Biology subjects

Gao, Y.

Publications and source records attributed to Gao, Y..

At least 289 records · Page 16Linked to original sources

bioRxiv2024

A Lung Cancer Mouse Model Database

Lung cancer, the leading cause of cancer mortality, exhibits diverse histological subtypes and genetic complexities. Numerous preclinical mouse models have been developed to study lung cancer, but data from these models are disparate, siloed, and difficult to compare in a centralized fashion. Here we established the Lung Cancer Mouse Model Database (LCMMDB), an extensive repository of 1,354 samples from 77 transcriptomic datasets covering 974 samples from genetically engineered mouse models (GEMMs), 368 samples from carcinogen-induced models, and 12 samples from a spontaneous model. Meticulous curation and collaboration with data depositors have produced a robust and comprehensive database, enhancing the fidelity of the genetic landscape it depicts. The LCMMDB aligns 859 tumors from GEMMs with human lung cancer mutations, enabling comparative analysis and revealing a pressing need to broaden the diversity of genetic aberrations modeled in GEMMs. Accompanying this resource, we developed a web application that offers researchers intuitive tools for in-depth gene expression analysis. With standardized reprocessing of gene expression data, the LCMMDB serves as a powerful platform for cross-study comparison and lays the groundwork for future research, aiming to bridge the gap between mouse models and human lung cancer for improved translational relevance.

cancer biology↗

bioRxiv2024

Proteomic Analysis of Urine from Youths Indulging in Gaming

Video game addiction manifests as an escalating enthusiasm and uncontrolled use of digital games, yet there are no objective indicators for gaming addiction. This study employed mass spectrometry proteomics to analyze the proteomic differences in the urine of adolescents addicted to gaming compared to those who do not play video games. The study included 10 adolescents addicted to gaming and 9 non-gaming adolescents as a control group. The results showed that there were 125 significantly different proteins between the two groups. Among these, 11 proteins have been reported to change in the body after the intake of psychotropic drugs and are associated with addiction: Calmodulin, ATP synthase subunit alpha, ATP synthase subunit beta, Acid ceramidase, Tomoregulin-2, Calcitonin, Apolipoprotein E, Glyceraldehyde-3-phosphate dehydrogenase, Heat shock protein beta-1, CD63 antigen, Ephrin type-B receptor 4, Tomoregulin-2. Additionally, several proteins were found to interact with pathways related to addiction: Dickkopf-related protein 3, Nicastrin, Leucine-rich repeat neuronal protein 4, Cerebellin-4. Enriched biological pathways discovered include those related to nitric oxide synthase, amphetamine addiction, and numerous calcium ion pathways, all of which are associated with addiction. Moreover, through the analysis of differentially expressed proteins, we speculated about some proteins not yet fully studied, which might play a significant role in the mechanisms of addiction: Protein kinase C and casein kinase substrate in neurons protein, Cysteine-rich motor neuron 1 protein, Bone morphogenetic protein receptor type-2, Immunoglobulin superfamily member 8. In the analysis of urinary proteins in adolescents addicted to online gaming, we identified several proteins that have previously been reported in studies of drug addiction.

molecular biology↗

bioRxiv2024

Establishment of an Inhalation Administration Noninvasive Murine Model for Rapidly Testing Drug Activity against Mycobacterium tuberculosis

The efficacy of many compounds against Mycobacterium tuberculosis is often limited when administered via conventional oral or injection routes due to suboptimal pharmacokinetic characteristics. Inhalation delivery methods have been investigated to achieve high local therapeutic doses in the lungs. However, previous models, typically employing wild-type M. tuberculosis strains, were intricate, time-consuming, labor-intensive, and with poor repeatability. In this study, we developed an autoluminescence-based inhalation administration model to evaluate drug activity by quantifying relative light units (RLUs) emitted from live mice infected with autoluminescent M. tuberculosis. This novel approach has several improvements: it eliminates the need for anesthesia in mice during administration and simplifies the instrument manipulation; it is cost-effective by utilizing mice instead of larger animals; it shortens time from several months to 16 or 17 days for obtaining result; it is non-invasive by measuring the live RLUs of mice; up to six mice can be administrated daily and simultaneously, even 2-3 times/day; results are relatively objective and repeatable minimizing human factors. Proof-of-concept experiments demonstrated that inhalable rifampicin, isoniazid, and ethambutol showed anti-M. tuberculosis activity at concentrations as low as 0.5, 0.5, and 0.625 mg/mL, respectively, as evidenced by comparing the live RLUs of mice. Furthermore, consistency between RLUs and colony-forming units of the lungs reaffirms the reliability of RLUs as an indicator of drug efficacy, highlighting the potential of this approach for accurately assessing anti-M. tuberculosis activity in vivo. This autoluminescence-based and non-invasive inhalation model offers a substantial reduction in the time, effort, and cost required for evaluating the efficacy of screening new drugs and repurposing old drugs in vivo via inhalation administration.

microbiology↗

bioRxiv2024

Ilamycins are dual inhibitors of ClpX and ClpC1 involved in proteostasis in Mycobacteria

The mycobacterial caseinolytic protease (Clp) system has been recognized as a promising therapeutic target. In this study, we identified two novel ilamycin analogs, ilamycin E (ILE) and ilamycin F (ILF), both targeting the ClpC1 component of the ClpC1P1P2 proteasome. ILE potently disrupts ClpC1P1P2-mediated proteolysis, leading to delayed bactericidal activity, while ILF also binds ClpC1, albeit with lower affinity. Notably, we discovered a unique mutation in clpX and a novel insertion in clpC1, both conferring resistance to ILE and ILF in mycobacterium, validated by gene editing. Furthermore, ILE can also inhibit the proteolytic activity of ClpXP1P2 in a manner dependent on the substrates tag sequence and adaptor. This first demonstration of clpX- and clpC1-mediated ilamycin resistance underscores the potential of ilamycins to target multiple components of the Clp protease system, offering a novel dual-target strategy for combating mycobacterial infections.

microbiology↗

bioRxiv2024

EmbB and EmbC Regulate the Sensitivity of Mycobacterium abscessus to Echinomycin

Treatment of Mycobacterium abscessus (Mab) infection is a major challenge due to its intrinsic resistance to most available drugs. It is thus imperative to find new anti-Mab drugs. In this study, we investigated the activity and intrinsic resistance mechanism of echinomycin (ECH) against Mab. ECH is active against Mab (MIC: 2 {micro}g/mL). The embC gene knockout strain (Mab{Delta}embC) showed hyper-sensitive to ECH (MIC: 0.0078-0.0156 {micro}g/mL). The MICs of ECH-resistant strains screened based on the Mab{Delta}embC strain were 0.25-1 {micro}g/mL. Mutations were found in the EmbB, including Asp306Ala, Asp306Asn, Arg350Gly, Val555Ile, and Gly581Ser, which led to increased resistance to ECH when overexpressed in Mab{Delta}embC individually (0.25-0.5 {micro}g/mL). The EmbB mutants edited by the CRISPR/Cpf1 system became more resistant to ECH (MIC: 0.25-0.5 {micro}g/mL). The permeability of gene-edited and overexpressed Mab strains was reduced, as shown by the ethidium bromide accumulation assay, but it was still significantly higher than that of the parent Mab. To summarize, our study demonstrates that ECH has a strong anti-Mab activity and confirms that EmbB and EmbC are related to the sensitivity of Mab to ECH. EmbB mutation may partially compensate for the function of EmbC. Impact StatementMycobacterium abscessus (Mab) is a rapidly growing, intrinsic multidrug-resistant Mycobacterium. This study demonstrated that echinomycin (ECH) has potent antibacterial activity against Mab, and the mechanism of ECH resistance to Mab is related to EmbB and EmbC. EmbB and EmbC can alter the sensitivity of Mab to ECH by altering the permeability of its cell wall. In addition, there is a functional complementary evolution between EmbB and EmbC to regulate sensitivity to ECH. Overall, our study provides a novel anti-Mab drug candidate ECH and a scientific foundation for developing effective strategies to prevent and control Mab.

microbiology↗

bioRxiv2024

Laboratory evolution reveals transcriptional mechanisms underlying thermal adaptation of Escherichia coli

Adaptive laboratory evolution (ALE) is able to generate microbial strains which exhibit extreme phenotypes, revealing fundamental biological adaptation mechanisms. Here, we use ALE to evolve Escherichia coli strains that grow at temperatures as high as 45.3{degrees}C, a temperature lethal to wild type cells. The strains adopted a hypermutator phenotype and employed multiple systems-level adaptations that made global analysis of the DNA mutations difficult. Given the challenge at the genomic level, we were motivated to uncover high temperature tolerance adaptation mechanisms at the transcriptomic level. We employed independently modulated gene set (iModulon) analysis to reveal five transcriptional mechanisms underlying growth at high temperatures. These mechanisms were connected to acquired mutations, changes in transcriptome composition, sensory inputs, phenotypes, and protein structures. They are: (i) downregulation of general stress responses while upregulating the specific heat stress responses; (ii) upregulation of flagellar basal bodies without upregulating motility, and upregulation fimbriae; (iii) shift toward anaerobic metabolism, (iv) shift in regulation of iron uptake away from siderophore production, and (v) upregulation of yjfIJKL, a novel heat tolerance operon which we characterized using AlphaFold. iModulons associated with these five mechanisms explain nearly half of all variance in the gene expression in the adapted strains. These thermotolerance strategies reveal that optimal coordination of known stress responses and metabolism can be achieved with a small number of regulatory mutations, and may suggest a new role for large protein export systems. ALE with transcriptomic characterization is a productive approach for elucidating and interpreting adaptation to otherwise lethal stresses.

systems biology↗

bioRxiv2024

Characterization of the SARS-CoV-2 BA.5 Variants in H11-K18-hACE2 Hamsters

This study aims to comprehensively characterize the SARS-CoV-2 BA.5 variants using K18 hACE2 transgenic mice and golden hamsters as model organisms. Previous research on SARS-CoV-2 has utilized both mouse and hamster models, leading to conflicting results concerning the viruss lethality. In our study, the finding suggests that H11-K18 hACE2 golden hamsters closely mimic the disease progression observed in human COVID-19 cases caused by BA.5 variants, demonstrating consistent severity and symptoms comparable to severe infections. Additionally, hamsters exhibit heightened respiratory viral replication, accurately reflecting the clinical viral kinetics observed in humans. The study emphasizes the critical importance of selecting an appropriate animal model for SARS-CoV-2 research, while also providing robust support for the hypothesis that BA.5 variants contribute to fatal outcomes in COVID-19 cases. These findings highlight the pivotal role of the golden hamster model in advancing our understanding of the pathogenic mechanisms underlying SARS-CoV-2 variants, as well as in the development of targeted therapeutic strategies. Significance StatementOur research work explores groundbreaking insights that could reshape our understanding of COVID-19 and pave the way for targeted therapies. We use golden hamster models to express the possibility of different animal models could contribute to human diseases. We hope this finding could clarify some conflicts existed, and help further development of medication for COVID.

immunology↗

bioRxiv2024

Regulatory divergences in dosage compensation cause hybrid male inviability in Caenorhabditis

The genetic basis of Haldanes rule, such as hybrid male incompatibility in XX systems, has long remained elusive. Here, we found that crosses of Caenorhabditis nigoni males with C. briggsae females result in insufficient expression of Cbr-xol-1, an X-linked master switch responsible for sex determination, consequently activating aberrant dosage compensation in males, and ultimately leading to embryonic inviability. Three compensatory divergences result in comparable xol-1 expression levels between the parental species but lethal Cbr-xol-1 underexpression in hybrid male embryos: 1) a less active Cbr-xol-1 promoter than its C. nigoni ortholog; 2) loss of an X-linked xol-1 paralog in C. briggsae; and 3) pseudogenization of a C. briggsae autosomal repressor of xol-1. Our results define an evolutionary scenario of sexual incompatibility leading to hybrid male inviability.

evolutionary biology↗

bioRxiv2024

Spatially Exploring RNA Biology in Archival Formalin-Fixed Paraffin-Embedded Tissues

Spatial transcriptomics has emerged as a powerful tool for dissecting spatial cellular heterogeneity but as of today is largely limited to gene expression analysis. Yet, the life of RNA molecules is multifaceted and dynamic, requiring spatial profiling of different RNA species throughout the life cycle to delve into the intricate RNA biology in complex tissues. Human disease-relevant tissues are commonly preserved as formalin-fixed and paraffin-embedded (FFPE) blocks, representing an important resource for human tissue specimens. The capability to spatially explore RNA biology in FFPE tissues holds transformative potential for human biology research and clinical histopathology. Here, we present Patho-DBiT combining in situ polyadenylation and deterministic barcoding for spatial full coverage transcriptome sequencing, tailored for probing the diverse landscape of RNA species even in clinically archived FFPE samples. It permits spatial co-profiling of gene expression and RNA processing, unveiling region-specific splicing isoforms, and high-sensitivity transcriptomic mapping of clinical tumor FFPE tissues stored for five years. Furthermore, genome-wide single nucleotide RNA variants can be captured to distinguish different malignant clones from non-malignant cells in human lymphomas. Patho-DBiT also maps microRNA-mRNA regulatory networks and RNA splicing dynamics, decoding their roles in spatial tumorigenesis trajectory. High resolution Patho-DBiT at the cellular level reveals a spatial neighborhood and traces the spatiotemporal kinetics driving tumor progression. Patho-DBiT stands poised as a valuable platform to unravel rich RNA biology in FFPE tissues to study human tissue biology and aid in clinical pathology evaluation.

systems biology↗

bioRxiv2024

Protein property prediction based on local environment by 3D equivariant convolutional neural networks

Predicting the properties of proteins is an important procedure in protein engineering. It determines the subspace of mutations for protein modifications, which is critical to the success of the project, but heavily relies on the knowledge and experience of scientists. In this study, we propose a novel deep 3D-CNN model, Eq3DCNN, specifically designed for local environment-related tasks in protein engineering. Eq3DCNN uses basic atom descriptors and their coordinates as inputs, utilizing customized data augmentations to enhance its training efficiency. To make the Eq3DCNN extracted features with more generalization capability, we incorporated a rotation equivariant module to get rotation invariant features. Using cross-validations with different data splitting strategies and under the scenarios of zero-shot predictions, we demonstrate that Eq3DCNN outperformed other 3D-CNN models in stability predictions, and also well-preformed on other prediction tasks, such as the binding pocket and the secondary structure predictions. Our results also identified the key factors that contribute to the models accuracy and the scope of its applications. These findings may help scientists in designing better mutation experiments and increasing the success rate in protein engineering.

bioinformatics↗

bioRxiv2024

The Origin and Evolution of Orphan Genes: A Case Study in Tea Plant Family

Orphan genes and transcription factor genes (TFs) are pervasive across genomes, play pivotal roles as regulators in a myriad of biological processes. Despite their ubiquity, the evolutionary trajectories and functional divergence of these genes remain largely unexplored. Theaceae family, encompassing the economically and culturally significant tea plant, presents a unique opportunity to study these dynamics. Here, we decoded a nearly complete, chromosome-scale reference genome of Stewartia gemmata spanning 2.95 Gb. This study is enhanced by integrating the genome of S. gemmata, an early-diverging species within Theaceae, crucial for phylogenomic analyses and understanding the functional dynamics of orphan genes in this family. Our analysis confirmed the absence of a recent specific whole-genome duplication (WGD) event, with tandem duplications emerging as the predominant mechanism for gene duplication at ancestral nodes within Theaceae. By conducting an extensive comparative genomics analysis across 13 Theaceae and comparing these with a wide array of eukaryotic and prokaryotic proteins, we identified 37,618 orphan genes and 25,884 TFs in Theaceae. Interestingly, some orphan genes appear to have ancient origins in tea plant ancestors, suggesting relatively early origins with frequent gains and losses, conversely, many others seem more specific and recent. Notably, the orphan genes are characterized by shorter lengths, fewer exons and functional domains than TFs, implying relatively simpler functional roles. These orphan genes demonstrate diverse cellular localization and functions as predicted by GO/KEGG analysis, and are implicated in environmental response and flavor formation in tea plants. This study not only sheds light on the distinct evolutionary histories and functional divergences between orphan genes and TFs in Theaceae, but also contributes to our understanding of the genetic complexity and adaptability of this economically and culturally valuable plant family. Short summary: The nearly complete genome of an early-diverging species Stewartia gemmata and phylogenomic studies provide insights into new gene evolution in Theaceae.

bioinformatics↗

bioRxiv2024

Forseti: A mechanistic and predictive model of the splicing status of scRNA-seq reads

MotivationShort-read single-cell RNA-sequencing (scRNA-seq) has been used to study cellular heterogeneity, cellular fate, and transcriptional dynamics. Modeling splicing dynamics in scRNA-seq data is challenging, with inherent difficulty in even the seemingly straightforward task of elucidating the splicing status of the molecules from which sequenced fragments are drawn. This difficulty arises, in part, from the limited read length and positional biases, which substantially reduce the specificity of the sequenced fragments. As a result, the splicing status of many reads in scRNA-seq is ambiguous because of a lack of definitive evidence. We are therefore in need of methods that can recover the splicing status of ambiguous reads which, in turn, can lead to more accuracy and confidence in downstream analyses. ResultsWe develop Forseti, a predictive model to probabilistically assign a splicing status to scRNA-seq reads. Our model has two key components. First, we train a binding affinity model to assign a probability that a given transcriptomic site is used in fragment generation. Second, we fit a robust fragment length distribution model that generalizes well across datasets deriving from different species and tissue types. Forseti combines these two trained models to predict the splicing status of the molecule of origin of reads by scoring putative fragments that associate each alignment of sequenced reads with proximate potential priming sites. Using both simulated and experimental data, we show that our model can precisely predict the splicing status of reads and identify the true gene origin of multi-gene mapped reads. AvailabilityForseti and the code used for producing the results are available at https://github.com/COMBINE-lab/forseti under a BSD 3-clause license.

bioinformatics↗

bioRxiv2024

PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization

Single-cell perturbation sequencing techniques (scPerturbation), represented by single cell genetic perturbation sequencing (e.g., Perturb-seq) and single cell chemical perturbation sequencing (e.g., sci-Plex), result from the integration of single-cell toolkits with conventional bulk screening methods. These innovative sequencing techniques empower researchers to dissect perturbation functions and mechanisms in complex biological systems at an unprecedented resolution. Despite these advancements, a notable gap exists in the availability of a dedicated database for exploring and querying scPerturbation data. To address this gap and facilitate seamless data sharing for researchers, we present PerturBase--the first and most comprehensive database designed for the analysis and visualization of scPerturbation data (http://www.perturbase.cn/). PerturBase consolidates 122 datasets from 46 publicly accessible research studies, covering 115 single-modal and 7 multi-modal datasets that include 24254 genetic and 230 chemical perturbations from about 6 million cells. The database provides insights through various software-analyzed results, encompassing quality control, denoising, differential expression gene analysis, perturbation function analysis, and correlation characterization between perturbations. All datasets and in-depth analyses are presented in user-friendly, easy-to-browse pages and can be visualized through intuitive tables and various image formats. In summary, PerturBase stands as a pioneering high-content database, intended for searching, visualizing, and analyzing scPerturbation datasets, contributing to an enhanced understanding of perturbation functions and mechanisms. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/578767v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@15bdfcborg.highwire.dtl.DTLVardef@c1be77org.highwire.dtl.DTLVardef@1bf7e32org.highwire.dtl.DTLVardef@f62e8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2024

Multiple Loci for Foveolar Vision in Macaque Monkey

A common tenet of neural sensory representation is that species-specific behaviors are reflected in specialized brain organizations1. In humans and nonhuman primates, the central one degree of vision is processed by the foveola2, a retinal structure which comprises a high density of photoreceptors and is crucial for primate-specific high acuity vision, color vision, and gaze-directed visual attention3,4,5. In this study, we have developed high spatial resolution ultrahigh field 7T fMRI methods for functional mapping of foveolar visual cortex in awake monkeys. We provide evidence that, in the ventral pathway (V1-V4 and TEO), viewing of a central small spot elicits a ring of multiple (at least 8) foveolar representations per hemisphere. This ring surrounds a large area called the foveolar core. This is an area populated by millimeter-scale functional domains sensitive to fine stimuli and high spatial frequencies, consistent with foveolar visual acuity, as well as color and achromatic information, and motion. The unique position of the foveolar core suggests it may be a hub subserving higher order needs of foveolar function, such as integrating different spatial scales of representation, integrating local and global features in object perception, and bringing together the four quadrants of visual space. Thus, this elaborate re-representation of central vision signifies a cortical specialization for various foveation behaviors.

neuroscience↗

bioRxiv2024

Epidermal ZBP1 stabilizes mitochondrial Z-DNA to drive UV-induced IFN signaling in autoimmune photosensitivity

Photosensitivity is observed in numerous autoimmune diseases and drives poor quality of life and disease flares. Elevated epidermal type I interferon (IFN) production primes for photosensitivity and enhanced inflammation, but the substrates that sustain and amplify this cycle remain undefined. Here, we show that IFN-induced Z-DNA binding protein 1 (ZBP1) stabilizes ultraviolet (UV)B-induced cytosolic Z-DNA derived from oxidized mitochondrial DNA. ZBP1 is significantly upregulated in the epidermis of adult and pediatric patients with autoimmune photosensitivity. Strikingly, lupus keratinocytes accumulate extensive cytosolic Z-DNA after UVB, and transfection of keratinocytes with Z-DNA results in stronger IFN production through cGAS-STING activation compared to B-DNA. ZBP1 knockdown abrogates UV-induced IFN responses, whereas overexpression results in a lupus-like phenotype with spontaneous Z-DNA accumulation and IFN production. Our results highlight Z-DNA and ZBP1 as critical mediators for UVB-induced inflammation and uncover how type I IFNs prime for cutaneous inflammation in photosensitivity. One Sentence Summary: ZBP1 and mitochondrial Z-DNA drive autoimmune photosensitivity via cGAS-STING activation.

immunology↗

bioRxiv2024

3D Bioprinting of Human Neural Tissues with Functional Connectivity

Probing how the human neural networks operate is hindered by the lack of reliable human neural tissues amenable for dynamic functional assessment of neural circuits. We developed a 3D bioprinting platform to assemble tissues with defined human neural cell types in a desired dimension using a commercial bioprinter. The printed neuronal progenitors differentiate to neurons and form functional neural circuits in and between tissue layers with specificity within weeks, evidenced by the cortical-to-striatal projection, spontaneous synaptic currents and synaptic response to neuronal excitation. Printed astrocyte progenitors develop into mature astrocytes with elaborated processes and form functional neuron-astrocyte networks, indicated by calcium flux and glutamate uptake in response to neuronal excitation under physiological and pathological conditions. These designed human neural tissues will likely be useful for understanding the wiring of human neural networks, modeling pathological processes, and serving as platforms for drug testing.

bioengineering↗

bioRxiv2024

Tmc7 deficiency causes acrosome biogenesis defects and male infertility in mice

Transmembrane channel-like (TMC) proteins are a highly conserved ion channel family consisting of eight members (TMC1-TMC8) in mammals. TMC1/2 are components of the mechanotransduction channel in hair cells, and mutations of TMC1/2 cause deafness in humans and mice. However, the physiological roles of other TMC proteins remain largely unknown. Here, we show that Tmc7 is specifically expressed in the testis and that it is required for acrosome biogenesis during spermatogenesis. Tmc7-/- mice exhibited abnormal sperm head, disorganized mitochondrial sheaths, and reduced number of elongating spermatids, similar to human oligo-astheno-teratozoospermia. We further demonstrate that TMC7 is colocalized with GM130 at the cis-Golgi region in round spermatids. TMC7 deficiency leads to aberrant Golgi morphology and impaired fusion of Golgi-derived vesicles to the developing acrosome. Moreover, upon loss of TMC7 intracellular ion homeostasis is impaired and ROS levels are increased, which in turn causes Golgi and endoplasmic reticulum (ER) stress. Taken together, these results suggest that TMC7 is required to maintain pH and ion homeostasis, which is needed for acrosome biogenesis. Our findings unveil a novel role for TMC7 in acrosome biogenesis during spermiogenesis.

developmental biology↗

bioRxiv2024

Toward subtask decomposition-based learning and benchmarking for genetic perturbation outcome prediction and beyond

Deciphering cellular responses to genetic perturbations is fundamental for a wide array of biomedical applications, ranging from uncovering gene roles and interactions to unraveling effective therapeutics. Accurately predicting the transcriptional outcomes of genetic perturbations is indispensable for optimizing experimental perturbations and deciphering cellular response mechanisms; however, three scenarios present principal challenges, i.e., predicting single genetic perturbation outcomes, predicting multiple genetic perturbation outcomes and predicting genetic outcomes across cell lines. In this study, we introduce SubTAsk decomposition Modeling for genetic Perturbation prediction (STAMP), a conceptually novel computational strategy for genetic perturbation outcome prediction and downstream applications. STAMP innovatively formulates genetic perturbation prediction as a subtask decomposition (STD) problem by resolving three progressive subtasks in a divide-and-conquer manner, i.e., identifying differentially expressed gene (DEG) postperturbations, determining the regulatory directions of DEGs and finally estimating the magnitudes of gene expression changes. In addition to facilitating perturbation prediction, STAMP also serves as a robust and generalizable benchmark guide for evaluating various genetic perturbation prediction models. As a result, STAMP exhibits a substantial improvement in terms of its genetic perturbation prediction ability over the existing approaches on three subtasks and beyond, including revealing the ability to identify key regulatory genes and pathways on small samples and to reveal precise genetic interactions. Overall, STAMP serves as a fundamentally novel and effective prediction and generalizable benchmarking strategy that can facilitate genetic perturbation prediction, guide the design of perturbation experiments, and broaden the understanding of perturbation mechanisms.

bioinformatics↗