clusters (Figure 2i, Figure 2—figure supplement 1). Overall, we concluded that the previously identified fibroblasts heterogeneity and the lineages could be identified in the scRNA-seq analysis of developing skin, with the additional subclusters of papillary fibroblasts (Figure 2e; ).

12To estimate and predict the future state of developing fibroblasts and to identify the driver genes for fibroblast heterogeneity, we performed RNA velocity analysis (Figure 2f; ). RNA velocity computationally compares the ratio of spliced and un-spliced mRNA from scRNA-seq data to estimate differentiation trajectories. The overall velocity analysis of developing fibroblasts is projected as arrows on the UMAP plot and it is defined by a list of putative driver genes (Supplementary file 2). Velocity analysis predicts that the dermal papilla is a differentiation endpoint, while papillary fibroblasts converge into the Dpp4 subcluster. Interestingly, the predicted differentiation trajectory of reticular fibroblasts suggests that they differentiate into arrector pili and also converge into the Dpp4 papillary subcluster. This contradicts previous in vivo lineage-tracing studies of the Dlk1+ fibroblast populations but agrees with ex vivo studies that tested the differentiation potential of Dpp4-/Dlk1+/Ly6a- fibroblast populations in chamber grafting and hydrogel assays. Hypodermal and fascia fibroblast clusters were predicted to maintain the lower lineage (Figure 2f).

13RNA velocity analysis predicts cellular trajectories using a list of the same driver genes that are ranked differently in each cluster (Figure 2i, Supplementary file 2). These genes are ranked based on their roles in driving the velocity trajectories. We performed PANTHER pathway classification on this list genes and found that the most highly represented pathways included Integrin signaling, Wnt signaling, Cadherin signaling and TGFb signaling pathways (Figure 2h; Supplementary file 5). We next ranked the top five genes that drive the velocity of each cluster (Figure 2i). We found that Dkk2, Mef2c, Lef1, and Egfl6 were identified to drive the velocity for different papillary clusters (Figure 2i). Col25a1, Smoc2, Fn1, Dcn, and Col4a1 were found to drive velocity to reticular and fascia clusters. Interestingly, Lef1 was found in the Papillary Dkk1 fibroblasts and the Dividing Papillary subclusters (Figure 2i). This suggests that the expression of Lef1 may drive RNA velocity toward papillary fibroblast and dermal papilla. We further analyzed Wnt signaling genes found in the papillary and dermal papilla clusters to determine the direction of the trajectory by phase contrast analysis (Figure 2j) Phase contrast analysis predicts that Lef1 and Wnt5a velocity increases towards to the papillary fibroblast and dermal papilla clusters (Figure 2j–k).

14To validate the expression and localization of Lef1 in developing skin fibroblasts, we visualized the in vivo expression pattern via immunostaining (Figure 2l–o). Our results confirmed the population of neonatal papillary fibroblasts that is found only in developing skin (Figure 2j, red arrows) and not in juvenile homeostatic skin (Figure 2k, white arrows). Co-staining with Dpp4 confirmed that Lef1 marked a subset of neonatal papillary fibroblasts (Figure 2l) that was also not found in juvenile skin (Figure 2m).

15The transient expression of Lef1 in neonatal papillary fibroblast correlates with the ability of neonatal developing skin to regenerate hair follicles in wounds. In addition, velocity analysis predicts that Lef1 drives developing fibroblast velocity to papillary fibroblast and DP. Importantly, subset analysis of regenerating and scarring fibroblasts did not identify fibroblasts defined by Lef1 expression, indicating that this transient population is unique to developing skin (Figure 2—figure supplement 2a–f; Supplementary file 4). We hypothesize that Lef1 expression in fibroblasts marks the ability of developing skin to regenerate hair follicles during the wound healing process.

16Based on our scRNA-seq findings, we postulated that Lef1 defines a neonatal papillary fibroblast that supports skin regeneration during neonatal wound healing. To test if Lef1 in fibroblasts is required to support neonatal regeneration, we produced a tissue-specific knockout model. We utilized the dermal specific promoter Twist2 to drive Cre expression, bred with a mouse line with flox sites flanking Exon 7 and 8 of the Lef1 locus. We called this mouse line Twist-Lef1cKO (Figure 3a). Twist-Lef1cKO mice were viable and fertile with small shifts in hair follicle phenotypes that resulted in less dense fur. We confirmed dermal Lef1 ablation from the papillary fibroblast at P2 and from adult DP by immunostaining (Figure 3b–e). We also performed 2 mm wounds on P2 Twist-Lef1cKO and wild-type littermates harvesting at 7dpw (Figure 3f). Our analyses revealed that Lef1 was expressed in the de-novo DP and regenerating hair follicle buds of wild-type mice (Figure 3g,i), but that wounded Twist-Lef1cKO mice lacked regeneration (Figure 3h,j,k). We conclude that Lef1 expression in neonatal fibroblasts is required for neonatal hair follicle regeneration in wounds.

17Our scRNA-seq data, together with tissue-specific knockout, implies that Lef1 expression in the dermis could convey the regenerative ability of neonatal papillary fibroblasts in adult skin. We hypothesize that constitutively active Lef1 expression in dermal fibroblasts will prime skin to support regeneration. To induce Lef1 expression in the dermis of the skin, we utilized a previously published transgenic mouse model Lef1KI bred with Twist2-Cre mouse line called the Twist-Lef1KI line (Figure 4a). We verified that Lef1 was expressed in all dermal fibroblast compartments in Twist-Lef1KI mice during development and in adult homeostatic skin conditions (Figure 4b–e). Importantly, the only phenotype detected was the early entry of the hair follicle cycling into anagen at P21 in Twist-Lef1KI mice (Figure 2d–e). In addition, Twist-Lef1KI mice have similar life spans as wild type mice without any adverse effects (Figure 4—figure supplement 1). Our results reveal that induced expression of Lef1 in fibroblasts does not negatively affect the development and homeostasis of murine skin.

18Adult skin normally does not regenerate but has the capacity to reform non-functional hair follicles (small and lack arrector pili) in wounds 1 cm2 or larger. To test if overexpression of Lef1 in adult dermal fibroblasts enhances hair regeneration in adult skin, we wounded wild type (Lef1KI) and Twist-Lef1KI mice at P24 with 1.2 cm2 wounds and harvested at 24dpw (Figure 4f). Our analysis comparing Lef1KI and Twist-Lef1KI wound beds revealed enhanced hair regeneration (Figure 4f–k). There were five times more regenerating hair follicles on average in Twist-Lef1KI wound beds compared to wild type wounds (Figure 4j–k). The non-functional hair follicles that typically regenerate in large adult wounds are small and lack the arrector pili, a smooth muscle that makes hair stand up when contracted. Strikingly, the hair follicles regenerating in the Twist-Lef1KI wound beds contained arrector pili (Figure 4i) and were larger than hair follicles found in wild-type wounds. We conclude that Lef1 expression in the dermis of the skin leads to enhances regeneration.

19Wound healing studies utilize a standardized approach to account for the hair follicle cycle, which influences the wound healing process. Consequently, the bulk of wound healing and regeneration studies are performed at 3 weeks of age (~P21) or at 7–8 weeks of age (~P57). In addition, a standard size wound of roughly 8 mm in diameter or smaller is used, which heal by scarring. Since Lef1KI mice showed enhanced regenerative capacity in large wounds, we explored the regeneration potential of Twist-Lef1KI skin in wounds that normally scar. To determine if the hair follicle cycle influences skin regeneration we performed wounds at different time points: P24 which undergoes a hair follicle cycle during wound healing; P40 which heals during the resting phase of the hair cycle; and P90 which is the beginning of the un-synchronized hair follicle cycling that occurs in adult mice (Figure 5a). Scars formed in wounds performed at P24 in both WT and Twist-Lef1KI mice (Figure 5b–c,l). However, hair follicle regeneration with arrector pili occurred in wounds performed at P40 and P90 in Twist-Lef1KI mice (Figure 5d–k,l; Figure 5—figure supplement 1; Figure 5—figure supplement 2). Occasionally, we observed cyst-like structures in regenerated wounds, similar to that observed in WIHN. We conclude that Lef1 expression in the dermis induces skin to support hair follicle regeneration in wounds with variation depends on the timepoints and hair follicle cycle.

20Our wound healing studies mirror previous work suggesting that the size of a wound can dictate the potential of skin to regenerate instead of scar. To explain ‘why size matters’ we investigated and mapped the timing of wound closure and regeneration in the context of molecular signals within the dermal macro-environment that are dynamically changing throughout the hair follicle cycle. Previous studies have defined the activators and inhibitors that regulate hair follicle cycling during this time (; Supplementary file 3). Activators include the Wnt signaling pathway, Noggin, Tgfb, and fibroblast markers such as Pdgfra. Inhibitors include the BMP signaling pathway. These activators and inhibitors have been previously shown to modulate Lef1 activity. To explain why Twist-Lef1KI mice scar at P24, we generated a diagram of wound re-epithelization and healing time points comparing 8 mm circular wounds to 1.2 cm2 wound in the context of gene expression for inhibitors and activators at all time points during the hair follicle cycle (Figure 5l). 8 mm circular wounds re-epithelialize 7 dpw in a macro-environment with high levels of Lef1 inhibitors, which are not inductive to hair follicle formation (Figure 5l). In contrast, large 1.2 cm2 wounds re-epithelialize during the time point of the hair cycle that has high activators and low inhibitors (Figure 5l). We conclude that the size of a wound dictates the time point when wound closure occurs which is associated with inhibitor or inductive regenerative signals.

21It is well established that embryonic and neonatal skin has the potential to heal in a scar-less manner. However, the cell types and signals that can transfer this ability to adult skin have not been identified. In this study, we identify developing papillary fibroblasts as a transient cell population that is defined by Lef1 expression. Inducing Lef1 expression in the adult dermis will prime skin to support enhanced hair follicle regeneration. Interestingly, ectopic Lef1 expression in the dermis did not result in any adverse phenotypes during development (Supplementary file 4).

22scRNA-seq has provided an unprecedented insight in the cell types and molecular pathways that are represented within regenerating and scarring wounds. For example, comparisons of these different conditions have identified the activation of the Shh pathway as a key pathway to support hair follicle regeneration in wounds of different sizes. However, the activation of ectopic Shh in either the epidermis or dermis is associated with unwanted phenotypes and cancer. Unexpectedly, we discovered a neonatal papillary fibroblast population that is defined by Lef1 expression in developing skin instead of in regenerating conditions. Importantly, our comparative analysis of regenerating and scarring wounds reveals their similarities (Figure 1i, Figure 2—figure supplement 2) more than their differences suggesting that the wound environment is a powerful driving force for gene expression even with a heterogeneous population of cells. Consequently, the basic mechanisms occurring during development and maintenance of neonatal tissue may hold the keys to transforming adult tissue to regenerate instead of scarring.

23Studies involving the activation of the Wnt and beta-catenin pathways in skin have led to important discoveries in wound healing research, but have produced contrasting results in the context of fibroblast biology and hair follicle formation. The activation of beta-catenin in fibroblasts during wound healing has been shown to inhibit hair follicle reformation in scars while deactivating Wnt signaling inhibited hair reformation. Moreover, persistent Wnt activity in the dermis has been recently shown to drive WIHN toward fibrotic wound healing. In contrast, the activation of beta-catenin during development increases hair formation and size. One explanation for these conflicting results is the presence of different fibroblast lineages present in either development or wounds, which express different Lef/Tcf factors to direct a Wnt/beta-catenin-specific response. We and others have shown that Lef1 is expressed in embryonic and neonatal papillary fibroblasts, which is lost in adult fibroblasts. Here, we demonstrate that Lef1 is a key transcription factor in developing fibroblasts that supports hair follicle formation in adult wounds. Our data indicates that Lef1 expression in the dermis of the skin primes a response to support hair follicle neogenesis and arrector pili reformation in the wound. Our results align with studies that induced Lef1 expression in cultured human dermal papilla cells to enhance hair follicle formation in vitro. In humans, at the age of 50+, the quality of the papillary dermis gradually deteriorates, which correlates with the aging skin decreased wound healing abilities. Our data suggests that activating the papillary region to retain its identity by expression of Lef1 has the potential to enhance wound healing in humans.

24All mice were outbred on a C57BL6/CBA background, with male and female mice used in all experiments. The following transgenic mouse lines were used in this study, Twist2-Cre (RRID:MGI:3840442) (Cat# 008712). The ROSA26-CAG-flox-GFP-STOP-flox-Lef1 and Lef1-flox-Exon7,8-flox mice (RRID:MGI:5447957) were a kind gift and have been previously described. Wild-type mice utilized in scRNA-seq experiments were an outbred background of C57BL6/CBA mice.

25All wounding experiments were done in accordance with the guidelines from approved protocols Washington State University IACUC. Mice were wounded at post-natal day (P) 2, P24, P40 and P90 as stated in the results section. All wounding experiments were carried out with mice under anesthetization. The dorsal hair was shaved, and wounding areas were disinfected. For full-thickness circular wound, 2 mm and 8 mm punch biopsy and surgical scissors were used to create circular wounds on P2 and P24/P40 mice, respectively. For large wounds, 1.44 cm2 (1.2 × 1.2 cm) squares were excised using surgical scissors. Wounds were harvested at 7 dpw, 14 dpw, 24 dpw, and 30 dpw.

26This procedure was described in. Briefly, full thickness skin samples were collected and fixed in 4% Paraformaldehyde (PFA), before being frozen in OCT compound in cryo-block. Samples were sectioned using cryostat at 60 micro m thickness. Skin sections were then stained with primary antibodies at 4°C overnight in PB buffer and with secondary antibodies in PB buffer for 1 hr. Samples were mounted on glass cover slip with glycerol as mounting medium.

27Tissues were collected from dorsal regions of unwounded P2 and P21 mice, and right on the edge of 2 mm wounds 7 days post wound from P2 wound and P21 wound. Cells isolation procedure was previously described in Jensen and Driskell 2009 Nature Protocols. Single-cell cDNA libraries were prepared using the 10X Genomics Chromium Single Cell 3’ kit. For each condition, three mice were used to generate three separate libraries, making it a total of 12 libraries across all four conditions. All samples were processed individually. The prepared libraries were sequenced on Illumina HiSeq 4000 (100 bp Paired-End). Demultiplexed Paired-End fastq files were aligned to mm10 reference genome using 10X Genomics CellRanger function (RRID:SCR_017344)(Cellranger version 3.0.2). FASTQ files for this manuscript can be access at NCBI Geo-Datasets: GSE153596. The outputs of CellRanger alignment were used to create loom files by Velocyto ‘run10x’ function. Loom files are the preferred input data for scVelo package (RRID:SCR_018168) to perform RNA Velocity analysis.

28For basic filtering of our data, we filtered out cells have expressed less than 200 genes and genes that are expressed in less than three cells. To ensure that the data is comparable among cells, we normalized the number of counts per cell to 10,000 reads per cell as suggested by the Scanpy pipeline (RRID:SCR_018139). Data were then log-transformed for downstream analysis and visualization. We also regressed out effects of total counts per cell and the percentage of mitochondrial genes expressed, then scaled the data to unit variance with the maximum standard deviation 10.

29Neighborhood graph of cells was computed using PCA presentation (n PCs = 40, n neighbors = 10). The graph was embedded in two dimensions using Uniform Manifold Approximation and Projection (UMAP) as suggested by Scanpy developers. Clusters of cell types were defined by Louvain and Leiden method for community detection on the generated UMAP graph at resolution of 0.2. The analysis pipeline is published on the Driskell lab Github page as Jupyter Notebook (https://github.com/DriskellLab/Priming-Skin-to-Regenerate-by-Inducing-Lef1-Expression-in-Fibroblasts-; copy archived at https://github.com/elifesciences-publications/Priming-Skin-to-Regenerate-by-Inducing-Lef1-Expression-in-Fibroblasts-; ).

30The microarray data were previously published (GEO GSE11186). RMA normalization was used, and the bottom twentieth percentile of genes were excluded from the analysis.