Biology subjects

Jiang, Q.

Publications and source records attributed to Jiang, Q..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Efficiency, accuracy and robustness of probability generating function based parameter inference method for stochastic biochemical reactions

Biochemical reactions are inherently stochastic, with their kinetics commonly described by chemical master equations (CMEs). However, the discrete nature of molecular states renders likelihood-based parameter inference from CMEs computationally intensive. Here, we introduce an inference method that leverages analytical solutions in the probability generating function (PGF) space and systematically evaluate its efficiency, accuracy, and robustness. Across both steady-state and time-resolved count data, our numerical experiments demonstrate that the PGF-based method consistently outperforms existing approaches in terms of both computational efficiency and inference accuracy, even under data contamination. These favorable properties further enable the extension of the PGF-based framework to model selection--a task typically considered computationally prohibitive. Using timeresolved data, we show that the method can correctly identify complex gene expression models with more than three gene states, a task that cannot be reliably achieved using steady-state data alone.

systems biology↗

bioRxiv2026

Phenotype-Guided In Silico Molecular Generation Using Large Language Models

Complex diseases often emerge from coordinated, system-level cellular state changes that are difficult to address with target centric drug discovery. Phenotypic drug discovery offers a principled alternative but remains constrained by the cost and scalability of pathologically relevant assays. Here we present GEMGen, a large language model-based framework that performs in silico phenotypic drug discovery by generating small molecules directly from transcriptomic representations of cellular states. GEMGen encodes desired phenotypic transitions as text-based representations of up- and down-regulated gene sets, enabling transferable modeling across experimental platforms and data modalities. Trained on large scale chemical perturbation data, GEMGen robustly identifies phenotype-oriented compounds and mechanistically related but structurally distinct candidates across multiple benchmarks. Applied to signatures induced by genetic perturbations, GEMGen produces small molecules that phenocopy gene knockdown effects and identifies chemically novel inhibitors, including previously unreported KEAP1 inhibitors that activate NRF2 signaling. Extending this approach to a disease relevant model of fibrosis, GEMGen generates compounds that reverse profibrotic transcriptional programs and cellular phenotypes. These results establish a scalable framework for translating transcriptomic phenotypes into candidate therapeutic molecules, enabling systems-level exploration of vast chemical space and offering a complementary in silico counterpart to physical phenotypic drug screens.

cell biology↗

bioRxiv2026

An ER-Inner Membrane Complex Bridge via VAP-VPS13A-DAT1 Drives Daughter Budding in Toxoplasma gondii

All alveolates including apicomplexa parasites contain an inner membrane complex (IMC) underneath the plasma membrane. The IMC is synthesized de novo during the daughter cell budding (endodyogeny) within the mother cell and serves as a crucial scaffold for supporting cytoskeletal structures and the glideosome machinery for the parasite locomotion. However, the mechanism(s) underlying the membrane biogenesis in the IMC are not well understood. Using clinically-relevant and globally-prevalent pathogenic protist model, Toxoplasma gondii, we identified the TgVAP-TgVPS13A-TgDAT1 complex bridging the IMC to the endoplasmic reticulum (ER) - the major site of phospholipid synthesis. Individual components of this complex play a crucial role in the IMC biogenesis, where the multi-modular TgVPS13A protein interacts with the lipid scramblase TgDAT1 in the IMC via its C-terminal VAB domain, and with the ER-resident TgVAP through its N-terminal region. DAT1 is recruited for the progeny formation sites during the early stages of budding. Conditional depletion of TgVPS13A, TgDAT1 or TgVAP results in collapse of the inner membrane complex, leading to parasite death, as visualized by endodyogeny-specific organelle markers. LactC2-GFP, a biosensor of phosphatidylserine and phosphatidylthreonine lipids made in the ER and enriched in the IMC, also mislocalizes upon protein depletion. In conclusion, we propose that TgVAP-TgVPS13A-TgDAT1 bridge the ER and IMC and mediate the inter-organelle transport of lipids, thus contributing to the organelle biogenesis and daughter budding in T. gondii. Author SummaryThe inner membrane complex (IMC) in apicomplexan parasites is essential for maintaining the structural stability of the parasite, as well as for its budding and motility. The IMC is composed of flattened vesicles, alveolins, and microtubules. However, the mechanism behind the biogenesis of these flattened vesicles remains unclear. In this study, we provide evidence that a protein complex formed by TgVAP, TgVPS13A, and TgDAT1 exists between the endoplasmic reticulum (ER) and the IMC. Phenotypic analysis indicates that the absence of any individual component of this protein complex disrupts the biogenesis of daughter IMCs, which in turn affects the budding of daughter parasites. We also demonstrated that TgDAT1 functions as a scramblase. Based on our findings, we propose a model in which the TgVAP-TgVPS13A-TgDAT1 complex mediates lipid transport from the ER to the nascent IMC, driving the expansion of the IMC membrane and the budding of daughter parasites in T. gondii. Furthermore, TgDAT1 may facilitate the transfer of lipids from the outer leaflet to the inner leaflet of the IMC sacs, promoting a balanced composition of the IMC membrane components.

microbiology↗

bioRxiv2025

Post-weaning social isolation impairs the orbitofrontal cortical circuit subserving contagious pain and prosocial behaviors

Empathic behaviors are sensitive to environmental factors like post-weaning social isolation (SI), yet the mechanisms by which SI affects empathy remain unclear. Here, we show that mice subjected to SI exhibit marked impairments in contagious pain and prosocial behaviors, including allo-grooming and allo-licking toward cagemates experiencing inflammatory pain. Mechanistically, we identify the glutamatergic projection from the ventromedial thalamic nucleus (VM) to the orbitofrontal cortex (OFC) as critical for these empathy-like responses. SI induces hypoexcitability of OFC glutamatergic neurons and attenuates excitatory synaptic transmission within the VM[->]OFC pathway. Remarkably, chemogenetic activation of OFC neurons or the VM[->]OFC projection restores empathic behaviors in SI mice. Furthermore, we uncover a molecular basis for SI-induced OFC hypoexcitability: the downregulation of Grik3, encoding a kainate-type glutamate receptor subunit. These findings reveal a previously uncharacterized thalamocortical mechanism through which early-life social deprivation disrupts empathic behaviors, offering insights into the underpinnings of social-affective dysfunction.

neuroscience↗

bioRxiv2025

A global deep-sea small protein atlas reveals a reservoir of noncanonical antimicrobial peptides

Small proteins encoded by small open reading frames (smORFs; [≤] 100 aa) represent a largely unexplored dimension of microbial diversity, especially in the deep sea. By analyzing 708 metagenomes from five major deep-sea biomes (hadal trenches, cold seeps, hydrothermal vents, abyssal plains, and seamounts), we constructed the Deep-Sea Small Protein Atlas, comprising 88.7 million smORFs with exceptional novelty and strong habitat specificity. Deep-learning predictions identified 5.47 million candidate antimicrobial peptides (c_AMPs), revealing a peptide space far larger and structurally distinct from known AMPs. Deep-sea c_AMPs are longer, enriched in nonpolar and acidic residues, and exhibit low charge and high intrinsic disorder, suggesting non-membranolytic modes of action. We synthesized 131 representative peptides, of which 87% were antimicrobial, with MICs as low as 1.25 M, broad-spectrum antibacterial and even antifungal efficacy, and minimal mammalian cytotoxicity. Transcriptomics, TEM imaging, and peptide-protein modeling showed that representative peptides preserve membrane integrity while disrupting intracellular processes such as translation and metabolism, supporting intracellular, non-lytic mechanisms. This work uncovers a vast reservoir of previously unrecognized deep-sea small proteins and structurally unconventional AMPs, providing a foundational resource for discovering next-generation peptide therapeutics.

microbiology↗

bioRxiv2025

Widespread remodeling of the RNA editome underlies transcriptional and clinical heterogeneity in pediatric acute lymphoblastic leukemia

Aberrant RNA editing by adenosine deaminases is increasingly recognized as a source of transcriptional diversity in adult cancer, yet its role in pediatric leukemia remains poorly understood. Here, we systematically profiled RNA editing events from bulk RNA-seq data of 1,025 pediatric T-cell acute lymphoblastic leukemia (T-ALL) samples, 37 matched B-ALL diagnosis/relapse pairs, and 6 age-matched non-leukemic controls. We uncovered a widespread global increase in A-to-I editing in T-ALL, affecting both non-coding Alu elements and coding sequences. By contrast, B-ALL shows relatively modest increases in RNA editing at both diagnosis and relapse with no differences in ADAR1 levels. ADAR1 expression is strongly associated with double-stranded RNA (dsRNA) sensors and interferon signaling in T-ALL. Genelevel analyses highlight recurrent editing of oncogenic drivers and regulators of immune signaling, chromatin remodeling, and RNA processing. Unexpectedly, increased editing levels in select genes (CD247, PRKCA and TRAF3IP2.ASI in T-ALL; SPPL3 in B-ALL) were significantly associated with better patient survival, suggesting a potential prognostic role for editing dysregulation at individual gene levels. Together, these results deepen our understanding of the pediatric ALL transcriptome landscape and provided novel candidate regulators and therapeutic targets for future mechanistic and translational investigation.

cancer biology↗

bioRxiv2025

Tissue-embedded CD4⁺ plasticity structures mucosal immunity in IBD-related inflammation

CD4 T helper (Th) cell responses to commensal microbiota are linked to Inflammatory Bowel Disease (IBD), yet how Th programs coexist and evolve in human tissues remains poorly defined. Here, we profiled CD4 memory T cells in intestinal biopsies using immunological and histological approaches to map their phenotypes, functional states, and spatial relationships across disease states. A marked expansion of CD4 T cells concomitant with a ROR{gamma}t Th population with elevated T-bet expression was linked to progression of inflammation. Moreover, Foxp3 cells co-expressing ROR{gamma}t emerged within the inflamed niche, indicating regulatory-Th17 plasticity. Trajectory visualization revealed a potential branched differentiation path towards either regulatory or tissue-resident Th17-like fates, with both termini expressing activation and proliferation markers. Correlation network analysis connected pro-inflammatory CD4 states to T-betGranzyme-B CD8 subsets, indicative of crosstalk between helper and cytotoxic lineages. Histology corroborated this organization, showing frequent interactions between CD4 and CD8 cells in the lamina propria and epithelial border. In functional assays, TCR stimulation during active disease revealed broad suppression of CD4 pro-inflammatory cytokines concomitant with expansion of Foxp3 cells. Conversely, HLA-DR+CD38+ memory subset retained multifunctionality, producing elevated levels of pro-inflammatory cytokines. Together, these results provide insight into a dynamic, tissue-embedded CD4 landscape in IBD. HighlightsO_LIIBD inflammation shapes CD4+ T-cell plasticity and tissue-residency programming. C_LIO_LICorrelated CD4+ and cytotoxic CD8+ T cells co-localize in inflamed mucosa. C_LIO_LIMucosal CD4 memory T cells show hypo-responsiveness in active IBD. C_LIO_LIHLA-DR+CD38+ memory CD4 T cells amplify inflammation via cytokine output. C_LI

immunology↗

bioRxiv2025

A 37-color spectral flow cytometry panel to characterize phenotype and cytokine expression in human intestinal T cells

We developed a 37-color spectral flow cytometry panel to characterize T cell function, with a focus CD4+ T helper (Th) cells, in the human intestine. The panel includes lineage-defining transcription factors, markers for memory status, tissue residency and T cell activation, and 11 cytokines representing multiple Th cell lineages. The panel is currently being used to investigate CD4+ Th cell function in intestinal and peripheral blood samples of inflammatory bowel disease (IBD) patients. The panel could however be applied to investigate both peripheral and tissue-resident T cell function in a range of immune-mediated diseases.

immunology↗

bioRxiv2025

Optic nerve regeneration requires the intracellular domain of LIFRa/CD118

Identifying cell-autonomous and non-autonomous factors that govern retinal ganglion cells (RGCs) ability to extend axons is an important step in developing therapies to achieve recovery after optic nerve injury. Here we report that the intracellular domain of the leukemia inhibitory factor receptor (LIFR/CD118) is essential for mature RGCs ability to regenerate injured axons independent of the cognate ligand (LIF) and other therapies. Overexpression of LIFR in adult RGCs induces neurite outgrowth in cultured RGCs and axon regeneration in vivo while strongly amplifying RGCs response to LIF itself and to unrelated growth factors. Conversely, in loss-of-function studies, down-regulation of LIFR eliminates the pro-regenerative effects of Pten deletion and other potent stimuli. LIFR bidirectionally regulates the constitutive activity of the MAP kinase pathway, in contrast to LIF itself, which primarily activates pSTAT3. Expression of a truncated LIFR lacking the extracellular domain is sufficient to promote axon regeneration and selectively increases the survival of particular RGC subtypes, placing the LIFR intracellular domain as an essential, cell-autonomous regulator of optic nerve regeneration.

neuroscience↗

bioRxiv2025

Genome writing to dissect consequences of SVA retrotransposon disease X-Linked Dystonia Parkinsonism

Human retrotransposon insertions are often associated with diseases. In the case of the neurodegenerative X-Linked Dystonia-Parkinsonism disease, a human-specific SINE-VNTR-Alu subfamily F retrotransposon was inserted in intron 32 of the TAF1 gene. Here, we genomically rewrote a portion of the mouse Taf1 allele with the corresponding 78-kb XDP patient derived TAF1 allele. In mESCs, the presence of the intronic SVAs--rather than the hybrid gene structure--reduces hyTAF1 levels. This leads to transcriptional downregulation of genes with TATA box enriched in their promoters and triggering apoptosis. Chromatin and transcriptome profiling revealed that intronic SVAs are actively transcribed, forming barriers that likely impede transcription elongation. In mice, neuronal lineage TAF1 humanization resulted lethality of male progeny within two months. XDP male mice had severe atrophy centered on the striatum--the same affected brain region in XDP patients. Lastly, CRISPRa-mediated activation of hyTAF1 restored mESC viability, suggesting boosting TAF1 transcription as a therapeutic approach.

genetics↗

bioRxiv2025

XomicsDB: a database of paired multi-omics datasets for systems biology

Life science research is primarily driven by data integration on the basis of theoretical development. Broad applications of multiomics (xomics) data calls for efficient integration of xomics data to infer cellular operation and regulation. To that end, it is urgently needed good-quality xomics data should be curated and shared for the community. Here we present XomicsDB, a database curating paired xomics datasets at both bulk and single-cell levels in model organisms. It contains 183 datasets from 13 model organisms, with a total of seven xomics data types. Users can download these datasets individually or in a batch from the ftp server provided. Users can also upload their paired xomics datasets for sharing. Incoporation of xomics data intom GSMs are demonstrated in model organisms Escherichia coli and human. Future efforts will be on collecting more single-cell xomics data and curating non-model oragnisms. The XomicsDB can be found at: http://xomicsdb.com.

systems biology↗

bioRxiv2025

HIF2-driven PTHrP Causes Cachexia and Hypercalcemia in Kidney Cancer: Treatment with HIF2 Inhibitors

Kidney cancer frequently causes paraneoplastic syndromes, including hypercalcemia and cachexia, but the underlying mechanisms are incompletely understood. The most common form of kidney cancer, clear cell renal cell carcinoma, is frequently caused by loss of the pVHL tumor suppressor protein and the resulting upregulation of the HIF2 transcription factor. We show that PTHLH, which resides on a ccRCC amplicon on chromosome 12p, is a direct HIF2 transcriptional target in ccRCC. Further, we show that the increased PTHLH expression is both necessary and sufficient for the induction of hypercalcemia and cachexia in preclinical orthotopic cell line tumor models. Consistent with these observations, two different allosteric HIF2 inhibitors, belzutifan and NKT2152, rapidly ameliorated hypercalcemia and cachexia in ccRCC patients, including in some patients who did not exhibit objective tumor shrinkage.

cancer biology↗

bioRxiv2025

Human-scATAC-Corpus: a comprehensive database of scATAC-seq data

Single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) profiles chromatin accessibility at cellular resolution, making it possible to reveal epigenomic landscapes that govern gene regulation in a variety of cells. Nevertheless, heterogeneous feature spaces and complex processing pipelines have impeded the construction of an ensemble resource capable of supporting diverse downstream analytical scenarios. To address this gap, we present Human-scATAC-Corpus (https://health.tsinghua.edu.cn/human-scatac-corpus/), a comprehensive database of human scATAC-seq comprising 5,407,621 cells from 35 datasets across 37 tissues or cell lines. To support complementary use cases, each dataset is distributed in three aligned formats: cell-by-candidate cis-regulatory element matrices for cross-dataset integration, raw fragment files for flexible processing, and cell-by-peak matrices for within-dataset analyses. This resource spans diverse biological contexts and includes rich metadata, enabling method benchmarking and development, as well as pretraining of foundation models. The website offers searchable browsing, detailed dataset pages, on-demand downloads, and tutorials. EpiAgent, a foundation model pretrained on Human-scATAC-Corpus, is further integrated to provide online analyses, including reference mapping, embedding extraction, and cell type annotation. Human-scATAC-Corpus establishes a unified and scalable substrate for single-cell epigenomics and is intended to accelerate discovery while standardizing evaluation across tasks. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/674505v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@e2c4c3org.highwire.dtl.DTLVardef@1e3eaf8org.highwire.dtl.DTLVardef@5768c1org.highwire.dtl.DTLVardef@9e96ad_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

METTL13 Promotes Pre-Leukemic Transformation and the Development of Pediatric Leukemia

Post-transcriptional RNA modifications, such as N6-methyladenosine (m6A) methylation and adenosine to inosine (A-to-I) editing, are critical regulators of hematopoietic stem cell (HSC) self-renewal and differentiation, yet their precise contributions to malignant transformation are not fully elucidated. In this study, we uncovered the epitranscriptomic landscape caused by knockdown of genes from the methyltransferase (METTL)-family in hematopoietic stem and progenitor cells (HSPCs). We identified both converging and distinct roles of METTL3 and METTL14, known members of the m6A writer complex, as well as orphan gene METTL13. Notably, METTL13 was uniquely upregulated by adenosine deaminase acting on RNA 1 (ADAR1) overexpression, while other METTL genes were downregulated. Knockdown of METTL13 altered the expression of multiple genes involved in oncogenic development in HSPCs. Furthermore, METTL13 was associated with a high-risk profile in pediatric T-cell acute lymphoblastic leukemia (T-ALL), and functional studies confirmed that METTL13 is required for T-ALL cell proliferation and survival both in vitro and in vivo. Collectively, our results indicate a previously unrecognized, oncogenic role for METTL13 in pre-leukemic transformation and T-ALL pathogenesis. SignificanceIn this study we uncovered a novel regulatory link between ADAR1 and the METTL-family of RNA methyltransferases in hematopoietic stem cells. Overexpression of ADAR1 uniquely upregulated METTL13 while suppressing other METTL genes. Loss of orphan gene METTL13 affected proliferation, apoptosis and p53 signaling in hematopoietic stem cells. Furthermore, loss of METTL13 suppressed cell proliferation and survival in pediatric T-cell acute lymphoblastic leukemia. Our findings suggest a potential role for METTL13 in pre-leukemia transformation and oncogenic development.

cancer biology↗

bioRxiv2025

Positive Selection Screen for Natural Product β-Catenin Inactivators

Many genetically validated targets in cancer, including the transcription factor {beta}-catenin ({beta}-cat), have historically been viewed as undruggable. Cell-based phenotypic screening of chemical compounds can reveal new biological and pharmacological principles. Natural products are powerful probes because of their superior structural diversity, drug-like properties, and biological activities as compared to unoptimized synthetic compounds. We screened 326,304 natural product mixtures (40,744 extracts and 285,560 fractions derived from them) using mammalian cells expressing an oncogenic version of {beta}-cat fused to a suicide protein. Multiple fractions degraded the {beta}-cat fusion protein or drove it into a compartment where both fusion partners were apparently inactive. The active natural product from one of the latter specifically activates novel, but not classical, protein kinase Cs (PKCs) and thereby relocates {beta}-cat to juxtamembrane vacuolar structures. These findings suggest a path for inactivating oncogenic {beta}-cat and underscore the power of screening natural product collections with robust phenotypic assays.

cancer biology↗

bioRxiv2025

Psilocybin triggers an activity-dependent rewiring of large-scale cortical networks

Psilocybin holds promise as a treatment for mental illnesses. One dose of psilocybin induces structural remodeling of dendritic spines in the medial frontal cortex in mice. The dendritic spines would be innervated by presynaptic neurons, but the sources of these inputs have not been identified. Here, using monosynaptic rabies tracing, we map the brain-wide distribution of inputs to frontal cortical pyramidal neurons. We discover that psilocybins effect on connectivity is network-specific: strengthening the routing of inputs from perceptual and medial regions (homolog of default mode network) to subcortical targets, while weakening inputs that are part of cortico-cortical recurrent loops. The pattern of synaptic reorganization depends on the drug-evoked spiking activity, because silencing a presynaptic region during psilocybin administration disrupts the rewiring. Collectively, the results reveal the impact of psilocybin on the connectivity of large-scale cortical networks and demonstrate neural activity modulation as an approach to sculpt the psychedelic-evoked neural plasticity.

neuroscience↗

bioRxiv2025

MSF-CPMP: A Novel Multi-Source Feature Fusion Model for Prediction of Cyclic Peptide Membrane Permeability

Cyclic peptides are becoming attractive molecules for drug discovery because of their properties with inherent stability and structural diversity. However, the high potential of cyclic peptide drugs is challenged by the limited membrane permeability cross cell membrane. To predict cyclic peptide membrane permeability (CPMP), an increased number of computational models or tools are designed and used. But these existing algorithms or models do not appropriately capture feature diversity of cyclic peptides. In this study, we introduce a novel multi-source feature fusion model called MSF-CPMP, which aims to increase the accuracy of predicted CPMP. The MSF-CPMP model incorporates three features extracted from SMILES sequences, graph-based molecular structures, and physicochemical properties of cyclic peptides. By benchmarking with other machine learning and deep learning-based methods, MSF-CPMP achieved the highest levels of the evaluation metrics such as accuracy of 0.9062 and AUROC of 0.9546, and further validated MSF-CPMP robustness in learning capabilities and efficacy of its multi-source fusion. Our result demonstrates that MSF-CPMP outperforms other methods in predicting CPMP, that provides also exemplifies the power of advanced deep learning methods in tackling complex biological challenges, offering contributions to computational biology and clinical treatment. Code is available at https://github.com/wanglabhku/MSF-CPMP Author summaryWe have recognized that cyclic peptides are one type of main macro-molecular drugs useful for treatment of human diseases. However, the structural diversity of cyclic peptides results in limited permeability across cell membranes which is challenging drug research or industrial development. Previously some computational models or tools including machine learning or deep learning ones tried to solve this problem, but they still are not efficient. There are urgent requirement for more effective methodologies. Thus, we introduce a novel multi-source feature fusion model called MSF-CPMP. Our aim is to enhance accuracy and efficiency of predicted CPMP. We carried out evaluation of performance metrics by comparative analysis between MSF-CPMP and other machine learning or deep learning methods. Our result demonstrates that MSF-CPMP outperforms other models in predicting CPMP. We further validated MSF-CPMP robustness in learning capabilities and efficacy of its multi-source feature fusion. In the future we would further improve our methods that can integrate broader biomedicine and biomedical information and provide guide for drug diversity in clinically treating complex human diseases.

bioinformatics↗

bioRxiv2025

Pre-Sequencing Assessment of RNA-Seq Library Quality Using Real-Time qPCR

RNA sequencing (RNA-Seq) is an essential sequencing assay for studying transcriptome profiling. Ribosomal RNA (rRNA) comprises more than 80 - 90% of total cellular RNA, efficient rRNA removal is essential for accurately capturing the transcriptome, particularly to sequence low-abundance mRNAs. Inefficient rRNA removal during library preparation can result from variations in sample quality, preparation methods and handling. Estimating rRNA content in RNA-Seq libraries pre-sequencing is therefore challenging due to the absence of a reliable and cost-effective assessment method. This study addresses the issue by introducing a scalable qPCR-based assay targeting 18S rRNA to evaluate rRNA depletion efficiency pre-sequencing. qPCR efficiency was optimized using serial dilutions of Universal Human Reference (UHR) control and Ct thresholds were established using pilot data from 644 libraries. Following this optimization, analysis of 1,748 Total RNA-Seq libraries and 445 Poly A+ two widely used RNA-Seq library methods, demonstrated a strong correlation between 18S rRNA qPCR results and post-sequencing rRNA rates. This assay was also used to evaluate the performance of Oligo dT beads from four different vendors to enrich mRNA. This 18S rRNA qPCR assay is a cost-effective, scalable approach for reliably predicting rRNA read percentage in RNA-Seq libraries pre-sequencing. Method SummaryThe 18S rRNA-specific qPCR assay is a cost-effective method for evaluating rRNA depletion efficiency in RNA-Seq libraries prior to sequencing by targeting the 18S ribosomal RNA. qPCR efficiency was optimized, and Ct thresholds were set from pilot data and validated across 1,748 Total RNA and 445 Poly A+ RNA-Seq libraries. A Ct threshold of [≥]16 for Total RNA and Ct 13-14 or greater for Poly A+ libraries demonstrates a strong correlation between qPCR results and post-sequencing rRNA read percentages. The assay enables early identification of poorly depleted samples, reducing unnecessary sequencing costs. Additionally, the method was employed to benchmark oligo-dT beads from four vendors, showing its utility in evaluating RNA-seq library preparation kits. This scalable approach supports quality control in both research and high-throughput sequencing environments.

molecular biology↗