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At least 1,783 records · Page 99

Comparative Genomic Analysis of Ochratoxin A Biosynthetic Cluster in Producing Fungi: New Evidence of a Cyclase Gene Involvement

The widespread use of Next-Generation Sequencing has opened a new era in the study of biological systems by significantly increasing the catalog of fungal genomes sequences and identifying gene clusters for known secondary metabolites as well as novel cryptic ones. However, most of these clusters still need to be examined in detail to completely understand the pathway steps and the regulation of the biosynthesis of metabolites. Genome sequencing approach led to the identification of the biosynthetic genes cluster of ochratoxin A (OTA) in a number of producing fungal species. Ochratoxin A is a potent pentaketide nephrotoxin produced by Aspergillus and Penicillium species and found as widely contaminant in food, beverages and feed. The increasing availability of several new genome sequences of OTA producer species in JGI Mycocosm and/or GenBank databanks led us to analyze and update the gene cluster structure in 19 Aspergillus and 2 Penicillium OTA producing species, resulting in a well conserved organization of OTA core genes among the species. Furthermore, our comparative genome analyses evidenced the presence of an additional gene, previously undescribed, located between the polyketide and non-ribosomal synthase genes in the cluster of all the species analyzed. The presence of a SnoaL cyclase domain in the sequence of this gene supports its putative role in the polyketide cyclization reaction during the initial steps of the OTA biosynthesis pathway. The phylogenetic analysis showed a clustering of OTA SnoaL domains in accordance with the phylogeny of OTA producing species at species and section levels. The characterization of this new OTA gene, its putative role and its expression evidence in three important representative producing species, are reported here for the first time.

59 BASIC BIOLOGICAL SCIENCES↗

A POSSIBLE BINARY SYSTEM OF A STELLAR REMNANT IN THE HIGH-MAGNIFICATION GRAVITATIONAL MICROLENSING EVENT OGLE-2007-BLG-514

We report the extremely high-magnification (A > 1000) binary microlensing event OGLE-2007-BLG-514. We obtained good coverage around the double peak structure in the light curve via follow-up observations from different observatories. The binary lens model that includes the effects of parallax (known orbital motion of the Earth) and orbital motion of the lens yields a binary lens mass ratio of q = 0.321 {+-} 0.007 and a projected separation of s = 0.072 {+-} 0.001 in units of the Einstein radius. The parallax parameters allow us to determine the lens distance D{sub L} = 3.11 {+-} 0.39 kpc and total mass M{sub L} = 1.40 {+-} 0.18 M{sub Sun }; this leads to the primary and secondary components having masses of M{sub 1} = 1.06 {+-} 0.13 M{sub Sun} and M{sub 2} = 0.34 {+-} 0.04 M{sub Sun }, respectively. The parallax model indicates that the binary lens system is likely constructed by the main-sequence stars. On the other hand, we used a Bayesian analysis to estimate probability distributions by the model that includes the effects of xallarap (possible orbital motion of the source around a companion) and parallax (q = 0.270 {+-} 0.005, s = 0.083 {+-} 0.001). The primary component of the binary lens is relatively massive, with M{sub 1} = 0.9{sup +4.6}{sub -0.3} M{sub Sun} and it is at a distance of D{sub L} = 2.6{sup +3.8}{sub -0.9} kpc. Given the secure mass ratio measurement, the companion mass is therefore M{sub 2} = 0.2{sup +1.2}{sub -0.1} M{sub Sun }. The xallarap model implies that the primary lens is likely a stellar remnant, such as a white dwarf, a neutron star, or a black hole.

79 ASTRONOMY AND ASTROPHYSICS↗

Solution of eigenvalue problems by Sturm sequence method.

A generalized eigenvalue algorithm is presented herein along with the complete listing of the associated computer program, which may be conveniently utilized for the efficient solution of certain broad classes of eigenvalue problems. Extensive applications of the procedure are envisaged in the analysis of many important engineering problems, such as stability and natural frequency analysis of practical discrete structural systems, idealized by the finite element technique. The procedure based on the Sturm sequence method is accurate and fast, possessing several significant advantages over other known methods of such analysis. Numerical results are also presented for two representative structural engineering problems.

Gupta, K. K.↗

Challenges and opportunities in understanding microbial communities with metagenome assembly (accompanied by IPython Notebook tutorial)

Metagenomic investigations hold great promise for informing the genetics, physiology, and ecology of environmental microorganisms. Current challenges for metagenomic analysis are related to our ability to connect the dots between sequencing reads, their population of origin, and their encoding functions. Assembly-based methods reduce dataset size by extending overlapping reads into larger contiguous sequences (contigs), providing contextual information for genetic sequences that does not rely on existing references. These methods, however, tend to be computationally intensive and are again challenged by sequencing errors as well as by genomic repeats. While numerous tools have been developed based on these methodological concepts, they present confounding choices and training requirements to metagenomic investigators. To help with accessibility to assembly tools, this review also includes an IPython Notebook metagenomic assembly tutorial. This tutorial has instructions for execution any operating system using Amazon Elastic Cloud Compute and guides users through downloading, assembly, and mapping reads to contigs of a mock microbiome metagenome. Despite its challenges, metagenomic analysis has already revealed novel insights into many environments on Earth. As software, training, and data continue to emerge, metagenomic data access and its discoveries will to grow.

54 ENVIRONMENTAL SCIENCES↗

Algorithm Optimally Orders Forward-Chaining Inference Rules

People typically develop knowledge bases in a somewhat ad hoc manner by incrementally adding rules with no specific organization. This often results in a very inefficient execution of those rules since they are so often order sensitive. This is relevant to tasks like Deep Space Network in that it allows the knowledge base to be incrementally developed and have it automatically ordered for efficiency. Although data flow analysis was first developed for use in compilers for producing optimal code sequences, its usefulness is now recognized in many software systems including knowledge-based systems. However, this approach for exhaustively computing data-flow information cannot directly be applied to inference systems because of the ubiquitous execution of the rules. An algorithm is presented that efficiently performs a complete producer/consumer analysis for each antecedent and consequence clause in a knowledge base to optimally order the rules to minimize inference cycles. An algorithm was developed that optimally orders a knowledge base composed of forwarding chaining inference rules such that independent inference cycle executions are minimized, thus, resulting in significantly faster execution. This algorithm was integrated into the JPL tool Spacecraft Health Inference Engine (SHINE) for verification and it resulted in a significant reduction in inference cycles for what was previously considered an ordered knowledge base. For a knowledge base that is completely unordered, then the improvement is much greater.

James, Mark↗

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

ABSTRACT There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (“functional modules”), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida . Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

09 BIOMASS FUELS↗

The role of structural parameters in DNA cyclization

Abstract Background The intrinsic bendability of DNA plays an important role with relevance for myriad of essential cellular mechanisms. The flexibility of a DNA fragment can be experimentally and computationally examined by its propensity for cyclization, quantified by the Jacobson-Stockmayer J factor. In this study, we use a well-established coarse-grained three-dimensional model of DNA and seven distinct sets of experimentally and computationally derived conformational parameters of the double helix to evaluate the role of structural parameters in calculating DNA cyclization. Results We calculate the cyclization rates of 86 DNA sequences with previously measured J factors and lengths between 57 and 325 bp as well as of 20,000 randomly generated DNA sequences with lengths between 350 and 4000 bp. Our comparison with experimental data is complemented with analysis of simulated data. Conclusions Our data demonstrate that all sets of parameters yield very similar results for longer DNA fragments, regardless of the nucleotide sequence, which are in agreement with experimental measurements. However, for DNA fragments shorter than 100 bp, all sets of parameters performed poorly yielding results with several orders of magnitude difference from the experimental measurements. Our data show that DNA cyclization rates calculated using conformational parameters based on nucleosome packaging data are most similar to the experimental measurements. Overall, our study provides a comprehensive large-scale assessment of the role of structural parameters in calculating DNA cyclization rates.

59 BASIC BIOLOGICAL SCIENCES↗

NASA Tech Briefs, September 2006

Topics covered include: Improving Thermomechanical Properties of SiC/SiC Composites; Aerogel/Particle Composites for Thermoelectric Devices; Patches for Repairing Ceramics and Ceramic- Matrix Composites; Lower-Conductivity Ceramic Materials for Thermal-Barrier Coatings; An Alternative for Emergency Preemption of Traffic Lights; Vehicle Transponder for Preemption of Traffic Lights; Automated Announcements of Approaching Emergency Vehicles; Intersection Monitor for Traffic-Light-Preemption System; Full-Duplex Digital Communication on a Single Laser Beam; Stabilizing Microwave Frequency of a Photonic Oscillator; Microwave Oscillators Based on Nonlinear WGM Resonators; Pointing Reference Scheme for Free-Space Optical Communications Systems; High-Level Performance Modeling of SAR Systems; Spectral Analysis Tool 6.2 for Windows; Multi-Platform Avionics Simulator; Silicon-Based Optical Modulator with Ferroelectric Layer; Multiplexing Transducers Based on Tunnel-Diode Oscillators; Scheduling with Automated Resolution of Conflicts; Symbolic Constraint Maintenance Grid; Discerning Trends in Performance Across Multiple Events; Magnetic Field Solver; Computing for Aiming a Spaceborne Bistatic- Radar Transmitter; 4-Vinyl-1,3-Dioxolane-2-One as an Additive for Li-Ion Cells; Probabilistic Prediction of Lifetimes of Ceramic Parts; STRANAL-PMC Version 2.0; Micromechanics and Piezo Enhancements of HyperSizer; Single-Phase Rare-Earth Oxide/Aluminum Oxide Glasses; Tilt/Tip/Piston Manipulator with Base-Mounted Actuators; Measurement of Model Noise in a Hard-Wall Wind Tunnel; Loci-STREAM Version 0.9; The Synergistic Engineering Environment; Reconfigurable Software for Controlling Formation Flying; More About the Tetrahedral Unstructured Software System; Computing Flows Using Chimera and Unstructured Grids; Avoiding Obstructions in Aiming a High-Gain Antenna; Analyzing Aeroelastic Stability of a Tilt-Rotor Aircraft; Tracking Positions and Attitudes of Mars Rovers; Stochastic Evolutionary Algorithms for Planning Robot Paths; Compressible Flow Toolbox; Rapid Aeroelastic Analysis of Blade Flutter in Turbomachines; General Flow-Solver Code for Turbomachinery Applications; Code for Multiblock CFD and Heat-Transfer Computations; Rotating-Pump Design Code; Covering a Crucible with Metal Containing Channels; Repairing Fractured Bones by Use of Bioabsorbable Composites; Kalman Filter for Calibrating a Telescope Focal Plane; Electronic Absolute Cartesian Autocollimator; Fiber-Optic Gratings for Lidar Measurements of Water Vapor; Simulating Responses of Gravitational-Wave Instrumentation; SOFTC: A Software Correlator for VLBI; Progress in Computational Simulation of Earthquakes; Database of Properties of Meteors; Computing Spacecraft Solar-Cell Damage by Charged Particles; Thermal Model of a Current-Carrying Wire in a Vacuum; Program for Analyzing Flows in a Complex Network; Program Predicts Performance of Optical Parametric Oscillators; Processing TES Level-1B Data; Automated Camera Calibration; Tracking the Martian CO2 Polar Ice Caps in Infrared Images; Processing TES Level-2 Data; SmaggIce Version 1.8; Solving the Swath Segment Selection Problem; The Spatial Standard Observer; Less-Complex Method of Classifying MPSK; Improvement in Recursive Hierarchical Segmentation of Data; Using Heaps in Recursive Hierarchical Segmentation of Data; Tool for Statistical Analysis and Display of Landing Sites; Automated Assignment of Proposals to Reviewers; Array-Pattern-Match Compiler for Opportunistic Data Analysis; Pre-Processor for Compression of Multispectral Image Data; Compressing Image Data While Limiting the Effects of Data Losses; Flight Operations Analysis Tool; Improvement in Visual Target Tracking for a Mobile Robot; Software for Simulating Air Traffic; Automated Vectorization of Decision-Based Algorithms; Grayscale Optical Correlator Workbench; "One-Stop Shopping" for Ocean Remote-Sensing and Model Data; State Analysis Database Tool; Generating CAHV and CAHVOmages with Shadows in ROAMS; Improving UDP/IP Transmission Without Increasing Congestion; FORTRAN Versions of Reformulated HFGMC Codes; Program for Editing Spacecraft Command Sequences; Flight-Tested Prototype of BEAM Software; Mission Scenario Development Workbench; Marsviewer; Tool for Analysis and Reduction of Scientific Data; ASPEN Version 3.0; Secure Display of Space-Exploration Images; Digital Front End for Wide-Band VLBI Science Receiver; Multifunctional Tanks for Spacecraft; Lightweight, Segmented, Mostly Silicon Telescope Mirror; Assistant for Analyzing Tropical-Rain-Mapping Radar Data; and Anion-Intercalating Cathodes for High-Energy- Density Cells.

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Livermore Metagenomics Analysis Toolkit

LMAT is designed to take as input a collection of raw metagenomic sequencer reads, and search each read against a reference genome database and assign a taxonomic label and confidence value to each read and report a summary of the predicted taxonomic contents of the metagenomic sample.

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A novel analysis method for paired-sample microbial ecology experiments

Many microbial ecology experiments use sequencing data to measure a community s response to an experimental treatment. In a common experimental design, two units, one control and one experimental, are sampled before and after the treatment is applied to the experimental unit. The four resulting samples contain information about the dynamics of organisms that respond to the treatment, but there are no analytical methods designed to extract exactly this type of information from this configuration of samples. Here we present an analytical method specifically designed to visualize and generate hypotheses about microbial community dynamics in experiments that have paired samples and few or no replicates. The method is based on the Poisson lognormal distribution, long studied in macroecology, which we found accurately models the abundance distribution of taxa counts from 16S rRNA surveys. To demonstrate the method s validity and potential, we analyzed an experiment that measured the effect of crude oil on ocean microbial communities in microcosm. Our method identified known oil degraders as well as two clades, Maricurvus and Rhodobacteraceae, that responded to amendment with oil but do not include known oil degraders. Furthermore, our approach is sensitive to organisms that increased in abundance only in the experimental unit but less sensitive to organisms that increased in both control and experimental units, thus mitigating the role of bottle effects .

59 BASIC BIOLOGICAL SCIENCES↗

NECAP 4.1: NASA's Energy Cost Analysis Program thermal response factor routine

A thermal response factor is described and calculation sequences and flowcharts for RESFAC2 are provided. RESFAC is used by NASA's (NECAP) to calculate hourly heat transfer coefficients (thermal response factors) for each unique delayed surface. NECAP uses these response factors to compute each spaces' hourly heat gain/loss.

Weise, M. R.↗

Globular cluster photometry with the Hubble Space Telescope. I - Description of the method and analysis of the core of 47 Tuc

Accurate photometry for individual post-main-sequence stars in the core of the Galactic globular cluster 47 Tuc is presented and analyzed using an empirical point spread function model and Monte Carlo simulations. A V vs. V-I color-magnitude diagrams is constructed which shows several distinct stellar types, including RGB and HB stars. Twenty-four blue straggler stars are detected in 47 Tuc, more concentrated toward the center of the cluster than the giants. This supports the hypothesis is that the stragglers are either coalesced stars or members of binary systems that are more massive than single stars. The radial profile of the projected stellar density is flat in the central region of 47 Tuc with a core radius of 23 +/- 2 arcsec. No signature of a collapsed core is evident. The observed radial cumulative distribution of stars rules out the presence of a massive compact object in the center.

Guhathakurta, Puragra↗

Livermore Metagenomics Analysis Toolkit

LMAT is designed to take as input a collection of raw metagenomic sequencer reads, and search each read against a reference genome database and assign a taxonomic label and confidence value to each read and report a summary of the predicted taxonomic contents of the metagenomic sample.

Source record↗

From DNA to FBA: How to Build Your Own Genome-Scale Metabolic Model

Microbiological studies are increasingly relying on in silico methods to perform exploration and rapid analysis of genomic data, and functional genomics studies are supplemented by the new perspectives that genome-scale metabolic models offer. A mathematical model consisting of a microbe’s entire metabolic map can be rapidly determined from whole-genome sequencing and annotating the genomic material encoded in its DNA. Flux-balance analysis (FBA), a linear programming technique that uses metabolic models to predict the phenotypic responses imposed by environmental elements and factors, is the leading method to simulate and manipulate cellular growth in silico. However, the process of creating an accurate model to use in FBA consists of a series of steps involving a multitude of connections between bioinformatics databases, enzyme resources, and metabolic pathways. We present the methodology and procedure to obtain a metabolic model using PyFBA, an extensible Pythonbased open-source software package aimed to provide a platform where functional annotations are used to build metabolic models (http://linsalrob.github.io/PyFBA). Backed by the Model SEED biochemistry database, PyFBA contains methods to reconstruct a microbe’s metabolic map, run FBA upon different media conditions, and gap-fill its metabolism. The extensibility of PyFBA facilitates novel techniques in creating accurate genome-scale metabolic models.

genome annotation↗

New signatures of the Milky Way formation in the local halo and inner-halo streamers in the era of Gaia

We explore the vicinity of the Milky Way through the use of spectrophotometric data from the Sloan Digital Sky Survey and high-quality proper motions derived from multi-epoch positions extracted from the Guide Star Catalog II database. In order to identify and characterize streams as relics of the Milky Way formation, we start with classifying, selecting, and studying 2417 subdwarfs with [Fe/H] < −1.5 up to 3 kpc away from the Sun as tracers of the local halo system. Then, through phase-space analysis, we find statistical evidence of five discrete kinematic overdensities among 67 of the fastest-moving stars and compare them to high-resolution N-body simulations of the interaction between a Milky Way–like galaxy and orbiting dwarf galaxies with four representative cases of merging histories. The observed overdensities can be interpreted as fossil substructures consisting of streamers torn from their progenitors; such progenitors appear to be satellites on prograde and retrograde orbits on different inclinations. In particular, of the five detected overdensities, two appear to be associated, yielding 21 additional main-sequence members, with the stream of Helmi et al. that our analysis confirms is on a high-inclination prograde orbit. The three newly identified kinematic groups could be associated with the retrograde streams detected by Dinescu and Kepley et al.; whatever their origin, the progenitor(s) would be on retrograde orbit(s) and inclination(s) within the range 10{sup ∘}÷60{sup ∘}. Finally, we use our simulations to investigate the impact of observational errors and compare the current picture to the promising prospect of highly improved data expected from the Gaia mission.

79 ASTRONOMY AND ASTROPHYSICS↗

Congruence of Clusters Defined By Whole Genome Sequencing and MALDI-TOF for Bacteria Isolated From Cleanrooms

Introduction: Oligotrophic conditions can render cleanrooms inhospitable to microbes. Despite these constraints, fungi and bacteria are frequently isolated from surfaces in astromaterials cleanrooms at the Johnson Space Center. Bacillus species are of particular concern because endospores belonging to this genus are resilient and can affect astromaterials. Current monitoring programs rely on 16S rRNA sequencing and the VITEK2 Compact system. These methods have limited power to resolve Bacillus species. Matrix-assisted laser desorption - time of flight mass spectrometry (MALDI-TOF MS), provides a rapid, low cost, method of identifying bacterial isolates and has a higher resolution than 16S rRNA sequencing, particularly for Bacillus species; however, few studies have compared this method to the industry gold standard, whole genome sequencing (WGS). Methods: Based on 16S rRNA classification, we selected 14 isolates for analysis with MALDI-TOF and WGS. Mass spectra were generated with MALDI-TOF MS and processed with custom scripts to identify clusters of closely related isolates and calculate a matrix of pairwise cosine similarity scores. Hybrid Illumina and Nanopore sequencing were used to generate draft genomes. Pairwise similarity scores were calculated from these genomes based on the average amino acid identity (AAI) predicted from single copy core genes. Congruence of clustering between these methods, was assessed by calculating adjusted Rand and Wallace coefficients. Results: Clusters of species generated from MALDI-TOF MS showed good agreement of phylotypes generated with WGS. Pairs of strains that were > 94% similar to each other in terms of predicted amino acid sequences consistently showed cosine similarities of mass spectra > 0.65 and, of the 9 clusters identified with WGS, 8 were identical with MALDI-TOF. This corresponds to an adjusted Rand index of 0.95 and a 95% confidence interval of 0.80 – 1.00 for adjusted Wallace coefficients. The only discordance was for a pair of isolates that were classified as Paenibacillus species. This pair showed relatively high similarity (0.84) in terms of MALDI-TOF MS but only 85% similarity in terms of AAI. Conclusion: This study shows that MALDI-TOF and WGS exhibit a similar ability to delineate Bacillus species isolated from cleanrooms and taxonomic units described by these two methods are consistent with one another. Since MALDI-TOF MS is low in cost and high in throughput, this approach appears to be an ideal option for routine microbial monitoring and identifying Bacillus species.

Farnaz Mazhari↗

Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution

With advances in DNA sequencing and miniaturized molecular biology workflows, rapid and affordable sequencing of single-cell genomes has become a reality. Compared to 16S rRNA gene surveys and shotgun metagenomics, large-scale application of single-cell genomics to whole microbial communities provides an integrated snapshot of community composition and function, directly links mobile elements to their hosts, and enables analysis of population heterogeneity of the dominant community members. To that end, we sequenced nearly 500 single-cell genomes from a low diversity hot spring sediment sample from Dewar Creek, British Columbia, and compared this approach to 16S rRNA gene amplicon and shotgun metagenomics applied to the same sample. We found that the broad taxonomic profiles were similar across the three sequencing approaches, though several lineages were missing from the 16S rRNA gene amplicon dataset, likely the result of primer mismatches. At the functional level, we detected a large array of mobile genetic elements present in the single-cell genomes but absent from the corresponding same species metagenome-assembled genomes. Moreover, we performed a single-cell population genomic analysis of the three most abundant community members, revealing differences in population structure based on mutation and recombination profiles. While the average pairwise nucleotide identities were similar across the dominant species-level lineages, we observed differences in the extent of recombination between these dominant populations. Most intriguingly, the creek's Hydrogenobacter sp. population appeared to be so recombinogenic that it more closely resembled a sexual species than a clonally evolving microbe. Together, this work demonstrates that a randomized single-cell approach can be useful for the exploration of previously uncultivated microbes from community composition to population structure.

59 BASIC BIOLOGICAL SCIENCES↗

HiFiAdapterFilt, a memory efficient read processing pipeline, prevents occurrence of adapter sequence in PacBio HiFi reads and their negative impacts on genome assembly

Abstract Background Pacific Biosciences HiFi read technology is currently the industry standard for high accuracy long-read sequencing that has been widely adopted by large sequencing and assembly initiatives for generation of de novo assemblies in non-model organisms. Though adapter contamination filtering is routine in traditional short-read analysis pipelines, it has not been widely adopted for HiFi workflows. Results Analysis of 55 publicly available HiFi datasets revealed that a read-sanitation step to remove sequence artifacts derived from PacBio library preparation from read pools is necessary as adapter sequences can be erroneously integrated into assemblies. Conclusions Here we describe the nature of adapter contaminated reads, their consequences in assembly, and present HiFiAdapterFilt, a simple and memory efficient solution for removing adapter contaminated reads prior to assembly.

59 BASIC BIOLOGICAL SCIENCES↗