Generalized DNA barcode design based on Hamming codes

Lentiviral vectors for precise expression to treat X-linked lymphoproliferative disease

X-linked lymphoproliferative disease (XLP1) results from SH2D1A gene mutations affecting the SLAM-associated protein (SAP). A regulated lentiviral vector (LV), XLP-SMART LV, designed to express SAP at therapeutic levels in T, NK, and NKT cells, is crucial for effective gene therapy. We experimentally identified 34 genomic regulatory elements of the SH2D1A gene and designed XLP-SMART LVs to emulate the lineage and stage-specific control of SAP. We screened them for their on-target enhancer activity in T, NK, and NKT cells and their off-target enhancer activity in B cell and myeloid populations. In combination, three enhancer elements increased SAP promoter expression up to 4-fold in on-target populations in vitro. NSG-Tg(Hu-IL15) xenograft studies with XLP-SMART LVs demonstrated up to 7-fold greater expression in on-target cells over a control EFS-LV, with no off-target expression. The XLP-SMART LVs exhibited stage-specific T and NK cell expression in peripheral blood, bone marrow, spleen, and thymic tissues (mimicking expression patterns of SAP). Transduction of XLP1 patient CD8+ T cells or BM CD34+ cells with XLP-SMART LVs restored restimulation-induced cell death and NK cytotoxicity to wild-type levels, respectively. These data demonstrate that it is feasible to create a lineage and stage-specific LV to restore the XLP1 phenotype by gene therapy.

Droplet-based single-cell sequencing: Strategies and applications

Notable advancements in single-cell omics technologies have not only addressed longstanding challenges but also enabled unprecedented studies of cellular heterogeneity with unprecedented resolution and scale. These strides have led to groundbreaking insights into complex biological systems, paving the way for a more profound comprehension of human biology and diseases. The droplet microfluidic technology has become a crucial component in many single-cell sequencing workflows in terms of throughput, cost-effectiveness, and automation. Utilizing a microfluidic chip to encapsulate and profile individual cells within droplets has significantly improved single-cell research. Therefore, this review aims to comprehensively elaborate the droplet microfluidics-assisted omics methods from a single-cell perspective. The strategies for using droplet microfluidics in the realms of genomics, epigenomics, transcriptomics, and proteomics analyses are first introduced. On this basis, the focus then turns to the latest applications of this technology in different sequencing patterns, including mono- and multi-omics. Finally, the challenges and further perspectives of droplet-based single-cell sequencing in both foundational research and commercial applications are discussed.

Systematic evaluation of the Precision ID GlobalFiler™ NGS STR panel v2 using single-source samples of various quantity and quality and mixed DNA samples

Massively parallel sequencing (MPS) techniques were developed approximately 15 years ago. Meanwhile, several MPS kits for forensic identification, phenotypic information, ancestry, and mitochondrial DNA analysis have been developed and their use has been established. Sequencing short tandem repeats (STRs) has certain advantages over the currently used length-based genotyping methods, which are based on PCR amplification followed by capillary electrophoresis (CE). MPS is more discriminative and includes the possibility of testing high numbers of targets (> 100), different types of markers [STRs and single nucleotide polymorphisms (SNPs)], as well as the use of smaller amplicons (< 300 bp). This study evaluated in 24 experimental runs the Precision ID GlobalFiler™ NGS STR panel v2 from ThermoFisher, which targets 31 autosomal STRs, amelogenin, and three Y-markers (one STR, SRY, and Yindel). Single-source samples were used in 18 experimental runs, for systematic evaluation. These included assessing library preparation benchmark conditions, limited DNA input, as well as testing repeatability, number of samples per run, and degraded DNA samples. Full profiles were consistently obtained from as little as 50 pg DNA input. Using the optional recovery PCR method improved outcomes for samples with low DNA input. Full profiles were also obtained from severely degraded DNA samples with degradation indices (DI) of > 60. In addition, six experimental runs were performed testing various two-person mixtures with mixture ratios ranging from 1:20 to 20:1. Major and minor contributors were distinguishable by their read counts (coverage), because less DNA input yielded lower read counts, analogous to the traditional CE technology, where less DNA produces lower peak heights. Mixture ratios of approximately 1:1 were indistinguishable, while a greater imbalance, i.e., higher mixture ratios, made the mixture more distinguishable between major and minor contributors. Based on this information, the highest success rate of correctly deconvoluted four-allelic loci was from mixtures with 1:3 ratios. At higher mixture ratios, the drop-out rate of the minor contributor increased, reducing the number of four-allelic loci.

Extracting, filtering and simulating cellular barcodes using CellBarcode tools

Identifying true DNA cellular barcodes among polymerase chain reaction and sequencing errors is challenging. Current tools are restricted in the diversity of barcode types supported or the analysis strategies implemented. As such, there is a need for more versatile and efficient tools for barcode extraction, as well as for tools to investigate which factors impact barcode detection and which filtering strategies to best apply. Here we introduce the package CellBarcode and its barcode simulation kit, CellBarcodeSim, that allows efficient and versatile barcode extraction and filtering for a range of barcode types from bulk or single-cell sequencing data using a variety of filtering strategies. Using the barcode simulation kit and biological data, we explore the technical and biological factors influencing barcode identification and provide a decision tree on how to optimize barcode identification for different barcode settings. We believe that CellBarcode and CellBarcodeSim have the capability to enhance the reproducibility and interpretation of barcode results across studies.

Gene-by-environment interactions are pervasive among natural genetic variants

Gene-by-environment (GxE) interactions, in which a genetic variant's phenotypic effect is condition specific, are fundamental for understanding fitness landscapes and evolution but have been difficult to identify at the single-nucleotide level. Although many condition-specific quantitative trait loci (QTLs) have been mapped, these typically contain numerous inconsequential variants in linkage, precluding understanding of the causal GxE variants. Here, we introduce BARcoded Cas9 retron precise parallel editing via homology (CRISPEY-BAR), a high-throughput precision genome editing strategy, and use it to map GxE interactions of naturally occurring genetic polymorphisms impacting yeast growth. We identified hundreds of GxE variants within condition-specific QTLs, revealing unexpected genetic complexity. Moreover, we found that 93.7% of non-neutral natural variants within ergosterol biosynthesis pathway genes showed GxE interactions, including many impacting antifungal drug resistance through diverse molecular mechanisms. In sum, our results suggest an extremely complex, context-dependent fitness landscape characterized by pervasive GxE interactions while also demonstrating massively parallel genome editing as an effective means for investigating this complexity.

Widespread epistasis among beneficial genetic variants revealed by high-throughput genome editing

The phenotypic effect of any genetic variant can be altered by variation at other genomic loci. Known as epistasis, these genetic interactions shape the genotype-phenotype map of every species, yet their origins remain poorly understood. To investigate this, we employed high-throughput genome editing to measure the fitness effects of 1,826 naturally polymorphic variants in four strains of Saccharomyces cerevisiae. About 31% of variants affect fitness, of which 24% have strain-specific fitness effects indicative of epistasis. We found that beneficial variants are more likely to exhibit genetic interactions and that these interactions can be mediated by specific traits such as flocculation ability. This work suggests that adaptive evolution will often involve trade-offs where a variant is only beneficial in some genetic backgrounds, potentially explaining why many beneficial variants remain polymorphic. In sum, we provide a framework to understand the factors influencing epistasis with single-nucleotide resolution, revealing widespread epistasis among beneficial variants.

DNAsmart: Multiple attribute ranking tool for DNA data storage systems

In an ever-growing need for data storage capacity, the Deoxyribonucleic Acid (DNA) molecule gains traction as a new storage medium with a larger capacity, higher density, and a longer lifespan over conventional storage media. To effectively use DNA for data storage, it is important to understand the different methods of encoding information in DNA and compare their effectiveness. This requires evaluating which decoded DNA sequences carry the most encoded information based on various attributes. However, navigating the field of coding theory requires years of experience and domain expertise. For instance, domain experts rely on various mathematical functions and attributes to score and evaluate their encodings. To enable such analytical tasks, we provide an interactive and visual analytical framework for multi-attribute ranking in DNA storage systems. Our framework follows a three-step view with user-settable parameters. It enables users to find the optimal en-/de-coding approaches by setting different weights and combining multiple attributes. We assess the validity of our work through a task-specific user study on domain experts by relying on three tasks. Results indicate that all participants completed their tasks successfully under two minutes, then rated the framework for design choices, perceived usefulness, and intuitiveness. In addition, two real-world use cases are shared and analyzed as direct applications of the proposed tool. DNAsmart enables the ranking of decoded sequences based on multiple attributes. In sum, this work unveils the evaluation of en-/de-coding approaches accessible and tractable through visualization and interactivity to solve comparison and ranking tasks.

Fast trimer statistics facilitate accurate decoding of large random DNA barcode sets even at large sequencing error rates

Predefined sets of short DNA sequences are commonly used as barcodes to identify individual biomolecules in pooled populations. Such use requires either sufficiently small DNA error rates, or else an error-correction methodology. Most existing DNA error-correcting codes (ECCs) correct only one or two errors per barcode in sets of typically ≲10⁴ barcodes. We here consider the use of random barcodes of sufficient length that they remain accurately decodable even with ≳6 errors and even at [Formula: see text] or 20% nucleotide error rates. We show that length ∼34 nt is sufficient even with ≳10⁶ barcodes. The obvious objection to this scheme is that it requires comparing every read to every possible barcode by a slow Levenshtein or Needleman-Wunsch comparison. We show that several orders of magnitude speedup can be achieved by (i) a fast triage method that compares only trimer (three consecutive nucleotide) occurence statistics, precomputed in linear time for both reads and barcodes, and (ii) the massive parallelism available on today's even commodity-grade Graphics Processing Units (GPUs). With 10⁶ barcodes of length 34 and 10% DNA errors (substitutions and indels), we achieve in simulation 99.9% precision (decode accuracy) with 98.8% recall (read acceptance rate). Similarly high precision with somewhat smaller recall is achievable even with 20% DNA errors. The amortized computation cost on a commodity workstation with two GPUs (2022 capability and price) is estimated as between US$ 0.15 and US$ 0.60 per million decoded reads.

Design considerations for advancing data storage with synthetic DNA for long-term archiving

Deoxyribonucleic acid (DNA) is increasingly emerging as a serious medium for long-term archival data storage because of its remarkable high-capacity, high-storage-density characteristics and its lasting ability to store data for thousands of years. Various encoding algorithms are generally required to store digital information in DNA and to maintain data integrity. Indeed, since DNA is the information carrier, its performance under different processing and storage conditions significantly impacts the capabilities of the data storage system. Therefore, the design of a DNA storage system must meet specific design considerations to be less error-prone, robust and reliable. In this work, we summarize the general processes and technologies employed when using synthetic DNA as a storage medium. We also share the design considerations for sustainable engineering to include viability. We expect this work to provide insight into how sustainable design can be used to develop an efficient and robust synthetic DNA-based storage system for long-term archiving.

An assessment of the mutational load caused by various reactions used in DNA encoded libraries

DNA encoded libraries have become an essential hit-finding tool in early drug discovery. Recent advances in synthetic methods for DNA encoded libraries have expanded the available chemical space, but precisely how each type of chemistry affects the DNA is unstudied. Available assays to quantify the damage are limited to write efficiency, where the ability to ligate DNA onto a working encoded library strand is measured, or qPCR is performed to measure the amplifiability of the DNA. These measures read signal quantity and overall integrity, but do not report on specific damages in the encoded information. Herein, we use next generation sequencing (NGS) to measure the quality of the read signal in order to quantify the truthfulness of the retrieved information. We identify CuAAC to be the worst offender in terms of DNA damage amongst commonly used reactions in DELs, causing an increase of G → T transversions. Furthermore, we show that the analysis provides useful information even in fully elaborated DELs; indeed we see that vestiges of the synthetic history, both chemical and biochemical, are written into the mutational spectra of NGS datasets.

Development of a program for in silico optimized selection of oligonucleotide-based molecular barcodes

Short DNA oligonucleotides (~4 mer) have been used to index samples from different sources, such as in multiplex sequencing. Presently, longer oligonucleotides (8–12 mer) are being used as molecular barcodes with which to distinguish among raw DNA molecules in many high-tech sequence analyses, including low-frequent mutation detection, quantitative transcriptome analysis, and single-cell sequencing. Despite some advantages of using molecular barcodes with random sequences, such an approach, however, makes it impossible to know the exact sequences used in an experiment and can lead to inaccurate interpretation due to misclustering of barcodes arising from the occurrence of unexpected mutations in the barcodes. The present study introduces a tool developed for selecting an optimal barcode subset during molecular barcoding. The program considers five barcode factors: GC content, homopolymers, simple sequence repeats with repeated units of dinucleotides, Hamming distance, and complementarity between barcodes. To evaluate a selected barcode set, penalty scores for the factors are defined based on their distributions observed in random barcodes. The algorithm employed in the program comprises two steps: i) random generation of an initial set and ii) optimal barcode selection via iterative replacement. Users can execute the program by inputting barcode length and the number of barcodes to be generated. Furthermore, the program accepts a user’s own values for other parameters, including penalty scores, for advanced use, allowing it to be applied in various conditions. In many test runs to obtain 100000 barcodes with lengths of 12 nucleotides, the program showed fast performance, efficient enough to generate optimal barcode sequences with merely the use of a desktop PC. We also showed that VFOS has comparable performance, flexibility in program running, consideration of simple sequence repeats, and fast computation time in comparison with other two tools (DNABarcodes and FreeBarcodes). Owing to the versatility and fast performance of the program, we expect that many researchers will opt to apply it for selecting optimal barcode sets during their experiments, including next-generation sequencing.

μCB-seq: microfluidic cell barcoding and sequencing for high-resolution imaging and sequencing of single cells

Single-cell RNA sequencing (scRNA-seq) enables the investigation of complex biological processes in multicellular organisms with high resolution. However, many phenotypic features that are critical to understanding the functional role of cells in a heterogeneous tissue or organ are not directly encoded in the genome and therefore cannot be profiled with scRNA-seq. Quantitative optical microscopy has long been a powerful approach for characterizing diverse cellular phenotypes including cell morphology, protein localization, and chemical composition. Combining scRNA-seq with optical imaging has the potential to provide comprehensive single-cell analysis, allowing for functional integration of gene expression profiling and cell-state characterization. However, it is difficult to track single cells through both measurements; therefore, coupling current scRNA-seq protocols with optical measurements remains a challenge. Here, we report microfluidic cell barcoding and sequencing (μCB-seq), a microfluidic platform that combines high-resolution imaging and sequencing of single cells. μCB-seq is enabled by a novel fabrication method that preloads primers with known barcode sequences inside addressable reaction chambers of a microfluidic device. In addition to enabling multi-modal single-cell analysis, μCB-seq improves gene detection sensitivity, providing a scalable and accurate method for information-rich characterization of single cells.

Tabu Variable Neighborhood Search for Designing DNA Barcodes

Massively parallel sequencing, a popular and efficient sequencing method, produces a tremendous number of sequences from multiple individual samples. Labeling sequences with barcodes (tags) prevents them from being unrecoverable or confused during sequencing, replication, and oligonucleotide synthesis. In view of DNA barcode set design, we propose a tabu variable neighborhood search (TVNS) to design DNA barcode sets. We propose using sequences with the maximum sum of edit distances as the basis for building the neighborhood structures of TVNS. We adopt an exhaustive search to complete local searches built from these structures. The algorithm switches between neighborhoods built from different seed data. Compared with previous designs, our proposed algorithm is effective for designing DNA barcode sets and improving the lower bound of DNA barcode sets.

ANP32 Proteins Are Essential for Influenza Virus Replication in Human Cells

ANP32 proteins have been implicated in supporting influenza virus replication, but most of the work to date has focused on the ability of avian Anp32 proteins to overcome restriction of avian influenza polymerases in human cells. Using a CRISPR approach, we show that the human acidic nuclear phosphoproteins (ANPs) ANP32A and ANP32B are functionally redundant but essential host factors for mammalian-adapted influenza A virus (IAV) and influenza B virus (IBV) replication in human cells. When both proteins are absent from human cells, influenza polymerases are unable to replicate the viral genome, and infectious virus cannot propagate. Provision of exogenous ANP32A or ANP32B recovers polymerase activity and virus growth. We demonstrate that this redundancy is absent in the murine Anp32 orthologues; murine Anp32A is incapable of recovering IAV polymerase activity, while murine Anp32B can do so. Intriguingly, IBV polymerase is able to use murine Anp32A. We show, using a domain swap and point mutations, that the leucine-rich repeat (LRR) 5 region comprises an important functional domain for mammalian ANP32 proteins. Our approach has identified a pair of essential host factors for influenza virus replication and can be harnessed to inform future interventions.IMPORTANCE Influenza virus is the etiological agent behind some of the most devastating infectious disease pandemics to date, and influenza outbreaks still pose a major threat to public health. Influenza virus polymerase, the molecule that copies the viral RNA genome, hijacks cellular proteins to support its replication. Current anti-influenza drugs are aimed against viral proteins, including the polymerase, but RNA viruses like influenza tend to become resistant to such drugs very rapidly. An alternative strategy is to design therapeutics that target the host proteins that are necessary for virus propagation. Here, we show that the human proteins ANP32A and ANP32B are essential for influenza A and B virus replication, such that in their absence cells become impervious to the virus. We map the proviral activity of ANP32 proteins to one region in particular, which could inform future intervention.

DNABarcodeCompatibility: an R-package for optimizing DNA-barcode combinations in multiplex sequencing experiments

Summary

Using adequate DNA barcodes is essential to unambiguously identify each DNA library within a multiplexed set of libraries sequenced using next-generation sequencers. We introduce DNABarcodeCompatibility, an R-package that allows one to design single or dual-barcoding multiplex experiments by imposing desired constraints on the barcodes (including sequencer chemistry, barcode pairwise minimal distance and nucleotide content), while optimizing barcode frequency usage, thereby allowing one to both facilitate the demultiplexing step and spare expensive library-preparation kits. The package comes with a user-friendly interface and a web app developed in Java and Shiny (https://dnabarcodecompatibility.pasteur.fr), respectively, with the aim to help bridge the expertise of core facilities with the experimental needs of non-experienced users.

Availability and implementation

DNABarcodeCompatibility can be easily extended to fulfil specific project needs. The source codes of the R-package and its user interfaces are publicly available along with documentation at [https://github.com/comoto-pasteur-fr] under the GPL-2 licence.

Supplementary information

Supplementary data are available at Bioinformatics online.

NGS-Based High-Throughput Screen to Identify MicroRNAs Regulating Growth of B-Cell Lymphoma

MicroRNAs (miRNAs) play important roles in development, differentiation, and homeostasis by regulating protein translation. In B-cell lymphoma, many miRNAs have altered expression levels, and for a limited subset of them, experimental data supports their functional relevance in lymphoma pathogenesis. This chapter describes an unbiased next-generation sequencing (NGS)-based high-throughput screening approach to identify miRNAs that are involved in the control of cell growth. First, we provide a protocol for performing high-throughput screening for miRNA inhibition and overexpression. Second, we describe the procedure for next-generation sequencing library preparation. Third, we provide a workflow for data analysis.

Bacterial and fungal communities in boreal forest soil are insensitive to changes in snow cover conditions

The northern regions are experiencing considerable changes in winter climate leading to more frequent warm periods, rain-on-snow events and reduced snow pack diminishing the insulation properties of snow cover and increasing soil frost and freeze-thaw cycles. In this study, we investigated how the lack of snow cover, formation of ice encasement and snow compaction affect the size, structure and activities of soil bacterial and fungal communities. Contrary to our hypotheses, snow manipulation treatments over one winter had limited influence on microbial community structure, bacterial or fungal copy numbers or enzyme activities. However, microbial community structure and activities shifted seasonally among soils sampled before snow melt, in early and late growing season and seemed driven by substrate availability. Bacterial and fungal communities were dominated by stress-resistant taxa such as the orders Acidobacteriales, Chaetothyriales and Helotiales that are likely adapted to adverse winter conditions. This study indicated that microbial communities in acidic northern boreal forest soil may be insensitive to direct effects of changing snow cover. However, in long term, the detrimental effects of increased ice and frost to plant roots may alter plant derived carbon and nutrient pools to the soil likely leading to stronger microbial responses.

Towards Quantitative Microbiome Community Profiling Using Internal Standards

An inherent issue in high-throughput rRNA gene tag sequencing microbiome surveys is that they provide compositional data in relative abundances. This often leads to spurious correlations, making the interpretation of relationships to biogeochemical rates challenging. To overcome this issue, we quantitatively estimated the abundance of microorganisms by spiking in known amounts of internal DNA standards. Using a 3-year sample set of diverse microbial communities from the Western Antarctica Peninsula, we demonstrated that the internal standard method yielded community profiles and taxon cooccurrence patterns substantially different from those derived using relative abundances. We found that the method provided results consistent with the traditional CHEMTAX analysis of pigments and total bacterial counts by flow cytometry. Using the internal standard method, we also showed that chloroplast 16S rRNA gene data in microbial surveys can be used to estimate abundances of certain eukaryotic phototrophs such as cryptophytes and diatoms. In Phaeocystis, scatter in the 16S/18S rRNA gene ratio may be explained by physiological adaptation to environmental conditions. We conclude that the internal standard method, when applied to rRNA gene microbial community profiling, is quantitative and that its application will substantially improve our understanding of microbial ecosystems.IMPORTANCE High-throughput-sequencing-based marine microbiome profiling is rapidly expanding and changing how we study the oceans. Although powerful, the technique is not fully quantitative; it provides taxon counts only in relative abundances. In order to address this issue, we present a method to quantitatively estimate microbial abundances per unit volume of seawater filtered by spiking known amounts of internal DNA standards into each sample. We validated this method by comparing the calculated abundances to other independent estimates, including chemical markers (pigments) and total bacterial cell counts by flow cytometry. The internal standard approach allows us to quantitatively estimate and compare marine microbial community profiles, with important implications for linking environmental microbiomes to quantitative processes such as metabolic and biogeochemical rates.

Spatiotemporal m(i)RNA Architecture and 3' UTR Regulation in the C. elegans Germline

In animal germlines, regulation of cell proliferation and differentiation is particularly important but poorly understood. Here, using a cryo-cut approach, we mapped RNA expression along the Caenorhabditis elegans germline and, using mutants, dissected gene regulatory mechanisms that control spatiotemporal expression. We detected, at near single-cell resolution, >10,000 mRNAs, >300 miRNAs, and numerous unannotated miRNAs. Most RNAs were organized in distinct spatial patterns. Germline-specific miRNAs and their targets were co-localized. Moreover, we observed differential 3' UTR isoform usage for hundreds of mRNAs. In tumorous gld-2 gld-1 mutants, gene expression was strongly perturbed. In particular, differential 3' UTR usage was significantly impaired. We propose that PIE-1, a transcriptional repressor, functions to maintain spatial gene expression. Our data also suggest that cpsf-4 and fipp-1 control differential 3' UTR usage for hundreds of genes. Finally, we constructed a "virtual gonad" enabling "virtual in situ hybridizations" and access to all data (https://shiny.mdc-berlin.de/spacegerm/).

A highly parallel strategy for storage of digital information in living cells

BACKGROUND

Encoding arbitrary digital information in DNA has attracted attention as a potential avenue for large scale and long term data storage. However, in order to enable DNA data storage technologies there needs to be improvements in data storage fidelity (tolerance to mutation), the facility of writing and reading the data (biases and systematic error arising from synthesis and sequencing), and overall scalability.

RESULTS

To this end, we have developed and implemented an encoding scheme that is suitable for detecting and correcting errors that may arise during storage, writing, and reading, such as those arising from nucleotide substitutions, insertions, and deletions. We propose a scheme for parallelized long term storage of encoded sequences that relies on overlaps rather than the address blocks found in previously published work. Using computer simulations, we illustrate the encoding, sequencing, decoding, and recovery of encoded information, ultimately demonstrating the possibility of a successful round-trip read/write. These demonstrations show that in theory a precise control over error tolerance is possible. Even after simulated degradation of DNA, recovery of original data is possible owing to the error correction capabilities built into the encoding strategy. A secondary advantage of our method is that the statistical characteristics (such as repetitiveness and GC-composition) of encoded sequences can also be tailored without sacrificing the overall ability to store large amounts of data. Finally, the combination of the overlap-based partitioning of data with the LZMA compression that is integral to encoding means that the entire sequence must be present for successful decoding. This feature enables inordinately strong encryptions. As a potential application, an encrypted pathogen genome could be distributed and carried by cells without danger of being expressed, and could not even be read out in the absence of the entire DNA consortium.

CONCLUSIONS

We have developed a method for DNA encoding, using a significantly different fundamental approach from existing work, which often performs better than alternatives and allows for a great deal of freedom and flexibility of application.

Molecular archaeoparasitology identifies cultural changes in the Medieval Hanseatic trading centre of Lübeck

Throughout history, humans have been afflicted by parasitic worms, and eggs are readily detected in archaeological deposits. This study integrated parasitological and ancient DNA methods with a large sample set dating between Neolithic and Early Modern periods to explore the utility of molecular archaeoparasitology as a new approach to study the past. Molecular analyses provided unequivocal species-level parasite identification and revealed location-specific epidemiological signatures. Faecal–oral transmitted nematodes (Ascaris lumbricoides and Trichuris trichiura) were ubiquitous across time and space. By contrast, high numbers of food-associated cestodes (Diphyllobothrium latum and Taenia saginata) were restricted to medieval Lübeck. The presence of these cestodes and changes in their prevalence at approximately 1300 CE indicate substantial alterations in diet or parasite availability. Trichuris trichiura ITS-1 sequences grouped into two clades; one ubiquitous and one restricted to medieval Lübeck and Bristol. The high sequence diversity of T.t.ITS-1 detected in Lübeck is consistent with its importance as a Hanseatic trading centre. Collectively, these results introduce molecular archaeoparasitology as an artefact-independent source of historical evidence.

Pairwise library screen systematically interrogates Staphylococcus aureus Cas9 specificity in human cells

Therapeutic genome editing with Staphylococcus aureus Cas9 (SaCas9) requires a rigorous understanding of its potential off-target activity in the human genome. Here we report a high-throughput screening approach to measure SaCas9 genome editing variation in human cells across a large repertoire of 88,692 single guide RNAs (sgRNAs) paired with matched or mismatched target sites in a synthetic cassette. We incorporate randomized barcodes that enable whitelisting of correctly synthesized molecules for further downstream analysis, in order to circumvent the limitation of oligonucleotide synthesis errors. We find SaCas9 sgRNAs with 21-mer or 22-mer spacer sequences are generally more active, although high efficiency 20-mer spacers are markedly less tolerant of mismatches. Using this dataset, we developed an SaCas9 specificity model that performs robustly in ranking off-target sites. The barcoded pairwise library screen enabled high-fidelity recovery of guide-target relationships, providing a scalable framework for the investigation of CRISPR enzyme properties and general nucleic acid interactions.

BARCOSEL: a tool for selecting an optimal barcode set for high-throughput sequencing

BACKGROUND

Current high-throughput sequencing platforms provide capacity to sequence multiple samples in parallel. Different samples are labeled by attaching a short sample specific nucleotide sequence, barcode, to each DNA molecule prior pooling them into a mix containing a number of libraries to be sequenced simultaneously. After sequencing, the samples are binned by identifying the barcode sequence within each sequence read. In order to tolerate sequencing errors, barcodes should be sufficiently apart from each other in sequence space. An additional constraint due to both nucleotide usage and basecalling accuracy is that the proportion of different nucleotides should be in balance in each barcode position. The number of samples to be mixed in each sequencing run may vary and this introduces a problem how to select the best subset of available barcodes at sequencing core facility for each sequencing run. There are plenty of tools available for de novo barcode design, but they are not suitable for subset selection.

RESULTS

We have developed a tool which can be used for three different tasks: 1) selecting an optimal barcode set from a larger set of candidates, 2) checking the compatibility of user-defined set of barcodes, e.g. whether two or more libraries with existing barcodes can be combined in a single sequencing pool, and 3) augmenting an existing set of barcodes. In our approach the selection process is formulated as a minimization problem. We define the cost function and a set of constraints and use integer programming to solve the resulting combinatorial problem. Based on the desired number of barcodes to be selected and the set of candidate sequences given by user, the necessary constraints are automatically generated and the optimal solution can be found. The method is implemented in C programming language and web interface is available at http://ekhidna2.biocenter.helsinki.fi/barcosel .

CONCLUSIONS

Increasing capacity of sequencing platforms raises the challenge of mixing barcodes. Our method allows the user to select a given number of barcodes among the larger existing barcode set so that both sequencing errors are tolerated and the nucleotide balance is optimized. The tool is easy to access via web browser.

Constructing DNA Barcode Sets Based on Particle Swarm Optimization

Following the completion of the human genome project, a large amount of high-throughput bio-data was generated. To analyze these data, massively parallel sequencing, namely next-generation sequencing, was rapidly developed. DNA barcodes are used to identify the ownership between sequences and samples when they are attached at the beginning or end of sequencing reads. Constructing DNA barcode sets provides the candidate DNA barcodes for this application. To increase the accuracy of DNA barcode sets, a particle swarm optimization (PSO) algorithm has been modified and used to construct the DNA barcode sets in this paper. Compared with the extant results, some lower bounds of DNA barcode sets are improved. The results show that the proposed algorithm is effective in constructing DNA barcode sets.

Genomics of cellular proliferation in periodic environmental fluctuations

Living systems control cell growth dynamically by processing information from their environment. Although responses to a single environmental change have been intensively studied, little is known about how cells react to fluctuating conditions. Here, we address this question at the genomic scale by measuring the relative proliferation rate (fitness) of 3,568 yeast gene deletion mutants in out-of-equilibrium conditions: periodic oscillations between two environmental conditions. In periodic salt stress, fitness and its genetic variance largely depended on the oscillating period. Surprisingly, dozens of mutants displayed pronounced hyperproliferation under short stress periods, revealing unexpected controllers of growth under fast dynamics. We validated the implication of the high-affinity cAMP phosphodiesterase and of a regulator of protein translocation to mitochondria in this group. Periodic oscillations of extracellular methionine, a factor unrelated to salinity, also altered fitness but to a lesser extent and for different genes. The results illustrate how natural selection acts on mutations in a dynamic environment, highlighting unsuspected genetic vulnerabilities to periodic stress in molecular processes that are conserved across all eukaryotes.

DNABarcodes: an R package for the systematic construction of DNA sample tags

Motivation

DNA barcodes are commonly used for counting and discriminating purposes in molecular and cell biology. Not every set of DNA sequences is equally suitable for this goal. There is a growing demand for more sophisticated barcode designs, with only few tools available. We prepared an R package that combines known algorithms and innovative methods for the efficient, flexible and near-optimal generation of robust barcode sets.

Results

Our R-software package 'DNABarcodes' generates sets of DNA barcodes from a few basic input parameters (e.g. length, distance metric, minimum distance, chemical properties). It satisfies the specifics of most particular experimental demands in de novo design of barcodes. Additionally, the package allows analysing existing sets of DNA barcodes as well as the generation of subsets of those existing sets to improve their error correction and detection properties. 'DNABarcodes' was designed for speed, versatility, provable correctness and large set sizes.

Availability and Implementation

The DNABarcodes R package is available from Bioconductor at http://bioconductor.org/packages/DNABarcodes under the GPL-2 license.

Contact

tilo.buschmann@izi.fraunhofer.de.

Supplementary information

Supplementary data are available at Bioinformatics online.

Large-scale DNA Barcode Library Generation for Biomolecule Identification in High-throughput Screens

High-throughput screens allow for the identification of specific biomolecules with characteristics of interest. In barcoded screens, DNA barcodes are linked to target biomolecules in a manner allowing for the target molecules making up a library to be identified by sequencing the DNA barcodes using Next Generation Sequencing. To be useful in experimental settings, the DNA barcodes in a library must satisfy certain constraints related to GC content, homopolymer length, Hamming distance, and blacklisted subsequences. Here we report a novel framework to quickly generate large-scale libraries of DNA barcodes for use in high-throughput screens. We show that our framework dramatically reduces the computation time required to generate large-scale DNA barcode libraries, compared with a naїve approach to DNA barcode library generation. As a proof of concept, we demonstrate that our framework is able to generate a library consisting of one million DNA barcodes for use in a fragment antibody phage display screening experiment. We also report generating a general purpose one billion DNA barcode library, the largest such library yet reported in literature. Our results demonstrate the value of our novel large-scale DNA barcode library generation framework for use in high-throughput screening applications.

Digitally Barcoding Mycobacterium tuberculosis Reveals In Vivo Infection Dynamics in the Macaque Model of Tuberculosis

Infection with Mycobacterium tuberculosis causes a spectrum of outcomes; the majority of individuals contain but do not eliminate the infection, while a small subset present with primary active tuberculosis (TB) disease. This variability in infection outcomes is recapitulated at the granuloma level within each host, such that some sites of infection can be fully cleared while others progress. Understanding the spectrum of TB outcomes requires new tools to deconstruct the mechanisms underlying differences in granuloma fate. Here, we use novel genome-encoded barcodes to uniquely tag individual M. tuberculosis bacilli, enabling us to quantitatively track the trajectory of each infecting bacterium in a macaque model of TB. We also introduce a robust bioinformatics pipeline capable of identifying and counting barcode sequences within complex mixtures and at various read depths. By coupling this tagging strategy with serial positron emission tomography coregistered with computed tomography (PET/CT) imaging of lung pathology in macaques, we define a lesional map of M. tuberculosis infection dynamics. We find that there is no significant infection bottleneck, but there are significant constraints on productive bacterial trafficking out of primary granulomas. Our findings validate our barcoding approach and demonstrate its utility in probing lesion-specific biology and dissemination. This novel technology has the potential to greatly enhance our understanding of local dynamics in tuberculosis.

Classically, M. tuberculosis infection was thought to result in either latent infection or active disease. More recently, the field has recognized that there is a spectrum of M. tuberculosis infection clinical outcomes. Within a single host, this spectrum is recapitulated at the granuloma level, where there can simultaneously be lesional sterilization and poorly contained disease. To better understand the lesional biology of TB infection, we digitally barcoded M. tuberculosis to quantitatively track the fate of each infecting bacterium. By combining this technology with serial PET-CT imaging, we can dynamically track both bacterial populations and granuloma trajectories. We demonstrate that there is little constraint on the bacterial population at the time of infection. However, the granuloma imposes a strong bottleneck on dissemination, and the subset of granulomas at risk of dissemination can be distinguished by physical features.

Clonal selection and asymmetric distribution of human leukemia in murine xenografts revealed by cellular barcoding

Genetic and phenotypic heterogeneity of human leukemia is thought to drive leukemia progression through a Darwinian process of selection and evolution of increasingly malignant clones. However, the lack of markers that uniquely identify individual leukemia clones precludes high-resolution tracing of their clonal dynamics. Here, we use cellular barcoding to analyze the clonal behavior of patient-derived leukemia-propagating cells (LPCs) in murine xenografts. Using a leukemic cell line and diagnostic bone marrow cells from 6 patients with B-progenitor cell acute lymphoblastic leukemia, we demonstrate that patient-derived xenografts were highly polyclonal, consisting of tens to hundreds of LPC clones. The number of clones was stable within xenografts but strongly reduced upon serial transplantation. In contrast to primary recipients, in which clonal composition was highly diverse, clonal composition in serial xenografts was highly similar between recipients of the same donor and reflected donor clonality, supporting a deterministic, clone-size-based model for clonal selection. Quantitative analysis of clonal abundance in several anatomic sites identified 2 types of anatomic asymmetry. First, clones were asymmetrically distributed between different bones. Second, clonal composition in the skeleton significantly differed from extramedullary sites, showing similar numbers but different clone sizes. Altogether, this study shows that cellular barcoding and xenotransplantation providea useful model to study the behavior of patient-derived LPC clones, which provides insights relevant for experimental studies on cancer stem cells and for clinical protocols for the diagnosis and treatment of leukemia.

From next-generation resequencing reads to a high-quality variant data set

Sequencing has revolutionized biology by permitting the analysis of genomic variation at an unprecedented resolution. High-throughput sequencing is fast and inexpensive, making it accessible for a wide range of research topics. However, the produced data contain subtle but complex types of errors, biases and uncertainties that impose several statistical and computational challenges to the reliable detection of variants. To tap the full potential of high-throughput sequencing, a thorough understanding of the data produced as well as the available methodologies is required. Here, I review several commonly used methods for generating and processing next-generation resequencing data, discuss the influence of errors and biases together with their resulting implications for downstream analyses and provide general guidelines and recommendations for producing high-quality single-nucleotide polymorphism data sets from raw reads by highlighting several sophisticated reference-based methods representing the current state of the art.

16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

The human impact on natural habitats is increasing the complexity of human-wildlife interactions and leading to the emergence of infectious diseases worldwide. Highly successful synanthropic wildlife species, such as rodents, will undoubtedly play an increasingly important role in transmitting zoonotic diseases. We investigated the potential for recent developments in 16S rRNA amplicon sequencing to facilitate the multiplexing of the large numbers of samples needed to improve our understanding of the risk of zoonotic disease transmission posed by urban rodents in West Africa. In addition to listing pathogenic bacteria in wild populations, as in other high-throughput sequencing (HTS) studies, our approach can estimate essential parameters for studies of zoonotic risk, such as prevalence and patterns of coinfection within individual hosts. However, the estimation of these parameters requires cleaning of the raw data to mitigate the biases generated by HTS methods. We present here an extensive review of these biases and of their consequences, and we propose a comprehensive trimming strategy for managing these biases. We demonstrated the application of this strategy using 711 commensal rodents, including 208 Mus musculus domesticus, 189 Rattus rattus, 93 Mastomys natalensis, and 221 Mastomys erythroleucus, collected from 24 villages in Senegal. Seven major genera of pathogenic bacteria were detected in their spleens: Borrelia, Bartonella, Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia. Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia have never before been detected in West African rodents. Bacterial prevalence ranged from 0% to 90% of individuals per site, depending on the bacterial taxon, rodent species, and site considered, and 26% of rodents displayed coinfection. The 16S rRNA amplicon sequencing strategy presented here has the advantage over other molecular surveillance tools of dealing with a large spectrum of bacterial pathogens without requiring assumptions about their presence in the samples. This approach is therefore particularly suitable to continuous pathogen surveillance in the context of disease-monitoring programs. IMPORTANCE Several recent public health crises have shown that the surveillance of zoonotic agents in wildlife is important to prevent pandemic risks. High-throughput sequencing (HTS) technologies are potentially useful for this surveillance, but rigorous experimental processes are required for the use of these effective tools in such epidemiological contexts. In particular, HTS introduces biases into the raw data set that might lead to incorrect interpretations. We describe here a procedure for cleaning data before estimating reliable biological parameters, such as positivity, prevalence, and coinfection, using 16S rRNA amplicon sequencing on an Illumina MiSeq platform. This procedure, applied to 711 rodents collected in West Africa, detected several zoonotic bacterial species, including some at high prevalence, despite their never before having been reported for West Africa. In the future, this approach could be adapted for the monitoring of other microbes such as protists, fungi, and even viruses.

Accurate Sample Assignment in a Multiplexed, Ultrasensitive, High-Throughput Sequencing Assay for Minimal Residual Disease

High-throughput sequencing (HTS) (next-generation sequencing) of the rearranged Ig and T-cell receptor genes promises to be less expensive and more sensitive than current methods of monitoring minimal residual disease (MRD) in patients with acute lymphoblastic leukemia. However, the adoption of new approaches by clinical laboratories requires careful evaluation of all potential sources of error and the development of strategies to ensure the highest accuracy. Timely and efficient clinical use of HTS platforms will depend on combining multiple samples (multiplexing) in each sequencing run. Here we examine the Ig heavy-chain gene HTS on the Illumina MiSeq platform for MRD. We identify errors associated with multiplexing that could potentially impact the accuracy of MRD analysis. We optimize a strategy that combines high-purity, sequence-optimized oligonucleotides, dual indexing, and an error-aware demultiplexing approach to minimize errors and maximize sensitivity. We present a probability-based, demultiplexing pipeline Error-Aware Demultiplexer that is suitable for all MiSeq strategies and accurately assigns samples to the correct identifier without excessive loss of data. Finally, using controls quantified by digital PCR, we show that HTS-MRD can accurately detect as few as 1 in 10(6) copies of specific leukemic MRD.

Reproducibility of Illumina platform deep sequencing errors allows accurate determination of DNA barcodes in cells

Background

Next generation sequencing (NGS) of amplified DNA is a powerful tool to describe genetic heterogeneity within cell populations that can both be used to investigate the clonal structure of cell populations and to perform genetic lineage tracing. For applications in which both abundant and rare sequences are biologically relevant, the relatively high error rate of NGS techniques complicates data analysis, as it is difficult to distinguish rare true sequences from spurious sequences that are generated by PCR or sequencing errors. This issue, for instance, applies to cellular barcoding strategies that aim to follow the amount and type of offspring of single cells, by supplying these with unique heritable DNA tags.

Results

Here, we use genetic barcoding data from the Illumina HiSeq platform to show that straightforward read threshold-based filtering of data is typically insufficient to filter out spurious barcodes. Importantly, we demonstrate that specific sequencing errors occur at an approximately constant rate across different samples that are sequenced in parallel. We exploit this observation by developing a novel approach to filter out spurious sequences.

Conclusions

Application of our new method demonstrates its value in the identification of true sequences amongst spurious sequences in biological data sets.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0999-4) contains supplementary material, which is available to authorized users.

Structural homology guided alignment of cysteine rich proteins

Background

Cysteine rich protein families are notoriously difficult to align due to low sequence identity and frequent insertions and deletions.

Results

Here we present an alignment method that ensures homologous cysteines align by assigning a unique 10 amino acid barcode to those identified as structurally homologous by the DALI webserver. The free inter-cysteine regions of the barcoded sequences can then be aligned using any standard algorithm. Finally the barcodes are replaced with the original columns to yield an alignment which requires the minimum of manual refinement.

Conclusions

Using structural homology information to constrain sequence alignments allows the alignment of highly divergent, repetitive sequences that are poorly dealt with by existing algorithms. Tools are provided to perform this method online using the CysBar web-tool (http://CysBar.science.latrobe.edu.au) and offline (python script available from http://github.com/ts404/CysBar).

Electronic supplementary material

The online version of this article (doi:10.1186/s40064-015-1609-z) contains supplementary material, which is available to authorized users.

Clonal Analysis of Cells with Cellular Barcoding: When Numbers and Sizes Matter

Cellular barcoding is a recently rediscovered tool to trace the clonal output of individual cells with genetically distinct and heritable DNA sequences. Each year a few dozens of papers are published using the cellular barcoding technique. Those publications largely focus on mutually related issues, namely: counting cells capable of clonal proliferation and expansion, monitoring clonal dynamics in time, tracing the origin of differentiated cells, characterizing the differentiation potential of stem cells and similar topics. Apart from their biological content, claims and conclusions, these studies show remarkable diversity in technical aspects of the barcoding method and sometimes in major conclusions. Although a diversity of approaches is quite usual in data analysis, deviant handling of barcode data might directly affect experimental results and their biological interpretation. Here, we will describe typical challenges and caveats in cellular barcoding publications available so far.

DNA Barcoding through Quaternary LDPC Codes

For many parallel applications of Next-Generation Sequencing (NGS) technologies short barcodes able to accurately multiplex a large number of samples are demanded. To address these competitive requirements, the use of error-correcting codes is advised. Current barcoding systems are mostly built from short random error-correcting codes, a feature that strongly limits their multiplexing accuracy and experimental scalability. To overcome these problems on sequencing systems impaired by mismatch errors, the alternative use of binary BCH and pseudo-quaternary Hamming codes has been proposed. However, these codes either fail to provide a fine-scale with regard to size of barcodes (BCH) or have intrinsic poor error correcting abilities (Hamming). Here, the design of barcodes from shortened binary BCH codes and quaternary Low Density Parity Check (LDPC) codes is introduced. Simulation results show that although accurate barcoding systems of high multiplexing capacity can be obtained with any of these codes, using quaternary LDPC codes may be particularly advantageous due to the lower rates of read losses and undetected sample misidentification errors. Even at mismatch error rates of 10⁻² per base, 24-nt LDPC barcodes can be used to multiplex roughly 2000 samples with a sample misidentification error rate in the order of 10⁻⁹ at the expense of a rate of read losses just in the order of 10⁻⁶.

Two new phragmotic ant species from Africa: morphology and next-generation sequencing solve a caste association problem in the genus Carebara Westwood

Phragmotic or "door head" ants have evolved independently in several ant genera across the world, but in Africa only one case has been documented until now. Carebara elmenteitae (Patrizi) is known from only a single phragmotic major worker collected from sifted leaf-litter near Lake Elmenteita in Kenya, but here the worker castes of two species collected from Kakamega Forest, a small rainforest in Western Kenya, are studied. Phragmotic major workers were previously identified as Carebara elmenteitae and non-phragmotic major and minor workers were assigned to Carebara thoracica (Weber). Using evidence of both morphological and next-generation sequencing analysis, it is shown that phragmotic and non-phragmotic workers of the two different species are actually the same and that neither name - Carebara elmenteitae or Carebara thoracica - correctly applies to them. Instead, this and another closey related species from Ivory Coast are both morphologically different from Carebara elmenteitae, and thus they are described as the new species Carebara phragmotica sp. n. and Carebara lilith sp. n.

DNA-Encoded Solid-Phase Synthesis: Encoding Language Design and Complex Oligomer Library Synthesis

The promise of exploiting combinatorial synthesis for small molecule discovery remains unfulfilled due primarily to the “structure elucidation problem”: the back-end mass spectrometric analysis that significantly restricts one-bead-one-compound (OBOC) library complexity. The very molecular features that confer binding potency and specificity, such as stereochemistry, regiochemistry, and scaffold rigidity, are conspicuously absent from most libraries because isomerism introduces mass redundancy and diverse scaffolds yield uninterpretable MS fragmentation. Here we present DNA-encoded solid-phase synthesis (DESPS), comprising parallel compound synthesis in organic solvent and aqueous enzymatic ligation of unprotected encoding dsDNA oligonucleotides. Computational encoding language design yielded 148 thermodynamically optimized sequences with Hamming string distance ≥ 3 and total read length <100 bases for facile sequencing. Ligation is efficient (70% yield), specific, and directional over 6 encoding positions. A series of isomers served as a testbed for DESPS’s utility in split-and-pool diversification. Single-bead quantitative PCR detected 9 × 10⁴ molecules/bead and sequencing allowed for elucidation of each compound’s synthetic history. We applied DESPS to the combinatorial synthesis of a 75 645-member OBOC library containing scaffold, stereochemical and regiochemical diversity using mixed-scale resin (160-μm quality control beads and 10-μm screening beads). Tandem DNA sequencing/MALDI-TOF MS analysis of 19 quality control beads showed excellent agreement (<1 ppt) between DNA sequence-predicted mass and the observed mass. DESPS synergistically unites the advantages of solid-phase synthesis and DNA encoding, enabling single-bead structural elucidation of complex compounds and synthesis using reactions normally considered incompatible with unprotected DNA. The widespread availability of inexpensive oligonucleotide synthesis, enzymes, DNA sequencing, and PCR make implementation of DESPS straightforward, and may prompt the chemistry community to revisit the synthesis of more complex and diverse libraries.

Low-Cost, High-Throughput Sequencing of DNA Assemblies Using a Highly Multiplexed Nextera Process

In recent years, next-generation sequencing (NGS) technology has greatly reduced the cost of sequencing whole genomes, whereas the cost of sequence verification of plasmids via Sanger sequencing has remained high. Consequently, industrial-scale strain engineers either limit the number of designs or take short cuts in quality control. Here, we show that over 4000 plasmids can be completely sequenced in one Illumina MiSeq run for less than $3 each (15× coverage), which is a 20-fold reduction over using Sanger sequencing (2× coverage). We reduced the volume of the Nextera tagmentation reaction by 100-fold and developed an automated workflow to prepare thousands of samples for sequencing. We also developed software to track the samples and associated sequence data and to rapidly identify correctly assembled constructs having the fewest defects. As DNA synthesis and assembly become a centralized commodity, this NGS quality control (QC) process will be essential to groups operating high-throughput pipelines for DNA construction.

GBSX: a toolkit for experimental design and demultiplexing genotyping by sequencing experiments

Background

Massive parallel sequencing is a powerful tool for variant discovery and genotyping. To reduce costs, sequencing of restriction enzyme based reduced representation libraries can be utilized. This technology is generally referred to as Genotyping By Sequencing (GBS). To deal with GBS experimental design and initial processing specific bioinformatic tools are needed.

Results

GBSX is a package that assists in selecting the appropriate enzyme and the design of compatible in-line barcodes. Post sequencing, it performs optimized demultiplexing using these barcodes to create fastq files per barcode which can easily be plugged into existing variant analysis pipelines. Here we demonstrate the usability of the GBSX toolkit and demonstrate improved in-line barcode demultiplexing and trimming performance compared to existing tools.

Conclusions

GBSX provides an easy to use suite of tools for designing and demultiplexing of GBS experiments.

Improved lower bounds of DNA tags based on a modified genetic algorithm

The well-known massively parallel sequencing method is efficient and it can obtain sequence data from multiple individual samples. In order to ensure that sequencing, replication, and oligonucleotide synthesis errors do not result in tags (or barcodes) that are unrecoverable or confused, the tag sequences should be abundant and sufficiently different. Recently, many design methods have been proposed for correcting errors in data using error-correcting codes. The existing tag sets contain small tag sequences, so we used a modified genetic algorithm to improve the lower bound of the tag sets in this study. Compared with previous research, our algorithm is effective for designing sets of DNA tags. Moreover, the GC content determined by existing methods includes an imprecise range. Thus, we improved the GC content determination method to obtain tag sets that control the GC content in a more precise range. Finally, previous studies have only considered perfect self-complementarity. Thus, we considered the crossover between different tags and introduced an improved constraint into the design of tag sets.

Insertion and deletion correcting DNA barcodes based on watermarks

Background

Barcode multiplexing is a key strategy for sharing the rising capacity of next-generation sequencing devices: Synthetic DNA tags, called barcodes, are attached to natural DNA fragments within the library preparation procedure. Different libraries, can individually be labeled with barcodes for a joint sequencing procedure. A post-processing step is needed to sort the sequencing data according to their origin, utilizing these DNA labels. The final separation step is called demultiplexing and is mainly determined by the characteristics of the DNA code words used as labels.

Currently, we are facing two different strategies for barcoding: One is based on the Hamming distance, the other uses the edit metric to measure distances of code words. The theory of channel coding provides well-known code constructions for Hamming metric. They provide a large number of code words with variable lengths and maximal correction capability regarding substitution errors. However, some sequencing platforms are known to have exceptional high numbers of insertion or deletion errors. Barcodes based on the edit distance can take insertion and deletion errors into account in the decoding process. Unfortunately, there is no explicit code-construction known that gives optimal codes for edit metric.

Results

In the present work we focus on an entirely different perspective to obtain DNA barcodes. We consider a concatenated code construction, producing so-called watermark codes, which were first proposed by Davey and Mackay, to communicate via binary channels with synchronization errors. We adapt and extend the concepts of watermark codes to use them for DNA sequencing. Moreover, we provide an exemplary set of barcodes that are experimentally compatible with common next-generation sequencing platforms. Finally, a realistic simulation scenario is use to evaluate the proposed codes to show that the watermark concept is suitable for DNA sequencing applications.

Conclusion

Our adaption of watermark codes enables the construction of barcodes that are capable of correcting substitutions, insertion and deletion errors. The presented approach has the advantage of not needing any markers or technical sequences to recover the position of the barcode in the sequencing reads, which poses a significant restriction with other approaches.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0482-7) contains supplementary material, which is available to authorized users.

Impact of three Illumina library construction methods on GC bias and HLA genotype calling

Next-generation sequencing (NGS) is increasingly recognized for its ability to overcome allele ambiguity and deliver high-resolution typing in the HLA system. Using this technology, non-uniform read distribution can impede the reliability of variant detection, which renders high-confidence genotype calling particularly difficult to achieve in the polymorphic HLA complex. Recently, library construction has been implicated as the dominant factor in instigating coverage bias. To study the impact of this phenomenon on HLA genotyping, we performed long-range PCR on 12 samples to amplify HLA-A, -B, -C, -DRB1, and -DQB1, and compared the relative contribution of three Illumina library construction methods (TruSeq Nano, Nextera, Nextera XT) in generating downstream bias. Here, we show high GC% to be a good predictor of low sequencing depth. Compared to standard TruSeq Nano, GC bias was more prominent in transposase-based protocols, particularly Nextera XT, likely through a combination of transposase insertion bias being coupled with a high number of PCR enrichment cycles. Importantly, our findings demonstrate non-uniform read depth can have a direct and negative impact on the robustness of HLA genotyping, which has clinical implications for users when choosing a library construction strategy that aims to balance cost and throughput with data quality.

Protocols for metagenomic DNA extraction and Illumina amplicon library preparation for faecal and swab samples

Next-generation sequencing (NGS) technology has extraordinarily enhanced the scope of research in the life sciences. To broaden the application of NGS to systems that were previously difficult to study, we present protocols for processing faecal and swab samples into amplicon libraries amenable to Illumina sequencing. We developed and tested a novel metagenomic DNA extraction approach using solid phase reversible immobilization (SPRI) beads on Western Bluebird (Sialia mexicana) samples stored in RNAlater. Compared with the MO BIO PowerSoil Kit, the current standard for the Human and Earth Microbiome Projects, the SPRI-based method produced comparable 16S rRNA gene PCR amplification from faecal extractions but significantly greater DNA quality, quantity and PCR success for both cloacal and oral swab samples. We furthermore modified published protocols for preparing highly multiplexed Illumina libraries with minimal sample loss and without post-adapter ligation amplification. Our library preparation protocol was successfully validated on three sets of heterogeneous amplicons (16S rRNA gene amplicons from SPRI and PowerSoil extractions as well as control arthropod COI gene amplicons) that were sequenced across three independent, 250-bp, paired-end runs on Illumina's MiSeq platform. Sequence analyses revealed largely equivalent results from the SPRI and PowerSoil extractions. Our comprehensive strategies focus on maximizing efficiency and minimizing costs. In addition to increasing the feasibility of using minimally invasive sampling and NGS capabilities in avian research, our methods are notably not avian-specific and thus applicable to many research programmes that involve DNA extraction and amplicon sequencing.

Degenerate adaptor sequences for detecting PCR duplicates in reduced representation sequencing data improve genotype calling accuracy

RAD-tag is a powerful tool for high-throughput genotyping. It relies on PCR amplification of the starting material, following enzymatic digestion and sequencing adaptor ligation. Amplification introduces duplicate reads into the data, which arise from the same template molecule and are statistically nonindependent, potentially introducing errors into genotype calling. In shotgun sequencing, data duplicates are removed by filtering reads starting at the same position in the alignment. However, restriction enzymes target specific locations within the genome, causing reads to start in the same place, and making it difficult to estimate the extent of PCR duplication. Here, we introduce a slight change to the Illumina sequencing adaptor chemistry, appending a unique four-base tag to the first index read, which allows duplicate discrimination in aligned data. This approach was validated on the Illumina MiSeq platform, using double-digest libraries of ants (Wasmannia auropunctata) and yeast (Saccharomyces cerevisiae) with known genotypes, producing modest though statistically significant gains in the odds of calling a genotype accurately. More importantly, removing duplicates also corrected for strong sample-to-sample variability of genotype calling accuracy seen in the ant samples. For libraries prepared from low-input degraded museum bird samples (Mixornis gularis), which had low complexity, having been generated from relatively few starting molecules, adaptor tags show that virtually all of the genotypes were called with inflated confidence as a result of PCR duplicates. Quantification of library complexity by adaptor tagging does not significantly increase the difficulty of the overall workflow or its cost, but corrects for differences in quality between samples and permits analysis of low-input material.

Enhancing the detection of barcoded reads in high throughput DNA sequencing data by controlling the false discovery rate

BACKGROUND

DNA barcodes are short unique sequences used to label DNA or RNA-derived samples in multiplexed deep sequencing experiments. During the demultiplexing step, barcodes must be detected and their position identified. In some cases (e.g., with PacBio SMRT), the position of the barcode and DNA context is not well defined. Many reads start inside the genomic insert so that adjacent primers might be missed. The matter is further complicated by coincidental similarities between barcode sequences and reference DNA. Therefore, a robust strategy is required in order to detect barcoded reads and avoid a large number of false positives or negatives.For mass inference problems such as this one, false discovery rate (FDR) methods are powerful and balanced solutions. Since existing FDR methods cannot be applied to this particular problem, we present an adapted FDR method that is suitable for the detection of barcoded reads as well as suggest possible improvements.

RESULTS

In our analysis, barcode sequences showed high rates of coincidental similarities with the Mus musculus reference DNA. This problem became more acute when the length of the barcode sequence decreased and the number of barcodes in the set increased. The method presented in this paper controls the tail area-based false discovery rate to distinguish between barcoded and unbarcoded reads. This method helps to establish the highest acceptable minimal distance between reads and barcode sequences. In a proof of concept experiment we correctly detected barcodes in 83% of the reads with a precision of 89%. Sensitivity improved to 99% at 99% precision when the adjacent primer sequence was incorporated in the analysis. The analysis was further improved using a paired end strategy. Following an analysis of the data for sequence variants induced in the Atp1a1 gene of C57BL/6 murine melanocytes by ultraviolet light and conferring resistance to ouabain, we found no evidence of cross-contamination of DNA material between samples.

CONCLUSION

Our method offers a proper quantitative treatment of the problem of detecting barcoded reads in a noisy sequencing environment. It is based on the false discovery rate statistics that allows a proper trade-off between sensitivity and precision to be chosen.

Thermodynamic Post-Processing versus GC-Content Pre-Processing for DNA Codes Satisfying the Hamming Distance and Reverse-Complement Constraints

Stochastic, meta-heuristic and linear construction algorithms for the design of DNA strands satisfying Hamming distance and reverse-complement constraints often use a GC-content constraint to pre-process the DNA strands. Since GC-content is a poor predictor of DNA strand hybridization strength the strands can be filtered by post-processing using thermodynamic calculations. An alternative approach is considered here, where the algorithms are modified to remove consideration of GC-content and rely on post-processing alone to obtain large sets of DNA strands with satisfactory melting temperatures. The two approaches (pre-processing GC-content and post-processing melting temperatures) are compared and are shown to be complementary when large DNA sets are desired. In particular, the second approach can give significant improvements when linear constructions are used.

SASI-Seq: sample assurance Spike-Ins, and highly differentiating 384 barcoding for Illumina sequencing

Background

A minor but significant fraction of samples subjected to next-generation sequencing methods are either mixed-up or cross-contaminated. These events can lead to false or inconclusive results. We have therefore developed SASI-Seq; a process whereby a set of uniquely barcoded DNA fragments are added to samples destined for sequencing. From the final sequencing data, one can verify that all the reads derive from the original sample(s) and not from contaminants or other samples.

Results

By adding a mixture of three uniquely barcoded amplicons, of different sizes spanning the range of insert sizes one would normally use for Illumina sequencing, at a spike-in level of approximately 0.1%, we demonstrate that these fragments remain intimately associated with the sample. They can be detected following even the tightest size selection regimes or exome enrichment and can report the occurrence of sample mix-ups and cross-contamination.

As a consequence of this work, we have designed a set of 384 eleven-base Illumina barcode sequences that are at least 5 changes apart from each other, allowing for single-error correction and very low levels of barcode misallocation due to sequencing error.

Conclusion

SASI-Seq is a simple, inexpensive and flexible tool that enables sample assurance, allows deconvolution of sample mix-ups and reports levels of cross-contamination between samples throughout NGS workflows.

Electronic supplementary material

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Multiplexing clonality: combining RGB marking and genetic barcoding

RGB marking and DNA barcoding are two cutting-edge technologies in the field of clonal cell marking. To combine the virtues of both approaches, we equipped LeGO vectors encoding red, green or blue fluorescent proteins with complex DNA barcodes carrying color-specific signatures. For these vectors, we generated highly complex plasmid libraries that were used for the production of barcoded lentiviral vector particles. In proof-of-principle experiments, we used barcoded vectors for RGB marking of cell lines and primary murine hepatocytes. We applied single-cell polymerase chain reaction to decipher barcode signatures of individual RGB-marked cells expressing defined color hues. This enabled us to prove clonal identity of cells with one and the same RGB color. Also, we made use of barcoded vectors to investigate clonal development of leukemia induced by ectopic oncogene expression in murine hematopoietic cells. In conclusion, by combining RGB marking and DNA barcoding, we have established a novel technique for the unambiguous genetic marking of individual cells in the context of normal regeneration as well as malignant outgrowth. Moreover, the introduction of color-specific signatures in barcodes will facilitate studies on the impact of different variables (e.g. vector type, transgenes, culture conditions) in the context of competitive repopulation studies.