Biology subjects

Takahashi, H.

Publications and source records attributed to Takahashi, H..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Open-source modular FPGA system for two-photon mesoscope enabling multi-layer, multi-depth neural activity recording and lifetime imaging

Large field-of-view (FOV) two-photon microscopy makes it possible to record a large number of neural activities from multiple brain regions simultaneously. However, the larger the field of view, the longer it takes to scan the entire FOV. To increase imaging speed, we have developed open-source software to digitize analogue signals from a photomultiplier tube using a field-programmable gate array (FPGA) at a rate of 3.2 GS/s. By combining this with a newly developed a circular delay-path module for a custom two-photon mesoscope (Diesel2p), we succeeded in simultaneous recording of >10,000 neurons from the entire bilateral dorsal cortex at up to four depths. We also demonstrated large FOV lifetime imaging using the same system. Our modular, open-source FPGA system can be readily integrated into any type of two-photon microscope and will accelerate the biomedical application of multi-scale two-photon imaging in a wide range of pathophysiological investigations.

neuroscience↗

bioRxiv2025

Functional redundancy between UTY and UTX in regulating the localization of transcription factors involved in pluripotency

The Y chromosome harbors few protein-coding genes, and their roles in early human development remain largely unclear. Here, we demonstrate that UTY, a Y-linked homolog of the histone demethylase UTX, plays a critical, demethylase-independent role in maintaining pluripotency in human embryonic stem cells (hESCs). Despite its low expression and weak enzymatic activity, UTY co-occupies active cis-regulatory elements with UTX and promotes the transcription of key pluripotency genes, including NODAL and LEFTY. Integrated genomic analyses of single and double knockout hESCs reveal that UTY and UTX function redundantly to maintain chromatin accessibility and ensure proper recruitment of core transcription factors such as OCT4 and SOX2. The combined loss of UTY and UTX disrupts transcription factor localization, induces widespread gene expression changes, and leads to a collapse of the pluripotent state, without detectable changes in H3K27 methylation. Instead, these defects are associated with impaired recruitment of ATP-dependent chromatin remodelers and reduced histone acetylation, suggesting a demethylase-independent mechanism. Our findings uncover an essential role for the evolutionarily conserved UTY in safeguarding enhancer function and transcription factor occupancy, highlighting Y-linked regulatory mechanisms that are critical for maintaining human pluripotency. Summary statementThis study reveals how UTX and UTY cooperate to maintain stable gene regulation in human stem cells and guide proper developmental programs.

developmental biology↗

bioRxiv2025

A genome-wide, machine learning-guided exploration of the cis-regulatory code involved in neuronal differentiation

Gene expression is controlled by proximal and distal cis-regulatory elements (CREs), containing DNA motifs bound by various transcription factors (TFs). Other sequence features, such as specific k-mers or low complexity regions, have also been implicated [1-3]. However, in a dynamic biological process such as cell differentiation, we lack an understanding of how the transcriptional activity of CREs progressively change and what sequence features underlie these transitions, which may reflect common and/or coordinated regulatory processes. Here, we use single-cell ATAC-seq and RNA-seq to follow, at a genome scale, CREs along differentiation of induced pluripotent stem cells into cortical neurons and develop a method to automatically identify the diversity of CRE profiles and their underlying sequence features. We propose a machine-learning guided clustering algorithm, STOIC (Statistical learning TO Inform Clustering), that jointly learns an unsupervised clustering of the CREs in the space of the activity profiles and a supervised predictor associated with each cluster in the DNA-sequence space. STOIC is specifically designed to provide readily interpretable results. We show that the method identifies CRE profiles associated with highly predictive sequence features and outperforms methods solely concerned with co-activity clustering on this task. Orthogonal data collected in the same settings link the inferred CRE clusters to specific enhancer or promoter signatures. Furthermore, we show that the DNA features unveiled by STOIC reflect biologically relevant regulators and offer a valuable basis to dissect elements of the cisregulatory grammar. Finally, we demonstrate the general applicability of STOIC by analyzing five bulk CAGE datasets of human cells responding to various treatments.

bioinformatics↗

bioRxiv2025

Unsupervised feature computation-based feature selection robustly extracted resting-state functional connectivity patterns related to mental disorders

Research on biomarkers for predicting psychiatric disorders from resting-state functional connectivity (FC) is advancing. While the focus has primarily been on the discriminative performance of biomarkers by machine learning, identification of abnormal FCs in psychiatric disorders has often been treated as a secondary goal. However, it is crucial to investigate the effect size and robustness of the selected FCs because they can be used as potential targets of neurofeedback training or transcranial magnetic stimulation therapy. Here, we incorporated approximately 5,000 runs of resting-state functional magnetic resonance imaging from six datasets, including individuals with three different psychiatric disorders (major depressive disorder [MDD], schizophrenia [SCZ], and autism spectrum disorder [ASD]). We demonstrated that an unsupervised feature-computation-based feature selection method can robustly extract FCs related to psychiatric disorders compared to other conventional supervised feature selection methods. We found that our proposed method robustly extracted FCs with larger effect sizes from the validation dataset compared to different types of feature selection methods based on supervised learning for MDD (Cohens d = 0.40 vs. 0.25), SCZ (0.37 vs. 0.28), and ASD (0.17 vs. 0.16). We found 78, 69, and 81 essential FCs for MDD, SCZ, and ASD, respectively, and these FCs were mainly thalamic and motor network FCs. The current study showed that the unsupervised feature-computation-based feature selection method robustly identified abnormal FCs in psychiatric disorders consistently across datasets. The discovery of such robust FCs will contribute to understanding neural mechanisms as abnormal brain signatures in psychiatric disorders. Furthermore, this finding can aid in developing precise therapeutic interventions, such as neurofeedback training or transcranial magnetic stimulation therapy.

neuroscience↗

bioRxiv2025

Harmonizing Inter-Site Differences in T1-Weighted Images Using CycleGAN

IntroductionWhen neuroimaging studies using magnetic resonance imaging (MRI) are conducted across multiple centers, they often encounter inter-site differences in MRI equipment and protocols leading to biases and confounding effects in MRI measurements. There are existing techniques for correcting these site effects, i.e., harmonization, but they have limitations, including the need for preprocessing of MRI data, which involves processes such as spatial normalization. Deep learning-based methods have emerged as potential alternatives that can handle site effects without the need for preprocessing steps. In this study, we propose a novel method based on the generative adversarial network (GAN) framework, CycleGAN, that effectively addresses inter-site differences in T1-weighted images with minimal preprocessing requirements. We compare the harmonization efficacy of CycleGAN with that of the commonly used method ComBat. MethodsWe trained the proposed CycleGAN method and the comparative ComBat method using data from 40 subjects at each of two sites. To evaluate the effectiveness of the two methods, we used data from nine subjects who underwent imaging at both sites. We assessed harmonization performance at the image level using the structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR). Additionally, we evaluated harmonization results at the feature level by analyzing regional cortical thickness and volume data. Cohens d was employed to quantify the differences between feature values. ResultsAt the image level, the ComBat method decreased the median baseline SSIM value from 0.86 (interquartile range [IQR], 0.02) to 0.84 (IQR, 0.02), whereas the proposed CycleGAN method maintained the SSIM value at 0.86 (IQR, 0.02). For PSNR, the baseline value was 18.33 (IQR, 1.78), which decreased to 15.30 (IQR, 2.20) after applying ComBat, but increased to 19.58 (IQR, 3.12) with the proposed CycleGAN method. These findings indicate that CycleGAN preserved the structural and signal similarity of the images. At the feature level, the effect size for cortical thickness decreased from 0.97 (IQR, 1.79) to 0.91 (IQR, 1.54) after applying ComBat, whereas the proposed CycleGAN method yielded an effect size of 1.05 (IQR, 1.14). For cortical volume, the effect size decreased from 0.95 (IQR, 1.78) to 0.69 (IQR, 1.00) after applying ComBat, and decreased to 0.88 (IQR, 0.74) with the CycleGAN method. Compared with baseline, Cohens d was significantly lower with both ComBat (p = 0.000002) and CycleGAN (p = 0.028) with no significant difference between the two methods, indicating similar performance of the two methods under the study conditions. ConclusionThe results underscore the ability of CycleGAN to harmonize data without explicit normalization and emphasize the potential impact of the normalization process on harmonization procedures. Our findings suggest that CycleGAN holds promise as a harmonization technique in multi-site neuroimaging studies.

neuroscience↗

bioRxiv2025

Apusomonad rhodopsins, a new family of ultraviolet to blue light absorbing rhodopsin channels

Apusomonads are a clade of understudied sediment-dwelling bacterivorous protists sister to Opisthokonta. Recently, apusomonads have been found to show a negative phototactic response to blue light. Here, by screening available apusomonad omics data we found genes of a distinct group of microbial rhodopsins, the ApuRs. ApuRs heterologously expressed in mammalian cells absorbed near-UV/violet or blue light, suggesting that ApuRs could be involved in apusomonads photoavoidance response. Electrophysiological measurements indicate that ApuRs are anion-selective rhodopsin channels which evolved independently of the family of channelrhodopsins widespread in other unicellular eukaryotes. Among the known rhodopsin channels, ApuRs collectively demonstrate the most blue-shifted absorption spectra. In ApuRs, the channel opening is triggered by photoisomerization of the retinal from its all-trans form to 13-cis and 11-cis forms. We found that intracellular proton transfer is involved in channel opening and determined the channels open/close kinetics. These findings expand our understanding of the photobiology of heterotrophic flagellates and showcase the significance of these organisms as a source of new rhodopsin families with unanticipated functions.

biophysics↗

bioRxiv2025

Integration of Proxy Intermediate Omics traits into a Nonlinear Two-Step model for accurate phenotypic prediction

Intermediate omics traits, which mediate the effects of genetic variation on phenotypic traits, are increasingly recognised as valuable components of genetic evaluation. In particular, rhizosphere microbiota play a crucial role in plant health and productivity; however, their complex interactions with host genetics remain challenging to model. Although two-step modeling frameworks have been proposed to integrate intermediate omics traits into phenotype prediction, existing approaches do not incorporate nonlinear relationships between different omics layers. To address this, we have proposed a two-step phenotype prediction framework that integrates genomic, rhizosphere microbiome, and metabolome (meta-metabolome) data, while explicitly capturing omicsomics nonlinearities. The first step is to predict meta-metabolome traits from genetic and microbial features, thus effectively isolating them from the environmental noise. In this process, intermediate "proxy" omics traits are generated as general biological information to provide robust models. The second step utilises this "proxy" to enhance the accuracy of the phenotype prediction. We compared the linear model (Best Linear Unbiased Prediction, BLUP) and the nonlinear model (Random Forest, RF) at each step, as demonstrated through simulations and empirical analysis of a multi-omics soybean dataset in which nonlinear modeling captures intricate omics interactions. Notably, our approach enables phenotype prediction without requiring the original meta-metabolome data used in model training, thereby reducing reliance on costly omics measurements. This framework integrates intermediate omics traits into genomic prediction to improve prediction accuracy and provide solutions for deeper insights into plant-microbiome interactions.

bioinformatics↗

bioRxiv2025

Cell type-specific intronic RNAs shape genome architecture during neuronal lineage specification

Cell differentiation towards neurons is accompanied by widespread changes in three-dimensional (3D) genome organization and gene expression. Chromatin-associated RNAs have been proposed to be important regulators of such changes; however, the type, abundance, and role of these RNAs during neuronal differentiation remain largely unexplored. Here, we integrate multi-omic data generated in the frame of the Functional ANnoTation Of the Mammalian genome (FANTOM6) to chart 3D genome, RNA-DNA contactome, and transcriptome changes occurring during in vitro differentiation of human induced pluripotent stem cells to neural stem cells and neurons. We reveal a previously unreported phenomenon, in which intronic RNAs engage in long-distance contacts with DNA loci distributed all over the genome. These trans-contacting intronic RNAs (TIRs) are produced from exceptionally long (mean length: 750 kilobases, kb) protein-coding genes that carry ultra-long introns and are selectively expressed in neurons. We show that TIRs do not undergo rapid co-transcriptional degradation but rather accumulate in the nucleus of neuronal cells, forming large dot clouds around their source loci and spreading across the nucleus, as visualized by single-molecule RNA fluorescence in situ hybridization. TIRs engage in contacts with a set of genomic regions (TIR-contacted regions or TIRCs) that carry much shorter (mean length: [~]30 kb) neuronally expressed genes forming high-connectivity hubs. We also show that the expression of genes within TIRCs contacted by the same set of TIRs is highly co-varied, and that TIR source genes, especially their introns, are enriched in genetic risk loci for neurodevelopmental and neuropsychiatric disorders. Our findings point to a functional role of the persistence of long intronic RNAs in the nucleus of neuronal cells and might contribute to explain why neurons uniquely express many ultra-long genes. We propose a model in which TIRs form pan-nuclear scaffolds--which we propose to name introsomes--that constitute a dynamically self-renewing regulatory layer, where transcription itself continuously regenerates the very scaffold that organizes genome function in neurons, and that might be involved in the pathogenesis of neurodevelopmental and neuropsychiatric disorders.

genomics↗

bioRxiv2025

Rare missense variants of the leukocyte common antigen related receptor (LAR) display reduced activity in transcellular adhesion and synapse formation

The leukocyte common antigen related receptor (LAR) is a member of the LAR receptor protein tyrosine phosphatase (RPTP) family of synaptic adhesion molecules that contribute to the proper alignment and specialization of synaptic connections in the mammalian brain. LAR-RPTP members have been genetically associated with neuropsychiatric disorders, but the molecular consequences of genetic perturbations of LAR remain unstudied. Using exome sequencing data from psychiatric patients and controls, we identify rare missense variants of LAR that render the extracellular domain (ECD) unstable and susceptible to proteolytic cleavage. Using recombinant and cellular systems, we describe three variants that cause disruption of the LAR:NGL-3 interaction, which results in loss of transcellular adhesion and synaptogenic effects. Furthermore, we show that overexpression of two of these variants elicit altered morphological phenotypes in an imaging-based morphological profiling assay compared to wild type LAR, suggesting that destabilization of the LAR ECD has broad effects on LAR function. In conclusion, our study identifies three rare, missense variants in LAR that could provide insights into LAR involvement with psychiatric pathobiology.

neuroscience↗

bioRxiv2025

Vagus nerve stimulation modulates information representation of sustained activity in layer specific manner in the rat auditory cortex

The brain of a living organism enables stable information processing in response to constantly changing external environments and internal states. As one of such cortical modulation, the present study focused on the effect of vagus nerve stimulation (VNS) therapy on information representation of the auditory cortex. By quantifying sound representation using machine learning, we investigated whether VNS alters cortical information representation in a layer-specific and frequency band-specific manner. A microelectrode array meticulously mapped the band-specific power and phase-locking value of sustained activities in every layer of the rat auditory cortex. Sparse logistic regression was used to decode the test frequency from these neural characteristics. The comparison of decoding accuracy before and after the application of VNS indicated that sound representation of the high-gamma band activity was impaired in the deeper layers, i.e., layers 5 and 6, while it was slightly improved in the superficial layers, i.e., layers 2, 3, and 4. Moreover, there was an improvement of sound representation in theta band activity in the deeper layers, demonstrating the layer-specific and frequency band-specific effect of VNS. Given that the cortical laminar structure and oscillatory activity in multiple frequency bands helps the auditory cortex to act as a hub for feed-forward and feed-back pathways in various information processing, the current findings support the possibility that VNS provide complex effects on brain function by altering the balance of cortical activity between layers and frequency bands.

neuroscience↗

bioRxiv2025

A single dimer of the SARS-CoV-2 N protein can associate with multiple fragments of single-stranded and stem-loop RNAs

The nucleocapsid (N) protein of SARS-CoV-2 associates with the viral genomic RNA (gRNA) and forms the ribonucleoprotein (RNP) granules. However, the detailed molecular structures of RNP and their formation mechanism are largely unknown. We used circular dichroism (CD) spectroscopy, fluorescence correlation spectroscopy (FCS) and single-molecule Forster resonance energy transfer (sm-FRET) spectroscopy to understand the interaction between the N protein and different structural units of RNA. We chose polyadenylate chains with 40, 30 and 20 bases possessing a single-stranded structure and three stem loops with 50, 41 and 29 bases selected from gRNA, and labeled their 5 and 3 ends by Alexa488 and Alexa647, respectively, for the FCS and sm-FRET measurements. We found that the N protein started to bind to the single-stranded RNAs at the concentrations between 10 and 100 nM. The binding of the N protein to one of the stem loops occurred at the concentration less than 10 nM without melting the stem loop. For all the samples, the binding of multiple molecules of the RNA fragments to a single dimer of the N protein was observed. These results demonstrate that the N protein acts as a non-specific binder to both single-stranded and stem-loop structures of RNA, and that the N protein might contract a long RNA chain by bridging its multiple segments. We propose that the RNP granules might be folded by the association of the numerous stem loops of gRNA triggered by the assembly of the N protein.

biophysics↗

bioRxiv2025

Self-organization of high-dimensional geometry of neural activity in culture

A vast number of neurons exhibit high-dimensional coordination for brain computation, both in processing sensory input and in generating spontaneous activity without external stimuli. Recent advancements in large-scale recordings have revealed that this high-dimensional population activity exhibits a scale-free structure, characterized by power law and distinct spatial patterns in principal components (PCs). However, the mechanisms underlying the formation of this high-dimensional neural coordination remain poorly understood. Specifically, it is unclear whether the characteristic high-dimensional structure of population activity emerges through self-organization or is shaped by the learning of sensory stimuli in animals. To address this question and clearly differentiate between these two possibilities, we investigated large-scale neural activity in dissociated neuronal culture using high-density multi-electrode arrays. Our findings demonstrate that the high-dimensional structure of neural activity self-organizes during network development in the absence of explicit sensory stimuli provided to animals. As the cultures mature, the PC variance exhibits a power-law decay, and the spatial structures of PCs transition from global to localized patterns, driven by the temporal correlations of neural activity. Furthermore, we observed an unexpected co-occurrence between the power-law decay in PCA and neuronal avalanches, suggesting a link between self-organized criticality and high-dimensional activity. To uncover the mechanism behind this co-occurrence, we developed a new theoretical framework and demonstrated that it arises from heavy-tailed synaptic connectivity. By highlighting a developmental origin of the high-dimensional structure of neural activity, these findings deepen our understanding of how coordinated neural computations are achieved in the brain. SignificanceOne of the most intriguing questions in neuroscience is how the extremely high-dimensional yet efficiently orchestrated coordination of neural activity is organized. Central to this question lies the "nature versus nurture" debate: Is the high-dimensional coordination self-organized during development, or is it acquired through learning in animals? We take a novel approach by applying cutting-edge analytical techniques to study high-dimensional neural activity in dissociated neuronal cultures. Our findings reveal that fundamental features characterizing the high-dimensional coordination of neurons, including the scale-free geometry of the neural manifold and the intrinsic spatial structure of neural dynamics, are self-organized without sensory stimuli. Remarkably, we also discover that this high-dimensional geometry emerges concurrently with neuronal avalanches, a hallmark of self-organized criticality in neural circuits.

neuroscience↗

bioRxiv2024

Discovery of allodiploid hybrid species Aspergillus latus in Japan

Allodiploid hybrid species, Aspergillus latus, belonging to section Nidulantes, is a hybrid of A. spinulosporus and unknown species closely related to A. quadrilineatus and A. subltus. This hybrid has often been misidentified as the species in section Nidulantes, such as A. nidulans, A. spinulosporus, A. sublatus, or other cryptic species. A. latus has not been reported in Japan as well as Asia so far. In this study, we screened 23 clinical strains identified as A. spinulosporus isolated in Japan from 2012 to 2023 and found seven A. latus strains. To characterize the A. latus strains, we conducted comprehensive phenotyping including morphological observation, whole genome sequences and phylogenetic analysis based on calmodulin (CaM) gene. In addition, we conducted antifungal susceptibility testing for A. latus strains. As a result, the morphological characters of A. latus were more similar to those of A. spinulosporus compared to A. sublatus. However, the ascospore of A. latus differed from that of A. spinulosporus. A. latus phylogenetically clustered with A. spinulosporus and A. sublatus. Furthermore, A. latus strains showed reduced susceptibility to caspofungin and amphotericin B compared to A. spinulosporus, while they were susceptible to azoles. Our results suggest that A. latus has been a causative pathogen of aspergillosis in Japan since 2013.

microbiology↗

bioRxiv2024

Dual fragmentation via collision-induced and oxygen attachment dissociations using water and its radicals for C=C position-resolved lipidomics

Oxygen attachment dissociation (OAD) is a tandem mass spectrometry (MS/MS) technique used to annotate the positions of double bonds (C=C) in complex lipids. Although OAD has been used for untargeted lipidomics, its availability has been limited to the positive-ion mode, requiring the independent use of a collision-induced dissociation (CID) method. In this study, we demonstrated the OAD-MS/MS technique in the negative-ion mode for profiling phosphatidylserines, phosphatidylglycerols, phosphatidylinositols, and sulfatides, where the fragmentation mechanism remained consistent with that in the positive-ion mode. Furthermore, we proposed optimal conditions for the simultaneous acquisition of CID- and OAD-specific fragment ions, termed OAciD. In the collision cell for OAD, oxygen atoms and hydroxy radicals facilitate C=C position-specific fragmentation, while residual water vapor induces cleavage of low-energy covalent bonds, such as ester and peptide bonds, at higher collision energy values, preserving OAD-specific ions under high collision energy conditions. Finally, theoretical fragment ions were implemented in MS-DIAL 5 to accelerate C=C position-resolved untargeted lipidomics. The OAciD methodology was applied to lipid profiling of five marmoset brain regions: the frontal lobe, hippocampus, midbrain, cerebellum, and medulla. Region-specific marmoset lipidomes were characterized with C=C positional information, where the ratios of C=C positional isomers such as delta 9- and delta 11 of fatty acid 18:1 in phosphatidylcholine were also estimated using OAciD-MS/MS. In addition, we characterized the profiles of polyunsaturated fatty acid-containing complex lipids with C=C positional information, where lipids containing omega-3 fatty acids were enriched in the cerebellum, while those containing omega-6 fatty acids were more abundant in the hippocampus and frontal lobe.

bioengineering↗

bioRxiv2024

CFC-seq: identification of full-length capped RNAs unveil enhancer-derived transcription

Long-read sequencing has transformed transcriptome profiling, yet capturing full-length, non-polyadenylated transcripts like enhancer RNAs (eRNAs) remains challenging. Here, we introduce CFC-seq, combining cap-trapping and in vitro poly(A)-tailing to sequence poly(A) and non-poly(A) RNAs with precise transcription start site. Paired with our assembler, SALA, we identified 39,425 novel transcriptional units, including [~]24,000 eRNAs. Our data reveal a distinct genomic code governing eRNA fate dictated by core promoter architecture. CpG-island enhancers show high chromatin connectivity but yield short, exosome-sensitive RNAs. Conversely, TATA-box enhancers systematically co-opt LTR retrotransposons to inherit structural motifs that produce long, stable, and spliced RNAs. Mechanistically, the pioneer factor NF-Y activates these viral elements to license transcription, balanced by TEAD4 activity across a dual-gear regulatory axis. Finally, non-poly(A) eRNAs terminate via exosome-associated processing at structural-depleted cleavage zones. This comprehensive annotation links enhancer sequence architecture to RNA fate, providing a new transformative framework for decoding the functional human genome. HighlightsO_LIExpanded genomic architecture: CFC-seq unmasks a hidden layer of human transcriptome, identifying 39,425 novel transcriptional units with high-confidence TSS support, including [~]24,000 eRNAs. C_LIO_LITSS-first assembler: We introduce SALA, a specialized long-read assembler that prioritizes authentic 5 Cap-trapped ends to accurately reconstruct the TSS-resolved transcript models. C_LIO_LIGenomic code of eRNA fate: CGI enhancers drive short and exosome-sensitive transcripts associated with repressive H3K27me3 mark and high chromatin connectivity. TATA-box enhancers produce cell-type-specific, long, stable, and frequently spliced eRNAs. C_LIO_LIEvolutionary co-option of retrotransposons: A major fraction of TATA-box eRNAs originate from LTR retrotransposons, providing a direct mechanism for integration of viral elements into the human regulatory landscape. C_LIO_LIA dual-gear pioneering axis: The pioneer factor NF-Y activates unprimed LTR-TATA enhancers to license transcription independent of histone acetylation cascades, operating in parallel with TEAD4-mediated activation. C_LIO_LIStructural determinants of eRNA termination: Non-poly(A) eRNA TES features a secondary structure depletion zone that coordinates pol II termination and calibrates exosome-mediated turnover. C_LI

genomics↗

bioRxiv2024

Global identification of AGO3-RNA interactions in Chlamydomonas reveals the small RNA-mediated regulation of nuclear and chloroplast gene expression

MicroRNAs (miRNAs) form complexes with Argonaute (AGO) proteins and bind to mRNAs with complementary sequences to repress their expression. Organisms typically possess several hundred miRNAs regulating diverse biological processes. Although the roles of miRNAs have been well elucidated in multicellular organisms, they remain largely unexplored in unicellular organisms. In the green alga Chlamydomonas reinhardtii, the first unicellular organism in which miRNAs were discovered, identifying miRNA target genes remains challenging. Here, we report the high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP) to generate global AGO3-RNA interaction maps, identifying 131 mRNAs derived from nuclear genes. We also detected mRNAs from two chloroplast genes, suggesting that AGO3 may also influence chloroplast gene expression. Our findings indicate that Chlamydomonas small RNAs repress nuclear and chloroplast gene expression. Furthermore, HITS-CLIP analyses are now feasible for any RNA-binding protein in Chlamydomonas, offering new opportunities to uncover the functions of RNA-binding proteins of interest.

plant biology↗

bioRxiv2024

Superiority illusion in older adults: volume and functional connectivity of the precuneus

AimPositive thinking, which has been known to extend the lifespan, tends to increase with age. One specific form of positive thinking, the superiority illusion (SI), involves the belief that one is better than others. Despite its potential benefits in aging, the neural basis of the SI in elderly populations remains underexplored. MethodsThis study combined a behavioral task, voxel-based morphometry (VBM), and resting-state functional connectivity (rsFC) analyses to investigate the neural substrates of the SI in a cohort of 100 participants, including young (N = 33), middle-aged (N = 33), and older adults (N = 34). ResultsOur findings indicated that higher SI scores in older adults were correlated with greater gray matter volume in the right precuneus and stronger rsFC between the right precuneus and the left lateral occipital cortex. However, these correlations were not evident in younger and middle-aged groups. ConclusionsOur findings underscore the importance of the right precuneus and its connectivity in the manifestation of the SI, particularly in older adults, highlighting its potential role in adaptive aging processes.

neuroscience↗

bioRxiv2024

Omission-responsive neurons encode negative prediction error and probability in the auditory cortex

Predictive coding posits the brain predicts incoming sensory information and signals prediction errors when actual input differs from expectations. Positive prediction errors occur when input exceeds predictions, while negative prediction errors arise when input falls short. Specific neurons are theorized to encode negative prediction errors, linked to responses to omitted expected inputs. However, the information encoded in omission responses remains unclear. We recorded single-unit activity in rat auditory cortex during an omission paradigm with varying tone probabilities. We identified neurons selectively responding to omissions, with responses increasing with evidence accumulation and correlating with tone predictability--key characteristics of negative prediction-error neurons. Interestingly, these neurons showed selective omission responses but broad tone responses, revealing an asymmetry in error signaling. We propose a circuit model with laterally interconnected prediction-error neurons reproducing this asymmetry. Our model demonstrates that lateral connections enhance precision and efficiency of prediction encoding, supported by the free energy principle.

neuroscience↗