Biology subjects

Warren, R.

Publications and source records attributed to Warren, R..

17 recordsLinked to original sources

bioRxiv2025

A molecular circuit regulates fate plasticity in emerging and adult AT2 cells

Alveolar AT1 and AT2 cells are vital for lung gas exchange and become compromised in several diseases. While key differentiation signals are known, their emergence and fate plasticity are unclear. Here we show in the embryonic lung that single AT2s emerge at intermediate zones, extrude, and connect with nearby epithelium via interlumenal junctioning. We observe that AT2s retain fate plasticity until the bZIP transcription factor C/EBP suppresses Notch signaling at a novel Dlk1 enhancer. Both Dlk1 and Cebpa are regulated by the polycomb repressive complex (PRC2), which together form a "pulse generator" circuit that times Dlk1 expression and thus Notch activation, resulting in a "salt and pepper" pattern of AT1 and AT2 fate. In injured adult lungs, C/EBP downregulation is required to re-access AT2 fate plasticity and is mediated by the dominant negative C/EBP family member CHOP. Finally, Cebpa loss also activates a "defender" AT2 state, distinct from its reparative state, and we propose AT2s toggle between either state following infection to protect and repair alveoli.

developmental biology↗

bioRxiv2024

Systematic review and meta-analysis of protocols and yield of direct from sputum sequencing of Mycobacterium tuberculosis

Direct sputum whole genome sequencing (dsWGS) can revolutionize Mycobacterium tuberculosis (Mtb) diagnosis by enabling rapid detection of drug resistance and strain diversity without the biohazard of culture. We searched PubMed, Web of Science and Google scholar, and identified 8 studies that met inclusion criteria for testing protocols for dsWGS. Utilising meta-regression we identify several key factors positively associated with dsWGS success, including higher Mtb bacillary load, mechanical disruption, and enzymatic/chemical lysis. Specifically, smear grades of 3+ (OR = 14.7, 95% CI: 3.5, 62.1; p = 0.0005) were strongly associated with improved outcomes, whereas decontamination with sodium hydroxide (NaOH) was negatively associated (OR = 0.005, 95% CI: 0.001, 0.03; p = 7e-06), likely due to its harsh effects on Mtb cells. Furthermore, mechanical lysis (OR = 193.3, 95% CI: 11.7, 3197.8; p = 0.008) and enzymatic/chemical lysis (OR = 18.5, 95% CI: 1.9, 183.1; p = 0.02) were also strongly associated with improved dsWGS. Across the studies, we observed a high degree of variability in approaches to sputum pre-processing prior to dsWGS highlighting the need for standardized best practices. In particular we conclude that optimizing pre-processing steps including decontamination with the exploration of alternatives to NaOH to better preserve Mtb cells and DNA, and best practices for cell lysis during DNA extraction as priorities. Further and considering the strong association between Mtb load and successful dsWGS, protocol improvements for optimal sputum sample collection, handling, and storage could also further enhance the success rate of dsWGS.

microbiology↗

bioRxiv2023

Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools

Contemporary pose estimation methods enable precise measurements of behavior via supervised deep learning with hand-labeled video frames. Although effective in many cases, the supervised approach requires extensive labeling and often produces outputs that are unreliable for downstream analyses. Here, we introduce "Lightning Pose," an efficient pose estimation package with three algorithmic contributions. First, in addition to training on a few labeled video frames, we use many unlabeled videos and penalize the network whenever its predictions violate motion continuity, multiple-view geometry, and posture plausibility (semi-supervised learning). Second, we introduce a network architecture that resolves occlusions by predicting pose on any given frame using surrounding unlabeled frames. Third, we refine the pose predictions post-hoc by combining ensembling and Kalman smoothing. Together, these components render pose trajectories more accurate and scientifically usable. We release a cloud application that allows users to label data, train networks, and predict new videos directly from the browser.

neuroscience↗

bioRxiv2022

Hippo signaling impairs alveolar epithelial regeneration in pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) consists of fibrotic alveolar remodeling and progressive loss of pulmonary function. Genetic and experimental evidence indicate that chronic alveolar injury and failure to properly repair the respiratory epithelium are intrinsic to IPF pathogenesis. Loss of alveolar type 2 (AT2) stem cells or mutations that either impair their self-renewal and/or impair their differentiation into AT1 cells can serve as a trigger of pulmonary fibrosis. Recent reports indicate increased YAP activity in respiratory epithelial cells in IPF lungs. Individual IPF epithelial cells with aberrant Yap activation in bronchiolized regions frequently co-express AT1, AT2, conducting airway selective markers and even mesenchymal or EMT markers, demonstrating "indeterminate" states of differentiation and suggesting that aberrant Yap signaling might promote pulmonary fibrosis. Yet, Yap and Taz have recently also been shown to be important for AT1 cell maintenance and alveolar epithelial regeneration after Streptococcus pneumoniae induced injury. To investigate how epithelial Yap/Taz might promote pulmonary fibrosis or drive alveolar epithelial regeneration, we inactivated the Hippo pathway in AT2 stem cells resulting in increased nuclear Yap/Taz and found that this promotes their alveolar regenerative capacity and reduces pulmonary fibrosis following bleomycin injury by pushing them along the AT1 cell lineage. Vice versa, inactivation of both Yap and Taz or Taz alone in AT2 cells stem cells impaired alveolar epithelial regeneration and resulted in increased pulmonary fibrosis upon bleomycin injury. Interestingly, inactivation of only Yap in AT2 stem cells promoted alveolar epithelial regeneration and reduced pulmonary fibrosis. Together, these data suggest that epithelial Yap promotes, and epithelial Taz reduces pulmonary fibrosis suggesting that targeting Yap but not Taz mediated transcription might help promote AT1 cell regeneration and treat pulmonary fibrosis.

developmental biology↗

bioRxiv2022

A thousand-genome panel retraces the global spread and climatic adaptation of a major crop pathogen

Human activity impacts the evolutionary trajectories of many species worldwide. Global trade of agricultural goods contributes to the dispersal of pathogens reshaping their genetic makeup and providing opportunities for virulence gains. Understanding how pathogens surmount control strategies and cope with new climates is crucial to predicting the future impact of crop pathogens. Here, we address this by assembling a global thousand-genome panel of Zymoseptoria tritici, a major fungal pathogen of wheat reported in all production areas worldwide. We identify the global invasion routes and ongoing genetic exchange of the pathogen among wheat-growing regions. We find that the global expansion was accompanied by increased activity of transposable elements and weakened genomic defenses. Finally, we find significant standing variation for adaptation to new climates encountered during the global spread. Our work shows how large population genomic panels enable deep insights into the evolutionary trajectory of a major crop pathogen.

genomics↗

bioRxiv2022

Condition-Specific Mapping of Operons (COSMO) using dynamic and static genome data

An operon is a set of adjacent genes which are transcribed into a single messenger RNA. Operons allow prokaryotes to efficiently circumvent environmental stresses. It is estimated that about 60% of the Mycobacterium tuberculosis genome is arranged into operons, which makes them interesting drug targets in the face of emerging drug resistance. We therefore developed COSMO - a tool for operon prediction in M. tuberculosis using RNA-seq data. We analyzed four algorithmic parameters and benchmarked COSMO against two top performing operon predictors. COSMO outperformed both predictors in its accuracy and in its ability to distinguish operons activated under distinct conditions. Author SummaryOperons may be important drug targets for the development of effective anti-microbials to combat the emerging, global drug resistance challenge. However, there is a shortage of known Mycobacterium tuberculosis (Mtb) operons. This is exacerbated by the fact that current operon predictors are not optimized for the unique genome of Mtb. COSMO removes the limitations imposed by using the constraints of a specific organisms genome and exploits RNA-seq data instead. This allows COSMO to more accurately predict full-length operons in Mtb, and it also avails COSMO to other microorganisms for the same purpose.

bioinformatics↗

bioRxiv2022

More than Mycobacterium tuberculosis: specific site-of-disease microbial communities, functional capacities, and their distinct clinical profiles in tuberculous lymphadenitis

BackgroundLymphadenitis is the most common extrapulmonary tuberculosis (EPTB) manifestation and a major cause of death. The microbiome is important to human health but uninvestigated in EPTB. We profiled the site-of-disease lymph node microbiome in tuberculosis lymphadenitis (TBL). MethodsFine needle aspiration biopsies (FNABs) were collected from 159 pre-treatment presumptive TBL patients in Cape Town, South Africa. 16S Illumina MiSeq rRNA gene sequencing was done. ResultsWe analysed 89 definite TBLs (dTBLs) and 61 non-TBLs (nTBLs), which had similar -but different {beta}-diversities (p=0.001). Clustering identified five lymphotypes prior to TB status stratification: Mycobacterium-, Prevotella- and Streptococcus-dominant lymphotypes were more frequent in dTBLs whereas a Corynebacterium-dominantlymphotype and a fifth lymphotype (no dominant taxon) were more frequent in nTBLs. When restricted to dTBLs, clustering identified a Mycobacterium-dominant lymphotype with low -diversity and other non-Mycobacterium-dominated lymphotypes (termed Prevotella-Corynebacterium and Prevotella-Streptococcus). The Mycobacterium dTBL lymphotype was associated with HIV-positivity and clinical features characteristic of severe lymphadenitis (e.g., node size). dTBL microbial communities were enriched with potentially proinflammatory microbial short chain fatty acid metabolic pathways (propanoate, butanoate) vs. those in nTBLs. 11% (7/61) of nTBLs had Mycobacterium reads. ConclusionsTBL at the site-of-disease is not microbially homogenous and distinct microbial community clusters exist that are associated with different immunomodulatory potentials and clinical characteristics. Non-Mycobacterium-dominated dTBL lymphotypes, which contain taxa potentially targeted by TB treatment, represent less severe potentially earlier stage disease. These investigations lay foundations for studying the microbiomes role in lymphatic TB and the long-term clinical significance of lymphotypes requires prospective evaluation.

molecular biology↗

bioRxiv2021

Comprehensive and accurate genetic variant identification from contaminated and low coverage Mycobacterium tuberculosis whole genome sequencing data.

Improved understanding of the genomic variants that allow Mycobacterium tuberculosis (Mtb) to acquire drug resistance, or tolerance, and increase its virulence are important factors in controlling the current tuberculosis epidemic. Current approaches to Mtb sequencing however cannot reveal Mtbs full genomic diversity due to the strict requirements of low contamination levels, high Mtb sequence coverage, and elimination of complex regions. We developed the XBS (compleX Bacterial Samples) bioinformatics pipeline which implements joint calling and machine-learning-based variant filtering tools to specifically improve variant detection in the important Mtb samples that do not meet these criteria, such as those from unbiased sputum samples. Using novel simulated datasets, that permit exact accuracy verification, XBS was compared to the UVP and MTBseq pipelines. Accuracy statistics showed that all three pipelines performed equally well for sequence data that resemble those obtained from high depth coverage and low-level contamination culture isolates. In the complex genomic regions however, XBS accurately identified 9.0% more single nucleotide polymorphisms and 8.1% more single nucleotide insertions and deletions than the WHO-endorsed unified analysis variant pipeline. XBS also had superior accuracy for sequence data that resemble those obtained directly from sputum samples, where depth of coverage is typically very low and contamination levels are high. XBS was the only pipeline not affected by low depth of coverage (5-10x), type of contamination and excessive contamination levels (>50%). Simulation results were confirmed using WGS data from clinical samples, confirming the superior performance of XBS with a higher sensitivity (98.8%) when analysing culture isolates and identification of 13.9% more variable sites in WGS data from sputum samples as compared to MTBseq, without evidence for false positive variants when ribosomal RNA regions were excluded. The XBS pipeline facilitates sequencing of less-than-perfect Mtb samples. These advances will benefit future clinical applications of Mtb sequencing, especially whole genome sequencing directly from clinical specimens, thereby avoiding in vitro biases and making many more samples available for drug resistance and other genomic analyses. The additional genetic resolution and increased sample success rate will improve genome-wide association studies and sequence-based transmission studies. Impact statementMycobacterium tuberculosis (Mtb) DNA is usually extracted from culture isolates to obtain high quantities of non-contaminated DNA but this process can change the make-up of the bacterial population and is time-consuming. Furthermore, current analytic approaches exclude complex genomic regions where DNA sequences are repeated to avoid inference of false positive genetic variants, which may result in the loss of important genetic information. We designed the compleX Bacterial Sample (XBS) variant caller to overcome these limitations. XBS employs joint variant calling and machine-learning-based variant filtering to ensure that high quality variants can be inferred from low coverage and highly contaminated genomic sequence data obtained directly from sputum samples. Simulation and clinical data analyses showed that XBS performs better than other pipelines as it can identify more genetic variants and can handle complex (low depth, highly contaminated) Mtb samples. The XBS pipeline was designed to analyse Mtb samples but can easily be adapted to analyse other complex bacterial samples. Data summarySimulated sequencing data have been deposited in SRA BioProject PRJNA706121. All detailed findings are available in the Supplementary Material. Scripts for running the XBS variant calling core are available on https://github.com/TimHHH/XBS The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

genomics↗

bioRxiv2021

The role of copper resistance in Mycobacterium tuberculosis pathogenesis

Despite the development of new drugs and social interventions, tuberculosis remains a leading cause of mortality. This burden falls disproportionately on developing countries, particularly those where the incidence of HIV is high. In the Western Cape, South Africa, we have identified and isolated two Beijing family strains of Mycobacterium tuberculosis that, despite few differences at a genomic level, differ greatly in their severity of disease caused, providing an opportunity to study virulence in this organism. The aim of this study was to identify differences at a genomic and transcriptomic level that may identify the cause of the different virulence levels observed in the two isolates. The isolates were compared at the transcriptome level under four different growth conditions including oxidative stress. In comparing the transcriptome of the two isolates, an operon containing genes involved in the production of molybdenum cofactor that showed consistently lower levels of expression in the hypervirulent isolate was identified. A copper sensing transcriptional regulator was identified as the most probable regulator, and we found that the Cso operon which it is known to regulate was similarly differentially expressed in the strains. The production of molybdenum cofactor is effected in two ways by copper levels. Through the independent insertion of copper into molybdopterin (MPT), and destabilisation of Fe-S clusters. As MoaA3 contains a Fe-S cluster that is known to be destabilised by copper, and a number of copper sensitive genes are likewise found differentially expressed, it is likely that the strains differ in terms of their levels of resistance to copper. It is therefore hypothesised that the differences in virulence are as a result of different levels of resistance to phagosome copper overload, and the mechanism by which copper levels are linked to the production of molybdenum cofactor is described. Author summaryIn this article, we describe the differences in gene expression of two closely related strains of Mycobacterium tuberculosis isolated in the Western Cape of South Africa that differ in the severity of disease that they cause. We compared the strains at a genomic and transcriptomic level, and in doing so, we discovered a set of molybdenum cofactor genes regulated by a copper sensing transcription factor that came up in all datasets. Further genes linked to copper response were identified, providing greater evidence that the difference between the two strains was the manner in which they responded to copper stress. Phagocytes are known to exploit high levels of copper to kill intracellular bacteria, suggesting an important link between copper and disease. We conclude that resistance to copper toxicity is the most probable reason for the relative increase in virulence, and describe the regulatory relationship between copper levels and molybdenum cofactor synthesis.

microbiology↗

bioRxiv2020

Low Dose Hyperoxia Primes Airways for Fibrosis in Mice after Influenza A Infection

It is well known that supplemental oxygen used to treat preterm infants in respiratory distress is associated with permanently disrupting lung development and the host response to influenza A virus (IAV). However, many infants who go home with normally functioning lungs are also at risk for hyperreactivity after a respiratory viral infection suggesting neonatal oxygen may have induced hidden molecular changes that may prime to the lung for disease. We discovered that thrombospondin-1 (TSP-1) is elevated in adult mice exposed to high-dose neonatal hyperoxia that is known to cause alveolar simplification and fibrotic lung disease following IAV infection. TSP-1 was also elevated in a new, low-dose hyperoxia mouse model (40% for 8 days; 40×8) that we recently reported causes a transient change in lung function that resolves by 8 weeks of age. Elevated TSP-1 was also identified in human autopsy samples of BPD-affected former preterm infants. Consistent with TSP-1 being a master TGFβ regulator, an early transient activation of TGFβ signaling, increased airway hyperreactivity, and peribronchial inflammation and fibrosis were seen when 40×8 mice were infected with IAV, which was not seen in infected room air controls. These findings reveal low dose of neonatal hyperoxia that does not affect lung function or structure may still change expression of genes, such as TSP-1, that may prime the lung for disease following respiratory viral infections, and may help explain why former preterm infants who have normal lung function are susceptible to airway obstruction and increased morbidity after viral infection.Competing Interest StatementThe authors have declared no competing interest.View Full Text

physiology↗

bioRxiv2020

Human Whole Genome Sequencing in South Africa

The advent and evolution of next generation sequencing has considerably impacted genomic research. Until recently, South African researchers were unable to access affordable platforms capable of human whole genome sequencing locally and DNA samples had to be exported. Here we report the whole genome sequences of the first six human DNA samples sequenced and analysed at the South African Medical Research Council Genomics Centre. We demonstrate that the data obtained is of high quality, with an average sequencing depth of 36.41, and that the output is comparable to data generated internationally on a similar platform. The Genomics Centre creates an environment where African researchers are able to access world class facilities, increasing local capacity to sequence whole genomes as well as store and analyse the data.Competing Interest StatementThe authors have declared no competing interest.View Full Text

genomics↗

bioRxiv2020

An active chromatin interactome elucidates the biological mechanisms underlying genetic risk factors of dermatological conditions in disease relevant cell lines

Chromatin looping between regulatory elements and gene promoters presents a potential mechanism whereby disease risk variants affect their target genes. Here we use H3K27ac HiChIP, a method for assaying the active chromatin interactome in two cell lines: keratinocytes and skin derived CD8+ T cells. We integrate public datasets for a lymphoblastoid cell line and primary CD4+ T cells and identify gene targets at risk loci for skin-related disorders. Interacting genes enrich for pathways of known importance in each trait, such as cytokine response (psoriatic arthritis, psoriasis) and replicative senescence (melanoma). We show examples of how our analysis can inform changes in the current understanding of multiple psoriasis associated risk loci. For example, the variant rs10794648, which is generally assigned to IFNLR1, was linked to GRHL3 in our dataset, a gene essential in skin repair and development. Our findings, therefore, indicate a renewed importance of skin related factors in the risk of disease. O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/973271v2_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@99cd40org.highwire.dtl.DTLVardef@1725b6dorg.highwire.dtl.DTLVardef@d05d21org.highwire.dtl.DTLVardef@1924d07_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract In this article we take disease associated variants from 5 dermatological conditions and use cell type specific datasets to map genes that could be affected by these variants, providing insight into disease mechanisms. C_FIG

genomics↗

bioRxiv2020

RBMS1 suppresses colon cancer metastasis through targeted stabilization of its mRNA regulon

Broad dysregulation of gene expression control is a hallmark of cancer progression. Identifying the underlying master regulators that drive pathological gene expression is a key challenge in precision oncology. Here, we have developed a network analytical framework, named PRADA, that identifies oncogenic RNA-binding proteins through the systematic detection of coordinated changes in their target regulons. Application of this approach to data collected from clinical samples, patient-derived xenografts, and cell line models of colon cancer metastasis revealed the RNA-binding protein RBMS1 as a suppressor of colon cancer progression. We observed that silencing RBMS1 results in increased metastatic capacity in xenograft mouse models, and that restoring its expression blunts metastatic liver colonization. We have found that RBMS1 functions as a post-transcriptional regulator of RNA stability by directly binding and stabilizing ~80 target mRNAs. Measurements in more than 180 clinical samples as well as survival analyses in publicly available datasets, have shown that RBMS1 silencing and the subsequent downregulation of its targets are strongly associated with disease progression and poor survival in colon cancer patients. Together, our findings establish a role for RBMS1 as a previously unknown regulator of RNA stability and as a suppressor of colon cancer metastasis with clinical utility for risk stratification of patients. SignificanceBy applying a new analytical approach to transcriptomic data from clinical samples and models of colon cancer progression, we have uncovered RBMS1 as a suppressor of metastasis and as a post-transcriptional regulator of RNA stability. Notably, RBMS1 silencing and downregulation of its targets are negatively associated with patient survival.

systems biology↗

bioRxiv2019

Chromatin-based techniques map DNA interaction landscapes in psoriasis susceptibility loci and highlight KLF4 as a target gene in 9q31

Genome-wide association studies (GWAS) have uncovered many genetic risk loci for psoriasis, yet many remain uncharacterised in terms of the causal gene and their biological mechanism in disease. Here, we use a disease-focused Capture Hi-C experiment to link psoriasis-associated variants with their target genes in psoriasis-relevant cell lines (HaCaT keratinocytes and My-La CD8+ T cells). We confirm previously assigned genes, suggest novel candidates and provide evidence for complexity at psoriasis GWAS loci. In the 9q31 risk locus we combine further epigenomic evidence to demonstrate how the psoriasis association forms a functional interaction with the distant (>500 kb) KLF4 gene. We use CRISPR activation coupled with RNA-seq to demonstrate how activation of psoriasis-associated enhancers upregulates KLF4 in HaCaT cells. Our study design provides a robust pipeline for following up on GWAS disease-associated variants, paving the way for functional translation of genetic findings into clinical benefit.

genomics↗

bioRxiv2018

A New Phylogenetic Framework for the Animal-adapted Mycobacterium tuberculosis Complex

Tuberculosis (TB) affects humans and other animals and is caused by bacteria from the Mycobacterium tuberculosis complex (MTBC). Previous studies have shown that there are at least nine members of the MTBC infecting animals other than humans; these have also been referred to as ecotypes. However, the ecology and the evolution of these animal-adapted MTBC ecotypes are poorly understood. Here we screened 12,886 publicly available MTBC genomes and newly sequenced 17 animal-adapted MTBC strains, gathering a total of 529 genomes of animal-adapted MTBC strains. Phylogenomic and comparative analyses confirm that the animal-adapted MTBC members are paraphyletic with some members more closely related to the human-adapted Mycobacterium africanum Lineage 6 than to other animal-adapted strains. Furthermore, we identified four main animal-adapted MTBC clades that might correspond to four main host shifts; two of these clades are proposed to reflect independent cattle domestication events. Contrary to what would be expected from an obligate pathogen, MTBC nucleotide diversity was not positively correlated with host phylogenetic distances, suggesting that host tropism in the animal-adapted MTBC seems to be driven more by contact rates and demographic aspects of the host population rather than host relatedness. By combining phylogenomics with ecological data, we propose an evolutionary scenario in which the ancestor of Lineage 6 and all animal-adapted MTBC ecotypes was a generalist pathogen that subsequently adapted to different host species. This study provides a new phylogenetic framework to better understand the evolution of the different ecotypes of the MTBC and guide future work aimed at elucidating the molecular mechanisms underlying host specificity.

evolutionary biology↗

bioRxiv2018

Building comprehensive MS-friendly databases for proteomic analysis of bacterial species of unknown genetic background

In proteomics, peptide information within mass spectrometry data from a specific organism sample is routinely challenged against a protein sequence database that best represent such organism. However, if the species/strain in the sample is unknown or poorly genetically characterized, it becomes challenging to determine a database which can represent such sample. Building customized protein sequence databases merging multiple strains for a given species has become a strategy to overcome such restrictions. However, as more genetic information is publicly available and interesting genetic features such as the existence of pan- and core genes within a species are revealed, we questioned how efficient such merging strategies are to report relevant information. To test this assumption, we constructed databases containing conserved and unique sequences for ten different species. Features that are relevant for probabilistic-based protein identification by proteomics were then monitored. As expected, increase in database complexity correlates with pangenomic complexity. However, Mycobacterium tuberculosis and Bortedella pertusis generated very complex databases even having low pangenomic complexity or no pangenome at all. This suggests that discrepancies in gene annotation is higher than average between strains of those species. We further tested database performance by using mass spectrometry data from eight clinical strains from Mycobacterium tuberculosis, and from two published datasets from Staphylococcus aureus. We show that by using an approach where database size is controlled by removing repeated identical tryptic sequences across strains/species, computational time can be reduced drastically as database complexity increases.

bioinformatics↗

bioRxiv2016

Overlapping long sequence reads: Current innovations and challenges in developing sensitive, specific and scalable algorithms

Identifying overlaps between error-prone long reads, specifically those from Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PB), is essential for certain downstream applications, including error correction and de novo assembly. Though akin to the read-to-reference alignment problem, read-to-read overlap detection is a distinct problem that can benefit from specialized algorithms that perform efficiently and robustly on high error rate long reads. Here, we review the current state-of-the-art read-to-read overlap tools for error-prone long reads, including BLASR, DALIGNER, MHAP, GraphMap, and Minimap. These specialized bioinformatics tools differ not just in their algorithmic designs and methodology, but also in their robustness of performance on a variety of datasets, time and memory efficiency, and scalability. We highlight the algorithmic features of these tools, as well as their potential issues and biases when utilizing any particular method. We benchmarked these tools, tracking their resource needs and computational performance, and assessed the specificity and precision of each. The concepts surveyed may apply to future sequencing technologies, as scalability is becoming more relevant with increased sequencing throughput.\n\nContactcjustin@bcgsc.ca; ibirol@bcgsc.ca\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗