Biology subjects

Miao, Y.

Publications and source records attributed to Miao, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Longitudinal Metaproteomic and Lysine Crotonylation Remodeling Defines Clinical Response to Fecal Microbiota Transplantation in Ulcerative Colitis

Background Fecal microbiota transplantation (FMT) can induce steroid-free clinical remission in a subset of patients with ulcerative colitis (UC), but treatment responses remain heterogeneous and are not fully explained by taxonomic microbiome shifts. To define functional molecular features associated with FMT efficacy, we performed integrated longitudinal fecal metaproteomic and lysine crotonylation (Kcr) profiling. Methods We analyzed 87 fecal samples from 23 patients with active UC collected at baseline and at weeks 1, 8, and 12 after FMT. Patients were classified as responders (n = 13) or non-responders (n = 10) according to steroid-free clinical remission at week 12. Across samples, we identified an average of 3,682 proteins and 562 Kcr sites per sample. Results Responders showed greater metaproteomic and meta-crotonylomic complexity at week 12, sustained enrichment of Prevotella and Faecalibacterium, and eight directionally consistent baseline-altered proteins with candidate prognostic value. After FMT, responders exhibited coordinated microbial functional remodeling, including increased proteins involved in short-chain fatty acid (SCFA) metabolism, acyl-CoA-centered pathways, nutrient transport, and polysaccharide degradation, together with attenuation of host neutrophil-related inflammatory protein and Kcr signatures. Non-responders showed minimal or opposing molecular changes. Conclusions: These findings nominate longitudinal fecal metaproteomic and Kcr remodeling as functional molecular readouts of clinical response to FMT in UC and highlight lysine crotonylation as an underexplored metabolite-sensitive layer linking microbial metabolic restoration with host inflammatory resolution.

microbiology↗

bioRxiv2026

Activation of Disease-Associated Polycystin-1 Mutants by Binding of Stalk-derived Agonist Peptides

Polycystin-1 (PC1) functions as an atypical G-protein-coupled receptor (GPCR) with an autocatalytic GAIN domain that cleaves PC1 into extracellular N-terminal (NTF) and membrane-embedded C-terminal (CTF) fragments. Mutations in PC1 are responsible for 85% of autosomal dominant polycystic kidney disease (ADPKD) cases. Activation of signaling by PC1 CTF has been shown to be allosterically mediated by a stalk tethered agonist (TA) and to be prevented by mutations of the stalk. Soluble, synthetic peptides derived from the PC1 stalk were also shown to re-activate signaling by a stalkless CTF mutant. Here, we have investigated the ability of selected stalk peptide agonists p9, p15 or p17 to re-activate signaling by PC1 CTF with ADPKD-associated missense mutations, G3052R or R3063C. Biochemical experimental data showed that each of the three stalk peptides was able to significantly reactivate signaling by the CTF-R3063C mutant. In contrast, signaling by CTF-G3052R could only be rescued by treatment with p17. In parallel, we employed peptide docking and novel Peptide Gaussian-accelerated Molecular Dynamics (Pep-GaMD) simulations to elucidate the binding conformations of p9, p15 and p17 to the PC1 mutants. The simulation findings were highly consistent with experimental data. Furthermore, Pep-GaMD revealed binding conformations of the agonist peptides and important low-energy conformational states of the PC1 CTF, as well as their critical residue interactions. Overall, our complementary approach provides important mechanistic insights into the re-activation of PC1 disease-associated mutants by stalk-derived peptide agonists. Such insights are expected to be valuable for the future design and development of peptide modulators targeting PC1 for an effective ADPKD therapeutic treatment.

bioinformatics↗

bioRxiv2026

An androgen-derived transcriptional state reveals signaling and mitochondrial vulnerabilities in cancer

Transcriptional states can provide functional information beyond genomic alterations, but whether states derived from nonmalignant physiological perturbations remain informative in cancer is unclear. We separated global RNA-output suppression from relative transcriptional remodeling induced by dihydrotestosterone in mouse adrenal zona fasciculata cells and derived a cross-sex transcriptional signature. Projection of this signature to human orthologs defined an androgen-suppressed transcriptional state (ASTS) across cancer cell lines. Integration with pharmacogenomic and CRISPR dependency datasets showed that higher ASTS was associated with resistance to EGFR-targeted drugs and reduced EGFR dependency, together with increased dependency on mitochondrial pathways, including mitochondrial translation and respiratory electron transport. These associations were not attributable to a single major cancer lineage and remained evident after adjustment for canonical oncogenic drivers and cell-state covariates. ASTS provides a proof of concept that an endocrine-derived transcriptional state can reveal candidate functional vulnerabilities in an unrelated cancer context.

cancer biology↗

bioRxiv2026

Gaussian accelerated Molecular Dynamics - Thermodynamic Integration (GaMD-TI): Improved alchemical free energy calculations with enhanced sampling

It is valuable to calculate alchemical free energy changes in drug discovery and development. Thermodynamics Integration (TI) has been widely used in computational chemistry for estimating free energy changes with alchemical transformations. However, TI based on usually short Molecular Dynamics (MD) simulations often suffers from insufficient conformational sampling. Here, we have integrated Gaussian accelerated MD and TI (GaMD-TI) to enhance the conformational sampling and improve accuracy of free energy calculations. GaMD-TI has been demonstrated in model systems of alchemical changes in the Valine dipeptide and mutation cycle of the Alanine <-> Valine <-> Isoleucine (AVI) residues. Simulations showed that when GaMD boost potentials followed near-Gaussian distribution, the free energy change could be reweighted accurately through generalized cumulant expansion to the second order. The total free energy change often exhibited faster convergence using Selective GaMD (SGaMD) than using conventional MD (cMD). Accuracy of the free energy estimates from SGaMD-TI simulations was similar to or higher than those from cMD-TI simulations, although the differences were subtle for these small model systems. Meanwhile, dihedral angles in the model systems underwent significantly more frequent conformational transitions in SGaMD than in cMD, indicating improved sampling. Future studies are planned on larger systems with more complicated alchemical changes, such as ligand binding to proteins/nucleic acids and mutations at biomolecular binding interfaces. GaMD-TI should be broadly applicable to alchemical free energy calculations and therapeutic design.

biochemistry↗

bioRxiv2026

Spatial profiling of pooled mRNA-LNP delivery in vivo with NanoSTAMP

Existing pooled lipid nanoparticle (LNP) screens lack spatial information on formulation localization, cellular uptake, and associated multicellular tissue responses. Here we introduce NanoSTAMP, a spatially resolved, pooled in vivo screening platform for barcoded LNP libraries that uses fluorescence in situ hybridization (FISH)-based barcode readout and is compatible with spatial omics. NanoSTAMP links LNP formulation to cell-type specific uptake, cargo expression, and nearby multicellular neighborhoods within intact tissue, which enables spatially-informed design of RNA delivery, establishing tissue architecture as a dimension of LNP performance.

bioengineering↗

bioRxiv2026

Benchmarking Docking Protocols for GPCR Allosteric Modulators

G protein-coupled receptor (GPCR) allosteric modulators (AMs) offer significant therapeutic advantages over orthosteric drugs, yet structure-based virtual screening lacks validated protocols accounting for the conformational complexity of GPCR allosteric sites. We benchmark docking protocols using PDB experimental structures and structural ensembles derived from Gaussian accelerated Molecular Dynamics (GaMD) simulations across four Class A GPCRs (including the muscarinic M2 and M4 receptors, the {beta}2-adrenergic receptor, and the C-C chemokine receptor type 2) with four programs (Glide HTVS, AutoDock Vina, DOCK3.8, and Boltz-2) against experimentally validated modulator libraries and property-matched decoys. GaMD ensemble docking improved early AM enrichment across all four targets under at least one program. Glide ensemble docking was the only protocol to consistently improve early AM recovery across all four targets, ranking known actives almost exclusively within the top 0.5% of compounds at CCR2 and improving M2R active recovery nearly 9-fold relative to the PDB structure. GaMD free-energy landscape topology governed ensemble re-ranking strategy selection: population-skewed landscapes favored top binding energy ranking (BEmin) while flat, multi-populated landscapes favored average binding energy ranking (BEavg), and at targets with dominant low-energy states, a single GaMD cluster matched or exceeded full ensemble or PDB performance. Taking the union of top percentile hits identified by both ensemble re-ranking methods, BEmin / BEavg, maximizes chemical diversity at the earliest percentiles. Program-specific scaffold recovery biases further motivated a consensus BEmin / BEavg approach to maximize hit diversity. The Boltz-2 deep-learning program showed minimal sensitivity to GaMD templates and underperformed conventional docking, suggesting its affinity predictions complement rather than replace physics- and empirical-based docking approaches for GPCR AM screening.

bioinformatics↗

bioRxiv2026

Before auxin distribution matters: Prepatterning of the Arabidopsis embryo axis by MPK6-dependent AUX/IAA8 phosphorylation

In growth and development of plants, the signaling molecule auxin plays an instrumental role. Many patterning processes are controlled by auxin signaling in a self-organizing matter. After fertilization, such a patterning process needs to be started for the first time during plant life. Contrary to previous models, we show that the first differential auxin response that separates embryonic from extra-embryonic development in the two zygotic daughter cells happens independently of a detectable auxin gradient. Instead, differential phosphorylation of the transcriptional inhibitor Aux/IAA8 by MAP kinase signaling leads to differences in auxin sensitivity between the two daughter cells, initiating embryonic development in the apical cell. IAA8 phosphorylation in the basal cell prevents proteasomal degradation, suppressing canonical auxin responses, which initiates extra-embryonic development. MAP kinase signaling therefore precedes auxin gradients and prepatterns the apical-basal axis independently of an auxin gradient.

plant biology↗

bioRxiv2026

An improved Stentor coeruleus genome and time-resolved transcriptomics link cyclic nucleotide-dependent kinase signaling to single-cell habituation

The giant ciliate Stentor coeruleus is a single cell capable of modifying its behavior through experience. When repeatedly disturbed, it undergoes habituation, a simple and widely conserved form of non-associative learning, despite lacking a nervous system. How a single cell achieves such behavioral plasticity at the molecular level remains poorly understood. Here, we report a compact, contiguous macronuclear reference genome for S. coeruleus, substantially improving genome continuity and annotation quality while resolving two successive rounds of whole-genome duplication and extensive lineage-specific gene-family expansion. Anchoring time-resolved transcriptomics to this reference, we profiled pooled RNA from behaviorally tracked cells collected at defined points during a mechanical stimulation paradigm and identified 341 genes with significant temporal expression dynamics during habituation. The dominant transcriptional signature of habituation was the coordinated, sustained up-regulation of a conserved cyclic nucleotide, calcium, and phosphatase signaling module centered on five cGMP-dependent protein kinase (PKG) paralogs together with a voltage-gated calcium channel and a protein phosphatase 2A regulatory subunit, representing conserved intracellular components of the neuronal long-term depression (LTD) pathway. By integrating an improved genome with time-resolved transcriptomics of habituation, this work provides a community resource for Stentor and identifies a conserved signaling program as a candidate molecular framework underlying single-cell habituation.

molecular biology↗

bioRxiv2026

Teneurins Are SPARCL1 Receptors

Extensive experiments document that SPARCL1, a secreted protein that is produced primarily by astrocytes in brain and endothelia throughout the body and that is also known as Hevin, enhances synapse formation. However, the mode of action of SPARCL1 at synapses remains unclear owing to divergent results in the literature. Here, we use cultured neurons from newborn male and female mouse embryos to show that the C-terminal follistatin-like and Ca2+-binding domains of SPARCL1, which account for only 35% of the total SPARCL1 sequence, are sufficient to potently enhance synapse numbers. SPARCL1 acts at nanomolar concentrations at which SPARCL1 does not robustly bind to neurexins, neuroligins or neurexin/neuroligin complexes but avidly interacts with all teneurins. Strikingly, the follistatin-like domain of SPARCL1 on its own strongly binds to teneurins but is unable to stimulate synapse formation. Only when combined with the SPARCL1 Ca2+- binding domain does the follistatin-like domain induce synapses, suggesting that SPARCL1 enhances synapse numbers by binding to teneurins via its C-terminal follistatin-like domain and by activating synapse formation via its Ca2+-binding domain. SIGNIFICANCE STATEMENTSPARCL1 (also known as Hevin) is a synaptogenic factor that is produced primarily by astrocytes in brain, and that enhances synapse formation. How SPARCL1 acts at synapses, however, remains unclear because divergent results describe its binding partners at synapses and the sequences involved in its synaptogenic activity remain unclear. In the present study, we show that SPARCL1 avidly binds to the presynaptic teneurins adhesion molecules, that this binding is mediated by its small follistatin-like domain, and that its synaptogenic activity requires both its follistatin-like and its Ca2+-binding EC domains. Thus, our results suggest that SPARCL1 is recruited to developing synapses by binding of its follistatin-like domain to teneurins and then induces synapse assembly via its Ca2+-binding domain.

neuroscience↗

bioRxiv2026

Multiscale harmonization and semantic integration of biomedical data enable biological insights through immersive exploration

Single-cell atlassing efforts like the Human BioMolecular Atlas Program (HuBMAP) and the Cellular Senescence Network (SenNet) are producing multiscale datasets across the healthy, adult, human body, but this data is typically explored only on 2D screens with limited 3D affordances, even though understanding a cells location within a tissue, organ, and body requires reasoning across many orders of spatial magnitude. The Human Reference Atlas (HRA) provides standard terminologies and a Common Coordinate Framework (CCF) for harmonizing such data spatially and semantically. Building on the HRA Organ Gallery in virtual reality (VR) application, we present "HRA: Powers of Ten," which integrates, harmonizes, and visualizes biological data from these efforts immersively in VR using a Multiscale Elevator System that lets users descend, like riding an elevator through an inverted skyscraper, from a whole body view of 81 reference organs to datasets across 5 organs (lymph node, brain, large intestine, small intestine, liver), 5 assay types (CODEX, Visium, v-CyCIF, Xenium, SBF-SEM), and 4 spatial scales. Contributed by Data Providers, these VR scenes enable biological insights into senescence patterns, cellular neighborhoods, 3D tissue reconstruction, and subcellular liver architecture. A standard operating procedure supports adding further datasets. Freely available on the Meta Store to over 20 million headset owners, the application, data, and code are open-source.

bioinformatics↗

bioRxiv2026

PEC: a robust algorithm to reconcile pedigree and SNP-chip data on the basis of LD block, haplotype information, and Mendelian conflicts

MotivationPedigree errors frequently occur in livestock populations due to long-term manual record-keeping, which reduces the efficiency of breeding programs. Although several pedigree correction methods exist, their practical application is often limited by complicated procedures, high computational cost, and insufficient accuracy. Therefore, an effective and efficient solution for pedigree error correction is needed. ResultsWe developed a new algorithm and software, PEC, to accurately and efficiently correct pedigree errors. The method matches haplotype fragments between candidate parents and offspring using estimated linkage disequilibrium patterns and subsequently checks for Mendelian conflicts to adjust the pedigree. Using simulated pig datasets, we compared PEC against SeekParentF90 and AlphaAssign in terms of accuracy, memory usage, and computation time. PEC demonstrated superior performance across all metrics. Furthermore, application of single-step genomic best linear unbiased prediction (ssGBLUP) in a real pig population showed that PEC corrected pedigrees significantly improved the accuracy and unbiasedness of genomic evaluations, highlighting the importance of pedigree error correction. AvailabilityThe PEC software is freely available at https://github.com/TXiang-lab/JPEC.

genetics↗

bioRxiv2026

Structural basis of MK-97 positive allosteric modulation at the M4 mAChR

Positive allosteric modulators (PAMs) of the M4 muscarinic acetylcholine receptor (mAChR) represent a promising therapeutic strategy for treating cognitive deficits and neuropsychiatric disorders. While first-generation M4 mAChR PAMs, like LY2033298, demonstrated proof-of-concept, second-generation compounds, such as MK-97, exhibit substantially improved potency and reduced species variability. Here we report the cryo-EM structure of the M4 mAChR bound to the endogenous agonist, acetylcholine, and MK-97 at 2.7 [A] resolution, revealing the molecular basis for improved M4 mAChR PAM activity. MK-97 adopts a distinctive boomerang-shaped conformation within the extracellular-facing allosteric binding site, with a central pyridine vertex, a lower cyclopentylmethylpyrazole arm extending toward the floor of the orthosteric site, and an upper isoindolinone arm projecting toward extracellular loop 2 (ECL2). This extended binding mode establishes a distributed interaction network across transmembrane helices TM2, TM3, TM5, TM6, and TM7, with key contacts including a hydrogen bond with Y922.64 and a {pi}-{pi} stacking interaction with W4357.35. Integration of structural data, molecular dynamics simulations, and mutagenesis validation reveals that the high affinity of MK-97 derives from optimized engagement across all three binding regions rather than dependence on any single critical contact. Insights from comprehensive structure-activity relationship (SAR) studies provide a molecular framework for the rational design of next-generation M4 mAChR PAMs with improved pharmacological properties. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=70 SRC="FIGDIR/small/723386v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@75cb90org.highwire.dtl.DTLVardef@1876c9corg.highwire.dtl.DTLVardef@1eba8d0org.highwire.dtl.DTLVardef@9818ad_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2026

Foundation cell segmentation models performance on live microscopy and spatial-omics data

Accurate cell segmentation is an essential step for quantitative analysis of biological imaging data. Recent advances in deep learning have led to the development of generalist segmentation models that perform robustly across multiple imaging modalities, including label-free phase contrast, fluorescence cell culture, and multiplexed fluorescence tissue imaging. However, systematic comparisons of these models at the level of downstream biological analysis remain limited. To address this gap, we evaluated several recent segmentation models, including Cellpose cyto3, Cellpose-SAM, {micro}SAM, and CellSAM, on phase contrast and fluorescence cell culture images. In addition, Mesmer and InstanSeg were included for benchmarking on multiplexed fluorescence tissue images generated using CO-Detection by IndEXing (CODEX). We found that Cellpose-SAM achieved strong performance on phase contrast images, while SAM-based models consistently performed well on fluorescence cell culture data. In contrast, no single model consistently outperformed others on CODEX datasets. Instead, each model exhibited distinct strengths and limitations, which led to differences in downstream analyses, including clustering and cell type identification. Together, our study emphasizes the importance of selecting segmentation models based on dataset characteristics and analytical goals, rather than relying on a single universal approach.

bioinformatics↗

bioRxiv2026

Engineering age-adaptive mRNA lipid nanoparticle cancer vaccines via reprogramming systemic gene expression

Lipid nanoparticle (LNP)-based mRNA vaccines have transformed cancer immunotherapy, yet their efficacy in older individuals, who represent the majority of cancer patients, remains poorly understood. Here, we uncover a critical and previously underappreciated barrier to mRNA LNP cancer vaccine performance in aged hosts: impaired systemic transgene expression. Using the SM-102 mRNA LNPs as a benchmark formulation, we show that while local immune activation and antigen presentation at the injection site and draining lymph nodes remain largely intact with age, transgene expression in peripheral organs, including the liver, lungs, and spleen, is markedly reduced. This deficit limits the magnitude and durability of CD8 and CD4 T cell responses and substantially compromises tumour control. Transcriptomic profiling further reveals that attenuated transgene expression parallels broad attenuation of antigen processing, presentation, and activation pathways in immune cells from aged animals, implicating impaired systemic mRNA translation as a central driver of the downstream immune defects and antitumour efficacy loss. Building on these insights, we identify a rationally selected LNP formulation that reestablishes distal antigen expression across age groups as an engineering strategy to revive T cell immunity, achieving full rescue of therapeutic efficacy in aged mice without additional intervention. Together, these findings establish systemic mRNA translation as a tuneable lever of vaccine performance and highlight that optimizing LNP formulations to sustain systemic transgene expression across age groups may enable next-generation, age-adaptive mRNA vaccines for cancer and other diseases of aging.

bioengineering↗

bioRxiv2026

Fatty acid scavenging enables cancer escape from KRAS inhibition

Although inhibitors of oncogenic KRAS have shown clinical efficacy1, resistance to KRAS inhibition is common2, and its molecular basis remains unclear. Here we show that KRASi-resistant cancer cells sustain mitochondrial bioenergetics through enhanced fatty acid (FA) metabolism, despite suppression of canonical KRAS signaling. Specifically, KRASi-resistant pancreatic cancer cells exploit macropinocytosis to scavenge FA released from adipose tissue, fueling beta-oxidation independently of KRAS-PI3K signaling. This adaptive metabolic program is driven by the adhesion G protein-coupled receptor ADGRB1, which activates non-canonical PI3K{gamma}-PAK1 signaling to stimulate macropinocytosis and maintain metabolic homeostasis under KRASi. Disruption of ADGRB1-PI3K{gamma} signaling dismantles this metabolic program and restores KRASi sensitivity. This pathway operates across multiple KRAS-mutated cancers and is associated with poor therapeutic response and outcome. These findings offer a promising strategy for overcoming KRASi resistance.

cancer biology↗

bioRxiv2026

Complete genome-derived metabolic interactions reveal impact of gut ecology on human health

Metabolic interactions govern gut microbiome assembly, yet functional rules remain obscured by genomic incompleteness and fragmentation. Here, we leverage 1,150 complete genomes to construct genome-scale metabolic models, demonstrating that draft genomes introduce systemic artifacts missing critical transport functions. We observe that metabolic interactions are intrinsically driven by genomic traits and niche specialization rather than random association. We stratifies strains into four ecological groups, including active players, resource predators, utilizers, and contributors, each of which exhibits distinct metabolite exchange/competition signatures. This functional architecture is strongly coupled to secondary metabolism. Applying this framework to inflammatory bowel disease revealed distinct temporal dynamics of ecological groups across disease subtypes, where group-specific dysbiosis predicted clinical phenotypes better than whole community profiles. Furthermore, integrating metabolic and co-occurrence networks to identify keystone for classifiers as features significantly improved disease diagnosis. Our study provides novel insights into gut metabolic interaction landscape, bridging the gap between genomic potential and clinical utility for precision microbiome therapeutics.

microbiology↗

bioRxiv2026

Imaging Intrinsic Stochastic Magnetic Fluctuations in Living Cells

SignificanceThis work establishes a probabilistic magnetometry framework for detecting weak stochastic magnetic fluctuations at the nanoscale, which provides the first quantitative access to intrinsic magnetic activity in living cells. Weak stochastic magnetic fluctuations at nanoscale are difficult to quantify. In living cells, ionic transport and molecular currents generate electromagnetic activity whose magnetic component is likewise nanoscale, weak, stochastic, and rapidly varying and has therefore remained experimentally inaccessible. Here we introduce Bio-Spin Probabilistic Inference (BISPIN), a digital statistical framework that can quantify weak, stochastic magnetic fluctuations at the nanoscale. Using threshold-resolved signals from enhanced nitrogen-vacancy quantum sensors, BISPIN converts unstable analog magnetic readouts into statistically convergent digital observables and infers fluctuation strength through probabilistic modeling, enabling robust quantification under random sensor orientations and biological heterogeneity within the experimental bandwidth. Applied to living cells, this approach distinguishes live from fixed cells, resolves agonist-induced activation, and maps subcellular variations in magnetic fluctuation strength. By providing the first quantitative access to intrinsic stochastic magnetic fluctuations in living cells, this work establishes a probabilistic magnetometry framework for cellular electrodynamics and opens a new magnetic dimension of cellular phenotyping for bio-spin omics.

biophysics↗

bioRxiv2026

Isoform-resolved spatial transcriptomics on a lab-made high-density array via a single-chip NGS-TGS workflow

High-resolution spatial transcriptomics is still cost-prohibitive and dominated by short-read sequencing, limiting in situ detection of transcript structures. Here we present a low-cost, lab-made, high-density bead-in-microwell chip assembled by routine centrifuge and decoded by a tri-part combinatorial long-barcode strategy. The design provides 5.6x107 barcode combinations across 4.1x10{square} capture sites, reducing collisions while remaining tolerant to third-generation sequencing raw errors. Using a single-chip, dual-platform workflow, we split full-length cDNA for next-generation and third-generation sequencing within the same spatial coordinates. In an incompatible tomato-pepper graft, we identified interface-associated splicing reprogramming, including thousands of unannotated isoforms, enriched novel CaGRP1 isoforms, and SlPIP2 intron retention, supported by individual long-read sequences. In mouse embryos, we further demonstrate cross-species applicability by resolving unannotated Col1a2 isoforms in oligodendrocyte progenitors and spatially restricted Dalrd3 intron retention. This cost-efficient system broadens access to spatial full-length transcriptomics and may support diverse biological studies.

plant biology↗