Biology subjects

Qian, Q.

Publications and source records attributed to Qian, Q..

At least 19 recordsLinked to original sources

bioRxiv2026

Rational Design of 5' UTRs for Optimized mRNA Expression and Cost-Effective, Rapid Analysis of Capped mRNA

In vitro-transcribed (IVT) messenger RNA (mRNA) therapeutics require rigorous quality control of 5' capping efficiency and 3' poly(A) tail length, both of which constitute critical quality attributes (CQAs). Current analytical workflows for these CQAs rely on hybridization with nucleic acid probes and biotin-based affinity purification, which constrain throughput and increase per-assay cost. Here, we report a rationally designed 5' untranslated region (5' UTR) that sustains high translational efficiency while enabling probe-free, one-step purification for rapid quantification of capping efficiency and poly(A) tail length distribution. This approach exploits a strategically engineered 5' UTR incorporating a purine-only RNase A-resistant fragment terminating at a single pyrimidine cleavage site, together with a translation-enhancing element comprising an N6-methyladenosine (m6A) deposition motif and an 18S rRNA complementarity sequence. This dual-function design accommodates GA-rich sequence segments without compromising mRNA translational output. Compared with conventional probe- and biotin-dependent workflows, the present method substantially reduces cost and processing time and is compatible with simultaneous detection of segmented AmGn poly(A) tail variants. This integrated platform provides a simplified, probe-free and construct-universal for high-throughput in-process control (IPC) of mRNA therapeutics.

bioengineering↗

bioRxiv2026

RamiGlyph Captures Microglial Morphological Diversity and Predicts Functional States in Ischemia Reperfusion and Amyloid Pathology

Microglia are resident immune cells of the central nervous system, whose ramified processes rapidly remodel in response to injury. However, how to capture subtle morphological changes and whether functional state can be predicted from morphology remain open questions. Here, we present RamiGlyph, a contrastive learning framework integrating topological and structural features, trained on more than 20,000 reconstructed microglia. RamiGlyph not only distinguishes physiological and pathological states of microglia but also generalizes to neuronal cell type classification. Projection of microglia morphological embeddings revealed a continuum rather than discrete classes, from which a morphology score was derived to quantify dynamic process remodeling. To link morphology with function, Gromov Wasserstein optimal transport was used to align unpaired morphological and functional data across stages of ischemia reperfusion injury and amyloid pathology. These alignment results enable prediction of microglial functional states using RamiGlyph embeddings alone, with prediction reliability increasing upon cell aggregation. In summary, RamiGlyph provides a robust framework for resolving continuous microglial morphological variation and linking morphology to functional states across acute and chronic neuropathological contexts.

bioinformatics↗

bioRxiv2026

Ensemble tests mask missing dynamics in protein conformational generators

Protein generators are increasingly used to produce conformational ensembles and trajectories as faster alternatives to molecular dynamics (MD). Yet whether agreement with an equilibrium ensemble demonstrates that a generator has learned dynamics remains unresolved. Here we show that this evidence survives the destruction of dynamics. Randomly reordering authentic MD frames leaves ensemble fidelity unchanged but reduces the geometrically gated kinetic pass rate from 0.963 to 0.004; an independent MD replicate reaches 0.95 under the same test. Dynbench separates recovery of conformational states, time-dependent behaviour and trajectory admissibility. Public generators that appear similar under ensemble tests separate sharply, and in a prospective 36-protein lockbox the reference and floor remain stable while two models reverse order. Ensemble tests can therefore systematically overstate evidence of learned dynamics, establishing time-resolved validation as a distinct requirement for claims about protein dynamics generators.

bioinformatics↗

bioRxiv2026

Molecular dynamics descriptors for 1,079 post-translationally modified protein systems

Databases of post-translational modifications (PTMs) catalogue modified sites and increasingly add static structural context, but trajectory-derived descriptors remain scattered across specialised tools and general molecular dynamics archives. Dyna-MO PTM brings together 1,079 AlphaFold 3-seeded systems covering lysine acetylation, lysine and arginine monomethylation, and serine, threonine and tyrosine phosphorylation. Each system is linked to three completed 10 ns replicas generated with CHARMM36m and TIP3P, for 32.37 s of aggregate sampling. A 118-column table joins simulation and quality-control provenance with global relaxation measures, site solvent exposure, rotamers, secondary structure and ionic-contact proxies. Versioned identifiers connect the records to starting structures, trajectories, manifests and analysis scripts. Researchers can use the resource to filter PTM contexts, reproduce descriptors, prioritise longer simulations and evaluate trajectory-analysis or generative methods. The trajectories describe finite-window relaxation rather than equilibrium free energies, kinetics or matched PTM effects.

biophysics↗

bioRxiv2026

A GPX4 phosphorylation switch by FGFR1 guards against ferroptosis

Ferroptosis is driven by lipid peroxidation, yet the mechanisms by which cells rapidly adjust their sensitivity to ferroptosis in response to extracellular cues remain elusive. We identify a direct phosphorylation switch controlling the activity of glutathione peroxidase 4 (GPX4), the core ferroptosis regulator. The receptor tyrosine kinase FGFR1 directly binds and phosphorylates GPX4 at Tyr180/Tyr196 in a kinase-dependent manner, requiring its Tyr730 as a docking site. This phosphorylation enhances GPX4s catalytic activity and suppresses ferroptosis. In cardiac ischemia/reperfusion injury, the FGFR1-GPX4 axis is suppressed, and a selective FGFR1 agonist (FGF-1{Delta}NT) reactivates it to protect against ferroptosis-mediated damage. Critically, a phosphorylation-deficient GPX4 knock-in mouse exhibits hypersensitivity to injury and non-responsive to this agonist, proving that GPX4 phosphorylation is essential. Our findings reveal a rapid mechanism for regulating ferroptosis via GPX4 tyrosine phosphorylation, directly linking receptor tyrosine kinase signaling to ferroptosis, and offering new strategies for treating ischemic-and other ferroptosis-associated diseases.

Cell Biology↗

bioRxiv2026

An Engineered Halotolerant Chimeric T7 RNA Polymerase for High-Yield, Low-Immunogenicity Synthesis of RNA via Simple Batch Transcription

The rapid advancement of mRNA therapeutics has imposed stringent requirements on both the quality and scalability of in vitro transcription (IVT) products. However, the accumulation of double-stranded RNA (dsRNA) byproducts and 3-terminal heterogeneity during T7 RNA polymerase (T7 RNAP)-mediated transcription can robustly trigger deleterious innate immune responses and compromise translation efficiency. Existing enzyme engineering strategies frequently struggle to reconcile the trade-offs between salt tolerance, volumetric productivity, and product purity. Here, we report a novel engineering strategy for halotolerant T7 RNAP by fusing optimized mutant polymerases with diverse DNA-binding domains (e.g., Sso7d, MC1). This approach orchestrated the development of a series of chimeric T7 RNAP mutants designed to bolster catalytic activity and template selectivity under high-salt conditions while concurrently suppressing RNA-dependent RNA polymerase (RdRP) activity. Our lead chimeric mutants exhibited exceptional salt tolerance and processivity in the presence of up to 270 mM NaCl. Notably, these mutants significantly diminished dsRNA formation to less than 0.001%, while markedly improving transcript integrity and 3 homogeneity, thereby facilitating superior translation efficiency for both linear mRNA and circular RNA (circRNA). Crucially, this heightened salt tolerance does not necessitate a trade-off in RNA yield, affording broader flexibility for downstream process optimization. In an enzymatic circRNA synthesis system, these mutants enabled a non-fed-batch configuration with high initial rNTP concentrations (15 mM each), resulting in a 50% increase in yield and achieving an unprecedented titer of 15 mg/mL. This research provides a robust enzymological solution that harmonizes quality and productivity for the industrial-scale manufacturing of high-concentration, low-immunogenicity RNA.

genomics↗

bioRxiv2026

ProteinFlux: accurate, rapid and scalable generative prediction of protein dynamics driven by post-translational modifications

The function of proteins, the building blocks of life, in health and disease depends not only on their 3D-conformational states but most importantly on the dynamic transition between states controlled by a wide array of post-translational modifications (PTMs). Recent major advances have been made in our ability to predict static 3D structures; however, understanding and predicting the impact of PTMs on protein conformational dynamics remains a major question and challenge in the field. Molecular dynamics (MD) simulation remains the major computational approach for studying protein dynamics. However, the high computational cost, lack of integration of PTMs as conditioning inputs and inefficient generation of continuous protein dynamics largely precludes PTM-regulated conformational dynamics and the study of slow conformational processes. To address this critical bottleneck, we developed ProteinFlux, a flow-matching generative framework that links PTM-conditioned conformational dynamics to evolutionary constraints encoded by PTM sites. Evolutionary information plays a critical role in capturing conformational dynamics beyond sequence identity, and PTM sites inherently encode evolutionary constraints critical to protein functional regulation. We therefore built FluxSite, a dual-modal PTM site predictor that integrates sequence evolutionary information and 3D structural features to generate a continuous conditional signal encoding conservation and functional importance for each predicted site. FluxSite achieves robust generalization across 18 PTM types and 30 disease-associated proteomes. ProteinFlux generates phosphorylation-conditioned, all-atom conformational trajectories across diverse protein fold classes, faithfully reproducing both thermodynamic properties such as free energy landscapes and kinetic features such as conformational transition pathways. It outperforms state-of-the-art predictors while achieving inference speeds several orders of magnitude faster than traditional MD. In addition, we introduce DynaMo-phos, a benchmark dataset of phosphorylated protein MD simulations. Together, ProteinFlux, FluxSite and DynaMo-phos provide a scalable, high-throughput platform for elucidating PTM-driven conformational mechanisms, with potential applications across allosteric drug design, functional annotation of disease-associated modifications and mechanism-guided therapeutic development.

bioinformatics↗

bioRxiv2026

LNGCN: A Distance-Aware Dynamics Network for Protein-Protein Interaction Prediction

High-throughput PPI screening requires not only interaction discrimination but also stable, calibrated scores for candidate prioritization and efficient experimental allocation. Conventional graph neural networks may over-smooth deep residue representations, reducing score separation among high-confidence candidates. We therefore developed LNGCN, a distance-aware continuous-time graph framework for experimental PPI prioritization. LNGCN integrates residue-level structural graphs with liquid neural dynamics, uses radial distance to drive continuous graph evolution, and applies hierarchical calibration to convert raw outputs into prioritization scores. It performed robustly on balanced human, 1:10 imbalanced, and cross-species yeast bench-marks. On the imbalanced dataset, the top 5% of candidates achieved 85.1% precision. LNGCN also preserved residue-level representation diversity better than conventional GCN variants. In FGF23-FGFR1c--Klotho, SHP2 signaling, Tdk1 oligomer-dependent binding, and a TPR study, it enriched known partners near the ranking top, and experimentally supported novel interactions. Overall, LNGCN enables sustained enrichment of experimentally relevant PPI candidates.

bioinformatics↗

bioRxiv2026

Sex stratified analyses enable new genetic insights into brain imaging phenotypes

Sex differences are commonly observed in neuroimaging phenotypes and in the risk of brain diseases, yet the underlying genetic mechanisms remain poorly understood. We investigated sex differences in the genetic architecture of 805 neuroimaging phenotypes in 22,950 males and 22,950 females matched for sample size and covariates, and systematically compared sex-stratified with sex-combined genetic analyses. We found eight variant-trait associations with significant sex differences, 235 fine-mapped sex-dominant causal associations, 457 sex-dominant colocalizations with sex hormones, and 96 sex-dominant colocalizations with schizophrenia. Compared with sex-combined analysis, sex-stratified analysis identified 47 new genetic associations, 170 new fine-mapped causal associations, 1,019 new colocalizations with sex hormones, and 191 new colocalizations with schizophrenia. Additionally, sex-stratified analysis improved global heritability and genetic-correlation estimates and enhanced polygenic prediction for certain phenotypes. This work highlights the need to routinely perform sex-stratified genetic association analyses to elucidate sex-specific and sex-shared genetic control of neuroimaging phenotypes and related disorders.

genetics↗

bioRxiv2026

Tumour neoantigen repertoire prediction in malignant peripheral nerve sheath tumours define private and public targets for immunotherapy

Malignant peripheral nerve sheath tumours (MPNSTs) are high grade soft-tissue sarcomas with an unmet need for novel therapies. Tumour antigen-based approaches, including neoantigen and tumour-associated antigens (TAA) directed therapies, offer potential opportunities for immunotherapy. Here, we integrated public domain tumour DNA and RNA sequencing data with in-silico predictions in order to characterise the potential (neo)antigenic landscape of MPNST. We stratified the computational predictions across the two known sub-groups of MPNST, those associated without and with Polycomb Repressor Complex 2 (PRC2) loss of function variants (PRC2-Loss). Using pVACtools, computationally identified high-confidence neoantigens based on predicted pMHC affinity were derived from somatic mutations and gene fusions, as well as recurrently overexpressed cell-surface TAAs. All predicted neoantigens were private to individual MPNST cases and across both tumour subtypes. Using ImSig and CIBERSORTx, PRC2-Loss tumours displayed reduced immune infiltration with downregulation of antigen processing and presentation pathways compared to PRC2-WT, confirming known intrinsic constraints to effective neoantigen-directed immune priming. Moreover, PRC2-Loss MPNSTs demonstrated recurrent copy number driven overexpression of cell surface TAAs derived from chromosome 8 amplification, providing potential immunotherapeutic targets that are pMHC independent. Overall, these predictive findings confirm a PRC2-independent private immuno-antigenic peptide repertoire, with an immune resistant MPNST microenvironment in PRC-Loss. These data provide further impetus for personalised functional validation and immune based treatment strategies, including personalised neoantigen vaccines and cell surface protein TAA-directed therapies dependent on PRC2 status.

cancer biology↗

bioRxiv2026

SCALE: Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction

Virtual cell models aim to enable in silico experimentation by predicting how cells respond to genetic, chemical, or cytokine perturbations from single-cell measurements. In practice, however, large-scale perturbation prediction remains constrained by three coupled bottlenecks: inefficient training and inference pipelines, unstable modeling in high-dimensional sparse expression space, and evaluation protocols that overemphasize reconstruction-like accuracy while underestimating biological fidelity. In this work we present a specialized large-scale foundation model SCALE for virtual cell perturbation prediction that addresses the above limitations jointly. First, we build a BioNeMo-based training and inference framework that substantially improves data throughput, distributed scalability, and deployment efficiency, yielding 12.51* speedup on pretrain and 1.29* on inference over the prior SOTA pipeline under matched system settings. Second, we formulate perturbation prediction as conditional transport and implement it with a set-aware flow architecture that couples LLaMA-based cellular encoding with endpoint-oriented supervision. This design yields more stable training and stronger recovery of perturbation effects. Third, we evaluate the model on Tahoe-100M using a rigorous cell-level protocol centered on biologically meaningful metrics rather than reconstruction alone. On this benchmark, our model improves PDCorr by 12.02% and DE Overlap by 10.66% over STATE. Together, these results suggest that advancing virtual cells requires not only better generative objectives, but also the co-design of scalable infrastructure, stable transport modeling, and biologically faithful evaluation.

cell biology↗

bioRxiv2025

EC-isHCR: a rapid method for in situ hybridization chain reaction in diverse animal samples

The in situ hybridization chain reaction (isHCR) visualizes RNA across multiple spatial scales, from organs to subcellular structures, in diverse samples. We previously proposed a rapid protocol, EC-isHCR, for Drosophila embryos and ovaries. Whether EC-isHCR retains the features of conventional isHCR, including wide-spatial-scale analyses in various samples, however, has remained unclear. Here, we show that EC-isHCR enables robust RNA detection in a broad range of samples, such as whole-mount fruit fly, parasitoid wasp, and aphid preparations; paraffin sections of trout; frozen mouse sections; and human cultured cells. Moreover, EC-isHCR enabled detection of subcellular RNA localization. EC-isHCR also visualized co-localization of RNA with phase-separated condensates in fruit fly embryos and detected the protrusion-enriched mRNA in HeLa cells. To broaden the applicability of EC-isHCR, we developed an automated probe design tool (https://github.com/ShuntaYorimoto/hcrkit). By combining this tool with EC-isHCR, we provide a fast and versatile framework to visualize mRNAs. This framework will help reduce the barrier to using fast isHCR and thereby facilitate research across diverse areas of the life sciences. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/696653v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1852584org.highwire.dtl.DTLVardef@621682org.highwire.dtl.DTLVardef@1b3bf5corg.highwire.dtl.DTLVardef@1d86841_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- EC-isHCR enables rapid acquisition of high-contrast images. - EC-isHCR preserves features of conventional isHCR, including versatile sample compatibility and high-resolution imaging. - An automated probe design tool was developed for EC-isHCR. - EC-isHCR/probe tool framework will help reduce the barrier to using fast isHCR.

bioengineering↗

bioRxiv2025

Xrp1 drives damage-induced cellular plasticity of enteroendocrine cells in the adult Drosophila midgut

Cellular plasticity, the ability of a differentiated cell to adopt another phenotypic identity, is restricted under basal conditions, but can be elicited upon damage to facilitate regeneration. Such damage-induced cellular plasticity restores homeostasis and prevents pathology, yet its underlying molecular basis remains largely unexplored. Here, we reported damage-induced cellular plasticity of secretory enteroendocrine cells (EEs) in the adult Drosophila midgut. We found that ionizing radiation enhanced EE plasticity such that it promoted EEs to dedifferentiate into ISCs and subsequently re-differentiate towards ECs. We identified that radiation induced the production of a stress-inducible transcription factor Xrp1 in EE lineages, and its upregulation was necessary for EE plasticity. Single-cell RNA sequencing of guts with EE-specific Xrp1 overexpression revealed ectopic expression of progenitor-specific genes in EEs, which was necessary for Xrp1 to drive EE plasticity. Our work provides a mechanistic framework for understanding cellular plasticity and suggests its potential role in damage-induced responses.

cell biology↗

bioRxiv2025

Thermogenic Adipose ADH5 Counteracts Age-related Metabolic Decline

Aging-associated decline in brown adipose tissue (BAT) function and mass contributes to energy and metabolic homeostasis disruption. Alcohol dehydrogenase 5 (ADH5) is a major denitrosylase that prevents cellular nitro-thiol redox imbalance, an essential feature of aging. However, the functional significance of BAT ADH5 in the context of aging is largely unknown. Here, we aimed to investigate the role of BAT ADH5 in protecting against age-related metabolic dysfunction. We show that aging elevates BAT protein S-nitrosylation modification and downregulates ADH5 in mice. Furthermore, BAT ADH5-deletion accelerates BAT senescence and aging-associated declines in metabolic homeostasis and cognition. Mechanistically, we found that aging inactivates BAT Adh5 by suppressing heat shock factor 1 (HSF1), a well-recognized proteostasis regulator. Moreover, pharmacologically enhancing HSF1 improved age-related BAT senescence, metabolic decline, and cognitive dysfunction. Together, these findings suggest that the BAT HSF1-ADH5 signaling cascade plays a key role in protecting against age-related systemic functional decline. Ultimately, unraveling the role of thermogenic adipose nitrosative signaling will provide novel insights into the interplay between BAT nitric oxide bioactivity and metabolism in the context of aging. HighlightsO_LIAging elevates general protein S-nitrosylation while downregulating ADH5 expression in BAT. C_LIO_LILoss of thermogenic adipose tissue ADH5 accelerates BAT senescence and exacerbates aging-associated metabolic and cognitive dysfunctions. C_LIO_LIDisruption of HSF1-activated Adh5 in BAT contributes to aging-associated metabolic and cognitive impairments. C_LIO_LIPharmacological targeting of BAT HSF1 alleviates aging-related BAT senescent and systemic declines. C_LI

physiology↗

bioRxiv2025

Population-specific brain charts reveal Chinese-Western differences in neurodevelopmental trajectories

Human brain charts provide unprecedented opportunities for decoding neurodevelopmental milestones and establishing clinical benchmarks for precision brain medicine 1-7. However, current lifespan brain charts are primarily derived from European and North American cohorts, with Asian populations severely underrepresented. Here, we present the first population-specific brain charts for China, developed through the Chinese Lifespan Brain Mapping Consortium (Phase I) using neuroimaging data from 43,037 participants (aged 0-100 years) across 384 sites nationwide. We establish the lifespan normative trajectories for 296 structural brain phenotypes, encompassing global, subcortical, and cortical measures. Cross-population comparisons with Western brain charts (based on data from 56,339 participants aged 0-100 years) reveal distinct neurodevelopmental patterns in the Chinese population, including prolonged cortical and subcortical maturation, accelerated cerebellar growth, and earlier development of sensorimotor regions relative to paralimbic regions. Crucially, these Chinese-specific charts outperform Western-derived models in predicting healthy brain phenotypes and detecting pathological deviations in Chinese clinical cohorts. These findings highlight the urgent need for diverse, population-representative brain charts to advance equitable precision neuroscience and improve clinical validity across populations.

neuroscience↗

bioRxiv2024

Interpretable high-resolution dimension reduction of spatial transcriptomics data by DeepFuseNMF

Spatial transcriptomics (ST) technologies have revolutionized tissue architecture studies by capturing gene expression with spatial context. However, high-dimensional ST data often have limited spatial resolution and exhibit considerable noise and sparsity, posing significant challenges in deciphering subtle spatial structures and underlying biological activities. Here, we introduce SpaHDmap, an interpretable dimension reduction framework that enhances spatial resolution by integrating ST gene expression with high-resolution histology images. SpaHDmap incorporates non-negative matrix factorization into a multimodal fusion encoder-decoder architecture, enabling the identification of interpretable, high-resolution embeddings. Furthermore, SpaHDmap can simultaneously analyze multiple samples and is compatible with various types of histology images. Extensive evaluations on synthetic and real ST datasets from various technologies and tissue types demonstrate that SpaHDmap can effectively produce highly interpretable, high-resolution embeddings, and detects refined spatial structures. SpaHDmap represents a powerful approach for integrating ST data and histology images, offering deeper insights into complex tissue structures and functions.

bioinformatics↗

bioRxiv2024

The mitochondrial dicarboxylate carrier mediates in vivo hepatic gluconeogenesis

Hepatic gluconeogenesis (GNG) is essential for maintaining euglycemia during prolonged fasting. However, GNG becomes pathologically elevated and drives chronic hyperglycemia in type 2 diabetes (T2D). Lactate/pyruvate is a major GNG substrate known to be imported into mitochondria for GNG. Yet, the subsequent mitochondrial carbon export mechanisms required to supply the extra-mitochondrial canonical GNG pathway have not been genetically delineated. Here, we evaluated the role of the mitochondrial dicarboxylate carrier (DiC) in mediating GNG from lactate/pyruvate. We generated liver-specific DiC knockout (DiC LivKO) mice. During lactate/pyruvate tolerance tests, DiC LivKO decreased plasma glucose excursion and 13C-lactate/-pyruvate flux into hepatic and plasma glucose. In a Western diet (WD) feeding model of T2D, acute DiC LivKO after induction of obesity decreased lactate/pyruvate-driven GNG, hyperglycemia, and hyperinsulinemia. Our results show that mitochondrial carbon export through the DiC mediates GNG and that the DiC contributes to impaired glucose homeostasis in a mouse model of T2D.

biochemistry↗

bioRxiv2024

Genetic diversity and evolution of rice centromeres

AbstractUnderstanding the mechanisms driving centromere evolution is crucial for deciphering eukaryotic evolution and speciation processes. Despite their widely recognized characteristics of conserved function in cell division, the centromeres have showed high diversity in composition and structure between species. The mechanism underlying this paradox remain poorly understood. Here, we assembled 67 high-quality rice genomes from Oryza AA group, encompassing both Asian and African rice species, and conducted an extensive analysis of over 800 nearly complete centromeres. Through de novo annotation of satellite sequences and employing a progressive compression strategy, we quantified the local homogenization and multi-layer nested structures of rice centromeres and found that genetic innovations in rice centromeres primarily arise from internal structural variations and retrotransposon insertions, along with a certain number of non-canonical satellite repeats (sati). Despite these rapid structural alterations, the single-base substitution rate in rice centromeres appears relatively lower compared to the chromosome arms. Contrary to the KARMA model for Arabidopsis centromere evolution, our model (RICE) suggests that centrophilic LTRs contribute to the decline of progenitor centromeres composed of satellite repeats, and facilitate the formation of evolutionary neo-centromeres, which are enriched with extended CENH3 binding regions beyond the native satellite arrays in plant genomes. In summary, this study provides novel insights into genomic divergence and reproductive barriers among rice species and subspecies, and advances our understanding of plant centromere evolution.

genetics↗