Biology subjects

Lu, J.

Publications and source records attributed to Lu, J..

At least 163 records · Page 9Linked to original sources

bioRxiv2024

A systematic evaluation of highly variable gene selection methods for single-cell RNA-sequencing

BackgroundSelecting highly variable features is a crucial step in most analysis pipelines of single-cell RNA-sequencing (scRNA-seq) data. Despite numerous methods proposed in recent years, a systematic understanding of the best solution is still lacking. ResultsHere, we systematically evaluate 47 highly variable gene (HVG) selection methods, consisting of 21 baseline methods developed based on different data transformations and mean-variance adjustment techniques and 26 hybrid methods developed based on mixtures of baseline methods. Across 19 diverse benchmark datasets, 18 objective evaluation criteria per method, and 5,358 analysis settings, we observe that no single baseline method consistently outperforms the others across all datasets and criteria. However, hybrid methods as a group robustly outperform individual baseline methods. Based on these findings, a new HVG selection approach, mixture HVG selection (mixHVG), that incorporates top-ranked features from multiple baseline methods is proposed as a better solution to HVG selection. An open source R package mixhvg is developed to enable convenient use of mixHVG and its integration into users data analysis pipelines. ConclusionOur benchmark study not only provides a systematic comparison of existing methods, leading to a better HVG selection solution, but also creates a pipeline and resource consisting of diverse benchmark data and criteria for evaluating new methods in the future.

bioinformatics↗

bioRxiv2024

Dysfunctional mechanotransduction regulates the progression of PIK3CA-driven vascular malformations

Somatic activating mutations in PIK3CA are common drivers of vascular and lymphatic malformations. Despite common biophysical signatures of tissues susceptible to lesion formation, including compliant extracellular matrix and low rates of perfusion, lesions vary in clinical presentation from localized cystic dilatation to diffuse and infiltrative vascular dysplasia. The mechanisms driving the differences in disease severity and variability in clinical presentation and the role of the biophysical microenvironment in potentiating progression are poorly understood. Here, we investigate the role of hemodynamic forces and the biophysical microenvironment in the pathophysiology of vascular malformations, and we identify hemodynamic shear stress and defective endothelial cell mechanotransduction as key regulators of lesion progression. We found that constitutive PI3K activation impaired flow-mediated endothelial cell alignment and barrier function. We show that defective shear stress sensing in PIK3CAE542Kendothelial cells is associated with reduced myosin light chain phosphorylation, junctional instability, and defective recruitment of vinculin to cell-cell junctions. Using 3D microfluidic models of the vasculature, we demonstrate that PIK3CAE542Kmicrovessels apply reduced traction forces and are unaffected by flow interruption. We further found that draining transmural flow resulted in increased sprouting and invasion responses in PIK3CAE542K microvessels. Mechanistically, constitutive PI3K activation decreased cellular and nuclear elasticity resulting in defective cellular tensional homeostasis in endothelial cells which may underlie vascular dilation, tissue hyperplasia, and hypersprouting in PIK3CA-driven venous and lymphatic malformations. Together, these results suggest that defective nuclear mechanics, impaired cellular mechanotransduction, and maladaptive hemodynamic responses contribute to the development and progression of PIK3CA-driven vascular malformations.

bioengineering↗

bioRxiv2024

Identifying unmeasured heterogeneity in microbiome data via quantile thresholding (QuanT)

BackgroundMicrobiome data, like other high-throughput data, suffer from technical heterogeneity stemming from differential experimental designs and processing. In addition to measured artifacts such as batch effects, there is heterogeneity due to unknown or unmeasured factors, which lead to spurious conclusions if unaccounted for. With the advent of large-scale multi-center microbiome studies and the increasing availability of public datasets, this issue becomes more pronounced. Current approaches for addressing unmeasured heterogeneity in high-throughput data were developed for microarray and/or RNA sequencing data. They cannot accommodate the unique characteristics of microbiome data such as sparsity and over-dispersion. ResultsHere, we introduce Quantile Thresholding (QuanT), a novel non-parametric approach for identifying unmeasured heterogeneity tailored to microbiome data. QuanT applies quantile regression across multiple quantile levels to threshold the microbiome abundance data and uncovers latent heterogeneity using thresholded binary residual matrices. We validated QuanT using both synthetic and real microbiome datasets, demonstrating its superiority in capturing and mitigating heterogeneity and improving the accuracy of downstream analyses, such as prediction analysis, differential abundance tests, and community-level diversity evaluations. ConclusionsWe present QuanT, a novel tool for comprehensive identification of unmeasured heterogeneity in microbiome data. QuanTs distinct non-parametric method markedly enhances downstream analyses, serving as a valuable tool for data integration and comprehensive analysis in microbiome research.

bioinformatics↗

bioRxiv2024

Identification of stable reference genes in Edwardsiella ictaluri for accurate gene expression analysis

Edwardsiella ictaluri is a Gram-negative bacterium causing enteric septicemia of catfish (ESC), leading to significant economic losses in the catfish farming industry. RT-PCR analysis is a powerful technique for quantifying gene expression, but normalization of expression data is critical to control experimental errors. Using stable reference genes, also known as housekeeping genes, is a common strategy for normalization, yet reference gene selection often lacks proper validation. In this work, our goal was to determine the most stable reference genes in E. ictaluri during catfish serum exposure and various growth phases. To this goal, we evaluated the expression of 27 classical reference genes (16SrRNA, abcZ, adk, arc, aroE, aspA, atpA, cyaA, dnaG, fumC, g6pd, gdhA, glnA, gltA, glyA, grpE, gyrB, mdh, mutS, pgi, pgm, pntA, recA, recP, rpoS, tkt, and tpi) using five analytical programs (GeNorm, BestKeeper, NormFinder, Comparative {Delta}CT, and Comprehensive Ranking). Results showed that aspA, atpA, dnaG, glyA, gyrB, mutS, recP, rpoS, tkt, and tpi were the most stable reference genes during serum exposure, whereas fumC, g6pd, gdhA, glnA, and mdh were the least stable. During various growth phases, aspA, g6pd, glyA, gyrB, mdh, mutS, pgm, recA, recP, and tkt were the most stable, while 16S rRNA, atpA, grpE, and tpi were the least stable. At least four analysis methods confirmed the stability of aspA, glyA, gyrB, mutS, recP, and tkt during serum exposure and different growth stages. However, no consensus was found among the programs for unstable reference genes under both conditions.

microbiology↗

bioRxiv2024

Neural Mechanism Underlying Successful Classification of Amnestic Mild Cognitive Impairment Using Multi-Sensory-Evoked Potentials

Early detection of amnestic mild cognitive impairment (aMCI) is crucial for timely interventions. This study combines scalp recordings of lateralized auditory, visual, and somatosensory stimuli with a flexible and interpretable support vector machine learning pipeline to differentiate individuals diagnosed with aMCI from healthy controls. Event-related potentials (ERPs) and functional connectivity (FC) matrices from each modality successfully predicted aMCI. Reduced ERP amplitude in aMCI contributed to classification. The analysis of FC using phase-locking value revealed higher FC in aMCI than controls in frontal regions, which predicted worse cognitive performance, and lower FC in posterior regions from delta to alpha frequency. We observe optimal classification accuracy (96.1%), sensitivity (97.7%) and specificity (94.3%) when combining information from all sensory conditions than when using information from a single modality. The results highlight the clinical potential of sensory-evoked potentials in detecting aMCI, with optimal classification using both amplitude and oscillatory-based FC measures from multiple modalities.

neuroscience↗

bioRxiv2024

3D Reconstruction of Neuronal Allometry and Neuromuscular Projections in Asexual Planarians Using Expansion Tiling Light Sheet Microscopy

The intricate coordination of the neural network in planarian growth and regeneration has remained largely unrevealed, partly due to the challenges of imaging the central nervous system (CNS) in three dimensions (3D) with high resolution and within a reasonable timeframe. To address this gap in systematic imaging of the CNS in planarians, we adopted high-resolution, nanoscale imaging by combining tissue expansion and tiling light-sheet microscopy, achieving up to 4-fold linear expansion. Using an automatic 3D cell segmentation pipeline, we quantitatively profiled neurons and muscle fibers at the single-cell level in over 400 wild-type planarians during homeostasis and regeneration. We validated previous observations of neuronal cell number changes and muscle fiber distribution. We found that the increase in neuron cell number tends to lag behind the rapid expansion of somatic cells during the later phase of homeostasis. By imaging the planarian with up to 120 nm resolution, we also observed distinct muscle distribution patterns at the anterior and posterior poles. Furthermore, we investigated the effects of {beta}-catenin RNAi on muscle fiber distribution at the posterior pole, consistent with changes in anterior-posterior polarity. The glial cells were observed to be close in contact with dorsal-ventral muscle fibers. Finally, we observed disruptions in neural-muscular networks in inr-1 RNAi planarians. These findings provide insights into the detailed structure and potential functions of the neural-muscular system in planarians and highlight the accessibility of our imaging tool in unraveling the biological functions underlying their diverse phenotypes and behaviors.

developmental biology↗

bioRxiv2024

Polyamines sustain epithelial regeneration in aged intestines by modulating protein homeostasis

Aging hampers the regenerative potential of intestinal epithelium across species including humans, yet the underlying causes remain elusive. Here, using proteomic and metabolomic profiling of intestinal tissues together with functional assays, we characterized the temporal dynamics of regeneration following injury induced by 5-fluorouracil, a commonly used chemotherapeutic agent. Comparison of regeneration dynamics in mice of different ages revealed the emergence of a proteostasis stress signature and increased levels of polyamines following injury exclusively in old epithelia. Mechanistically, we show that delayed regeneration is an intrinsic feature of aged epithelial cells that display reduced protein synthesis and accumulation of ubiquitylated proteins. Notably, dietary restriction followed by re-feeding prior to injury increases polyamine pathway activation, enhances protein synthesis, and restores the regenerative capacity of aged intestines. Our findings highlight promising epithelial targets for interventions aimed at tackling the decline in tissue repair mechanisms associated with aging.

molecular biology↗

bioRxiv2024

FLASH proton reirradiation, with or without hypofractionation, mitigates chronic toxicity in the normal murine intestine, skin, and bone.

Background and purposeThe normal tissue sparing afforded by FLASH radiotherapy (RT) is being intensely investigated for potential clinical translation. Here, we studied the effects of FLASH proton RT (F-PRT) in the reirradiation setting, with or without hypofractionation. Chronic toxicities in three murine models of normal tissue toxicity including the intestine, skin, and bone were investigated. Materials and methodsIn studies of the intestine, single-dose irradiation was performed with 12 Gy of Standard proton RT (S-PRT), followed by a second dose of 12 Gy of F-PRT or S-PRT. Additionally, a hypofractionation scheme was applied in the reirradiation setting (3 x 6.4 Gy of F-PRT or S-PRT, given every 48 hrs). In studies of skin/bone of the murine leg, 15 Gy of S-PRT was followed by hypofractionated reirradiation with F-PRT or S-PRT (3 x 11 Gy). ResultsCompared to reirradiation with S-PRT, F-PRT reduced intestinal fibrosis and collagen deposition in the reirradiation setting and significantly increased survival rate, demonstrating its protective effects on intestinal tissues. In previously irradiated leg tissues, reirradiation with hypofractionated F-PRT created transient dermatitis that fully resolved in contrast to reirradiation with hypofractionated S-PRT. Lymphedema was also alleviated after a second course of radiation with F-PRT, along with significant reductions in the accumulation of fibrous connective tissue in the skin compared to mice reirradiated with S-PRT. The delivery of a second course of fractionated S-PRT induced tibial fractures in 83.3% of the mice, whereas only 20% of mice reirradiated with F-PRT presented with fractures. ConclusionThese studies provide the first evidence of the sparing effects of F-PRT, in the setting of hypofractionated reirradiation. The results support FLASH as highly relevant to the reirradiation regimen where it exhibits significant potential to minimize chronic complications for patients undergoing RT.

cell biology↗

bioRxiv2024

Opto-Myomatrix: μLED integrated microelectrode arrays for optogenetic activation and electrical recording in muscle tissue

ObjectiveOptogenetics is a valuable and widely-used technique that allows precise perturbations of selected groups of cells with high temporal and spatial resolution by using optical systems and genetic engineering technologies. This study aims to develop Opto-Myomatrix, a novel optogenetic tool for precise muscle fiber control and high-resolution electrophysiological recording. MethodBased on a flexible and biocompatible polymer substrate, the device incorporates an integrated {micro}LED that delivers light at 465 nm for optogenetic stimulation and 32 PEDOT:PSS-coated electrodes for electromyography (EMG) recording. We also added a reflector to improve optical power output. ResultsThe fabricated Opto-Myomatrix device achieves an optical output intensity as high as 129.46 mW/mm2 in the direction of interest, which is enhanced by nearly 100%. The PEDOT:PSS-coated electrodes exhibit 85% lower impedance than uncoated contacts, enabling high signal-to-noise EMG acquisition. We investigated heat dissipation characteristics of the {micro}LED through measurements and finite element simulations, confirming that temperature changes remain within safe limits. The Opto-Myomatrix device was implanted in transgenetic mice and successfully stimulated targeted jaw muscles, inducing movement while simultaneously capturing EMG signals. ConclusionThe Opto-Myomatrix effectively combines precise optical stimulation and high-quality EMG recording in a flexible and biocompatible device, focusing on optogenetic applications in muscle. SignificanceWhile optogenetic tools are well-established for brain and central nervous system (CNS) research, the development of Opto-Myomatrix addresses a critical gap by enabling precise muscle fiber control and high-resolution recording for advancing neuromuscular studies.

bioengineering↗

bioRxiv2024

Flexible EMG arrays with integrated electronics for scalable electrode density

Recent developments in electrode technology have demonstrated the power of flexible microelectrode arrays (FMEAs) for measuring muscle activity at high resolution. We recently introduced the Myomatrix array, an FMEA optimized for measuring the activity of individual motor units (the collection of muscle fibers innervated by a single motor neuron) [1] in freely behaving animals. Although FMEAs are fundamentally changing the way electromyography (EMG) is acquired, the number of recording channels is limited by the size of the plug that interfaces with the signal processing hardware and the density of electrode connections on the array. Increasing EMG channel count and supporting electrophysiological studies in smaller animals depends on two seemingly incompatible goals: reducing device size while increasing the number of recording channels. The solution to these goals is to increase the channel count per wire output. Current off-the-shelf designs require a separate headstage and FMEA to be used simultaneously. In our prior devices [1], each FMEA had a dedicated wire output for every electrode input, creating a channel density of 1:1. To improve this channel density, we have developed an FMEA with an integrated digital amplifier (Bare-Die RHD2216, INTAN INC, USA). The design of the FMEA reduces the footprint of the devices back end by 74% and relocates the Intan bare die from the headstage to the FMEA itself, creating a channel density of 1:3.2. Our methodology combines standard FMEA microfabrication with wire-bonding and surface-mounted components, enabling direct integration into a Serial Peripheral Interface (SPI) connection into the device itself, without any separate headstage. With this initial device there is a 1 : 3.2 channel density; however, our method allows using other bare die amplifiers (Intan, Inc., USA) for a channel density of 1:12.8. Our findings present a robust technique for chip embedding in custom FMEAs applicable to in-vivo electrophysiology

neuroscience↗

bioRxiv2024

Innate immune system signaling and CD11b+CD11c+CD103+ cell migration to the brain underlie changes in mouse behavior after microbial colonization.

Background and AimsAccumulating evidence suggests the microbiota is a key factor in disorders of gut-brain interaction (DGBI), by affecting host immune and neural systems. However, the underlying mechanisms remain elusive due to their complexity and clinical heterogeneity of patients with DGBIs. We aimed to identify neuroimmune pathways that are critical in microbiota-gut-brain communication during de novo gut colonization. MethodsWe employed a combination of gnotobiotic and state-of-the-art microbial tools, behavioral analysis, immune and pharmacological approaches. Germ-free wild type, MyD88-/- Ticam1-/- and SCID mice were studied before and after colonization with specific pathogen-free microbiota, Altered Schaedler Flora, E. coli or S. typhimurium (permanent or transient colonizers). TLR agonists and antagonists, CCR7 antagonist or immunomodulators were used to study immune pathways. We assessed brain c-Fos, brain-derived neurotrophic factor, and dendritic and glial cells by immunofluorescence, expression of neuroimmune genes by NanoString and performed brain proteomics. ResultsBacterial monocolonization, conventionalization or administration of microbial products to germ-free mice altered mouse behavior similarly, acting through Toll-like receptor or nucleotide-binding oligomerization domain signaling. The process required CD11b+CD11c+CD103+ cell activation and migration into the brain. The change in behavior did not require the continued presence of bacteria and was associated with activation of multiple neuro-immune networks in the gut and the brain. ConclusionsChanges in neural plasticity occur rapidly upon initial gut microbial colonization and involve innate immune signaling to the brain, mediated by CD11b+CD11c+CD103+ cell migration. The results identify a new target with therapeutic potential for DGBIs developing in context of increased gut and blood-brain barrier permeability. HighlightsO_LIMicrobiota impairment is a key factor in disorders of gut-brain interaction (DGBI) C_LIO_LIMicrobial colonization induces changes in brain and behavior via innate immunity C_LIO_LIMicrobial colonization activates multiple neuro-immune networks in gut and brain C_LIO_LIBehavioral change is mediated by CD11b+CD11c+CD103+ cells migration to the brain C_LI

animal behavior and cognition↗

bioRxiv2024

B cell receptor dependent enhancement of dengue virus infection

Dengue virus (DENV) is the causative agent of dengue, a mosquito-borne disease that represents a significant and growing public health burden around the world. A unique pathophysiological feature of dengue is immune-mediated enhancement, wherein preexisting immunity elicited by a primary infection can enhance the severity of a subsequent infection by a heterologous DENV serotype. A leading mechanistic explanation for this phenomenon is antibody dependent enhancement (ADE), where sub-neutralizing concentrations of DENV-specific IgG antibodies facilitate entry of DENV into Fc{gamma}R expressing cells such as monocytes, macrophages, and dendritic cells. Accordingly, this model posits that phagocytic mononuclear cells are the primary reservoir of DENV. However, analysis of samples from individuals experiencing acute DENV infection reveals that B cells are the largest reservoir of infected circulating cells, representing a disconnect in our understanding of immune-mediated DENV tropism. In this study, we demonstrate that the expression of a DENV-specific B cell receptor (BCR) renders cells highly susceptible to DENV infection, with the infection-enhancing activity of the membrane-restricted BCR correlating with the ADE potential of the IgG version of the antibody. In addition, we observed that the frequency of DENV-infectable B cells increases in previously flavivirus-naive volunteers after a primary DENV infection. These findings suggest that BCR-dependent infection of B cells is a novel mechanism immune-mediated enhancement of DENV-infection.

immunology↗

bioRxiv2024

Myo-optogenetics: optogenetic stimulation and electrical recording in skeletal muscles

Complex movements involve highly coordinated control of local muscle elements. Highly controlled perturbations of motor outputs can reveal insights into the neural control of movements. Here we introduce an optogenetic method, compatible with electromyography (EMG) recordings, to perturb muscles in transgenic mice. By expressing channelrhodopsin in muscle fibers, we achieved noninvasive, focal activation of orofacial muscles, enabling detailed examination of the mechanical properties of optogenetically evoked jaw muscle contractions. We demonstrated simultaneous EMG recording and optical stimulation, revealing the electrophysiological characteristics of optogenetically triggered muscle activity. Additionally, we applied optogenetic activation of muscles in physiologically and behaviorally relevant settings, mapping precise muscle actions and perturbing active behaviors. Our findings highlight the potential of muscle optogenetics to precisely manipulate muscle activity, offering a powerful tool for probing neuromuscular control systems and advancing our understanding of motor control.

neuroscience↗

bioRxiv2024

Comprehensive analysis of microbial content in whole-genome sequencing samples from The Cancer Genome Atlas project

In recent years, a growing number of publications have reported the presence of microbial species in human tumors and of mixtures of microbes that appear to be highly specific to different cancer types. Our recent re-analysis of data from three cancer types revealed that technical errors have caused erroneous reports of numerous microbial species found in sequencing data from The Cancer Genome Atlas (TCGA) project. Here we have expanded our analysis to cover all 5,734 whole-genome sequencing (WGS) data sets currently available from TCGA, covering 25 distinct types of cancer. We analyzed the microbial content using updated computational methods and databases, and compared our results to those from two major recent studies that focused on bacteria, viruses, and fungi in cancer. Our results expand upon and reinforce our recent findings, which showed that the presence of microbes is far smaller than had been previously reported, and that many species identified in TCGA data are either not present at all, or are known contaminants rather than microbes residing within tumors. As part of this expanded analysis, and to help others avoid being misled by flawed data, we have released a dataset that contains detailed read counts for bacteria, viruses, archaea, and fungi detected in all 5,734 TCGA samples, which can serve as a public reference for future investigations. One-sentence summaryAnalysis of microbial content in 5,734 whole-genome sequencing samples from TCGA yields a comprehensive new resource for investigating the role of microbes in cancer.

cancer biology↗

bioRxiv2024

DeepVID v2: Self-Supervised Denoising with Decoupled Spatiotemporal Enhancement for Low-Photon Voltage Imaging

SignificanceVoltage imaging is a powerful tool for studying the dynamics of neuronal activities in the brain. However, voltage imaging data are fundamentally corrupted by severe Poisson noise in the low-photon regime, which hinders the accurate extraction of neuronal activities. Self-supervised deep learning denoising methods have shown great potential in addressing the challenges in low-photon voltage imaging without the need for ground truth, but usually suffer from the tradeoff between spatial and temporal performance. AimWe present DeepVID v2, a novel self-supervised denoising framework with decoupled spatial and temporal enhancement capability to significantly augment low-photon voltage imaging. ApproachDeepVID v2 is built on our original DeepVID framework,1,2 which performs frame-based denoising by utilizing a sequence of frames around the central frame targeted for denoising to leverage temporal information and ensure consistency. The network further integrates multiple blind pixels in the central frame to enrich the learning of local spatial information. Additionally, DeepVID v2 introduces a new edge extraction branch to capture fine structural details in order to learn high spatial resolution information. ResultsWe demonstrate that DeepVID v2 is able to overcome the tradeoff between spatial and temporal performance, and achieve superior denoising capability in resolving both high-resolution spatial structures and rapid temporal neuronal activities. We further show that DeepVID v2 is able to generalize to different imaging conditions, including time-series measurements with various signal-to-noise ratios (SNRs) and in extreme low-photon conditions. ConclusionsOur results underscore DeepVID v2 as a promising tool for enhancing voltage imaging. This framework has the potential to generalize to other low-photon imaging modalities and greatly facilitate the study of neuronal activities in the brain.

neuroscience↗

bioRxiv2024

Development of the overlapping network modules in the human brain

Developmental connectomic studies have shown that the modular organization of functional networks in the human brain undergoes substantial reorganization with age to support cognitive growth. However, these studies implicitly assume that each brain region belongs to one and only one specific network module, ignoring the potential spatial overlap between functional modules. How the overlapping functional modular architecture develops and whether this development is related to structural signatures remain unknown. Using longitudinal multimodal structural, functional, and diffusion MRI data from 305 children (aged 6-14 years), we investigated the development of the overlapping modular architecture of functional networks, and further explored their structural associations. Specifically, an edge-centric network model was used to identify the overlapping functional modules, and the nodal overlap in module affiliations was quantified using the entropy measure. We showed a remarkable regional inhomogeneity in module overlap in children, with higher entropy in the ventral attention, somatomotor, and subcortical networks and lower entropy in the visual and default-mode networks. Furthermore, the overlapping modules developed in a linear, spatially dissociable manner from childhood to adolescence, with significantly reduced entropy in the prefrontal cortex and putamen and increased entropy in the parietal lobules. Personalized overlapping modular patterns capture individual brain maturity as characterized by brain age. Finally, the overlapping functional modules can be significantly predicted by integrating gray matter morphology and white matter network properties. Our findings highlight the maturation of overlapping network modules and their structural substrates, thereby advancing our understanding of the principles of connectome development.

neuroscience↗

bioRxiv2024

Maternal obesity may disrupt offspring metabolism by inducing oocyte genome hyper-methylation via increased DNMTs

Maternal obesity has deleterious effects on the process of establishing oocyte DNA methylation; yet the underlying mechanisms remain unclear. In the present study, we found that maternal obesity induced by high-fat diet (HFD) disrupted the genomic methylation of oocytes, and that at least a part of the altered DNA methylation was transmitted to the F2 oocytes and the livers via females. We further examined the metabolome of serum and found that the altered metabolites such as melatonin may play a key role in the disrupted genomic methylation in the oocytes of obese mice. We further found that exogenous melatonin treatment significantly reduced the hyper-methylation of HFD oocytes, and the increased expression of DNMT3a and DNMT1 in HFD oocytes was also decreased. To address how melatonin regulates the expression of DNMTs, the function of melatonin was inhibited or activated upon oocytes. Results revealed that melatonin may regulate the expression of DNMTs via the cAMP/PKA/CREB pathway. These results suggest that maternal obesity induces genomic methylation alterations in oocytes, which can be partly transmitted to F2 in females, and that melatonin is involved in regulating the hyper-methylation of HFD oocytes by increasing the expression of DNMTs via the cAMP/PKA/CREB pathway.

developmental biology↗

bioRxiv2024

Identifying and quantifying the contribution of maize plant traits to nitrogen uptake and use through plant modelling

Breeding for high nitrogen use efficient crops can contribute to maintaining or even increasing yield with less nitrogen. Nitrogen use is co-determined by N uptake and physiological use efficiency (PE, biomass per unit of N taken up), to which soil processes as well as plant architectural, physiological and developmental traits contribute. The relative contribution of these crop traits to N use is not well known but relevant to identify breeding targets in important crop species like maize. To quantify the contribution of component plant traits to maize N uptake and use, we used a functional-structural plant model. We evaluated the effect of varying both shoot and root traits on crop N uptake across a range of nitrogen levels. Root architectural traits were found to play a more important role in root N uptake than physiological traits. Phyllochron determined the structure of the shoot through changes in source: sink ratio over time which, in interaction with light and temperature, resulted in a significant effect on PE and N uptake. Photosynthesis traits were more relevant to biomass accumulation rather than yield, especially under high nitrogen conditions. The traits identified in this study are potential targets in maize breeding for improved crop N uptake and use. HighlightOur research provides insight into the relevance of a range of traits for maize N uptake and N use, and identifies several potential target traits based on underlying mechanisms to assist maize breeding.

plant biology↗