Fig 2: Myb function is required for both Hoxb8 and non-Hoxb8 hematopoietic progenitors during fetal liver hematopoiesis. (A-C) Representative flow cytometry plots of Ter119- Kit+ cells gated for tdTomato from the fetal liver (FL) of (A) E11.5, (B) E12.5 and (C) E14.5 Myb+/+ and Myb-/- embryos. (D,E) Representative flow cytometry plots of CD16/32+ EMPs (CD41+ Kit+) gated for tdTomato from fetal livers of E12.5 (D) Myb+/+ and (E) Myb-/- embryos. (F-H) Number of Hoxb8 lineage (B8L) and non-Hoxb8 lineage (nB8L) cells in the Kit+ population in fetal livers of (F) E11.5, (G) E12.5 and (H) E14.5 Myb+/+ and Myb-/- embryos. E11.5: n=2 biological replicates per group; two-way ANOVA with post-hoc analysis comparing Myb+/+ with Myb-/- in B8L (P=0.0351) and nB8L (P<0.0001). E12.5: n=2 biological replicates per group; two-way ANOVA with post-hoc analysis comparing Myb+/+with Myb-/- in B8L (P=0.0047) and nB8L (P<0.0001). E14.5: n=5 biological replicates (Myb+/+) and n=3 biological replicates (Myb-/-); two-way ANOVA with post-hoc analysis comparing Myb+/+ with Myb-/- in B8L (P<0.0001) and nB8L (P=0.9406). (I) Number of B8L and nB8L cells in the CD16/32+ EMP population of the E12.5 fetal liver. n=2 biological replicates per group; two-way ANOVA with post-hoc analysis comparing Myb+/+ with Myb-/- in B8L (P=0.0040) and nB8L (P=0.0150). Gray circles are individual data points. Data are mean±s.e.m. n.s., non-significant, *P<0.05, **P<0.01, ****P<0.0001. Data are from two or three independent experiments per time point.

Fig 3: Hoxb8 lineage CD16/32+ EMPs become the dominant EMP population in the fetal liver. (A,B) Representative flow cytometry plots of EMPs (Kithigh CD16/32+ CD41+) gated for tdTomato from (A) yolk sac (E8.5, E9.5 and E11.5) and (B) fetal liver (E11.5, E12.5 and E14.5). (C) Percentage of Hoxb8 (B8L) and non-Hoxb8 (nB8L) CD16/32+ EMPs during development in the yolk sac (YS) and fetal liver (FL). E8.5 YS, E9.5 YS and E10.5 YS: n=5 pooled biological replicates. E11.5 YS, E11.5 FL, E12.5 FL and E14.5 FL: n=6 biological replicates. Two-way ANOVA with post-hoc analysis comparing nB8L cells with B8L cells across all time points examined: ****P<0.0001. Gray circles are individual data points. Data are mean±s.e.m. Data are from two or three independent experiments per time point. (D,E) Representative images of YS and FL sections from E11.5 and E14.5 embryos marked with (D) Hoxb8-tdTomato, Cx3cr1-GFP and Kit, and (E) Hoxb8-tdTomato, Cx3cr1-GFP and CD41 antibodies. n=3 biological replicates per time point. Scale bars: 50 µm. White arrows indicate tdTomato+ GFP- cells that are (D) Kit+ or (E) CD41+.

Fig 4: Morphological characterization of MKs from mice with breast cancer.Spontaneous tumor growth within the mammary fat pads of (A) MMTV-PyMT (PyMT) mice and tumor growth in mice orthotopically inoculated with either Met-1 (B) or AT-3 (C) cells. Arrows depict age of PyMT animals or days post-inoculation upon sacrifice. n = 5 to 10 mice per condition. (D to F) Femurs from PyMT and wild-type (WT) mice, or orthotopically injected animals were immunofluorescently stained for MKs (CD41, cyan), nuclei (DAPI, gray), and blood vessels (laminin, magenta). Phosphate-buffered saline (PBS)–injected mice were used as orthotopic tumor-naïve controls. Scale bars, 50 µm; n = 4 to 5 mice per condition. P values were determined by two-sample t tests. (G to I) Polyploidization of native MKs from either PyMT and WT mice or orthotopic Met-1 and AT-3 models. n = 4 to 5 mice per condition. *P < 0.05 and **P < 0.01, as determined by one-way ANOVA.

Fig 5: Transcriptomic profiling of MKs from a model of murine breast cancer.CD41+ DAPIlow cells were isolated from the BM of a 13-week-old PyMT mouse and a WT littermate for scRNA-seq. (A) Dimensionality reduction using Uniform Manifold Approximation and Projection (UMAP) of pooled PyMT and WT samples. Cells of MK lineage (orange) were separated into five clusters (G1 = 1699, G2/M = 1395, MK1 = 871, MK2 = 537, and MK3 = 344 cells) based on differential gene expression. Gray cells from non-MK clusters (n = 4184 cells) were excluded. (B) Overlay of PyMT (red, n = 3817) and WT (blue, n = 5213) cells. (C) Heatmaps clustered according to average log fold change depicting the top 50 differentially expressed genes between PyMT and WT cells in MK1, MK2, and MK3. Scatterplots depict gene expression of all recorded transcripts. Red lines model no change in gene expression between WT and PyMT samples. (D) Diseases and functions associated with differentially expressed genes in MKs from PyMT mice. (E) Expression levels of thrombospondin 1 (Thbs1), cathepsin G (Ctsg), S100a8, and S100a9 mRNA transcripts among MK subclusters.