Biology subjects

Zhou, G.

Publications and source records attributed to Zhou, G..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

A single dorsal vagal complex circuit mediates the aversive and anorectic responses to GLP1R agonists

GLP-1 receptor agonists (GLP1RAs) effectively reduce feeding to treat obesity, although nausea and other aversive side effects of these drugs can limit their use. Brainstem circuits that promote satiation and that mediate the physiologic control of body weight can be distinguished from those that cause aversion. It remains unclear whether brainstem Glp1r neurons contribute to the normal regulation of energy balance and whether GLP1RAs control appetite via circuits distinct from those that mediate aversive responses, however. Hence, we defined roles for AP and NTS Glp1r-expressing neurons (APGlp1r and NTSGlp1r neurons, respectively) in the physiologic control of body weight, the GLP1RA-dependent suppression of food intake, and the GLP1RA-mediated stimulation of aversive responses. While silencing non-aversive NTSGlp1r neurons interfered with the physiologic restraint of feeding and body weight, restoring NTSGlp1r neuron Glp1r expression on an otherwise Glp1r-null background failed to enable long-term body weight suppression by GLP1RAs. In contrast, selective Glp1r expression in APGlp1r neurons restored both aversive responses and long-term body weight suppression by GLP1RAs. Thus, while non-aversive NTSGlp1r neurons control physiologic feeding, aversive APGlp1r neurons mediate both the anorectic and weight loss effects of GLP1RAs, dictating the functional inseparability of these pharmacologic GLP1RA responses at a circuit level.

neuroscience↗

bioRxiv2025

An improved FLARE system for recording and manipulating neuronal activity

Recording and manipulating neuronal ensembles that underlie cognition and behavior in vivo is challenging. FLARE is a light- and calcium-gated transcriptional reporting system for labeling activated neurons on the order of minutes. However, FLARE is limited by its sensitivity to prolonged neuronal activities. Here, we present an improved version of FLARE, termed cytoFLARE. cytoFLARE incorporates cytosolic expression of the transcription factor and a more sensitive pair of calcium sensing domains. We showed that cytoFLARE provides more calcium- and light-dependent signals in HEK293T cells and higher signal-to-background ratios in neuronal cultures. We further established cytoFLARE transgenic Drosophila models and applied cytoFLARE to label activated neurons upon sensory or optogenetic stimulation within a defined time window. Notably, through cytoFLARE-driven expression of an optogenetic actuator, we successfully reactivated neurons involved in the larval nociceptive system. Our findings demonstrate the first characterization and application of time-gated calcium integrators in Drosophila.

bioengineering↗

bioRxiv2024

RNAGenesis: Foundation Model for Enhanced RNA Sequence Generation and Structural Insights

RNA molecules are central to gene regulation, catalysis, and molecular recognition, and offer broad opportunities for therapeutic applications. However, uncovering their complex sequence, structure, and function relationships, particularly for non-coding RNAs, remains a formidable challenge. Here, we introduce RNAGenesis, a Generalist RNA foundation model that integrates sequence representation, structural prediction, and de novo functional design within a single generative framework. Trained on diverse clustered non-coding RNAs, RNAGenesis leverages a BERT-style encoder, query-based latent compression, and a diffusion-guided decoder enhanced by inference-time alignment with gradient guidance and beam search strategies. Through comprehensive evaluations, RNAGenesis achieves state-of-the-art performance on 11 of 13 tasks in the BEACON benchmark and surpasses structure-aware models in inverse folding, 3D structure prediction, and de novo structure design. We further introduce RNATx-Bench, a dedicated benchmark for RNA therapeutics comprising over 100,000 experimentally validated sequences. RNAGenesis demonstrates strong predictive performance across ASOs, siRNAs, shRNAs, circRNAs, and untranslated region (UTR) variants. Furthermore, RNAGenesis enables functional RNA design, including aptamers targeting IGFBP3 and structurally constrained sgRNA scaffolds. Wet-lab validation confirms aptamer binding with KD values as low as 4.02 nM and up to 2.5-fold improvement in editing efficiency across CRISPR-Cas9, base editing, and prime editing systems. These results position RNAGenesis as a next-generation general-purpose RNA foundation model with broad utility for computational modeling and experimental therapeutic design.

bioinformatics↗

bioRxiv2024

Single-cell transcriptome profiling of the myeloid cells repopulating after chemotherapy identifies a neutrophil-like monocyte subset with pro-tumor activities

Patients with cancer often receive chemotherapy to control tumor progression and reduce disease symptoms. Cytotoxic chemotherapeutic agents not only kill rapidly growing cancer cells but also reduce normal cells including myeloid cells, the main innate immune population involved in fighting infections and repairing tissue damages. Rapid loss of myeloid cells caused by chemotherapy triggers myelopoiesis, a process in which the hematopoietic stem and progenitor cells in the bone marrow regenerate myeloid cells, including monocytes, neutrophils, dendritic cells and macrophages, to reconstitute the myeloid cell compartment. We previously reported that chemotherapy with an alkylating agent cyclophosphamide (CTX) in mice leads to repopulation of myeloid cells that acquire immunosuppressive activities within the monocyte subset. However, detailed information on the cellular composition and molecular identity of these chemotherapy- induced immunosuppressive monocytes is lacking. Here, we investigated how the various myeloid cell subsets in the bone marrow of mice respond to CTX chemotherapy through single-cell RNA sequencing analysis (scRNAseq). We found that myeloid progenitor cells and monocytes were reduced 2 days after chemotherapy but rebounded and surpassed their pretreatment levels by day 7. Further scRNAseq analysis of pre-enriched monocytes revealed that the monocyte population was heterogenous, and that chemotherapy tilted myelopoiesis towards the production of neutrophil-like monocytes (NeuMo). We identified Cxcr4 and Cx3cr1 as suitable markers for isolation of chemotherapy-induced NeuMo and demonstrated that these cells were suppressive to T cells. Together with the evidence that CTX-induced monocytes can promote breast cancer metastasis in mice, our data reveal the heterogeneity of the monocytes reemerging after chemotherapy and identify the NeuMo subset as a potential therapeutic target for enhancing the efficacy of chemotherapy in cancer.

immunology↗

bioRxiv2024

Uncovering the signaling networks of disseminated glioblastoma cells in vivo with INSIGHT

Dysregulation of intracellular signaling networks underpins cancer. However, a systems-level elucidation of how signaling networks within distinct cell subpopulations drive cancer progression in vivo has been unattainable due to technical limitations. We developed INSIGHT (INvestigating SIGnaling network of specific cell subpopulation in Heterogeneous Tissue), a new platform technology combining fluorescence-activated cell sorting with ultra-sensitive mass spectrometry to enable phosphoproteomic characterization of rare and discrete cell subpopulations from fixed tissues. We demonstrated the broad utility of INSIGHT by analyzing the oligodendroglial cell-specific signaling network in the mouse brain. We then applied INSIGHT to investigate the rare, disseminated tumor cell subpopulation in glioblastoma patient-derived xenograft models. INSIGHT uncovered a global rewiring of signaling networks with tumor cell dissemination, marked by a transition from proliferation-associated signaling in the primary tumor cells to signaling associated with postsynapse, neuronal migration, and ion homeostasis in disseminated tumor cells. We reveal interconnections between signaling circuitries within the networks, with numerous proteins, including GluA2, exhibiting altered phosphorylation without protein expression changes, emphasizing the role of post-translational modifications in glioblastoma dissemination. We validated key phosphorylation changes and inferred differentially active kinases with tumor spread to offer new systems-level insights into glioblastoma dissemination mechanisms in vivo. INSIGHT is generally applicable to a wide range of biological systems without genetic engineering and provides quantitative phosphorylation and protein expression data for selected cell subpopulations from heterogeneous tissues.

systems biology↗

bioRxiv2024

Automated identification of small molecules in cryo-electron microscopy data with density- and energy-guided evaluation

Methodological improvements in cryo-electron microscopy (cryoEM) have made it a useful tool in ligand-bound structure determination for biology and drug design. However, determining the conformation and identity of bound ligands is still challenging at the resolutions typical for cry-oEM. Automated methods can aid in ligand conformational modeling, but current ligand identification tools -- developed for X-ray crystallography data -- perform poorly at resolutions common for cryoEM. Here, we present EMERALD-ID, a method capable of docking and evaluating small molecule conformations for ligand identification. EMERALD-ID identifies 43% of common ligands exactly and identifies closely related ligands in 66% of cases. We then use this tool to discover possible ligand identification errors, as well as previously unidentified ligands. Furthermore, we show EMERALD-ID is capable of identifying ligands from custom ligand libraries of various small molecule types, including human metabolites and drug fragments. Our method provides a valuable addition to cryoEM modeling tools to improve small molecule model accuracy and quality.

biochemistry↗

bioRxiv2024

Interaction between time-of-day and oxytocin efficacy in mice and humans with and without gestational diabetes

Management of labor in women with diabetes is challenging due to the high risk of peri- and postpartum complications. To avoid cesarean section and assist with labor progression, Pitocin, a synthetic oxytocin, is frequently used to induce and augment labor. However, the efficacy of Pitocin is often compromised in diabetic pregnancies, leading to increased cesarian delivery. As diabetes deregulates the bodys circadian timekeeping system and the time-of-day of the first Pitocin administration contributes to labor duration, our objective was to determine how the time of day and the circadian clock gene, Bmal1, gates oxytocin efficacy. Our studies in mice show that, compared to the rest phase of the day (lights on), the uterotonic efficacy of oxytocin is significantly increased during the active phase (lights off). Using in vitro studies, a myometrium-specific Bmal1 conditional knockout mouse model, and a mouse model of food-induced gestational diabetes, we find that Bmal1 is crucial for maintaining oxytocin receptor expression and response in the myometrium in mice. These findings also translate to humans, where oxytocin-induced human myometrial cell contraction is time-of-day dependent, and retrospective clinical data suggest that administration of Pitocin in the morning should be considered for pregnant women with gestational diabetes.

physiology↗

bioRxiv2024

PM2.5 from Automobile Exhaust Induces Apoptosis in Male Rat Germ Cells via the ROS-UPRmt Signaling Pathway

ObjectiveTo explore the underlying mechanism behind the fine particulate matters (PM2.5)-mediated regulation of reproductive function in male rats, and to determine the role of vitamins in this process. MethodsIn all, 32 male SD rats were randomized to a control cohort (normal saline), a Vit cohort (vitamin C at 100 mg/kg + vitamin E at 50 mg/kg), a PM2.5 cohort (PM2.5 10 mg/kg), and a PM2.5+Vit cohort (PM2.5 exposure + vitamin C at 100 mg/kg + vitamin E at 50 mg/kg), with eight rats in each cohort. After four weeks of exposure, mating experiments were carried out. Thereafter, rats were euthanized, and the testis and epididymis tissues were excised for hematoxylin-eosin (HE) staining and sperm quality analysis. Apoptosis of testis tissues was quantified via a terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) assay. Moreover, the testicular oxidative stress (OS)-, apoptosis- and mitochondrial unfolded protein response (UPRmt)-related essential protein expressions were measured via western blotting (WB). ResultsAfter PM2.5 exposure, the sperm count and motility decreased, while sperm abnormality and the apoptosis index increased. HE staining showed that the number of spermatogenic cells decreased. WB showed that the PM2.5 group had decreased expressions of superoxide dismutase (SOD), nuclear factor E2-related factor 2 (Nrf2), and B-cell lymphoma-2 (Bcl-2) (p < 0.05), increased expressions of malondialdehyde (MDA), Bcl-2 associated X protein (Bax), and Caspase3 (p < 0.05), and downregulated expressions of C/EBP homologous protein (CHOP), heat shock protein 60 (HSP60), and activating transcription factor 5 (ATF5) (p < 0.05). These were all reversed by vitamin intervention. ConclusionPM2.5 from automobile exhaust disrupts male reproductive function. A combination of vitamins may protect reproductive function via the reactive oxygen species (ROS)-UPRmt signaling pathway. HighlightsO_LIPM2.5 from vehicle exhaust can cause apoptosis of male germ cells. C_LIO_LIPM2.5 from vehicle exhaust induces germ cell apoptosis through the ROS-UPRmt signaling pathway. C_LIO_LICombined vitamin C and E can enhance UPRmt activity to alleviate the germ cell apoptosis caused by PM2.5 from vehicle exhaust. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/621651v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@d3f5edorg.highwire.dtl.DTLVardef@1b6daa1org.highwire.dtl.DTLVardef@1cba0b4org.highwire.dtl.DTLVardef@1a3c9f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2024

Modeling protein-small molecule conformational ensembles with ChemNet

Modeling the conformational heterogeneity of protein-small molecule interactions is important for understanding natural systems and evaluating designed systems, but remains an outstanding challenge. We reasoned that while residue level descriptions of biomolecules are efficient for de novo structure prediction, for probing heterogeneity of interactions with small molecules in the folded state an entirely atomic level description could have advantages in speed and generality. We developed a graph neural network called PLACER (Protein-Ligand Atomistic Conformational Ensemble Resolver) trained to recapitulate correct atomic positions from partially corrupted input structures from the Cambridge Structural Database and the Protein Data Bank; the nodes of the graph are the atoms in the system. PLACER accurately generates structures of diverse organic small molecules given knowledge of their atom composition and bonding, and given a description of the larger protein context, builds up structures of small molecules and protein side chains for protein-small molecule docking. Because PLACER is rapid and stochastic, ensembles of predictions can be readily generated to map conformational heterogeneity. In enzyme design efforts described here and elsewhere, we find that using PLACER to assess the accuracy and pre-organization of the designed active sites results in higher success rates and higher activities; we obtain a preorganized retroaldolase with a kcat/KM of 11000 M-1min-1, considerably higher than any pre-deep learning design for this reaction. We anticipate that PLACER will be widely useful for rapidly generating conformational ensembles of small molecule and small molecule-protein systems, and for designing higher activity preorganized enzymes.

biochemistry↗

bioRxiv2024

Genomic re-sequencing reveals substantial mutational divergence across genetically engineered strains of model archaea

Because archaea are the evolutionary ancestors of eukaryotes, archaeal molecular biology has been a topic of intense recent research. The hypersaline adapted archaeal species Halobacterium salinarum and Haloferax volcanii serve as important model organisms because facile tools enable genetic manipulation. As a result, the number of strains in circulation among the haloarchaeal research community has increased over the last few decades. However, the degree of genetic divergence and effects on genetic integrity during inter-lab transfers remain unclear. To address this question, we performed whole genome re-sequencing on a cross-section of wild-type, parental, and knockout strains in both model species. Integrating these data with existing repositories of re-sequencing data, we identify mutations that have arisen in a collection of 60 strains, sampled from 2 species across 8 different labs. Independent of sequencing, we construct strain lineages, identifying branch points and significant genetic effects in strain history. Combining this with our sequencing data, we identify small clusters of mutations that definitively separate lab strains. Additionally, an analysis of gene knockout strains suggests that roughly 1 in 3 strains currently in use harbors second-site mutations of potential phenotypic impact. Overall, we find that divergence among lab strains is thus far minimal, though as the archaeal research community continues to grow, careful strain provenance and genomic re-sequencing are required to keep inter-lab divergence to a minimum, prevent the compounding of mutations into fully independent lineages, and maintain the current high degree of reproducible research between lab groups in the haloarchaeal research community. Data SummaryNovel sequencing data for this project was submitted to the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) and can be found under bioproject accession PRJNA1120443. SRA accessions for previously published sequencing data are available in supplementary table 1. R code for performing analysis and generating figures is available at https://github.com/andrew-soborowski/halophile_genome_resequencing. Impact StatementArchaea are important due to their shared evolutionary history with eukaryotes. As the archaeal research community grows, keeping track of the genetic integrity of archaeal strains of interest is necessary. In particular, routine genetic manipulations and the common practice of sharing strains between labs allow mutations to arise in lab stocks. If these mutations affect cellular processes, they may jeopardize the reproducibility of work between research groups and confound the results of future studies. In this work, we examine DNA sequences from 60 strains across two species of archaea. We identify shared and unique mutations occurring between and within strains. Independently, we trace the lineage of each strain, identifying which genetic manipulations lead to observed off-target mutations. While overall divergence across labs is minimal so far, our work highlights the need for labs to continue proper strain husbandry.

genomics↗

bioRxiv2024

Dose-related Mutagenic and Clastogenic Effects of Benzofluoranthene in Mouse Somatic Tissues Detected by Duplex Sequencing and the Micronucleus Assay

Polycyclic aromatic hydrocarbons (PAHs) are common environmental pollutants that originate from the incomplete combustion of organic materials. We investigated the clastogenicity and mutagenicity of benzo[b]fluoranthene (BbF), one of 16 priority PAHs, in MutaMouse males after a 28-day oral exposure. BbF causes robust dose-dependent increases in micronucleus frequency in peripheral blood, indicative of chromosome damage. Duplex Sequencing (DS), an error-corrected sequencing technology, reveals that BbF induces dose-dependent increases in mutation frequencies in bone marrow (BM) and liver. Mutagenicity is increased in intergenic relative to genic regions, suggesting a role for transcription-coupled repair of BbF-induced DNA damage. At higher doses, the maximum mutagenic response to BbF is higher in liver, which has a lower mitotic index but higher metabolic capacity than BM; however, mutagenic potency is comparable between the two tissues. BbF induces primarily C:G>A:T mutations, followed by C:G>T:A and C:G>G:C, indicating that BbF metabolites mainly target guanines and cytosines. The mutation spectrum of BbF correlates with cancer mutational signatures associated with tobacco exposure, supporting its contribution to the carcinogenicity of combustion-derived PAHs in humans. Overall, BbFs mutagenic effects are similar to benzo[a]pyrene, a well-studied mutagenic PAH. Our work showcases the utility of DS for effective mutagenicity assessment of environmental pollutants. SynopsisWe used Duplex Sequencing to study the mutagenicity of benzo[b]fluoranthene across the mouse genome. Dose-dependent changes in mutation frequency and spectrum quantify its role in PAH-induced carcinogenicity.

pharmacology and toxicology↗

bioRxiv2024

Context-driven interaction retrieval and classification for modeling, curation, and reuse

Automated extraction of molecular interactions from scientific literature has outpaced the development of systematic methods for integrating this information with curated models and knowledge graphs. Here we present VIOLIN (Versatile Interaction Organizing to Leverage Information in Networks), a configurable, attribute-aware reconciliation framework that formally compares newly extracted interaction lists against structured baseline graphs. VIOLIN classifies each interaction as a corroboration, contradiction, flagged case, or extension, and supports configurable attribute inclusion strategies and mismatch semantics to adjust reconciliation strictness. We evaluate VIOLIN using interaction lists generated by two traditional NLP systems (REACH, INDRA) and two large language models (GPT-4.1, Llama 3) across multiple literature corpora and structurally distinct baseline graphs. Across all conditions, reconciliation outcomes were stable and interpretable, with extensions dominating and corroboration-contradiction balance reflecting intrinsic structural relationships between baseline graphs and extracted evidence. Sensitivity analyses demonstrate that attribute inclusion and classification scheme selection shift category boundaries predictably. Benchmark evaluations confirm high algorithmic correctness and alignment with expert curation. VIOLIN is publicly available as a Python package and through web-based interface (https://nmzlab.github.io/Tools-UI).

systems biology↗

bioRxiv2024

PINDER: The protein interaction dataset and evaluation resource

Protein-protein interactions (PPIs) are fundamental to understanding biological processes and play a key role in therapeutic advancements. As deep-learning docking methods for PPIs gain traction, benchmarking protocols and datasets tailored for effective training and evaluation of their generalization capabilities and performance across real-world scenarios become imperative. Aiming to overcome limitations of existing approaches, we introduce PINDER, a comprehensive annotated dataset that uses structural clustering to derive non-redundant interface-based data splits and includes holo (bound), apo (unbound), and computationally predicted structures. PINDER consists of 2,319,564 dimeric PPI systems (and up to 25 million augmented PPIs) and 1,955 high-quality test PPIs with interface data leakage removed. Additionally, PINDER provides a test subset with 180 dimers for comparison to AlphaFold-Multimer without any interface leakage with respect to its training set. Unsurprisingly, the PINDER benchmark reveals that the performance of existing docking models is highly overestimated when evaluated on leaky test sets. Most importantly, by retraining DiffDock-PP on PINDER interface-clustered splits, we show that interface cluster-based sampling of the training split, along with the diverse and less leaky validation split, leads to strong generalization improvements.

bioinformatics↗

bioRxiv2024

PLINDER: The protein-ligand interactions dataset and evaluation resource

Protein-ligand interactions (PLI) are foundational to small molecule drug design. With computational methods striving towards experimental accuracy, there is a critical demand for a well-curated and diverse PLI dataset. Existing datasets are often limited in size and diversity, and commonly used evaluation sets suffer from training information leakage, hindering the realistic assessment of method generalization capabilities. To address these shortcomings, we present PLIN-DER, the largest and most annotated dataset to date, comprising 449,383 PLI systems, each with over 500 annotations, similarity metrics at protein, pocket, interaction and ligand levels, and paired unbound (apo) and predicted structures. We propose an approach to generate training and evaluation splits that minimizes task-specific leakage and maximizes test set quality, and compare the resulting performance of DiffDock when retrained with different kinds of splits.

biochemistry↗

bioRxiv2024

Modulation of ribosomal subunit associations by eIF6 is critical for mitotic exit and cancer progression.

Moderating the pool of active ribosomal subunits is critical for maintaining global translation rates. A factor crucial for modulating the 60S ribosomal subunits is eukaryotic translation initiation factor 6. Release of eIF6 from 60S is essential to permit 60S interactions with 40S. Here, using the N106S mutant of eIF6, we show that disrupting eIF6 interaction with 60S leads to an increase in vacant 80S. It further highlights a dichotomy in the anti-association activity of eIF6 that is distinct from its role in 60S biogenesis and shows that the nucleolar localization of eIF6 is not dependent on uL14-BCCIP interactions. Limiting active ribosomal pools markedly deregulates translation especially in mitosis and leads to chromosome segregation defects, mitotic exit delays and mitotic catastrophe. Ribo-Seq analysis of the eIF6-N106S mutant shows a significant downregulation in the translation efficiencies of mitotic factors and specifically transcripts with long 3'UTRs. eIF6-N106S mutation also limits cancer invasion, and this role is correlated with the overexpression of eIF6 only in high-grade invasive cancers suggesting that deregulation of eIF6 is probably not an early event in cancers. Thus, this study highlights the segregation of eIF6 functions and its role in moderating 80S availability for mitotic translation and cancer progression.

molecular biology↗

bioRxiv2024

TYK2 as a novel therapeutic target in Alzheimer Disease

Neuroinflammation is a pathological feature of many neurodegenerative diseases, including Alzheimers disease (AD)1,2 and amyotrophic lateral sclerosis (ALS)3, raising the possibility of common therapeutic targets. We previously established that cytoplasmic double-stranded RNA (cdsRNA) is spatially coincident with cytoplasmic pTDP-43 inclusions in neurons of patients with C9ORF72-mediated ALS4. CdsRNA triggers a type-I interferon (IFN-I)-based innate immune response in human neural cells, resulting in their death 4. Here, we report that cdsRNA is also spatially coincident with pTDP-43 cytoplasmic inclusions in brain cells of patients with AD pathology and that type-I interferon response genes are significantly upregulated in brain regions affected by AD. We updated our machine-learning pipeline DRIAD-SP (Drug Repurposing In Alzheimers Disease with Systems Pharmacology) to incorporate cryptic exon (CE) detection as a proxy of pTDP-43 inclusions and demonstrated that the FDA-approved JAK inhibitors baricitinib and ruxolitinib that block interferon signaling show a protective signal only in cortical brain regions expressing multiple CEs. Furthermore, the JAK family member TYK2 was a top hit in a CRISPR screen of cdsRNA-mediated death in differentiated human neural cells. The selective TYK2 inhibitor deucravacitinib, an FDA-approved drug for psoriasis, rescued toxicity elicited by cdsRNA. Finally, we identified CCL2, CXCL10, and IL-6 as candidate predictive biomarkers for cdsRNA-related neurodegenerative diseases. Together, we find parallel neuroinflammatory mechanisms between TDP-43 associated-AD and ALS and nominate TYK2 as a possible disease-modifying target of these incurable neurodegenerative diseases.

neuroscience↗

bioRxiv2024

SEIR: a novel multi-locus GWAS method that provides higher statistical power for fast identifying variant-phenotype associations

Multi-locus genome-wide association study (GWAS) methods have considered the joint effects of multiple variants to more accurately unravel the genetic basis of complex traits. Here, we developed a novel multi-locus GWAS method named Selector-Embedded Iterative Regression (SEIR), which integrates the embedded selector with fast single-marker scanning in an iterative manner. SEIR has excellent adaptability and flexibility under various genetic architectures for qualitative and quantitative traits. Reliability of SEIR was experimentally supported by integrating GWAS with 3D epigenomics in a real trait. Conclusively, SEIR exhibits higher statistical power for fast identifying putative variants compared to other single- and multi-locus methods.

genetics↗

bioRxiv2024

Observing one-divalent-metal-ion dependent and histidine-promoted His-Me family I-PpoI nuclease catalysis in crystallo

Metal-ion-dependent nucleases play crucial roles in cellular defense and biotechnological applications. Time-resolved crystallography has resolved catalytic details of metal-ion-dependent DNA hydrolysis and synthesis, uncovering the essential roles of multiple metal ions during catalysis. The histidine-metal (His-Me) superfamily nucleases are renowned for binding one divalent metal ion and requiring a conserved histidine to promote catalysis. Many His-Me family nucleases, including homing endonucleases and Cas9 nuclease, have been adapted for biotechnological and biomedical applications. However, it remains unclear how the single metal ion in His-Me nucleases, together with the histidine, promotes water deprotonation, nucleophilic attack, and phosphodiester bond breakage. By observing DNA hydrolysis in crystallo with His-Me I-PpoI nuclease as a model system, we proved that only one divalent metal ion is required during its catalysis. Moreover, we uncovered several possible deprotonation pathways for the nucleophilic water. Interestingly, binding of the single metal ion and water deprotonation are concerted during catalysis. Our results reveal catalytic details of His-Me nucleases, which is distinct from multi-metal-ion-dependent DNA polymerases and nucleases.

biochemistry↗