bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bin2cell reconstructs cells from high resolution Visium HD data
Authors: Polański Krzysztof , Bartolomé-Casado Raquel , Sarropoulos Ioannis , Xu Chuan , England Nick , Jahnsen Frode L. , Teichmann Sarah A. , Yayon Nadav 
Published: June 2024

AbstractSummaryVisium HD by 10X Genomics is the first commercially available platform capable of capturing full scale transcriptomic data paired with a reference morphology image from archived FFPE blocks at sub-cellular resolution. However, aggregation of capture regions to single cells poses challenges. Bin2cell reconstructs cells from the highest resolution data (2μm bins) by leveraging morphology image segmentation and gene expression information. It is compatible with established Python single cell and spatial transcriptomics software, and operates efficiently in a matter of minutes without requiring a GPU. We demonstrate improvements in downstream analysis when using the reconstructed cells over default 8μm bins on mouse brain and human colorectal cancer data.Availability and ImplementationBin2cell is available athttps://github.com/Teichlab/bin2cell, along with documentation and usage examples, and can be installed from pip. Probe design functionality is available athttps://github.com/Teichlab/gene2probeContactny1@sanger.ac.uk,st9@sanger.ac.ukSupplementary informationSupplementary data are available online.
Φ-Space: Continuous phenotyping of single-cell multi-omics data
Authors: Mao Jiadong , Deng Yidi , Lê Cao Kim-Anh 
Published: June 2024

AbstractSingle-cell multi-omics technologies have empowered increasingly refined characterisation of the heterogeneity of cell populations. Automated cell type annotation methods have been developed to transfer cell type labels from well-annotated reference datasets to emerging query datasets. However, these methods suffer from some common caveats, including the failure to characterise transitional and novel cell states, sensitivity to batch effects and under-utilisation of phenotypic information other than cell types (e.g. sample source and disease conditions).We developed Φ-Space, a computational framework for the continuous phenotyping of single-cell multi-omics data. In Φ-Space we adopt a highly versatile modelling strategy to continuously characterise query cell identity in a low-dimensional phenotype space, defined by reference phenotypes. The phenotype space embedding enables various downstream analyses, including insightful visualisations, clustering and cell type labelling.We demonstrate through three case studies that Φ-Space (i) characterises developing and out-of-reference cell states; (ii) is robust against batch effects in both reference and query; (iii) adapts to annotation tasks involving multiple omics types; (iv) overcomes technical differences between reference and query.The versatility of Φ-Space makes it applicable to a wide range analytical tasks beyond cell type transfer, and its ability to model complex phenotypic variation will facilitate biological discoveries from different omics types.
Neural Dynamics of Object Manifold Alignment in the Ventral Stream
Authors: Wang Binxu , Ponce Carlos R. 
Published: June 2024

AbstractVisual neurons respond across a vast landscape of images, comprising objects, textures, and places. Natural images can be parameterized using deep generative networks, raising the question of whether latent factors learned by some networks control images in ways that better align with visual neurons. We studied neurons in areas V1, V4 and posterior IT, optimizing images using a closed-loop evolutionary algorithm. We used two generative image models: (1) DeePSim, which parameterizes local image patterns, and (2) BigGAN which parameterizes object identity and nuisance variables. We found that neurons could guide image optimization on both pattern- and object-based image manifolds across areas; V1 aligned best with the DeePSim image space, whereas PIT aligned well with both DeePSim and BigGAN spaces. While initially PIT neurons responded well to the textural manifold, their responses to objects also emerged over time, suggesting that object-like responses required further processing. We identified similar local features common to both textural and object images, but not optimal global configuration. We conclude that visual cortex neurons are aligned to a representational space not yet captured by current artificial model of the visual system.
ESR2 orchestrates cytokinin dynamics leading to developmental reprogramming and green callus formation
Authors: Durán-Medina Yolanda , Díaz-Ramírez David , Herrera-Ubaldo Humberto , Di Marzo Maurizio , Gómez Felipe Andrea , Cruz-Valderrama J. Erik , Vázquez Carlos A. , Guerrero-Largo Herenia , Colombo Lucia , Novak Ondrej , de Folter Stefan , Marsch-Martínez Nayelli 
Published: June 2024

AbstractCallus formation and shoot regeneration are natural plant abilities triggered by stress and damage. They are also key components of tissue culture, which for many species is crucial for gene editing, transformation, propagation, and other technologies, and their study provides valuable insights into plant development. The transcription factor ENHANCER OF SHOOT REGENERATION 2 (ESR2/DRNL/BOL/SOB) promotes green callus formation in roots and shoot regeneration when overactive, while the phythormone cytokinin plays a prominent role in both phenomena. Yet, the positive action of ESR2 on the cytokinin pathway had not been previously described. We explored the effects of ESR2 and found that cytokinin content and the expression of the cytokinin biosynthesis geneISOPENTENYLTRANSFERASE 5(IPT5)increase in plants where ESR2 activity is induced. ESR2 also regulates the cytokinin signaling repressorARABIDOPSIS HISTIDINE PHOSPHOTRANSFER 6(AHP6),and surprisingly, the ESR2-stimulated green calli formation requires bothIPT5andAHP6. Therefore, ESR2 promotes both cytokinin biosynthesis and cytokinin signaling inhibition and requires a paradoxical combination of these two for green callus induction. This finding provides a foundation to better understand the processes involved in tissue reprogramming towards callus formation and the role of ESR2 in shoot regeneration and the development of new organs.
Rapid spread of African Swine Fever across Borneo
Authors: Daniel Olivia Z , Heon Sui Peng , Donnelly Christl A , Bernard Henry , Orme C. David L , Ewers Robert M 
Published: June 2024

AbstractAfrican Swine Fever (ASF) reached the island of Borneo at the end of 2020. The first mortalities occurred in wild bearded pigs (Sus barbatus) in Sabah, north-east Borneo. The virus then began to spread across the island but, confounded by COVID 19 lockdowns the spread was difficult to monitor on the ground. The Babi Hutan Project was launched in April 2021 to gather data on pig sightings using citizen science. Here we bring together the data from this project and other online sources to show how the virus encompassed almost the entire island within a one-year period. The speed of spread appears to increase with time following an exponential model: we estimate an average speed of spread of 0.89km/day after 100 days since the first observation and at 4.28km/day after 400 days. We include recommendations of next steps for the bearded pigs of Borneo.
Lactucasuper-pangenome reduces bias towards reference genes in lettuce research
Authors: van Workum Dirk-Jan M. , Mehrem Sarah L. , Snoek Basten L. , Alderkamp Marrit C. , Lapin Dmitry , Mulder Flip F.M. , Van den Ackerveken Guido , de Ridder Dick , Schranz M. Eric , Smit Sandra 
Published: June 2024

AbstractBreeding of lettuce (Lactuca sativaL.), the most important leafy vegetable worldwide, for enhanced disease resistance and resilience relies on multiple wild relatives to provide the necessary genetic diversity. In this study, we constructed a super-pangenome based on fourLactucaspecies (representing the primary, secondary and tertiary gene pools) and comprising 474 accessions. We include 68 newly sequenced accessions to improve cultivar coverage and add important foundational breeding lines. With the super-pangenome we find substantial presence/absence variation (PAV) and copy-number variation (CNV). Functional enrichment analyses of core and variable genes show that transcriptional regulators are conserved whereas disease resistance genes are variable. PAV-genome-wide association studies (GWAS) and CNV-GWAS are largely congruent with single-nucleotide polymorphism (SNP)-GWAS. Importantly, they also identify several major novel quantitative trait loci (QTL) for resistance againstBremia lactucaein variable regions not present in the reference lettuce genome. The usability of the super-pangenome is demonstrated by identifying the likely origin of non-reference resistance loci from the wild relativesLactuca serriola, Lactuca salignaandLactuca virosa. The provided methodology and data provide a strong basis for research into PAVs, CNVs and other variation underlying important biological traits of lettuce and other crops.
Design of linear and cyclic peptide binders of different lengths from protein sequence information
Authors: Li Qiuzhen , Vlachos Efstathios Nikolaos , Bryant Patrick 
Published: June 2024

AbstractStructure prediction technology has revolutionised the field of protein design, but key questions such as how to design new functions remain. Many proteins exert their functions through interactions with other proteins, and a significant challenge is designing these interactions effectively. While most efforts have focused on larger, more stable proteins, shorter peptides offer advantages such as lower manufacturing costs, reduced steric hindrance, and the ability to traverse cell membranes when cyclized. However, less structural data is available for peptides and their flexibility makes them harder to design. Here, we present a method to design both novel linear and cyclic peptide binders of varying lengths based solely on a protein target sequence. Our approach does not specify a binding site or the length of the binder, making the procedure completely blind. We demonstrate that linear and cyclic peptide binders of different lengths can be designed with nM affinity in a single shot, and adversarial designs can be avoided through orthogonalin silicoevaluation, tripling the success rate. Our protocol,EvoBind2is freely availablehttps://github.com/patrickbryant1/EvoBind.
Neocortical long-range inhibition promotes cortical synchrony and sleep
Authors: Ratliff Jacob M , Terral Geoffrey , Lutzu Stefano , Heiss Jaime , Mota Julie , Stith Bianca , Vazquez Lechuga Arenski , Ramakrishnan Charu , Fenno Lief E , Daigle Tanya , Deisseroth Karl , Zeng Hongkui , Ngai John , Tasic Bosiljka , Sjulson Lucas , Rudolph Stephanie , Kilduff Thomas S. , Batista-Brito Renata 
Published: June 2024

AbstractBehavioral states such as sleep and wake are highly correlated with specific patterns of rhythmic activity in the cortex. During low arousal states such as slow wave sleep, the cortex is synchronized and dominated by low frequency rhythms coordinated across multiple regions. Although recent evidence suggests that GABAergic inhibitory neurons are key players in cortical state modulation, thein vivocircuit mechanisms coordinating synchronized activity among local and distant neocortical networks are not well understood. Here, we show that somatostatin and chondrolectin co-expressing cells (Sst-Chodl cells), a sparse and unique class of neocortical inhibitory neurons, are selectively active during low arousal states and are largely silent during periods of high arousal. In contrast to other neocortical inhibitory neurons, we show these neurons have long-range axons that project across neocortical areas. Activation of Sst-Chodl cells is sufficient to promote synchronized cortical states characteristic of low arousal, with increased spike co-firing and low frequency brain rhythms, and to alter behavioral states by promoting sleep. Contrary to the prevailing belief that sleep is exclusively driven by subcortical mechanisms, our findings reveal that these long-range inhibitory neurons not only track changes in behavioral state but are sufficient to induce both sleep-like cortical states and sleep behavior, establishing a crucial circuit component in regulating behavioral states.
Elucidating DNA-binding protein dynamics inSalmonellaTyphimurium within macrophages using a breakthrough low-input ChIP-exo approach
Authors: Park Joon Young , Jang Minchang , Choi Eunna , Lee Sang-Mok , Bang Ina , Woo Jihoon , Kim Seoyeon , Lee Eun-Jin , Kim Donghyuk 
Published: June 2024

AbstractGenome-wide identification of binding profiles for DNA-binding proteins inSalmonellaTyphimurium within macrophages is crucial for understanding virulence gene expression and cellular processes. However, this task remains challenging due to the limited amount of intracellular bacterial cells. Here, we present ChIP-mini, a low-input ChIP-exo utilizing 5,000-fold reduced number of initial bacterial cells and analysis pipeline (DiffExo), to identify genome-wide binding dynamics of DNA-binding proteins in host-infected pathogens. Applying ChIP-mini to intracellularS.Typhimurium, we identified 642 and 1,837 binding sites of H-NS and RpoD, respectively, with near-base pair resolution, elucidating their roles in transcriptional initiation. Post-infection, we observed 21 significant reductions in H-NS binding at intergenic regions, exposing the promoter region of virulence genes, such that those inSalmonellapathogenicity islands-2, 3 and effectors, facilitating RpoD binding for transcription initiation. Furthermore, we identified 24 novel RpoD binding sites and 19 significantly increased RpoD bindings at the transcription start sites of virulence genes. These findings substantially enhance our understanding of how H-NS and RpoD simultaneously coordinate the transcription initiation of virulence genes within macrophages. Collectively, this optimized method demonstrates a tool that can be broadly adapted to elucidate transcriptional regulatory networks of host-infected pathogens, revealing critical interactions between host and microbe.
Integrative multi-environmental genomic prediction in apple
Authors: Jung Michaela , Quesada-Traver Carles , Roth Morgane , Aranzana Maria José , Muranty Hélène , Rymenants Marijn , Guerra Walter , Holzknecht Elias , Pradas Nicole , Lozano Lidia , Didelot Frédérique , Laurens François , Yates Steven , Studer Bruno , Broggini Giovanni AL , Patocchi Andrea 
Published: June 2024

ABSTRACTGenomic prediction for multiple environments can aid the selection of genotypes suited to specific soil and climate conditions. Methodological advances allow effective integration of phenotypic, genomic (additive, non-additive), and large-scale environmental (enviromic) data into multi-environmental genomic prediction models. These models can also account for genotype-by-environment interaction, utilize alternative relationship matrices (kernels), or substitute statistical approaches with deep learning. However, the application of multi-environmental genomic prediction in apple remained limited, likely due to the challenge of building multi-environmental datasets and structurally complex models. Here, we applied efficient statistical and deep learning models for multi-environmental genomic prediction of eleven apple traits with contrasting genetic architectures by integrating genomic- and enviromic-based model components. Incorporating genotype-by-environment interaction effects into statistical models improved predictive ability by up to 0.08 for nine traits compared to the benchmark model. This outcome, based on Gaussian and Deep kernels, shows these alternatives can effectively substitute the standard G-BLUP. Including non-additive effects slightly improved predictive ability by up to 0.03 for two traits, but enviromic-based effects resulted in no improvement. The deep learning approach achieved the highest predictive ability for three traits with simpler genetic architectures, outperforming the benchmark by up to 0.10. Our results demonstrate that the tested statistical models capture genotype-by-environment interactions particularly well, and the deep learning models efficiently integrate data from diverse sources. This study will foster the adoption of multi-environmental genomic prediction to select apple cultivars adapted to diverse environmental conditions, providing an opportunity to address climate change impacts.
Dissecting the genetic regulation of lateral root development in tomato under salt stress
Authors: Rahmati Ishka Maryam , Sussman Hayley , Zhao Jiantao , Craft Eric , Yu Li’ang , Nelson Andrew , Pineros Miguel , Tester Mark , Kawa Dorota , Fei Zhangjun , Julkowska Magdalena M. 
Published: June 2024

AbstractTomatoes are crucial for global food security and agricultural economies. With over 50% of arable land projected to become saline by 2050, understanding tomato responses to saline environments is essential. Soil salinization, prevalent in arid regions, leads to salt stress. Roots are primary salinity sensors and integrate stress responses like nutrient deficiency. Understanding the molecular processes maintaining root growth is vital for crop resilience. While salt stress impacts on tomato seed germination, shoot growth, and fruit yield are documented, root development remains underexplored. Most studies have focused on a limited number of cultivars and their physiological responses, not the genetic basis of salt resilience. Wild tomato relatives, such asSolanum pimpinellifolium, offer traits that are beneficial for breeding resilient crops. However, few studies have examined the genetics of salinity tolerance inS. pimpinellifolium. This study characterizes salt stress-induced changes in root system architecture (RSA) using a natural diversity panel of 220 wild tomato accessions. We identified natural variation in lateral root development and several candidate loci through Genome-Wide Association Study (GWAS). Bulk segregant analysis (BSA) revealed 22 candidate genes overlapping with GWAS findings. Exploring root transcriptome reprogramming in two accessions with differing lateral root responses highlighted genotype-specific changes. Integrating GWAS, BSA, and RNA sequencing data identified four key genes underlying differential lateral root development under salt stress. These findings offer novel genetic targets for improving salt resilience in tomatoes, providing opportunities for future research and breeding programs to enhance crop sustainability and productivity.
Within-host environmental heterogeneity is associated with phenotypic but not genomic diversity inWolbachiaendosymbionts
Authors: Pigeault Romain , Dussert Yann , Jorge Raphaël , Panza Marie , Raimond Maryline , Delaunay Carine , Ogereau David , Moumen Bouziane , Peccoud Jean , Cordaux Richard 
Published: June 2024

AbstractThe mechanisms underlying within-host diversification in parasite populations are still poorly understood. Yet, diversification in parasite phenotype and genotype may have important clinical and epidemiological consequences. Our aim was to determine if the constraints associated with the infection of different host tissues lead to the emergence and co-existence of multiple parasite sub-populations with different phenotypes. We tested this hypothesis by injecting the most widespread bacterial endosymbiont,Wolbachia, isolated from three tissues of the common pill-bugArmadillidium vulgareinto uninfected individuals, and by monitoring the growth rate and virulence of each bacterial sub-population in the new hosts. Our results highlighted that within-host environmental heterogeneity led to diverse phenotypes inWolbachia. This variability did not appear to result from genomic variation, but from phenotypic plasticity. Indeed, we did not find recurrent tissue-specific genomic variation among infected individuals. Whole genome resequencing of theWolbachiasub-populations and pedigree data from the animals used in this study demonstrated however the coexistence of twoWolbachiavariants within our host lineage for almost 20 years. Our results further supported the stability of theWolbachiagenome with respect to small-scale genomic variation, in agreement with reports on other symbiotic systems.
Spinal interneuron population dynamics underlying flexible pattern generation
Authors: Wimalasena Lahiru N. , Pandarinath Chethan , Yong Nicholas Au 
Published: June 2024

AbstractThe mammalian spinal locomotor network is composed of diverse populations of interneurons that collectively orchestrate and execute a range of locomotor behaviors. Despite the identification of many classes of spinal interneurons constituting the locomotor network, it remains unclear how the network’s collective activity computes and modifies locomotor output on a step-by-step basis. To investigate this, we analyzed lumbar interneuron population recordings and multi-muscle electromyography from spinalized cats performing air stepping and used artificial intelligence methods to uncover state space trajectories of spinal interneuron population activity on single step cycles and at millisecond timescales. Our analyses of interneuron population trajectories revealed that traversal of specific state space regions held millisecond-timescale correspondence to the timing adjustments of extensor-flexor alternation. Similarly, we found that small variations in the path of state space trajectories were tightly linked to single-step, microvolt-scale adjustments in the magnitude of muscle output.One sentence summaryFeatures of spinal interneuron state space trajectories capture variations in the timing and magnitude of muscle activations across individual step cycles, with precision on the scales of milliseconds and microvolts respectively.
Deficiency in DNAH12 causes male infertility by impairing DNAH1 and DNALI1 recruitment in humans and mice
Authors: Yang Menglei , Hussain Hafiz Muhammad Jafar , Khan Manan , Muhammad Zubair , Zhou Jianteng , Ma Ao , Huang Xiongheng , Ye Jingwei , Chen Min , Zhi Aoran , Liu Tao , Khan Ranjha , Ali Asim , Shah Wasim , Zeb Aurang , Ahmad Nisar , Zhang Huan , Xu Bo , Ma Hui , Shi Qinghua , Shi Baolu 
Published: June 2024

AbstractAsthenoteratozoospermia, a prevalent cause of male infertility, lacks a well-defined etiology. DNAH12 is a special dynein featured by the absence of a microtubule-binding domain, however, its functions in spermatogenesis remain largely unknown. Through comprehensive genetic analyses involving whole-exome sequencing and subsequent Sanger sequencing on infertile patients and fertile controls from six distinct families, we unveiled six biallelic mutations inDNAH12that co-segregate recessively with male infertility in the studied families. Transmission electron microscopy (TEM) revealed pronounced axonemal abnormalities, including inner dynein arms (IDAs) impairment and central pair (CP) loss in sperm flagella of the patients. Mouse models (Dnah12−/−andDnah12mut/mut) were generated and recapitulated the reproductive defects in the patients. Noteworthy, DNAH12 deficiency did not show effects on cilium organization and function. Mechanistically, DNAH12 was confirmed to interact with two other IDA components DNALI1 and DNAH1, while disruption of DNAH12 leads to failed recruitment of DNALI1 and DNAH1 to IDAs and compromised sperm development. Furthermore, DNAH12 also interacts with radial spoke head proteins RSPH1, RSPH9, and DNAJB13 to regulate CP stability. Moreover, the infertility ofDnah12−/−mice could be overcome by intracytoplasmic sperm injection (ICSI) treatment. Collectively, DNAH12 plays a crucial role in the proper organization of axoneme in sperm flagella, but not cilia, by recruiting DNAH1 and DNALI1 in both humans and mice. These findings expand our comprehension of dynein component assembly in flagella and cilia and provide a valuable marker for genetic counseling and diagnosis of asthenoteratozoospermia in clinical practice.