Biology subjects

Han, J.

Publications and source records attributed to Han, J..

At least 19 recordsLinked to original sources

bioRxiv2026

NeuroPilot: Longitudinal intravital neural imaging across scales and modalities through an agentic platform

Longitudinal intravital imaging is essential for understanding how neural populations evolve across behavioral states, yet converting large-scale recordings into biological insight remains a fundamental challenge because neural signals are degraded by noise, non-rigid motion, and heterogeneous recording conditions. Here we introduce NeuroPilot, an agentic framework that transforms neural imaging analysis into a closed-loop, context-aware process, integrating a multimodal large language model with callable computational imaging modules to adaptively coordinate workflows from raw recordings to population-level readouts. Across heterogeneous imaging and experimental regimes, NeuroPilot restores motion-degraded recordings and supports consistent neural signal recovery, detection, and tracking in challenging deep-brain, freely moving, and longitudinal settings. These enable neuronal population tracking across spinal stimulation paradigms, deep-brain imaging, and continuous 24-hour mPFC recordings aligned with spontaneous sleep-wake behavior. By converting heterogeneous intravital recordings into stable population activity maps, NeuroPilot supports behavioral decoding and reveals structured neural dynamics across behavioral states and transitions. NeuroPilot establishes a scalable agentic paradigm for neural imaging analysis, expanding experimental access to the measurement, visualization, and interpretation of neural population activity.

neuroscience↗

bioRxiv2026

BioMod: Biological Module Tokenization for Single-Cell Foundation Modeling

Single-cell foundation models typically represent cells as flat sequences of individual genes, requiring higher-order biological organization to be inferred implicitly from sparse expression profiles. Similar to the evolution from character-level to semantic tokenization in natural language processing,we hypothesize that cellular states can be more efficiently represented using biologically meaningful intermediate units. Here we present BioMod, a 50-million-parameter single-cell foundation model that introduces biological modules as representation units between genes and cells. BioMod constructs an overlapping vocabulary of 660 biological modules derived from curated pathways and data-driven gene programs, replacing thousands of gene-level inputs with compact module representations. Pretrained on approximately 73 million human cells using high-ratio module masking with an asymmetric decoder, BioMod achieves state-of-the-art performance across cell-type annotation, zero-shot batch integration, perturbation-response prediction and drug-response forecasting while maintaining a compact architecture that enables efficient inference on a single GPU. Module-level analyses further demonstrate that BioMod captures biologically meaningful cellular programs and preserves pathway-level organization.

bioinformatics↗

bioRxiv2026

High-throughput variant libraries and machine learning enable robust target-site selection for toehold-switch design in Detectrons

Programmable RNA sensors enable sequence-specific detection of RNA inputs for diagnostics, genetic circuit control, and multiplexed molecular readouts. Although readily programmable, their performance varies substantially with the target site selected within a transcript, making target-site selection a major challenge. Here, we report DeSTAR (Detectron Sensor TARget-site ranker), a machine-learning-assisted target-site ranking model for programmable RNA sensors. To train this model, we generated transcript-wide, single-nucleotide-resolution tiling sensor libraries across six diverse RNA targets, enabling generalization to be tested across transcripts rather than within a single RNA. In leave-one-transcript-out evaluation, DeSTAR's top-ranked sites were enriched for high-performing sensors in held-out transcripts, driven predominantly by interpretable sequence grammar in the sensor stem rather than transcript-specific patterns. Prospectively, on an unseen SARS-CoV-2 transcript, the model's top-ranked sites yielded working sensors roughly five-fold more often than random selection. These results support DeSTAR as a generalizable strategy for target-site selection in RNA sensors across transcripts.

synthetic biology↗

bioRxiv2026

Defense-associated reverse transcriptases synthesize DNA in a telomerase-like manner

Defense-associated reverse transcriptases (DRTs) constitute an emerging class of bacterial defense systems that harness reverse-transcriptase activity to generate cDNA products and counter phage infection. A distinct subset of DRT10 systems evolutionarily related to telomerase generates tandem-repeat DNA to confer antiphage immunity. Here, we biochemically characterize the reverse transcription activity of DRT10 and determine cryo-EM structures of DRT10-ncRNA complex in three functional states, revealing an unanticipated 2:1 RT:ncRNA assembly mode. Two DRT10 protomers dimerize through a central pair of interlocked {beta}-hairpins and are further embraced by a single ncRNA. This architecture distinguishes DRT10 from previously characterized DRT complexes, which either lack an ncRNA component or exhibit an equivalent stoichiometry of RT:ncRNA. Strikingly, despite the nearly identical conformations of the two DRT10 protomers, cDNA product density was resolved in only one catalytic pocket, revealing different product occupancy within the dimer. Moreover, along with flanking linkers, the stem loops of the ncRNA as fixed points to supply steric barriers help define the template boundary. These findings reveal a distinctive ncRNA-mediated DRT10 dimeric assembly and establish a mechanistic framework for protein-primed reverse transcription constrained by the length of the RNA flanking linker.

biochemistry↗

bioRxiv2026

Molecular characterization of a cytochrome P450 involved in the skeletal diversification of tricyclic coumarins in Angelica keiskei.

Abstract Tricyclic coumarins (TCs) exhibit defensive properties against herbivorous insects and possess valuable pharmacological properties for humans. They are mainly distributed in the Apiaceae, Rutaceae, Moraceae, and Fabaceae families. The chemical structural diversity of TCs in these families primarily arises from differences in skeletal variety and attachment position of the third ring, as observed in unsaturated furanocoumarins (FCs) and saturated dihydrofuranocoumarins (DHFCs). In TC biosynthesis, the FC and DHFC pathways diverge through distinct oxidation patterns. The product specificity of the reported cytochrome P450 monooxygenase at the branching point suggests that these TC groups are produced in nearly identical ratios; however, some species of the genus Angelica (Apiaceae) accumulate DHFCs at higher levels than FCs. In this study, we investigated the enzymatic mechanism responsible for forming these two TC groups using A. keiskei, a Japanese native species used as a medicinal and edible herb. Organ-specific transcriptome analysis highlighted a P450 member CYP71AJ62 that exhibited a close correlation with TC accumulation across organs. Enzymatic characterization demonstrated that CYP71AJ62 predominantly forms a hydroxylated DHFC, vaginidiol, which may promote DHFC over FC skeletal formation in TC biosynthesis. Phylogenetic analysis suggested that CYP71AJ62 has been derived from a gene responsible for FC formation by functional shift without gene duplication. Subsequent three-dimensional structural modeling and site-directed mutagenesis revealed that two amino acid residues on substrate recognition sites cooperatively determine the product specificity of this P450 enzyme. This study provides new insights into the molecular evolutionary process underlying ring-structure diversification and, more broadly, the adaptation of plants to their environments.

plant biology↗

bioRxiv2026

The Genome In A Bottle HG002 assembly-based variant benchmark set enables comprehensive benchmarking of small and structural variants.

High-accuracy, high-resolution benchmark data are fundamental to improving the accuracy and generalizability of sequencing technologies and associated algorithms. Most existing benchmarks for DNA sequencing rely on mapping to a single linear reference, omitting inaccessible and highly repetitive complex genomic regions. Here, we present the Genome in a Bottle (GIAB) Consortium's HG002 v5.0q benchmark set, a more comprehensive variant benchmark derived from a fully phased, highly curated, and accurate diploid assembly of HG002. Our approach leverages recent advances in long-read sequencing and assembly to provide confident small- and structural-variant calls across previously inaccessible regions, including segmental duplications, homopolymers, tandem repeats, and complex immune loci. The v5.0 benchmark significantly expands the callable genome relative to v4.2.1, adding x200 Mbp of sequence and increasing variant detection by 18 % for small variants and 3-fold for structural variants compared to previous benchmarks. The benchmark regions include more variants in repetitive regions, including 1.2 x segmental duplications, 1.8 x tandem repeats, and 2.0 x homopolymers, compared to v4.2.1. Separate and combined small- and structural-variant benchmarks are available for three versions of the human reference genome (GRCh37, GRCh38, and CHM13). We validate the reliability of this benchmark set by comparing multiple sequencing technologies and variant calling pipelines and curating differences. The v5.0q benchmark provides a critical resource for the development and validation of next-generation sequencing technologies and analysis methods.

genomics↗

bioRxiv2026

Predicting viral host range for reverse zoonosis surveillance

Zoonotic transmission of viruses has triggered major outbreaks throughout history. However, human-to-animal transmission, or reverse zoonotic transmission, also represents an underappreciated public health threat. Reverse zoonoses can establish novel animal reservoirs that fuel viral evolution and enable eventual spillback into humans, underscoring the importance of defining viral host range. Current approaches for host range prediction are limited. Experimental methods are retrospective and rely on brute-force testing in a small number of models, whereas computational approaches often lack experimental grounding. Here, we present a platform that integrates high-throughput experimental screening with deep learning to predict viral host range from sequence. We screened a yeast-displayed SARS-CoV-2 receptor-binding domain library against 15 ACE2 orthologs from diverse species, and deep sequenced the ACE2-binding and non-binding populations to generate an atlas of 8.8 million unique RBD:ACE2 interaction measurements. These data were used to train a transformer-based deep learning model that predicts RBD:ACE2 compatibility across animal species from sequence alone, and generalizes in a zero-shot manner to ACE2 orthologs not observed during training. Critically, the model pairs each prediction with a distance-based uncertainty estimate, allowing hundreds of candidate species to be triaged by both predicted host compatibility and confidence. This framework enables the rapid prioritization of animal species for SARS-CoV-2 surveillance and provides a general strategy for anticipating viral host range.

bioengineering↗

bioRxiv2026

Immune Reconstitution and Antigenic Exposure History Shape Virus-Specific Humoral Immunity in People with HIV

CD4+ T-cell recovery is widely used to assess immune reconstitution in people with HIV, but its relationship to virus-specific humoral immunity across pathogens remains unclear. We characterized neutralizing activity against SARS-CoV-2, HIV-1, and influenza viruses in ART-treated, virologically suppressed individuals spanning distinct CD4+ T-cell levels. BA.5 was the dominant SARS-CoV-2 neutralization target across CD4 strata, whereas D614G neutralization increased with greater immune reconstitution. This gradient was largely absent for the antigenically divergent NB.1.8.1 and XFG variants. HIV-1 neutralization was inversely associated with CD4+ T-cell count, while influenza showed strain-dependent patterns. Neutralization-to-protection bridging preserved a CD4-associated gradient for D614G but not for highly immune-evasive variants. These findings show that immune reconstitution does not translate uniformly into antiviral humoral function. Instead, antibody profiles reflect host immune status, prior antigenic exposure, and viral antigenic evolution, supporting pathogen-specific functional assessment alongside conventional immune monitoring.

immunology↗

bioRxiv2026

Architecture and Energy Transfer of the Bacterial Photosynthetic Unit

In phototrophic organisms, pigment-protein membrane complexes are densely packed to form photosynthetic units (PSUs) that capture solar energy and convert it into chemical energy. Although the structures of many individual photosynthetic complexes have been resolved, how they are arranged and interact with others within photosynthetic membranes to enable efficient excitation energy transfer (EET) remains poorly understood. Here, we report cryo-electron microscopy structures of PSU supercomplex assemblies from the phototrophic a-proteobacterium Rhodovulum viride, including an RC-LH1 core associated with one or two peripheral LH2 complexes and a curved LH2 tetramer. These membrane-derived assemblies define the relative positions and orientations of neighboring photosynthetic complexes and place their pigment arrays in proximity across antenna-antenna and antenna-core interfaces. Structure-based simulations identify potential EET pathways within the PSU assemblies and reveal rapid energy transfer across both LH2-LH2 and LH2-LH1 interfaces. Collectively, these findings provide insights into the assembly and structural modularity of bacterial PSUs and elucidate how the lateral organization of membrane protein complexes facilitates efficient energy transfer. This work extends structural studies of bacterial photosynthesis from individual complexes to their native higher-order assembly, providing a framework for understanding how photosynthetic supercomplex organization shapes energy migration and for guiding the design of artificial photosynthesis.

biochemistry↗

bioRxiv2026

Reelin doses normalizing behavioural alterations induced by repeated corticosterone avoid eliciting neuroinflammation-associated morphology in hippocampal microglia

Chronic stress elicits widespread, multisystem alterations, among them the increased production of inflammatory mediators by immune cells, that culminate in physiological and psychological disruptions. Microglia are resident macrophages of the CNS that show altered morphology alongside increases in pro-inflammatory cytokine release and phagocytosis in response to chronic stress. Chronic stress-induced behavioural and physiological alterations can be replicated in rats using daily injections of corticosterone (CORT) over a prolonged period. Reelin, a glycoprotein reduced in depression and animal models of chronic stress, rapidly reverses chronic CORT-induced symptoms following a single 3 g injection. However, high levels of reelin may be pro-inflammatory, indicating the need to determine if a dose of reelin that resolves chronic stress-induced impairments exacerbates neuroinflammation as a possible adverse effect of reelin treatment. Using either a single 3 g reelin injection following chronic stress or repeated (3) reelin injections throughout chronic stress in male Long Evans rats, we show that reelin does not promote microglia morphologies indicative of pro-inflammatory function within the context of chronic stress, and that both reelin administration schedules rapidly reverse chronic stress-induced despair-like behaviour. These results offer insight into the effect of peripheral reelin administration on processes underlying neuroinflammation and suggest that restoring reelin following chronic stress does not exacerbate microglia-driven neuroinflammation. This research together with past research from our lab supports the advancement of reelin or reelin peptides towards clinical evaluation as a rapid antidepressant.

neuroscience↗

bioRxiv2026

The evolutionarily conserved EHMT1/G9a histone methyltransferase family regulates sleep maintenance through ROS homeostasis in insulin-producing cells

Sleep disturbances are a common, still poorly characterized feature of Kleefstra syndrome (KLEFS1), a neurodevelopmental disorder caused by rare variants in the epigenetic regulator EHMT1. The gap in understanding the characteristics and origin of these sleep disturbances poses a major barrier for therapy development. In this cross-species study, we reveal that 70% of individuals with KLEFS1 experience severe sleep maintenance insomnia, marked by fragmented sleep due to frequent night awakenings. Furthermore, common genetic variation at the EHMT1 locus was associated with short sleep and insomnia symptoms in the general population. Drosophila mutants of the EHMT1 orthologue G9a recapitulate these phenotypes, exhibiting reduced and fragmented sleep. We show that G9a is required in insulin-producing cells (IPCs) and the fat body, in the latter during development, to ensure adult sleep integrity. Untargeted metabolomics revealed widespread metabolic dysregulation in G9a mutants, particularly affecting methionine metabolism. Mutants exhibited reduced methionine and elevated methionine sulfoxide (Met-SO), pointing to increased reactive oxygen species (ROS). Redox sensors revealed increased H2O2-dependent oxidation in the larval brain and an elevated glutathione redox potential in IPCs during development but not in adulthood. IPC-specific knockdown of MsrA, the enzyme that reduces Met-SO back to methionine, reproduced sleep fragmentation. Developmental, but not acute, antioxidant treatment fully restored adult sleep consolidation, demonstrating that G9a safeguards sleep via ROS homeostasis in early life. Finally, we show that a Drosophila sleep-restriction paradigm based on human sleep-restriction therapy can override the developmental defects and restore sleep continuity in adulthood. Our findings establish an evolutionarily conserved role for EHMT1/G9a in sleep regulation and provide a mechanistic framework to understand and treat sleep disturbances in KLEFS1.

genetics↗

bioRxiv2026

TomatoPGFM: A graph-conditioned foundation model for tomato pangenomes

Most genomic foundation models are pretrained on independent linear assemblies and therefore do not explicitly represent population-level segment sharing or local graph connectivity. We developed TomatoPGFM, a graph-conditioned model pretrained on 54.65 Gb of sequence from 66 tomato (Solanum spp.) accessions. Sequence tokens were conditioned on pangenome node attributes and local adjacency, and the model was optimised using masked language modelling and graph-feature reconstruction. To evaluate model responses to graph-conditioned input, we compared aligned, shuffled and disabled graph inputs in 25,000 windows from the training panel. Sequence-aligned graph input produced lower masked language modelling loss than graph-off at all five curriculum stages in both training-panel strata, while the shuffled perturbation generally yielded intermediate losses. We then assessed sequence-only transfer in Solanum sitiens LA1974 and S. lycopersicum MicroTom, neither of which was used for graph construction or pretraining. Frozen-probe AUROC values for gene-versus-intergenic and coding-sequence-versus-intergenic classification ranged from 0.8489 to 0.9593. TomatoPGFM produced higher AUROC point estimates than DNABERT-2 in all four comparisons. Enabling the zero-feature GraphAdapter pathway with adjacency messaging disabled changed throughput by less than 1% at 512-2,048 positions under the tested configuration. Together, these results show that TomatoPGFM responds consistently to sequence-aligned pangenome context in training-panel sequences and provides informative sequence representations for genic-region classification in accessions excluded from graph construction and pretraining.

bioinformatics↗

bioRxiv2026

Descending somatosensory and motor cortical inputs shape auditory processing in the midbrain

Integrating multisensory and behavioral information is essential for sensory perception. In the auditory system, multisensory and behavioral influences emerge early in subcortical structures. Descending projections from non-auditory cortical areas are well positioned to convey such signals, yet how they shape subcortical auditory processing remains poorly understood. Here, we investigated corticocollicular projections from the primary somatosensory (S1) and motor (M1) cortices to the inferior colliculus (IC), a principal integration center in the auditory midbrain. We found that trunk- and limb-related regions of S1 and M1 form prominent monosynaptic projections to the IC, and that optogenetic activation of these projections robustly drives IC activity. Notably, a substantial population of cortical-responsive neurons did not respond to sound. In sound-responsive neurons, concurrent cortical stimulation enhanced sound-evoked responses, whereas cortical activation preceding sound onset suppressed them. Furthermore, both cortical-responsive IC neurons and deep-layer S1 and M1 neurons exhibited locomotion-related modulation and anticipatory activity prior to movement onset, suggesting that these descending pathways convey movement-related signals to the IC. Together, our findings identify a descending sensorimotor circuit that integrates body- and movement-related information with auditory processing in the auditory midbrain.

neuroscience↗

bioRxiv2026

Cross-species discovery of large structural variants reveals distinct evolutionary dynamics in primates

Large-scale structural variants (SVs) are major drivers of genome evolution and disease susceptibility, shaping lineage-specific gene content, genome architecture, and phenotypic diversity. Yet, their systematic detection across divergent species has been hindered by complex rearrangements and reference bias, limiting our understanding of their evolutionary impact. Here we present LGvar, a divergence-aware tool for identifying SVs in population-scale and cross-species genome assemblies, enabling up to a 7-fold increase in the detection of large deletions, insertions, inversions and complex rearrangements ([≥]10 kbp). Application of LGvar uncovers 112 previously undetected large SVs overlooked by conventional methods and quantifies the effect of evolutionary divergence on SV discovery across primate euchromatic genomes, revealing an approximately 30% overall decline in detection sensitivity with increasing phylogenetic distance. Mapping SVs from comparable syntenic regions onto the primate phylogeny shows that large deletions ([≥]10 kbp) accumulate approximately two-fold faster than insertions and eight-fold faster than inversions, in contrast to the dynamics of smaller SVs (<10 kbp). Integrating structurally divergent regions with the synteny region analysis reveals over 606 previously unreported gene gains and losses in great apes and refined the totals to 134 human-lineage-specific and 51 great-ape-lineage-specific protein coding genes. These results suggest that large SVs follow distinct evolutionary trajectories, with potential selective constraints shaping genome structure. Our study establishes a generalizable strategy for cross-species SV discovery and provides a high-resolution view of how large SVs contribute to genome evolution in primates.

genomics↗

bioRxiv2026

AlphaGenome deletion responses complement supervised enhancer-gene relation prediction in primary human astrocytes

Sequence-to-function models predict molecular readouts directly from DNA, but recognizing a functional regulatory element is not equivalent to assigning the gene it regulates. We evaluated whether AlphaGenome deletion responses identify experimentally supported enhancer-gene relations, using a frozen K562 analysis and a primary-human-astrocyte CRISPR interference (CRISPRi) resource external to our analysis. The K562 mean contrast was positive but heavy-tailed, and exact joins showed direct collision with released Gasperini and ENCODE-rE2G resources; we therefore treated K562 as supporting evidence. In a frozen evaluation of 2,307 AstroREG relations, AlphaGenome deletion strength discriminated 133 functional relations from 2,174 well-powered nonfunctional relations (average precision 0.479, enhancer-cluster 95% confidence interval 0.394-0.561, prevalence 0.058; area under the receiver-operating-characteristic curve 0.726, 0.659-0.786). Adding AlphaGenome to distance, ABC score, enhancer length, measured expression and assay-depth context increased enhancer-grouped out-of-fold average precision from 0.396 to 0.534 and improved log loss from 0.169 to 0.150. The authors cross-fitted EGrf score was stronger alone (average precision 0.559); in a post-hoc calibration that held out both gene and enhancer folds, adding AlphaGenome increased average precision from 0.550 to 0.619 (paired enhancer-cluster increment 0.068, interval 0.023-0.115) and improved log loss from 0.143 to 0.132. This comparison had asymmetric inputs: EGrf was supervised on AstroREG labels and used local epigenomic and context features, whereas the AlphaGenome score was not fitted in this study to those labels or that feature panel but was read from a pre-existing primary-astrocyte RNA-seq output track. A post-hoc same-enhancer analysis gave conditional AUC 0.741 (0.663-0.814); a smaller same-gene analysis (34 genes, 155 relations) gave 0.701 (0.571-0.823). AstroREG labels and EGrf outputs were public before AlphaGenomes public release, so this evaluation is external to our study but not a post-release or proven-unseen benchmark. The results support complementary relation-level utility, not EGrf superiority, sequence-only deployment, causal assignment at arbitrary loci or equivalence between sequence deletion and CRISPRi.

genomics↗

bioRxiv2026

ASOCompass: Context- and Chemistry-Aware Activity Prediction for Transferable Antisense Oligonucleotide Screening

Antisense oligonucleotide (ASO) activity is jointly influenced by nucleotide sequence, chemical modification, target-RNA context, dose, delivery protocol, and cellular environment. Most existing computational screening methods model only a subset of these factors, limiting their ability to predict experimentally measured activity across heterogeneous screening conditions and previously unseen biological contexts. We introduce ASOCompass, a context-and chemistry-aware framework for ASO activity prediction and candidate ranking. ASOCompass integrates contextualized ASO and target-RNA sequence representations with position-specific molecular representations of chemical modifications. It further incorporates dose and delivery information together with prototype-adapted transcriptomic representations of target genes and cell lines. To encourage chemically and biophysically informative representations, the model is jointly trained on auxiliary molecular-property and sequence-derived thermodynamic prediction tasks. We evaluate ASOCompass on ASO Atlas, a large patent-derived dataset of RNase H-mediated gapmer ASOs, under held-out drug, target-gene, cell line, and joint gene-cell line settings. ASOCompass achieves an overall Spearman correlation of 0.5970, improving over the strongest ASO-specific baseline by 0.0421, and consistently performs best across all four distribution shifts. When adapted to unseen SOD1 and KLKB1 targets, ASOCompass also provides more accurate candidate ranking across different annotation budgets, reaching correlations of 0.830 and 0.696 with 1,024 target-specific labels. Additional analyses suggest that molecular-property supervision improves modification-specific ranking, while the auxiliary thermodynamic task produces representations more closely aligned with measured inhibition. These results demonstrate the potential of jointly modeling sequence, chemistry, and experimental-biological context for transferable ASO screening.

bioinformatics↗

bioRxiv2026

Comparative connectomics of parasite esophagus suggests evolutionary simplification of a nervous system

Several prominent examples suggest that the evolution of parasitism is accompanied by nervous system simplification. However, it is unclear if this is a generalizable rule and whether parasite- associated simplification occurs at the level of synaptic connectivity. The nematode esophagus is a specialized neuromuscular feeding organ that varies with diet and lifestyle. Plant-parasitic nematodes are major agricultural pests that feed through a protrusible stylet and release of extensive glandular effectors; however, the neuronal mechanisms controlling parasite feeding are unclear. Here, we used serial-section electron microscopy to reconstruct the esophageal connectome of the infective second-stage juvenile of the soybean cyst nematode, Heterodera glycines, and compared it with those of the free-living species Caenorhabditis elegans and Pristionchus pacificus. Similar to these species, H. glycines has 20 esophageal neurons with relatively conserved cell body positions. Despite this conservation, the H. glycines chemical synaptic network is highly reduced in output to musculature. A unique ensheathment of neurons by a gland cell facilitates novel synaptic connectivity in H. glycines. The H. glycines esophageal network is strongly biased toward monadic synapses and shows a greater proportion of neuron- neuron and neuron-gland connections. Consistent with a reduction in motor output, network analysis indicates that the H. glycines esophageal network is smaller and less clustered than free-living species. Using centrality analysis and synthetic ablation, we predict that control of multiple feeding modules in H. glycines depends on distinct neurons compared to free-living species. These findings show how parasitism reshapes a feeding circuit and identify candidate species-specific circuits for parasite control. Significance statementAnimal nervous systems are tuned to the behaviors they support. Nematodes occupy diverse ecological niches, and their feeding organ, the esophagus, is specialized to their diet. Understanding the esophageal nervous system provides evolutionary insights into parasitism as well as pathways for future control targets. We present the esophageal connectome of the soybean cyst nematode Heterodera glycines, which causes devastating damage to soybean production worldwide. By comparing H. glycines and free-living species, which diverged over 350 million years ago, we identify evolutionarily conserved features of the feeding circuit and highlight parasite-specific circuits as candidate targets for control.

neuroscience↗

bioRxiv2026

Hidden genetic diversity in 320 nearly-complete East Asian genome assemblies

East Asian populations, representing over 20% of the global population, remain critically underrepresented in human genomic studies, limiting our understanding of population-stratified genetic variation and its implications for health and disease. Here we present the first phase of the Asian Pan-Genome project (APG), comprising 320 nearly complete, fully phased haploid genome assemblies from 160 East Asian individuals. These assemblies achieve unprecedented quality, with an average contig N50 of 144.3 megabase pairs and an average quality value of 64.5. Leveraging these superior assemblies, we reveal previously uncharacterized diversity in human repeatome, including population-stratified patterns in centromere satellites and rDNA arrays. Compared to existing global human genome assemblies, the newly generated genomes supplement 152 million base pairs of novel sequences, 355 gene gains, 18,300 structural variation loci and 26 large euchromatic inversions missing from current human pangenomes. We perform population stratification analyses of structural variations, and further resolve the structural haplotypes of complex genomic regions such as Major Histocompatibility Complex and Survival Motor Neuron loci across global pangenomes, exemplifying tandem-duplicate and inversion-rich complex locus architectures in the human genome, respectively. This resource provides a critical foundation for human genetic studies, especially for East Asian populations, promoting more accurate variant discovery, reducing bias, and ultimately advancing the equity and efficacy of genomic medicine.

genomics↗