Regulatory Logic Research Articles

Two coacting shadow enhancers regulate twin of eyeless expression during early Drosophila development.

The Drosophila PAX6 homolog twin of eyeless (toy) sits at the pinnacle of the genetic pathway controlling eye development, the retinal determination network. Expression of toy in the embryo is first detectable at cellular blastoderm stage 5 in an anterior-dorsal band in the presumptive procephalic neuroectoderm, which gives rise to the primordia of the visual system and brain. Although several maternal and gap transcription factors that generate positional information in the embryo have been implicated in controlling toy, the regulation of toy expression in the early embryo is currently not well characterized. In this study, we adopt an integrated experimental approach utilizing bioinformatics, molecular genetic testing of putative enhancers in transgenic reporter gene assays and quantitative analysis of expression patterns in the early embryo, to identify 2 novel coacting enhancers at the toy gene. In addition, we apply mathematical modeling to dissect the regulatory landscape for toy. We demonstrate that relatively simple thermodynamic-based models, incorporating only 5 TF binding sites, can accurately predict gene expression from the 2 coacting enhancers and that the HUNCHBACK TF plays a critical regulatory role through a dual-modality function as an activator and repressor. Our analysis also reveals that the molecular architecture of the 2 enhancers is very different, indicating that the underlying regulatory logic they employ is distinct.

Interpreting deep neural networks for the prediction of translation rates

BackgroundThe 5’ untranslated region of mRNA strongly impacts the rate of translation initiation. A recent convolutional neural network (CNN) model accurately quantifies the relationship between massively parallel synthetic 5’ untranslated regions (5’UTRs) and translation levels. However, the underlying biological features, which drive model predictions, remain elusive. Uncovering sequence determinants predictive of translation output may allow us to develop a more detailed understanding of translation regulation at the 5’UTR.ResultsApplying model interpretation, we extract representations of regulatory logic from CNNs trained on synthetic and human 5’UTR reporter data. We reveal a complex interplay of regulatory sequence elements, such as initiation context and upstream open reading frames (uORFs) to influence model predictions. We show that models trained on synthetic data alone do not sufficiently explain translation regulation via the 5’UTR due to differences in the frequency of regulatory motifs compared to natural 5’UTRs.ConclusionsOur study demonstrates the significance of model interpretation in understanding model behavior, properties of experimental data and ultimately mRNA translation. By combining synthetic and human 5’UTR reporter data, we develop a model (OptMRL) which better captures the characteristics of human translation regulation. This approach provides a general strategy for building more successful sequence-based models of gene regulation, as it combines global sampling of random sequences with the subspace of naturally occurring sequences. Ultimately, this will enhance our understanding of 5’UTR sequences in disease and our ability to engineer translation output.

Gene module reconstruction identifies cellular differentiation processes and the regulatory logic of specialized secretion in zebrafish.

During differentiation, cells become structurally and functionally specialized, but comprehensive views of the underlying remodeling processes are elusive. Here, we leverage single-cell RNA sequencing (scRNA-seq) developmental trajectories to reconstruct differentiation using two secretory tissues as models-the zebrafish notochord and hatching gland. First, we integrated expression and functional similarities to identify gene modules, revealing dozens of modules representing known and newly associated differentiation processes and their dynamics. Second, we focused on the unfolded protein response (UPR) transducer module to study how general versus cell-type-specific secretory functions are regulated. Profiling loss- and gain-of-function embryos identified that the UPR transcription factors creb3l1, creb3l2, and xbp1 are master regulators of a general secretion program. creb3l1/creb3l2 additionally activate an extracellular matrix secretion program, while xbp1 partners with bhlha15 to activate a gland-like secretion program. Our study presents module identification via multi-source integration for reconstructing differentiation (MIMIR) and illustrates how transcription factors confer general and specialized cellular functions.

Developmental transcriptomics in Pristionchus reveals the logic of a plasticity gene regulatory network.

Developmental plasticity enables the production of alternative phenotypes in response to different environmental conditions. While significant advances in understanding the ecological and evolutionary implications of plasticity have been made, understanding its genetic basis has lagged. However, a decade of genetic screens in the model nematode Pristionchus pacificus has culminated in 30 genes which affect mouth-form plasticity. We also recently reported the critical window of environmental sensitivity, and therefore have clear expectations for when differential gene expression should matter. Here, we collated previous data into a gene-regulatory network (GRN), and performed developmental transcriptomics across different environmental conditions, genetic backgrounds, and mouth-form mutants to assess the regulatory logic of plasticity. We found that only two genes in the GRN (eud-1 and seud-1/sult-1) are sensitive to the environment during the critical window. Interestingly, the time points of their sensitivity differ, suggesting that they act as sequential checkpoints. We also observed temporal constraint upon the transcriptional effects of mutating the GRN and revealed unexpected feedback between mouth-form genes. Surprisingly, expression of seud-1/sult-1, but not eud-1, correlated with mouth form biases across different strains and species. Finally, a comprehensive analysis of all samples identified metabolism as a shared pathway for regulating mouth-form plasticity. These data are presented in a Shiny app to facilitate gene-expression comparisons across development in up to 14 different conditions. Collectively, our results suggest that mouth-form plasticity evolved a constrained, two-tiered logic to integrate environmental information leading up to the final developmental decision.

Regulatory logic and transposable element dynamics in nematode worm genomes.

Genome sequencing has revealed a tremendous diversity of transposable elements (TEs) in eukaryotes but there is little understanding of the evolutionary processes responsible for TE diversity. Non-autonomous TEs have lost the machinery necessary for transposition and rely on closely related autonomous TEs for critical proteins. We studied two mathematical models of TE regulation, one assuming that both autonomous tranposons and their non-autonomous relatives operate under the same regulatory logic, competing for transposition resources, and one assuming that autonomous TEs self-attenuate transposition while non-autonomous transposons continually increase, parasitizing their autonomous relatives. We implemented these models in stochastic simulations and studied how TE regulatory relationships influence transposons and populations. We found that only outcrossing populations evolving with Parasitic TE regulation resulted in stable maintenance of TEs. We tested our model predictions in Caenorhabditis genomes by annotating TEs in two focal families, autonomous LINEs and their non-autonomous SINE relatives and the DNA transposon Mutator . We found broad variation in autonomous - non-autonomous relationships and rapid mutational decay in the sequences that allow non-autonomous TEs to transpose. Together, our results suggest that individual TE families evolve according to disparate regulatory rules that are relevant in the early, acute stages of TE invasion.

Negative feedback of cyclic di-GMP levels optimizes switching between sessile and motile lifestyles in Vibrio cholerae.

The signaling molecule cyclic di-GMP (cdG) controls the switch between bacterial motility and biofilm production, and fluctuations in cellular levels of cdG have been implicated in Vibrio cholerae pathogenesis. Intracellular concentrations of cdG are controlled by the interplay of diguanylate cyclase (DGC) enzymes, which synthesize cdG to promote biofilms, and phosphodiesterase (PDE) enzymes, which hydrolyse cdG to drive motility. To track the complete regulatory logic of how V. cholerae responds to changing cdG levels, we followed a timecourse of overexpression of either the V. harveyi diguanylate cyclase QrgB or a variant of QrgB lacking catalytic activity (QrgB*). We find that QrgB increases cdG levels relative to QrgB* for 30 minutes after overexpression, but the effect of QrgB on cdG levels plateaus at 30 minutes, indicating tight adaptive control of cdG levels. In contrast, loss of VpsR, a master regulator activating biofilm formation upon binding to cdG, leads to higher baseline levels of cdG and continuously increasing cdG through 60 minutes after QrgB induction, revealing the existence of a negative feedback loop on cdG levels operating through VpsR. Through a combination of RNA polymerase ChIP-seq, RNA-seq, and genetic approaches, we show that transcription of a gene encoding a PDE, cdgC, is activated by VpsR at high cdG concentrations, mediating this negative feedback on cdG levels. We further identify a transcript encoded within, and antisense to, the cdgC open reading frame which we name sRNA negative regulator of CdgC (SnrC). RNA polymerase ChIP-seq and RNA-seq demonstrate SnrC to be expressed specifically under conditions of high cdG in the absence of VpsR. Ectopic SnrC expression increases cdG levels in a manner dependent on CdgC, demonstrating that its effect on cdG levels is likely through interference with CdgC production. Further, although cells lacking cdgC exhibit enhanced biofilm formation, these mutants are outcompeted by wild type V. cholerae in colonization assays that reward a combination of attachment, dispersal, and motility behaviors. These results underscore the importance of negative feedback regulation of cdG to maintain appropriate homeostatic levels for efficient transitioning between biofilm formation and motility, both of which are necessary over the course of the V. cholerae infection cycle.

Dissecting the regulatory logic of specification and differentiation during vertebrate embryogenesis.

The interplay between transcription factors and chromatin accessibility regulates cell type diversification during vertebrate embryogenesis. To systematically decipher the gene regulatory logic guiding this process, we generated a single-cell multi-omics atlas of RNA expression and chromatin accessibility during early zebrafish embryogenesis. We developed a deep learning model to predict chromatin accessibility based on DNA sequence and found that a small number of transcription factors underlie cell-type-specific chromatin landscapes. While Nanog is well-established in promoting pluripotency, we discovered a new function in priming the enhancer accessibility of mesendodermal genes. In addition to the classical stepwise mode of differentiation, we describe instant differentiation, where pluripotent cells skip intermediate fate transitions and terminally differentiate. Reconstruction of gene regulatory interactions reveals that this process is driven by a shallow network in which maternally deposited regulators activate a small set of transcription factors that co-regulate hundreds of differentiation genes. Notably, misexpression of these transcription factors in pluripotent cells is sufficient to ectopically activate their targets. This study provides a rich resource for analyzing embryonic gene regulation and reveals the regulatory logic of instant differentiation.

An intracellular phosphorus-starvation signal activates the PhoB/PhoR two-component system in Salmonella enterica.

Bacteria acquire P primarily as inorganic orthophosphate (Pi, PO43-). Once internalized, Pi is rapidly assimilated into biomass during the synthesis of ATP. Because Pi is essential, but excessive ATP is toxic, the acquisition of environmental Pi is tightly regulated. In the bacterium Salmonella enterica (Salmonella), growth in Pi-limiting environments activates the membrane sensor histidine kinase PhoR, leading to the phosphorylation of its cognate transcriptional regulator PhoB and subsequent transcription of genes involved in adaptations to low Pi. Pi limitation promotes PhoR kinase activity by altering the conformation of a membrane signaling complex comprised of PhoR, the multicomponent Pi transporter system PstSACB and the regulatory protein PhoU. However, the identity of the Pi-starvation signal and how it controls PhoR activity remain unknown. Here, we identify conditions where the PhoB and PhoR signal transduction proteins can be maintained in an inactive state when Salmonella is grown in media lacking Pi. Our results demonstrate that PhoB/PhoR is activated by an intracellular P-insufficiency signal.IMPORTANCEIn enteric bacteria, the transcriptional response to phosphorus (P) starvation is controlled by a specialized signal transduction system comprised of a membrane-bound, multicomponent signal sensor, and a cytoplasmic transcriptional factor. Whereas this system has been primarily studied in the context of phosphate (Pi) starvation, it is currently unknown how this stress initiates signal transduction. In the current study, we establish that this signaling system is regulated by a cytoplasmic signal arising from insufficient P. We demonstrate that rather than responding to extracellular conditions, cells couple the activation of their P starvation response to the availability of cytoplasmic P. This regulatory logic may enable cells to prevent toxicity resulting from excessive Pi acquisition and hinder the onset of a P starvation response when their metabolic demands are being met through the consumption of P sources other than Pi.

Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome.

Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Pseudotime analysis of perturbations connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state.

Multiscale regulation of nutrient stress responses in Escherichia coli from chromatin structure to small regulatory RNAs.

Recent research has indicated the presence of heterochromatin-like regions of extended protein occupancy and transcriptional silencing of bacterial genomes. We utilized an integrative approach to track chromatin structure and transcription in E. coli K-12 across a wide range of nutrient conditions. In the process, we identified multiple loci which act similarly to facultative heterochromatin in eukaryotes, normally silenced but permitting expression of genes under specific conditions. We also found a strong enrichment of small regulatory RNAs (sRNAs) among the set of differentially expressed transcripts during nutrient stress. Using a newly developed bioinformatic pipeline, the transcription factors regulating sRNA expression were bioinformatically predicted, with experimental follow-up revealing novel relationships for 36 sRNA-transcription factors candidates. Direct regulation of sRNA expression was confirmed by mutational analysis for five sRNAs of metabolic interest: IsrB, CsrB and CsrC, GcvB, and GadY. Our integrative analysis thus reveals additional layers of complexity in the nutrient stress response in E. coli and provides a framework for revealing similar poorly understood regulatory logic in other organisms.

Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling.

Annotation of the cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to improving our understanding of tumor biology. Herein, we present a compendium of matched chromatin accessibility (scATAC-seq) and transcriptome (scRNA-seq) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell-of-origin for luminal breast tumors and basal breast tumors and then introduce a novel methodology that implements linear mixed-effects models to systematically quantify associations between regions of chromatin accessibility (i.e. regulatory elements) and gene expression in malignant cells versus normal mammary epithelial cells. These data unveil regulatory elements with that switch from silencers of gene expression in normal cells to enhancers of gene expression in cancer cells, leading to the upregulation of clinically relevant oncogenes. To translate the utility of this dataset into tractable models, we generated matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing, for each subtype, a conserved oncogenic gene expression program between in vitro and in vivo cells. Together, this work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of BC cells at single-cell resolution.

Circular single-stranded DNA as a programmable vector for gene regulation in cell-free protein expression systems

Cell-free protein expression (CFE) systems have emerged as a critical platform for synthetic biology research. The vectors for protein expression in CFE systems mainly rely on double-stranded DNA and single-stranded RNA for transcription and translation processing. Here, we introduce a programmable vector - circular single-stranded DNA (CssDNA), which is shown to be processed by DNA and RNA polymerases for gene expression in a yeast-based CFE system. CssDNA is already widely employed in DNA nanotechnology due to its addressability and programmability. To apply above methods in the context of synthetic biology, CssDNA can not only be engineered for gene regulation via the different pathways of sense CssDNA and antisense CssDNA, but also be constructed into several gene regulatory logic gates in CFE systems. Our findings advance the understanding of how CssDNA can be utilized in gene expression and gene regulation, and thus enrich the synthetic biology toolbox.

The Evolution Law of the Subject of Enterprise Compliance Management in China Conflicts with the Logic of Regulation

This paper aims to discuss the conflict between the evolution law of the enterprise compliance management subject and the regulation logic in China. By analyzing the background and demand of the evolution of compliance management subjects, the innovative compliance management concept is put forward, and the application of this concept in enterprise compliance management is introduced in detail. The results show that this concept has significant advantages in promoting the development of enterprise compliance management and solving the conflict of regulatory logic. The study of this paper is of great significance for the deep understanding and application of the evolution law of enterprise compliance management subjects in China.

A multi-omic single-cell landscape of cellular diversification in the developing human cerebral cortex

The vast neuronal diversity in the human neocortex is vital for high-order brain functions, necessitating elucidation of the regulatory mechanisms underlying such unparalleled diversity. However, recent studies have yet to comprehensively reveal the diversity of neurons and the molecular logic of neocortical origin in humans at single-cell resolution through profiling transcriptomic or epigenomic landscapes, owing to the application of unimodal data alone to depict exceedingly heterogeneous populations of neurons. In this study, we generated a comprehensive compendium of the developing human neocortex by simultaneously profiling gene expression and open chromatin from the same cell. We computationally reconstructed the differentiation trajectories of excitatory projection neurons of cortical origin and inferred the regulatory logic governing lineage bifurcation decisions for neuronal diversification. We demonstrated that neuronal diversity arises from progenitor cell lineage specificity and postmitotic differentiation at distinct stages. Our data paves the way for understanding the primarily coordinated regulatory logic for neuronal diversification in the neocortex.

A conserved molecular logic for neurogenesis to gliogenesis switch in the cerebral cortex

During development, neural stem cells in the cerebral cortex, also known as radial glial cells (RGCs), generate excitatory neurons, followed by production of cortical macroglia and inhibitory neurons that migrate to the olfactory bulb (OB). Understanding the mechanisms for this lineage switch is fundamental for unraveling how proper numbers of diverse neuronal and glial cell types are controlled. We and others recently showed that Sonic Hedgehog (Shh) signaling promotes the cortical RGC lineage switch to generate cortical oligodendrocytes and OB interneurons. During this process, cortical RGCs generate intermediate progenitor cells that express critical gliogenesis genes Ascl1, Egfr, and Olig2. The increased Ascl1 expression and appearance of Egfr+ and Olig2+ cortical progenitors are concurrent with the switch from excitatory neurogenesis to gliogenesis and OB interneuron neurogenesis in the cortex. While Shh signaling promotes Olig2 expression in the developing spinal cord, the exact mechanism for this transcriptional regulation is not known. Furthermore, the transcriptional regulation of Olig2 and Egfr has not been explored. Here, we show that in cortical progenitor cells, multiple regulatory programs, including Pax6 and Gli3, prevent precocious expression of Olig2, a gene essential for production of cortical oligodendrocytes and astrocytes. We identify multiple enhancers that control Olig2 expression in cortical progenitors and show that the mechanisms for regulating Olig2 expression are conserved between the mouse and human. Our study reveals evolutionarily conserved regulatory logic controlling the lineage switch of cortical neural stem cells.

A gray box framework that optimizes a white box logical model using a black box optimizer for simulating cellular responses to perturbations

Predicting cellular responses to perturbations requires interpretable insights into molecular regulatory dynamics to perform reliable cell fate control, despite the confounding non-linearity of the underlying interactions. There is a growing interest in developing machine learning-based perturbation response prediction models to handle the non-linearity of perturbation data, but their interpretation in terms of molecular regulatory dynamics remains a challenge. Alternatively, for meaningful biological interpretation, logical network models such as Boolean networks are widely used in systems biology to represent intracellular molecular regulation. However, determining the appropriate regulatory logic of large-scale networks remains an obstacle due to the high-dimensional and discontinuous search space. To tackle these challenges, we present a scalable derivative-free optimizer trained by meta-reinforcement learning for Boolean network models. The logical network model optimized by the trained optimizer successfully predicts anti-cancer drug responses of cancer cell lines, while simultaneously providing insight into their underlying molecular regulatory mechanisms.

Integration of single-cell transcriptomic and chromatin accessibility on heterogenicity of human peripheral blood mononuclear cells utilizing microwell-based single-cell partitioning technology

Abstract Single-cell RNA sequencing (scRNA-Seq) deepens our understanding of cellular development and heterogeneity. However, limitations exist in unraveling cell states and gene regulatory programs. Chromatin state profiles assess gene expression potential and offer insights into transcriptional regulation. Integrated with gene expression data, chromatin accessibility region (CAR) profiles establish fundamental gene regulatory logic for cell fate. ATAC-seq (Assay for Transposase-Accessible Chromatin using Sequencing) is a highly potent approach for profiling genome-wide CARs. To investigate the power of the multiomics assay in identifying differentiated gene regulations, we conducted multiomic snATAC-seq+ snRNA-seq on PBMCs from two different donors, by utilizing the gentle and robust microwell-based single-cell partitioning technology. The assay showed high sensitivity and specificity metrics (>10,000 median unique fragments/cell, >0.7 fragments in peak score). Integrative analysis across donors revealed enriched transcription factor motifs and fragment coverage tracks in distinct cell types, correlating significantly with gene expression data. These findings highlight mRNA's intricate connections with CARs in immune cell development. Our study underscores the power of multiomic analysis in analyzing heterogeneity of PBMC cell populations and offers a toolkit to identify gene regulation specific to diverse cell types, enhancing our comprehension of epigenetic diversity.

Xenopus tropicalis osteoblast-specific open chromatin regions reveal promoters and enhancers involved in human skeletal phenotypes and shed light on early vertebrate evolution

While understanding the genetic underpinnings of osteogenesis has far-reaching implications for skeletal diseases and evolution, a comprehensive characterization of the osteoblastic regulatory landscape in non-mammalian vertebrates is still lacking. Here, we compared the ATAC-Seq profile of Xenopus tropicalis (Xt) osteoblasts to a variety of non mineralizing control tissues, and identified osteoblast-specific nucleosome free regions (NFRs) at 527 promoters and 6747 distal regions. Sequence analyses, Gene Ontology, RNA-Seq and ChIP-Seq against four key histone marks confirmed that the distal regions correspond to bona fide osteogenic transcriptional enhancers exhibiting a shared regulatory logic with mammals. We report 425 regulatory regions conserved with human and globally associated to skeletogenic genes. Of these, 35 regions have been shown to impact human skeletal phenotypes by GWAS, including one trps1 enhancer and the runx2 promoter, two genes which are respectively involved in trichorhinophalangeal syndrome type I and cleidocranial dysplasia. Intriguingly, 60 osteoblastic NFRs also align to the genome of the elephant shark, a species lacking osteoblasts and bone tissue. To tackle this paradox, we chose to focus on dlx5 because its conserved promoter, known to integrate regulatory inputs during mammalian osteogenesis, harbours an osteoblast-specific NFR in both frog and human. Hence, we show that dlx5 is expressed in Xt and elephant shark odontoblasts, supporting a common cellular and genetic origin of bone and dentine. Taken together, our work (i) unravels the Xt osteogenic regulatory landscape, (ii) illustrates how cross-species comparisons harvest data relevant to human biology and (iii) reveals that a set of genes including bnc2, dlx5, ebf3, mir199a, nfia, runx2 and zfhx4 drove the development of a primitive form of mineralized skeletal tissue deep in the vertebrate lineage.

A logic-incorporated gene regulatory network deciphers principles in cell fate decisions.

Organisms utilize gene regulatory networks (GRN) to make fate decisions, but the regulatory mechanisms of transcription factors (TF) in GRNs are exceedingly intricate. A longstanding question in this field is how these tangled interactions synergistically contribute to decision-making procedures. To comprehensively understand the role of regulatory logic in cell fate decisions, we constructed a logic-incorporated GRN model and examined its behavior under two distinct driving forces (noise-driven and signal-driven). Under the noise-driven mode, we distilled the relationship among fate bias, regulatory logic, and noise profile. Under the signal-driven mode, we bridged regulatory logic and progression-accuracy trade-off, and uncovered distinctive trajectories of reprogramming influenced by logic motifs. In differentiation, we characterized a special logic-dependent priming stage by the solution landscape. Finally, we applied our findings to decipher three biological instances: hematopoiesis, embryogenesis, and trans-differentiation. Orthogonal to the classical analysis of expression profile, we harnessed noise patterns to construct the GRN corresponding to fate transition. Our work presents a generalizable framework for top-down fate-decision studies and a practical approach to the taxonomy of cell fate decisions.

A logic-incorporated gene regulatory network deciphers principles in cell fate decisions

Organisms utilize gene regulatory networks (GRN) to make fate decisions, but the regulatory mechanisms of transcription factors (TF) in GRNs are exceedingly intricate. A longstanding question in this field is how these tangled interactions synergistically contribute to decision-making procedures. To comprehensively understand the role of regulatory logic in cell fate decisions, we constructed a logic-incorporated GRN model and examined its behavior under two distinct driving forces (noise-driven and signal-driven). Under the noise-driven mode, we distilled the relationship among fate bias, regulatory logic, and noise profile. Under the signal-driven mode, we bridged regulatory logic and progression-accuracy trade-off, and uncovered distinctive trajectories of reprogramming influenced by logic motifs. In differentiation, we characterized a special logic-dependent priming stage by the solution landscape. Finally, we applied our findings to decipher three biological instances: hematopoiesis, embryogenesis, and trans-differentiation. Orthogonal to the classical analysis of expression profile, we harnessed noise patterns to construct the GRN corresponding to fate transition. Our work presents a generalizable framework for top-down fate-decision studies and a practical approach to the taxonomy of cell fate decisions.