Biology subjects

Lee, H.

Publications and source records attributed to Lee, H..

At least 379 records · Page 21Linked to original sources

bioRxiv2021

Narratives as Networks: Predicting Memory from the Structure of Naturalistic Events

When we remember events, we often do not only recall individual events, but also the connections between them. However, extant research has focused on how humans segment and remember discrete events from continuous input, with far less attention given to how the structure of connections between events impacts memory. Here we conduct a functional magnetic resonance imaging study in which subjects watch and recall a series of realistic audiovisual narratives. By transforming narratives into networks of events, we demonstrate that more central events--those with stronger semantic or causal connections to other events--are better remembered. During encoding, central events evoke larger hippocampal event boundary responses associated with memory formation. During recall, high centrality is associated with stronger activation in cortical areas involved in episodic recollection, and more similar neural representations across individuals. Together, these results suggest that when humans encode and retrieve complex real-world experiences, the reliability and accessibility of memory representations is shaped by their location within a network of events.

neuroscience↗

bioRxiv2021

Visualization of reactive astrocytes in living brain of Alzheimer's disease patient

An early appearance of reactive astrocytes is a hallmark of Alzheimers disease (AD)1,2, providing a substrate for early diagnostic neuroimaging targets. However, there is no clinically validated neuroimaging probe to visualize the reactive astrogliosis in the human brain in vivo. Here, we report that PET/CT imaging with 11C-acetate and 18F-fluorodeoxyglucose (18F-FDG) functionally visualizes the reactive astrocyte-mediated neuronal hypometabolism in the brains with neuroinflammation and AD. We demonstrate that reactive astrocytes excessively absorb acetate through elevated monocarboxylate transporter-1 (MCT1), leading to aberrant GABA synthesis and release which suppresses neuronal glucose uptake through decreased glucose transporter-3 (GLUT3) in both animal and human brains. We propose the non-invasive functional PET/CT imaging for astrocytic acetate-hypermetabolism and neuronal glucose-hypometabolism as an advanced diagnostic strategy for early stages of AD.

neuroscience↗

bioRxiv2021

Global-scale CRISPR gene editor specificity profiling by ONE-seq identifies population-specific, variant off-target effects

Defining off-target profiles of gene-editing nucleases and CRISPR base editors remains an important challenge for use of these technologies, therapeutic or otherwise. Existing methods can identify off-target sites induced by these gene editors on an individual genome but are not designed to account for the broad diversity of genomic sequence variation that exists within populations of humans or other organisms. Here we describe OligoNucleotide Enrichment and sequencing (ONE-seq), a novel in vitro method that leverages customizable, high-throughput DNA synthesis technology instead of purified genomic DNA (gDNA) from individual genomes to profile gene editor off-target sites. We show that ONE-seq matches or exceeds the sensitivity of existing single-genome methods for identifying bona fide CRISPR-Cas9 off-target sites in cultured human cells and in vivo in a liver-humanized mouse model. In addition, ONE-seq outperforms existing best-in-class single-genome methods for defining off-target sites of CRISPR-Cas12a nucleases, cytosine base editors (CBEs), and adenine base editors (ABEs), unveiling previously undescribed bona fide off-target sites for all these editors in human cells. Most importantly, we leveraged ONE-seq to generate the first experimentally-derived population-scale off-target profiles for Cas9 nucleases that define the impacts of sequence variants from >2,500 individual human genome sequences in the 1000 Genomes Project database. Notably, some of the variants we identified that lead to increased mutation frequencies at off-target sites are enriched in specific human populations. We validated that novel population-specific, variant-sensitive off-target sites nominated by ONE-seq in vitro can show increased frequencies of mutations in human lymphoblastoid cells (LCLs) harboring these sequence variants. Collectively, our results demonstrate that ONE-seq is a highly sensitive off-target nomination method that can uniquely be used to identify population subgroup-linked differences in off-target profiles of gene editors. ONE-seq provides an important new pathway by which to assess the impacts of global human genetic sequence diversity on the specificities of gene editors, thereby enabling a broader and more all-inclusive approach for profiling off-target effects of these transformative therapeutic technologies.

molecular biology↗

bioRxiv2021

Machine learning algorithms in big data analyses identify determinants of insulin gene transcription

Machine learning (ML)-workflows enable unprejudiced/robust evaluation of complex datasets. Here, we analyzed over 490,000,000 data points to compare 10 different ML-workflows in a large (N=11,652) training dataset of human pancreatic single-cell (sc-)transcriptomes to identify genes associated with the presence or absence of insulin transcript(s). Prediction accuracy/sensitivity of each ML-workflow were tested in a separate validation dataset (N=2,913). Ensemble ML-workflows, in particular Random Forest ML-algorithm delivered high predictive power (AUC=0.83) and sensitivity (0.98), compared to other algorithms. The transcripts identified through these analyses also demonstrated significant correlation with insulin in bulk RNA-seq data from human islets. The top-10 features, (including IAPP, ADCYAP1, LDHA and SST) common to the three Ensemble ML-workflows were significantly dysregulated in scRNA-seq datasets from Ire-1{beta}-/- mice that demonstrate dedifferentiation of pancreatic {beta}-cells in a model of type 1 diabetes (T1D) and in pancreatic single cells from individuals with type 2 Diabetes (T2D). Our findings provide direct comparison of ML-workflows in big data analyses, identify key determinants of insulin transcription and provide workflows for future analyses.

genetics↗

bioRxiv2021

High Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Non-Covalent Inhibitor

Despite the recent availability of vaccines against the acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the search for inhibitory therapeutic agents has assumed importance especially in the context of emerging new viral variants. In this paper, we describe the discovery of a novel non-covalent small-molecule inhibitor, MCULE-5948770040, that binds to and inhibits the SARS-Cov-2 main protease (Mpro) by employing a scalable high throughput virtual screening (HTVS) framework and a targeted compound library of over 6.5 million molecules that could be readily ordered and purchased. Our HTVS framework leverages the U.S. supercomputing infrastructure achieving nearly 91% resource utilization and nearly 126 million docking calculations per hour. Downstream biochemical assays validate this Mpro inhibitor with an inhibition constant (Ki) of 2.9 {micro}M [95% CI 2.2, 4.0]. Further, using room-temperature X-ray crystallography, we show that MCULE-5948770040 binds to a cleft in the primary binding site of Mpro forming stable hydrogen bond and hydrophobic interactions. We then used multiple {micro}s-timescale molecular dynamics (MD) simulations, and machine learning (ML) techniques to elucidate how the bound ligand alters the conformational states accessed by Mpro, involving motions both proximal and distal to the binding site. Together, our results demonstrate how MCULE-5948770040 inhibits Mpro and offers a springboard for further therapeutic design. O_TEXTBOXSignificance StatementThe ongoing novel coronavirus pandemic (COVID-19) has prompted a global race towards finding effective therapeutics that can target the various viral proteins. Despite many virtual screening campaigns in development, the discovery of validated inhibitors for SARS-CoV-2 protein targets has been limited. We discover a novel inhibitor against the SARS-CoV-2 main protease. Our integrated platform applies downstream biochemical assays, X-ray crystallography, and atomistic simulations to obtain a comprehensive characterization of its inhibitory mechanism. Inhibiting Mpro can lead to significant biomedical advances in targeting SARS-CoV-2 treatment, as it plays a crucial role in viral replication. C_TEXTBOX

biophysics↗

bioRxiv2021

Microbiome Maps: Hilbert Curve Visualizations of Metagenomic Profiles

MotivationAbundance profiles from metagenomic sequencing data synthesize information from billions of sequenced reads coming from thousands of microbial genomes. Analyzing and understanding these profiles can be a challenge since the data they represent are complex. Particularly challenging is their visualization, as existing techniques are inadequate when the taxa number is in the thousands. We present a technique, and accompanying software, for the visualization of metagenomic abundance profiles using a space-filling curve that transforms a profile into an interactive 2D image. ResultsWe created JO_SCPLOWASPERC_SCPLOW, an easy to use tool for the visualization and exploration of metagenomic profiles from DNA sequencing data. It orders taxa using a space-filling Hilbert curve, and creates a "Microbiome Map", where each position in the image represents the abundance of a single taxon from a reference collection. JO_SCPLOWASPERC_SCPLOW can order taxa in multiple ways, and the resulting microbiome maps can highlight "hot spots" of microbes that are dominant in taxonomic clades or biological conditions. We use JO_SCPLOWASPERC_SCPLOW to visualize samples from a variety of microbiome studies, and discuss ways in which microbiome maps can be an invaluable tool to visualize spatial, temporal, disease, and differential profiles. Our approach can create detailed microbiome maps involving hundreds of thousands of microbial reference genomes with the potential to unravel latent relationships (taxonomic, spatio-temporal, functional, and other) that could remain hidden using traditional visualization techniques. The maps can also be converted into animated movies that bring to life the dynamicity of microbiomes. AvailabilityJO_SCPLOWASPERC_SCPLOW is freely available at microbiomemaps.org and via biorg.cs.fiu.edu/jasper Contactcvaldes2@unl.edu; giri@fiu.edu Supplementary informationSupplementary materials are available at microbiomemaps.org

bioinformatics↗

bioRxiv2021

A Deep Learning Model for Molecular Label Transfer that Enables Cancer Cell Identification from Histopathology Images

Deep learning cancer classification systems have the potential to improve cancer diagnosis. However, development of these computational approaches depends on prior annotation through a pathologist. This initial step relying on a manual, low-resolution, time-consuming process is highly variable and subject to observer variance. To address this issue, we developed a novel method, H&E Molecular neural network (HEMnet). This two-step process utilises immunohistochemistry as an initial molecular label for cancer cells on a H&E image and then we train a cancer classifier on the overlapping clinical histopathological images. Using this molecular transfer method, we show that HEMnet accurately distinguishes colorectal cancer from normal tissue at high resolution without the need for an initial manual histopathologic evaluation. Our validation study using histopathology images from TCGA samples accurately estimates tumour purity. Overall, our method provides a path towards a fully automated delineation of any type of tumor so long as there is a cancer-oriented molecular stain available for subsequent learning. Software, tutorials and interactive tools are available at: https://github.com/BiomedicalMachineLearning/HEMnet

bioinformatics↗

bioRxiv2021

Eliminating Mosquitoes with Precision Guided Sterile Males

The mosquito Aedes aegypti is the principal vector for arboviruses including dengue/yellow fever, chikungunya, and zika, infecting hundreds of millions of people annually. Unfortunately, traditional control methodologies are insufficient, so innovative control methods are needed. To complement existing measures, here we develop a molecular genetic control system termed precision guided sterile insect technique (pgSIT) in Aedes aegypti. PgSIT uses a simple CRISPR-based approach to generate sterile males that are deployable at any life stage. Supported by mathematical models, we empirically demonstrate that released pgSIT males can compete, suppress, and eliminate mosquitoes in multigenerational population cages. This platform technology could be used in the field, and adapted to many vectors, for controlling wild populations to curtail disease in a safe, confinable, and reversible manner.

genetics↗

bioRxiv2021

TPX2 Amplification-Driven Aberrant Mitosis in Long-Term Cultured Human Embryonic Stem Cells

Although human embryonic stem cells (hESCs) are equipped with highly effective machinery for the maintenance of genome integrity, the frequency of genetic aberrations during long-term in vitro hESC culture has been a serious issue that raises concerns over their safety in future clinical applications. By passaging hESCs over a broad range of timepoints, we found that mitotic aberrations, such as the delay of mitosis, multipolar centrosomes, and chromosome mis-segregation, were increased in the late-passaged hESCs (LP-hESCs) in parallel with polyploidy compared to early-passaged hESCs (EP-hESCs). Through high-resolution genome-wide approaches and by following transcriptome analysis, we found that LP-hESCs with a minimal amplicon in chromosome 20q11.21 highly expressed TPX2 (targeting protein for Xklp2), a key protein for governing spindle assembly and cancer malignancy. Consistent with these findings, the inducible expression of TPX2 in EP-hESCs reproduced aberrant mitotic events, such as the delay of mitotic progression, spindle stability, misaligned chromosomes, and polyploidy. This data suggests that the amplification and increased transcription of the TPX2 gene at 20q11.21 could contribute to an increase in aberrant mitosis due to altered spindle dynamics.

cell biology↗

bioRxiv2021

Parallel processing of working memory and temporal information by distinct types of cortical projection neurons

It is unclear how different types of cortical projection neurons work together to support diverse cortical functions. We examined the discharge characteristics and inactivation effects of intratelencephalic (IT) and pyramidal tract (PT) neurons--two major types of cortical excitatory neurons that project to cortical and subcortical structures, respectively--in the medial prefrontal cortex of mice performing a delayed response task. We found that IT neurons, but not PT neurons, convey significant working memory-related signals. We also found that the inactivation of IT neurons, but not PT neurons, impairs behavioral performance. In contrast, PT neurons convey far more temporal information than IT neurons during the delay period. Our results indicate a division of labor between IT and PT projection neurons in the prefrontal cortex for the maintenance of working memory and for tracking the passage of time, respectively.

neuroscience↗

bioRxiv2021

Potent, Novel SARS-CoV-2 PLpro Inhibitors Block Viral Replication in Monkey and Human Cell Cultures

Antiviral agents blocking SARS-CoV-2 viral replication are desperately needed to complement vaccination to end the COVID-19 pandemic. Viral replication and assembly are entirely dependent on two viral cysteine proteases: 3C-like protease (3CLpro) and the papain-like protease (PLpro). PLpro also has deubiquitinase (DUB) activity, removing ubiquitin (Ub) and Ub-like modifications from host proteins, disrupting the host immune response. 3CLpro is inhibited by many known cysteine protease inhibitors, whereas PLpro is a relatively unusual cysteine protease, being resistant to blockade by such inhibitors. A high-throughput screen of biased and unbiased libraries gave a low hit rate, identifying only CPI-169 and the positive control, GRL0617, as inhibitors with good potency (IC50 < 10 {micro}M). Analogues of both inhibitors were designed to develop structure-activity relationships; however, without a co-crystal structure of the CPI-169 series, we focused on GRL0617 as a starting point for structure-based drug design, obtaining several co-crystal structures to guide optimization. A series of novel 2-phenylthiophene-based non-covalent SARS-CoV-2 PLpro inhibitors were obtained, culminating in low nanomolar potency. The high potency and slow inhibitor off-rate were rationalized by newly identified ligand interactions with a "BL2 groove" that is distal from the active site cysteine. Trapping of the conformationally flexible BL2 loop by these inhibitors blocks binding of viral and host protein substrates; however, until now it has not been demonstrated that this mechanism can induce potent and efficacious antiviral activity. In this study, we report that novel PLpro inhibitors have excellent antiviral efficacy and potency against infectious SARS-CoV-2 replication in cell cultures. Together, our data provide structural insights into the design of potent PLpro inhibitors and the first validation that non-covalent inhibitors of SARS-CoV-2 PLpro can block infection of human cells with low micromolar potency.

microbiology↗

bioRxiv2021

Nigro-striatal dopamine activation lowers behavioral and neuronal phenotypes associated with obsessive-compulsive disorder

Dorsal striatal dopamine transmission engages the cortico-striato-thalamo-cortical (CSTC) circuit, which is implicated in many neuropsychiatric diseases, including obsessive-compulsive disorder (OCD). Yet it is unknown if dorsal striatal dopamine hyperactivity is the cause or consequence of changes elsewhere in the CSTC circuit. Classical pharmacological and neurotoxic manipulations of the CSTC and other brain circuits suffer from various drawbacks related to off-target effects and adaptive changes. Chemogenetics, on the other hand, enables a highly selective targeting of specific neuronal populations within a given circuit. In this study, we developed a chemogenetic method for selective activation of dopamine neurons in the substantia nigra, which innervating the rat dorsal striatum. We used this model to investigate effects of targeted dopamine activation on CSTC circuit function, especially in fronto-cortical regions. We found that chemogenetic activation of these neurons increased movement, as expected from dopamine release, rearings and time spend in center, while it also lowered self-grooming and increased prepulse inhibition in females. Remarkably, we observed reduced [18F]FDG metabolism in frontal cortex, following dopamine activation in the dorsal striatum, yet total glutamate levels-in this region were increased. A finding which may help explain the contradiction in some clinical studies of increased [18F]FDG metabolism and lower glutamate levels in diseases like OCD. Taken together, these results establish the importance of nigro-striatal dopamine transmission for modulating CSTC function, especially with respect to fronto-cortical activity, glutamate levels and behaviors related anxiety and compulsive actions. One Sentence SummaryDorsal striatum dopamine induce fronto-cortical hypoactivity and reduce compulsive behaviors in rats

neuroscience↗

bioRxiv2021

Elucidating the Mechanical Energy for Cyclization of a DNA Origami Tile

DNA origami has emerged as a versatile method to synthesize nanostructures with high precision. This bottom-up self-assembly approach can produce not only complex static architectures, but also dynamic reconfigurable structures with tunable properties. While DNA origami has been explored increasingly for diverse applications such as biomedical and biophysical tools, related mechanics are also under active investigation. Here we studied the structural properties of DNA origami and investigated the energy needed to deform the DNA structures. We used a single-layer rectangular DNA origami tile as a model system and studied its cyclization process. This origami tile was designed with an inherent twist by placing crossovers every 16 base-pairs (bp), corresponding to a helical pitch of 10.67 bp/turn which is slightly different from that of native B-form DNA (10.5 bp/turn). We used molecular dynamics (MD) simulations based on a coarse-grained model on an open-source computational platform, oxDNA. We calculated the energies needed to overcome the initial curvature and induce mechanical deformation by applying linear spring forces. We found that the initial curvature may be overcome gradually during cyclization and a total of ~33.1 kcal/mol is required to complete the deformation. These results provide insights into the DNA origami mechanics and should be useful for diverse applications such as adaptive reconfiguration and energy absorption.

biophysics↗

bioRxiv2021

Direct acetylation of the conserved threonine of an immune regulator by bacterial effectors activates RPM1-dependent immunity in Arabidopsis

Plant pathogenic bacteria deliver effectors into plant cells to suppress immunity and promote pathogen survival (Buttner, 2016; Deslandes and Rivas, 2012); however, these effectors can be recognised by plant disease resistance (R) proteins to activate innate immunity (Jones and Dangl, 2006; Spoel and Dong, 2012). The bacterial acetyltransferase effectors HopZ5 and AvrBsT trigger immunity in Arabidopsis thaliana genotypes lacking SUPPRESSOR OF AVRBST-ELICITED RESISTANCE 1 (SOBER1) (Choi et al., 2018; Jayaraman et al., 2017). Using an Arabidopsis accession, Tscha-1, that naturally lacks functional SOBER1 but is unable to recognise HopZ5, we demonstrate that RESISTANCE TO P. SYRINGAE PV MACULICOLA 1 (RPM1) and RPM1-INTERACTING PROTEIN 4 (RIN4) are indispensable for HopZ5- or AvrBsT-triggered immunity. Remarkably, T166 of RIN4, the phosphorylation of which is induced by AvrB and AvrRpm1, was directly acetylated by HopZ5 and AvrBsT. Furthermore, we demonstrate that acetylation of RIN4 T166 is required and sufficient for activation of HopZ5- or AvrBsT-triggered defence. Finally, we show that SOBER1 interferes with HopZ5- or AvrBsT-triggered immunity by deacetylating RIN4 T166. Our findings indicate that multiple pathogen effectors with distinct biochemical properties modify a single residue in a guardee protein and activate a plant NLR immune receptor. We have thus elucidated detailed molecular mechanisms underlying the activation and suppression of plant innate immunity triggered by bacterial acetyltransferases.

plant biology↗

bioRxiv2021

Mutational impact and signature of ionizing radiation

Whole-genome sequencing (WGS) of human tumors and normal cells exposed to various carcinogens has revealed distinct mutational patterns that provide deep insights into the DNA damage and repair processes. Although ionizing radiation (IR) is conventionally known as a strong carcinogen, its genome-wide mutational impacts have not been comprehensively investigated at the single-nucleotide level. Here, we explored the mutational landscape of normal single-cells after exposure to the various levels of IR. On average, 1 Gy of IR exposure generated [~]16 mutational events with a spectrum consisting of predominantly small nucleotide deletions and a few characteristic structural variations. In [~]30% of the post-irradiated cells, complex genomic rearrangements, such as chromoplexy, chromothripsis, and breakage-fusion-bridge cycles, were resulted, indicating the stochastic and chaotic nature of DNA repair in the presence of the massive number of concurrent DNA double-strand breaks. These mutational signatures were confirmed in the genomes of 22 IR-induced secondary malignancies. With high-resolution genomic snapshots of irradiated cells, our findings provide deep insights into how IR-induced DNA damage and subsequent repair processes operate in mammalian cells.

genomics↗

bioRxiv2020

Profiling diverse sequence tandem repeats in colorectal cancer reveals co-occurrence of microsatellite and chromosomal instability involving Chromosome 8

Colorectal carcinomas (CRCs) which have lost DNA mismatch repair display hypermutability evident in a molecular phenotype called microsatellite instability (MSI). These mismatch repair deficient tumors are thought to lack widespread genomic instability features, such as copy number changes and rearrangements. To identify MSI for clinical diagnosis, current molecular testing looks for changes in mononucleotide or dinucleotide repeats. However, microsatellites have other types of sequence tandem repeats such as tri- and tetranucleotide motifs. These additional classes of microsatellites are generally not examined for MSI but are known to be unstable in a phenotype known as elevated microsatellite alterations at selected tetranucleotide repeats, or EMAST. We developed a sequencing approach that provides ultra-high coverage (>2500X) of microsatellite targets and cancer genes for profiling genomic instability. We assessed the diverse repeat motifs across 200 microsatellites. Our approach provides highly sensitive detection of MSI with high specificity, evaluates copy number alterations with high accuracy, delineates chromosomal instability (CIN) classification and deconvolutes subclonal architecture. By examining both MSI and CIN, we discovered mutations and copy number alterations that defined mixed genomic instability states of CIN and MSI, which are normally considered exclusive. An increase in copy number of chromosome arm 8q was prevalent among MSI tumors. Moreover, we identified an inter-chromosomal translocation event from a CRC with co-occurrence of MSI. Subclonal analysis demonstrated that mutations which are typically considered to be exclusive in MSI, shows mutual occurrence in MSI tumors with more sensitive characterization. Our approach revealed that MSH3 mutations are a potential source of mixed genomic instability features. Overall, our study demonstrates that some colorectal cancers have features of both microsatellite and chromosomal instability. This result may have implications for immunotherapy treatment.

genomics↗

bioRxiv2020

Using physiological signals to predict temporal defense responses: a multi-modality analysis

Defense responses are a highly conserved behavioral response set across species. Defense responses motivate organisms to detect and react to threats and potential danger as a precursor to anxiety. Accurate measurement of temporal defense responses is important for understanding clinical anxiety and mood disorders, such as post-traumatic stress disorder, obsessive compulsive disorder, and generalized anxiety disorder. Within these conditions, anxiety is defined as a state of prolonged defense response elicitation to a threat that is ambiguous or unspecific. In this study, we aimed to develop a data-driven approach to capture temporal defense response elicitation through a multi-modality data analysis of physiological signals, including electroencephalogram (EEG), electrocardiogram (ECG), and eye-tracking information. A fear conditioning paradigm was adopted to develop a defense response classification model. From a classification model based on 42 feature sets, a higher order crossing feature set-based model was chosen for further analysis with cross-validation loss of 0.0462 (SEM: 0.0077). To validate our model, we compared predicted defense response occurrence ratios from a comprehensive situation that generates defense responses by watching movie clips with fear awareness and threat existence predictability, which have been reported to correlate with defense response elicitation in previous studies. We observed that defense response occurrence ratios are correlated with threat existence predictability, but not with fear awareness. These results are similar to those of previous studies using comprehensive situations. Our study provides insight into measurement of temporal defense responses via a novel approach, which can improve understanding of anxiety and related clinical disorders for neurobiological and clinical researchers.

neuroscience↗

bioRxiv2020

Direct RNA targeted transcriptomic profiling in tissue using Hybridization-based RNA In Situ Sequencing (HybRISS)

Highly multiplexed spatial mapping of multiple transcripts within tissues allows for investigation of the transcriptomic and cellular diversity of mammalian organs previously unseen. Here we explore the possibilities of a direct RNA (dRNA) detection approach incorporating the use of padlock probes and rolling circle amplification in combination with hybridization-based in situ sequencing (HybISS) chemistry. We benchmark a dRNA targeting kit that circumvents the standard reverse transcription limiting, cDNA-based in situ sequencing (ISS). We found a five-fold increase in transcript detection efficiency when compared to cDNA-based ISS and also validated its multiplexing capability by targeting a curated panel of 50 genes from previous publications on mouse brain sections, leading to additional data interpretation such as de novo cell typing. With this increased efficiency, we maintain specificity, multiplexing capabilities and ease of implementation. Overall, the dRNA chemistry shows significant improvements in target detection efficiency, closing the gap between the gold standard of fluorescent in situ hybridization (FISH) based technologies and opens up possibilities to explore new biological questions previously not possible with cDNA-based ISS, nor with FISH.

molecular biology↗