bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rot or not? Uncovering the spatial patterns and drivers of Norway spruce root rot with harvester data
Authors: Suvanto Susanne , Heikkinen Juha , Holmström Eero , Honkaniemi Juha , Piri Tuula , Hantula Jarkko , Räsänen Tapio , Riekki Kirsi , Sorsa Juha-Antti , Hytönen Harri , Höglund Henna , Rajala Tuomas , Lehtonen Aleksi , Peltoniemi Mikko 
Published: February 2025

AbstractRoot rot is a major problem for forestry, leading to reduced timber quality, growth losses, and increased disturbance risks. Harvester data provides a promising source of information for improving the knowledge on the root rot distribution. Here, we used harvester data (1) to map the risk of spruce root rot in southern and central Finland, and (2) to understand the drivers of the spatial patterns in rot occurrence. First, we built a statistical model predicting the percentage of stems affected by root rot on stand-level. To train the model, we used an extensive set of harvester data, containing 10,402 clear-cut forest stands, where the presence of root rot was recorded for each cut tree using an algorithm based on bucking patterns (i.e., cutting of the stem into different log assortments) recorded by the harvester. The model consisted of two parts, a fixed component describing the effects of different drivers of root rot, and a spatial random component describing the spatial patterns not explained by the fixed part of the model. The fixed part included forest and site attributes, landscape characteristics and proxies of forest-use legacies. The model was then used to map root rot risk, by predicting the probability of root rot occurrence using spatial data sets of the variables in the fixed part of the model, and the known rot status of locations in the data set for the random part of the model. Finally, the map was tested with an independent validation data, verifying its ability to identify the high-risk areas. Proxies of forest-use legacies, tree size and site fertility were found to drive the percentage of rot-affected stems in stands. The results quantify the root rot risk in Finland in higher detail than before and demonstrate the large potential of harvester data in informing about the risk of root rot in boreal forests.
Pangenome graph augmentation from unassembled long reads
Authors: Denti Luca , Bonizzoni Paola , Brejova Brona , Chikhi Rayan , Krannich Thomas , Vinar Tomas , Hormozdiari Fereydoun 
Published: February 2025

AbstractPangenomes are becoming increasingly popular data structures for genomics analyses due to their ability to compactly represent the genetic diversity within populations. Constructing a pangenome graph, however, is still a time-consuming and expensive process. A promising approach for pangenome construction consists of progressively augmenting a pangenome graph with additional high-quality assemblies. Currently, there is no approach to augment a pangenome graph using unassembled reads from newly sequenced samples that does not require to align them and genotype the new individuals.In this work, we present the first assembly-free and mapping-free approach for augmenting an existing pangenome graph using unassembled long reads from an individual not already present in the pangenome. Our approach consists of finding sample specific sequences in reads using efficient indexes, clustering reads corresponding to the same novel variant(s), and then building a consensus sequence to be added to the pangenome graph for each variant separately.Using simulated reads based on Human Pangenome Reference Consortium (HPRC) assemblies, we demonstrate the effectiveness of the proposed approach for progressively augmenting the pangenome with long reads, without the need forde novoassembly or predicting genetic variants of the new sample. The software is freely available athttps://github.com/ldenti/palss.
Constitutive and regulatory responses ofArabidopsis thalianato harmonically oscillating light
Authors: Niu Yuxi , Fuente David , Matsubara Shizue , Lazár Dušan , Nedbal Ladislav 
Published: February 2025

AbstractThe rate of net CO2uptake is proportional to dim light and saturates when the light exceeds the plant assimilation capacity. This simple relationship between constant light and photosynthesis becomes intriguingly complex when the light oscillates. The rates of photosynthesis may differ between the descending and ascending phases of light oscillation. This hysteresis changes with the frequency and amplitude of the light and reports on the dynamics of the photosynthetic reactions and their regulation. Here, we investigated the chlorophyll fluorescence response ofArabidopsis thalianato light oscillating with three different amplitudes: 100–200, 100–400, and 100–800 μmol photons·m-2·s-1, each with periods ranging from 1 s to 8 min. The light amplitudes and periods were chosen to represent light patterns often appearing in nature. Three genotypes were compared: wild-type Col-0 andnpq1andnpq4mutants that are incapacitated in the rapidly reversible energy-dependent non-photochemical quenching (qE). The experiments identified two major dynamic patterns. One was found in oscillation periods shorter than 30 s, characterized by constitutive non-linearity and hysteresis. The other was mainly formed by regulatory non-linearity and hysteresis, occurring when the oscillation periods were longer than 30 s. The mathematical model simulating the chlorophyll fluorescence dynamics qualitatively reproduced the constitutive and regulatory dynamic patterns observed in the experiments. The model simulations illustrated the dynamics of non-photochemical quencher activation, plastoquinone pool reduction, and lumen pH that form the constitutive and regulatory non-linearities. The model simulations provided mechanistic insight into molecular processes forming the plant response to oscillating light.
Benchmarking the impact of reference genome selection on taxonomic profiling accuracy
Authors: van Bemmelen Jasper , Nika Ioanna , Baaijens Jasmijn A. 
Published: February 2025

AbstractMotivationOver the past decades, genome databases have expanded exponentially, often incorporating highly similar genomes at the same taxonomic level. This redundancy can hinder taxonomic classification, leading to difficulties distinguishing between closely related sequences and increasing computational demands. While some novel taxonomic classification tools address this redundancy by filtering the input genome database, there is limited work exploring the impact of different sequence dereplication methods across taxonomic classification tools.ResultsWe assess the effect of genome selection approaches on taxonomic classification using both bacterial and viral datasets. Our results demonstrate that careful selection of reference genomes can improve classification accuracy. We also show that using prior knowledge about a metagenomic sample, such as sampling location, can significantly improve classification accuracy. Finally, we find that using a redundancy-filtered genome database generally reduces the computational resources required, with minimal loss in classification accuracy.
miR-124acts duringDrosophiladevelopment to determine the phase of adult circadian behavior
Authors: Xia Yongliang , Chen Chenghao , Emery Patrick 
Published: February 2025

AbstractCircadian behaviors need to be properly phased with the day/night cycle to be beneficial. We previously showed that the microRNAmiR-124regulates circadian behavior phase inDrosophila. Here, we report thatmiR-124expression during larval development is required for proper phasing of both morning and evening peaks of activity in adults. Loss ofmiR-124results in significant miswiring within the circadian neural network and severely alters neural activity rhythms in the ventral Lateral Neurons (s-LNvs) and the posterior Dorsal Neurons 1 (DN1ps), which control the timing of morning and evening activity. Silencing the s-LNvs inmiR-124mutant flies restores the phase of evening activity, while activating the DN1ps rescues the phases of both morning and evening activities. Our findings thus reveal the pivotal role ofmiR-124in sculpting the circadian neural network during development and its long-lasting impact on circuit activity and adult circadian behavior.
Versatile Modular Antibodies for Sensitive and Specific Detection of Poly-ADP-Ribose
Authors: Dauben Helen , Matić Ivan 
Published: February 2025

AbstractADP-ribosylation is a chemically versatile modification of proteins, RNA and DNA that regulates various important signaling pathways, many of which are implicated in human diseases. Despite being discovered 60 years ago in the form of poly-ADP-ribosylation - the most studied form of this modification - investigating ADP-ribosylation at the molecular level has historically been challenging. By applying serine ADP-ribosylation-based antibody engineering technology, we have developed the first site-specific, as well as sensitive, mono-ADP-ribosylation modular antibodies. Here, we extend the scope of this technology to poly-ADP-ribosylation. By combining serine poly-ADP-ribosylated peptides as antigens, PARP1 serine mono- and poly-ADP-ribosylation for validation, phage display and the SpyTag protein ligation systems, we developed modular antibodies that are highly specific for poly-ADP-ribosylation. SpyTag-based coupling of horseradish peroxidase at specific positions, distant from the antigen-binding region of the antibody, yields a format that simplifies immunoblotting while dramatically enhancing poly-ADP-ribosylation detection sensitivity. Additionally, the creation of synthetic immunoglobulin formats – mouse, rabbit and human – enables straightforward co-detection of mono- and poly-ADP-ribosylation in cells by immunofluorescence. Our new tools improve and simplify the detection of poly-ADP-ribosylation, particularly in immunoblotting, enabling specific investigations of this key cellular signal in the context of other distinct forms of ADP-ribosylation.
Cytokine mRNA Delivery and Local Immunomodulation in the Placenta using Lipid Nanoparticles
Authors: Hofbauer Samuel I. , Fink Luisa A. , Young Rachel E. , Vijayakumar Tara , Nelson Katherine M. , Bellopede Nia , Alameh Mohamad-Gabriel , Weissman Drew , Gleghorn Jason P. , Riley Rachel S. 
Published: February 2025

AbstractDuring pregnancy, the maternal immune system adapts to balance tolerance of the semi-allogenic fetus while protecting the fetus from pathogens. Dysregulated immune activity at the maternal-fetal interface contributes to pregnancy complications, such as recurrent pregnancy loss and preeclampsia. Compared to healthy placentas, preeclamptic placentas exhibit increased pro-inflammatory signaling, including a predominance of inflammatory macrophages, leading to impaired tissue remodeling and restricted blood flow. However, the precise mechanisms driving this immune imbalance remain poorly understood, in part due to the lack of tools to probe individual pathways. Here, we use lipid nanoparticles (LNPs) to deliver cytokine-encoded mRNA to placental cells, called trophoblasts, enabling local immunomodulation. LNP-mediated delivery of IL-4 and IL-13 mRNA induced cytokine secretion by trophoblasts, leading to polarization of primary human monocytes toward anti-inflammatory phenotypes. Notably, lowering the mRNA dose increased expression of alternatively-activated macrophage markers, revealing an inverse relationship between dose and polarization status. Intravenous injection of LNPs in pregnant mice achieved placental secretion of IL-4 and IL-13 with minimal changes to pro-inflammatory cytokines in the serum. These findings establish LNPs as a tool for local immunomodulation in the placenta, offering a strategy to study and treat immune dysfunction in pregnancy and in other inflammatory conditions.
Mouse-to-human modeling of microglia single-nuclei transcriptomics identifies immune signaling pathways and potential therapeutic candidates associated with Alzheimer’s disease
Authors: Bergendorf Alexander , Park Jee Hyun , Ball Brendan K. , Brubaker Douglas K. 
Published: February 2025

ABSTRACTAlzheimer’s disease (AD) is a progressive neurodegenerative disease characterized by memory loss and behavior change. Studies have found that dysregulation of microglial cells is pivotal to AD pathology. These mechanisms have been studied in mouse models to uncover potential therapeutic biomarkers. Despite these findings, there are limitations to the translatable biological information from mice to humans due to differences in physiology, timeline of disease, and the heterogeneity of humans. To address the inter-species discrepancies, we developed a novel implementation of the Translatable Components Regression (TransComp-R) framework, which integrated microglia single-nuclei mouse and human transcriptomics data to identify biological pathways in mice predictive of human AD. We compared model variations with sparse and traditional principal component analysis. We found that both dimensionality reduction techniques encoded similar AD disease biology on mouse principal components with limited differences in technical performance. Several mouse sparse principal components explained high amounts of variance in humans and significantly differentiated human AD from control microglial cells. Additionally, we identified FDA-approved medications that induced gene expression profiles correlated with projections of healthy human microglia on mouse principal components. Such medications included cabergoline, selumetinib, and palbociclib. This computational framework may support uncovering cross-species disease insights and candidate pharmacological solutions from single-cell datasets.
Allodiploid hybridization, loss-of-heterozygosity and aneuploidy in the green algaAuxenochlorella, an emerging model for discovery research and bioengineering
Authors: Craig Rory J. , Dueñas Marco A. , Camacho Dimitrios J. , Gallaher Sean D. , Blaby-Haas Crysten E. , Moseley Jeffrey L. , Merchant Sabeeha S. 
Published: February 2025

ABSTRACTAuxenochlorellaare diploid oleaginous green algae that are highly amenable to genetic transformation by homologous recombination, providing great potential for discovery research and bioengineering. Vegetatively diploid organisms experience specific evolutionary phenomena, including allodiploid hybridization, mitotic recombination, loss-of-heterozygosity and aneuploidy; however, studies of these forces have mostly focused on fungi. Here, we present a telomere-to-telomere phased diploid genome assembly ofAuxenochlorellaUTEX 250-A, revealing a streamlined nuclear genome architecture with a haploid length of 22 Mb. We demonstrate that UTEX 250-A is an allodiploid hybrid via sequencing ofAuxenochlorella protothecoidesandAuxenochlorella symbionticastrains, two close relatives differentiated by extensive chromosomal rearrangements. The UTEX 250-A haplotypes are a mosaic of each parental species following mitotic recombination, and two chromosomes are trisomic, which we confirm via allele-specific transformation of a trisomic chromosome. Loss-of-heterozygosity events are likely pervasive acrossAuxenochlorelladue to mitotic recombination and transient aneuploidy, and can evolve rapidly in laboratory culture. We present high-quality structural annotations, yielding ∼7,500 genes per haplotype.Auxenochlorellahave experienced extensive gene family loss and reduction, including core photosynthesis genes. Nevertheless, a minimal set of genes required for sexual reproduction is potentially present. We demonstrate periodic adenine and cytosine methylation around promoters and across gene bodies. Finally, ∼10% of genes, especially those involved in DNA repair and sex, overlap antisense long noncoding RNAs, potentially representing a regulatory mechanism. These results demonstrate the generality of several evolutionary forces associated with vegetative diploidy, and provide a genomic foundation for the use ofAuxenochlorellaas a reference organism.
Microbiome-oriented data mining of operational monitoring of anaerobic digestion reactor during steady operation period, failure, and restoration
Authors: Panou M. , Kavakiotis I. , Mitsopoulos Anastasios , Tsioni Vasiliki , Sfetsas Themistoklis 
Published: February 2025

AbstractAnaerobic digestion (AD) is an essential biotechnology for sustainable waste management and bioenergy production, driven by a complex microbial ecosystem. However, the stability and efficiency of AD reactors are frequently challenged by microbial shifts resulting from operational disturbances. This study employs microbiome-oriented data mining and bioinformatics approaches to analyze microbial community dynamics in an anaerobic digestion reactor under steady-state operation, failure, and restoration phases. Data were extracted from a biogas plant and used to evaluate a system failure, providing crucial insights into microbial shifts associated with operational instability. A custom-built microbiome-oriented database, μ2Gas, was developed to integrate sequencing data with physicochemical monitoring results, enabling structured data storage, retrieval, and correlation analysis. This database was instrumental in identifying key microbial taxa responsible for reactor destabilization and in predicting failure events based on microbial and physicochemical trends. Through high-throughput 16S rRNA gene sequencing and advanced bioinformatics analysis, microbial shifts were correlated with key operational parameters such as pH, volatile fatty acids (VFAs), and ammonia concentrations. Results indicate that methanogenic archaea, particularly Methanosarcina, experienced a sharp decline during reactor failure, followed by a gradual recovery, demonstrating their sensitivity to environmental stressors. Additionally, the balance between Firmicutes and Actinobacteria was identified as a crucial determinant of reactor stability, with Firmicutes recovering in tandem with system restoration. Feedstock composition was found to play a significant role in microbial shifts, with seasonal variability influencing community composition and reactor performance. Machine learning models applied to the database suggested the potential for predictive analytics in anticipating system failures. By leveraging microbial abundance patterns, these models were able to identify early warning signs of instability. Restoration efforts, including feedstock adjustments and operational parameter optimization, successfully reinstated core microbial communities essential for biogas production. This study underscores the critical role of microbiome monitoring in anaerobic digestion and highlights the potential of bioinformatics tools for enhancing reactor resilience. Future research should focus on real-time microbiome tracking, machine learning-driven predictive maintenance, and adaptive operational strategies to further improve AD efficiency and biogas yield.
Functional Connectivity Shapes Spine Stability in the Hippocampus
Authors: Rais Cynthia , Wiegert J. Simon 
Published: February 2025

ABSTRACTSynaptic connections between neurons determine the flow of information in the brain. Changes in synaptic weight, along with synapse formation and pruning, reshape the functional connectivity of neural circuits—key mechanisms underlying learning and memory. However, the relationship between functional strength and the structural dynamics of individual glutamatergic synapses in the living mammalian brain remains poorly understood. Specifically, how spine morphology and stability relate to functional adaptations is unclear. Here, we repeatedly recorded excitatory postsynaptic calcium transients in single postsynaptic spines of CA1 neurons in response to optogenetic stimulation of presynaptic CA3 cells in awake, head-fixed mice for over 2 weeks. We found that functional connectivity predicted both the structural stability and clustering of synaptic inputs. Spines with large responses exhibited larger volume and higher stability compared to non-responding spines. Over time, responses were highly variable at individual synapses, but stable at the dendritic level, suggesting that dendritic branches receive stable input despite large fluctuations at individual synapses.
CryoEM structure of ALK2:BMP6 reveals distinct mechanisms that allow ALK2 to interact with both BMP and Activin ligands
Authors: Goebel Erich J. , Aykul Senem , Saotome Kei , Economides Aris N. , Franklin Matthew C. , Idone Vincent J. 
Published: February 2025

AbstractLigands in the TGFβ family (activins, BMPs and TGFβs), signal by bringing together two type I and two type II receptors. ALK2 is the only type I receptor among the seven TGFβ type I receptors that interacts with both activin and BMP ligands. With BMPs, ALK2 acts as a signaling receptor to activate SMAD1/5/8 signaling. Alternatively, with activins, such as Activin A (ActA), ALK2 forms nonsignaling complexes that negatively regulate ALK2 and ActA signaling. To gain insight into how ALK2 interacts with two distinct classes of ligands, we resolved the cryoelectron microscopy structure of ALK2 in complex with the type II receptor, ActRIIB, and the ligand, BMP6, in parallel with the corresponding structure with ALK3 for direct comparison. These structures demonstrate that ALK2 and ALK3 utilize different mechanisms to interact with BMP6 at the wrist interface, with ALK2 relying on BMP6 glycosylation and ALK3 relying on a salt bridge. Modeling of ALK2:ActA reveals that binding relies on ActA’s fingertip region, mirroring the interaction of ActA with its other receptor, ALK4. Our results demonstrate that ALK2 is a ‘hybrid’ receptor that incorporates features of BMP type I receptors such as ALK3 at the wrist interface, and an activin type I receptor such as ALK4 at the fingertip.SignificanceALK2 interacts with two different classes of TGFβ ligands: the BMPs and the activins. With BMP ligands, ALK2 signals to play roles in bone modeling, while with activins, ALK2 negatively regulates signaling by forming nonsignaling complexes. We demonstrate that ALK2 binds to favored ligand, BMP6, by utilizing the ligand wrist-helix stabilized by a glycosylation, rather than a charged interaction observed with similar receptor, ALK3. We also show that ALK2 interaction with activin ligand, ActA, is reliant on a single interaction at the other side of the receptor – the fingertip interface. Thus, this study elucidates first structure of ALK2 in complex with a ligand and provides the molecular insight into how ALK2 is able to bind to BMP and activin ligands.
Genomic Characterization of Novel Endophyte Strains from Tall Fescue Shows Genome Fragmentation Post-Hybridization
Authors: Lee Kendall , Bentz Philip , Vaughn Justin , Missaoui Ali 
Published: February 2025

ABSTRACTInterspecific hybridization in fungi has gained attention for its role in fungal evolution and potential commercial applications. Successful hybridization can enhance fitness and facilitate adaptation to new ecological niches. However, the genomic consequences of hybridization in fungi remain poorly understood.Epichloëis a genus of fungi that includes both non-hybrid and hybrid species, with the hybrids forming through parasexual hybridization and reproducing asexually. SomeEpichloëhybrids are of commercial significance, as they colonizeLolium arundinaceum(Schreb.) Darbysh., a crucial forage and turf grass species. In this study, we sought to generate high-quality genome assemblies for two previously uncharacterizedEpichloëhybrid strains, both of which are similar toEpichloësp. FaTG-3. We aimed to characterize their genomes and examine the effects of parasexual interspecific hybridization on fungal genome structure. Our results reveal that the genomes of both strains are rich in AT-rich blocks and repetitive elements. Upon comparison with putative progenitor genomes, we observed significant fragmentation and rearrangement. Despite the genomic instability, more than 85% of gene homologs from each progenitor species were retained. This study demonstrates that while parasexual hybridization dramatically alters genome structure, it does not significantly affect gene content.