Biology subjects

Yao, D.

Publications and source records attributed to Yao, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Photo-thermal Bidirectional Coupling Model for Transcranial Photobiomodulation

BackgroundAccurate optical-field simulation is critical for precise dosage delivery in transcranial photobiomodulation (tPBM). Current simulations neglect photon absorption-induced tissue heating which leads to temperature-dependent alterations of the optical field, thus fails to account for the bidirectional photo-thermal coupling effect. ObjectiveThis paper aims to establish a dynamic photo-thermal couple model that rigorously quantifies the bidirectional interaction between tissue heating and light propagation, and improves the optical dose prediction. ModelWe propose a Photo-Thermal bidirectional coupling Model (PTM). First, the Pennes Bioheat Equation (PBE) is employed to model the thermal response induced by photon absorption. Second, a Real-time temperature-dependent Absorption coefficient Model (RAM) is newly developed to quantify the thermal effect. Third, the PBE and RAM are integrated into the photon diffusion equation, forming the PTM. Finally, this coupled framework is solved temporally by an unconditionally stable Crank-Nicolson scheme. SimulationsBenchmarking against an analytical solution (two-layer cylindrical domain) demonstrates that PTM reduces the temperature prediction error by over 2.35% compared to the uncoupled baseline. Simulations using a realistic head model reveal that, compared to PTM, uncoupled modeling underestimates energy deposition by 150 J/m3 and overestimates photon fluence by 3 J/m2 within just one minute, and such discrepancies will be amplified with increasing exposure duration and power. Furthermore, the PTM identifies a 1.43-mm advantage in penetration depth for pulsed-wave over continuous-wave modality under iso-energy conditions, a key insight enabled by the coupled modeling approach. ConclusionThe PTM provides a high-fidelity simulation framework that captures the dynamic, bidirectional photo-thermal coupling in tPBM, explicitly quantifying the thermal feedback ignored by current models and thereby enabling more reliable treatment optimization and safer clinical translation.

neuroscience↗

bioRxiv2026

Structural basis of substrate recognition and allosteric inhibition in human B0AT2

The SLC6 family is a major target for neuropsychiatric therapeutics. Human B0AT2 (SLC6A15) regulates amino acid homeostasis and glutamatergic transmission and is linked to major depressive disorder, yet its transport and inhibition mechanisms remain unclear. Here we report cryo-EM structures of B0AT2 in apo state and in complex with substrates (proline, leucine, methionine) and inhibitors (loratadine, tiagabine), capturing outward-open, early substrate-bound intermediate, outward-occluded, and inward-open conformations along the transport cycle. These structures reveal an early substrate-sensing mechanism at the substrate-binding pocket (S1), where a substrate-dependent rotameric switch of Phe308 remodels pocket geometry to tune substrate accommodation and selectivity. Loratadine stabilizes an outward-occluded state via allosteric inhibition at the extracellular S2 pocket, whereas tiagabine stabilizes the inward-open state through cooperative multi-site inhibition involving S1 and two previously unrecognized intracellular cavities (S3 and S4). Together with functional assays, these data define the molecular basis of B0AT2 substrate selectivity and state-dependent inhibition. Notably, the two intracellular cavities are conserved across SLC6 transporters, reflecting a shared intracellular vestibular architecture and enabling rational design of conformation-selective modulators for neuropsychiatric disorders.

biophysics↗

bioRxiv2026

An EEG-fMRI Jointly Constrained Digital Twin Brain and Its Application in Alzheime's Disease

Current digital twin brain (DTB) models are typically optimized using single-modality functional neuroimaging data, which restricts their ability to simulate brain dynamics across multiple spatiotemporal scales. Here, we bridged this gap by developing a two-stage DTB (TS-DTB) modeling framework jointly constrained by functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data. Validation in both the healthy young and Alzheimers disease (AD) cohorts demonstrated that the TS-DTB model simultaneously captures subject-specific features of multi-scale brain dynamics. In particular, the TS-DTB models of AD patients successfully recapitulated spectral-temporal signatures of cognitive decline, mechanistically linking these deficits to excitation-inhibition (E-I) imbalances. By simulating responses to repetitive transcranial magnetic stimulation (rTMS), we further revealed that cognitive recovery in AD patients can be driven by E-I rebalancing via synaptic reconfiguration and background suppression. Overall, these findings underscore the potential of the TS-DTB to advance the mechanistic understanding of the brain and inform personalized digital therapeutics.

neuroscience↗

bioRxiv2026

Tract-explainable and underexplained synchrony play complementary roles in the functional organization of the brain

Macroscale functional connectivity emerges from a complex interplay between structural wiring and non-tract-mediated mechanisms. However, the intrinsic entanglement of these contributions obscures their specific roles in brain organization. Here, we introduce a computational modeling framework to disentangle functional synchrony into two fundamentally distinct components: tract-explainable and tract-underexplained synchrony. Validated across two large-scale human cohorts (n = 1214) and an independent marmoset dataset (n = 24), this dissociation reveals an evolutionarily conserved architectural principle. We show that tract-explainable synchrony aligns closely with structural connectomes to facilitate global integration. Conversely, tract-underexplained synchrony drives local modularity and is anchored by multiscale cortical similarity, encompassing microstructural, receptor, and transcriptomic profiles. Crucially, these components gradually dissociate from sensori-motor to higher-order association cortices, with the importance of tract-underexplained synchrony progressively increasing. Furthermore, the tract-underexplained synchrony exhibits greater individual variability and demonstrates a stronger association with individual cognitive performance. Ultimately, tract-based and non-tract-mediated mechanisms serve distinct yet complementary roles, jointly shaping a functional organization that balances conserved macroscopic stability with higher-order cognitive flexibility.

neuroscience↗

bioRxiv2026

Characterizing the metabolomes of microglia, astrocytes, and neurons in aging and Alzheimer's brains

Neurons and glia are distinct in their morphology, development, and function, possessing unique transcriptomes and proteomes, but little is known about their metabolomes. The challenge of brain cell metabolic profiling is to obtain a large number of cells for reliable analysis. Here, we purified microglia, astrocytes, and neurons from mouse brains, identifying >70 metabolites through targeted metabolomics and 9,854 metabolite features via untargeted metabolomics. We systematically characterized cell type-enriched metabolites and metabolic pathways, revealing an enrichment of glutathione (GSH) and polyamine metabolism in microglia. This enrichment was validated in vivo and showed significant decreases with aging and in an Alzheimers disease (AD) model. Notably, GSH and polyamine metabolism correlated strongly with chemokine-related gene expression. Disrupting the GSH pathway in microglia resulted in downregulation of chemokine-related genes, aberrant morphogenesis, and {beta}-amyloid deposition. Our results provide a valuable resource (https://metabolismocean.org/braincell) for metabolic studies related to aging, AD, and other neurological diseases.

neuroscience↗

bioRxiv2026

Shared and distinct default mode systems in mental time travel and affective experience over time

Overarching conceptualizations propose a critical role of the default mode network (DMN) in self-referential mental time travel, particularly in autobiographical memory retrieval and episodic future thinking, and internal (intrinsic) emotion generation and regulation. However, these conceptualizations have not been directly evaluated. Against this background, the present fMRI study aimed to identify both shared and distinct neural systems underlying autobiographical episodic processing across different temporal contexts - specifically, episodic memory retrieval (EMR) and episodic future thinking (EFT) - and to examine how these systems interact with affective experiences, including valence and arousal. Our findings demonstrated the central role of the DMN - encompassing the medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), and medial temporal lobe (MTL) - in both EMR and EFT. Importantly, we identified a functional dissociation along both valence and temporal dimensions: the ventromedial prefrontal cortex (vmPFC) was more strongly associated with positive experiences and simulations, whereas the dorsomedial prefrontal cortex (dmPFC) was consistently engaged during the processing of negative affect across past and future contexts. Moreover, representational similarity and parametric analyses indicated that the hippocampus supports differential processing of valence and arousal across temporal domains. Together, these findings provide empirical evidence for the involvement of cortical midline core DMN systems in autobiographical processing across time and suggest overlapping and distinct systems for the integration of emotional experiences across mental time travel.

neuroscience↗

bioRxiv2025

Real-time functional connectivity-based neurofeedback of the DLPFC-amygdala pathway during threat-exposure attenuates anxiety

BackgroundAdaptive regulation of negative emotion is vital for mental health and dysregulations in this domain contribute to the major mental disorders, including anxiety and depression. On the neural level, efficient emotion regulation has been linked to functional communication between the dorsolateral prefrontal cortex (DLPFC) and the amygdala. Gaining voluntary control over this pathway may present an effective strategy for potentiating emotion regulation. ObjectiveAgainst this background, we developed a novel connectivity-based real-time fMRI (rt-fMRI) neurofeedback (NF) training that enables individuals to gain volitional control over the DLPFC-amygdala pathway during exposure to threatening stimuli. MethodsThe study employed a pre-registered, randomized, sham-controlled design with the experimental group (n = 22) receiving real-time NF information on connectivity between the right DLPFC and the amygdala during threat exposure and the sham control group (n = 23) receiving connectivity NF from a circuit not related to emotion regulation. The ability to maintain regulatory control in the absence of feedback was assessed after four NF runs. Primary outcomes included functional connectivity of the target pathway, as well as anxiety scores. ResultsThe results demonstrate that successful acquisition of self-regulation of the rDLPFC-amygdala top-down regulatory circuit in the experimental NF group facilitated attenuation of anxiety. ConclusionIn summary, our findings suggest that real-time fMRI neurofeedback (rtfMRI-NF) allows to volitionally enhance rDLPFC-amygdala connectivity, and in turn reduces negative emotional states, rendering the training a promising neurotechnology intervention for mental disorders.

neuroscience↗

bioRxiv2025

An image-based CRISPR screen reveals splicing-mediated control of HP1α condensates

Heterochromatin Protein 1 (HP1) is a fundamental component of constitutive heterochromatin, forming subnuclear condensates whose regulation and function remain poorly understood. Here, we present an image-based CRISPR screen targeting nuclear factors that identifies splicing as a pivotal pathway regulating HP1 condensates. We discovered that unspliced intronic RNA modulates HP1 condensates by interacting co-transcriptionally with HP1. By modulating the intron content, RNA processing restricts HP1-RNA interactions at chromatin, thus enabling heterochromatin organization. Disruption of HP1 condensates due to enhanced interactions with unspliced RNA leads to loss of heterochromatin and the activation of stress response protective genes. We propose that RNA is a central component of heterochromatin that modulates HP1 condensates, and that RNA processing enzymes act as a surveillance mechanism for condensates by dynamically regulating the network of multi-valent interactions between RNA and chromatin factors. This model underscores the crosstalk between chromatin organization, transcription, and RNA processing, potentially governing broader nuclear functions.

genetics↗

bioRxiv2025

Disgust propensity, not disgust sensitivity, shapes the reactivity of a subjective disgust circuit in humans

Disgust constitutes an evolutionary adaptive defensive-avoidance response, yet humans vary markedly in their dispositional tendency to experience disgust (disgust propensity) and in their negative appraisal of such experience (disgust sensitivity). Conceptual frameworks and neuroimaging studies suggest that these traits may differentially modulate neural responses to disgust-eliciting stimuli; however, methodological constraints have left their precise roles unresolved. Our comparably large fMRI study (n = 142) therefore aimed to systematically determine how trait disgust modulates neural responses to carefully selected and validated disgust-specific visual stimuli across varying levels of subjective disgust experience. The whole-brain voxel-wise regression analyses revealed a neural dissociation between the two disgust traits, with disgust propensity, but not disgust sensitivity, modulating disgust-related neural activity in the anterior, middle, and posterior insula, as well as the caudate, putamen, thalamus, hippocampus, and parahippocampal gyrus. Mediation and network-level analyses further supported this dissociation by showing that disgust propensity shapes disgust experience via insula - striatal - hippocampal pathways. Together, these findings provide evidence for a neurofunctional dissociation of disgust propensity and sensitivity and elucidate how trait disgust shapes subjective experiences. They further suggest that disgust propensity and the identified systems may represent promising targets for the regulation of disgust-related pathology.

neuroscience↗

bioRxiv2024

Rational molecular design for improved ZHD101 thermal stability based on the introduction of disulfide bonds at the dimer interface and B-factor analysis

AbstractZearalenone hydrolase 101 (ZHD101), derived from Clonostachys rosea, is known to effectively degrade the main contaminant (zearalenone) in animal feed, but the thermal instability of ZHD101 limits its industrial application. In this study, we successfully enhanced the thermal stability of ZHD101 through two iterative rounds of rational molecular design. First, after the prediction of disulfide bond sites, ZHD101T229C was obtained, and a new disulfide bond was formed between two single ZHD101 subunits to construct a dimer ZHD101. Then, based on ZHD101T229C, two high-vibration hotspot amino acids N137 and D170 were selected by analyzing atomic position fluctuations and dynamic information A small and precise mutant library containing three mutants (ZHD101T229C/N137L, ZHD101T229C/D170L, and ZHD101T229C/D170C) was obtained by saturation mutagenesis and calculation of binding energy in silico. Compared with the wild type, the thermal half-inactivation temperature (T50) of ZHD101T229C/D170C increased by 7{degrees}C, its half-life (t1/2) increased by 200% at 50{degrees}C, and its melting temperature (Tm) increased by 18.1{degrees}C. Molecular docking suggested that new covalent bond formation and shorter bond distance may contribute to the improved thermal stability of ZHD101. The rational design strategy proposed in this work can provide a reference for the thermal stability modification and optimization of other proteins. ImportanceZearalenone (ZEN) is a nonsteroidal estrogenic mycotoxin that poses a significant threat to animal feed safety. ZEN hydrolase 101 (ZHD101) catalyzes the conversion of ZEN into a nontoxic product, offering a promising detoxification strategy. However, the thermal instability of ZHD101 severely limits its industrial application. In this study, the thermal stability of ZHD101 was significantly improved through two rounds of rational design, resulting in the ZHD101T229C/D170C mutant. ZHD101T229C/D170C exhibited the improved half-inactivation temperature (T50), half-life (t1/2) and the highest melting temperature (Tm) reported thus far. Overall, the iterative combinatiorial mutation strategy involved the introduction of a disulfide bond between two single subunits and the application of B-factor analysis to identify hotspot amino acids residues. This approach effectively enhanced the enzymes structural stability, paving the way for its industrial application. ZHD101T229C/D170C and the rational design strategy presented in this work provide a robust framework for the thermal stability optimization of similar biocatalysts, advancing the practical use of ZHD101 in the feed industry.

molecular biology↗

bioRxiv2024

Does Unfairness Evoke Anger or Disgust? A Quantitative Neurofunctional Dissection Based on 25 Years of Neuroimaging

Over the last decades, the traditional Homo economicus model has been increasingly challenged by convergent evidence underscoring the impact of emotions on decision-making. A classic example is the perception of unfairness operationalized in the Ultimatum Game where humans readily sacrifice personal gains to punish those who violate fairness norms. While the emotional mechanism underlying costly punishments has been widely acknowledged, the distinct contributions of moral emotions (anger or disgust) remain debated, partly due to methodological limitations of the conventional experiments. Here, we capitalize on a quantitative neurofunctional dissection approach by combining recent developments in neuroimaging meta-analyses, behavioral-level, network-level, and neurochemical-level decoding and data from 3,266 participants from functional neuroimaging studies to determine the common and distinct neural representations between unfairness and the two moral emotions. Experience of unfairness engaged a widespread bilateral network encompassing insular, cingulate, and frontal regions, with dorsal striatal regions mediating the decision to reject unfair offers. Disgust engaged a defensive-avoidance circuit encompassing amygdalar, occipital, and frontal regions, while anger engaged non-overlapping systems including mid-cingulate, thalamic, and frontal regions. Unfairness and anger or disgust respectively commonly engaged the anterior and mid-insula, while the latter additionally showed common recruitment of ventrolateral prefrontal and orbitofrontal cortices. Multimodal network, behavioral, and serotonergic decoding provided a more granular and convincing dissection of these results. Findings indicate a shared neuroaffective basis underlying the impact of emotions on unfairness-induced punishment behavior and suggest a common brain circuit has been evolutionarily shaped to protect individuals from personal harm and enforce societal norms.

neuroscience↗

bioRxiv2024

Integrative multiomic approaches reveal ZMAT3 and p21 as conserved hubs in the p53 tumor suppression network

TP53, the most frequently mutated gene in human cancer, encodes a transcriptional activator that induces myriad downstream target genes. Despite the importance of p53 in tumor suppression, the specific p53 target genes important for tumor suppression remain unclear. Recent studies have identified the p53-inducible gene Zmat3 as a critical effector of tumor suppression, but many questions remain regarding its p53-dependence, activity across contexts, and mechanism of tumor suppression alone and in cooperation with other p53-inducible genes. To address these questions, we used Tuba-seqUltra somatic genome editing and tumor barcoding in a mouse lung adenocarcinoma model, combinatorial in vivo CRISPR/Cas9 screens, meta-analyses of gene expression and Cancer Dependency Map data, and integrative RNA-sequencing and shotgun proteomic analyses. We established Zmat3 as a core component of p53-mediated tumor suppression and identified Cdkn1a as the most potent cooperating p53-induced gene in tumor suppression. We discovered that ZMAT3/CDKN1A serve as near-universal effectors of p53-mediated tumor suppression that regulate cell division, migration, and extracellular matrix organization. Accordingly, combined Zmat3-Cdkn1a inactivation dramatically enhanced cell proliferation and migration compared to controls, akin to p53 inactivation. Together, our findings place ZMAT3 and CDKN1A as hubs of a p53-induced gene program that opposes tumorigenesis across various cellular and genetic contexts.

cancer biology↗

bioRxiv2024

Long range regulation of transcription scales with genomic distance in a gene specific manner

While critical for tuning the timing and level of transcription, enhancer communication with distal promoters is not well understood. Here we bypass the need for sequence-specific transcription factors and recruit activators directly using CARGO-VPR, an approach for targeting dCas9-VPR using a multiplexed array of RNA guides. We show that this approach achieves effective activator recruitment to arbitrary genomic sites, even those inaccessible by single dCas9. We utilize CARGO-VPR across the Prdm8-Fgf5 locus in mESCs, where neither gene is expressed. We demonstrate that while activator recruitment to any tested region results in transcriptional induction of at least one gene, the expression level strongly depends on the genomic distance between the promoter and activator recruitment site. However, the expression-distance relationship for each gene scales distinctly in a manner not attributable to differences in 3D contact frequency, promoter DNA sequence or presence of the repressive chromatin marks at the locus.

molecular biology↗

bioRxiv2024

AMPGLDA: Predicting LncRNA-Disease Associations Based on Adaptive Meta-Path Generation and Multi-Layer Perceptron

Increased evidence suggests that long non-coding RNA (lncRNA) holds a vital position in intricate human diseases. Nonetheless, the current pool of identified lncRNA linked to diseases remains restricted. Hence, the scientific community emphasizes the need for a reliable and cost-effective computational approach to predict the probable correlations between lncRNA and diseases. It would facilitate the exploration of the underlying mechanisms of lncRNA in ailments and the development of novel disease treatments. In this study, we propose a novel approach for predicting the associations between lncRNAs and diseases, which relies on the adaptive meta-path generation (AMPGLDA). Firstly, we integrate information about lncRNA, diseases, and miRNAs to construct a heterogeneous graph. Then, we utilize principal component analysis to extract global features from nodes. Based on this heterogeneous graph, AMPGLDA adaptively generates multiple meta-path graph structures and uses a graph convolutional neural network to learn the semantic feature representations of lncRNA and disease from the meta-path. Ultimately, AMPGLDA utilizes a deep neural network classifier to accurately predict the association between lncRNA and disease. The AMPGLDA model achieves impressive results, with AUC and AUPR scores of 99.66% and 99.66%, respectively, under the independent test set. Furthermore, three case studies demonstrate its accuracy in discovering new lncRNA-disease associations.

bioinformatics↗

bioRxiv2024

Distinct neural computations scale the violation of expected reward and emotion in social transgressions

Traditional decision-making models conceptualize humans as optimal learners aiming to maximize outcomes by leveraging reward prediction errors (PE). While violated emotional expectations (emotional PEs) have recently been formalized, the underlying neurofunctional basis and whether it differs from reward PEs remain unclear. Using a modified fMRI Ultimatum Game on n=43 participants we modelled reward and emotional PEs in response to unfair offers and subsequent punishment decisions. Computational modelling revealed distinct contributions of reward and emotional PEs to punishment decisions, with reward PE exerting a stronger impact. This process was neurofunctionally dissociable such that (1) reward engaged the dorsomedial prefrontal cortex while emotional experience recruited the anterior insula, (2) multivariate decoding accurately separated reward and emotional PEs. Predictive neural expressions of reward but not emotional PEs in fronto-insular systems predicted neurofunctional and behavioral punishment decisions. Overall, these findings suggest distinct neurocomputational processes underlie reward and emotional PEs which uniquely impact social decisions.

neuroscience↗

bioRxiv2023

An encyclopedia of enhancer-gene regulatory interactions in the human genome

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease1-6. Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and large-scale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 element-gene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancer-promoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

genomics↗

bioRxiv2023

A neural signature for the subjective experience of threat anticipation under uncertainty

Uncertainty about potential future threats and the associated anxious anticipation represents a key feature of anxiety. However, the neural systems that underlie the subjective experience of threat anticipation under uncertainty remain unclear. Combining a novel uncertain shock anticipation paradigm that allows precise modulation of the level of momentary anxious arousal during functional magnetic resonance imaging (fMRI) with multivariate predictive modeling, we trained a brain model that accurately predicted the intensity of subjective experience of anxious arousal on the population and individual level. In a series of analyses utilizing available fMRI datasets, we further demonstrate that the signature specifically predicted anxious anticipation and was not sensitive in predicting pain, general anticipation or unspecific arousal. The signature was functionally and spatially distinguishable from representations of subjective fear or negative affect. We developed a sensitive, generalizable, and specific neuromarker for subjective anxious arousal experienced during uncertain threat anticipation that can facilitate model development and clinical translation.

neuroscience↗

bioRxiv2023

Programmable multi-kilobase RNA editing using CRISPR-mediated trans-splicing

Current gene editing approaches in eukaryotic cells are limited to single base edits or small DNA insertions and deletions, and remain encumbered by unintended permanent effects and significant challenges in the delivery of large DNA cargo. Here we describe Splice Editing, a generalizable platform to correct gene transcripts in situ by programmable insertion or replacement of large RNA segments. By combining CRISPR-mediated RNA targeting with endogenous cellular RNA-splicing machinery, Splice Editing enables efficient, precise, and programmable large-scale editing of gene targets without DNA cleavage or mutagenesis. RNA sequencing and measurement of spliced protein products confirm that Splice Editing achieves efficient and specific targeted RNA and protein correction. We show that Splice Editors based on novel miniature RNA-targeting CRISPR-Cas systems discovered and characterized in this work can be packaged for effective delivery to human cells and affect different types of edits across multiple targets and cell lines. By editing thousands of bases simultaneously in a single reversible step, Splice Editing could expand the treatable disease population for monogenic diseases with large allelic diversity without the permanent unintended effects of DNA editing. One-sentence summaryCRISPR-guided trans-splicing enables efficient and specific recombination of large RNA molecules in mammalian cells, with broad applications in therapeutic development for genetic diseases and as a research tool for the study of basic RNA biology.

genomics↗