Biology subjects

Li, T.

Publications and source records attributed to Li, T..

At least 217 records · Page 12Linked to original sources

bioRxiv2024

Key contribution of prefrontal inhibition to passive coping behaviour: chronic stress and fast-acting antidepressant

Persistent passive coping behaviour is a hallmark feature in major depression and is reversed by fast-acting antidepressants (such as ketamine). This behaviour is regulated by a specific cortico-midbrain circuit. However, whether the prefrontal cortex (PFC), especially inhibition in PFC, contributes to the modulation of passive coping, and whether this modulation is important for mediating the impacts of chronic stress and/or fast-acting antidepressants, are poorly understood. Here, we found that rostral prelimbic cortex (rPL) bidirectionally controls the occurrence of passive coping behaviour where excitatory and inhibitory neurons play opposite roles. Chronic stress leads to reduced excitation/inhibition (E/I) ratio, reflected as alterations in in vivo spiking rate, synaptic inputs and intrinsic excitability of both excitatory and inhibitory neurons. A fast-acting antidepressant, (2R, 6R)-hydroxynorketamine (HNK), reduced passive coping behaviour, restored rPL E/I ratio and partially reversed altered properties in rPL neurons, in chronically stressed mice. Importantly, chronic stress and HNK mostly affected fast-spiking/parvalbumin inhibitory neurons instead of other inhibitory neurons, indicating the important role of this subtype of inhibitory neurons in the above processes. These findings demonstrate the importance of rPL E/I balance in regulating passive coping, which can be modulated by chronic stress and rapidly restored by fast-acting antidepressant.

neuroscience↗

bioRxiv2024

Elevated Ubiquitin Phosphorylation by PINK1 Contributes to Proteasomal Impairment and Promotes Neurodegeneration

Ubiquitin (Ub), a central regulator of protein turnover, can be phosphorylated by PINK1 (PTEN-induced putative kinase 1) to generate S65-phosphorylated ubiquitin (pUb). Elevated pUb levels have been observed in aged human brains and in Parkinsons disease, but the mechanistic link between pUb elevation and neurodegeneration remains unclear. Here, we demonstrate that pUb elevation is a common feature under neurodegenerative conditions, including Alzheimers disease, aging, and ischemic injury. We show that impaired proteasomal activity leads to the accumulation of sPINK1, the cytosolic form of PINK1 that is normally proteasome-degraded rapidly. This accumulation increases ubiquitin phosphorylation, which then inhibits ubiquitin-dependent proteasomal activity by interfering with both ubiquitin chain elongation and proteasome-substrate interactions. Specific expression of sPINK1 in mouse hippocampal neurons induced progressive pUb accumulation, accompanied by protein aggregation, proteostasis disruption, neuronal injury, neuroinflammation, and cognitive decline. Conversely, pink1 knockout mitigated protein aggregation in both mouse brains and HEK293 cells. Furthermore, the detrimental effects of sPINK1 could be counteracted by co-expressing Ub/S65A phospho-null mutant but exacerbated by over-expressing Ub/S65E phospho-mimic mutant. Together, these findings reveal that pUb elevation, triggered by reduced proteasomal activity, inhibits proteasomal activity and forms a feedforward loop that drives progressive neurodegeneration.

biochemistry↗

bioRxiv2024

Adhesion G protein-coupled receptor ADGRG1 promotes protective microglial response in Alzheimer's disease

Germline genetic architecture of Alzheimers disease (AD) indicates microglial mechanisms of disease susceptibility and outcomes. However, the mechanisms that enable microglia to mediate protective responses to AD pathology remain elusive. Adgrg1 is specifically expressed in yolk-sac-derived microglia. This study reveals the role of yolk-sac-derived microglia in AD pathology, highlighting the function of ADGRG1 in modulating microglial protective responses to amyloid deposition. Utilizing both constitutive and inducible microglial Adgrg1 knockout 5xFAD models, we demonstrate that Adgrg1 deficiency leads to increased amyloid deposition, exacerbated neuropathology, and accelerated cognitive impairment. Transcriptomic analyses reveal a distinct microglial state characterized by downregulated genes associated with homeostasis, phagocytosis, and lysosomal functions. Functional assays in mouse models and human embryonic stem cells-derived microglia support that microglial ADGRG1 is required for efficient A{beta} phagocytosis. Together, these results uncover a GPCR-dependent microglial response to A{beta}, pointing towards potential therapeutic strategies to alleviate disease progression by enhancing microglial functional competence.

neuroscience↗

bioRxiv2024

Models of microbiome evolution incorporating environmental microbial selection

The environment plays a crucial role in shaping the microbial composition of hosts. Different environments harbor distinct microbial communities, leading to variation in the availability of different microbes to potential hosts. Over the past few decades, human activities have significantly altered the environment, resulting in a decline in microbial diversity. Currently, the impact of this environmentally-induced reduction in microbial diversity on environmental microbial communities, host-microbiome interactions, and their evolutionary implications remains unclear. In this paper, we simulated how environmental microbial selection can lead to decreasing microbial diversity, using a previously-developed selection model. Our results indicate that microbial communities are influenced by both environmental conditions and host preferences. The diversity of the microbiome carried by hosts is impacted by the environment, with stronger environmental microbial selection reducing microbial diversity in the hosts, while at the same time, facilitating the emergence of mutually beneficial symbioses between microorganisms and hosts. Environmental microbial selection (EMS) leads to the survival of highly fit microorganisms in the environment, while the fitnesses of hosts and microbes within hosts remain relatively unaffected by environmental microbial selection.

evolutionary biology↗

bioRxiv2024

Estrogen Receptor 1 Signaling in Hepatic Stellate Cells Designates Resistance to Liver Fibrosis

The prevalence and severity of liver fibrosis appear higher in men than in premenopausal women, while postmenopausal women exhibit the worsened disease. However, the pathophysiological mechanism underlying such clinical observations remains incompletely understood. Here, we show that sex hormone depletion in adult female mice exaggerates the model of liver fibrosis, while estradiol replacement in castrated male mice is sufficient to mitigate the disease severity. Transcriptomic analyses and immunohistochemistry then demonstrate that both human and mouse hepatic stellate cells (HSCs), the primary cell type responsible for extracellular fibrous depositions, predominantly express the estrogen receptor 1 (ESR1). Of importance, genetic deletion of ESR1 in mouse HSCs markedly promotes liver fibrosis. Moreover, chromatin immunoprecipitation followed by sequencing (ChIP-seq) and in vitro manipulations reveal that ESR1 can directly target the expression of fibrosis-related genes in HSCs. Together, this study has elucidated a critical aspect of ESR1 signaling in the sexual dimorphism of liver fibrosis.

pathology↗

bioRxiv2024

Global transcription factors analyses reveal hierarchy and synergism of regulatory networks and master virulence regulators in Pseudomonas aeruginosa

The transcription factor (TF) regulatory network in Pseudomonas aeruginosa is complex and involves multiple regulators that respond to various environmental signals and physiological cues by regulating gene expression. However, the biological functions of at least half of its 373 putative TFs remain uncharacterised. Herein, chromatin immunoprecipitation sequencing (ChIP-seq) was used to investigate the binding sites of 172 TFs in the P. aeruginosa PAO1 strain. The results revealed 81,009 significant binding peaks in the genome, more than half of which were located in the promoter regions. To further decode the diverse regulatory relationships among TFs, a hierarchical network was assembled into three levels: top, middle, and bottom. Thirteen ternary regulatory motifs revealed flexible relationships among TFs in small hubs, and a comprehensive co-association atlas was established, showing the enrichment of seven core associated clusters. Twenty-four TFs were identified as the master regulators of virulence-related pathways. The pan-genome analysis revealed the conservation and evolution of TFs in P. aeruginosa complex and other species. A Web-based database combining existing and new data from ChIP-seq and the high-throughput systematic evolution of ligands by exponential enrichment was established for searching TF-binding sites. This study provides important insights into the pathogenic mechanisms of P. aeruginosa and related bacteria and is expected to contribute to the development of effective therapies for infectious diseases caused by this pathogen.

microbiology↗

bioRxiv2024

EPHA2 Regulates SOX2 during Esophageal Development

The human esophagus, derived from the anterior foregut endoderm, requires proper dorsal-ventral patterning for development. The transcription factor SOX2, crucial in this process, when dysregulated, leads to congenital esophageal abnormalities. EPHA2, a receptor tyrosine kinase, is vital in various developmental processes and cancer models, where it activates SOX2. This study demonstrates that EPHA2 regulates SOX2 expression during esophageal development using human iPSCs and iPSC-derived human esophageal organoids (HEO). Inhibition of EPHA2 decreased iPSC-derived HEO formation and SOX2 expression. These findings provide evidence of EPHA2 as being a key regulator of SOX2 signaling in early esophageal development. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/617209v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@16b8a8aorg.highwire.dtl.DTLVardef@1548672org.highwire.dtl.DTLVardef@46e28corg.highwire.dtl.DTLVardef@1c35578_HPS_FORMAT_FIGEXP M_FIG SFD: Serum-Free Differentiation media; EPC: esophageal progenitor cells; HEO: human esophageal organoids Created with BioRender.com C_FIG HighlightsO_LISOX2 is crucial for proper esophageal development. C_LIO_LIEPHA2 is a receptor tyrosine kinase involved in various developmental processes. C_LIO_LIEPHA2 activates SOX2. C_LIO_LIInhibition of EPHA2 decreased SOX2 expression and human esophageal organoid formation. C_LI

developmental biology↗

bioRxiv2024

Diversified, miniaturized and ancestral parts for mammalian genome engineering and molecular recording

As the synthetic biology and genome engineering fields mature and converge, there is a clear need for a "parts list" of components that are diversified with respect to both functional activity (to facilitate design) and primary sequence (to facilitate assembly). Here we designed libraries composed of extant, ancestral, mutagenized or miniaturized variants of Pol III promoters or guide RNA (gRNA) scaffolds and quantified their ability to mediate precise edits to the mammalian genome via multiplex prime editing. We identified thousands of parts that reproducibly drive a range of editing activities in human and mouse stem cells and cancer cell lines, including hundreds exhibiting similar or greater activity than the sequences used in conventional genome engineering constructs. We further conducted saturation mutagenesis screens of canonical Pol III promoters (U6p, 7SKp, H1p) and the prime editing guide RNA (pegRNA) scaffold, which identified tolerated variants that can be superimposed on baseline parts to further enhance sequence diversity. While characterizing thousands of orthologous promoters from hundreds of extant or ancestral genomes, we incidentally mapped the functional landscape of mammalian Pol III promoter evolution. Finally, to showcase the usefulness of these parts, we designed a "ten key" molecular recording array that lacks repetitive subsequences in order to facilitate its one-step assembly in yeast. Upon delivering this 15.8 kb tandem array of promoters and guides to mammalian cells, individual pegRNAs exhibited balanced activities as predicted by the activity of component parts, despite their relocation to a single locus. Looking forward, we anticipate that the diversified parts and variant effect maps reported here can be leveraged for the design, assembly and deployment of synthetic loci encoding arrays of gRNAs exhibiting predictable, differentiated levels of activity, which will be useful for multiplex perturbation, advanced biological recorders and complex genetic circuits.

synthetic biology↗

bioRxiv2024

Mapping the landscape of social behavior

Social interaction is integral to animal behavior. However, we lack tools to describe it with quantitative rigor, limiting our understanding of its principles and neuropsychiatric disorders, like autism, that perturb it. Here, we present a technique for high-resolution 3D tracking of postural dynamics and social touch in freely interacting animals, solving the challenging subject occlusion and part assignment problems using 3D geometric reasoning, graph neural networks, and semi-supervised learning. We collected over 140 million 3D postures in interacting rodents, featuring new monogenic autism rat lines lacking reports of social behavioral phenotypes. Using a novel multi-scale embedding approach, we identified a rich landscape of stereotyped actions, interactions, synchrony, and body contact. This enhanced phenotyping revealed a spectrum of changes in autism models and in response to amphetamine that were inaccessible to conventional measurements. Our framework and large library of interactions will greatly facilitate studies of social behaviors and their neurobiological underpinnings.

animal behavior and cognition↗

bioRxiv2024

Analytical and computational solution for the estimation of SNP-heritability in biobank-scale and distributed datasets

Estimation of heritability has been a routine in statistical genetics, in particular with the increasing sample size such as biobank-scale data and distributed datasets, the latter of which has increasing concerns of privacy. Recently a randomized Haseman-Elston regression (RHE-reg) has been proposed to estimate SNP-heritability, and given sufficient iteration (B) RHE-reg can tackle biobank-scale data, such as UK Biobank (UKB), very efficiently. In this study, we present an analytical solution that balances iteration B and RHE-reg estimation, which resolves the convergence of the proposed RHE-reg in high precision. We applied the method for 81 UKB quantitative traits and estimated their SNP-heritability and test statistics precisely. Furthermore, we extended RHE-reg into distributed datasets and demonstrated their utility in real data application and simulated data. The software for estimating SNP-heritability for biobank-scale data is released: https://github.com/gc5k/gear2.

genetics↗

bioRxiv2024

Identification of Intrinsic Features for Cortical Separability of Human and Mouse Neurons

This work introduces a novel framework for holistic comparative analysis of cortical regions in mouse and human brains at single-neuron resolution, with a primary focus on the morphological and molecular characteristics of neurons. To do so, we generated one of the largest dendritic reconstruction datasets of cortical neurons to date, comprising 2,363 human neurons and 16,011 mouse neurons from the frontal, parietal, and temporal lobes, followed by establishing a rigorous procedure to identify anatomically and functionally corresponding brain regions with minimal variability in brain mapping. Additionally, we leveraged single nucleus/cell transcriptomic data from independent groups to validate the molecular correspondence of the brain regions identified in this study. The significance of these anatomically, functionally, and molecularly corresponding mouse-human region pairs is highlighted by examining the intrinsic features of their respective cortical regions. Our findings reveal that human neuron branching patterns differ dramatically from those in mouse brains, particularly in terms of dendritic branching frequency and normalized dendritic branching intervals. This difference is pronounced in the frontal and temporal lobes, underscoring the distinct neuronal architectures between the two species. At the single-neuron level, we found that neurons from the human frontal and parietal lobes are six times more separable than those from the same regions in mouse brains. This heightened separability is also observed between the frontal and temporal lobes, as well as between the parietal and temporal lobes in humans. We thoroughly explored the entire morphological feature space, along with its characteristic subspaces, and consistently found this distinct separability. Remarkably, this neuronal separability can be partially recapitulated when examining the global functional states of these brain lobes--using newly acquired Electroencephalography (EEG) and Magnetoencephalography (MEG) signals as physiological measures--as well as their global metabolic states, molecular profiles, and cortical geometry. These findings suggest that our comparative analysis of single-neuron intrinsic features could serve as a valuable foundation for future comprehensive studies of cross-species brain structures and functions.

neuroscience↗

bioRxiv2024

Unlocking expanded flagellin perception through rational receptor engineering

The surface-localized receptor kinase FLS2 detects the flg22 epitope from bacterial flagella. FLS2 is conserved across land plants, but bacterial pathogens exhibit polymorphic flg22 epitopes. Most FLS2 homologs possess narrow perception ranges, but four with expanded perception ranges have been identified. Using diversity analyses, AlphaFold-Multimer modeling, and amino acid properties, key residues enabling expanded recognition were mapped to FLS2s concave surface, interacting with the co-receptor and polymorphic flg22 residues. Synthetic biology enabled engineering of expanded recognition from QvFLS2 (Quercus variabilis) and FLS2XL (Vitis riparia) into homologs with canonical perception. Evolutionary analyses across three plant orders showed residues under positive selection aligning with those binding the co-receptor and flg22s C-terminus, suggesting more alleles with expanded perception exist. Our experimental data enabled the identification of specific receptor amino acid properties and AlphaFold3 metrics that facilitate predicting FLS2-flg22 recognition. This study provides a framework for rational receptor engineering to enhance pathogen restriction.

plant biology↗

bioRxiv2024

m6AConquer: a Data Resource for Unified Quantification and Integration of m6A Detection Techniques

N6-methyladenosine (m6A) is the most prevalent RNA modification in mammalian cells and the most extensively studied epitranscriptomic mark. More than 10 m6A detection techniques have been proposed to measure m6A stoichiometry at either the site or peak level. However, these detection techniques are processed through heterogeneous pipelines, using different computational filters and reference features, leading to difficulties in fully harnessing data integration and analysis across orthogonal m6A detection techniques. Our m6AConquer (Consistent Quantification of External m6A RNA Modification Data) tackles this challenge by establishing a consistent multi-omics data-sharing standard, summarizing quantitative m6A data from 10 detection techniques using a unified reference feature set. Furthermore, we standardize site calling and m6A count matrix normalization procedures across platforms through a computational framework that accounts for over-dispersion in m6A levels. Available m6A detection techniques can be categorized into four types: antibody-assisted, chemical-assisted, enzyme-assisted, and direct-RNA sequencing. We leverage this categorization to develop a reproducibility-based integration framework that enables the reliable detection of high-confidence m6A sites confirmed across orthogonal techniques. Empirical evaluations report that both the site-calling and the integration framework outperform common alternatives, enhancing biological relevance. We apply interpretable machine learning models on our integrated high-confidence sites, and the result consistently identify proximity to intron-exon junctions as the driving predictor of m6A site coordinates across different techniques, demonstrating the high quality of the data curated in m6AConquer. m6AConquer webserver is freely accessible under: http://rnamd.org/m6aconquer. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/612173v1_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@f9d1a8org.highwire.dtl.DTLVardef@1339b41org.highwire.dtl.DTLVardef@115ececorg.highwire.dtl.DTLVardef@7580aa_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Discovery of novel 1,4-dicarbonylthiosemicarbazides as DNA gyrase inhibitors for the treatment of MRSA infection

Antibiotic resistance has become a serious threat to public health, thus novel antibiotics are urgently needed to combat drug-resistant bacteria including MRSA (methicillin-resistant S. aureus). The 1,4-dicarbonylthiosemicarbazide is an interesting chemotype that could exhibit antibacterial activity. However, the currently available compounds are not as potent as clinical antibiotics. Herein, we adopted the computer-aided drug design strategy, substructure search, to retrieve antibacterial 1,4-dicarbonylthiosemicarbazide derivatives, and identified compound B5 (Specs ID: AG-690/15432331) from the Specs chemical library that exhibited moderate activity (minimum inhibitory concentration (MIC): 6.25 {micro}g/mL) against S. aureus (ATCC 29213). Based on that compound, we further designed and synthesized 45 derivatives, and evaluated their antibacterial activity. Eight derivatives were more potent than or equivalent to vancomycin (MIC: 1.56 {micro}g/mL). We compared the three most potent ones for their cytotoxicity to HepG2 and HUVEC cells and selected compound 1b as our lead compound for comprehensive biological evaluation. As a result, compound 1b exhibited a bacteriostatic mode, and was active against a panel of gram-positive bacteria strains, metabolically stable, and effective to protect the mice from MRSA infection. More importantly, we applied 2D similarity calculation and reverse docking to predict potential targets of compound 1b. Through experimental validation and molecular dynamics simulation, we were able to confirm that compound 1b inhibited S. aureus DNA gyrase (IC50: 1.81 {micro}M) and DNA supercoiling, potentially by binding to the ATPase domain, where ASP81, GLU58 and GLN91 formed key hydrogen bonds. Taken together, we have discovered a new class of DNA gyrase inhibitors represented by compound 1b for the treatment of MRSA infection, through the design, synthesis, and biological evaluation of novel 1,4-dicarbonylthiosemicarbazides. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/611349v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@549dadorg.highwire.dtl.DTLVardef@13bff64org.highwire.dtl.DTLVardef@1fc2c00org.highwire.dtl.DTLVardef@acee76_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIAn interesting 1,4-dicarbonylthiosemicarbazide derivative B5 with moderate antibacterial activity for S. aureus was discovered by substructure search. C_LIO_LIBased on B5, 45 new 1,4-dicarbonylthiosemicarbazides were designed, synthesized and biologically evaluated, which led to the discovery of a promising lead compound 1b. C_LIO_LICompound 1b exhibited good antibacterial activity for a panel of gram-positive bacteria strains, and was effective to protect mice from MRSA infection. C_LIO_LIThe 1,4-dicarbonylthiosemicarbazides represented by compound 1b were discovered as a new class of DNA gyrase inhibitors, by target prediction and experimental validation. C_LI

pharmacology and toxicology↗

bioRxiv2024

Deep Generative Optimization of mRNA Codon Sequences for Enhanced Protein Production and Therapeutic Efficacy

Messenger RNA (mRNA) therapeutics show immense promise, but their efficacy is limited by suboptimal protein expression. Here, we present RiboDecode, a deep learning framework that generates mRNA codon sequences for enhanced mRNA translation. RiboDecode introduces several advances, including direct learning from large-scale ribosome profiling data and generative exploration of a large sequence space. In silico analysis demonstrates RiboDecode s robust predictive accuracy for unseen genes and cellular environments. In vitro experiments showed substantial improvements in protein expression, significantly outperforming past methods. In addition, RiboDecode enables mRNA design with consideration of cellular context and demonstrates robust performance across different mRNA formats, including m1{Psi}-modified and circular mRNAs, an important feature for mRNA therapeutics. In vivo mouse studies showed that optimized influenza hemagglutinin mRNAs induce ten times stronger neutralizing antibody responses against influenza virus compared to the unoptimized sequence. In an optic nerve crush model, optimized nerve growth factor mRNAs achieve equivalent neuroprotection of retinal ganglion cells at one-fifth the dose of the unoptimized sequence. Collectively, RiboDecode represents a paradigm shift from rule-based to a data-driven, context-aware approach for mRNA therapeutic applications, enabling the development of more potent and dose-efficient treatments.

bioinformatics↗

bioRxiv2024

Genotype inference from aggregated chromatin accessibility data reveals genetic regulatory mechanisms

BackgroundUnderstanding the genetic causes for variability in chromatin accessibility can shed light on the molecular mechanisms through which genetic variants may affect complex traits. Thousands of ATAC-seq samples have been collected that hold information about chromatin accessibility across diverse cell types and contexts, but most of these are not paired with genetic information and come from diverse distinct projects and laboratories. ResultsWe report here joint genotyping, chromatin accessibility peak calling, and discovery of quantitative trait loci which influence chromatin accessibility (caQTLs), demonstrating the capability of performing caQTL analysis on a large scale in a diverse sample set without pre-existing genotype information. Using 10,293 profiling samples representing 1,454 unique donor individuals across 653 studies from public databases, we catalog 23,381 caQTLs in total. After joint discovery analysis, we cluster samples based on accessible chromatin profiles to identify context-specific caQTLs. We find that caQTLs are strongly enriched for annotations of gene regulatory elements across diverse cell types and tissues and are often strongly linked with genetic variation associated with changes in expression (eQTLs), indicating that caQTLs can mediate genetic effects on gene expression. We demonstrate sharing of causal variants for chromatin accessibility and diverse complex human traits, enabling a more complete picture of the genetic mechanisms underlying complex human phenotypes. ConclusionsOur work provides a proof of principle for caQTL calling from previously ungenotyped samples, and represents one of the largest, most diverse caQTL resources currently available, informing mechanisms of genetic regulation of gene expression and contribution to disease.

genomics↗

bioRxiv2024

Interpretable scRNA-seq Analysis with Intelligent Gene Selection

AO_SCPLOWBSTRACTC_SCPLOWSingle-cell RNA sequencing (scRNA-seq) data analysis faces multiple challenges, including high dimensionality, significant noise, and data loss. To effectively address these issues, we introduce AIGS, a robust and transparent single-cell analysis framework. AIGS utilizes an intelligent gene selection method that systematically identifies the most informative genes for clustering based on the normalized mutual information between pre-learned pseudo-labels and quantified genes. Additionally, AIGS incorporates a scale-invariant distance metric to assess cell-to-cell similarity, enhancing connections between homogenous cells and ensuring more accurate and robust results. Through comprehensive comparisons with state-of-the-art techniques, AIGS demonstrates superior performance in both clustering accuracy and multi-resolution visualization quality. Our in-depth analysis of clustering and visualization results further reveals that AIGS can uncover complex, stage-specific gene expression patterns during the same developmental cell stage.

bioinformatics↗

bioRxiv2024

GageTracker: a tool for dating gene age by micro- and macro-synteny with high speed and accuracy

With the advent of the Earth Genome Project, an increasing number of species' genomes presents exciting opportunities for exploring genetic and phenotypic diversity in organisms. Determining the origin time of genes facilitates the elucidation of crucial genetic mechanisms underlying significant biological evolutionary questions such as the transition from aquatic to terrestrial life, the emergence of mammals, the origin of humans, as well as the development of species- or lineage-specific traits. However, accurately determining the origin time of these genes in species separated by long evolutionary distances remains a major challenge in bioinformatics as these genes often undergo significant changes in their genome sequences, making it difficult to trace them back to their origin. Here, we proposed a new approach for dating gene age based on the micro- and macro-synteny algorithms. This approach employs the parallel computation of orthologous genome alignments across multiple species. Our method was integrated into the GageTracker (Gene Age Tracker) software, providing a fast and accurate way to trace gene age with minimal user input, available at https://github.com/RiversDong/GageTracker. Benchmarked against the simMammals dataset (Alignathon), GageTracker achieved the same high-quality genome alignments as the optimized LastZ aligner, but improved operation speed by 1.4-7 times. In a separate analysis of 12 Drosophila genomes, GageTracker efficiently assessed the ages of 23,720 genes (including ~13,965 protein-coding genes) in just ~22 hours with default parameters. When comparing with the GenTree database (recognized as the most comprehensive and accurate tool for evaluating gene age), GageTracker achieved an impressive ~94.4% accuracy and ~99% macro consistency in assessing the age of protein-coding genes. Moreover, for the ~5.6% conflicting genes, GageTracker displayed slightly higher support rates than GenTree, as evidenced by data from OrthoDB, FlyBase, and Ensembl ortholog databases. Notably, younger genes identified by GageTracker exhibited a preferential expression pattern in the testis, further reinforcing the reliability of GageTracker in accurately tracing gene age.

bioinformatics↗