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Results for “molecular biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

PIWI Proteins Act at Multiple Steps in the Production of Their Own Guides

In animals, piRNAs guide PIWI-proteins to silence transposons and regulate gene expression. The mechanisms for making piRNAs have been proposed to differ among cell types, tissues, and animals. Our data instead suggest a single model that explains piRNA production in most animals. piRNAs initiate piRNA production by guiding PIWI proteins to slice precursor transcripts. Next, PIWI proteins direct the stepwise fragmentation of the sliced precursor transcripts, yielding tail-to-head strings of phased pre-piRNAs. Our analyses detect evidence for this piRNA biogenesis strategy across an evolutionarily broad range of animals including humans. Thus, PIWI proteins initiate and sustain piRNA biogenesis by the same mechanism in species whose last common ancestor predates the branching of most animal lineages. The unified model places PIWI-clade Argonautes at the center of piRNA biology and suggests that the ancestral animal--the Urmetazoan--used PIWI proteins both to generate piRNA guides and to execute piRNA function.

molecular biology↗

bioRxiv2019

DDX3 depletion selectively represses translation of structured mRNAs

DDX3 is an RNA chaperone of the DEAD-box family that regulates translation. Ded1, the yeast ortholog of DDX3, is a global regulator of translation, whereas DDX3 is thought to preferentially affect a subset of mRNAs. However, the set of mRNAs that are regulated by DDX3 are unknown, along with the relationship between DDX3 binding and activity. Here, we use ribosome profiling, RNA-seq, and PAR-CLIP to define the set of mRNAs that are regulated by DDX3 in human cells. We find that while DDX3 binds highly expressed mRNAs, depletion of DDX3 particularly affects the translation of a small subset of the transcriptome. We further find that DDX3 binds a site on helix 16 of the human ribosome, placing it immediately adjacent to the mRNA entry channel. Translation changes caused by depleting DDX3 levels or expressing an inactive point mutation are different, consistent with different association of these genetic variant types with disease. Taken together, this work defines the subset of the transcriptome that is responsive to DDX3 inhibition, with relevance for basic biology and disease states where DDX3 is altered.

molecular biology↗

bioRxiv2023

Identification of a carbohydrate-recognition motif of purinergic receptors

As a major class of biomolecules, carbohydrates play indispensable roles in various biological processes. However, it remains largely unknown how carbohydrates directly modulate important drug targets, such as G-protein coupled receptors (GPCRs). Here, we employed P2Y purinoceptor 14 (P2Y14), a drug target for inflammation and immune responses, to uncover the sugar nucleotide activation of GPCRs. Integrating molecular dynamics simulation with functional study, we identified the uridine diphosphate (UDP)-sugar-binding site on P2Y14, and revealed that a UDP-glucose might activate the receptor by bridging the transmembrane helices (TM) 2 and 7. Between TM2 and TM7 of P2Y14, a conserved salt bridging chain (K2.60-D2.64-K7.35-E7.36, KDKE) was identified to distinguish different UDP-sugars, including UDP-glucose, UDP-galactose, UDP-glucuronic acid and UDP-N-acetylglucosamine. We identified the KDKE chain as a conserved functional motif of sugar binding for both P2Y14 and P2Y purinoceptor 12 (P2Y12), and then designed three sugar nucleotides as agonists of P2Y12. These results not only expand our understanding for activation of purinergic receptors but also provide insights for the carbohydrate drug development for GPCRs.

molecular biology↗

bioRxiv2024

GraFusionNet: Integrating Node, Edge, and Semantic Features for Enhanced Graph Representations

Understanding complex graph-structured data is a cornerstone of modern research in fields like cheminformatics and bioinformatics, where molecules and biological systems are naturally represented as graphs. However, traditional graph neural networks (GNNs) often fall short by focusing mainly on node features while overlooking the rich information encoded in edges. To bridge this gap, we present GraFusionNet, a framework designed to integrate node, edge, and molecular-level semantic features for enhanced graph classification. By employing a dual-graph autoencoder, GraFusionNet transforms edges into nodes via a line graph conversion, enabling it to capture intricate relationships within the graph structure. Additionally, the incorporation of Chem-BERT embeddings introduces semantic molecular insights, creating a comprehensive feature representation that combines structural and contextual information. Our experiments on benchmark datasets, such as Tox21 and HIV, highlight GraFusionNets superior performance in tasks like toxicity prediction, significantly surpassing traditional models. By providing a holistic approach to graph data analysis, GraFusion-Net sets a new standard in leveraging multi-dimensional features for complex predictive tasks. CCS CONCEPTSO_LIComputing methodologies [->] Neural networks. C_LI ACM Reference FormatMd Toki Tahmid, Tanjeem Azwad Zaman, and Mohammad Saifur Rahman. 2018. GraFusionNet: Integrating Node, Edge, and Semantic Features for Enhanced Graph Representations. In Proceedings of Make sure to enter the correct conference title from your rights confirmation email (Conference acronym XX). ACM, New York, NY, USA, 9 pages. https://doi.org/XXXXXXX.XXXXXXX

molecular biology↗

bioRxiv2025

DNA2 and MSH2 activity collectively mediate chemically stabilized G4 for efficient telomere replication

G-quadruplexes (G4s) are widely existing stable DNA secondary structures in mammalian cells. A long-standing hypothesis is that timely resolution of G4s is needed for efficient and faithful DNA replication. In vitro, G4s may be unwound by helicases or alternatively resolved via DNA2 nuclease mediated G4 cleavage. However, little is known about the biological significance and regulatory mechanism of the DNA2-mediated G4 removal pathway. Here, we report that DNA2 deficiency or its chemical inhibition leads to a significant accumulation of G4s and stalled replication forks at telomeres, which is demonstrated by a high-resolution technology: Single molecular analysis of replicating DNA (SMARD). We further identify that the DNA repair complex MutS (MSH2-MSH6) binds G4s and stimulates G4 resolution via DNA2-mediated G4 excision. MSH2 deficiency, like DNA2 deficiency or inhibition, causes G4 accumulation and defective telomere replication. Meanwhile, G4-stabilizing environmental compounds block G4 unwinding by helicases but not G4 cleavage by DNA2. Consequently, G4 stabilizers impair telomere replication and cause telomere instabilities, especially in cells deficient in DNA2 or MSH2.

molecular biology↗

bioRxiv2026

Nucleic Acid Capture from Human Blood Plasma Uncovers G-Quadruplex Structures

Ultrashort (US) cell-free DNA (cfDNA) is a population of approximately 50-nucleotide single-stranded DNA molecules in human plasma.1-3 Although it holds biological and diagnostic potential, US cfDNA escapes detection by conventional double-stranded library preparation methods.1-3 Independent studies have linked US cfDNA to regulatory genomic regions and to sequences predicted to form noncanonical structures, prompting the hypothesis that higher-order DNA structure contributes to its molecular properties. This interpretation, however, has so far rested on computational prediction rather than experimental evidence. Here we test this hypothesis using computational, biophysical and biochemical approaches. In silico size-selected US cfDNA from 20 healthy donors was selectively enriched at putative quadruplex sequences (PQS) that overlap both experimentally observed quadruplex sequences and accessible chromatin of blood cells. Synthetic oligonucleotides corresponding to the most enriched of these loci adopted predominantly parallel G-quadruplex (G4) structures, as revealed by circular dichroism. Endogenous nucleic acids captured directly from pooled plasma by poly(A)-tailing and immobilization, without extraction, denaturation or annealing at any step, displayed folded G4 structures. Two orthogonal probes detected these structures: the BG4 antibody and the fluorogenic ligand N-methyl mesoporphyrin IX. Reciprocal competition with a third, chemically unrelated G4 ligand, pyridostatin, confirmed the signal. Together, these experiments provide direct experimental evidence for the presence of folded G4 structures in human blood plasma.

molecular biology↗

bioRxiv2020

Fe(III) heme sets an activation threshold for processing distinct groups of pri-miRNAs in mammalian cells

The essential biological cofactor heme is synthesized in cells in the Fe(II) form. Oxidized Fe(III) heme is specifically required for processing primary transcripts of microRNAs (pri-miRNAs) by the RNA-binding protein DGCR8, a core component of the Microprocessor complex. It is unknown how readily available Fe(III) heme is in the largely reducing environment in human cells and how changes in cellular Fe(III) heme availability alter microRNA (miRNA) expression. Here we address the first question by characterizing DGCR8 mutants with various degrees of deficiency in heme-binding. We observed a strikingly simple correlation between Fe(III) heme affinity in vitro and the Microprocessor activity in HeLa cells, with the heme affinity threshold for activation estimated to be between 0.6-5 pM under typical cell culture conditions. The threshold is strongly influenced by cellular heme synthesis and uptake. We suggest that the threshold reflects a labile Fe(III) heme pool in cells. Based on our understanding of DGCR8 mutants, we reanalyzed recently reported miRNA sequencing data and conclude that heme is generally required for processing canonical pri-miRNAs, that heme modulates the specificity of Microprocessor, and that cellular heme level and differential DGCR8 heme occupancy alter the expression of distinct groups of miRNAs in a hierarchical fashion. Overall, our study provides the first glimpse of a labile Fe(III) heme pool important for a fundamental physiological function and reveal principles governing how Fe(III) heme modulates miRNA maturation at a genomic scale. We also discuss potential states and biological significance of the labile Fe(III) heme pool.

molecular biology↗

bioRxiv2021

iCodon: ideal codon design for customized gene expression

Messenger RNA (mRNA) stability substantially impacts steady-state gene expression levels in a cell. mRNA stability, in turn, is strongly affected by codon composition in a translation-dependent manner across species, through a mechanism termed codon optimality. We have developed iCodon (www.iCodon.org), an algorithm for customizing mRNA expression through the introduction of synonymous codon substitutions into the coding sequence. iCodon is optimized for four vertebrate transcriptomes: mouse, human, frog, and fish. Users can predict the mRNA stability of any coding sequence based on its codon composition and subsequently generate more stable (optimized) or unstable (deoptimized) variants encoding for the same protein. Further, we show that codon optimality predictions correlate with expression levels using fluorescent reporters and endogenous genes in human cells and zebrafish embryos. Therefore, iCodon will benefit basic biological research, as well as a wide range of applications for biotechnology and biomedicine.

molecular biology↗

bioRxiv2023

MitoQuicLy: a high-throughput method for quantifying cell-free DNA from human plasma, serum, and saliva

Circulating cell-free mitochondrial DNA (cf-mtDNA) is an emerging biomarker of psychobiological stress and disease which predicts mortality and is associated with various disease states. To evaluate the contribution of cf-mtDNA to health and disease states, standardized high-throughput procedures are needed to quantify cf-mtDNA in relevant biofluids. Here, we describe MitoQuicLy: Mitochondrial DNA Quantification in cell-free samples by Lysis. We demonstrate high agreement between MitoQuicLy and the commonly used column-based method, although MitoQuicLy is faster, cheaper, and requires a smaller input sample volume. Using 10 {micro}L of input volume with MitoQuicLy, we quantify cf-mtDNA levels from three commonly used plasma tube types, two serum tube types, and saliva. We detect, as expected, significant inter-individual differences in cf-mtDNA across different biofluids. However, cf-mtDNA levels between concurrently collected plasma, serum, and saliva from the same individual differ on average by up to two orders of magnitude and are poorly correlated with one another, pointing to different cf-mtDNA biology or regulation between commonly used biofluids in clinical and research settings. Moreover, in a small sample of healthy women and men (n=34), we show that blood and saliva cf-mtDNAs correlate with clinical biomarkers differently depending on the sample used. The biological divergences revealed between biofluids, together with the lysis-based, cost-effective, and scalable MitoQuicLy protocol for biofluid cf-mtDNA quantification, provide a foundation to examine the biological origin and significance of cf-mtDNA to human health.

molecular biology↗

bioRxiv2024

Concatemer Assisted Stoichiometry Analysis (CASA): a targeted mass spectrometry method for protein quantification

Large multi-protein machines are central to multiple biological processes. However, stoichiometric determination of protein complex subunits in their native states presents a significant challenge. This study addresses the limitations of current tools in accuracy and precision by introducing concatemer-assisted stoichiometry analysis (CASA). CASA leverages stable isotope-labeled concatemers and liquid chromatography parallel reaction monitoring mass spectrometry (LC-PRM-MS) to achieve robust quantification of proteins with sub-femtomole sensitivity. As a proof-of-concept, CASA was applied to study budding yeast kinetochores. Stoichiometries were determined for ex vivo reconstituted kinetochore components, including the canonical H3 nucleosomes, centromeric (Cse4CENP-A) nucleosomes, centromere proximal factors (Cbf1 and CBF3 complex), inner kinetochore proteins (Mif2CENP-C, Ctf19CCAN complex), and outer kinetochore proteins (KMN network). Absolute quantification by CASA revealed Cse4CENP-A as a cell-cycle controlled limiting factor for kinetochore assembly. These findings demonstrate that CASA is applicable for stoichiometry analysis of multi-protein assemblies. SummaryThis study presents Concatemer-Assisted Stoichiometry Analysis (CASA) to address a common challenge in cell biological research: quantifying the number of each protein subunit in a native protein complex.

molecular biology↗

bioRxiv2025

TEMI: Tissue Expansion Mass Spectrometry Imaging

The spatial distribution of diverse biomolecules in multicellular organisms is essential for their physiological functions. High-throughput in situ mapping of biomolecules is crucial for both basic and medical research, and requires high scanning speed, spatial resolution, and chemical sensitivity. Here, we developed a Tissue Expansion method compatible with matrix-assisted laser desorption/ionization Mass spectrometry Imaging (TEMI). TEMI reaches single-cell spatial resolution without sacrificing voxel throughput and enables the profiling of hundreds of biomolecules, including lipids, metabolites, peptides (proteins), and N-glycans. Using TEMI, we mapped the spatial distribution of biomolecules across various mammalian tissues and uncovered metabolic heterogeneity in tumors. TEMI can be easily adapted and broadly applied in biological and medical research, to advance spatial multi-omics profiling.

molecular biology↗

bioRxiv2025

Medium-chain fatty acids mitigate endoplasmic reticulum stress in yeast cells

Upon endoplasmic reticulum (ER) stress, eukaryotic cells commonly trigger cytoprotective transcriptome changes, namely the unfolded protein response (UPR). In yeast Saccharomyces cerevisiae, the UPR is mediated by the transcription factor Hac1, which is induced in response to ER stress. Since Hac1 controls hundreds of genes, the biological phenomena that result from UPR are not yet fully understood. Here, we show that cells carrying a mutation to constitutively express Hac1 abundantly contained C10:0 and C12:0 fatty acids, known as medium-chain fatty acids (MCFs). UPR induction by some ER stress stimuli was attenuated by externally supplied MCFs in cells in which fatty acid elongation was genetically or pharmacologically halted. The cell survival assay also indicated the mitigation of ER stress by the MCFs. Moreover, we demonstrated that MCFs leads to the diffusion of a mutant transmembrane protein aggregated in the ER. We propose that, as a biologically beneficial outcome of UPR, MCFs are produced to change the properties of the ER membrane, such as fluidity, in ER-stressed yeast cells.

molecular biology↗

bioRxiv2018

Comparative RNAi Screens in Isogenic Human Stem Cells Reveal SMARCA4 as a Differential Regulator

Large-scale RNAi screens are a powerful approach to identify functions of genes in a cell-type specific manner. For model organisms, genetically identical (isogenic) cells from different cell-types are readily available, making comparative studies meaningful. For humans, however, screening isogenic cells is not straightforward. Here, we show that RNAi screens are possible in genetically identical human stem cells, employing induced pluripotent stem cell as intermediates. The screens revealed SMARCA4 (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily A member 4) as a stemness regulator, while balancing differentiation distinctively for each cell type. SMARCA4 knockdown in hematopoietic stem progenitor cells (HSPC) caused impaired self-renewal in-vitro and in-vivo with skewed myeloid differentiation; whereas in neural stem cells (NSC), it impaired selfrenewal while biasing differentiation towards neural lineage, through combinatorial SWI/SNF subunit assembly. Our findings pose a powerful approach for deciphering human stem cell biology and attribute distinct roles to SMARCA4 in stem cell maintenance.

molecular biology↗

bioRxiv2020

Analysis of new nosological models from disease similarities using clustering

While classical disease nosology is based on phenotypical characteristics, the increasing availability of biological and molecular data is providing new understanding of diseases and their underlying relationships, that could lead to a more comprehensive paradigm for modern medicine. In the present work, similarities between diseases are used to study the generation of new possible disease nosologic models that include both phenotypical and biological information. To this aim, disease similarity is measured in terms of disease feature vectors, that stood for genes, proteins, metabolic pathways and PPIs in the case of biological similarity, and for symptoms in the case of phenotypical similarity. An improvement in similarity computation is proposed, considering weighted instead of Booleans feature vectors. Unsupervised learning methods were applied to these data, specifically, density-based DBSCAN clustering algorithm. As evaluation metric silhouette coefficient was chosen, even though the number of clusters and the number of outliers were also considered. As a results validation, a comparison with randomly distributed data was performed. Results suggest that weighted biological similarities based on proteins, and computed according to cosine index, may provide a good starting point to rearrange disease taxonomy and nosology.

bioinformatics↗

bioRxiv2021

New loci and neuronal pathways for resilience to heat stress in animals

Climate change and resilience to warming climates have implications for humans, livestock, and wildlife. The genetic mechanisms that confer thermotolerance to mammals are still not well characterized. We used dairy cows as a model to study heat tolerance because they are lactating, and therefore often prone to thermal stress. The data comprised almost 0.5 million milk records (milk, fat, and proteins) of 29,107 Australian Holsteins, each having around 15 million imputed sequence variants. Dairy animals often reduce their milk production when temperature and humidity rise; thus, the phenotypes used to measure an individuals heat tolerance were defined as the rate of milk production decline (slope traits) with a rising temperature-humidity index. With these slope traits, we performed a genome-wide association study (GWAS) using different approaches, including conditional analyses, to correct for the relationship between heat tolerance and level of milk production. The results revealed multiple novel loci for heat tolerance, including 61 potential functional variants at sites highly conserved across vertebrate species. Moreover, it was interesting that specific candidate variants and genes are related to the neuronal system (ITPR1, ITPR2, and GRIA4) and neuroactive ligand-receptor interaction functions for heat tolerance (NPFFR2, CALCR, and GHR), providing a novel insight that can help to develop genetic and management approaches to combat heat stress. Author summaryWhile understanding the genetic basis of heat tolerance is crucial in the context of global warmings effect on humans, livestock, and wildlife, the specific genetic variants and biological features that confer thermotolerance in animals are still not well characterized. The ability to tolerate heat varies across individuals, with substantial genetic control of this complex trait. Dairy cattle are excellent model in which to find genes associated with individual variations in heat tolerance since they significantly suffer from heat stress due to the metabolic heat of lactation. By genome-wide association studies of more than 29,000 cows with 15 million sequence variants and controlled phenotype measurements, we identify many new loci associated with heat tolerance. The biological functions of these loci are linked to the neuronal system and neuroactive ligand-receptor interaction functions. Also, several putative causal mutations for heat tolerance are at genomic sites that are otherwise evolutionarily conserved across 100 vertebrate species. Overall, our findings provide new insight into the molecular and biological basis of heat tolerance that can help to develop genetic and management approaches to combat heat stress.

genomics↗

bioRxiv2026

A Wolbachia pipientis protein confers resistance to virus infection in Drosophila melanogaster

The intracellular bacterium Wolbachia pipientis alters the biology of its arthropod hosts in many ways, and can increase resistance to RNA viruses in both Drosophila and mosquitoes. Wolbachia-induced pathogen blocking has generated much interest because of its potential to restrict insect vector transmission of human diseases caused by RNA viruses. However, the molecular mechanisms by which Wolbachia affects host viral resistance are still mostly elusive. We used dilp2-3,5 mutant Drosophila, which are long-lived, but only in the presence of Wolbachia, to show that the presence of Wolbachia also increased the resistance of the mutant flies to infection with Drosophila C virus (DCV), relative both to mutants lacking Wolbachia and to wild type flies with and without Wolbachia. The insulin mutant flies had higher Wolbachia titres than wild type flies. By RNA-seq analysis of the Wolbachia transcriptome, we identified Wolbachia genes that were more strongly expressed in dilp2-3,5 mutant flies. Ankyrin-domain-containing proteins were among the most strongly up-regulated and they are predicted to be secreted effector proteins. To address their effect on host physiology, we generated 4 transgenic fly lines each with inducible expression of a different genes encoding ankyrin-domain-containing proteins. Expression of 3 of these did not cause obvious effects, but expression of WD0754 at high levels severely shortened fly survival. Interestingly, however, chronic low-level induction of WD0754 increased the resistance of the flies to DCV infection. Proteomics analysis showed a robust, tissue-specific, anti-viral response upon WD0754 induction, and identified the NFkB-like IMD pathway as a potential mediator of the antiviral activity of WD0754. Consistently, WD0754 expression activated Relish, a key downstream transcriptional mediator of IMD signalling, while loss-of Relish blocked the antiviral effect of WD0754. In summary, we identified a Wolbachia-derived ankyrin domain containing protein that modulates host immunity through the IMD pathway.

molecular biology↗

bioRxiv2019

In vivo mRNA structure regulates miRNA cleavage in Arabidopsis

MicroRNA (miRNA)-mediated cleavage is involved in numerous essential cellular pathways. miRNAs recognize target RNAs via sequence complementarity. In addition to complementarity, in vitro and in silico studies have suggested that RNA structure may influence the accessibility of mRNAs to miRNA-Induced Silencing Complexes (miRISCs), thereby affecting RNA silencing. However, the regulatory mechanism of mRNA structure in miRNA cleavage remains elusive. Here, we investigated the role of in vivo RNA secondary structure in miRNA cleavage by developing the new CAP-STRUCTURE-seq method to capture the intact mRNA structurome in Arabidopsis thaliana. This approach revealed that miRNA target sites were not structurally accessible for miRISC binding prior to cleavage in vivo. Instead, the unfolding of the target site structure is the primary determinant for miRISC activity in vivo. Notably, we found that the single-strandedness of the two nucleotides immediately downstream of the target site, named Target Adjacent structure Motif (TAM), can promote miRNA cleavage but not miRNA binding, thus decoupling target site binding from cleavage. Our findings demonstrate that mRNA structure in vivo can regulate miRNA cleavage, providing evidence of mRNA structure-dependent regulation of biological processes.

molecular biology↗

bioRxiv2021

OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data

Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting of genes using newly developed tools such as CRISPR-based gene modulation. A number of methods have used transcriptomics data to predict operons, based on the premise that contiguous genes in an operon will be expressed at similar levels. While promising results have been observed using these methods, most of them do not address uncertainty caused by technical variability between experiments, which is especially relevant when the amount of data available is small. In addition, many existing methods do not provide the flexibility to determine whether the stringency with which genes should be evaluated for being in an operon pair. We present OperonSEQer, a set of machine learning algorithms that uses the statistic and p-value from a non-parametric analysis of variance test (Kruskal-Wallis) to determine the likelihood that two adjacent genes are expressed from the same RNA molecule. We implement a voting system to allow users to choose the stringency of operon calls depending on whether your priority is high coverage of operons or high accuracy of the calls. In addition, we provide the code so that users can retrain the algorithm and re-establish hyperparameters based on any data they choose, allowing for this method to be expanded on as additional data is generated and incorporated. We show that our approach detects operon pairs that are missed by current methods by comparing our predictions to publicly available long-read sequencing data. OperonSEQer therefore improves on existing methods in terms of accuracy, flexibility and adaptability. Author SummaryBacteria and archaea, single-cell organisms collectively known as prokaryotes, live in all imaginable environments and comprise the majority of living organisms on this planet. Prokaryotes play a critical role in the homeostasis of multicellular organisms (such as animals and plants) and ecosystems. In addition, bacteria can be pathogenic, and cause a variety of diseases in these same hosts and ecosystems. In short, understanding the biology and molecular functions of bacteria and archaea and devising mechanisms to engineer and optimize their properties are critical scientific endeavors with significant implications in healthcare, agriculture, manufacturing and climate science among others. One major molecular difference between unicellular and multicellular organisms is the way the express genes - rather than making individual RNA molecules like multicellular organisms, prokaryotes express genes in long contiguous RNA molecules known as operons, which are subsequently processed. Understanding which genes exist within operons is critical for elucidating basic biology and for engineering organisms. In this work, we use a combination of statistical and machine learning-based methods to use next-generation sequencing data to predict operon structure across a range of prokaryotes. Our method provides a easily implemented, robust, accurate and flexible way to determine operon structure in an organism-agnosic manner using readily-available data.

bioinformatics↗