Biology subjects

Dzyubenko, E.

Publications and source records attributed to Dzyubenko, E..

9 recordsLinked to original sources

bioRxiv2026

Optimizing resource allocation in Miscanthus breeding with sparse testing designs for genomic prediction

Phenotyping high-biomass perennial crops is laborious and the rate of genetic gain in perennial crop breeding programs is typically low. So, it is especially important to identify methods that produce efficiency gains in the breeding process. Miscanthus is a C4 perennial grass with favorable characteristics for producing biomass as a feedstock for biofuels and diverse biobased products. Increasing biomass yield will increase profitability and environmental benefits, so is a key target for Miscanthus breeding. In addition, the identification of well-adapted genotypes across a wide range of environmental conditions requires the establishment of multi-environment trials (METs). Sparse testing is a genomic prediction-based strategy that reduces the phenotyping costs in METs by selecting a subset of genotypes to evaluate in a subset of environments and then predicts the performance of the unobserved genotype-environment combinations. A Miscanthus sacchariflorus (MSA) population comprising 336 genotypes observed across three environments was analyzed. Three prediction models considering main effects (environments, genotypes, genomic) and interaction effects (genotype-by-environment; GxE interaction) were implemented for forecasting dry biomass yield (YDY), total culm (TCM), average internode length (AIL), and culm node number (CNN). Multiple calibration sets based on different compositions and sizes were considered to evaluate performance in terms of the predictive ability (PA) and the mean square error (MSE) for a fixed testing set size. The training set size ranged from 52 to 112 to predict a fixed set of 224 unobserved genotypes across all three environments. The results showed that the model accounting for GxE interaction presented the highest PA and the lowest MSE for CNN (PA: [~]0.77, MSE: [~]0.5) and YDY (PA: [~]0.70, MSE: [~]1.3) while for TCM and AIL these ranged from [~]0.28 to 0.41 and [~]1.3 to 4.3, respectively. Overall, varying training sets and allocation strategies did not affect PA and MSE, with 52 non-overlapping and 0 overlapping genotypes per environment as the optimal cost-effective allocation framework. This suggests that implementing sparse testing designs could significantly reduce phenotyping costs by fivefold, without compromising PA in breeding programs for perennial crops such as Miscanthus.

genomics↗

bioRxiv2026

Multi-trait Multi-environment Genomic Prediction Strategies for Miscanthus sacchariflorus Populations

Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (GxExT) and (2) two single-trait multi-environment (STME) models (with and without GxE interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.

genomics↗

bioRxiv2026

Weather Characterization for Optimizing Genomic Prediction in Miscanthus sacchariflorus

Environmental factors affect crop growth and development thus their consideration across sites and years become essential for genotypic evaluation. Genomic selection (GS) has been broadly implemented to accelerate breeding cycles by skipping field evaluations thus allowing early identification of outperforming genotypes. In this study, 7,740 phenotypic records corresponding to 516 Miscanthus sacchariflorus genotypes evaluated in five locations across three years were considered for analysis. Additionally, environmental data on six weather covariates was implemented to characterize similarities between locations. Different sets of locations of variable sizes were used for model calibration based on two cross-validations (CV00 and CV0) schemes leaving out one location at a time. Predictive ability across locations of the best model varied between 0.45 and 0.90 for both schemes. These results were compared to associate predictive ability in function of weather patterns between training and testing sets to allow models calibration optimization. We found it is feasible to optimize resource allocation by considering environmentally correlated sets. In most cases, the information from only one and, at most, two locations were enough to deliver better results than using all four locations, reducing training sets by up to 75%. The results obtained shed light on helping breeders make informed decisions considering weather data when designing evaluations.

genomics↗

bioRxiv2026

ENHANCING GENOMIC PREDICTION MODELS IN MISCANTHUS POPULATIONS BY INCORPORATING THE GENOTYPE-BY-ENVIRONMENT INTERACTION

Giant Miscanthus giganteus (Mxg) is one of the most promising perennial crops to generate biomass feedstock for bioenergy and biobased products. It is derived from the natural inter-species hybridization of Miscanthus sacchariflorus (Msa) and Miscanthus sinensis (Msi) species, thus population improvement within these species is crucial. Genomic selection (GS) is an attractive option to accelerate breeding of perennial grasses, such as Miscanthus, which requires up to three years of evaluation to produce reliable phenotypic data. Hence, genotypes are observed in multiple years and locations causing inconsistent response patterns from one year to the next, between location, and/or location-by-year combinations. These inconsistencies are known as the genotype-by-environment interaction effect (GxE). Although GS has been successfully implemented in multiple annual crops where straightforward cross-validation schemes exist to assess the levels of predictive ability that can be reached, for perennial crops new cross-validation schemes will help avoid data contamination. Here, we propose a series of cross-validation schemes to evaluate model performance for perennial crops. We perform a case study by analyzing one panel of each species (516 genotypes of Msa, 280 genotypes of Msi) scored for biomass yield at different locations around the world over several years. The results of the different cross-validation schemes provide insights about the usefulness of GS to accelerate the breeding process of Miscanthus species. In addition, leveraging the GxE effects of different types significantly increases predictive ability (up to 10% in Msa and 30% for Msi) compared to the conventional approaches based on main effects only.

genomics↗

bioRxiv2026

Histone neutralization protects the ischemic brain against stroke-associated pneumonia

Bacterial pneumonia aggravates ischemic stroke via mechanisms that still remain to be determined. In ischemic stroke patients and mice exposed to middle cerebral artery occlusion, we show that stroke-associated pneumonia markedly worsens clinical stroke outcome. In mice, pneumonia induced 3 days after stroke impaired neurological recovery and increased brain neutrophil infiltrates, blood-brain barrier breakdown, cerebral microvascular thrombosis, and progressive brain atrophy. The antibiotic amoxicillin only partially ameliorated pneumonia-associated neurological deficits and neutrophil infiltrates. Neutrophils were critical mediators of pneumonia-induced blood-brain barrier breakdown and microvascular thrombosis. Notably, administration of a neutralizing anti-histone antibody during pneumonia--unlike degradation or blockade of neutrophil extracellular trap formation or myeloperoxidase inhibition--restored long-term neurological recovery and prevented brain atrophy in stroke-associated pneumonia mice. This study identifies extracellular histones as key drivers of secondary inflammatory brain injury and establishes histone neutralization as a therapeutic strategy with an extended treatment window in the post-acute stroke phase. One Sentence SummaryNeutralizing extracellular histones reverses pneumonia-driven secondary brain injury and restores long-term recovery after ischemic stroke.

neuroscience↗

bioRxiv2025

Astrocytic PIEZO activation by heartbeat sound promotes extracellular matrix and maturation in human brain organoids

Heartbeat sound is one of the first rhythmic stimuli encountered by the developing human brain, yet its biological role has remained unexplored. Here we show that heartbeat sound promotes structural and functional maturation of human cortical organoids with a physiological astrocyte-to-neuron ratio. Continuous stimulation with heartbeat expanded the extracellular space (ECS), visualized by super-resolution 3D STED and 2-photon shadow imaging, and increased extracellular matrix (ECM) synthesis, detected by LC-MS/MS proteomics. Heartbeat sound promoted neuronal and astrocytic differentiation, synaptogenesis, and organoid maturation, as shown by single-cell RNA sequencing, synaptic marker immunohistochemistry, and high-density multielectrode electrophysiology. Transcriptomic analyses demonstrated astrocyte-specific expression of mechanosensitive PIEZO channels. Using Ca2+ imaging, we confirmed that low-frequency sound stimulation, including heartbeat, activates PIEZO-mediated Ca2+ responses, which in turn upregulate astrocytic ECM synthesis. Experiments with biomimetic hydrogels demonstrated that physiological matrix stiffness attenuates PIEZO activation, suggesting a mechanoprotective mechanism. Our findings demonstrate a fundamental mechanism for inducing ECM synthesis and neural differentiation through astrocytic PIEZO activation by heartbeat sound, suggesting that interoception of the internal acoustic environment is an underappreciated driver of human brain development. HighlightsO_LIHeartbeat sound activates PIEZO ion channels C_LIO_LIAstrocytic PIEZO activation promotes extracellular matrix synthesis C_LIO_LIHeartbeat sound stimulates neural differentiation and brain organoid maturation C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/683816v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1ba3159org.highwire.dtl.DTLVardef@fdd741org.highwire.dtl.DTLVardef@13ef417org.highwire.dtl.DTLVardef@b3064_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Perineuronal net loosening associates with the remodeling of GABAergic terminals on motor cortical layer 5 interneurons and precedes motor coordination recovery post stroke

Stroke remains one of the leading causes of long-term disability worldwide, and the development of effective restorative therapies is hindered by an incomplete understanding of intrinsic brain recovery mechanisms. Here we explored how perineuronal nets (PNNs), the facet-like extracellular matrix layers surrounding fast-spiking interneurons, contribute to neurological recovery after focal cerebral ischemia in mice with and without induced stroke tolerance. Due to the insufficient resolution of conventional microscopy methods, the contribution of structural changes in PNNs to post stroke brain plasticity remained unknown. Using superresolution stimulated emission depletion (STED) and structured illumination (SR-SIM) microscopy, we revealed that PNN facets become larger and less dense in the post-acute stroke phase. These morphological alterations in PNNs are transient and correlate with the increased surface of contact between activated microglia and PNN-coated neurons. The transient loosening of PNNs after stroke allows for dynamic reorganization of GABAergic axonal terminals on inhibitory interneurons in the motor cortical layer 5. The coherent remodeling of PNNs and their perforating inhibitory synapses precedes the recovery of motor coordination after stroke and depends on the severity of the ischemic injury. Our data suggest a novel mechanism of motor cortical plasticity after stroke, and we propose that prolonging PNN loosening during the post-acute period can extend the opening neuroplasticity window into the chronic stroke phase. HighlightsO_LIPNNs are degraded partially and transiently post-stroke C_LIO_LITransient attenuation of PNNs correlates with GABAergic synapse remodeling C_LIO_LITransient attenuation of PNNs precedes functional recovery post stroke C_LIO_LIActivated microglia preferentially contact PNN-coated neurons post stroke C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/510951v2_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@13815d3org.highwire.dtl.DTLVardef@1210182org.highwire.dtl.DTLVardef@1ea12e6org.highwire.dtl.DTLVardef@7ed5b1_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

Manage flowering time in Miscanthus and sugarcane to facilitate intra- and intergeneric crosses

Miscanthus is a close relative of Saccharum and a potentially valuable genetic resource for improving sugarcane. Differences in flowering time within and between Miscanthus and Saccharum hinders intra- and interspecific hybridizations. A series of greenhouse experiments were conducted over three years to determine how to synchronize flowering time of Saccharum and Miscanthus genotypes. We found that day length was an important factor influencing when Miscanthus and Saccharum flowered. Sugarcane could be induced to flower in a central Illinois greenhouse using supplemental lighting to reduce the rate at which days shortened during the autumn and winter to 1 min d-1, which allowed us to synchronize the flowering of some sugarcane genotypes with Miscanthus genotypes primarily from low latitudes. In a complementary growth chamber experiment, we evaluated 33 Miscanthus genotypes, including 28 M. sinensis, 2 M. floridulus, and 3 M. xgiganteus collected from 20.9{degrees} S to 44.9{degrees} N for response to three day lengths (10 h, 12.5 h, and 15 h). High latitude-adapted M. sinensis flowered mainly under 15 h days, but unexpectedly, short days resulted in short, stocky plants that did not flower; in some cases, flag leaves developed under short days but heading did not occur. In contrast, for M. sinensis and M. floridulus from low latitudes, shorter day lengths typically resulted in earlier flowering, and for some low latitude genotypes, 15 h days resulted in no flowering. However, the highest ratio of reproductive shoots to total number of culms was typically observed for 12.5 h or 15 h days. Latitude of origin was significantly associated with culm length, and the shorter the days, the stronger the relationship. Nearly all entries achieved maximal culm length under the 15 h treatment, but the nearer to the equator an accession originated, the less of a difference in culm length between the short-day treatments and the 15 h day treatment. Under short days, short culms for high-latitude accessions was achieved by different physiological mechanisms for M. sinensis genetic groups from the mainland in comparison to those from Japan; for mainland accessions, the mechanism was reduced internode length, whereas for Japanese accessions the phyllochron under short days was greater than under long days. Thus, for M. sinensis, short days typically hastened floral induction, consistent with the expectations for a facultative short-day plant. However, for high latitude accessions of M. sinensis, days less than 12.5 h also signaled that plants should prepare for winter by producing many short culms with limited elongation and development; moreover, this response was also epistatic to flowering. Thus, to flower M. sinensis that originates from high latitudes synchronously with sugarcane, the former needs day lengths >12.5 h (perhaps as high as 15 h), whereas that the latter needs day lengths <12.5 h.

plant biology↗

bioRxiv2020

Extracellular matrix supports excitation-inhibition balance in neuronal networks by stabilizing inhibitory synapses

Maintaining the balance between excitation and inhibition is essential for the appropriate control of neuronal network activity. Sustained excitation-inhibition (E-I) balance relies on the orchestrated adjustment of synaptic strength, neuronal activity and network circuitry. While growing evidence indicates that extracellular matrix (ECM) of the brain is a crucial regulator of neuronal excitability and synaptic plasticity, it remains unclear whether and how ECM contributes to neuronal circuit stability. Here we demonstrate that the integrity of ECM supports the maintenance of E-I balance by retaining inhibitory connectivity. Depletion of ECM in mature neuronal networks preferentially decreases the density of inhibitory synapses and the size of individual inhibitory postsynaptic scaffolds. After ECM depletion, inhibitory synapse strength homeostatically increases via the reduction of presynaptic GABAB receptors. However, the inhibitory connectivity reduces to an extent that inhibitory synapse scaling is no longer efficient in controlling neuronal network activity. Our results indicate that the brain ECM preserves the balanced network state by stabilizing inhibitory synapses. Significance statementThe question how the brains extracellular matrix (ECM) controls neuronal plasticity and network activity is key for an appropriate understanding of brain functioning. In this study, we demonstrate that ECM depletion much more strongly affects the integrity of inhibitory than excitatory synapses in vitro and in vivo. We revealed that by retaining inhibitory connectivity, ECM ensures the efficiency of inhibitory control over neuronal network activity. Our work significantly expands our current state of knowledge about the mechanisms of neuronal network activity regulation. Our findings are similarly relevant for researchers working on the physiological regulation of neuronal plasticity in vitro and in vivo and for researchers studying the remodeling of neuronal networks upon brain injury, where prominent ECM alterations occur.

neuroscience↗