Biology subjects

Ma, L.

Publications and source records attributed to Ma, L..

At least 145 records · Page 8Linked to original sources

bioRxiv2024

PhaSeDis: A Manually Curated Database of Phase Separation-Disease Associations and Corresponding Small Molecules

Biomacromolecules form membraneless organelles through liquid-liquid phase separation in order to regulate the efficiency of particular biochemical reactions. Dysregulation of phase separation might result in pathological condensation or sequestration of biomolecules, leading to diseases. Thus, phase separation and phase separating factors may serve as drug targets for disease treatment. Nevertheless, such associations have not yet been integrated into phase separation related databases. Therefore, based on MloDisDB, a database for membraneless organelle factor-disease association previously developed by our lab, we constructed PhaSeDis, the phase separation-disease association database. We increased the number of phase separation entries from 52 to 185, and supplemented the evidence provided by the original article verifying the phase separation nature of the factors. Moreover, we included the information of interacting small molecules with low or high-throughput evidence that might serve as potential drugs for phase separation entries. PhaSeDis strives to offer comprehensive descriptions of each entry, elucidating how phase separating factors induce pathological conditions via phase separation and the mechanisms by which small molecules intervene. We believe that PhaSeDis would be very important in the application of phase separation regulation in treating related diseases. PhaSeDis is available at http://mlodis.phasep.pro.

bioinformatics↗

bioRxiv2024

VGLL2 and TEAD1 fusion proteins drive YAP/TAZ-independent transcription and tumorigenesis by engaging p300

Studies on Hippo pathway regulation of tumorigenesis largely center on YAP and TAZ, the transcriptional co-regulators of TEAD. Here, we present an oncogenic mechanism involving VGLL and TEAD fusions that is Hippo pathway-related but YAP/TAZ-independent. We characterize two recurrent fusions, VGLL2-NCOA2 and TEAD1-NCOA2, recently identified in spindle cell rhabdomyosarcoma. We demonstrate that in contrast to VGLL2 and TEAD1, the fusion proteins are strong activators of TEAD-dependent transcription, and their function does not require YAP/TAZ. Furthermore, we identify that VGLL2 and TEAD1 fusions engage specific epigenetic regulation by recruiting histone acetyltransferase p300 to control TEAD-mediated transcriptional and epigenetic landscapes. We showed that small molecule p300 inhibition can suppress fusion proteins-induced oncogenic transformation both in vitro and in vivo. Overall, our study reveals a molecular basis for VGLL involvement in cancer and provides a framework for targeting tumors carrying VGLL, TEAD, or NCOA translocations.

cancer biology↗

bioRxiv2024

pNet: A toolbox for personalized functional networks modeling

Personalized functional networks (FNs) derived from functional magnetic resonance imaging (fMRI) data are useful for characterizing individual variations in the brain functional topography associated with the brain development, aging, and disorders. To facilitate applications of the personalized FNs with enhanced reliability and reproducibility, we develop an open-source toolbox that is user-friendly, extendable, and includes rigorous quality control (QC), featuring multiple user interfaces (graphics, command line, and a step-by-step guideline) and job-scheduling for high performance computing (HPC) clusters. Particularly, the toolbox, named personalized functional network modeling (pNet), takes fMRI inputs in either volumetric or surface type, ensuring compatibility with multiple fMRI data formats, and computes personalized FNs using two distinct modeling methods: one method optimizes the functional coherence of FNs, while the other enhances their independence. Additionally, the toolbox provides HTML-based reports for QC and visualization of personalized FNs. The toolbox is developed in both MATLAB and Python platforms with a modular design to facilitate extension and modification by users familiar with either programming language. We have evaluated the toolbox on two fMRI datasets and demonstrated its effectiveness and user-friendliness with interactive and scripting examples. pNet is publicly available at https://github.com/MLDataAnalytics/pNet.

neuroscience↗

bioRxiv2024

A generalized framework to identify SARS-CoV-2 broadly neutralizing antibodies

Monoclonal antibodies (mAbs) targeting the SARS-CoV-2 receptor-binding domain (RBD) are used to treat and prevent COVID-19. However, the rapid evolution of SARS-CoV-2 drives continuous escape from therapeutic mAbs. Therefore, the ability to identify broadly neutralizing antibodies (bnAbs) against future variants is needed. Here, we use deep mutational scanning (DMS) to predict viral RBD evolution and to select for mAbs neutralizing both existing and prospective variants. A retrospective analysis of 1,103 SARS-CoV-2 wildtype-elicited mAbs shows that this method can increase the probability of identifying effective bnAbs against the XBB.1.5 strain from 1% to 40% in an early pandemic setup. Among these bnAbs, BD55-1205 exhibited potent activity against all tested variants. Cryo-EM structural analyses revealed the receptor mimicry of BD55-1205, explaining its broad reactivity. Delivery of mRNA-LNPs encoding BD55-1205-IgG in mice resulted in ~5,000 serum NT50 against XBB.1.5, HK.3.1, and JN.1 variants. Combining bnAb identification using viral evolution prediction with the versatility of mRNA delivery technology can enable rapid development of next-generation antibody-based countermeasures against SARS-CoV-2 and potentially other pathogens with pandemic potential.

immunology↗

bioRxiv2024

Directed evolution-based discovery of ligands for in vivo restimulation of CAR-T cells

Chimeric antigen receptor (CAR) T cell therapy targeting CD19 elicits remarkable clinical efficacy in B-cell malignancies, but many patients relapse due to failed expansion and/or progressive loss of CAR-T cells. We recently reported a strategy to potently restimulate CAR-T cells in vivo, enhancing their functionality by administration of a vaccine-like stimulus comprised of surrogate peptide ligands for a CAR linked to a lymph node-targeting amphiphilic PEG-lipid (termed CAR-T-vax). Here, we demonstrate a general strategy to generate and optimize peptide mimotopes enabling CAR-T-vax generation for any CAR. Using the clinical CD19 CAR (FMC63) as a test case, we employed yeast surface display to identify peptide binders to soluble IgG versions of FMC63, which were subsequently affinity matured by directed evolution. CAR-T vaccines using these optimized mimotopes triggered marked expansion and memory development of CD19 CAR-T cells in both syngeneic and humanized mouse models of B-ALL/Lymphoma, and enhanced control of disease progression. This approach thus enables vaccine boosting to be applied to any clinically relevant CAR-T cell product.

bioengineering↗

bioRxiv2024

Evaluation of Deep Neural Network Models for Instance Segmentation of Lumbar Spine MRI

Intervertebral disc disease, a prevalent ailment, frequently leads to intermittent or persistent low back pain, and diagnosing and assessing of this disease rely on accurate measurement of vertebral bone and intervertebral disc geometries from lumbar MR images. Deep neural network (DNN) models may assist clinicians with more efficient image segmentation of individual instances (discs and vertebrae) of the lumbar spine in an automated way, which is termed as instance image segmentation. In this work, we evaluated 15 existing DNN models for lumbar spine MR image segmentation. We introduced a new data augmentation technique to create synthetic yet realistic MR image dataset, named SSMSpine, which is made publicly available. The 15 image segmentation models are evaluated on our private in-house dataset and the public SSMSpine dataset, using two metrics, Dice Similarity Coefficient and 95% Hausdorff Distance. The SSMSpine dataset are available at https://github.com/jiasongchen/SSMSpine.

bioengineering↗

bioRxiv2024

EAP: a versatile cloud-based platform for comprehensive and interactive analysis of large-scale ChIP/ATAC-seq data sets

Epigenome profiling techniques such as ChIP-seq and ATAC-seq have revolutionized our understanding of gene expression regulation in tissue development and disease progression. However, increasing amount of ChIP/ATAC-seq data poses challenges in computational resources, and the absence of systematic tools for epigenomic analysis underscores the necessity for an efficient analysis platform. To address these issues, we developed the Epigenomic Analysis Platform (EAP, https://www.biosino.org/epigenetics), a scalable cloud-based tool that efficiently analyzes large-scale ChIP/ATAC-seq data sets. EAP employs advanced computational algorithms to derive biologically meaningful insights from heterogeneous datasets and automatically generates publication-ready figures and tabular results, enabling comprehensive epigenomic analysis and data mining in areas like cancer subtyping and therapeutic target discovery.

bioinformatics↗

bioRxiv2024

Prevalent co-release of glutamate and GABA throughout the mouse brain

Several neuronal populations in the brain transmit both the excitatory and inhibitory neurotransmitters, glutamate, and GABA, to downstream neurons. However, it remains largely unknown whether these opposing neurotransmitters are co-released onto the same postsynaptic neuron simultaneously or are independently transmitted at different time and locations (called co-transmission). Here, using whole-cell patch-clamp recording on acute mouse brain slices, we observed biphasic miniature postsynaptic currents, i.e., minis with time-locked excitatory and inhibitory currents, in striatal spiny projection neurons (SPNs). This observation cannot be explained by accidental coincidence of monophasic miniature excitatory and inhibitory postsynaptic currents (mEPSCs and mIPSCs, respectively), arguing for the co-release of glutamate and GABA. Interestingly, these biphasic minis could either be an mEPSC leading an mIPSC or vice versa. Although dopaminergic axons release both glutamate and GABA in the striatum, deletion of dopamine neurons did not eliminate biphasic minis, indicating that the co-release originates from another neuronal type. Importantly, we found that both types of biphasic minis were detected in other neuronal subtypes in the striatum as well as in nine out of ten additionally tested brain regions. Our results suggest that co-release of glutamate and GABA is a prevalent mode of neurotransmission in the brain.

neuroscience↗

bioRxiv2024

Dual-view jointly learning improves personalized drug synergy prediction

BackgroundAccurate and robust estimation of the synergistic drug combination is important for precision medicine. Although some computational methods have been developed, some predictions are still unreliable especially for the cross-dataset predictions, due to the complex mechanism of drug combinations and heterogeneity of cancer samples. MethodsWe have proposed JointSyn that utilizes dual-view jointly learning to predict sample-specific effects of drug combination from drug and cell features. JointSyn capture the drug synergy related features from two views. One view is the embedding of drug combination on cancer cell lines, and the other view is the combination of two drugs embeddings on cancer cell lines. Finally, the prediction net uses the features learned from the two views to predict the drug synergy of the drug combination on the cell line. In addition, we used the fine-tuning method to improve the JointSyns performance on the unseen subset within a dataset or cross dataset. ResultsJointSyn outperforms existing state-of-the-art methods in predictive accuracy and robustness across various benchmarks. Each view of JointSyn captures drug synergy-related characteristics and make complementary contributes to the final accurate prediction of drug combination. Moreover, JointSyn with fine-tuning improves its generalization ability to predict a novel drug combination or cancer sample only using a small number of experimental measurements. We also used JointSyn to generate an estimated atlas of drug synergy for pan-cancer and explored the differential pattern among cancers. ConclusionsThese results demonstrate the potential of JointSyn to predict drug synergy, supporting the development of personalized combinatorial therapies. The source code is available on GitHub at https://github.com/LiHongCSBLab/JointSyn.

cancer biology↗

bioRxiv2024

Normative growth modeling of brain morphology reveals neuroanatomical heterogeneity and biological subtypes in children with ADHD

BackgroundNeuroimaging studies suggest substantial individual heterogeneity in brain phenotypes in attention-deficit/hyperactivity disorder (ADHD). However, how these individual-level brain phenotypes contribute to the identification of ADHD biotypes and whether these biotypes have different treatment outcomes and neurobiological underpinnings remain largely unknown. MethodsWe collected multisite, high-quality structural magnetic resonance imaging data from 1,006 children aged 6-14 years, including 351 children with ADHD and 655 typically developing children. Normative growth models of cortical thickness were established for 219 regions in the typically developing children. Individual-level deviations from these normal references were quantified and clustered to identify ADHD biotypes. We validated the replicability and generalizability of the ADHD biotypes using two independent datasets and evaluated the associations of the biotypes with symptomatic, cognitive, and gene expression profiles, as well as follow-up treatment outcomes. FindingsNo more than 10% of children with ADHD had extreme deviations in cortical thickness in a single region, suggesting high heterogeneity among individuals with ADHD. On the basis of the brain deviation maps, we discovered two robust ADHD biotypes, an infra-normal subtype with cortical thinning associated with ADHD symptoms and a supranormal subtype with cortical thickening associated with cognition. Patients with the infra-normal subtype responded better to methylphenidate than to atomoxetine, although both subtypes showed treatment efficacy. Brain deviations in the infra-normal subtype were explained by the expression levels of genes enriched in presynaptic and axonal development and polygenic risk of ADHD. InterpretationWe identified anatomically distinct, clinically valuable, and biologically informed ADHD subtypes, providing insight into the neurobiological basis of clinical heterogeneity and facilitating a personalized medication strategy for ADHD patients. Panel: Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSubstantial individual heterogeneity in brain phenotypes in attention-deficit/hyperactivity disorder (ADHD) motivates the need to discover homogeneous biotypes. We searched PubMed for research articles on ADHD biotypes using brain MRI published before December 1, 2023, using the search terms ((attention deficit hyperactivity disorder [Title/Abstract]) OR (ADHD [Title/Abstract])) AND ((subtypes [Title/Abstract]) OR (subgroups [Title/Abstract]) OR (subtyping [Title/Abstract])) AND ((MRI [Title/Abstract]) OR (neuroimaging [Title/Abstract]) OR (brain [Title/Abstract])) without language restrictions. Of the eight included studies, two identified ADHD biotypes using structural morphology, four used functional activity, and two used multimodal features. However, none of these studies considered the developmental effect of the brain phenotypes, examined treatment response, or investigated the genetic correlates of the biotypes. Added value of this studyThis study is the first to use individualized brain measures extracted from normative models to investigate ADHD biotypes in a large sample of more than 1,000 children. We identified two reproducible ADHD biotypes, characterized by distinct symptomatic, cognitive, and gene expression profiles, as well as differential treatment responses. This study advances our understanding of the neurobiological basis underlying the clinical heterogeneity of ADHD and highlights the critical need to discover ADHD biotypes using an unbiased and individualized approach. Implications of all the available evidenceThis study revealed remarkable neuroanatomical heterogeneity in ADHD patients and identified anatomically distinct, clinically valuable, and biologically informed ADHD biotypes. Our findings have potential value for the investigation of data-driven biotypes to evaluate treatment efficacy and facilitate personalized treatment. We also highlight the need for future studies to move beyond the understanding of ADHD solely based on the "average patient" perspective.

neuroscience↗

bioRxiv2024

Phase Contrast Tomography (PCT)

Phase contrast microscopy has been employed for 2D imaging of thin samples since its invention. Herein, we propose and demonstrate phase contrast tomography (PCT) that incorporates the scanning of LED illumination with quantitative phase contrast microscopy (QPCM) to realize 3D phase imaging of a sample. The proposed PCT is demonstrated 3D imaging of 200-nm polystyrene microspheres (PMs) and sub-organelles inside COS7 cells. The results reveal that the proposed PCT has high spatial resolution and stability without speckle noise, and thence, it has a great potential to be applied to industrial testing and life science research.

biophysics↗

bioRxiv2024

HER2 Prognostic Significance and Therapeutic Implications in Gastric Cardia Adenocarcinoma: Insights from Multi-Omics Profiling

Therapeutic targets for Gastric Cardia Adenocarcinoma (GCA), particularly for HER2- negative patients, are lacking. Here, we conducted multi-omics profiling on 128 GCA patients using mass spectrometry, whole-exome sequencing, RNA-Seq, and metabolomics. We found HER2 to be a favorable prognostic marker for GCA. Employing molecular counting, we categorized patients into HER2-high, -low, and -negative groups. We uncovered an enrichment of DNA repair features in the HER2-high group, while HER2-low and -negative groups exhibited strong inflammation. We found that tumor mutation burden may not be the distinguishing factor among these three groups. We revealed that the HER2-negative and -low groups have a tumor-suppressive immune microenvironment, and HER2 expression is associated with fatty acid metabolic profiles and inflammation in the blood of patients. Our study revealed anti-inflammatory and immune checkpoint inhibition, targeting PD-L2 and the CD47/SIRPA pair, as therapeutic strategies for HER2-negative GCA patients. These findings highlight promising avenues for personalized treatment for GCA.

cancer biology↗

bioRxiv2024

A 10-valent composite mRNA vaccine against both influenza and COVID-19

The COVID-19 pandemic caused by SARS-CoV-2 viruses has had a persistent and significant impact on global public health for four years. Recently, there has been a resurgence of seasonal influenza transmission worldwide. The co-circulation of SARS-CoV-2 and seasonal influenza viruses results in a dual burden on communities. Additionally, the pandemic potential of zoonotic influenza viruses, such as avian Influenza A/H5N1 and A/H7N9, remains a concern. Therefore, a combined vaccine against all these respiratory diseases is in urgent need. mRNA vaccines, with their superior efficacy, speed in development, flexibility, and cost-effectiveness, offer a promising solution for such infectious diseases and potential future pandemics. In this study, we present FLUCOV-10, a novel 10-valent mRNA vaccine created from our proven platform. This vaccine encodes hemagglutinin (HA) proteins from four seasonal influenza viruses and two avian influenza viruses with pandemic potential, as well as spike proteins from four SARS-CoV-2 variants. A two-dose immunization with the FLUCOV-10 elicited robust immune responses in mice, producing IgG antibodies, neutralizing antibodies, and antigen-specific cellular immune responses against all the vaccine-matched viruses of influenza and SARS-CoV-2. Remarkably, the FLUCOV-10 immunization provided complete protection in mouse models against both homologous and heterologous strains of influenza and SARS-CoV-2. These results highlight the potential of FLUCOV-10 as an effective vaccine candidate for the prevention of influenza and COVID-19. Author summaryAmidst the ongoing and emerging respiratory viral threats, particularly the concurrent and sequential spread of SARS-CoV-2 and influenza, our research introduces FLUCOV-10. This novel mRNA-based combination vaccine, designed to counteract both influenza and COVID-19, by incorporating genes for surface glycoproteins from various influenza viruses and SARS-CoV-2 variants. This combination vaccine showed highly effective in preclinical trials, generating strong immune responses, and ensuring protection against both matching and heterologous strains of influenza and SARS-CoV-2. FLUCOV-10 represents a significant step forward in our ability to address respiratory viral threats, showcasing potential as a singular, adaptable vaccine solution for global health challenges.

microbiology↗

bioRxiv2024

Secondary microglia formation center in the human fetal brain

Yolk sac-derived microglia migrate and populate the brain during development, constituting 10-15% of the total brain cells. The human brain is the largest and most complex brain with the highest cognitive capacity among all species. Therefore, the limitations of rodent brain studies in interpreting the human brain are evident. By co-immunostaining microglia in 50 {micro}m fetal brain sections from 7.5 to 16 gestational weeks (gw) and combining high-resolution scanning, we identified a highly proliferative microglia aggregate (0.108-2.129 mm2) that expanded in Downs Syndrome fetal brain (4.168 mm2) and was located near the ganglion eminence, in which Ki67+ microglia accounted for 23.4% of total microglia compared to 6.3% in other brain regions. The microglia in the aggregates lack phagocytic bulbs, membrane ruffles, and long/branching processes compared to microglia in other brain regions. Introducing human microglia into cortical organoids, but not macrophages, replicated proliferative microglial aggregates on the brain organoid surface and sufficiently penetrated deeper regions of the cortical organoids. Penetrating microglia display phagocytic capacity, enhance immunity, and accelerate the maturation of brain organoids. The large proliferative microglial aggregate may be a unique secondary microglial formation center in the human fetal brain to compensate for the enormous microglial demands during brain expansion.

neuroscience↗

bioRxiv2024

HKDC1 Promotes Liver Cancer Stemness Under Hypoxia via Stabilizing β-Catenin

Background and AimsHexokinases (HKs), a group of enzymes catalyzing the first step of glycolysis, have been shown to play important roles in liver metabolism and tumorigenesis. Our recent studies identified HKDC1 as a top candidate associated with liver cancer metastasis. We aimed to compare its cell-type specificity with other HKs upregulated in liver cancer and investigate the molecular mechanisms underlying its involvement in liver cancer metastasis. Approach and ResultsWe found that, compared to HK1 and HK2, the other two commonly upregulated HKs in liver cancer, HKDC1 was most strongly associated with the metastasis potential of tumors and organoids derived from two liver cancer mouse models we previously established. RNA in situ hybridization and single-cell RNA-seq analysis revealed that HKDC1 was specifically upregulated in malignant cells in hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) patient tumors, whereas HK1 and HK2 were widespread across various tumor microenvironment lineages. An unbiased metabolomic profiling demonstrated that HKDC1 overexpression in HCC cells led to metabolic alterations distinct from those from HK1 and HK2 overexpression, with HKDC1 particularly impacting the tricarboxylic acid (TCA) cycle. HKDC1 was prometastatic in HCC orthotopic and tail vein injection mouse models and, molecularly, HKDC1 was induced by hypoxia and bound to glycogen synthase kinase 3{beta} to stabilize {beta}-catenin, leading to enhanced stemness of HCC cells. ConclusionsOverall, our findings underscore HKDC1 as a prometastatic HK specifically expressed in the malignant compartment of primary liver tumors, thereby providing a mechanistic basis for targeting this enzyme in advanced liver cancer.

cancer biology↗

bioRxiv2024

MetaWorm: A Complete Model Bridging Brain, Body and Environment of C. elegans

The behavior of an organism is profoundly influenced by the complex interplay between its brain, body, and environment. Existing data-driven models focusing on either the brain or the body-environment separately. A model that integrates these two components is yet to be developed. Here, we present MetaWorm, an integrative data-driven model of a widely studied organism, C. elegans. This model consists of two sub-models: the brain model and the body & environment model. The brain model was built by multi-compartment models with realistic morphology, connectome, and neural population dynamics based on experimental data. Simultaneously, the body & environment model employed a lifelike body and a 3D physical environment, facilitating easy behavior quantification. Through the closed-loop interaction between two sub-models, MetaWorm faithfully reproduced the realistic zigzag movement towards attractors observed in C. elegans. Notably, MetaWorm is the first model to achieve seamless integration of detailed brain, body, and environment simulations, enabling unprecedented insights into the intricate relationships between neural structures, neural activities, and behaviors. Leveraging this model, we investigated the impact of neural system structure on both neural activities and behaviors. Consequently, MetaWorm can enhance our understanding of how the brain controls the body to interact with its surrounding environment.

neuroscience↗

bioRxiv2024

Molecular, Cellular, and Developmental Organization of the Mouse Vomeronasal Organ at Single Cell Resolution

We have generated single cell transcriptomic atlases of vomeronasal organs (VNO) from juvenile and adult mice. Combined with spatial molecular imaging, we uncover a distinct, previously unidentified class of cells that express the vomeronasal receptors and a population of canonical olfactory sensory neurons in the VNO. High resolution trajectory and cluster analyses reveal the lineage relationship, spatial distribution of cell types, and a putative cascade of molecular events that specify the V1r, V2r, and OR lineages from a common stem cell population. The expression of vomeronasal and olfactory receptors follow power law distributions, but there is high variability in average expression levels between individual receptor and cell types. Substantial co-expression is found between receptors across clades, from different classes, and between olfactory and vomeronasal receptors, with nearly half from pairs located on the same chromosome. Interestingly, the expression of V2r, but not V1r, genes is associated with various transcription factors, suggesting distinct mechanisms of receptor choice associated with the two cell types. We identify association between transcription factors, surface axon guidance molecules, and individual VRs, thereby uncovering a molecular code that guides the specification of the vomeronasal circuitry. Our study provides a wealth of data on the development and organization of the accessory olfactory system at both cellular and molecular levels to enable a deeper understanding of vomeronasal system function.

neuroscience↗

bioRxiv2024

Population genomics of the rice landrace Acuce reveals exceptional dynamics of immune receptors

In cultivated plants such as Oryza sativa, landraces harbour high levels of diversity, in sharp contrast with genetically uniform modern varieties. The Yuanyang terraces (China) are renowned for traditional farming involving landraces and low disease incidence. To understand the molecular basis of these resistance levels, we explored the genomic diversity of Acuce, one of the oldest landraces in the region. Based on whole-genome resequencing of over 200 Acuce plants, we evaluated the diversity of immunity and agronomical genes with respect to the rest of the genome. In parallel, we analysed the genetic basis of pathogen resistance and agronomical traits. Acuce exhibits high levels of diversity, reaching 38% of the worldwide levels. We uncovered an excess of diversity and signatures of directional selection associated with immunity genes, in contrast with agricultural traits. Furthermore, cultures of mixed genotypes exhibited superior performances for both pathogen resistance and agricultural traits. We showed that, within one single landrace, traditional farmer practices selected optimal agricultural traits while maintaining diversity enabling pathogen resistance. This study elucidates the complex interplay between genetic diversity, natural selection related to pathogens, and selection for agricultural traits within traditional landraces, providing insights into sustainable agricultural practices in diverse cropping systems.

genomics↗