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Li, Q.

Publications and source records attributed to Li, Q..

At least 433 records · Page 24Linked to original sources

Concatenated tandem constructs of BK channels reveal three distinct types of subunit stoichiometry in channel modulation by the auxiliary γ subunit and mutations in the channel pore region

Big-conductance, Ca2+-activated K+ (BK) channels consist of Ca2+- and voltage-sensing, pore-forming (BK) subunits and regulatory auxiliary {beta} or {gamma} subunits. Concatenated subunit constructs are powerful tools for elucidating subunit stoichiometry in ion channel gating and regulation, allowing control over subunit arrangement, stoichiometry, and mutation. However, the additional S0 transmembrane segment in BK places its N- and C-termini on opposite sides of the membrane, preventing tandem BK channel subunit construction by conventional methods. To investigate the atypical "all-or-none" modulatory function of {gamma} subunits and the subunit stoichiometry of BK channel gating, we developed concatenated constructs containing 2 or 4 BK subunits by splicing them into modular forms that can be co-expressed to form functional channels. These constructs retained voltage and Ca2+ gating properties similar to intact BK channels. By fusing the LRRC26 ({gamma}1) subunit to the N-terminus of tandem BK constructs, we found that a single {gamma}1 subunit per subunit tetramer is sufficient to fully modulate the channel. Furthermore, the L312A mutation in the deep pore region exhibited a stoichiometrically graded effect on voltage-gated BK channel activation. In contrast, a V288A mutation at the selectivity filter induced channel inactivation only when present in all four BK subunits. Thus, by engineering concatenated BK constructs, we identified three distinct stoichiometric modes of BK channel gating control by LRRC26, the pore, and the selectivity filter. This study offers new molecular tools and advances our understanding of subunit stoichiometry in BK channel gating and modulation.

biochemistry↗

FM3VCF: A Software Library for Accelerating the Loading of Large VCF Files in Genotype Data Analyses

BackgroundThe increasing size of genotype data has led to the loading of VCF files becoming a computational bottleneck in various analyses, including imputation and genome-wide association studies (GWAS). To address this issue, we developed a software library, FM3VCF (fast M3VCF), that utilizes multiple CPU threads to accelerate this process. FindingsFM3VCF can convert VCF files into the exclusive data format of MINIMAC4[1], M3VCF[1], and efficiently read and parse data from VCF files. In comparison to m3vcftools[1], FM3VCF is approximately 20 times faster for compressing VCF files to M3VCF format. Furthermore, FM3VCF is approximately 3 times faster than HTSlib[2], including decompressing and parsing, for reading compressed VCF files. FM3VCF is written in C and is open-source, available for download from https://github.com/Oliver-111/m3vcf under the MIT/BSD license. ConclusionFM3VCF is a powerful tool for accelerating the loading of large VCF files in genotype data analyses. By fully utilizing multiple CPU threads, FM3VCF can significantly reduce the computational burden in various genomic analyses.

bioinformatics↗

African swine fever virus I196L is a virulence determinant and its deletant induces robust protection in Domestic pig

The worldwide pandemic of African swine fever virus (ASFV) has a profound impact on the global pig industry. ASFV is a complex multilayered structure and the functions of unknown genes are being revealed. Here we deleted I196L from virulent ASFV SY18 with different length and obtained two recombinant viruses. The replication efficiency of the two recombinant viruses were similar but significantly lower than parental SY18. The pigs all survived the two recombinant viruses with 106.0TCID50 except one pig occurred sudden death and the suvived pigs all resisted the challenge without fever after intramuscularly injecting a lethal dose (102.0TCID50) of ASFV SY18. The recombinant viruses induced a strong anti-p54 humoral immune response. Meanwhile, the pigs also inevitably appeared moderate to high viremia throughout the observation period and presented a gradually downward trend. The results show that deleting I196L gene is a potential and effective vaccine that protects pigs from ASFV. IMPORTANCEThe worldwide outbreak of African swine fever (ASF) cannot be effectively prevented due to no availably commercial vaccine. Many different types of vaccine candidates are researched and reported, which is a hopeful trend to develop safety and efficacy vaccine. Here we report on an unknown functional gene, I196L, which affects the virulence and replication of ASFV. When I196L was deleted from ASFV SY18, the recombinant virus decreased virulence and resisted the challenge of parental strain. This is a novel, effective, potential live attenuated vaccine (LAVs) for ASF.

immunology↗

A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders

Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive, and may be unavailable for legacy datasets used for genome-wide association studies (GWAS). Using an integrated feature selection/aggregation model, we developed Image-Mediated Association Study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression Quantitative Trait Loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost-savings for integrated analysis of genetics and imaging.

bioinformatics↗

A genetic program for vascular pericyte precursors

Brain pericytes are one of the critical cell types that regulate endothelial barrier function and activity, thus ensuring adequate blood flow to the brain. The genetic pathways guiding undifferentiated cells into mature pericytes are not well understood. We show here that pericyte precursor populations from both neural crest and head mesoderm of zebrafish express the transcription factor nkx3.1 develop into brain pericytes. We identify the gene signature of these precursors, and show that an nkx3.1, foxf2a, and cxcl12b -expressing pericyte precursor population is present around the basilar artery prior to artery formation and pericyte recruitment. The precursors later spread throughout the brain and differentiate to express canonical pericyte markers. Cxcl12b-Cxcr4 signaling is required for pericyte attachment and differentiation. Further, both nkx3.1 and cxcl12b are necessary and sufficient in regulating pericyte number as loss inhibits and gain increases pericyte number. Through genetic experiments we have defined a precursor population for brain pericytes and identified genes critical for their differentiation.

developmental biology↗

Levy statistics define anxiety and depression in mice subjected to chronic stress

IntroductionAnxiety and depression are recognized as adaptive responses to external stressors in organisms. Current methods for evaluating anxiety and depression in rodents are both burdensome and stressful. The objective of this investigation is to explore a simplified methodology for identifying stress-induced and stress-free states, as well as anxiety and depression levels, by analyzing the movement patterns of rodents. MethodsTo address this issue, we utilized Levy statistics to examine the movement patterns of stressed rodents and compared them to non-stressed controls. We employed the two-dimensional Kolmogorov-Smirnov test to identify significant differences in the {gamma} and parameters derived from Levy flight (LF) between anxiety, depression, and control mice. Additionally, we employed the support vector machine algorithm to optimize the classification of each group. ResultsOur analysis revealed that stressed mice displayed heavy-tailed distributions of movement velocity in open fields, resembling the movement patterns observed in animal predators searching for scarce food sources in nature. In contrast, non-stressed mice exhibited a normal distribution of speed. Notably, the effectiveness of this methodology in the field of drug discovery was confirmed by the response of stressed mice to fluoxetine, a well-established selective serotonin reuptake inhibitor (SSRI). ConclusionThis study unveils a previously unidentified statistical walking pattern in mice experiencing anxiety and depression. These findings offer a novel and accessible approach for distinguishing between anxiety, depression, and healthy mice. This method provides a one-step gentle approach (free walk in an open field) instead of the traditional multi-step stressful tests.

animal behavior and cognition↗

Integrating Image and Molecular Profiles for Spatial Transcriptomics Analysis

The spatially resolved transcriptomics (SRT) field has revolutionized our ability to comprehensively leverage image and molecular profiles to elucidate spatial organization of cellular microenvironments. Current clustering analysis of SRT data primarily relies on molecular information and fails to fully exploit the morphological features present in histology images, leading to compromised accuracy and interpretability. To overcome these limitations, we have developed a multi-stage statistical method called iIMPACT. It includes a finite mixture model to identify and define histology-based spatial domains based on AI-reconstructed histology images and spatial context of gene expression measurements, and a negative binomial regression model to detect domain-specific spatially variable genes. Through multiple case studies, we demonstrate iIMPACT outperformed existing methods, confirmed by ground truth biological knowledge. These findings underscore the accuracy and interpretability of iIMPACT as a new clustering approach, providing valuable insights into the cellular spatial organization and landscape of functional genes within spatial transcriptomics data.

bioinformatics↗

Successful placentation in human pregnancy is regulated by reciprocal interactions between maternal uterine NK cells and fetal placental trophoblast

Fetal growth and development during human pregnancy depends on delivery of adequate maternal oxygen and nutrients to the fetus via the placenta. In humans, the balanced invasion of fetal placental trophoblast cells into the maternal uterine lining, where they interact with uterine natural killer cells (uNK), is thought to be critical for a successful pregnancy but exactly how this influences reproductive outcomes remains undefined. Here, we used our trophoblast organoid model and primary tissue samples to determine how uNK affect placentation. By locating potential interaction axes between primary trophoblast cells and uNK using single cell transcriptomics, and in vitro modelling of these interactions in trophoblast organoids, we identify a uNK-derived cytokine signal that promotes trophoblast differentiation by enhancing epithelial-mesenchymal transition and increasing trophoblast cells at the late stage of the invasive pathway. Moreover, it affects transcriptional programs involved in increasing blood flow, placental access to nutrients, and dampening inflammatory and adaptive immune responses, as well as gene signatures associated with disorders of pregnancy such as pre-eclampsia. Our findings shed new light on how optimal immunological interactions between maternal uNK cells and fetal trophoblast enhance reproductive success.

developmental biology↗

RETROFIT: REFERENCE-FREE DECONVOLUTION OF CELL-TYPE MIXTURES IN SPATIAL TRANSCRIPTOMICS

Spatial transcriptomics (ST) enables genome-wide measurement of gene expression in intact tissues, but typically captures mixtures of multiple cell types at each spatial location. Deconvolving these mixtures is essential for resolving cell-type-specific spatial organization and transcriptional programs. Existing approaches often rely on matched single-cell references or curated marker genes, which may be unavailable, incomplete, or difficult to integrate across platforms. We present RETROFIT, a Bayesian framework for reference-free deconvolution of spatial transcriptomics data that operates directly on sequencing measurements and incorporates external information only at a post hoc annotation stage when available. Across extensive simulations and multiple real datasets, RETROFIT demonstrates robust performance, outperforming existing reference-free methods and matching or exceeding reference-based approaches when references are imperfect. Notably, RETROFIT remains effective at near-single-cell resolution, as demonstrated on Visium HD data, recovering fine-grained spatial patterns without requiring single-cell references or marker genes. These results establish RETROFIT as a broadly applicable approach for reference-free spatial transcriptomics analysis across platforms and resolutions. RETROFIT is available at https://bioconductor.org/packages/retrofit/.

bioinformatics↗

Enhancing gene co-expression network inference for the malaria parasite Plasmodium falciparum

BackgroundMalaria results in more than 550,000 deaths each year due to drug resistance in the most lethal Plasmodium (P.) species P. falciparum. A full P. falciparum genome was published in 2002, yet 44.6% of its genes have unknown functions. Improving functional annotation of genes is important for identifying drug targets and understanding the evolution of drug resistance. ResultsGenes function by interacting with one another. So, analyzing gene co-expression networks can enhance functional annotations and prioritize genes for wet lab validation. Earlier efforts to build gene co-expression networks in P. falciparum have been limited to a single network inference method or gaining biological understanding for only a single gene and its interacting partners. Here, we explore multiple inference methods and aim to systematically predict functional annotations for all P. falciparum genes. We evaluate each inferred network based on how well it predicts existing gene-Gene Ontology (GO) term annotations using network clustering and leave-one-out cross-validation. We assess overlaps of the different networks edges (gene co-expression relationships) as well as predicted functional knowledge. The networks edges are overall complementary: 47%-85% of all edges are unique to each network. In terms of accuracy of predicting gene functional annotations, all networks yield relatively high precision (as high as 87% for the network inferred using mutual information), but the highest recall reached is below 15%. All networks having low recall means that none of them capture a large amount of all existing gene-GO term annotations. In fact, their annotation predictions are highly complementary, with the largest pairwise overlap of only 27%. We provide ranked lists of inferred gene-gene interactions and predicted gene-GO term annotations for future use and wet lab validation by the malaria community. ConclusionsThe different networks seem to capture different aspects of the P. falciparum biology in terms of both inferred interactions and predicted gene functional annotations. Thus, relying on a single network inference method should be avoided when possible. Supplementary dataAttached. Availability and implementationAll data and code are available at https://nd.edu/~cone/pfalGCEN/. Contacttmilenko@nd.edu

systems biology↗

Lymphoid tissues contribute to viral clonotypes present in plasma at early post-ATI in SIV-infected rhesus macaques

The rebound-competent viral reservoir (RCVR), comprised of virus that is able to persist during antiretroviral therapy (ART) and mediate reactivation of systemic viral replication and rebound viremia after antiretroviral therapy interruption (ATI), remains the biggest obstacle to the eradication of HIV infection. A better understanding of the cellular and tissue origins and the dynamics of viral populations that initiate rebound upon ATI could help develop targeted therapeutic strategies for reducing the RCVR. In this study, barcoded SIVmac239M was used to infect rhesus macaques to enable monitoring of viral barcode clonotypes contributing to virus detectable in plasma after ATI. Blood, lymphoid tissues (LTs, spleen, mesenteric and inguinal lymph nodes), and non-lymphoid tissues (NLTs, colon, ileum, lung, liver, and brain) were analyzed using viral barcode sequencing, intact proviral DNA assay, single-cell RNA sequencing, and combined CODEX/RNAscope/in situ hybridization. Four of seven animals had viral barcodes detectable by deep sequencing of plasma at necropsy although plasma viral RNA remained < 22 copies/mL. Among the tissues studied, mesenteric and inguinal lymph nodes, and spleen contained viral barcodes detected in plasma, and trended to have higher cell-associated viral loads, higher intact provirus levels, and greater diversity of viral barcodes. CD4+ T cells were the main cell type harboring viral RNA (vRNA) after ATI. Further, T cell zones in LTs showed higher vRNA levels than B cell zones for most animals. These findings are consistent with LTs contributing to virus present in plasma early after ATI. One Sentence SummaryThe reemerging of SIV clonotypes at early post-ATI are likely from the secondary lymphoid tissues.

immunology↗

RAPSYN-Mediated Neddylation of BCR-ABL Alternatively Determines the Fate of Philadelphia Chromosome-positive Leukemia

Philadelphia chromosome-positive (Ph+) leukemia is a fatal hematological malignancy. Although standard treatments with tyrosine kinase inhibitors (TKI) have achieved remarkable success in prolonging patient survival, intolerance, relapse and TKI resistance remain serious issues for patients with Ph+ leukemia. Here, we report a new leukemogenic process in which RAPSYN and BCR-ABL co-occur in Ph+ leukemia, and RAPSYN mediates the neddylation of BCR-ABL. Consequently, neddylated BCR-ABL enhances the stability by competing its c-CBL-mediated degradation. Furthermore, SRC phosphorylates RAPSYN to activate its NEDD8 E3 ligase activity, promoting BCR-ABL stabilization and disease progression. Moreover, in contrast to in vivo ineffectiveness of PROTAC-based degraders, depletion of RAPSYN expression or its ligase activity decreased BCR-ABL stability and, in turn, inhibited tumor formation and growth. Collectively, these findings represent an alternative to tyrosine kinase activity for the oncoprotein and leukemogenic cells and generate a rationale of targeting RAPSYN-mediated BCR-ABL neddylation for the treatment of Ph+ leukemia.

cancer biology↗

Neo-functionalization and co-option of Pif genes facilitate the evolution of a novel shell microstructure in oysters

Molluscan shell, composed of a diverse range of architectures and microstructures, is a classic model system to study the relationships between molecular evolution and biomineralized structure formation. The shells of oysters differ from those of other molluscs by possessing a novel microstructure, chalky calcite, which facilitates adaptation to the sessile lifestyle. However, the genetic basis and evolutionary origin of this adaptive innovation remain largely unknown. Here, we present the first chromosome-level genome and shell proteomes of the Iwagaki oyster Crassostrea nippona. Multi-omic integrative analyses revealed that independently evolved and co-opted genes as well as lineage-specific domains are involved in the formation of chalky layer in the oysters. Rapid mineralization involving chalky calcite are essential for reconstruction of the shell. Importantly, von Willebrand factor type A and chitin-binding domains are identified as basic members of molluscan biomineralization toolkit. We show that the well-known Pif shared a common origin in the last common ancestor of Bilateria. Furthermore, Pif and LamG3 genes acquire new genetic function for shell mineralization in bivalves and the chalky layer formation in oysters through a combination of gene duplication and domain reorganization. Our findings highlight neo-functionalization as a crucial mechanism for shell diversity, which may be applied more widely for studies on the evolution of metazoan biomineralization. This study also has potential implications for material science and biomimetic research.

evolutionary biology↗

Establishment of hairy root culture and its genetic transformation of Stephania tetrandra S. Moore for production of BIAs

Metabolic engineering improvement of plants will play an essential role in future agriculture, but this largely depends on the establishment of genetic transformation. Stephania tetrandra S. Moore is a traditional Chinese medicine used for rheumatalgia that accumulates benzylisoquinoline alkaloids as its main active ingredients. Wild or farmed plants have remained the main source of these essential medicines, resulting in supply pressure due to the scarcity of wild plant resources and the slow growth rate in cultivation. Here, we constructed Agrobacterium rhizogenes (C58C1)-mediated hairy root culture and a co-transformation system in S. tetrandra to obtain a new source of bisbenzylisoquinoline alkaloids production. We show that the biomass of the hairy roots increased by 10-fold, and the content of tetrandrine reached 8.382 {+/-} 0.160 mg/g DW after 50 days of cultivation. In addition, overexpression of (R, S)-norcoclaurine 6-O-methyltransferase (6OMT) gene or treatment of hairy roots with methyl jasmonate (MJ) increased protoberberine alkaloid content. This work provides a method of obtaining hairy roots and a genetic transformation system for S. tetrandra, not only broadening the access to S. tetrandra resources, but also laying a foundation for further elucidation of the biosynthesis of tetrandrine and related alkaloids.

plant biology↗

An Interpretable Bayesian Clustering Approach with Feature Selection for Analyzing Spatially Resolved Transcriptomics Data

SO_SCPLOWUMMARYC_SCPLOWRecent breakthroughs in spatially resolved transcriptomics (SRT) technologies have enabled comprehensive molecular characterization at the spot or cellular level while preserving spatial information. Cells are the fundamental building blocks of tissues, organized into distinct yet connected components. Although many non-spatial and spatial clustering approaches have been used to partition the entire region into mutually exclusive spatial domains based on the SRT high-dimensional molecular profile, most require an ad-hoc selection of less interpretable dimensional-reduction techniques. To overcome this challenge, we propose a zero-inflated negative binomial mixture model to cluster spots or cells based on their molecular profiles. To increase interpretability, we employ a feature selection mechanism to provide a low-dimensional summary of the SRT molecular profile in terms of discriminating genes that shed light on the clustering result. We further incorporate the SRT geospatial profile via a Markov random field prior. We demonstrate how this joint modeling strategy improves clustering accuracy, compared with alternative state-of-the-art approaches, through simulation studies and two real data applications.

bioinformatics↗

Integrated multi-omics approach reveals the role of SPEG in skeletal muscle biology including its relationship with myospryn complex

Autosomal-recessive mutations in SPEG (striated muscle preferentially expressed protein kinase) have been linked to centronuclear myopathy. Loss of SPEG is associated with defective triad formation, abnormal excitation-contraction coupling, and calcium mishandling in skeletal muscles. To elucidate the underlying molecular pathways, we have utilized multi-omics tools and analysis to obtain a comprehensive view of the complex biological processes. We identified that SPEG interacts with myospryn complex proteins (CMYA5, FSD2, RyR1), and SPEG deficiency results in myospryn complex abnormalities. In addition, transcriptional and protein profiles of SPEG-deficient muscle revealed defective mitochondrial function including aberrant accumulation of enlarged mitochondria on electron microscopy. Furthermore, SPEG regulates RyR1 phosphorylation at S2902, and its loss affects JPH2 phosphorylation at multiple sites. On analyzing the transcriptome, the most dysregulated pathways affected by SPEG deficiency included extracellular matrix-receptor interaction and peroxisome proliferator-activated receptors signaling, which may be due to defective triad and mitochondrial abnormalities. In summary, we have elucidated the critical role of SPEG in triad as it works closely with myospryn complex, phosphorylates JPH2 and RyR1, and demonstrated that its deficiency is associated with mitochondrial abnormalities. This study emphasizes the importance of using multi-omics techniques to comprehensively analyze the molecular anomalies of rare diseases. Synopsis O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC="FIGDIR/small/538136v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@bc3cbborg.highwire.dtl.DTLVardef@37195dorg.highwire.dtl.DTLVardef@1624caeorg.highwire.dtl.DTLVardef@985a2c_HPS_FORMAT_FIGEXP M_FIG C_FIG We have previously linked mutations in SPEG (striated preferentially expressed protein) with a recessive form of centronuclear myopathy and/or dilated cardiomyopathy and have characterized a striated muscle-specific SPEG-deficient mouse model that recapitulates human disease with disruption of the triad structure and calcium homeostasis in skeletal muscles. In this study, we applied multi-omics approaches (interactomic, proteomic, phosphoproteomic, and transcriptomic analyses) in the skeletal muscles of SPEG-deficient mice to assess the underlying pathways associated with the pathological and molecular abnormalities. O_LISPEG interacts with myospryn complex proteins (CMYA5, FSD2, RyR1), and its deficiency results in myospryn complex abnormalities. C_LIO_LISPEG regulates RyR1 phosphorylation at S2902, and its loss affects JPH2 phosphorylation at multiple sites. C_LIO_LISPEG and SPEG{beta} have different interacting partners suggestive of differential function. C_LIO_LITranscriptome analysis indicates dysregulated pathways of ECM-receptor interaction and peroxisome proliferator-activated receptor signaling. C_LIO_LIMitochondrial defects on the transcriptome, proteome, and electron microscopy, may be a consequence of defective calcium signaling. C_LI

molecular biology↗

An automated proximity proteomics pipeline for subcellular proteome and protein interaction mapping

Proximity labeling (PL) through biotinylation coupled with mass spectrometry (MS) has emerged as a powerful technique for capturing spatial proteomes within living cells. Large-scale sample processing for proximity proteomics requires a workflow that minimizes hands-on time while enhancing quantitative reproducibility. Here, we present a scalable PL pipeline integrating automated enrichment of biotinylated proteins in a 96-well plate format. By combining this pipeline with an optimized quantitative MS acquisition method based on data-independent acquisition (DIA), we not only significantly increased sample throughput but also improved the reproducibility of protein identification and quantification. We applied this pipeline to delineate subcellular proteomes across various cellular compartments, including endosomes, late endosomes/lysosomes, the Golgi apparatus, and the plasma membrane. Moreover, employing 5HT2A serotonin receptor as a model, we investigated temporal changes of proximal interaction networks induced by the receptors activation with serotonin. Finally, to demonstrate the applicability of our PL pipeline across multiple experimental conditions, we further modified the PL pipeline for reduced sample input amounts to accommodate CRISPR-based gene knockout, and assessed the dynamics of the 5HT2A network in response to the perturbation of selected proximal interactors. Importantly, the presented PL approach is universally applicable to PL proteomics using biotinylation-based PL enzymes, increasing both throughput and reproducibility of standard protocols.

systems biology↗

A longitudinal resource for population neuroscience of school-age children and adolescents in China

During the past decade, cognitive neuroscience has been calling for population diversity to address the challenge of validity and generalizability, ushering in a new era of population neuroscience. The developing Chinese Color Nest Project (devCCNP, 2013-2022), a ten-year pilot stage of the lifespan CCNP (2013-2032), is an ongoing project focusing on brain-mind development. The project aims to create and share a large-scale, longitudinal and multimodal dataset of typically developing children and adolescents (ages 6.0-17.9 at enrolment) in the Chinese population. The devCCNP houses not only phenotypes measured by demographic, biophysical, psychological and behavioural, cognitive, affective, and ocular-tracking assessments but also neurotypes measured with magnetic resonance imaging (MRI) of brain morphometry, resting-state function, naturalistic viewing function and diffusion structure. This Data Descriptor introduces the first data release of devCCNP including a total of 864 visits from 479 participants. Herein, we provided details of the experimental design, sampling strategies, and technical validation of the devCCNP resource. We demonstrate and discuss the potential of a multicohort longitudinal design to depict normative brain growth curves from the perspective of developmental population neuroscience. The devCCNP resource is shared as part of the "Chinese Data-sharing Warehouse for In-vivo Imaging Brain" in the Chinese Color Nest Project (CCNP) - Lifespan Brain-Mind Development Data Community (https://www.scidb.cn/en/c/ccnp) at the Science Data Bank. Design TypesO_LIAccelerated longitudinal design C_LIO_LIBrain-mind development C_LIO_LIPopulation imaging C_LIO_LIBrain chart C_LIO_LIRepeated measure C_LI MeasurementsO_LIPsychological behaviours C_LIO_LIBiophysical and physical measures C_LIO_LIIntelligence quotient measure C_LIO_LINeuroimaging C_LI Sample Characteristic - OrganismO_LIHomo sapiens C_LI Sample Characteristic - EnvironmentO_LISchool- and community-based sample C_LI Sample Characteristic - LocationO_LIChongqing and Beijing, China C_LI DurationO_LI10 years (2013-2022) C_LI

neuroscience↗