Search bioRxiv⌕ Search

Biology subjects

Yang, C.-H.

Publications and source records attributed to Yang, C.-H..

At least 19 recordsLinked to original sources

Response to SMAC mimetics in patient-derived models of triple-negative breast cancer relies on RIPK1 activation

Triple-negative breast cancer (TNBC) is a highly metastatic and aggressive breast cancer subtype with limited targeted treatment options. Second mitochondrial activator of caspases (SMAC) mimetics represent a promising therapeutic class for TNBC patients, although they have yet to be approved clinically. Screening a repository of 69 breast cancer patient-derived xenograft organoid (PDxO) lines revealed that approximately 39% were sensitive to the SMAC mimetic birinapant. To define the basis of resistance in lines that did not respond, we compared birinapant-sensitive (S-) and de novo resistant (R-) TNBC PDxOs. Birinapant caused degradation of inhibitor of apoptosis proteins (IAPs) in both groups but failed to induce cell death in R-PDxOs. We determined that R-PDxOs were susceptible to certain types of apoptosis but were specifically resistant to TNFR-mediated cell death, an integral pathway involved in SMAC mimetic response. Moreover, RIPK1 activation via autophosphorylation, a critical event in TNFR-mediated apoptosis, was absent in both R-PDxOs and PDxOs selected for acquired birinapant resistance. Pharmacologic inhibition or degradation of RIPK1 protected S-PDxOs from birinapant-induced cell death, demonstrating that RIPK1 activation is required for response in TNBC. To investigate how to restore RIPK1 activation in R-PDxOs, we discovered that HOIP, an E3 ubiquitin ligase that inhibits RIPK1 autophosphorylation, was more abundant in R-PDxOs compared to S-PDxOs. Inhibiting HOIP activity restored RIPK1 autophosphorylation and sensitized a subset of R-PDxOs to birinapant. Together, these findings identify impaired RIPK1 autophosphorylation as a mechanism of birinapant resistance in TNBC and suggest that RIPK1 activation state may distinguish SMAC mimetic-sensitive and -resistant tumors. Targeting HOIP may provide a strategy to overcome resistance in selected tumors.

cancer biology↗

DS5: An Open-Source Framework for Standardized High-Throughput Drug Screening Data Storage, Analysis, and Drug Prioritization

Background. High-throughput drug screening (HTS) is increasingly used in precision oncology across cell lines, patient-derived models such as organoids (PDO) and xenograft organoids (PDxO), and ex vivo patient samples, with multiple active clinical trials incorporating HTS for individualizing treatment. Yet HTS efforts predominantly rely on ad hoc, spreadsheet-based workflows, with no standardized infrastructure for storing, analyzing, and comparing screens across patients, cohorts, or institutions, limiting reproducibility and slowing clinical data exchange. Existing tools address isolated pieces of the workflow, handling either data management or analysis and visualization, but none integrate standardized storage, reproducible dose-response analysis, individualized drug prioritization, and clinician and molecular tumor board friendly reporting in a single open-source framework. Results. We present DS5, an open-source Python framework that operates on an HDF5-based DS5 file format that unifies standardized storage, quality control, dose-response analysis, cohort-level drug prioritization, and automated reporting in a single lightweight package. DS5 enforces raw-data immutability, integrates RxNorm-based drug name standardization, and scales from small clinical cohorts to large pharmacogenomics datasets on a standard laptop. We validated DS5 against two public benchmarks spanning over 428,000 drug, cell line pairs, recovering published LN IC50 values from GDSC2 (Pearson r = 0.973) and Emax values from CTRP (r = 0.961). Using a published breast cancer PDxO dataset (45 compounds by 16 models), we reproduced GR-based profiles via a custom-metric extension and used DS5's cohort-level prioritization to predict in vivo tumor response with ROC AUC = 0.907 across 30 drug PDX pairs. Finally, we demonstrate the utilities of DS5 in an ongoing pediatric brain tumor precision oncology initiative, where its cohort-normalized drug rankings and automated reports directly support molecular tumor board discussions. Conclusion. DS5 provides the cancer basic and translational research community with a standardized file format and reproducible computational analysis methods to support functional drug screening experiments; and its reporting features facilitate bridging raw drug screening measurements to translational decisions. DS5 is released open-source under the permissible MIT license.

bioinformatics↗

Multi-kingdom microbial diversity and interaction landscapes in mosquitoes revealed by 5,163 individual meta-transcriptomes

Mosquitoes are pathogen vectors embedded within diverse microbial ecosystems. However, the nature and interactions among their multi-kingdom microbiome remain poorly understood. We conducted a nationwide single-mosquito meta-transcriptomic survey of 5,163 mosquitoes representing 100 species across China, integrating viral discovery with marker-gene profiling of bacteria, archaea, fungi, and other eukaryotic microbes. From this, we identified 1,606 microbial species-level taxa, including extensive novel diversity, and revealed pronounced host species-specific organization of mosquito-associated communities. We detected 34 pathogens or potential pathogens of human or animal relevance, whose prevalence, abundance, host range, and geographic distribution defined distinct epidemiological patterns. Network analysis uncovered pervasive cross-kingdom microbial associations, including candidate antiviral relationships involving Wolbachia and other microbial taxa. Our study establishes a detailed view of the full-spectrum microbiome and provides a resource and conceptual framework for studying vector competence, pathogen emergence, and microbiome-informed mosquito-borne disease control.

microbiology↗

Adaptive sampling-based enrichment enables genome reconstruction of intracellular symbionts despite host background and reference divergence

Recovering genomes of intracellular microbes from host-dominated samples remains a major challenge in microbial genomics, due to low target abundance, overwhelming host DNA, and the inability to culture these organisms independently. Despite extensive interest in Wolbachia, efficient genome recovery directly from host tissues remains limited by the inefficiency of host-dominated sequencing and the constraints of existing enrichment strategies. Here, we demonstrate that Oxford Nanopore adaptive sampling (AS) enables efficient, real-time enrichment of target DNA directly from complex host tissues, providing a culture-free approach for genome recovery in such systems. To our knowledge, this represents the first application of enrichment-mode adaptive sampling to achieve de novo reconstruction of an intracellular endosymbiont genome in a mosquito system. Using Aedes aegypti mosquitoes infected with a locally derived wAlbB-like strain, we applied enrichment-mode AS to selectively sequence Wolbachia DNA. This resulted in an increase from <1% Wolbachia reads in conventional shotgun data to [~]90% under adaptive sampling. De novo assembly of AS-enriched long reads yielded a near-complete genome ([~]1.5 Mb) in two contigs with >96-99% completeness. Comparative analyses revealed multiple large-scale chromosomal rearrangements relative to the reference wAlbB genome, demonstrating that adaptive sampling does not impose reference-dependent genome structure. Annotation further identified three prophage-associated regions, including two strain-specific expansions absent from the reference genome. Notably, cytoplasmic incompatibility genes (cifA and cifB) were identified adjacent to one of these regions, consistent with their known genomic association with prophage elements. Importantly, adaptive sampling remained effective despite substantial structural divergence between the reference and target genomes, revealing an unexpectedly robust application of this approach beyond its presumed operating conditions. Together, these results establish enrichment-mode adaptive sampling as a robust and scalable strategy for genome-resolved analysis of intracellular bacteria in host-associated systems.

genomics↗

HSPB8 regulates CTP synthase filaments to couple nucleotide metabolism and autophagy in tumors

Metabolic adaptation and proteostasis are essential for tumor survival under nutrient stress, yet how these processes are mechanistically integrated remains unclear. Here, we identify CTP synthase (CTPS) filament dynamics as a regulatory nexus linking nucleotide metabolism to autophagic flux. Under glutamine deprivation--a hallmark of poorly vascularized solid tumors--CTPS undergoes polymerization into filamentous assemblies that exhibit reduced enzymatic activity. We demonstrate that filament formation is driven by intracellular asparagine availability and stabilized by the accumulation of misfolded proteins. Using APEX2-based proximity labeling and proteomics, we identify the small heat shock protein HSPB8 as a filament-associated regulator. HSPB8, acting within the chaperone-assisted selective autophagy (CASA) pathway, antagonizes CTPS polymerization by promoting clearance of misfolded proteins, thereby restoring soluble, catalytically active CTPS. Filament disassembly increases CTP production and enhances synthesis of autophagy-related phospholipids, including phosphatidylinositol and phosphatidylethanolamine, resulting in accelerated autophagic flux. Cells expressing filament-deficient CTPS mutants display elevated autophagosome formation and increased LC3-II accumulation upon lysosomal blockade, confirming enhanced flux. In vivo, disruption of CTPS filament assembly impairs xenograft tumor growth and is associated with excessive autophagy. Analysis of TCGA datasets further reveals that high CTPS and low HSPB8 expression correlate with poor patient survival across multiple cancers. Collectively, our findings establish CTPS filament dynamics as a proteostasis-sensitive metabolic switch that coordinates nucleotide biosynthesis with autophagy, revealing a previously unrecognized vulnerability in tumors adapting to nutrient limitation.

cell biology↗

A precision oncology-focused deep learning framework for personalized selection of cancer therapy

Precision oncology matches tumors to targeted therapies based on the presence of actionable molecular alterations. However, most tumors lack actionable alterations, restricting treatment options to cytotoxic chemotherapies for which few data-driven prioritization strategies currently exist. Here, we report an integrated computational/experimental treatment selection approach applicable for both chemotherapies and targeted agents irrespective of actionable alterations. We generated functional drug response data on a large collection of patient-derived tumor models and used it to train ScreenDL, a novel deep learning-based cancer drug response prediction model. ScreenDL leverages the combination of tumor omic and functional drug screening data to predict the most efficacious treatments. We show that ScreenDL accurately predicts response to drugs with diverse mechanisms, outperforming existing methods and approved biomarkers. In our preclinical study, this approach achieved superior clinical benefit and objective response rates in breast cancer patient-derived xenografts, suggesting that testing ScreenDL in clinical trials may be warranted.

cancer biology↗

Spatial learning in feature-impoverished environments in Drosophila

The ability to return to memorized goal locations is essential for animal survival. While it is well documented that animals use visual landmarks to locate goals1,2, how they navigate spatial learning tasks in environments lacking such landmarks remains poorly understood. Here, using a high-throughput spatial learning task we developed to investigate this question in Drosophila, we found that Drosophila can simultaneously use self-generated olfactory cues and self-motion cues to learn a spatial goal under visually challenging conditions. Specifically, flies mark a rewarded goal location with self-deposited scents, to which they assign a positive value, and use these scents and their self-motion cues to guide them back to the goal. This learning process is mediated by the mushroom body (MB) - an olfactory learning center responsible for associating odors with reinforcement3 - and by PFN neurons, which encode egocentric translational velocity4,5, a self-motion cue. Intriguingly, when the environment is enriched with prominent external olfactory landmarks, flies shift to prioritizing landmarks over self-generated cues - a strategy adjustment reflected in both the critical circuit involved and an altered transcriptome in the brain. Our findings demonstrate that Drosophila can dynamically adapt to environmental complexities when solving spatial learning tasks by creating and integrating internal and external cues, revealing an unexpected level of sophistication in their cognitive capacities.

neuroscience↗

Zebrafish Foxl2l functions in proliferating germ cells for female meiotic entry

AbstractZebrafish sex differentiation is a complicated process and the detailed mechanism has not been fully understood. Here we characterized a transcription factor, Foxl2l, that participates in female oogenesis. We show that it is expressed specifically in proliferating germ cells in juvenile gonads and mature ovaries. We have used CRISPR-Cas9 to generate zebrafish deficient in foxl2l expression. Zebrafish with foxl2l-/- are all males, and this female-to-male sex reversal cannot be reversed by tp53 mutation, indicating this sex reversal is unrelated to cell death. We have generated transgenic fish expressing GFP under the control of foxl2l promoter to track the development of foxl2l+-germ cells, which failed to enter meiosis and were accumulated as cystic cells. Our RNA-seq analysis also showed the reduced expression of genes in meiosis and oogenesis among other affected pathways. All together, we show that zebrafish Foxl2l is a nuclear factor controlling the expression of meiotic and oogenic genes, and its deficiency leads to defective meiotic entry and the accumulation of premeiotic germ cells. HighlightsO_LIZebrafish foxl2l is expressed only in proliferating germ cells in juvenile gonads and mature ovaries. C_LIO_LIFoxl2l is a nuclear factor that promotes expression of genes involved in meiosis and oogenesis. C_LIO_LIZebrafish depleted of foxl2l lack meiotic oocytes in juveniles and become all males in adults. C_LIO_LIMutation of foxl2l leads to the accumulation of premeiotic germ cells. C_LI

developmental biology↗

Unraveling the immunological roles of serum amyloid A3 in aortic immune cell subsets during atherosclerosis progression

Atherosclerosis is a growing concern in developed nations, necessitating the identification of therapeutic targets for advancing personalized medicine. Serum amyloid A3 (Saa3) has been linked to accelerated plaque progression by affecting cholesterol metabolism and modulation of inflammation. We hypothesize that knocking out Saa3 (Saa3-/-) could mitigate plaque development by regulating aortic immune cell compositions during atherosclerosis progression. Using a murine model, we induced atherosclerosis via a gain-of-function mutant PCSK9-encoding adeno-associated viral vector (AAVmPCSK9) in female wild-type (WT) and Saa3-/- mice. Saa3-/- mice developed smaller plaques than WT mice, and single-cell RNA sequencing revealed significant differences in aortic immune cell populations, particularly among aortic macrophages. Aortic macrophages in atherosclerotic Saa3-/-mice represent an anti-inflammatory and tissue-repairing phenotype and the Trem2hi macrophages, characterized by high Gpnmb, Lpl, and Spp1 expressions, predominated over the typical foamy macrophages in Saa3-/- compared to WT mice. Notably, SAA3 regulates cholesterol metabolism and inflammatory responses in foamy macrophages. Our study highlights Saa3 as a key modulator of aortic immune cells that impact atherosclerosis progression.

immunology↗

Massively Parallel Polyribosome Profiling Reveals Translation Defects of Human Disease-Relevant UTR Mutations

The untranslated regions (UTRs) of mRNAs harbor regulatory elements influencing translation efficiency. Although 3.7% of disease-relevant human mutations occur in UTRs, their exact role in pathogenesis remains unclear. Through metagene analysis, we mapped pathogenic UTR mutations to regions near coding sequences, with a focus on the upstream open reading frame (uORF) initiation site. Subsequently, we utilized massively parallel poly(ribo)some profiling to compare the ribosome associations of 6,555 pairs of wildtype and mutant UTR fragments. We identified 46 UTR variants that altered polysome profiles, with enrichment in pathogenic mutations. Both univariate analysis and the elastic net regression model highlighted the significance of motifs of short repeated sequences, including SRSF2 binding sites, as mutation hotspots that lead to aberrant translation. Furthermore, these polysome-shifting mutations exhibited considerable impact on RNA secondary structures, particularly for upstream AUG-containing 5 UTRs. Integrating these features, our model achieved high accuracy (AUROC > 0.8) in predicting polysome-shifting mutations in the test dataset. Additionally, several lines of evidence indicate that changes in uORF usage underlie the translation deficiency arising from these mutations. Illustrating this, we demonstrate that a pathogenic mutation in the IRF6 5 UTR suppresses translation of the primary open reading frame by creating a uORF. Remarkably, site- directed ADAR editing of the mutant mRNA rescued this translation deficiency. Overall, our study provides insights into the molecular mechanisms of UTR mutations and their links to clinical impacts through translation defects. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=187 SRC="FIGDIR/small/589132v2_ufig1.gif" ALT="Figure 1000"> View larger version (50K): org.highwire.dtl.DTLVardef@57217corg.highwire.dtl.DTLVardef@575410org.highwire.dtl.DTLVardef@15013bforg.highwire.dtl.DTLVardef@408840_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

A single cell atlas of the mouse seminal vesicle

During mammalian reproduction, sperm are delivered to the female reproductive tract bathed in a complex medium known as seminal fluid, which plays key roles in signaling to the female reproductive tract and in nourishing sperm for their onwards journey. Along with minor contributions from the prostate and the epididymis, the majority of seminal fluid is produced by a somewhat understudied organ known as the seminal vesicle. Here, we report the first single-cell RNA-seq atlas of the mouse seminal vesicle, generated using tissues obtained from 23 mice of varying ages, exposed to a range of dietary challenges. We define the transcriptome of the secretory cells in this tissue, identifying a relatively homogeneous population of the epithelial cells which are responsible for producing the majority of seminal fluid. We also define the immune cell populations - including large populations of macrophages, dendritic cells, T cells, and NKT cells - which have the potential to play roles in producing various immune mediators present in seminal plasma. Together, our data provide a resource for understanding the composition of an understudied reproductive tissue with potential implications for paternal control of offspring development and metabolism.

genomics↗

Multiplexed Assays of Human Disease-relevant Mutations Reveal UTR Dinucleotide Composition as a Major Determinant of RNA Stability

UTRs contain crucial regulatory elements for RNA stability, translation and localization, so their integrity is indispensable for gene expression. Approximately 3.7% of genetic variants associated with diseases occur in UTRs, yet a comprehensive understanding of UTR variant functions remains limited due to inefficient experimental and computational assessment methods. To systematically evaluate the effects of UTR variants on RNA stability, we established a massively parallel reporter assay on 6,555 UTR variants reported in human disease databases. We examined the RNA degradation patterns mediated by the UTR library in two cell lines, and then applied LASSO regression to model the influential regulators of RNA stability. We found that UA dinucleotides and UA-rich motifs are the most prominent destabilizing element. Gain of UA dinucleotide outlined mutant UTRs with reduced stability. Studies on endogenous transcripts indicate that high UA-dinucleotide ratios in UTRs promote RNA degradation. Conversely, elevated GC content and protein binding on UA dinucleotides protect high-UA RNA from degradation. Further analysis reveals polarized roles of UA- dinucleotide-binding proteins in RNA protection and degradation. Furthermore, the UA- dinucleotide ratio of both UTRs is a common characteristic of genes in innate immune response pathways, implying a coordinated stability regulation through UTRs at the transcriptomic level. We also demonstrate that stability-altering UTRs are associated with changes in biobank-based health indices, underscoring the importance of precise UTR regulation for wellness. Our study highlights the importance of RNA stability regulation through UTR primary sequences, paving the way for further exploration of their implications in gene networks and precision medicine.

genetics↗

Zebrafish Foxl2l suppresses stemness and directs feminization of germline progenitors

Zebrafish is an important organism for genetic studies, but its germ cell types and the mechanism of sex differentiation remain elusive. Here, we conducted a single-cell transcriptomic profiling and charted a developmental trajectory going from germline stem cells, through early, committed, and late progenitors, to pre-meiotic and meiotic cells. A transcription factor, Foxl2l, is expressed in the progenitors committed to the ovary fate. CRISPR-Cas9-mediated mutation of foxl2l produced 100% male fish with normal fertility. Another single-cell profiling of foxl2l-/- germ cells reveals the arrest of early progenitors. Concomitantly the expression of nanos2 (stem cell marker) and id1 (transcription repressor in stem cells) was elevated together with an increase of nanos2+ germ cell in foxl2l mutants, indicating the reversion to the stem cell state. Thus, we have identified developmental stages of germ cells in juvenile zebrafish and demonstrated that Foxl2l drives zebrafish germ cell progenitors toward feminization and prevents them from reverting back to the stem cell state.

developmental biology↗

Cross-institutional HER2 assessment via a computer-aided system using federated learning and stain composition augmentation

The rapid advancement of precision medicine and personalized healthcare has heightened the demand for accurate diagnostic tests. These tests are crucial for administering novel treatments like targeted therapy. To ensure the widespread availability of accurate diagnostics with consistent standards, the integration of computer-aided systems has become essential. Specifically, computer-aided systems that assess biomarker expression have thrusted through the widespread application of deep learning for medical imaging. However, the generalizability of deep learning models has usually diminished significantly when being confronted with data collected from different sources, especially for histological imaging in digital pathology. It has therefore been challenging to effectively develop and employ a computer-aided system across multiple medical institutions. In this study, a biomarker computer-aided framework was proposed to overcome such challenges. This framework incorporated a new approach to augment the composition of histological staining, which enhanced the performance of federated learning models. A HER2 assessment system was developed following the proposed framework, and it was evaluated on a clinical dataset from National Taiwan University Hospital and a public dataset coordinated by the University of Warwick. This assessment system showed an accuracy exceeding 90% for both institutions, whose generalizability outperformed a baseline system developed solely through the clinical dataset by 30%. Compared to previous works where data across different institutions were mixed during model training, the HER2 assessment system achieved a similar performance while it was developed with guaranteed patient privacy via federated learning.

pathology↗

Developmental priming of cancer susceptibility

DNA mutations are necessary drivers of cancer, yet only a small subset of mutated cells go on to cause the disease. To date, the mechanisms that determine which rare subset of cells transform and initiate tumorigenesis remain unclear. Here, we take advantage of a unique model of intrinsic developmental heterogeneity (Trim28+/D9) and demonstrate that stochastic early life epigenetic variation can trigger distinct cancer-susceptibility states in adulthood. We show that these developmentally primed states are characterized by differential methylation patterns at typically silenced heterochromatin, and that these epigenetic signatures are detectable as early as 10 days of age. The differentially methylated loci are enriched for genes with known oncogenic potential. These same genes are frequently mutated in human cancers, and their dysregulation correlates with poor prognosis. These results provide proof-of-concept that intrinsic developmental heterogeneity can prime individual, life-long cancer risk.

cancer biology↗

Revisiting chromatin packaging in mouse sperm

Mammalian sperm exhibit an unusual and heavily-compacted genomic packaging state. In addition to its role in organizing the compact and hydrodynamic sperm head, it has been proposed that sperm chromatin architecture helps to program gene expression in the early embryo. Scores of genome-wide surveys in sperm have reported patterns of chromatin accessibility, histone localization, histone modification, and chromosome folding. Here, we revisit these studies in light of recent reports that sperm obtained from the mouse epididymis are contaminated with low levels of cell-free chromatin. In the absence of proper sperm lysis we readily recapitulate multiple prominent genome-wide surveys of sperm chromatin, suggesting that these profiles primarily reflect contaminating cell-free chromatin. Removal of cell-free DNA, along with appropriate lysis conditions, are required to reveal a sperm chromatin state distinct from most previous reports. Using ATAC-Seq to explore relatively accessible genomic loci, we identify a landscape of open loci associated with early development and transcriptional control. Histone modification and chromosome folding studies also strongly support the hypothesis that prior studies suffer from contamination, but technical challenges associated with reliably preserving the architecture of the compacted sperm head prevent us from confidently assaying true localization patterns for these epigenetic marks. Together, our studies strongly argue that our knowledge of mammalian chromosome packaging remains largely incomplete, and motivate future efforts to more accurately characterize genome organization in mature sperm.

molecular biology↗

Characterization of a novel estrogen- and progesterone-responsive endometrial cancer cell line: HCI-EC-23

Most endometrial cancers express the hormone receptor estrogen receptor alpha (ER) and are driven by excess estrogen signaling. However, evaluation of the estrogen response in endometrial cancer cells has been limited by the availability of hormonally responsive in vitro models, with one cell line, Ishikawa, being used in most studies. Here, we describe a novel, adherent endometrioid endometrial cancer (EEC) cell line model, HCI-EC-23. We show that HCI-EC-23 retains ER expression and that ER functionally responds to estrogen induction over a range of passages. We also demonstrate that this cell line retains paradoxical activation of ER by tamoxifen, which is also observed in Ishikawa and is consistent with clinical data. The mutational landscape shows that HCI-EC-23 is mutated at many of the commonly altered genes in EEC, has relatively few copy-number alterations, and is microsatellite instable high (MSI-high). In vitro proliferation of HCI-EC-23 is strongly reduced upon combination estrogen and progesterone treatment. HCI-EC-23 exhibits strong estrogen dependence for tumor growth in vivo and tumor size is reduced by combination estrogen and progesterone treatment. Molecular characterization of estrogen induction in HCI-EC-23 revealed hundreds of estrogen-responsive genes that significantly overlapped with those regulated in Ishikawa. Analysis of ER genome binding identified similar patterns in HCI-EC-23 and Ishikawa, although ER exhibited more bound sites in Ishikawa. This study demonstrates that HCI-EC-23 is an estrogen- and progesterone-responsive cell line model that can be used to study the hormonal aspects of endometrial cancer.

cancer biology↗

A family of fitness landscapes modeled through gene regulatory networks

Over 100 years, Fitness landscapes have been a powerful metaphor for understanding the evolution of biological systems. These landscapes describe how genotypes are connected to each other and are related according to relative fitness. Despite the high dimensionality of such real-world landscapes, empirical studies are often limited in their ability to quantify the fitness of different genotypes beyond point mutations, while theoretical works attempt statistical/mechanistic models to reason the overall landscape structure. However, most classical fitness landscape models overlook an instinctive constraint that genotypes leading to the same phenotype almost certainly share the same fitness value, since the information of genotype-phenotype mapping is rarely incorporated. Here, we investigate fitness landscape models through the lens of Gene Regulatory Networks (GRNs), where the regulatory products are computed from multiple genes and collectively treated as the phenotypes. With the assumption that regulatory mediators/products exhibit binary states, we prove topographical features of GRN fitness landscape models such as accessibility and connectivity insensitive to the choice of the fitness function. Furthermore, using graph theory, we deduce a mesoscopic structure underlying GRN fitness landscape models that retains necessary information for evolutionary dynamics with minimal complexity. We also propose an algorithm to construct such a mesoscopic backbone which is more efficient than the brute-force approach. Combined, this work provides mathematical implications for fitness landscape models with high-dimensional genotype-phenotype mapping, yielding the potential to elucidate empirical landscapes and their resulting evolutionary processes in a manner complementary to existing computational studies.

evolutionary biology↗