Biology subjects

Singh, G.

Publications and source records attributed to Singh, G..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

SARS-CoV-2 antibodies cross-react and enhance dengue infection

The presence of non-neutralizing antibodies of any dengue serotype, increase the severity of subsequent infection by other dengue serotypes. During SARS-CoV-2 pandemic, the number of symptomatic dengue cases increased in India. We describe that antibodies isolated from convalescent plasma from COVID-19 patients enhances DENV2 infection in vitro. CR3022, one antibody against SARS-CoV-2 spike protein, also showed elevated DENV2 infection in vitro. In silico protein-protein interactions between the spike antibodies and the DENV2 E-protein revealed significant interactions. Likewise, few monoclonal/polyclonal antibodies against SARS-CoV-2 showed increased dengue infection in vitro. Importantly, the AG129 mice infected with SARS-CoV-2 three-weeks prior to DENV2 infection, showed elevated dengue pathogenesis. Thus, highlighting the possibilities of elevated infection and symptomatic dengue disease in COVID-19 survivors.

immunology↗

bioRxiv2023

Chromatinization Modulates Topoisomerase II Processivity

Type IIA topoisomerases are essential DNA processing enzymes that must robustly and reliably relax DNA torsional stress in vivo. While cellular processes constantly create different degrees of torsional stress, how this stress feeds back to control type IIA topoisomerase function remains obscure. Using a suite of single-molecule approaches, we examined the torsional impact on supercoiling relaxation of both naked DNA and chromatin by eukaryotic topoisomerase II (topo II). We observed that topo II was at least [~] 50-fold more processive on plectonemic DNA than previously estimated, capable of relaxing > 6000 turns. We further discovered that topo II could relax supercoiled DNA prior to plectoneme formation, but with a [~]100-fold reduction in processivity; strikingly, the relaxation rate in this regime decreased with diminishing torsion in a manner consistent with the capture of transient DNA loops by topo II. Chromatinization preserved the high processivity of the enzyme under high torsional stress. Interestingly, topo II was still highly processive ([~] 1000 turns) even under low torsional stress, consistent with the predisposition of chromatin to readily form DNA crossings. This work establishes that chromatin is a major stimulant of topo II function, capable of enhancing function even under low torsional stress.

biophysics↗

bioRxiv2023

Single cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

BackgroundThe encoding of cell intrinsic resistance states in breast cancer reflects the contributions of genomic and non-genomic variation. However, identifying the potential contributions of each requires accurate measurement and subtraction of the contribution of clonal fitness from co-measurement of transcriptional states. Somatic genomic variation in gene dosage, copy number variation, is the dominant mutational mechanism in breast cancer contributing to transcriptional variation and has recently been shown to contribute to platinum chemotherapy resistance states. Here we deploy time series measurements of triple negative breast cancer single cell transcriptomes in conjunction with co-measured single cell copy number associated clonal fitness to identify the contributions of genomic and non-genomic mechanisms to drug associated transcription states. ResultsWe generated serial scRNA-seq data (126,556 cells) from triple negative breast cancer (TNBC) patient-derived xenograft (PDX) experiments over 2.5 years in duration, and matched it against genomic copy number single cell data from the same biological samples. We show that the cell memory of transcriptional states of TNBC tumors serially exposed to platinum identifies distinct clonal responses within individual tumours. Copy-number clones with high drug fitness leading to clonal sweeps exhibit less transcriptional reversion, whereas clones with weak drug fitness exhibit highly dynamic transcription on drug withdrawal. Pathway analysis shows that copy number associated and copy number independent transcripts converge on epithelial-mesenchymal transition (EMT) and cytokine signaling states associated with resistance. We show from trajectory analysis that transcriptional reversion exhibits hysteresis, indicating that new intermediate transcriptional states are generated by platinum exposure. ConclusionsWe discovered that copy number clones with strong genotype associated fitness under platinum became fixed in their states, resulting in minimal transcriptional reversion on drug withdrawal. In contrast clones with weaker fitness undergo non-genomic transcriptional plasticity and these distinct responses co-exist within single tumours. Together the data suggest that copy number associated and copy number independent transcriptional states may contribute to platinum drug resistance within individual tumours. The dominance of genomic or non-genomic mechanisms within individual polyclonal tumours has implications for approaches to restoration of drug sensitivity and re-treatment strategies. Data availabilityUploaded Data URL: https://ega-archive.org/studies/EGAS00001007242 Github manuscript: https://github.com/molonc/drug_resistant_material/

genomics↗

bioRxiv2023

Tradeoffs of increasing temperatures for the spread of antimicrobial resistance in river biofilms

River microbial communities regularly act as the first defense barrier against the spread of antimicrobial resistance genes (ARG) that enter environmental microbiomes through wastewaters. However, how the invasion dynamics of wastewater-born ARGs into river biofilm communities will shift due to increasing average and peak temperatures worldwide through climate change remains unknown. Here we aimed at elucidating the effects of increasing temperatures on both, the natural river biofilm resistome, as well as the river biofilms invadability by foreign, wastewater-born ARGs. To achieve this, natural biofilms were grown in a pristine German river and transferred to artificial laboratory recirculation flume systems at three different temperatures (20{degrees}C, 25{degrees}C, 30{degrees}C). Already after one week of acclimatization to the temperatures, significant increases in the abundance of most naturally occurring ARGs were detected in the biofilms exposed to the highest temperature. Thereafter, biofilms were exposed to a single pulse of wastewater and the invasion dynamics of wastewater-born ARGs were analyzed over a period of two weeks. While initially after one day ARGs were able to invade all biofilms successfully and in equal proportions, the foreign invading ARGs were lost at a far increased rate at 30{degrees}C over time. ARG levels dropped to the initial natural levels at 30{degrees}C after 14 days. Contrary at the lower temperatures ARGs remained far elevated and certain ARGs were able to establish themselves in the biofilms. Overall, we here demonstrate tradeoffs of increasing temperature between increases in naturally occurring and faster loss dynamics of invading ARGs.

microbiology↗

bioRxiv2023

Mucosal antibody responses to SARS-CoV-2 booster vaccination and breakthrough infection

Coronavirus disease 2019 (COVID-19) vaccines have saved millions of lives. However, variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged causing large numbers of breakthrough infections. These developments necessitated the rollout of COVID-19 vaccine booster doses. It has been reported that mucosal antibody levels in the upper respiratory tract, especially for secretory IgA (sIgA), correlate with protection from infection with SARS-CoV-2. However, it is still unclear how high levels of mucosal antibodies can be induced. In this study, we measured serum IgG, saliva IgG and saliva sIgA responses in individuals who received COVID-19 mRNA booster vaccinations or who experienced breakthrough infections. We found that mRNA booster doses could induce robust serum and saliva IgG responses, especially in individuals who had not experienced infections before, but saliva sIgA responses were weak. In contrast, breakthrough infections in individuals who had received the primary mRNA vaccination series induced robust serum and saliva IgG as well as saliva sIgA responses. Individuals who had received a booster dose and then had a breakthrough infection showed low IgG induction in serum and saliva but still responded with robust saliva sIgA induction. These data suggest that upper respiratory tract exposure to antigen is an efficient way of inducing mucosal sIgA while exposure via intramuscular injection is not. ImportanceAntibodies on mucosal surfaces of the upper respiratory tract have been shown to be important for protection from infection with SARS-CoV-2. Here we investigate the induction of serum IgG, saliva IgG and saliva sIgA after COVID-19 mRNA booster vaccination or breakthrough infections.

immunology↗

bioRxiv2023

Unravelling the novel genetic diversity and marker-trait associations of corn leaf aphid resistance in wheat using microsatellite markers

The study was conducted to identify novel simple sequence repeat (SSR) markers associated with resistance to corn aphid (CLA), Rhopalosiphum maidis L. in 48 selected bread wheat (Triticum aestivum L.) and wild wheat (Aegilops spp. & T. dicoccoides) genotypes during two consecutive cropping seasons (2018-19 and 2019-20). A total of 51 polymorphic markers containing 143 alleles were used for the analysis. The frequency of the major allele ranged from 0.552 (Xgwm113) to 0.938 (Xcfd45, Xgwm194 and Xgwm526), with a mean of 0.731. Gene diversity ranged from 0.116 (Xgwm526) to 0.489 (Xgwm113), with a mean of 0.354. The polymorphic information content (PIC) value for the SSR markers ranged from 0.107 (Xgwm526) to 0.370 (Xgwm113) with a mean of 0.282. The results of the STRUCTURE analysis revealed the presence of four main subgroups in the populations. Analysis of molecular variance (AMOVA) showed that the between-group difference was around 37% of the total variation contributed to the diversity by the whole germplasm, while 63% of the variation was attributed between individuals within the group. A general linear model (GLM) was used to identify marker-trait associations, which detected a total of 23 and 27 significant new marker-trait associations (MTAs) at the p < 0.01 significance level during the 2018-19 and 2019-20 crop seasons, respectively. The findings of this study have important implications for the identification of molecular markers associated with CLA resistance. These markers can increase the accuracy and efficiency of aphid-resistant germplasm selection, ultimately facilitating the transfer of resistance traits to desirable wheat genotypes.

molecular biology↗

bioRxiv2023

Senescent Subtypes Transition Model

Senescence has both beneficial and detrimental roles across the tissues over time. This dual nature is mediated by the senescence-associated secretory phenotype (SASP). Still, transient and persistent SASP secretion is poorly understood. There are some unknown mechanisms through which phenotypic transition takes place from beneficial helper (H) senescent cells to deleterious (D) senescent cell states. NOTCH1 is suggested to mediate switching between the different SASP secretomes. NOTCH1 also suppresses a transcription factor C/EBP{beta} during the SASP secretion. Therefore, a hypothesis is proposed about the existence of negative feedback from C/EBP{beta} to NOTCH1 together forming a senescence-switching circuit that might be mediating this phenotypic transition at the molecular level. Using a population dynamics model with competitive interaction to decipher the underlying transition mechanism between the senescent cell subtypes and a mechanistic model to explain the underlying molecular mechanisms of NOTCH1 signaling in modulating the two waves of SASP secretion. By designing effective senescence therapies with selective removal of deleterious senescent cells and maintaining sufficient helper senescent cells can enhance health span and reduce age-related effects.

systems biology↗

bioRxiv2023

A Multi-omics Data Analysis Workflow Packaged as a FAIR Digital Object

BackgroundApplying good data management and FAIR data principles (Findable, Accessible, Interoperable, and Reusable) in research projects can help disentangle knowledge discovery, study result reproducibility, and data reuse in future studies. Based on the concepts of the original FAIR principles for research data, FAIR principles for research software were recently proposed. FAIR Digital Objects enable discovery and reuse of Research Objects, including computational workflows for both humans and machines. Practical examples can help promote the adoption of FAIR practices for computational workflows in the research community. We developed a multi-omics data analysis workflow implementing FAIR practices to share it as a FAIR Digital Object. FindingsWe conducted a case study investigating shared patterns between multi-omics data and childhood externalizing behavior. The analysis workflow was implemented as a modular pipeline in the workflow manager Nextflow, including containers with software dependencies. We adhered to software development practices like version control, documentation, and licensing. Finally, the workflow was described with rich semantic metadata, packaged as a Research Object Crate, and shared via WorkflowHub. ConclusionsAlong with the packaged multi-omics data analysis workflow, we share our experiences adopting various FAIR practices and creating a FAIR Digital Object. We hope our experiences can help other researchers who develop omics data analysis workflows to turn FAIR principles into practice. O_TEXTBOXKey PointsO_LIThe FAIR4RS principles provide guidelines to enhance the discovery and reuse of research software. C_LIO_LIFAIR Digital Objects support Findability, Accessibility, Interoperability, and Reusability by both humans and machines. C_LIO_LIWe here demonstrate the implementation multi-omics data analysis workflow and share it as a FAIR Digital Object. C_LI C_TEXTBOX

bioinformatics↗

bioRxiv2023

Breakthrough infections by SARS-CoV-2 variants boost cross-reactive hybrid immune responses in mRNA-vaccinated Golden Syrian Hamsters

Hybrid immunity to SARS-CoV-2 provides superior protection to re-infection. We performed immune profiling studies during breakthrough infections in mRNA-vaccinated hamsters to evaluate hybrid immunity induction. mRNA vaccine, BNT162b2, was dosed to induce binding antibody titers against ancestral spike, but inefficient serum virus neutralization of ancestral SARS-CoV-2 or variants of concern (VoCs). Vaccination reduced morbidity and controlled lung virus titers for ancestral virus and Alpha but allowed breakthrough infections in Beta, Delta and Mu-challenged hamsters. Vaccination primed T cell responses that were boosted by infection. Infection back-boosted neutralizing antibody responses against ancestral virus and VoCs. Hybrid immunity resulted in more cross-reactive sera. Transcriptomics post-infection reflects both vaccination status and disease course and suggests a role for interstitial macrophages in vaccine-mediated protection. Therefore, protection by vaccination, even in the absence of high titers of neutralizing antibodies in the serum, correlates with recall of broadly reactive B and T-cell responses.

microbiology↗

bioRxiv2023

TGF-β Ligand Interactions in the Response of Caenorhabditis elegans to Bacterial Pathogens

The Transforming Growth Factor beta (TGF-{beta}) family consists of numerous secreted peptide growth factors that play significant roles in cell function, tissue patterning, and organismal homeostasis, including wound repair and immunity. Typically studied as homodimers, these ligands have the potential to diversify their functions through ligand interactions that are synergistic, cooperative, additive, and/or antagonistic. In the nematode Caenorhabditis elegans, there are only five TGF-{beta} ligands, providing an opportunity to dissect ligand interactions in fewer combinations than in vertebrates. As in vertebrates, these ligands can be divided into bone morphogenetic protein (BMP) and TGF-{beta}/Activin subfamilies that predominantly signal through discrete signaling pathways. The BMP subfamily ligand DBL-1 has been well studied for its role in the innate immune response in C. elegans. Here we show that all five TGF-{beta} ligands play a role in the immune response. We also demonstrate that multiple TGF-{beta} ligands act cooperatively as part of this response. We show that the two BMP-like ligands - DBL-1 and TIG-2 - function independently of each other in the immune response, while TIG-2/BMP and the TGF-{beta}/Activin-like ligand TIG-3 function cooperatively. Structural modeling supports the potential for TIG-2 and TIG-3 to form heterodimers. Finally, we show that canonical DBL-1/BMP receptor and Smad signal transducers function in the response to bacterial pathogens, while components of the DAF-7 TGF-{beta}/Activin signaling pathway do not play a role in survival. These results demonstrate a novel potential for BMP and TGF-{beta}/Activin subfamily ligands to interact, and may provide a mechanism for distinguishing the developmental and homeostatic functions of these ligands from an acute response such as the innate immune response to bacterial pathogens.

physiology↗

bioRxiv2023

Different roles of dFOXO and HSF in spatio-temporal dynamics of stress-inducible Hsp70 in lgl-yorkie & lgl-Ras driven epithelial tumours in Drosophila

Oncogenic stress responses are critical modulators of tumour cell adaptation to hostile microenvironments and clonal dynamics. The evolutionarily conserved Hsp70 chaperone promotes tumour cell survival by suppressing apoptosis and facilitating metastatic progression. However, the temporal order and regulation of its expression in neoplastic tumours remains ill-defined. Here, we show a non-canonical regulation of Hsp70 expression during neoplastic transformation in the Drosophila wing epithelium. The malignant lgl ykiOE MARCM clones exhibited a delayed and progressive induction of Hsp70, tightly correlated with clonal expansion and tissue invasion. Loss of Hsp70 function in developing lgl ykiOE clones suppressed tumour growth in both larval wing discs and allograft assays, underscoring its significant role in tumour fitness and growth. We identify a non-canonical pathway where ROS-activated JNK signalling drives FOXO-dependent induction of Hsp70, bypassing HSF/Hif1, to promote tumour growth and invasion. Genetic disruption of Nox or JNK abrogated Hsp70 induction and curtailed tumour expansion. Stress adaptation and malignancy of developing lgl ykiOE epithelial tumour thus require Hsp70 as a redox-responsive, temporally regulated effector of the JNK-FOXO axis.

cell biology↗

bioRxiv2023

RawHash: Enabling Fast and Accurate Real-Time Analysis of Raw Nanopore Signals for Large Genomes

Nanopore sequencers generate electrical raw signals in real-time while sequencing long genomic strands. These raw signals can be analyzed as they are generated, providing an opportunity for real-time genome analysis. An important feature of nanopore sequencing, Read Until, can eject strands from sequencers without fully sequencing them, which provides opportunities to computationally reduce the sequencing time and cost. However, existing works utilizing Read Until either 1) require powerful computational resources that may not be available for portable sequencers or 2) lack scalability for large genomes, rendering them inaccurate or ineffective. We propose RawHash, the first mechanism that can accurately and efficiently perform real-time analysis of nanopore raw signals for large genomes using a hash-based similarity search. To enable this, RawHash ensures the signals corresponding to the same DNA content lead to the same hash value, regardless of the slight variations in these signals. RawHash achieves an accurate hash-based similarity search via an effective quantization of the raw signals such that signals corresponding to the same DNA content have the same quantized value and, subsequently, the same hash value. We evaluate RawHash on three applications: 1) read mapping, 2) relative abundance estimation, and 3) contamination analysis. Our evaluations show that RawHash is the only tool that can provide high accuracy and high throughput for analyzing large genomes in real-time. When compared to the state-of-the-art techniques, UNCALLED and Sigmap, RawHash provides 1) 25.8x and 3.4x better average throughput and 2) significantly better accuracy for large genomes, respectively. Source code is available at https://github.com/CMU-SAFARI/RawHash.

bioinformatics↗

bioRxiv2022

miR-17~92 Suppresses Proliferation and Invasion of Cervical Cancer Cells by Inhibiting Cell Cycle Regulator Cdt2

Cervical cancer (CC) is 4th largest killer of women worldwide when diagnosed in late stages the treatment options are almost negligible. 99% of CC is caused by high risk human papilloma viruses (HR-HPV). Upon integration into human genome the encoded viral proteins mis-regulates various onco-suppressor and checkpoint factors including cell cycle regulators. One such factor is cell cycle S phase licensing factor Cdt2, which has been reported to be highly upregulated in various cancers including CC. HPV proteins also suppress several tumor suppressor miRNAs concluding miR-17-92 cluster. In this study we report that miR-17-92 directly recruits to 3UTR of Cdt2 and downregulates this oncogene which suppresses the proliferation, migration, invasion capabilities of the CC cell lines while normal cells are fine. Suppression of Cdt2 by miR17-92 blocks the cancerous cells in S phase and induces apoptosis eventually leading to their death. Hence, our work for the first time mechanistically shows how miR17-92 could work as tumor suppressor opening up the potential of miR17-92 to be used in developing therapy for cervical cancer treatment.

cancer biology↗

bioRxiv2022

Protein Language Model for Prediction of Subcellular Localization of Protein Sequences from Gram-negative bacteria (ProtLM.SCL)

The prediction of bacterial protein Sub-Cellular Localization (SCL) is critical for antigen identification and reverse vaccinology, especially when determining protein localization in the lab is time consuming, expensive and not possible for all species. While PSORTb is one of the most widely used tool for predicting SCL, it has several limitations, including the tendency to label a large number of proteins as Unknown. To address these shortcomings, we present a protein language model capable of predicting the subcellular localization of a given protein (ProtLM.SCL) from gram-negative bacteria. By performing 10-fold cross validation on the PSORTb public data set, we demonstrate that ProtLM.SCL is more accurate and precise than PSORTb. When compared to empirically validated published data, our models also outperformed PSORTb, particularly when categorizing difficult occurrences.

bioinformatics↗

bioRxiv2022

Surface-modified measles vaccines encoding oligomeric, fusion-stabilized SARS-CoV-2 spike glycoproteins bypass measles seropositivity, boosting neutralizing antibody responses to omicron and historical variants.

Serum titers of SARS-CoV-2 neutralizing antibodies (nAb) correlate well with protection from symptomatic COVID-19, but decay rapidly in the months following vaccination or infection. In contrast, measles-protective nAb titers are life-long after measles vaccination, possibly due to persistence of the live-attenuated virus in lymphoid tissues. We therefore sought to generate a live recombinant measles vaccine capable of driving high SARS-CoV-2 nAb responses. Since previous clinical testing of a live measles vaccine encoding a SARS-CoV-2 spike glycoprotein resulted in suboptimal anti-spike antibody titers, our new vectors were designed to encode prefusion-stabilized SARS-CoV-2 spike glycoproteins, trimerized via an inserted peptide domain and displayed on a dodecahedral miniferritin scaffold. Additionally, to circumvent the blunting of vaccine efficacy by preformed anti-measles antibodies, we extensively modified the measles surface glycoproteins. Comprehensive in vivo mouse testing demonstrated potent induction of high titer nAb in measles-immune mice and confirmed the significant incremental contributions to overall potency afforded by prefusion stabilization, trimerization, and miniferritin-display of the SARS-CoV-2 spike glycoprotein, and vaccine resurfacing. In animals primed and boosted with a MeV vaccine encoding the ancestral SARS-CoV-2 spike, high titer nAb responses against ancestral virus strains were only weakly cross-reactive with the omicron variant. However, in primed animals that were boosted with a MeV vaccine encoding the omicron BA.1 spike, antibody titers to both ancestral and omicron strains were robustly elevated and the passive transfer of serum from these animals protected K18-ACE2 mice from infection and morbidity after exposure to BA.1 and WA1/2020 strains. Our results demonstrate that antigen engineering can enable the development of potent measles-based SARS-CoV-2 vaccine candidates.

microbiology↗

bioRxiv2022

TargetCall: Eliminating the Wasted Computation in Basecalling via Pre-Basecalling Filtering

Basecalling is an essential step in nanopore sequencing analysis where the raw signals of nanopore sequencers are converted into nucleotide sequences, i.e., reads. State-of-the-art basecallers employ complex deep learning models to achieve high basecalling accuracy. This makes basecalling computationally-inefficient and memory-hungry; bottlenecking the entire genome analysis pipeline. However, for many applications, the majority of reads do no match the reference genome of interest (i.e., target reference) and thus are discarded in later steps in the genomics pipeline, wasting the basecalling computation. To overcome this issue, we propose TargetCall, the first fast and widely-applicable pre-basecalling filter to eliminate the wasted computation in basecalling. TargetCalls key idea is to discard reads that will not match the target reference (i.e., off-target reads) prior to basecalling. TargetCall consists of two main components: (1) LightCall, a lightweight neural network basecaller that produces noisy reads; and (2) Similarity Check, which labels each of these noisy reads as on-target or off-target by matching them to the target reference. TargetCall filters out all off-target reads before basecalling; and the highly-accurate but slow basecalling is performed only on the raw signals whose noisy reads are labeled as on-target. Our thorough experimental evaluations using both real and simulated data show that TargetCall 1) improves the end-to-end basecalling performance of the state-of-the-art basecaller by 3.31 x while maintaining high (98.88%) sensitivity in keeping on-target reads, 2) maintains high accuracy in downstream analysis, 3) precisely filters out up to 94.71% of off-target reads, and 4) achieves better performance, sensitivity, and generality compared to prior works. We freely open-source TargetCall to aid future research in pre-basecalling filtering at https://github.com/CMU-SAFARI/TargetCall.

bioinformatics↗

bioRxiv2022

T-cell receptor specific protein language model for prediction and interpretation of epitope binding (ProtLM.TCR)

The cellular adaptive immune response relies on epitope recognition by T-cell receptors (TCRs). We used a language model for TCRs (ProtLM.TCR) to predict TCR-epitope binding. This model was pre-trained on a large set of TCR sequences (~62.106) before being fine-tuned to predict TCR-epitope bindings across multiple human leukocyte antigen (HLA) of class-I types. We then tested ProtLM.TCR on a balanced set of binders and non-binders for each epitope, avoiding model shortcuts like HLA categories. We compared pan-HLA versus HLA-specific models, and our results show that while computational prediction of novel TCR-epitope binding probability is feasible, more epitopes and diverse training datasets are required to achieve a better generalized performances in de novo epitope binding prediction tasks. We also show that ProtLM.TCR embeddings outperform BLOSUM scores and hand-crafted embeddings. Finally, we have used the LIME framework to examine the interpretability of these predictions.

bioinformatics↗

bioRxiv2022

BLEND: A Fast, Memory-Efficient, and Accurate Mechanism to Find Fuzzy Seed Matches in Genome Analysis

Generating the hash values of short subsequences, called seeds, enables quickly identifying similarities between genomic sequences by matching seeds with a single lookup of their hash values. However, these hash values can be used only for finding exact-matching seeds as the conventional hashing methods assign distinct hash values for different seeds, including highly similar seeds. Finding only exact-matching seeds causes either 1) increasing the use of the costly sequence alignment or 2) limited sensitivity. We introduce BLEND, the first efficient and accurate mechanism that can identify both exact-matching and highly similar seeds with a single lookup of their hash values, called fuzzy seed matches. BLEND 1) utilizes a technique called SimHash, that can generate the same hash value for similar sets, and 2) provides the proper mechanisms for using seeds as sets with the SimHash technique to find fuzzy seed matches efficiently. We show the benefits of BLEND when used in read overlapping and read mapping. For read overlapping, BLEND is faster by 2.4x-83.9x (on average 19.3x), has a lower memory footprint by 0.9x-14.1 x (on average 3.8x), and finds higher quality overlaps leading to accurate de novo assemblies than the state-of-the-art tool, minimap2. For read mapping, BLEND is fasterby 0.8x-4.1x (on average 1.7x) than minimap2. Source code is available at https://github.com/CMU-SAFARI/BLEND.

bioinformatics↗