bluuebunny/crossref_metadata_2025_split huggingface dataset:
Knockoff procedure improves causal gene identifications in conditional transcriptome-wide association studies
Authors: Zhang Xiangyu , Wang Lijun , Zhao Jia , Zhao Hongyu 
Published: February 2025

AbstractTranscriptome-wide association studies (TWASs) have been developed to nominate candidate genes associated with complex traits by integrating genome-wide association studies (GWASs) with expression quantitative trait loci (eQTL) data. However, most existing TWAS methods evaluate the marginal association between a single gene and the trait of interest without accounting for other genes within the same genomic region or the same gene from different tissues. Additionally, false-positive gene-trait pairs can arise due to correlations with the direct effects of genetic variants. In this study, we introduce TWASKnockoff, a new knockoff-based framework for detecting causal gene-tissue pairs using GWAS summary statistics and eQTL data. Unlike marginal testing in traditional TWAS methods, TWASKnockoff examines the conditional independence for each gene-trait pair, considering both correlations in cis-predicted expression across genes and correlations between gene expression levels and genetic variants. TWASKnockoff estimates the theoretical correlation matrix for all genetic elements (cis-predicted expression across genes and genotypes for genetic variants) by averaging estimations from parametric boot-strap samples and then performs knockoff-based inference to detect causal gene-trait pairs while controlling the false discovery rate (FDR). Through empirical simulations and an application to type 2 diabetes (T2D) data, we demonstrate that TWASKnockoff achieves superior FDR control and improves the average power in detecting causal gene-trait pairs at a fixed FDR level.
Unraveling diversity by isolating peptide sequences specific to distinct taxonomic groups
Authors: Bochalis Eleftherios , Patsakis Michail , Chantzi Nikol , Mouratidis Ioannis , Chartoumpekis Dionysios , Georgakopoulos-Soares Ilias 
Published: February 2025

AbstractThe identification of succinct, universal fingerprints that enable the characterization of individual taxonomies can reveal insights into trait development and can have widespread applications in pathogen diagnostics, human healthcare, ecology and the characterization of biomes. Here, we investigated the existence of peptide k-mer sequences that are exclusively present in a specific taxonomy and absent in every other taxonomic level, termed taxonomic quasi-primes. By analyzing proteomes across 24,073 species, we identified quasi-prime peptides specific to superkingdoms, kingdoms, and phyla, uncovering their taxonomic distributions and functional relevance. These peptides exhibit remarkable sequence uniqueness at six- and seven-amino- acid lengths, offering insights into evolutionary divergence and lineage-specific adaptations. Moreover, we show that human quasi-prime loci are more prone to harboring pathogenic variants, underscoring their functional significance. This study introduces taxonomic quasi-primes and offers insights into their contributions to proteomic diversity, evolutionary pathways, and functional adaptations across the tree of life, while emphasizing their potential impact on human health and disease.
The creation and validation of a fully animal component-free media for select adherent cell types
Authors: Mogilever Nicolette B. , Godin Pagé Marie-Hélène , Solola Anjolaoluwatikiitan , Pelling Andrew E. 
Published: February 2025

AbstractFetal Bovine Serum (FBS) is one of the most commonly used media supplement for the maintenance of mammalian cell types, yet the expensive costs, ethical concerns, and lot-to-lot variation have provoked a clear need for a serum that is standardized and derived from non-animal sources. Several serum-free formulations have been developed in the past, however they are often cell type specific, contain animal-derived components, and lack long-term culture validation. In this study, we developed a novel animal component-free (ACF) media and investigated its effectiveness on four commonly used mammalian cell lines via long-term (up to 90 days) morphological, transcriptomic, and proliferative analyses. Cells cultured in our ACF medium exhibited comparable cellular morphologies and equal or greater growth rates compared with cells cultured with FBS. Additionally, differentially expressed genes between the FBS-grown and ACF-grown groups were predominantly associated with functions linked to proliferation and cell attachment. The findings from this study indicate that this medium is a suitable replacement to FBS-containing medium for several common cell lines.
All-transretinoic acid and fluid transport in myopigenesis
Authors: Dvoriashyna Mariia , Bentley-Ford Melissa , Yu Jianshi , Chatterjee Saptarshi , Pardue Machelle T. , Kane Maureen A. , Repetto Rodolfo , Ethier C. Ross 
Published: February 2025

AbstractMyopia, or near-sightedness, is rapidly growing in prevalence, with significant long-term implications for ocular health. There is thus great impetus to better understand molecular signaling pathways leading to myopia. We and others have reported that all-trans retinoic acid (atRA) is involved in myopigenic signaling, yet the understanding of how atRA is transported and exerts a myopigenic influence is poor. Here we measured the concentrations of atRA in the serum in wild-type C57BL/6 mice under control conditions and after atRA feeding, previously shown to induce myopia. We also developed a mathematical model that describes fluid fluxes and the advective-diffusive transport of atRA in choroid and sclera, including atRA synthesis in the choriocapillaris, atRA degradation by scleral cells, and binding of atRA to the carrier protein serum albumin. This model, developed for both mice and humans, showed that atRA produced in the choriocapillaris was able to permeate well into the sclera in both mice and humans at biologically-relevant concentrations, and that atRA feeding greatly increased tissue levels of atRA across both the choroid and sclera. We were also able to identify which parameters most influence atRA concentration in ocular tissues, guiding future experimental work. Our findings support atRA’s role in myopigenic signaling.
Multitask deep learning for the emulation and calibration of an agent-based malaria transmission model
Authors: Mondal Agastya , Anirudh Rushil , Selvaraj Prashanth 
Published: February 2025

AbstractAgent-based models of malaria transmission are useful tools for understanding disease dynamics and planning interventions, but they can be computationally intensive to calibrate. We present a multitask deep learning approach for emulating and calibrating a complex agent-based model of malaria transmission. Our neural network emulator was trained on a large suite of simulations from the EMOD malaria model, an agent-based model of malaria transmission dynamics, capturing relationships between immunological parameters and epidemiological outcomes such as age-stratified incidence and prevalence across eight sub-Saharan African study sites. We then use the trained emulator in conjunction with parameter estimation techniques to calibrate the underlying model to reference data. Taken together, this analysis shows the potential of machine learning-guided emulator design for complex scientific processes and their comparison to field data.Author summaryMathematical models can help understand and design interventions for infectious diseases such as malaria, but they can be complex and time-consuming to work with. In this study, we developed a machine learning approach to create a fast and accurate emulator for a detailed malaria transmission model. Our emulator can quickly predict various disease outcomes based on different immune system parameters. We trained it using a large set of simulations created using the EMOD malaria model and tested it against real-world data from multiple African countries. The emulator not only matches the original model’s predictions closely, but can also be used to efficiently find the best parameter values to match field observations. We hope that this work can serve as a demonstration of machine learning tools to link complex models of disease transmission to field data.
Sequence similarity estimation by random subsequence sketching
Authors: Chen Ke , Pattar Vinamratha , Shao Mingfu 
Published: February 2025

AbstractSequence similarity estimation is essential for many bioinformatics tasks, including functional annotation, phylogenetic analysis, and overlap graph construction. Alignment-free methods aim to solve large-scale sequence similarity estimation by mapping sequences to more easily comparable features that can approximate edit distances efficiently. Substrings or kmers, as the dominant choice of features, face an unavoidable compromise between sensitivity and specificity when selecting the properk-value. Recently, subsequence-based features have shown improved performance, but they are computationally demanding, and determining the ideal subsequence length remains an intricate art. In this work, we introduce SubseqSketch, a novel alignment-free scheme that maps a sequence to an integer vector, where the entries correspond to dynamic, rather than fixed, lengths of random subsequences. The cosine similarity between these vectors exhibits a strong correlation with the edit similarity between the original sequences. Through experiments on benchmark datasets, we demonstrate that SubseqSketch is both efficient and effective across various alignment-free tasks, including nearest neighbor search and phylogenetic clustering. A C++ implementation of SubseqSketch is openly available athttps://github.com/Shao-Group/SubseqSketch.
SortingF. graminearumcore effector candidates shows multiple fungal proteins that target the wheat cell nucleus during Fusarium Head Blight
Authors: Ayilalath Shimlal , Faurie Lilian , Vanrobays Emmanuel , Rocher Florian , Loizeau Loriane , Philippe Géraldine , Javel Marie , Bosio Mickaël , Sallaud Christophe , Tatout Christophe , Bonhomme Ludovic 
Published: February 2025

AbstractEffectors are small molecules secreted by microbial pathogens that disrupt host basal functioning and responses during infection by targeting various plant susceptibility factors. This study reports a candidate selection approach for identifying novel, potential plant nuclear localized effectors fromFusarium graminearumsecretory proteins. From a dataset of core secretory proteins conserved across severalFusariumstrains, candidates were selected based on predicted nuclear localization, structural characteristics, and expression profiles during infection. Transient expression inNicotiana benthamianaconfirmed accumulation in the plant nucleus, that were further confirmed in wheat protoplasts. One of these proteins was selected for yeast two-hybrid (Y2H) screening to identify wheat protein targets, using aFusarium-infected wheat spike cDNA library specifically generated for this study. The screening identified a high confident interaction with a nuclear-localized wheat beta-amylase 2. The structural modeling of the protein complex between beta-amylase 2 and the putative effector was used to predict interacting amino acid residues and informed a deletion analysis to disrupt the interaction. This research identifies aF. graminearumsecretory core protein that interacts with a conserved wheat beta-amylase 2, showcasing a method to select pathogenicity factors conserved across multiple pathogens and host plants, with implications for developing broad-spectrum resistance strategies.HighlightThis study proposes a method based onin silicoandin vivoscreens to identify interacting pairs between core pathogenicity effectors localized in the nucleus and susceptibility factors in plants.
Beyond RNA Structure Alone: Complex-Aware Feature Fusion for Tertiary Structure-based RNA Design
Authors: Zhang Zixun , Zheng Jiayou , Zhou Yuzhe , Wang Sheng , Cui Shuguang , Li Zhen 
Published: February 2025

AbstractTertiary structure-based RNA design plays a crucial role in synthetic biology and therapeutics. While existing methods have explored structure-to-sequence mappings, they focus solely on RNA structures and overlook the role of complex-level information, which is crucial for effective RNA design. To address this limitation, we proposettheComplex-Aware tertiary structure-basedRNADesign model,CARD, that integrates complex-level information to enhance tertiary structure-based RNA sequence design. To be specific, our method incorporates protein features extracted by protein language model (e.g., ESM-2), enabling the design model to generate more accurate and complex relevant sequences. Considering the biological complexity of protein-RNA interactions, we introduce a distance-aware filtering for local features from protein representation. Furthermore, we design a high-affinity design framework that combines our CARD with an affinity evaluation model. In this framework, candidate RNA sequences are generated and rigorously screened based on affinity and structural alignment to produce high-affinity RNA sequences. Extensive experiments demonstrate the effectiveness of our method with an improvement of5.6%compared with base model without our complex-aware feature integration. A concrete case study for 2LBS further validates the superiority of our CARD.
Deep origins and distinct adaptations indicated for a glacial relict seal
Authors: Löytynoja Ari , Pohjoismäki Jaakko , Valtonen Mia , Laakkonen Juha , Morita Wataru , Kunnasranta Mervi , Väinölä Risto , Olsen Morten Tange , Auvinen Petri , Jernvall Jukka 
Published: February 2025

AbstractIsolated populations of postglacial relicts are known from many regions and are typically found on mountains for terrestrial species and in lakes for aquatic species. Among the few aquatic mammalian relicts, the Saimaa ringed seal (Pusa hispida saimensis) has been land-locked in Lake Saimaa, Finland, for the last 10,000 years. Saimaa ringed seals show genetic, behavioral, and morphological differences to the other ringed seal subspecies, but the extent these differences stem from the end of the last glacial period remains unclear. Here, we demonstrate with comprehensive sampling and state-of-the-art genomic methods that the Saimaa ringed seals are much older than the lake they inhabit, having formed a separate evolutionary branch for at least 60,000 years ago. This deep evolutionary origin of the Saimaa ringed seals is further underscored by our ecomorphological analyses revealing adaptively distinct features in their dentition and tongue. Overall, glacial relicts, many threatened by extinction, may harbor a richer selection of evolutionary history than might be expected from their recent isolation history alone.
Infection signatures of multipleNucleocytoviricotavirus lineages in the brown algaeUndaria pinnatifidarevealed by population-wide genome analysis
Authors: Ban Hiroki 
Published: February 2025

AbstractUndaria pinnatifidais a large brown algae native to the northwest Pacific. It has been introduced to numerous countries and is listed among the world’s 100 worst invasive species. However, it is also edible and produces various bioactive compounds, making it commercially important. Despite its ecological and economic value, the viruses that infectU. pinnatifidaremain unknown. In this study, a population-wide genome analysis was performed to investigate viral infection signatures inU. pinnatifida. A nearly complete 551-Kb giant endogenous viral element of aNucleocytoviricotavirus was identified on a pseudochromosome in the Korean strain genome Upin_Kr2015. This viral region contained viral hallmark genes and auxiliary metabolic genes, including kinases and GDP-mannose dehydrogenase. Additionally, we detected viral hallmark genes in all 43 whole-genome assemblies analyzed, with origins tracing to the ordersPandoravirales,Algavirales, orImitevirales. Our findings provide strong evidence of frequentU. pinnatifidainfections by multipleNucleocytoviricotaviruses.
Targeting FGFR4 Abrogates HNF1A-driven Metastasis in Pancreatic Ductal Adenocarcinoma
Authors: Crawford Katherine J. , Humphrey Kennedy S. , Cortes Eduardo , Wang Jianxin , Feigin Michael E. , Witkiewicz Agnieszka K. , Knudsen Erik S. , Abel Ethan V. 
Published: February 2025

AbstractPurposeWe previously identified an oncogenic role for the transcription factor HNF1A in pancreatic ductal adenocarcinoma (PDAC). However, the role of HNF1A in the metastatic progression of PDAC remains unknown and targeting modalities for HNF1A -dependent phenotypes have yet to be identified.Experimental DesignTranswell chambers were used to assess the effects of HNF1A and FGFR4 modulation on the migration and invasion of ATCC and patient-derived PDAC cellsin vitro. An intrasplenic injection xenograft model was used to evaluate the impact of HNF1A knockdown and overexpression on metastatic tumor burden. Single-cell RNA sequencing, tissue microarray (TMA) data, and UMAP spatial profiling were used to identify FGFR4 as an HNF1A target gene upregulated in metastatic cells. RNAi and two FGFR4 inhibiting modalities (H3B-6527 and U3- 1784) were utilized to demonstrate the efficacy of FGFR4 inhibiting agents at reducing HNF1A- driven metastasis.ResultsKnockdown of HNF1A significantly decreases and HNF1A overexpression significantly increases PDAC cell migration and invasion.In vivostudies show that HNF1A knockdown significantly abrogates metastasis, while overexpression significantly promotes metastasis. Single-cell RNAseq shows that FGFR4 is upregulated in metastatic PDAC cells and staining for HNF1A and FGFR4 in a PDAC TMA reveals significant correlation between HNF1A and FGFR4 in PDAC patients. Further, knockdown and inhibition of FGFR4 significantly decreases HNF1A- mediated cell migration and invasion, and blocks HNF1A-driven metastasisin vivo.ConclusionsThese findings demonstrate that HNF1A drives PDAC metastasis via upregulation of FGFR4, and FGFR4 inhibition is a potential mechanism to target metastasis in PDAC patients.Translational RelevancePancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, made even more devastating when metastases overwhelm major organs. The vast majority of PDAC patients either present with metastases or will relapse with recurrent metastatic PDAC after primary tumor resection. Unfortunately, toxic and largely ineffective chemotherapies are currently the only approved treatment options for these patients and therefore there exists a critical and unmet clinical need for targeted therapies against pro-metastatic pathways in PDAC. In the current study, we identify HNF1A as an oncogenic transcription factor that drives metastasis in PDAC, and it does so through upregulation of the receptor tyrosine kinase FGFR4. Importantly, FGFR4 is a targetable vulnerability and treatment with an FGFR4 blocking antibody reduces HNF1A-driven metastasis. These findings suggest that FGFR4 inhibitors could be an efficacious treatment for PDAC patients for the prevention or delay of metastatic tumor development.
An oomycete effector that induces shade avoidance like growth and suppresses plant defenses targets the AUX/IAA protein IAA11
Authors: Bogino Maria Florencia , Lapegna Senz Juan Marcos , Tamagnone Nicolás , Kourdova Lucille Tihomirova , Romanowski Andrés , Wirthmueller Lennart , Fabro Georgina 
Published: February 2025

AbstractFilamentous pathogens, such as oomycetes, employ multiple strategies to suppress plant immunity, one of which involves manipulating phytohormone signaling pathways. The effector HaRxL106 from Hyaloperonospora arabidopsidis (Hpa), known to induce shade avoidance syndrome (SAS)-like growth, has previously been shown to interact with brassinosteroid signaling components. Here, we investigate the role of HaRxL106 in altering auxin signaling, revealing that HaRxL106 targets the AUX/IAA protein IAA11, a key negative regulator of auxin responses. Our data suggest that HaRxL106 impedes the repressive function of IAA11, enhancing auxin signaling and promoting SAS, which concurrently suppresses plant immune responses. These findings provide insights into how pathogen effectors manipulate plant growth and immunity to facilitate infection.
Asymmetric subspecies-selection of an NLR-TF immune module and reconstruction of broad-spectrum disease resistance in rice
Authors: Lin Hui , Chen Fudan , Cheng Guanyun , Yan Bingxiao , Yuan Meng , Qiu Jie , Chen Ying , Wang Yijie , Cui Kaixuan , Gong Xiangyu , Liu Shasha , Liu Jiyun , Wang Jianjun , Li Rongbai , Mao Bizeng , Xu Jianlong , Jeon Jong-Seong , Huang Xuehui , Han Bin , Deng Yiwen , Chen Gongyou , He Zuhua 
Published: February 2025

AbstractArtificial selection has greatly shaped crop agronomic traits; however, the mechanistic basis of immunity selection has remained elusive. This study identifies a new rice NLR XA48 and its downstream transcription factor OsVOZ1, which confer bacterial blight resistance. XA48 perceives an ancient pathogen effector, XopG, to activates effector-triggered immunity (ETI). The XA48-OsVOZ1 module has undergone subspecies-specific selection.Xa48is retained inindicabut functionally lost injaponicarice. OsVOZ1 has also diverged into two haplotypes,indicakept both OsVOZ1A/Salleles that match XA48; whilejaponicaonly inherited OsVOZ1Athat greatly decreases yield whenXa48is reintroduced intojaponica, mechanistically explaining theXa48loss injaponica. We resurrected wild rice broad-spectrum resistance by stacking XA48-mediated ETI with XA21-mediated pattern-triggered immunity (PTI). Thus, our study reveals that the asymmetric selection of an NLR-TF module shapes both disease resistance and reproduction, and provides a paradigm for breeding crops by harnessing the immunity of wild relatives.
Wild and farmedSaccharina latissimain Europe: genetic insights for sustainable cultivation, traceability and environmental challenges
Authors: Jaugeon Lucie , Destombe Christophe , Ruggeri Paolo , Mauger Stéphane , Coudret Jérôme , Cock J. Mark , Potin Philippe , Valero Myriam 
Published: February 2025

AbstractKelp cultivation is expanding rapidly worldwide, although the aquaculture ofSaccharina latissima(sugar kelp) in Europe remains in its early stages. However, major concerns have emerged about the potential impact of selected cultivars of the species on native populations ofS. latissimawhich are already vulnerable to stressors including climate change.To address these concerns and support sustainable cultivation, it is essential to characterise genetic diversity and structure of wild kelp populations to monitor potential farm-to-wild gene flow. In this study we used 21 microsatellite loci to characterise the genetic structure of 24 natural and 3 farmed populations ofS. latissimaalong European coasts. Results confirmed strong genetic differentiation between the northern and southern coasts, refining the boundaries between these two clusters compared to previous studies. Within each cluster, a clear genetic substructure was detected, with population differentiation being far more pronounced in the southern cluster.Cultivated sporophytes exhibited pedigrees that were all traced back to the local parent populations. Bayesian model-based structure analysis, discriminant analysis of principal components and assignment tests revealed no significant genetic differentiation between the farms and their wild populations. This indicates that farmed populations and neighbouring populations share the same gene pool, reflecting current cultivation practices. These findings contribute to understanding risks of gene flow between wild and farmed populations and demonstrate that strain traceability is feasible. Additionally, the study highlights the challenge European seaweed farmers face in securing reliable seedling stock, especially in the context of global change.