Biology subjects

Chang, C.

Publications and source records attributed to Chang, C..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

The ZIP8 A391T Crohn's disease-linked risk variant induces colonic metal ion dyshomeostasis, microbiome compositional shifts, and inflammation

The pathogenesis of Crohns disease involves genetic and environmental factors, with the gut microbiome playing a crucial role. The Crohns disease-associated variant rs13107325 in the SLC39A8 gene results in an A391T substitution in the ZIP8 metal ion transporter and has previously been linked to alterations in the colonic microbiome in variant carriers. We hypothesized that the A391T substitution alters metal ion homeostasis in the colonic mucosal-luminal interface, thereby inducing dysbiosis which may promote intestinal inflammation. To evaluate this hypothesis, we generated a SLC39A8 A393T mouse model (matching human A391T). Consistent with an effect of the variant on ZIP8 function, homozygous A393T mice exhibited increased cobalt in the colonic mucosa, but reduced iron, zinc, manganese, cobalt, copper, and cadmium in the colonic lumen. We performed 16S rRNA gene sequencing of colon samples and histological scoring of colon tissue collected from the SLC39A8 A393T mouse model at different ages. We identified variant-linked effects on microbiome beta diversity in 2-month, 3-4 month, and 12-month old mice and spontaneous intestinal inflammation in 10-month but not 5-month old mice. Predicted pathway analysis of the microbiome samples revealed differential enrichment of iron-, zinc- and cobalt-dependent pathways in A393T mice compared to wild-type controls. These results suggest that the variant in SLC39A8 primarily restricts metal availability to the microbiota, resulting in compositions that can adapt to the environment, and that A393T-linked dysbiosis occurs prior to the onset of inflammation. This study paves the way for future studies investigating risk variants as microbiome-disease modifiers. NEW & NOTEWORTHYMice recapitulating the human A391T Crohns disease-linked risk variant in the SLC39A8-encoded ZIP8 transporter exhibit reduced luminal trace metals and an altered microbiome composition. The microbiome compositional shift occurs prior to the onset of spontaneous colonic inflammation. This study supports an emerging paradigm by which genetic risk for inflammatory bowel disease may confer disease susceptibility through modulation of the gut microbiome.

genomics↗

bioRxiv2024

Sleep defined by arousal threshold reveals decreases in corticocortical functional correlations independently from the conventional sleep stages

Reports of sleep-specific brain activity patterns have been constrained by assessing brain function as it related to the conventional polysomnographic sleep stages. This limits the variety of sleep states and underlying activity patterns that one can discover. The current study used all-night functional MRI sleep data and defined sleep behaviorally with auditory arousal threshold (AAT) to characterize sleep depth better by searching for novel neural markers of sleep depth that are neuroanatomically localized and temporally unrelated to the conventional stages. Functional correlation values calculated in a four-min time window immediately before the determination of AAT were entered into a linear mixed effects model, allowing multiple arousals across the night per subject into the analysis, and compared to models with sleep stage to determine the unique relationships with AAT. These unique relationships were for thalamocerebellar correlations, the relationship between the right language network and the right "default-mode network dorsal medial prefrontal cortex subsystem," and the relationship between thalamus and ventral attention network. These novel neural markers of sleep depth would have remained undiscovered if the data were merely analyzed with the conventional sleep stages. Significance StatementThe original classification of sleep into distinct stages used behavioral characteristics. With the proliferation of new techniques, the first experiments might have been to perform correlations with arousal threshold. These experiments have never been performed, either with functional MRI or with any other modern technique. The amount of communication between brain regions as measured by all-night functional magnetic resonance imaging was correlated with arousal threshold. This revealed novel neural markers of sleep depth that would have remained undiscovered if the data were merely analyzed with the conventional stages. This expands our understanding of sleep and its functions beyond the constraints imposed by the conventional stages.

neuroscience↗

bioRxiv2024

The influence of basal CO2 on neurofluid dynamics measured using resting-state BOLD fMRI

An understanding of neurofluid dynamics has been gaining importance, in part given the link between neurofluid dynamics and glymphatic flow. Recently, CSF pulsations have been attributed to widespread changes in cerebral blood volume (CBV) driven by sleep-state slow-wave electrocortical activity (Fultz et al., 2019), by localized neuronal activity (Williams et al., 2023), by respiration-related autonomic tone (Picchioni et al., 2022) and by vigilance (Z. Yang et al., 2024). It was further suggested that the slow-wave induced CSF pulsations are in fact driven by autonomic (ANS) regulation (Picchioni et al., 2022), and that CSF dynamics are ultimately modulated by ANS mechanisms instead of by sleep per se. To further understand the role of this ANS regulation of vascular tone independently of sleep, and given the established influence of carbon dioxide (CO2) on both ANS tone and vascular tone, we hypothesized that a modulation of basal CO2, producing altered global vascular tone and respiration, may highlight the role of ANS regulation in driving CSF flow, and more broadly, neurofluid flow. In this work, we report on observations of neurofluid dynamics at awake normocapnia as well as mild hyper- and hypocapnia steady states. We use the resting-state BOLD fMRI time courses in neurofluid regions (i.e. blood vessels, CSF compartments) as a surrogate of neurofluid dynamics. We found that 1) the manner biomechanical does not drive the variations in neurfluid dynamics across capnias; 2) besides respiration, cardiac pulsation also independently drives neurofluid flow as an indication of the ANS pathway of control; 3) changed CO2 alters neurofluid dynamics primarily through frequency rather than amplitude of heart-rate and respiratory-volume variability. These findings suggest that hyper- and hypocapnia both represent a disruption of homeostasis that engages ANS regulation, as reflected by the deviations in CRF and RRF from normocapnia. Our work demonstrates in awake humans previously reported ANS regulation observed during sleep. As basal CO2 can modulate this ANS regulation, it represents a new avenue for modulating neurofluid dynamics independently of sleep, attention or neuronal activation. More broadly, individuals with different basal capnic states may manifest differences in CSF dynamics, giving rise to a novel paradigm for modulating neurofluid flow in awake humans.

physiology↗

bioRxiv2024

Genome sequencing of 'Fuji' apple clonal varieties reveals evolutionary history and genetic mechanism of the spur-type morphology

Somatic variations arising during asexual reproduction can lead to the emergence of bud sports exhibiting advantageous traits, forming the basis for bud sport breeding in perennial plants. Here, we report a near-complete, fully phased genome assembly of Fuji apple, enabling comprehensive identification of somatic variants across 74 clonally propagated Fuji varieties. Phylogenetic analysis of Fuji sport varieties indicates that the emergence of spur-type and early maturation traits results from multiple independent formation events. A number of putative functional somatic variants are identified, including one spur-type specific deletion located in the promoter of the TCP transcription factor gene MdTCP11. DNA methylation level of the deletion-associated miniature inverted-repeat transposable element is lower in the spur-type varieties compared to the standard-type varieties, while the expression of MdTCP11 is significantly higher. Overexpression of MdTCP11 in apple decreases the plant height, highlighting its important role in the development of spur-type apple varieties. This study sheds light on the 80-year cloning history of Fuji and provides valuable candidate causative mutations for apple breeding.

plant biology↗

bioRxiv2024

Pi-PrimeNovo: An Accurate and Efficient Non-Autoregressive Deep Learning Model for De Novo Peptide Sequencing

Peptide sequencing via tandem mass spectrometry (MS/MS) is fundamental in proteomics data analysis, playing a pivotal role in unraveling the complex world of proteins within biological systems. In contrast to conventional database searching methods, deep learning models excel in de novo sequencing peptides absent from existing databases, thereby facilitating the identification and analysis of novel peptide sequences. Current deep learning models for peptide sequencing predominantly use an autoregressive generation approach, where early errors can cascade, largely affecting overall sequence accuracy. And the usage of sequential decoding algorithms such as beam search suffers from the low inference speed. To address this, we introduce{pi} -PrimeNovo, a non-autoregressive Transformer-based deep learning model designed to perform accurate and efficient de novo peptide sequencing. With the proposed novel architecture,{pi} -PrimeNovo achieves significantly higher accuracy and up to 69x faster sequencing compared to the state-of-the-art methods. This remarkable speed makes it highly suitable for computation-extensive peptide sequencing tasks such as metaproteomic research, where{pi} -PrimeNovo efficiently identifies the microbial species-specific peptides. Moreover,{pi} -PrimeNovo has been demonstrated to have a powerful capability in accurately mining phosphopeptides in a non-enriched phosphoproteomic dataset, showing an alternative solution to detect low-abundance post-translational modifications (PTMs). We suggest that this work not only advances the development of peptide sequencing techniques but also introduces a transformative computational model with wide-range implications for biological research.

bioinformatics↗

bioRxiv2024

Observing one-divalent-metal-ion dependent and histidine-promoted His-Me family I-PpoI nuclease catalysis in crystallo

Metal-ion-dependent nucleases play crucial roles in cellular defense and biotechnological applications. Time-resolved crystallography has resolved catalytic details of metal-ion-dependent DNA hydrolysis and synthesis, uncovering the essential roles of multiple metal ions during catalysis. The histidine-metal (His-Me) superfamily nucleases are renowned for binding one divalent metal ion and requiring a conserved histidine to promote catalysis. Many His-Me family nucleases, including homing endonucleases and Cas9 nuclease, have been adapted for biotechnological and biomedical applications. However, it remains unclear how the single metal ion in His-Me nucleases, together with the histidine, promotes water deprotonation, nucleophilic attack, and phosphodiester bond breakage. By observing DNA hydrolysis in crystallo with His-Me I-PpoI nuclease as a model system, we proved that only one divalent metal ion is required during its catalysis. Moreover, we uncovered several possible deprotonation pathways for the nucleophilic water. Interestingly, binding of the single metal ion and water deprotonation are concerted during catalysis. Our results reveal catalytic details of His-Me nucleases, which is distinct from multi-metal-ion-dependent DNA polymerases and nucleases.

biochemistry↗

bioRxiv2024

Cysteine Rich Intestinal Protein 2 is a copper-Responsive regulator of skeletal muscle differentiation.

Copper (Cu) is an essential trace element required for respiration, neurotransmitter synthesis, oxidative stress response, and transcriptional regulation. Imbalance in Cu homeostasis can lead to several pathological conditions, affecting neuronal, cognitive, and muscular development. Mechanistically, Cu and Cu-binding proteins (Cu-BPs) have an important but underappreciated role in transcription regulation in mammalian cells. In this context, our lab investigates the contributions of novel Cu-BPs in skeletal muscle differentiation using murine primary myoblasts. Through an unbiased synchrotron X-ray fluorescence-mass spectrometry (XRF/MS) metalloproteomic approach, we identified the murine cysteine rich intestinal protein 2 (mCrip2) in a sample that showed enriched Cu signal, which was isolated from differentiating primary myoblasts derived from mouse satellite cells. Immunolocalization analyses showed that mCrip2 is abundant in both nuclear and cytosolic fractions. Thus, we hypothesized that mCrip2 might have differential roles depending on its cellular localization in the skeletal muscle lineage. mCrip2 is a LIM-family protein with 4 conserved Zn2+-binding sites. Homology and phylogenetic analyses showed that mammalian Crip2 possesses histidine residues near two of the Zn2+-binding sites (CX2C-HX2C) which are potentially implicated in Cu+-binding and competition with Zn2+. Biochemical characterization of recombinant human hsCRIP2 revealed a high Cu+-binding affinity for two and four Cu+ ions and limited redox potential. Functional characterization using CRISPR/Cas9-mediated deletion of mCrip2 in primary myoblasts did not impact proliferation, but impaired myogenesis by decreasing the expression of differentiation markers, possibly attributed to Cu accumulation. Transcriptome analyses of proliferating and differentiating mCrip2 KO myoblasts showed alterations in mRNA processing, protein translation, ribosome synthesis, and chromatin organization. CUT&RUN analyses showed that mCrip2 associates with a select set of gene promoters, including MyoD1 and metallothioneins, acting as a novel Cu-responsive or Cu-regulating protein. Our work demonstrates novel regulatory functions of mCrip2 that mediate skeletal muscle differentiation, presenting new features of the Cu-network in myoblasts.

molecular biology↗

bioRxiv2024

Integrative machine learning approaches for predicting disease risk using multi-omics data from the UK Biobank

We train prediction and survival models using multi-omics data for disease risk identification and stratification. Existing work on disease prediction focuses on risk analysis using datasets of individual data types (metabolomic, genomics, demographic), while our study creates an integrated model for disease risk assessment. We compare machine learning models such as Lasso Regression, Multi-Layer Perceptron, XG Boost, and ADA Boost to analyze multi-omics data, incorporating ROC-AUC score comparisons for various diseases and feature combinations. Additionally, we train Cox proportional hazard models for each disease to perform survival analysis. Although the integration of multi-omics data significantly improves risk prediction for 8 diseases, we find that the contribution of metabolomic data is marginal when compared to standard demographic, genetic, and biomarker features. Nonetheless, we see that metabolomics is a useful replacement for the standard biomarker panel when it is not readily available.

genomics↗

bioRxiv2024

Efficient storage and regression computation for population-scale genome sequencing studies

In the era of big data in human genetics, large-scale biobanks aggregating genetic data from diverse populations have emerged as important for advancing our understanding of human health and disease. However, the computational and storage demands of whole genome sequencing (WGS) studies pose significant challenges, especially for researchers from underfunded institutions or developing countries, creating a disparity in research capabilities. We introduce new approaches that significantly enhance computational efficiency and reduce data storage requirements for WGS studies. By developing algorithms for compressed storage of genetic data, focusing particularly on optimizing the representation of rare variants, and designing regression methods tailored for the scale and complexity of WGS data, we significantly lower computational and storage costs. We integrate our approach into PLINK 2.0. The implementation demonstrates considerable reductions in storage space and computational time without compromising analytical accuracy, as evidenced by the application to the AllofUs project data. We optimized the runtime of an exome-wide association analysis involving 19.4 million variants and the body mass index phenotype of 125,077 individuals, reducing it from 695.35 minutes (approximately 11.5 hours) on a single machine to just 1.57 minutes using 30 GB of memory and 50 threads (or 8.67 minutes with 4 threads). Additionally, we extended this approach to support multi-phenotype analyses. We anticipate that our approach will enable researchers across the globe to unlock the potential of population biobanks, accelerating the pace of discoveries that can improve our understanding of human health and disease.

genetics↗

bioRxiv2024

Quinoline-based compounds can inhibit diverse enzymes that act on DNA

DNA methylation, as exemplified by cytosine-C5 methylation in mammals and adenine-N6 methylation in bacteria, is a crucial epigenetic mechanism driving numerous vital biological processes. Developing non-nucleoside inhibitors to cause DNA hypomethylation is a high priority, in order to treat a variety of significant medical conditions without the toxicities associated with existing cytidine-based hypomethylating agents. In this study, we have characterized fifteen quinoline-based analogs. Notably, compounds with additions like a methylamine (9) or methylpiperazine (11) demonstrate similar low micromolar inhibitory potency against both human DNMT1 (which generates C5-methylcytosine) and Clostridioides difficile CamA (which generates N6-methyladenine). Structurally, compounds 9 and 11 specifically intercalate into CamA-bound DNA via the minor groove, adjacent to the target adenine, leading to a substantial conformational shift that moves the catalytic domain away from the DNA. This study adds to the limited examples of DNA methyltransferases being inhibited by non-nucleotide compounds through DNA intercalation, following the discovery of dicyanopyridine-based inhibitors for DNMT1. Furthermore, our study shows that some of these quinoline-based analogs inhibit other enzymes that act on DNA, such as polymerases and base excision repair glycosylases. Finally, in cancer cells compound 11 elicits DNA damage response via p53 activation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/587980v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@da2e94org.highwire.dtl.DTLVardef@27f909org.highwire.dtl.DTLVardef@4ec628org.highwire.dtl.DTLVardef@1b384df_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LISix of fifteen quinoline-based derivatives demonstrated comparable low micromolar inhibitory effects on human cytosine methyltransferase DNMT1, and the bacterial adenine methyltransferases Clostridioides difficile CamA and Caulobacter crescentus CcrM. C_LIO_LICompounds 9 and 11 were found to intercalate into a DNA substrate bound by CamA. C_LIO_LIThese quinoline-based derivatives also showed inhibitory activity against various base excision repair DNA glycosylases, and DNA and RNA polymerases. C_LIO_LICompound 11 provokes DNA damage response via p53 activation in cancer cells. C_LI

molecular biology↗

bioRxiv2024

High Frequency Terahertz Stimulation Alleviates Neuropathic Pain by Inhibiting the Pyramidal Neuron Activity in the Anterior Cingulate Cortex of mice

Neuropathic pain (NP) is caused by a lesion or disease of the somatosensory system and is characterized by abnormal hypersensitivity to stimuli and nociceptive responses to non-noxious stimuli, affecting approximately 7-10% of the general population. However, current first-line drugs like non-steroidal anti-inflammatory agents and opioids have limitations, including dose-limiting side effects, dependence, and tolerability issues. Therefore, developing new interventions for the management of NP is urgent. In this study, we discovered that the high-frequency terahertz stimulation (HFTS) at approximate 36 THz effectively alleviates NP symptoms in mice with spared nerve injury. Computational simulation suggests that the frequency resonates with the carbonyl group in the filter region of Kv1.2 channels, facilitating the translocation of potassium ions. In vivo and in vitro results demonstrate that HFTS reduces the excitability of pyramidal neurons in the anterior cingulate cortex through enhancing the voltage-gated K+ and also the leak K+ conductance. This research presents a novel optical intervention strategy with terahertz waves for the treatment of NP and holds promising application in other nervous system diseases.

neuroscience↗

bioRxiv2024

Decoding cell identity with multi-scale explainable deep learning

Cells are the fundamental structural and functional units of life. Studying the definition and composition of different cell types can help us understand the complex mechanisms underlying biological diversity and functionality. The increasing volume of extensive single-cell omics data makes it possible to provide detailed characterisations of cell types. Recently, there has been a rise in deep learning-based approaches that generate cell type labels solely through mapping query data to reference data. However, these approaches lack multi-scale descriptions and interpretations of identified cell types. Here, we propose Cell Decoder, a biological prior knowledge informed model to achieve multi-scale representation of cells. We implemented automated machine learning and post-hoc analysis techniques to decode cell identity. We have shown that Cell Decoder compares favourably to existing methods, offering multi-view interpretability for decoding cell identity and data integration. Furthermore, we have showcased its applicability in uncovering novel cell types and states in both human bone and mouse embryonic contexts, thereby revealing the multi-scale heterogeneity inherent in cell identities.

bioinformatics↗

bioRxiv2024

GPX3 supports ovarian cancer tumor progression in vivo and promotes expression of GDF15

ObjectiveWe previously reported that high expression of the extracellular glutathione peroxidase GPX3 is associated with poor patient outcome in ovarian serous adenocarcinomas, and that GPX3 protects ovarian cancer cells from oxidative stress in culture. Here we tested if GPX3 is necessary for tumor establishment in vivo and to identify novel downstream mediators of GPX3s pro-tumorigenic function. MethodsGPX3 was knocked-down in ID8 ovarian cancer cells by shRNA to test the role of GPX3 in tumor establishment using a syngeneic IP xenograft model. RNA sequencing analysis was carried out in OVCAR3 cells following shRNA-mediated GPX3 knock-down to identify GPX3-dependent gene expression signatures. ResultsGPX3 knock-down abrogated clonogenicity and intraperitoneal tumor development in vivo, and the effects were dependent on the level of GPX3 knock-down. RNA sequencing showed that loss of GPX3 leads to decreased gene expression patterns related to pro-tumorigenic signaling pathways. Validation studies identified GDF15 as strongly dependent on GPX3. GDF15, a member of the TGF-{beta} growth factor family, has known oncogenic and immune modulatory activities. Similarly, GPX3 expression positively correlated with pro-tumor immune cell signatures, including regulatory T-cell and macrophage infiltration, and displayed significant correlation with PD-L1 expression. ConclusionsWe show for the first time that tumor produced GPX3 is necessary for ovarian cancer growth in vivo and that it regulates expression of GDF15. The immune profile associated with GPX3 expression in serous ovarian tumors suggests that GPX3 may be an alternate marker of ovarian tumors susceptible to immune check-point inhibitors.

cancer biology↗

bioRxiv2023

SpatialCells: Automated Profiling of Tumor Microenvironments with Spatially Resolved Multiplexed Single-Cell Data

BackgroundCancer is a complex cellular ecosystem where malignant cells coexist and interact with immune, stromal, and other cells within the tumor microenvironment. Recent technological advancements in spatially resolved multiplexed imaging at single-cell resolution have led to the generation of large-scale and high-dimensional datasets from biological specimens. This underscores the necessity for automated methodologies that can effectively characterize the molecular, cellular, and spatial properties of tumor microenvironments for various malignancies. ResultsThis study introduces SpatialCells, an open-source software package designed for region-based exploratory analysis and comprehensive characterization of tumor microenvironments using multiplexed single-cell data. ConclusionsSpatialCells efficiently streamlines the automated extraction of features from multiplexed single-cell data and can process samples containing millions of cells. Thus, SpatialCells facilitates subsequent association analyses and machine learning predictions, making it an essential tool in advancing our understanding of tumor growth, invasion, and metastasis. Availability of code and materialshttps://github.com/SemenovLab/SpatialCells.

bioinformatics↗

bioRxiv2023

Molecular basis for dual functions in pilus assembly modulated by the lid of a pilus-specific sortase

The biphasic assembly of Gram-positive pili begins with the covalent polymerization of distinct pilins catalyzed by a pilus-specific sortase, followed by the cell wall anchoring of the resulting polymers mediated by the housekeeping sortase. In Actinomyces oris, the pilus-specific sortase SrtC2 not only polymerizes FimA pilins to assemble type 2 fimbriae with CafA at the tip, but it can also act as the anchoring sortase, linking both FimA polymers and SrtC1-catalyzed FimP polymers (type 1 fimbriae) to peptidoglycan when the housekeeping sortase SrtA is inactive. To date, the structure-function determinants governing the unique substrate specificity and dual enzymatic activity of SrtC2 have not been illuminated. Here, we present the crystal structure of SrtC2 solved to 2.10-[A] resolution. SrtC2 harbors a canonical sortase fold and a lid typical for class C sortases and additional features specific to SrtC2. Structural, biochemical, and mutational analyses of SrtC2 reveal that the extended lid of SrtC2 modulates its dual activity. Specifically, we demonstrate that the polymerizing activity of SrtC2 is still maintained by alanine-substitution, partial deletion, and replacement of the SrtC2 lid with the SrtC1 lid. Strikingly, pilus incorporation of CafA is significantly reduced by these mutations, leading to compromised polymicrobial interactions mediated by CafA. In a srtA mutant, the partial deletion of the SrtC2 lid reduces surface anchoring of FimP polymers, and the lid-swapping mutation enhances this process, while both mutations diminish surface anchoring of FimA pili. Evidently, the extended lid of SrtC2 enables the enzyme the cell wall-anchoring activity in a substrate-selective fashion.

microbiology↗

bioRxiv2023

Protein language models-assisted engineering of Uracil-N glycosylase enables programmable T-to-G and T-to-C base editing

Current base editors use DNA deamination enzymes, such as cytidine deaminase (CBE) or adenine deaminase (ABE), to facilitate transition nucleotide substitutions. Combining CBE or ABE with glycosylase enzymes, including CGBE and AYBE, can induce limited transversion mutations. Nonetheless, a critical demand remains for base editors capable of generating alternative mutation types, such as T>G corrections, which could address over 17% of monogenic SNVs responsible for human genetic diseases. In this study, we leveraged protein language models to engineer a uracil-N-glycosylase (UNG) variant with altered substrate specificities to thymines (eTDG). Notably, after only two rounds of testing fewer than 50 predicted variants, more than 50% exhibited a 1.5-11-fold enhancement in enzymatic activities, a success rate much greater than random mutagenesis. When eTDG was fused with Cas9 nickase without deaminases, it effectively induced programmable T to G or T to C substitutions and precisely corrected db/db diabetic mutation in mice (up to 55%). Our findings not only establish orthogonal strategies for developing novel base editors, but also demonstrate the capacities of protein language models for optimizing enzymes without extensive task-specific training data or laborious experimental procedures.

bioengineering↗

bioRxiv2023

SiamEEGNet: Siamese Neural Network-Based EEG Decoding for Drowsiness Detection

Recent advancements in deep-learning have significantly enhanced EEG-based drowsiness detection. However, most existing methods overlook the importance of relative changes in EEG signals compared to a baseline, a fundamental aspect in conventional EEG analysis including event-related potential and time-frequency spectrograms. We herein introduce SiamEEGNet, a Siamese neural network architecture designed to capture relative changes between EEG data from the baseline and a time window of interest. Our results demonstrate that SiamEEGNet is capable of robustly learning from high-variability data across multiple sessions/subjects and outperforms existing model architectures in cross-subject scenarios. Furthermore, the models interpretability associates with previous findings of drowsiness-related EEG correlates. The promising performance of SiamEEGNet highlights its potential for practical applications in EEG-based drowsiness detection. We have made the source codes available at http://github.com/CECNL/SiamEEGNet.

neuroscience↗

bioRxiv2023

Integrating large-scale meta-GWAS and PigGTEx resources to decipher the genetic basis of complex traits in pig.

Understanding the molecular and cellular mechanisms that underlie complex traits in pigs is crucial for enhancing their genetic improvement program and unleashing their substantial potentials in human biomedicine research. Here, we conducted a meta-GWAS analysis for 232 complex traits with 28.3 million imputed whole-genome sequence variants in 70,328 individuals from 14 pig breeds. We identified a total of 6,878 genomic regions associated with 139 complex traits. By integrating with the Pig Genotype-Tissue Expression (PigGTEx) resource, we systemically explored the biological context and regulatory circuits through which these trait-associated variants act and finally prioritized 16,664 variant-gene-tissue-trait circuits. For instance, rs344053754 regulates the expression of UGT2B31 in the liver by affecting the activity of regulatory elements and ultimately influences litter weight at weaning. Furthermore, we investigated the conservation of genetic and regulatory mechanisms underlying 136 human traits and 232 pig traits. Overall, our multi-breed meta-GWAS in pigs provides invaluable resources and novel insights for understanding the regulatory and evolutionary mechanisms of complex traits in both pigs and humans.

genetics↗