Biology subjects

Rodriguez, J.

Publications and source records attributed to Rodriguez, J..

At least 19 recordsLinked to original sources

bioRxiv2026

MaCADEMIA: a software toolbox for single-molecule fluorescence image quantification

Single-molecule localisation microscopy (SMLM) is a powerful tool in molecular and cellular biology and part of the broad umbrella of super-resolution microscopy. A distinct feature of SMLM, is its capacity for deep quantification, beyond just spatial information, to copy number, stoichiometry, molecular interaction and dynamics in living cells. The hardware required is increasingly straightforward to implement. However, complexity remains in the image analysis where much remains fragmented across specialised software tools. Here, we present MaCADEMIA (Matlab Computational Analysis of Diffusion, Emitter Molecular Intensity and Abundance), a simple yet powerful toolbox of MATLAB functions and associated documentation to enable straightforward extraction of quantitative single-molecule information. MaCADEMIA performs ensemble particle detection achieving localisation accuracies down to 0.5 pixels Root mean squared error (RMSE) across wide signal-to-noise (SNR) ranges on standardised particle tracking benchmarks, consistently matching or exceeding the performance of 14 leading methods. Our integrated workflow enables molecular counting and stoichiometry determination through stepwise photobleaching analysis, mobility measurement via mean squared displacement, colocalisaton analysis and absolute protein copy number quantification using three-dimensional cellular models.

bioinformatics↗

bioRxiv2026

Accurate and scalable demultiplexing of single-cell RNA sequencing using BEACON

Barcode-based multiplexing strategies can significantly increase sample throughput and decrease costs, while mitigating batch effects of single-cell RNA sequencing experiments. However, these approaches can be limited by inaccurate or inefficient demultiplexing, resulting in cell loss and reduced statistical power. Here, we present BEACON, a novel sample demultiplexing method that efficiently learns the background count distribution from data and removes it from individual cells, thereby improving classification accuracy. BEACON outperforms other state-of-the-art methods on multiple human data sets. We apply it to cancer cell line time course experiments in vitro, enabling the identification of genes associated with aggressive tumors in vivo. Finally, we adapt BEACON to multimodal protein-transcriptome profiling, enhancing protein signal recovery to identify a CD161-positive effector memory CD4 T-cell population with a Th17-like phenotype, which we prospectively validate. BEACON can therefore be applied to other droplet-based single-cell sequencing methodologies.

bioinformatics↗

bioRxiv2026

This must be the place: deep learning local adaptation

Climate change is increasingly disrupting the relationship between locally adapted populations and the environments in which they evolved, creating an urgent need for tools that connect genomic variation to climate. Common-garden and provenance trials remain the gold standard for characterizing local adaptation, but their time and resource requirements limit how broadly they can be applied. Genomic approaches provide a complementary path. Genotype--environment association (GEA) methods identify environmentally associated loci. Machine-learning models have also shown that geographic origin can be predicted directly from genotypes. Here we introduce EcoLocator, a supervised deep neural network that jointly predicts geographic location and climate of origin from genotypes. Through extensive simulations we demonstrate that EcoLocator accurately recovers geographic location and environment of origin from genotype data, and, with SHAP-based feature attribution, identifies adaptive loci more reliably than benchmark GEA methods. We apply our method to coastal Douglas-fir (Pseudotsuga menziesii var. menziesii), where EcoLocator predicts geographic origin (R2=0.75--0.83) and climate of origin (R2=0.52--0.72) under leave-one-out cross-validation. Notably, we find that climate predicted directly from genotypes outperforms climate inferred by first predicting geographic origin, showing that EcoLocator captures genotype--climate signal that cannot be recovered from geography alone. Our prediction errors fall within the tolerances used in existing seed-transfer guidelines, demonstrating that EcoLocator's predictions are ready for practical application, and our approach is readily extendable to other species and conservation contexts.

evolutionary biology↗

bioRxiv2026

Targeting Nitric Oxide Synthase 2 Reverses Learning Deficits in an Oligodendrocyte-Focused Model of Costello Syndrome

Oligodendrocyte (OL) functions greatly improve information processing in the brain; consequently, compromised OL biology negatively impacts brain function in various diseases. Young-adult Costello Syndrome (CS) patients present with learning disabilities and regression of psychomotor skills in correlation with abnormal brain white matter, delayed myelination, and dysmyelination. This suggests the involvement of OLs and myelin in abnormal brain physiology during and beyond development; however, the neuropathophysiology of CS remains poorly understood. Replacing the endogenous HRas gene with the CS-causing HRasG12V mutant gene in adult OLs (pHRasG/+ mice) induces structural myelin abnormalities; nonetheless, any functional impact is unknown. Here we show robust learning - but not memory - deficits in pHRasG/+ males and modest, delayed learning issues in females. Learning phenotypes are transient, likely involving compensatory responses from the OL lineage and microglia. Diffusion-weighted magnetic resonance imaging revealed regional time- and sex-dependent compromised myelin microstructure, coinciding with the peak of learning issues. Remarkably, transcripts associated with inflammation/immune function are upregulated and pharmacological control of nitric oxide synthase 2 restores learning in male pHRasG+/- mice. Our study supports the notion that abnormal nitric oxide signaling in mature OLs affects learning, suggests a chronic impact of glia-myelin mechanisms in CS neuropathology, and proposes molecular targets with therapeutic potential.

neuroscience↗

bioRxiv2026

Biodegradable Architected Stents for Endoscopic Internal Drainage

Postoperative gastric leak after bariatric surgery is a serious complication associated with prolonged treatment, repeated interventions, and substantial morbidity. Endoscopic internal drainage using double pigtail stents is widely adopted. However, current stents, originally designed for biliary use and often based on simple cylindrical geometries, are not optimized for post-bariatric gastric leak anatomy, mechanical support, or fluid drainage. Here, we present BRIDGE (Biodegradable aRchitected Internal DrainaGE), a stent concept integrating triply periodic minimal surface (TPMS) architectures to control mechanical compliance, kink resistance, and drainage performance. Using computational modeling, mechanical testing, and benchtop flow studies, we evaluate TPMS designs and identify volume fraction as a key parameter balancing flexibility, structural integrity, and hydraulic performance. TPMS-integrated designs tolerated a 7.1-fold smaller bend radius than a commercial stent without kinking and achieved up to a 2-fold increase in drainage. We also developed a stereolithography-printable biodegradable resin and fabricated a prototype lattice-integrated stent. TeaserA biodegradable, 3D-printed stent with an architected lattice design improves flexibility, kink resistance, and abscess drainage while eliminating the need for device removal.

bioengineering↗

bioRxiv2026

Protocol for measuring endocrine disruptive effects on transcriptional bursting using single-molecule imaging in human breast cancer cells

Transcriptional bursts regulate gene expression by altering burst size or burst frequency. Here, we present a protocol that integrates fixed-cell smFISH and live-cell single-molecule imaging to analyze estrogen-responsive transcriptional bursting of the TFF1 gene in human breast cancer cell lines. This workflow enables measurement of burst size, burst initiation, and active allele frequency to determine how endocrine disruptor chemicals modulate transcriptional bursting dynamics. For complete details on the use and execution of this protocol, please refer to Day, Yasar et al.1

cell biology↗

bioRxiv2026

Synovial transcriptional clusters link cartilage degeneration to cell-type-specific gene expression in knee osteoarthritis

ObjectivesTo identify synovial transcriptional clusters in human knee osteoarthritis (OA) and determine how these relate to synovial histologic features, cell-type-associated gene expression, and cartilage degeneration severity. MethodsBulk RNA sequencing (RNA-seq) of synovial tissue from n = 135 patients with knee OA was analyzed using consensus clustering. Clusters were compared by clinical and histologic features, including cartilage degeneration severity (OARSI score). Single-cell RNA-seq (n = 18) and spatial transcriptomics were used to relate cartilage degeneration-associated gene expression patterns to synovial cell populations. ResultsFour synovial transcriptional clusters that differed in synovial histologic features and cartilage degeneration severity were identified. Greater cartilage degeneration was associated with enrichment of lining fibroblast- and inflammatory myeloid-associated gene expression, whereas lesser cartilage degeneration was associated with enrichment of sublining fibroblast, endothelial, mural cell, and adipocyte-associated gene expression. ConclusionsHuman knee OA synovium segregates into transcriptional clusters associated with cartilage degeneration severity. Synovial transcriptional heterogeneity corresponds to cell-type-associated gene expression. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIOsteoarthritis synovium exhibits marked histologic and molecular heterogeneity. C_LIO_LISynovial inflammation detected by MRI correlates with cartilage degeneration and predicts progressive cartilage loss in knee OA. C_LIO_LIPrior transcriptomic studies have identified molecular subsets of OA synovium, but their relationship to cartilage degeneration severity remains unclear. C_LI What this study addsO_LIOA synovium segregates into four transcriptional clusters: Sublining (C1), Lymphomyeloid (C2), Myeloid (C3), and Major trauma (C4). C_LIO_LIGreater cartilage degeneration is associated with enrichment of inflammatory myeloid and lining fibroblast gene expression, whereas lesser degeneration is associated with enrichment of adipocyte, sublining fibroblast, endothelial, and mural cell-associated gene expression. C_LI How this study might affect research, practice or policyO_LIProvides a framework for a clinically relevant biological stratification of OA patients based on synovial molecular features. C_LIO_LIInforms future efforts to link synovial biology with OA prognosis, cartilage degeneration, treatment allocation, and development of targeted therapeutic strategies. C_LI

genomics↗

bioRxiv2026

SpaFlow depicts the dynamics of ligand-receptor interaction in spatial transcriptomics data

Spatial transcriptomics (ST) enables the study of cell-cell communication in native tissue context, but current methods for the ligand-receptor interaction (LRI) inference generally rely on static, distance-based assumptions. Here we present SpaFlow, a reaction-diffusion framework that models ligand diffusion, binding, dissociation, production and degradation to infer spatially resolved LRI activity and hotspots from ST data. Across paired 10x Visium and CosMx metastatic renal cell carcinoma datasets, SpaFlow outperformed existing methods in recovering spatially coherent LRIs, with inferred LRI activity showing stronger association with downstream signaling. In hepatocellular carcinoma after neoadjuvant immunotherapy, SpaFlow identified CXCL12-CXCR4 hotspots enriched at immune-rich tumor boundaries in responders. In aging mouse heart, SpaFlow resolved niche-specific pro-fibrotic and senescence-associated signaling, highlighting Postn-Itgav/Itgb5 as an additional pro-fibrotic axis and Angptl2-Pirb as a candidate mediator of inter-niche senescence-related communication. In human idiopathic pulmonary fibrosis lung, SpaFlow localized CXCL12-CXCR4 signaling between adventitial fibroblasts and CD4 T cells, CD8 T cells, and B cells in the fibrotic surrounding regions. Together, SpaFlow provides a physically informed framework for quantifying spatially constrained cell-cell communication and mechanistically interpreting signaling patterns in complex tissues.

bioinformatics↗

bioRxiv2026

Layered Single-Cell Heterogeneity in Hormone Receptor Signaling Across Mouse Organoids and Human ERα+ Cancer Cells

Hormone receptor signaling is often interpreted through receptor abundance as a proxy for hormone responsiveness, yet the determinants of single-cell variability in hormone response remain unclear. Using murine mammary organoids, we mapped estrogen (E2) and progesterone (P4) responses at single-cell resolution. Despite controlled 3D culture conditions, basal cell-derived organoids exhibit striking variability in hormone-induced transcriptional responses, with ER cells varying in the fraction of responsive genes engaged. This variability is not explained by receptor abundance alone. Instead, response magnitude correlates with expression of transcriptional co-regulators including Ncoa1, Ncor1, and Ncor2, suggesting that co-regulator balance contributes to variation in endocrine response magnitude. Organoids exhibit a mixed basal-luminal enhancer landscape and growth factor-dependent remodeling of ER and PR protein abundance. MCF7 cells show delayed activation kinetics and reach a lower response plateau. Together, these findings reveal that hormone response magnitude varies independently of receptor abundance in mammary organoids and follows distinct activation dynamics in human ER+ cancer cells.

cell biology↗

bioRxiv2026

Community-Based Surveillance for Highly Pathogenic Avian Influenza Viruses among Deceased Birds

Highly pathogenic avian influenza (HPAI) viruses of H5N1 clade 2.3.4.4b, are spreading worldwide, posing a threat to wildlife, domestic animals, and humans. In 2025, a multidisciplinary collaboration for HPAI H5N1 surveillance among birds within Galveston County, Texas, was initiated. Between November and December 2025, oropharyngeal and cloacal swabs were collected from wild and domestic birds reported as dead or dying by Galveston County residents. Specimens were studied with molecular assays, Sanger sequencing, virus isolation, and next-generation sequencing. Molecular evidence of HPAI H5N1 was detected in 7 of 10 (70%) birds, and the virus was successfully cultured in MDCK cells. Next-generation sequencing analysis of eight influenza A genome segments demonstrated a 4:4 gene segment reassortant constellation within clade 2.3.4.4b, consistent with genotype D1.1. Community members exposed to HPAI were offered antiviral prophylaxis. No human infections were identified. This surveillance demonstrates that community involvement combined with cross-sectoral collaboration can ensure rapid detection and characterization of circulating avian influenza viruses. Sustained local surveillance is essential for early warning, risk assessment, and prevention of virus spread to poultry, mammals, and humans.

molecular biology↗

bioRxiv2026

A whole organism screening platform identifies gut microbiome microproteins that modulate host metabolism

Advances in metagenomic sequencing over the past two decades have identified vast numbers of previously uncharacterised small open reading frames that may encode microproteins (<50aa). Although computational tools have accelerated gene sequence prediction from metagenomic data, the function of most annotated proteins remains unknown and untested, especially in the context of host-microbiome interactions. Here, we present a scalable phenotypic screening pipeline to identify gut microbiome-derived proteins that modulate host function. Using the nematode worm Caenorhabditis elegans as a whole animal model that is amenable to systematic screening approaches, our pipeline integrates high-throughput cloning, expression and delivery to worms via feeding, followed by behavioural phenomics screening. We apply this approach to a pilot library of 126 uncharacterised microproteins (< 50 aa) from healthy human gut metagenomes, identifying a set of high-interest targets with potential activity and ultimately validating a microprotein that modulates host fatty acid metabolism when expressed. With protein-based therapies increasingly recognised as a promising alternative to traditional small molecules, this work highlights the potential of a target-agnostic approach for the systematic screening and discovery of novel bioactive proteins.

microbiology↗

bioRxiv2026

Ulacamten: A Novel, RLC-Targeting Cardiac Myosin Inhibitor for Potential Treatment of Cardiac Hypercontractility, Including HFpEF

BackgroundCardiac myosin inhibitors (CMIs) demonstrate advantages over other guideline-directed therapy for patients with obstructive hypertrophic cardiomyopathy (oHCM). By reducing hypercontractility, CMIs abrogate excessive systolic function and improve diastolic function; diminish hypertrophy of the left ventricle (LV); and improve exercise capacity, functional class, and symptoms. Whether CMIs are therapeutic in heart failure with preserved ejection fraction (HFpEF) is of interest because a significant subset of these patients demonstrate supranormal ejection fractions and abnormal LV structure, characteristics in common with HCM, where CMIs have proved effective. ObjectivesOur goal was to characterize the mechanism of myosin inhibition for ulacamten and determine its efficacy in a rodent model of HFpEF. MethodsUlacamten was characterized using biophysical and biochemical approaches, cardiomyocytes from humans and the ZSF1 obese rat model of HFpEF, hypercontractile human-engineered heart tissues, and echocardiography in the ZSF1 rat model. ResultsUnlike the other CMIs, aficamten and mavacamten, ulacamten binds outside the S1 domain of myosin and requires the regulatory light chain domain to bind and inhibit the activity of 2-headed myosin. Ulacamten only partially inhibits the myosin ATPase activity in both myofibrillar and protein systems, but inhibition of contractility was nearly complete in cardiomyocytes. Improvement in relaxation was demonstrated in hypercontractile-engineered heart tissues, and chronic treatment of ZSF1 obese rats showed benefits in both cardiac structure and function. ConclusionsUlacamten inhibits myosin in a manner distinct from aficamten and mavacamten, potentially broadening the mechanistic properties of CMIs available for treatment of hypercontractile cardiac dysfunction. CONDENSED ABSTRACTCardiac myosin inhibitors (CMIs) abrogate excessive systolic function and improve diastolic function, diminish cardiac hypertrophy, and improve exercise capacity in humans with obstructive hypertrophic cardiomyopathy (oHCM). Supranormal ejection fraction underlies heart failure with preserved ejection fraction (HFpEF) in some patients. We describe a new CMI, ulacamten, with binding and inhibitory properties distinct from two other FDA-approved CMIs, aficamten and mavacamten. Specifically, ulacamten requires 2-headed myosin to inhibit activity, whereas aficamten and mavacamten inhibit single-headed myosin. Ulacamten inhibits contractility in primary myocytes isolated from control human and hypercontractile ZSF1 obese rat hearts, as well as engineered heart tissues created with induced pluripotent stem cell cardiomyocytes bearing an HCM mutation. Chronic treatment of ZSF1 obese rats as a preclinical model of HFpEF improves diastolic function and reduces hypertrophy and fibrosis, broadening the potential mechanistic landscape of CMIs. Visual abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/701387v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@11f9cecorg.highwire.dtl.DTLVardef@776847org.highwire.dtl.DTLVardef@15f19ddorg.highwire.dtl.DTLVardef@9b20c6_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2026

The Training Village: an open platform for continuous testing of rodents in cognitive tasks

The development of new methods for dissecting neural circuits in rodents promises to transform the study of higher-order cognitive functions. However, the adaptation of complex cognitive tasks from humans to rodents remains very limited as these tasks require long periods of animal training with significant researcher expertise and effort. Multi-box setups can mitigate the problem but remain labor-intensive and costly to maintain. Newly developed home cage training systems, while minimizing costs, are limited to specific conditions and tasks. Here, we present the Training Village (TV), an open-source, affordable, and fully automated system for continuous rodent training. In the TV, a group of rodents lives in enriched arenas while individually accessing an operant box at any time. The system provides personalized training, continuous monitoring of task performance and home cage activity, and real-time remote supervision. Its graphical interface and modular design make it user-friendly and easy to integrate with other behavioral systems running a wide range of cognitive paradigms. We validated the TV across multiple tasks and cohorts of mice and rats, demonstrating efficient operant box usage, stable long-term task engagement, and its potential to link home cage behavior with task performance. Overall, the TV is an easy-to-adopt platform that can greatly accelerate brain research by fully automating rodent training in complex cognitive tasks.

animal behavior and cognition↗

bioRxiv2025

High-throughput phenomics of global ant biodiversity

The big data era in biology is underway, but the study of organismal form has been slow to capitalize on advances in imaging and computation. Modern imaging can digitize whole organisms, but low throughput has limited the effort to document morphological diversity. Within the open science initiative Antscan, we applied high-throughput synchrotron X-ray microtomography to capture phenotypes across a diverse and ecologically dominant insect group -- ants. We provide 2193 whole-body 3D ant datasets from 792 species to broadly cover the ant phylogeny with a global scope, also pairing phenomic data with genome sequencing projects. Scans acquired with standardized parameters facilitate automated analysis and free access to data can broaden the audience and incentivize methods development. Antscan presents a scalable approach to create libraries of diverse anatomies, heralding a new era of studies on the evolution, structure, and function of organismal phenotypes.

zoology↗

bioRxiv2025

Enhanced Zika Virus Suppression by Coupling Ribavirin with Biodegradable Drug Delivery

Advancement and implementation of nanoparticle-based systems for enhanced drug delivery have become essential for the suppression of viral pathogens due to lack of viable treatment options. This study focuses on characterization and application of mPEG-PCL co-polymers for development of pH-responsive, biodegradable micellar nanoparticles (MNPs) for the delivery of the antiviral drug ribavirin against Zika virus. Synthesis of mPEG-PCL diblock copolymers was confirmed through FTIR and 1H NMR, which validated the formation of ester functional groups and accurate structure of copolymers. mPEG-PCL MNPs, loaded with ribavirin, exhibited a mean diameter of approximately 34.29 {+/-} 5.214 nm and a zeta potential of -3.28 {+/-} 0.718 mV, suitable for evading immune detection and facilitating cellular entry. The ribavirin-loaded mPEG-PCL MNPs demonstrated pH-dependent release, with approximately 88% of ribavirin released at pH 5.5, compared to 20% at pH 7.4. This pH-responsive release is crucial for targeted drug delivery within the endosomal pathway. In vitro studies using JEG-3 cells infected with Zika virus showed that ribavirin-loaded mPEG-PCL MNPs achieved an EC50 of 0.22nM, significantly enhancing drug efficacy compared to unencapsulated ribavirin, which required micromolar concentrations to achieve similar effects. The MTT assay results indicated minimal cytotoxicity of the ribavirin-loaded mPEG-PCL MNPs, with approximately 80% cell viability at the highest concentration evaluated. Confocal microscopy and RT-PCR analysis further confirmed the efficient cellular uptake and potent antiviral activity of the ribavirin-loaded MNPs. These findings highlight the potential of mPEG-PCL MNPs as an effective delivery system for broad-spectrum antivirals like ribavirin, enhancing their therapeutic efficacy while minimizing cytotoxicity.

microbiology↗

bioRxiv2025

H3K27me3 chromatin heterogeneity reveals variable cell responses to estrogen and endocrine treatment

Gene expression heterogeneity generates subpopulations of tumor cells that can evade therapeutic pressure. This heterogeneity has been observed in both primary Estrogen Receptor alpha positive (ER+) breast tumors and cell lines. Therefore, understanding the mechanisms regulating expression heterogeneity is critical towards developing effective therapies. A key contributor to gene expression variability is the stochastic nature of transcription. Transcription occurs in a probabilistic, burst-like manner, in which gene activation occurs intermittently, producing RNA in pulses and interspersed with transcriptional off-periods. The estrogen-responsive gene TFF1 is expressed in the majority of ER breast tumors and exemplifies such heterogeneity, with transcriptional inactivity ranging from minutes to several days. Here, we identify the molecular mechanism underlying the wide range in TFF1 expression by analyzing cells sorted based on their TFF1 activity levels. We observed that TFF1 inactive (TFF1low) cells exhibit a repressive chromatin state marked by H3K27me3 at the TFF1 promoter and enhancer. Despite global similarity in ER binding, occupancy at the TFF1 regulatory elements was selectively reduced in TFF1low cells, resulting in fewer active alleles and diminished transcriptional bursting frequency. Conversely, TFF1high cells exhibited more active TFF1 alleles and hyperbursting. These cells also retained sensitivity to endocrine therapy, while TFF1low cells displayed reduced drug responsiveness. Genome-wide, differentially enriched H3K27me3 regions correlated with variable expression of estrogen-responsive genes, highlighting a broader regulatory mechanism that links chromatin state to expression variability. Together, our findings establish how repressive chromatin dynamics contribute to gene expression heterogeneity and endocrine resistance in ER breast cancer. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=67 SRC="FIGDIR/small/677184v1_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@1194eedorg.highwire.dtl.DTLVardef@8cb67aorg.highwire.dtl.DTLVardef@202ad9org.highwire.dtl.DTLVardef@1dd222a_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2025

Contractility governs cardiomyocyte cell cycle activity

The hearts rhythmic contractions keep blood flowing to deliver the oxygen and nutrients that sustain life, but this very strength may also explain why the heart has so little capacity to regenerate. Whereas embryonic and neonatal hearts can repair themselves, this ability is rapidly lost after birth as heart muscle cells (cardiomyocytes) exit the cell cycle. We tested whether the force-generating machinery of the heart acts as a barrier to regeneration. Across human cardiomyocytes, engineered heart tissue, and myocardial slices, we found that active force generation suppresses proliferation, whereas its inhibition, through chemogenetic or pharmacological modulation, enabled cell cycle re-entry. These findings identify contractility as a central regulator of regenerative potential, highlighting new directions for strategies to restore repair in the diseased heart.

cell biology↗

bioRxiv2025

Harnessing drought tolerance in a reference set of Andean amaranths

Climate change and low-input farming systems increasingly expose crops to drought stress. Andean amaranths (Amaranthus spp.), as neglected and underutilized species, offer potential for climate-resilient agriculture due to their inherent drought tolerance and adaptability. In Northwest Argentina (NWA), a region with high environmental heterogeneity, exploiting this genetic diversity may improve food security. This study evaluated drought tolerance and yield stability among Andean amaranth genotypes to: assess the effects of genotype and GxE interaction, determine the potential for selecting specifically adapted genotypes, and identify high-yielding, stable genotypes for drought-prone conditions. Eleven genotypes (cultivars, breeding lines, and landraces of A. caudatus and A. mantegazzianus) were tested across four agroecological zones in NWA under irrigated and drought-stressed conditions. Grain yield data were analyzed using linear mixed models and AMMI analysis. Genotypes differed significantly in grain yield across environments and irrigation regimes. Strong GxE interactions led to genotype re-ranking across sites. Several A. caudatus breeding lines (G1, G2, G3, G6) combined high yield and stability. The A. mantegazzianus landrace (G11) was highly stable but low yielding. Amaranth genotypes showed distinct responses to drought, with some lines exhibiting broad adaptation and others, specific adaptation to stress-prone environments.

plant biology↗