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Biology subjects

Ge, T.

Publications and source records attributed to Ge, T..

At least 19 recordsLinked to original sources

Mapping the genetic architecture of human cortical expansion and its links to neuropsychiatric disorders

Cortical expansion is a defining feature of human evolution and neurodevelopment, involving the tangential growth and gyrification of the cerebral cortex. Although disruptions to the expansion of the cortex are implicated in diverse brain-based disorders, the genetic architecture underlying this process remains undercharacterized. Here, we integrated GWAS data for five neuroanatomical phenotypes measured in up to 73,800 individuals to model a latent genomic factor capturing the shared genetic basis of cortical surface area, folding, curvature, gyrification, and intracranial volume. Using a multivariate framework, we mapped this pleiotropic architecture across biological scales, identifying novel effector genes, neural cell types, and developmental pathways involved in cortical expansion. Functional genomic evidence indicated that a diverse cellular ensemble contributes to the tangential growth and gyrification of the cortex during prenatal neurodevelopment, with progenitor cell lineages prominently involved. Regional analyses further revealed that genetic influences are spatially heterogeneous and organized along canonical anatomical, functional, and developmental gradients. Finally, cortical expansion exhibited substantial genetic overlap with neurodevelopmental, psychiatric, and neurological disorders, with shared genetic influences often concentrated in prefrontal cortical regions. Together, these findings map the genetic architecture of human cortical expansion and implicate it as a common etiological axis linking evolution, neurodevelopment, and health and disease.

genomics↗

Precision Functional Parcellation of the Human Cortex via Rest-Task fMRI Fusion

Individual-specific cortical parcellations enable the characterization of brain network organization that is often obscured by population-level atlases, with broad implications for both basic neuroscience and translational applications. However, existing methods rely primarily on resting-state fMRI and underutilize task-evoked data, which provide complementary information about functional specialization. This limitation partly reflects the challenge of integrating heterogeneous datasets that differ in task design, sample size, and cortical coverage. Here, we present mRBM-HBP, a scalable hierarchical Bayesian framework that incorporates a multinomial restricted Boltzmann machine to model spatial dependencies, enabling efficient and flexible integration of resting-state and task fMRI across diverse datasets and inference of both group-level and individual-level cortical parcellations. We show that mRBM-HBP achieves performance comparable to state-of-the-art resting-state-based parcellation methods while substantially reducing computational cost. By integrating large-scale task-fMRI datasets, we derive a task-based parcellation and demonstrate that resting-state and task conditions reveal largely consistent macroscopic networks, while task data provide state-specific refinements of functional boundaries. Moreover, a fused rest-task group-level atlas improves the accuracy, reliability, and individual specificity of inferred parcellations, particularly when individual-level data are limited. These results indicate that integrating resting-state and task fMRI enhances precision mapping of functional brain organization.

neuroscience↗

Discovering disease genetic variation impacting gene expression in 103 brain tissues with the Brain Ontology Expression (BRONTE) graph neural network model

Uncovering genes dysregulated in neuropsychiatric diseases promises to put forward therapeutic targets. By linking disease risk variants to tissue-specific gene regulation, the Genotype-Tissue Expression (GTEx) project has enabled discovery of disease genes and the brain tissues where these pathogenic effects occur. But, GTEx requires huge investment in obtaining human brain tissues, limiting the sample size and tissue diversity available. Crucially, this resource does not contain all key tissues where brain diseases are known to originate. Here, we propose a novel graph convolutional model that integrates the GTEx brain expression data with the Allen Brain Atlas, a resource spanning over 100 fine grained brain tissues that are annotated with an ontology of tissue organization. Our model, Brain Ontology Expression (BRONTE), allows completion of the GTEx data for 221 individuals to impute expanded expression in 103 uncollected detailed brain tissues. We show that expression data imputed by BRONTE recovers measured variation in expression across subjects, genes, and brain tissues. Most importantly, our method both recapitulates known relationships between genetic variations and gene expression, and simultaneously discovers both new genes impacted by genetic variants, and the tissues impacted. This allows us to put forward novel mechanisms of effect for genetic variation associated with 30 brain-related traits, supplying therapeutic targets in overlooked tissues of the brain.

bioinformatics↗

Next-Generation saRNA Platforms: Systematic Screening and Engineering Enhances Superior Protein Expression and Organ-Specific Targeting for RNA Therapeutics

Self-amplifying RNA (saRNA), derived from alphaviruses, encodes nonstructural proteins (NSP1-4) that form a replicase complex, enabling prolonged and amplified protein expression at lower doses than conventional mRNA. However, its high immunogenicity and limited replication efficiency require optimization for improved protein expression. Here, we systematically optimized a widely used Venezuelan Equine Encephalitis Virus (VEEV)-based saRNA by refining its capping structure, nucleotide modifications, polyA tail length, and regulatory elements, achieving over 10-fold enhancement in protein expression compared to the wild-type. Additionally, we screened 28 alphavirus-derived saRNA constructs in vitro, selecting the top 3 candidates Everglades virus (EVEV), Mosso das Pedras virus (MDPV), and Rio Negro virus (RNV) for in vivo evaluation using SM102 lipid nanoparticle (LNP) formulations and luciferase reporters. These optimized saRNAs demonstrated sustained expression and distinct extrahepatic tissue-specific biodistribution, notably high spleen targeting compared to conventional mRNA. Such organ-specific expression profiles present novel strategies for targeted RNA therapeutics, and further integration with advanced delivery technologies could enhance the precision, efficacy, and therapeutic potential of mRNA-based treatments. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=149 SRC="FIGDIR/small/644708v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@1eed9bdorg.highwire.dtl.DTLVardef@192815org.highwire.dtl.DTLVardef@196a8e9org.highwire.dtl.DTLVardef@2b6e53_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOTOC figureC_FLOATNO C_FIG

molecular biology↗

A Mouse-adapted SARS-CoV-2 Model for Investigating Post-acute Sequelae of COVID infection

The coronavirus disease of 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), remains a major health issue after nearly 7 millions of death toll in the last four years. As the world is recovering with improving vaccines and antiviral treatments, the alarming rate of long-COVID, or Post-acute Sequelae of COVID-19 (PASC), calls for further investigations. Among a list of symptoms associated with multi-organ dysfunctions, the neurological complications are particularly intriguing, yet the underlying mechanisms remain elusive. With the recently developed mouse adapted SARS-CoV-2 stain, we are now able to model the mild COVID infection in C57BL/6 mice and study the chronic immune responses and subsequent damages in different organs long after the viruses are clearly naturally in the body. More specifically, we found adult C57BL/6J mice developed neurological impairments, including behavior changes related to sensorimotor coordination, depression- and anxiety-like behaviors, and inflammation in multiple organs including lung, liver and brain, which persisted over at least 4 weeks in mice even with mild infection. Therefore, this model can be used to further explopred the mechanisms of PASC, as well as potential intervention or therapeutic approaches.

neuroscience↗

All of Us diversity and scale improve polygenic prediction contextually with greatest improvements for underrepresented populations

Recent studies have demonstrated that polygenic risk scores (PRS) trained on multi-ancestry data can improve prediction accuracy in groups historically underrepresented in genomic studies, but the availability of linked health and genetic data from large-scale diverse cohorts representative of a wide spectrum of human diversity remains limited. To address this need, the All of Us research program (AoU) generated whole-genome sequences of 245,388 individuals (release v7) who collectively reflect the diversity of the USA. Leveraging this resource and another widely-used population-scale biobank, the UK Biobank (UKB) with a half million participants, we developed PRS trained on multi-ancestry and multi-biobank data with up to [~]750,000 participants for 32 common, complex traits and diseases across a range of genetic architectures. We then evaluated effects of ancestry, PRS methodology, and genetic architecture on PRS accuracy across a held out subset of ancestrally diverse AoU participants. Overall, we found that the increased diversity of AoU significantly improved PRS performance in some participants in AoU, especially underrepresented individuals, across multiple phenotypes. Notably, maximizing sample size by combining discovery data across AoU and UKB is not the optimal approach for predicting some phenotypes particularly in African ancestry populations; rather, using data from only AoU for these traits resulted in the greatest accuracy. This was especially true for less polygenic traits with large ancestry-enriched effects, and larger heritability estimates in African ancestry populations, such as neutrophil count (R2: 0.055 vs. 0.035 using AoU vs. cross-biobank meta-analysis, respectively, because of e.g. DARC). Lastly, we calculated individual-level PRS accuracies rather than grouping by continental ancestry, a critical step towards interpretability in precision medicine. Individualized PRS accuracy decays linearly as a function of ancestry divergence, but the slope was smaller using multi-ancestry GWAS compared to using European GWAS. Our results highlight the potential of biobanks with more balanced representations of human diversity to facilitate more accurate PRS for the individuals least represented in genomic studies.

genomics↗

Exportin-1 functions as an adaptor for transcription factor-mediated docking of chromatin at the nuclear pore complex.

Nuclear pore proteins (Nups) in yeast, flies and mammals physically interact with hundreds or thousands of chromosomal sites, which impacts transcriptional regulation. In budding yeast, transcription factors mediate interaction of Nups with enhancers of highly active genes. To define the molecular basis of this mechanism, we exploited a separation-of-function mutation in the Gcn4 transcription factor that blocks its interaction with the nuclear pore complex (NPC) without altering its DNA binding or activation domains. SILAC mass spectrometry revealed that this mutation reduces the interaction of Gcn4 with the highly conserved nuclear export factor Crm1/Xpo1. Crm1 both interacts with the same sites as Nups genome-wide and is required for Nup2 to interact with the yeast genome. In vivo, Crm1 undergoes extensive and stable interactions with the NPC. In vitro, Crm1 binds to Gcn4 and these proteins form a complex with the nuclear pore protein Nup2. Importantly, the interaction between Crm1 and Gcn4 does not require Ran-GTP, suggesting that it is not through the nuclear export sequence binding site. Finally, Crm1 stimulates DNA binding by Gcn4, supporting a model in which allosteric coupling between Crm1 binding and DNA binding permits docking of transcription factor-bound enhancers at the NPC.

cell biology↗

SARS-COV-2 induces blood-brain barrier and choroid plexus barrier impairments and vascular inflammation in mice

The coronavirus disease of 2019 (COVID-19) pandemic that has led to more than 700 million confirmed cases and near 7 million deaths. Although Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) virus mainly infects the respiratory system, neurological complications are widely reported in both acute infection and long-COVID cases. Despite the success of vaccines and antiviral treatments, neuroinvasiveness of SARS-CoV-2 remains as an important question, which is also centered on the mystery whether the virus is capable of breaching the barriers into the central nervous system. By studying the K18-hACE2 infection model, we observed clear evidence of microvascular damage and breakdown of the blood-brain barrier (BBB). Mechanistically, SARS-CoV-2 infection caused pericyte damage, tight junction loss, endothelial activation and vascular inflammation, which together drive microvascular injury and BBB impairment. In addition, the blood-cerebrospinal fluid barrier at the choroid plexus was also impaired after infection. Therefore, cerebrovascular and choroid plexus dysfunctions are important aspects of COVID-19 and may contribute to the neurological complications both acutely and in long COVID.

neuroscience↗

A single-cell atlas of the single versus multiple parous Hu Sheep ovary

In the modern sheep production system, the reproductive performance of ewes determines the economic profitability of farming. The mechanism of difference in litter size is important for the selection and breeding of high-fecundity ewes. Hu sheep is a high-quality sheep breed with high fecundity in China and is ideal for investigating high reproductive traits. In the current study, the sheep with lambing number [≥]3 in three consecutive lambing records were assigned to the HLS group, and lambing number = 1 as the LLS group selected from the same farm with three consecutive lambing. Three randomly picked ewes were slaughtered within 12 h of estrus, and unilateral ovarian tissue was collected and analyzed by single-cell RNA sequencing in each group. A total of five types of somatic cells were identified, and corresponding expression profiles were mapped in the ovaries of the Hu sheep. Additionally, the results of the difference in ovary somatic cell expression profiles between HLS and LLS present that the differences between multiples vs. singleton Hu sheep were mainly clustered in the GCs. In addition, 4 granulosa cell subtypes were identified. GeneSwitches results revealed the opening of JPH1 expression and the closure of LOC101112291, which leads to different evolutionary directions of the granular cells. The expression levels of FTH1 and FTL in GCs of Hu sheep in the HLS group were significantly higher, which inhibited necroptosis and ferroptosis of mural- GCs from decreasing follicular atresia. This study constructed the cellular atlas of the ovary and revealed related biological characteristics at the cellular molecular level. It provides a theoretical basis for the mechanisms underlying the differences in ovulation numbers, which contributes to breeding high-fertility sheep and molecular genetics-based selection.

zoology↗

Extra-islet expression of islet antigen boosts T-cell exhaustion to prevent autoimmune diabetes

Persistent antigen exposure results in the differentiation of functionally impaired, also termed exhausted, T cells which are maintained by a distinct population of precursors of exhausted T (TPEX) cells. T cell exhaustion is well studied in the context of chronic viral infections and cancer, but it is unclear if and how antigen-driven T cell exhaustion controls progression of autoimmune diabetes and whether this process can be harnessed to prevent diabetes. Using non-obese diabetic (NOD) mice, we show that some CD8+ T cells specific for the islet antigen, islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP) displayed terminal exhaustion characteristics within pancreatic islets but were maintained in the TPEX cell state in peripheral lymphoid organs. To examine the impact of antigen on T cell exhaustion in diabetes, we generated transgenic NOD mice with inducible IGRP expression in peripheral antigen presenting cells. Antigen exposure in the extra-islet environment induced severely exhausted IGRP-specific T cells with reduced ability to produce IFN{gamma}, which protected these mice from diabetes. Our data demonstrate that T cell exhaustion induced by delivery of antigen can be harnessed to prevent autoimmune diabetes.

immunology↗

Atypical language network lateralization is reflected throughout the macroscale functional organization of cortex

Hemispheric specialization is a fundamental feature of human brain organization. However, it is not yet clear to what extent the lateralization of specific cognitive processes may be evident throughout the broad functional architecture of cortex. While the majority of people exhibit left-hemispheric language dominance, a substantial minority of the population shows reverse lateralization. Using twin and family data from the Human Connectome Project, we provide evidence that atypical language dominance is associated with global shifts in cortical organization. Individuals with atypical language organization exhibited corresponding hemispheric differences in the macroscale functional gradients that situate discrete large-scale networks along a continuous spectrum, extending from unimodal through association territories. Analyses revealed that both language lateralization and gradient asymmetries are, in part, driven by genetic factors. These findings pave the way for a deeper understanding of the origins and relationships linking population-level variability in hemispheric specialization and global properties of cortical organization.

neuroscience↗

The molecular genetic landscape of human brain size variation

Human brain size increases dynamically through early development, peaks in adolescence, and varies up to two-fold among adults. Although previous studies have elucidated changes in brain size across evolution, development, traits, and diseases, the molecular underpinnings of interindividual variation in brain size remain unknown. Here, we leverage postmortem brain RNA sequencing and estimates of brain weight (BW) in 2,531 individuals across three independent datasets, to identify 928 genes that show genome-wide significant associations with either higher or lower BW (BW+, BW-, respectively). These BW gene sets showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto developmental, functional and cellular axes of brain organization. Expression differences among evolutionarily conserved BW genes were predictive of interspecies differences in brain size, and functional annotation of BW genes revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses of in vivo neuroimaging phenotypes confirmed that the genetic regulation of BW-transcripts influences cortical surface area and volume, as well as behavioral traits related to brain function and disease. Cumulatively, our study represents a major step towards the goal of delineating the causal mechanisms of human brain size variation in health and disease.

neuroscience↗

Genome-wide signatures of geographic expansion and breeding process in soybean

The clarification of genomic signatures left during evolutionary histories of crops is crucial for breeding varieties adapting to changing climate. Soybean, a leguminous crop, provides both plant oil and protein. Here, we analyzed genome sequences of 2,214 soybeans and proposed its evolutionary route, which includes four geographic paths, expansion of annual wild soybean (Glycine soja Sieb. & Zucc.) from Southern China, domestication in Central China, expansion of landrace (G. max (L.) Merr.), and local breeding. We observed that local adaptation of the wild and cultivated soybeans was largely independent, and that genetic introgression was mostly derived from sympatric rather than allopatric wild populations during the range expansion of soybean landraces. Range expansion and breeding processes were accompanied with positive selection of flowering-time genes including GmSPA3c as validated by knock-out mutants. Our study shed lights on the evolutionary history of soybean and provides valuable genetic resources for future breeding. TeaserThe expansion and selection history of soybean

genomics↗

Improving the computation efficiency of polygenic risk score modeling: Faster in Julia

To enable large-scale application of polygenic risk scores in a computationally efficient manner we translate a widely used polygenic risk score construction method, Polygenic Risk Score - Continuous Shrinkage (PRS-CS), to the Julia programing language, PRS.jl. On nine different traits with varying genetic architectures, we demonstrate that PRS.jl maintains accuracy of prediction while decreasing the average run time by 5.5x. Additional programmatic modifications improve usability and robustness. This freely available software substantially improves work flow and democratizes utilization of polygenic risk scores by lowering the computational burden of the PRS-CS method.

genetics↗

Comprehensive analysis of DNA replication timing in genetic diseases and gene knockouts identifies MCM10 as a novel regulator of the replication program

Cellular proliferation depends on the accurate and timely replication of the genome. Several genetic diseases are caused by mutations in key DNA replication genes; however, it remains unclear whether these genes influence the normal program of DNA replication timing. Similarly, the factors that regulate DNA replication dynamics are poorly understood. To systematically identify trans-acting modulators of replication timing, we profiled replication in 184 cell lines from three cell types, encompassing 60 different gene knockouts or genetic diseases. Through a rigorous approach that considers the background variability of replication timing, we concluded that most samples displayed normal replication timing. However, mutations in two genes showed consistently abnormal replication timing. The first gene was RIF1, a known modulator of replication timing. The second was MCM10, a highly conserved member of the pre-replication complex. MCM10 mutant cells demonstrated replication timing variability comprising 46% of the genome and at different locations than RIF1 knockouts. Replication timing alterations in MCM10-mutant cells was predominantly comprised of replication initiation defects. Taken together, this study demonstrates the remarkable robustness of the human replication timing program and reveals MCM10 as a novel modulator of DNA replication timing.

genetics↗

Atp13a5 Marker Reveals Pericytes of The Central Nervous System in Mice

Perivascular mural cells including vascular smooth cells (VSMCs) and pericytes are integral components of the vascular system. In the central nervous system (CNS), pericytes are also known as the guardian of the blood-brain barrier, blood-spinal cord barrier and blood-retinal barrier, and play key roles in maintaining cerebrovascular and neuronal functions. However, the functional difference between CNS and peripheral pericytes has not been resolved at the genetic and molecular levels. Hence, the generation of reliable CNS pericyte-specific models and genetic tools remains very challenging. Here, we report a new CNS pericyte marker in mice. This cation-transporting ATPase 13A5 (Atp13a5) marker is highly specific to the pericytes in brain, spinal cord and retina. We generated a transgenic model with a knock-in tdTomato reporter and Cre recombinase. The tdTomato reporter reliably labels the CNS pericytes, but not found in any other CNS cell types including closely related VSMCs, or in peripheral organs. More importantly, Atp13a5 is turned on at embryonic day E15, suggesting brain pericytes are shaped by the developing neural environment. We hope that the new tools will allow us to further explore the heterogeneity of pericytes and achieve a better understanding of CNS pericytes in health and diseases.

neuroscience↗

The Cost of Untracked Diversity in Brain-Imaging Prediction

Brain-imaging research enjoys increasing adoption of supervised machine learning for singlesubject disease classification. Yet, the success of these algorithms likely depends on population diversity, including demographic differences and other factors that may be outside of primary scientific interest. Here, we capitalize on propensity scores as a composite confound index to quantify diversity due to major sources of population stratification. We delineate the impact of population heterogeneity on the predictive accuracy and pattern stability in two separate clinical cohorts: the Autism Brain Imaging Data Exchange (ABIDE, n=297) and the Healthy Brain Network (HBN, n=551). Across various analysis scenarios, our results uncover the extent to which cross-validated prediction performances are interlocked with diversity. The instability of extracted brain patterns attributable to diversity is located preferentially to the default mode network. Our collective findings highlight the limitations of prevailing deconfounding practices in mitigating the full consequences of population diversity.

neuroscience↗

Functional architecture of the aging brain

The intrinsic functional organization of the brain changes into older adulthood. Age differences are observed at multiple spatial scales, from global reductions in modularity and segregation of distributed brain systems, to network-specific patterns of dedifferentiation. Whether dedifferentiation reflects an inevitable, global shift in brain function with age, circumscribed, experience dependent changes, or both, is uncertain. We employed a multi-method strategy to interrogate dedifferentiation at multiple spatial scales. Multi-echo (ME) resting-state fMRI was collected in younger (n=181) and older (n=120) healthy adults. Cortical parcellation sensitive to individual variation was implemented for precision functional mapping of each participant, while preserving group-level parcel and network labels. ME-fMRI processing and gradient mapping identified global and macroscale network differences. Multivariate functional connectivity methods tested for microscale, edge-level differences. Older adults had lower BOLD signal dimensionality, consistent with global network dedifferentiation. Gradients were largely age-invariant. Edge-level analyses revealed discrete, network-specific dedifferentiation patterns in older adults. Visual and somatosensory regions were more integrated within the functional connectome; default and frontoparietal control network regions showed greater connectivity; and the dorsal attention network was more integrated with heteromodal regions. These findings highlight the importance of multi-scale, multi-method approaches to characterize the architecture of functional brain aging.

neuroscience↗