Biology subjects

Zhao, J.

Publications and source records attributed to Zhao, J..

At least 253 records · Page 14Linked to original sources

bioRxiv2024

Short heat shock factor A2 confers heat sensitivity in Arabidopsis: Insights into heat resistance and growth balance

Cells prevent heat damage through the highly conserved canonical heat stress response (HSR), where heat shock factors (HSFs) bind heat shock elements (HSEs) to activate heat shock proteins (HSPs). Plants generate short HSFs (S-HSFs) derived from HSF splicing variants, yet their functions remain poorly understood. While an enhanced canonical HSR confers thermotolerance, its hyperactivation inhibits plant growth. How plants prevent this hyperactivation to ensure proper growth remains unknown. Here, we report that Arabidopsis S-HsfA2, S-HsfA4c, and S-HsfB1 confer sensitivity to extreme heat (45 {degrees}C) and constitute new HSF types featuring a unique truncated DNA-binding domain (tDBD). This tDBD binds a new heat-regulated element (HRE), which confers minimal promoter heat-responsiveness and exhibits heat stress sensing and transmission patterns. Using S-HsfA2, we investigated whether and how S-HSFs prevent canonical HSR hyperactivation. HSP17.6B, a common direct target of HsfA2 and S-HsfA2, confers thermotolerance; however, its overexpression partially causes HSR hyperactivation. Moreover, HRE-HRE-like and HSE elements mediate the HSP17.6B promoters heat response. We further show S-HsfA2 alleviates hyperactivation via two mechanisms: 1) S-HsfA2 negatively regulates HSP17.6B via the HRE-HRE-like element, establishing a noncanonical HSR (S-HsfA2-HRE-HSP17.6B) that antagonistically represses HsfA2-activated HSP17.6B expression. 2) S-HsfA2 binds the HsfA2 DBD, preventing HsfA2 from binding HSEs and thereby attenuating HsfA2-activated HSP17.6B promoter activity. Overall, our findings highlight the essential role of S-HsfA2 in preventing hyperactivation of plant heat tolerance to maintain proper growth.

plant biology↗

bioRxiv2024

Bayesian Occam's Razor to Optimize Models for Complex Systems

Modeling complex biological systems necessitates the integration of vast and multifaceted information spanning various aspects of these systems, and is expected to yield more insights into the system than any of the inputs. Metamodeling, a specialized form of integrative modeling, addresses this by integrating existing models. Developing and optimizing metamodels pose challenges due to the complexities introduced by diverse input models and their inherent uncertainties. In this study, we employ Bayesian formalism to rigorously analyze the propagation of probability throughout the metamodeling process and propose quantitative assessments for it. Building on this, we introduce a method for optimizing metamodeling that adheres to the Bayesian Occams razor rationale, by (i) minimizing model uncertainty; (ii) maximizing model consistency; and (iii) reducing model complexity. To illustrate the benefits of this method, we apply it to the dynamic system of glucose-stimulated insulin secretion in pancreatic {beta}-cells. The optimized metamodel delivers more accurate estimates of impaired {beta}-cell dynamics and function in T2D subjects compared to the non-optimized one, underscoring the critical role of optimization in enhancing both model reliability and applicability. This method is implemented through the Integrative Modeling Platform (IMP), facilitating the development of accurate, precise, and sufficiently simple models for a variety of complex systems.

bioinformatics↗

bioRxiv2024

Efficient small fragment sequencing of human, cow, and bison miRNA, small RNA or csRNA-seq libraries using AVITI

Next-Generation Sequencing (NGS) catalyzed breakthroughs across various scientific domains. Illuminas sequencing by synthesis method has long been essential for NGS but emerging technologies like Element Biosciences sequencing by avidity (AVITI) represent a novel approach. It has been reported that AVITI offers improved signal-to-noise ratios and cost reductions. However, the method relies on rolling circle amplification which can be impacted by polymer size, raising questions about its efficacy sequencing small RNAs (sRNA) molecules including microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), and others that are crucial regulators of gene expression and involved in various biological processes. In addition, capturing capped small RNAs (csRNA-seq) has emerged as a powerful method to map active or "nascent" RNA polymerase II transcription initiation in tissues and clinical samples. Here, we report a new protocol for seamlessly sequencing short DNA fragments on the AVITI and demonstrate that AVITI and Illumina sequencing technologies equivalently capture human, cattle (Bos taurus) and the bison (Bison bison) sRNA or csRNA sequencing libraries, augmenting the confidence in both approaches. Additionally, analysis of generated nascent transcription start sites (TSSs) data for cattle and bison revealed inaccuracies in their current genome annotations and highlighted the possibility and need to translate small RNA sequencing methodologies to livestock. Our accelerated and optimized protocol therefore bridges the advantages of AVITI sequencing and critical methods that rely on sequencing short DNA fragments.

genomics↗

bioRxiv2024

Cell-type specific inference from bulk RNA-sequencing data by integrating single cell reference profiles via EPIC-unmix

Cell type specific (CTS) analysis is essential to reveal biological insights obscured in bulk tissue data. However, single-cell (sc) or single-nuclei (sn) resolution data are still cost-prohibitive for large-scale samples. Thus, computational methods to perform deconvolution from bulk tissue data are highly valuable. We here present EPIC-unmix, a novel two-step empirical Bayesian method integrating reference sc/sn RNA-seq data and bulk RNA-seq data from target samples to enhance the accuracy of CTS inference. We demonstrate through comprehensive simulations across three tissues that EPIC-unmix achieved 4.6% - 109.8% higher accuracy compared to alternative methods. By applying EPIC-unmix to human bulk brain RNA-seq data from the ROSMAP and MSBB cohorts, we identified multiple genes differentially expressed between Alzheimers disease (AD) cases versus controls in a CTS manner, including 57.4% novel genes not identified using similar sample size sc/snRNA-seq data, indicating the power of our in-silico approach. Among the 6-69% overlapping, 83%-100% are in consistent direction with those from sc/snRNA-seq data, supporting the reliability of our findings. EPIC-unmix inferred CTS expression profiles similarly empowers CTS eQTL analysis. Among the novel eQTLs, we highlight a microglia eQTL for AD risk gene AP3B2, obscured in bulk and missed by sc/snRNA-seq based eQTL analysis. The variant resides in a microglia-specific cCRE, forming chromatin loop with AP3B2 promoter region in microglia. Taken together, we believe EPIC-unmix will be a valuable tool to enable more powerful CTS analysis.

genomics↗

bioRxiv2024

Large scale loss-of-function mutations during chicken evolution and domestication

Evolution and domestication are often driven by genetic innovations, yet the role of gene loss remains debated. Here, we present comparative genomic analyses of four indigenous chicken breeds from Yunnan Province, China and a reference red jungle fowl genome (GRCg6a). We identify extensive gene presence-absence variation and large numbers of pseudogenes, revealing highly dynamic gene repertoires among closely related chickens. By reconstructing ancestral gene content, we estimate that the common ancestor harbored at least 21,972 genes, of which 7,993 are dispensable. Each lineage has independently lost thousands of genes through both complete gene loss and pseudogenization. These loss-of-function events are non-random: pseudogenization mutations are biased toward gene termini, frequently fixed in populations, and enriched in specific biological pathways. Notably, patterns of gene loss recapitulate phylogenetic relationships, suggesting that loss-of-function mutations are shaped by selection rather than neutral drift. Analysis of four other chicken genomes assembled using PacBio HiFi reads draws the same conclusion. Thus, our results support a model in which large-scale loss-of-function mutations are a major driver of chicken evolution and domestication, consistent with the "less-is-more" hypothesis of adaptive evolution.

bioinformatics↗

bioRxiv2024

NPD1/GPR37 axis protects painful traumatic brain injury and its complications

Patients with traumatic brain injury (TBI) frequently exhibit heightened pain and associated complications such as cognitive decline, depression, and anxiety. GPR37 is widely expressed in various brain regions, but its function remains largely unclear. We recently discovered neuroprotectin D1 (NPD1) as a novel GPR37 ligand. In this study, we examined the protective role of the NPD1/GPR37 signaling pathway in TBI-induced neuropathic pain and its complications. TBI was induced by closed-head impact and resulted in transient neuropathic pain for less than two weeks, showing periorbital and cutaneous mechanical allodynia/hyperalgesia, as well as motor deficiency and cognitive impairment. We found that peri-surgical treatment with NPD1, effectively prevented TBI-induced mechanical hypersensitivity, motor deficiency, and cognitive impairment. NPD1 treatment also substantially inhibited TBI-induced microgliosis, astrogliosis (including A1 astrocyte markers), and neuroinflammation in the sensory cortex and hippocampus. RNA sequencing and GO enrichment analysis revealed downregulations of genes related to "calcium ion homeostasis," and "GPCR signaling pathway" in the TBI-affected brain. These downregulations were restored by NPD1 treatment. RNAscope in situ hybridization revealed predominant Gpr37 mRNA expression in oligodendrocytes. TBI resulted in rapid and remarkable demyelination and downregulation of Gpr37 mRNA expression in oligodendrocytes, and both were protected by NPD1 treatment. NPD1s inhibition of periorbital and cutaneous mechanical pain was abolished in Gpr37-/- mice. Moreover, TBI-induced neuropathic pain was prolonged by swimming stress, and NPD1 treatment prevented the stress-induced transition from acute to chronic pain in wild-type mice but not Gpr37-/- mice. Finally, chronic pain was associated with depression and anxiety, and NPD1 treatment mitigated these chronic pain complications through GPR37. Thus, through modulation of demyelination, diverse responses of glial cells, and neuroinflammation, the NPD1/GPR37 axis serves as a protective mechanism and a therapeutic target against painful traumatic brain injury and its complications.

animal behavior and cognition↗

bioRxiv2024

Interleukin-1 prevents SARS-CoV-2-induced membrane fusion to restrict viral transmission via induction of actin bundles

Innate immune responses triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection play pivotal roles in the pathogenesis of COVID-19, while host factors including pro-inflammatory cytokines are critical for viral containment. By utilizing quantitative and qualitative models, we discovered that soluble factors secreted by human monocytes potently inhibit SARS-CoV-2-induced cell-cell fusion in viral-infected cells. Through cytokine screening, we identified that interleukin-1{beta} (IL-1{beta}), a key mediator of inflammation, inhibits syncytia formation mediated by various SARS-CoV-2 strains. Mechanistically, IL-1{beta} activates RhoA/ROCK signaling through a non-canonical IL-1 receptor-dependent pathway, which drives the enrichment of actin bundles at the cell-cell junctions, thus prevents syncytia formation. Notably, in vivo infection experiments in mice confirms that IL-1{beta} significantly restricted SARS-CoV-2 spreading in the lung epithelia. Together, by revealing the function and underlying mechanism of IL-1{beta} on SARS-CoV-2-induced cell-cell fusion, our study highlights an unprecedented antiviral function for cytokines during viral infection.

immunology↗

bioRxiv2024

IL-4 Licenses B Cell Activation Through Cholesterol Synthesis

Lymphocyte activation involves a transition from quiescence and associated catabolic metabolism to a metabolic state with noted similarities to cancer cells such as heavy reliance on aerobic glycolysis for energy demands and increased nutrient requirements for biomass accumulation and cell division1-3. Following antigen receptor ligation, lymphocytes require spatiotemporally distinct "second signals". These include costimulatory receptor or cytokine signaling, which engage discrete programs that often involve remodeling of organelles and increased nutrient uptake or synthesis to meet changing biochemical demands4-6. One such signaling molecule, IL-4, is a highly pleiotropic cytokine that was first identified as a B cell co-mitogen over 30 years ago7. However, how IL-4 signaling mechanistically supports B cell proliferation is incompletely understood. Here, using single cell RNA sequencing we find that the cholesterol biosynthetic program is transcriptionally upregulated following IL-4 signaling during the early B cell response to influenza virus infection, and is required for B cell activation in vivo. By limiting lipid availability in vitro, we determine cholesterol to be essential for B cells to expand their endoplasmic reticulum, progress through cell cycle, and proliferate. In sum, we demonstrate that the well-known ability of IL-4 to act as a B cell growth factor is through a previously unknown rewiring of specific lipid anabolic programs, relieving sensitivity of cells to environmental nutrient availability.

immunology↗

bioRxiv2024

MAST-Decon: Smooth Cell-type Deconvolution Method for Spatial Transcriptomics Data

AO_SCPLOWBSTRACTC_SCPLOWSpatial transcriptomics (ST) technologies have gained increasing popularity due to their ability to provide positional context of gene expressions in a tissue. One major limitation of current commercially available ST methods such as the 10X Genomics Visium platform is the lack of single cell resolution. Cell type deconvolution for ST data is critical in order to fully reveal underlying biological mechanisms. Existing ST data deconvolution methods share two common limitations: first, few of them utilize spatial neighborhood information. Existing methods such as RCTD and SPOTlight intrinsically treat each spatial spot as independent of neighboring spots, although we anticipate nearby spots to share similar cell type compositions based on clinical evidence of tissue structures. Such limitation could be amplified when sequencing depths at single spots are relatively low so that borrowing information from neighboring spots is necessary in order to obtain reliable deconvolution results. Second, although Visium data provide us with a histological image which could add additional information regarding spot heterogeneity, most existing methods do not utilize this H&E image. To solve these two limitations, we developed Multiscale Adaptive ST Deconvolution (MAST-Decon), a smooth deconvolution method for ST data. MAST-Decon uses a weighted likelihood approach and incorporates both gene expression data, spatial neighborhood information and H&E image features by constructing different kernel functions to obtain a smooth deconvolution result. We showcased the strength of MAST-Decon through simulations based on real data, including a single-cell dataset of mouse brain primary visual cortex, and real-world Visium datasets to demonstrate its robust and superior performance compared with other state-of-the-art methods.

genomics↗

bioRxiv2024

Near infrared fluorescent nanosensors for high spatiotemporal oxytocin imaging

Oxytocin is a neuropeptide involved in regulating social and emotional behavior. Current techniques for oxytocin imaging are generally limited in spatial and temporal resolution, real-time imaging capacity, selectivity for oxytocin over vasopressin, and application in young and non-model organisms. To address these issues, we developed a method to evolve purely synthetic molecular recognition for oxytocin on the surface of near-infrared fluorescent single-walled carbon nanotubes (SWCNT) using single-stranded DNA (ssDNA). The best-performing nanosensor nIROT-SELEC reversibly undergoes up to a 172% fluorescence increase in response to oxytocin with micromolar dissociation, nanomolar limit of detection, and and high selectivity over oxytocin analogs, receptor agonists and antagonists, and co-released neurochemicals. We next demonstrated the versatility of nIROT-SELEC by performing live imaging of synaptic evoked oxytocin released in acute brain slices of mice and prairie voles. Our method for high throughput evolution of neuropeptide nanosensors holds promise to enable synaptic scale visualization of neuropeptide signaling in the brain cross different species and developmental stages, to advance the study of neurochemical signaling for its role in both health and disease.

neuroscience↗

bioRxiv2024

CRISPR Screening Uncovers a Long-Range Enhancer for ONECUT1 in Pancreatic Differentiation and Links a Diabetes Risk Variant

Functional enhancer annotation is a valuable first step for understanding tissue-specific transcriptional regulation and prioritizing disease-associated non-coding variants for investigation. However, unbiased enhancer discovery in physiologically relevant contexts remains a major challenge. To discover regulatory elements pertinent to diabetes, we conducted a CRISPR interference screen in the human pluripotent stem cell (hPSC) pancreatic differentiation system. Among the enhancers uncovered, we focused on a long-range enhancer [~]664 kb from the ONECUT1 promoter, since coding mutations in ONECUT1 cause pancreatic hypoplasia and neonatal diabetes. Homozygous enhancer deletion in hPSCs was associated with a near-complete loss of ONECUT1 gene expression and compromised pancreatic differentiation. This enhancer contains a confidently fine-mapped type 2 diabetes associated variant (rs528350911) which disrupts a GATA motif. Introduction of the risk variant into hPSCs revealed substantially reduced binding of key pancreatic transcription factors (GATA4, GATA6 and FOXA2) on the edited allele, accompanied by a slight reduction of ONECUT1 transcription, supporting a causal role for this risk variant in metabolic disease. This work expands our knowledge about transcriptional regulation in pancreatic development through the characterization of a long-range enhancer and highlights the utility of enhancer discovery in disease-relevant settings for understanding monogenic and complex disease.

developmental biology↗

bioRxiv2024

Evolution of a Eukaryotic Transcription Factor's co-TF Dependence Involves Multiple Intrinsically Disordered Regions Affecting Activation and Autoinhibition

Combinatorial control by transcription factors (TFs) is central to eukaryotic gene regulation, yet its mechanism, evolution, and regulatory impact are not well understood. Here we use natural variation in the yeast phosphate starvation (PHO) response to examine the genetic basis and species variation in TF interdependence. In Saccharomyces cerevisiae, main TF Pho4 relies on the co-TF Pho2 to regulate [~]28 genes, whereas in the related pathogen Candida glabrata, Pho4 has reduced Pho2 dependence and regulates [~]70 genes. We found C. glabrata Pho4 (CgPho4) binds the same motif with 3-4 fold higher affinity. Machine learning and yeast one-hybrid assay identify two intrinsically disordered regions (IDRs) in CgPho4 that boost its activation domains activity. In ScPho4, an IDR next to the DNA binding domain both allows for enhanced activity with Pho2 and inhibits activity without Pho2. This study reveals how IDR divergence drives TF interdependence evolution by influencing activation potential and autoinhibition.

evolutionary biology↗

bioRxiv2024

Utility Analyses of AVITI Sequencing Chemistry

BackgroundDNA sequencing is a critical tool in modern biology. Over the last two decades, it has been revolutionized by the advent of massively parallel sequencing, leading to significant advances in the genome and transcriptome sequencing of various organisms. Nevertheless, challenges with accuracy, lack of competitive options and prohibitive costs associated with high throughput parallel short-read sequencing persist. ResultsHere, we conduct a comparative analysis using matched DNA and RNA short-reads assays between Element Biosciences AVITI and Illuminas NextSeq 550 chemistries. Similar comparisons were evaluated for synthetic long-read sequencing for RNA and targeted single-cell transcripts between the AVITI and Illuminas NovaSeq 6000. For both DNA and RNA short-read applications, the study found that the AVITI produced significantly higher per sequence quality scores. For PCR-free DNA libraries, we observed an average 89.7% lower experimentally determined error rate when using the AVITI chemistry, compared to the NextSeq 550. For short-read RNA quantification, AVITI platform had an average of 32.5% lower error rate than that for NextSeq 550. With regards to synthetic long-read mRNA and targeted synthetic long read single cell mRNA sequencing, both platforms respective chemistries performed comparably in quantification of genes and isoforms. The AVITI displayed a marginally lower error rate for long reads, with fewer chemistry-specific errors and a higher mutation detection rate. ConclusionThese results point to the potential of the AVITI platform as a competitive candidate in high-throughput short read sequencing analyses when juxtaposed with the Illumina NextSeq 550.

genomics↗

bioRxiv2024

A New Large-Scale Extracellular Vesicle Production Strategy for Biomedical Drug Development

1.Extracellular Vesicles (EVs) are nanoscale to microscale membranous vesicles released by cells. They are vital for intercellular communications in physiological and pathological conditions, offering immense potential in diagnostics and therapeutical applications due to their ability to transfer diverse biological cargos between cells. While research of EVs is continuously gaining popularity in academia, large-scale manufacturing aiming for clinical applications remains challenging. Herein, we introduce a novel large-scale EV production strategy, including an upstream process with fed-batch suspension HEK293 cell culture, and a downstream process with chromatographic purification for ultra-pure EVs. Such promising EV production strategy enables the potential capability of large scale GMP manufacture of EVs for clinical applications.

bioengineering↗

bioRxiv2024

Massively parallel jumping assay decodes Alu retrotransposition activity

The human genome contains millions of retrotransposons, several of which could become active due to somatic mutations having phenotypic consequences, including disease. However, it is not thoroughly understood how nucleotide changes in retrotransposons affect their jumping activity. Here, we developed a novel massively parallel jumping assay (MPJA) that can test the jumping potential of thousands of transposons en masse. We generated nucleotide variant library of selected four Alu retrotransposons containing 165,087 different haplotypes and tested them for their jumping ability using MPJA. We found 66,821 unique jumping haplotypes, allowing us to pinpoint domains and variants vital for transposition. Mapping these variants to the Alu-RNA secondary structure revealed stem-loop features that contribute to jumping potential. Combined, our work provides a novel high-throughput assay that assesses the ability of retrotransposons to jump and identifies nucleotide changes that have the potential to reactivate them in the human genome.

genomics↗

bioRxiv2024

Prominent involvement of acetylcholine in shaping stable olfactory representation across the Drosophila brain

Despite the vital role of neuromodulation in the neural system, the specific spatiotemporal dynamics of neuromodulators and their interactions with neuronal activities in vivo are still unclear, hampering our understanding of their information representation and functional contributions systemically. To address this problem, we employed two-photon synthetic aperture microscopy (2pSAM) to record long-term neuronal and neuromodulatory olfactory responses across the Drosophila brain at high speed. Our results revealed distinct response properties, global information propagation, functional connectivity, and odor identity representation among neuronal, cholinergic, and serotoninergic dynamics across multiple brain regions. We discovered the compensation between neuronal activity and cholinergic dynamics, both in the odor identity representation across the brain and the functional connectivity network structures of specific brain regions. Moreover, employing low-dimensional manifold and functional connectivity network analyses, we characterized the stable representation of cholinergic dynamics over a long term. Collectively, our unbiased and comprehensive investigation unveiled the prominent involvement of acetylcholine (ACh) in shaping olfactory representation across the brain, underscoring the inadequacy of solely considering neuronal activities when examining information representation of the brain.

neuroscience↗

bioRxiv2024

A rapid and efficient in vivo inoculation method for introducing tree stem canker pathogens onto leaves, suitable for large-scale assessment of resistance in poplar breeding progeny

Hybrid breeding, a direct and efficient strategy for disease control and management in tree species, is currently limited by the selection method of resist clones: the "in vitro stem segment inoculation method." This method, constrained by the availability of inoculating materials, cannot rapidly, efficiently, and cost-effectively screen the resistance of all hybrid clones. To overcome these limitations, we introduce a novel pathogen inoculation method for the resistance assessment of hybrid clones in the poplar-Valsa sordida pathosystem. This method involves inoculating the stem canker pathogen on the host leaf, a unique and promising approach we have successfully validated. Results showed that stem canker pathogen V. sordida induced the extended necrotic lesion and even induced the formation of pycnidium structure and conidia on the leaf surface five days after mycelium inoculation; 1) the upper 5-7th leaves exhibited higher resistance than the middle 18-20th leaves; 2) the shading conditions induced more severe symptoms on the leaves than lighting conditions; 3) the juvenile mycelium inoculums (4-day-cultured) were more susceptible to poplar leaves than the old ones (7-day-cultured). Our results demonstrate the robustness of the "in vivo leaf inoculation method" in revealing the resistance differentiation in poplar hybrid clones. According to the leaf necrotic area disease index, we divided these poplar clones into seven different resistance groups. The resistance assessed by leaf assessment was validated in 15 selected poplar clones using the "in vitro stem segment inoculation method." Results showed that the effectiveness of these two methods was consistent. Moreover, the leaf inoculation method can be used to detect the pathogenicity diversity of the pathogen population of tree species. Compared to the conventional "in vitro stem segment inoculation method," the leaf method has the advantages of abundant inoculation materials, easy operation, rapid disease onset, and almost no adverse effect on the host. It is particularly suitable for the resistance screening of all progeny and the early (seedling) phenotypic selection of resistant poplar clones in poplar stem disease resistance breeding. The "in vivo leaf inoculation method" holds significant promise in poplar breeding, tree pathology, and molecular biology research on tree stem diseases.

plant biology↗

bioRxiv2024

BinDash 2.0: New MinHash Scheme Allows Ultra-fast and Accurate Genome Search and Comparisons

MotivationComparing large number of genomes in term of their genomic distance is becoming more and more challenging because there is an increasing number of microbial genomes deposited in public databases. Nowadays, we may need to estimate pairwise distances between millions or even billions of genomes. Few softwares can perform such comparisons efficiently. ResultsHere we update the multi-threaded software BinDash by implementing several new MinHash algorithms and computational optimization (e.g. Simple Instruction Multiple Data, SIMD) for ultra-fast and accurate genome search and comparisons at trillion scale. That is, we implemented b-bit one-permutation rolling MinHash with optimal/faster densification with SIMD. Now with BinDash 2, we can perform 0.1 trillion (or [~]10^11) pairs of genome comparisons in about 1.8 hours on a descent computer cluster or several hours on personal laptops, a [~]50% or more improvement over original version. The ANI (average nucleotide identity) estimated by BinDash is well correlated with other accurate but much slower ANI estimators such as FastANI or alignment-based ANI. In line with the findings from comparing 90K genomes ([~]10^9 comparisons) via FastANI, the 85% [~] 95% ANI gap is consistent in our study of [~]10^11 prokaryotic genome comparisons via BinDash2, which indicates fundamental ecological and evolutionary forces keeping species-like unit (e.g., > 95% ANI) together. Availability and implementationBinDash is released under the Apache 2.0 license at: https://github.com/zhaoxiaofei/bindash Contactkostas.konstantinidis@gatech.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗