Schematic representation of cell fate decisions driven by noise (A) and signal (B) from a view of epigenetic landscape.

(A-B) Valleys represent stable attractors. Cells (yellow balls) in stem cell fate (denoted as “S”, green well in landscape) differentiate into downstream fates, lineage X (denoted as “LX”, blue well) and lineage Y (denoted as “LY”, purple well). These abbreviations were used for following Figure 2-7.

Models of the Cross-Inhibition with Self-activation (CIS) network incorporated logic motifs.

(A) A table listing the topologies with logic nodes, logic functions and Cis-Regulatory Elements (CRE) configurations in the CIS network incorporated AND-AND and OR-OR logic (denoted as AND-AND motif and OR-OR motif). X and Y are lineage-specifying transcription factors (TF). Xt+1 indicates the value of X at the next time step. X*, Y* represent activated forms of X and Y, respectively. The true or false signs denote whether gene X can be transcribed, respectively. These annotations were used for the following Figure 3-7.

(B) State spaces of the AND-AND (top panel) and OR-OR (bottom panel) motifs in Boolean models. Updated rules of Boolean models are stated in Figure 2. Rectangles indicate cell states. Green, blue, purple represent S, LX, and LY, respectively. Solid arrows indicate transitions between states under corresponding Boolean models. Dotted arrows indicate forced transition imposed by external perturbations.

(C) State spaces of the AND-AND (top panel) and OR-OR (bottom panel) motifs in ODE models. Dark and red lines represent nullclines of , respectively. Stable steady states (SSS) are denoted as orange dots. Unstable Steady States (USSs) are denoted as white dots. Each axis represents the concentration of each transcription factor, which units are arbitrary. Blue, green and purple areas in state spaces indicate attractor basins representing LX, S and LY, respectively. Color of each point in state space was assigned by the attractors they finally enter according to the deterministic models (Eq1, Eq2). These annotations were used for the following Figure 3-7.

(D) The solution landscape both for the AND-AND and OR-OR motifs. The crimson X-cross sign denotes the first-order saddle node. Blue, green, and purple circles indicate attractors. These annotations were used for the following Figure 3-7.

(E-F) Simulation result of stochastic differential equation models of the AND-AND (E) and OR-OR (F) motifs. Other than adding a white noise, parameters were identical with those in (C). Initial values were set to the attractor representing S fate in Figure 2C top panel (E) and Figure 2C bottom panel (F). Noise levels of Xx) and Yy) are both set to 0.14 in the AND-AND motif (E), and 0.1 in the OR-OR motif (F). Stochastic simulation was preformed 3500 times, with each final state recorded as a dot on the plot. Color of heatmap corresponds to the density of points. Unit of concentration is arbitrary.

Two logic motifs exhibit opposite bias of fate decisions under the noise-driven mode.

(A and C) Stochastic simulation in both the AND-AND and OR-OR motifs. σx is set to 0.18, and σy is 0.12. In both (A) and (C), initial values were identical with attractors of stem cell fate in Figure 2C (SSSs in green attractor basins). Simulation was preformed 1500 times, with each initial (A left and C left) and final (A right and C right) states recorded as a dot on the plot.

(B and D) Time courses of the percentage of cells in different fates in stochastic simulation, under the AND-AND motif (B) and OR-OR motif (D). Fates of cells were assigned by their final states according to the basins of the deterministic models in Figure 2C. Unit of time is arbitrary.

(E) Heatmaps showing the bias of cell fate decisions under different noise levels of X and Y. Color of heatmap indicates the extent of bias. Here, bias . nLX, nLY represent number of LX, LY, respectively. ntotal represents the total number of cells (ntotal = 1500). The method of assigning fate to cells is identical with Figure 3B and 3D. The red marked cells correspond to the noise conditions simulated in (A) and (C).

(F) Schematic illustration in that stem cell populations possessing the same bias of fate decisions need to have opposite noise patterns, according to whether they are in the AND-AND or OR-OR motif. The red and bold arrow indicates the bias of fate decisions.

Two logic motifs decide oppositely between differentiation and maintenance under the signal- driven mode.

(A-B) Bifurcation diagrams for the AND-AND motif (A) and OR-OR motif (B) driven by parameter u (u = ux = uy) in the CIS model. SSSs and USSs are denoted as solid dots and hollow dots, respectively.

(C and F) Changes in the state spaces for the AND-AND motif (C) and OR-OR motif (F) with increasing parameter u, from top to down.

(D and G) Changes in the solution landscape with increasing of u, in company with these in (C and F). The crimson X-cross sign and yellow triangle denote first-order and second-order saddle nodes, respectively. Relative energy is quantified by the geometric minimum action method [90], see Methods.

(E) The solution landscape with parameter u = 0.0565 for the AND-AND motif from a view of three dimensions. It describes a hierarchical structure of the steady states. From top to bottom, it represents 2-saddle (yellow triangle), 1-saddles (crimson X-cross sign), and the attractors (green dot). The layer of 1-saddles is represented by a blue translucent plane, and the bottom layer is the flow field diagram. The connections from 2-saddle to 1-saddles are represented by red lines, and the connection from 1-saddles to the attractors are represented by blue lines. In the flow field diagram, the direction and color of the arrows correspond to the direction and size of the flow at that location. The corresponding positions of 2-saddle and 1-saddles in the flow field are marked with yellow and red dots, respectively, with black dashed lines indicating the corresponding relationship.

The progression-accuracy trade-off in cell fate decisions.

(A) Schematic illustration of S-to-LX cell fate decisions with X-inducing signals. The red and bold arrow indicates the direction of fate decisions.

(B-C) Bifurcation diagrams for the AND-AND motif (B) and OR-OR motif (C) driven by parameter ux.

(D and F) Changes in the state spaces for the AND-AND motif (D) and OR-OR motif (F) with increasing values of ux, from top to down.

(E and G) Changes in the solution landscape with increasing of ux, in company with these in (D and F).

The CIS network performs differently during hematopoiesis and embryogenesis.

(A) Schematic illustration of S differentiating into LX. We took fate transition labeled in light pink shade as an example in following simulation.

(B) Time courses on the coefficient of variation in expression levels of X and Y genes in silico during differentiation towards LX (uxswitches from 0 to 0.08 from time point 1 to 9) in the AND-AND motif. Initial values were set to the attractors of stem cell fate in Figure 2C top panel (SSS in green attractor basin). σx and σy are both set to 0.07. Stochastic simulation was preformed 1000 times for each pseudo-time point. Unit of time is arbitrary.

(C) Time courses on the coefficient of variation in expression levels of X and Y genes in silico during differentiation towards LX (uxswitches from 0 to 0.24 from time point 1 to 9) in the OR-OR motif. Initial values were set to the attractors of stem cell fate in Figure 2C bottom panel (SSS in green attractor basin). σx and σy are both set to 0.05. Stochastic simulation was preformed 1000 times for each pseudo-time point. Unit of time is arbitrary.

(D) Schematic illustration of distinctive cell fate decision patterns under the AND-AND and OR-OR motifs in the state space. Dark and red gradients represent the extent of “AND-AND” and “OR-OR” in the actual regulatory network, respectively. Each axis represents expression levels of the lineage-specifying TFs. Blue, green, and purple circles indicate the cell fates of LX, S, and LY, respectively.

(E) Schematic illustration of Gata1-PU.1 circuit that dominates the primary fate decisions in hematopoiesis (CMP: Common myeloid progenitor; MEP: megakaryocyte-erythroid progenitor; GMP: Granulocyte-monocyte progenitor).

(F) Measured coefficient of variation of expression levels of Gata1 and PU.1 changing over time during differentiation from CMPs to MEPs and GMPs. Expression levels were quantified via single-cell RT-qPCR [85]. Error bars on points represent standard deviation (SD). For details of data processing, see Methods.

(G) Schematic illustration of the differentiation from mESCs in induction system [95].

(H) Measured expression levels of Gbx2 and Tbx3 among cells in embryogenesis quantified via single-cell SMART-seq2 [95]. For details of data processing, see Methods.

The chemical-induced reprogramming of human EB to iMK is the signal-driven fate decisions with an OR-OR-like motif.

(A) Schematic illustration of the differentiation from MEPs in vivo and in vitro. Red arrows represent the route of reprogramming [98]

(B) Measured expression levels of KLF1 and FLI1 in reprogramming quantified via single-cell 10X. For details of data processing, see Methods.

(C) Bifurcation diagrams for the OR-OR motif driven by parameter uy in the CIS model.

(D) Fate transition representing reprogramming of EB to iMK in silico. Top panel: changes in the solution landscape with increasing of parameter uy, from left to right; Bottom panel: changes in the state spaces for the OR- OR motif with increasing values of uy, in company with these in top panel. Unit of concentration is arbitrary.

(E) Left panel: coefficient of variation of expression levels of KLF1 and FLI1 changes in silico over time under given parameter (uy= 0.11) in the OR-OR motif. Noise level of KLF1x) and FLI1y) are set to 0.087. Initial values were identical with LX attractor in Figure 2C bottom panel (SSS in blue attractor basin). Stochastic simulation was preformed 1000 times per round for each time point. We totally preformed 3 round simulations. Error bars on points represent SD; Right panel: measured coefficient of variation of expression levels of KLF1 and FLI1 changing over time in the processes from EBs to iMKs. Unit of time is arbitrary.

(F) Identification of distinct temporal patterns of expression variance by fuzzy c-means clustering. The x axis represents four time points, while the y axis represents scaled CV (coefficient of variation) in each time point. Dark trend lines in the middle indicate the average of scaled CV over genes in cluster.

(G) Enriched major Gene Ontology terms for cluster 5 and 10.

(H) Regulatory network of TFs in cluster 5 and 10. Circle size indicates the sum of in-degree and out-degree. Node colors indicate different Supermodules (adapted from [98]). Green and red edges indicate activation and inhibition, respectively. The light blue and light pink shades denote genes in cluster 5 and 10, respectively.