Levenshtein error-correcting barcodes for multiplexed DNA sequencing

A genome-wide atlas of human cell morphology

A key challenge of the modern genomics era is developing empirical data-driven representations of gene function. Here we present the first unbiased morphology-based genome-wide perturbation atlas in human cells, containing three genome-wide genotype-phenotype maps comprising CRISPR-Cas9-based knockouts of >20,000 genes in >30 million cells. Our optical pooled cell profiling platform (PERISCOPE) combines a destainable high-dimensional phenotyping panel (based on Cell Painting) with optical sequencing of molecular barcodes and a scalable open-source analysis pipeline to facilitate massively parallel screening of pooled perturbation libraries. This perturbation atlas comprises high-dimensional phenotypic profiles of individual cells with sufficient resolution to cluster thousands of human genes, reconstruct known pathways and protein-protein interaction networks, interrogate subcellular processes and identify culture media-specific responses. Using this atlas, we identify the poorly characterized disease-associated TMEM251/LYSET as a Golgi-resident transmembrane protein essential for mannose-6-phosphate-dependent trafficking of lysosomal enzymes. In sum, this perturbation atlas and screening platform represents a rich and accessible resource for connecting genes to cellular functions at scale.

Protocol for detecting genomic insulators in Drosophila using insulator-seq, a massively parallel reporter assay

Genomic insulators are DNA elements that prevent transcriptional activation of a promoter by an enhancer when interposed. We present a protocol for insulator-seq that enables high-throughput screening of genomic insulators using a plasmid-based massively parallel reporter assay in Drosophila cultured cells. We describe steps for insulator reporter plasmid library generation, transient transfection into cultured cells, and sequencing library preparation and provide a pipeline for data analysis. For complete details on the use and execution of this protocol, please refer to Tonelli et al.1.

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.

Seasonal shifts and land-use impact: unveiling the gut microbiomes of bank voles (Myodes glareolus) and common voles (Microtus arvalis)

Gut microbial diversity influences the health and vitality of the host, yet it is itself affected by internal and external factors, including land-use. The impact of land-use practices on wild rodents' gut microbiomes remains understudied, despite their abundance and potential as reservoirs for zoonotic pathogens. We examined the bacterial and fungal gut microbiomes of bank voles (Myodes glareolus) and common voles (Microtus arvalis) across grassland and forest habitats with varying land-use intensities and types. We collected rodents seasonally and used 16S rRNA and ITS amplicon sequencing for microbe identification. We found significant differences in alpha and beta diversities between the species, with M. arvalis exhibiting higher diversity. Seasonality emerged as a prominent factor influencing microbial diversity, with significant variations between sampling months. While land-use affects the gut microbiome, its impact is subordinate to seasonal variations. Differential abundance analysis underscores the dynamic nature of microbial composition, with seasonal changes playing a predominant role. Overall, our findings highlight the significant influence of seasonality on gut microbiome diversity and composition in wild rodents, reflecting dietary shifts associated with seasonal changes. Understanding the interplay between environmental factors and microbial communities in wild rodents enahnces our knowledge of ecosystem health and resilience, warranting further investigation.

Deconvolving organogenesis in space and time via spatial transcriptomics in thick tissues

Organ development is guided by a space-time landscape that constraints cell behavior. This landscape is challenging to characterize for the hair follicle - the most abundant mini organ - due to its complex microscopic structure and asynchronous development. We developed 3DEEP, a tissue clearing and spatial transcriptomic strategy for characterizing tissue blocks up to 400 µm in thickness. We captured 371 hair follicles at different stages of organogenesis in 1 mm3 of skin of a 12-hour-old mouse with 6 million transcripts from 81 genes. From this single time point, we deconvoluted follicles by age based on whole-organ molecular pseudotimes to animate a stop-motion 3D atlas of follicle development along its trajectory. We defined molecular stages for hair follicle organogenesis and characterized the order of emergence for its structures, differential signaling dynamics at its top and bottom, morphogen shifts preceding and accompanying structural changes, and series of structural changes leading to the formation of its canal and opening. We further found that hair follicle stem cells and their niche are established and stratified early in organogenesis, before the formation of the hair bulb. Overall, this work demonstrates the power of increased depth of spatial transcriptomics to provide a four-dimensional analysis of organogenesis.

Cryptographic approaches to authenticating synthetic DNA sequences

In a bioeconomy that relies on synthetic DNA sequences, the ability to ensure their authenticity is critical. DNA watermarks can encode identifying data in short sequences and can be combined with error correction and encryption protocols to ensure that sequences are robust to errors and securely communicated. New digital signature techniques allow for public verification that a sequence has not been modified and can contain sufficient information for synthetic DNA to be self-documenting. In translating these techniques from bacteria to more complex genetically modified organisms (GMOs), special considerations must be made to allow for public verification of these products. We argue that these approaches should be widely implemented to assert authorship, increase the traceability, and detect the unauthorized use of synthetic DNA.

Generating barcodes for nanopore sequencing data with PRO

DNA barcodes, short and unique DNA sequences, play a crucial role in sample identification when processing many samples simultaneously, which helps reduce experimental costs. Nevertheless, the low quality of long-read sequencing makes it difficult to identify barcodes accurately, which poses significant challenges for the design of barcodes for large numbers of samples in a single sequencing run. Here, we present a comprehensive study of the generation of barcodes and develop a tool, PRO, that can be used for selecting optimal barcode sets and demultiplexing. We formulate the barcode design problem as a combinatorial problem and prove that finding the optimal largest barcode set in a given DNA sequence space in which all sequences have the same length is theoretically NP-complete. For practical applications, we developed the novel method PRO by introducing the probability divergence between two DNA sequences to expand the capacity of barcode kits while ensuring demultiplexing accuracy. Specifically, the maximum size of the barcode kits designed by PRO is 2,292, which keeps the length of barcodes the same as that of the official ones used by Oxford Nanopore Technologies (ONT). We validated the performance of PRO on a simulated nanopore dataset with high error rates. The demultiplexing accuracy of PRO reached 98.29% for a barcode kit of size 2,922, 4.31% higher than that of Guppy, the official demultiplexing tool. When the size of the barcode kit generated by PRO is the same as the official size provided by ONT, both tools show superior and comparable demultiplexing accuracy.

A high-throughput synthetic biology approach for studying combinatorial chromatin-based transcriptional regulation

The construction of synthetic gene circuits requires the rational combination of multiple regulatory components, but predicting their behavior can be challenging due to poorly understood component interactions and unexpected emergent behaviors. In eukaryotes, chromatin regulators (CRs) are essential regulatory components that orchestrate gene expression. Here, we develop a screening platform to investigate the impact of CR pairs on transcriptional activity in yeast. We construct a combinatorial library consisting of over 1,900 CR pairs and use a high-throughput workflow to characterize the impact of CR co-recruitment on gene expression. We recapitulate known interactions and discover several instances of CR pairs with emergent behaviors. We also demonstrate that supervised machine learning models trained with low-dimensional amino acid embeddings accurately predict the impact of CR co-recruitment on transcriptional activity. This work introduces a scalable platform and machine learning approach that can be used to study how networks of regulatory components impact gene expression.

High-throughput RNA isoform sequencing using programmed cDNA concatenation

Full-length RNA-sequencing methods using long-read technologies can capture complete transcript isoforms, but their throughput is limited. We introduce multiplexed arrays isoform sequencing (MAS-ISO-seq), a technique for programmably concatenating complementary DNAs (cDNAs) into molecules optimal for long-read sequencing, increasing the throughput >15-fold to nearly 40 million cDNA reads per run on the Sequel IIe sequencer. When applied to single-cell RNA sequencing of tumor-infiltrating T cells, MAS-ISO-seq demonstrated a 12- to 32-fold increase in the discovery of differentially spliced genes.

Representing and extracting knowledge from single-cell data

Single-cell analysis is currently one of the most high-resolution techniques to study biology. The large complex datasets that have been generated have spurred numerous developments in computational biology, in particular the use of advanced statistics and machine learning. This review attempts to explain the deeper theoretical concepts that underpin current state-of-the-art analysis methods. Single-cell analysis is covered from cell, through instruments, to current and upcoming models. The aim of this review is to spread concepts which are not yet in common use, especially from topology and generative processes, and how new statistical models can be developed to capture more of biology. This opens epistemological questions regarding our ontology and models, and some pointers will be given to how natural language processing (NLP) may help overcome our cognitive limitations for understanding single-cell data.

Fragment-sequencing unveils local tissue microenvironments at single-cell resolution

Cells collectively determine biological functions by communicating with each other-both through direct physical contact and secreted factors. Consequently, the local microenvironment of a cell influences its behavior, gene expression, and cellular crosstalk. Disruption of this microenvironment causes reciprocal changes in those features, which can lead to the development and progression of diseases. Hence, assessing the cellular transcriptome while simultaneously capturing the spatial relationships of cells within a tissue provides highly valuable insights into how cells communicate in health and disease. Yet, methods to probe the transcriptome often fail to preserve native spatial relationships, lack single-cell resolution, or are highly limited in throughput, i.e. lack the capacity to assess multiple environments simultaneously. Here, we introduce fragment-sequencing (fragment-seq), a method that enables the characterization of single-cell transcriptomes within multiple spatially distinct tissue microenvironments. We apply fragment-seq to a murine model of the metastatic liver to study liver zonation and the metastatic niche. This analysis reveals zonated genes and ligand-receptor interactions enriched in specific hepatic microenvironments. Finally, we apply fragment-seq to other tissues and species, demonstrating the adaptability of our method.

Optimisation of TP53 reporters by systematic dissection of synthetic TP53 response elements

TP53 is a transcription factor that controls multiple cellular processes, including cell cycle arrest, DNA repair and apoptosis. The relation between TP53 binding site architecture and transcriptional output is still not fully understood. Here, we systematically examined in three different cell lines the effects of binding site affinity and copy number on TP53-dependent transcriptional output, and also probed the impact of spacer length and sequence between adjacent binding sites, and of core promoter identity. Paradoxically, we found that high-affinity TP53 binding sites are less potent than medium-affinity sites. TP53 achieves supra-additive transcriptional activation through optimally spaced adjacent binding sites, suggesting a cooperative mechanism. Optimally spaced adjacent binding sites have a ∼10-bp periodicity, suggesting a role for spatial orientation along the DNA double helix. We leveraged these insights to construct a log-linear model that explains activity from sequence features, and to identify new highly active and sensitive TP53 reporters.

A genome-wide atlas of human cell morphology

A key challenge of the modern genomics era is developing data-driven representations of gene function. Here, we present the first unbiased morphology-based genome-wide perturbation atlas in human cells, containing three genome-scale genotype-phenotype maps comprising >20,000 single-gene CRISPR-Cas9-based knockout experiments in >30 million cells. Our optical pooled cell profiling approach (PERISCOPE) combines a de-stainable high-dimensional phenotyping panel (based on Cell Painting1,2) with optical sequencing of molecular barcodes and a scalable open-source analysis pipeline to facilitate massively parallel screening of pooled perturbation libraries. This approach provides high-dimensional phenotypic profiles of individual cells, while simultaneously enabling interrogation of subcellular processes. Our atlas reconstructs known pathways and protein-protein interaction networks, identifies culture media-specific responses to gene knockout, and clusters thousands of human genes by phenotypic similarity. Using this atlas, we identify the poorly-characterized disease-associated transmembrane protein TMEM251/LYSET as a Golgi-resident protein essential for mannose-6-phosphate-dependent trafficking of lysosomal enzymes, showing the power of these representations. In sum, our atlas and screening technology represent a rich and accessible resource for connecting genes to cellular functions at scale.

A biological camera that captures and stores images directly into DNA

The increasing integration between biological and digital interfaces has led to heightened interest in utilizing biological materials to store digital data, with the most promising one involving the storage of data within defined sequences of DNA that are created by de novo DNA synthesis. However, there is a lack of methods that can obviate the need for de novo DNA synthesis, which tends to be costly and inefficient. Here, in this work, we detail a method of capturing 2-dimensional light patterns into DNA, by utilizing optogenetic circuits to record light exposure into DNA, encoding spatial locations with barcoding, and retrieving stored images via high-throughput next-generation sequencing. We demonstrate the encoding of multiple images into DNA, totaling 1152 bits, selective image retrieval, as well as robustness to drying, heat and UV. We also demonstrate successful multiplexing using multiple wavelengths of light, capturing 2 different images simultaneously using red and blue light. This work thus establishes a 'living digital camera', paving the way towards integrating biological systems with digital devices.

Multimodal perturbation analyses of cyclin-dependent kinases reveal a network of synthetic lethalities associated with cell-cycle regulation and transcriptional regulation

Cell-cycle control is accomplished by cyclin-dependent kinases (CDKs), motivating extensive research into CDK targeting small-molecule drugs as cancer therapeutics. Here we use combinatorial CRISPR/Cas9 perturbations to uncover an extensive network of functional interdependencies among CDKs and related factors, identifying 43 synthetic-lethal and 12 synergistic interactions. We dissect CDK perturbations using single-cell RNAseq, for which we develop a novel computational framework to precisely quantify cell-cycle effects and diverse cell states orchestrated by specific CDKs. While pairwise disruption of CDK4/6 is synthetic-lethal, only CDK6 is required for normal cell-cycle progression and transcriptional activation. Multiple CDKs (CDK1/7/9/12) are synthetic-lethal in combination with PRMT5, independent of cell-cycle control. In-depth analysis of mRNA expression and splicing patterns provides multiple lines of evidence that the CDK-PRMT5 dependency is due to aberrant transcriptional regulation resulting in premature termination. These inter-dependencies translate to drug-drug synergies, with therapeutic implications in cancer and other diseases.

Multiplexed protein stability (MPS) profiling of terminal degrons using fluorescent timer libraries in Saccharomyces cerevisiae

N-terminal protein sequences and their proteolytic processing and modifications influence the stability and turnover of proteins by creating potential degrons for cellular proteolytic pathways. Understanding the impact of genetic perturbations of components affecting the processing of protein N-termini and thereby their stability, requires methods compatible with proteome-wide studies of many N-termini simultaneously. Tandem fluorescent timers (tFT) allow the in vivo measurement of protein turnover completely independent of protein abundance and can be deployed for proteome-wide studies. Here we present a protocol for Multiplexed Protein Stability (MPS) profiling of tFT-libraries encoding large numbers of different protein N-termini fused to tFT in the yeast Saccharomyces cerevisiae. This protocol includes fluorescence cell sorting based profiling of these libraries using a pooling approach. Analysis of the sorted pools is done by using multiplexed deep sequencing, in order to generate a stability index for each N-terminally peptide fused to the tFT reporter, and to evaluate half-life changes across all species represented in the library.

Exon architecture controls mRNA m6A suppression and gene expression

N6-methyladenosine (m6A) is the most abundant messenger RNA (mRNA) modification and plays crucial roles in diverse physiological processes. Using a massively parallel assay for m6A (MPm6A), we discover that m6A specificity is globally regulated by suppressors that prevent m6A deposition in unmethylated transcriptome regions. We identify exon junction complexes (EJCs) as m6A suppressors that protect exon junction-proximal RNA within coding sequences from methylation and regulate mRNA stability through m6A suppression. EJC suppression of m6A underlies multiple global characteristics of mRNA m6A specificity, with the local range of EJC protection sufficient to suppress m6A deposition in average-length internal exons but not in long internal and terminal exons. EJC-suppressed methylation sites colocalize with EJC-suppressed splice sites, which suggests that exon architecture broadly determines local mRNA accessibility to regulatory complexes.

A universal sequencing read interpreter

Massively parallel DNA sequencing has led to the rapid growth of highly multiplexed experiments in biology. These experiments produce unique sequencing results that require specific analysis pipelines to decode highly structured reads. However, no versatile framework that interprets sequencing reads to extract their encoded information for downstream biological analysis has been developed. Here, we report INTERSTELLAR (interpretation, scalable transformation, and emulation of large-scale sequencing reads) that decodes data values encoded in theoretically any type of sequencing read and translates them into sequencing reads of another structure of choice. We demonstrated that INTERSTELLAR successfully extracted information from a range of short- and long-read sequencing reads and translated those of single-cell (sc)RNA-seq, scATAC-seq, and spatial transcriptomics to be analyzed by different software tools that have been developed for conceptually the same types of experiments. INTERSTELLAR will greatly facilitate the development of sequencing-based experiments and sharing of data analysis pipelines.

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.

Measuring transcription factor binding and gene expression using barcoded self-reporting transposon calling cards and transcriptomes

Calling cards technology using self-reporting transposons enables the identification of DNA-protein interactions through RNA sequencing. Although immensely powerful, current implementations of calling cards in bulk experiments on populations of cells are technically cumbersome and require many replicates to identify independent insertions into the same genomic locus. Here, we have drastically reduced the cost and labor requirements of calling card experiments in bulk populations of cells by introducing a DNA barcode into the calling card itself. An additional barcode incorporated during reverse transcription enables simultaneous transcriptome measurement in a facile and affordable protocol. We demonstrate that barcoded self-reporting transposons recover in vitro binding sites for four basic helix-loop-helix transcription factors with important roles in cell fate specification: ASCL1, MYOD1, NEUROD2 and NGN1. Further, simultaneous calling cards and transcriptional profiling during transcription factor overexpression identified both binding sites and gene expression changes for two of these factors. Lastly, we demonstrated barcoded calling cards can record binding in vivo in the mouse brain. In sum, RNA-based identification of transcription factor binding sites and gene expression through barcoded self-reporting transposon calling cards and transcriptomes is an efficient and powerful method to infer gene regulatory networks in a population of cells.

Novel High-Throughput DNA Part Characterization Technique for Synthetic Biology

This study presents a novel DNA part characterization technique that increases throughput by combinatorial DNA part assembly, solid plate-based quantitative fluorescence assay for phenotyping, and barcode tagging-based long-read sequencing for genotyping. We confirmed that the fluorescence intensities of colonies on plates were comparable to fluorescence at the single-cell level from a high-end, flow-cytometry device and developed a high-throughput image analysis pipeline. The barcode tagging-based long-read sequencing technique enabled rapid identification of all DNA parts and their combinations with a single sequencing experiment. Using our techniques, forty-four DNA parts (21 promoters and 23 RBSs) were successfully characterized in 72 h without any automated equipment. We anticipate that this high-throughput and easy-to-use part characterization technique will contribute to increasing part diversity and be useful for building genetic circuits and metabolic pathways in synthetic biology.

High throughput SARS-CoV-2 variant analysis using molecular barcodes coupled with next generation sequencing

The identification of SARS-CoV-2 variants across the globe and their implications on the outspread of the pandemic, infection potential and resistance to vaccination, requires modification of the current diagnostic methods to map out viral mutations rapidly and reliably. Here, we demonstrate that integrating DNA barcoding technology, sample pooling and Next Generation Sequencing (NGS) provide an applicable solution for large-population viral screening combined with specific variant analysis. Our solution allows high throughput testing by barcoding each sample, followed by pooling of test samples using a multi-step procedure. First, patient-specific barcodes are added to the primers used in a one-step RT-PCR reaction, amplifying three different viral genes and one human housekeeping gene (as internal control). Then, samples are pooled, purified and finally, the generated sequences are read using an Illumina NGS system to identify the positive samples with a sensitivity of 82.5% and a specificity of 97.3%. Using this solution, we were able to identify six known and one unknown SARS-CoV-2 variants in a screen of 960 samples out of which 258 (27%) were positive for the virus. Thus, our diagnostic solution integrates the benefits of large population and epidemiological screening together with sensitive and specific identification of positive samples including variant analysis at a single nucleotide resolution.

Multiplexed Assembly and Annotation of Synthetic Biology Constructs Using Long-Read Nanopore Sequencing

Recombinant DNA is a fundamental tool in biotechnology and medicine. These DNA sequences are often built, replicated, and delivered in the form of plasmids. Validation of these plasmid sequences is a critical and time-consuming step, which has been dominated for the last 35 years by Sanger sequencing. As plasmid sequences grow more complex with new DNA synthesis and cloning techniques, we need new approaches that address the corresponding validation challenges at scale. Here we prototype a high-throughput plasmid sequencing approach using DNA transposition and Oxford Nanopore sequencing. Our method, Circuit-seq, creates robust, full-length, and accurate plasmid assemblies without prior knowledge of the underlying sequence. We demonstrate the power of Circuit-seq across a wide range of plasmid sizes and complexities, generating full-length, contiguous plasmid maps. We then leverage our long-read data to characterize epigenetic marks and estimate plasmid contamination levels. Circuit-seq scales to large numbers of samples at a lower per-sample cost than commercial Sanger sequencing, accelerating a key step in synthetic biology, while low equipment costs make it practical for individual laboratories.

met v1: expanding on old estimations of biodiversity from eDNA with a new database framework

A long-standing problem in environmental DNA has been the inability to compute across large number of datasets. Here we introduce an open-source software framework that can store a large number of environmental DNA datasets, as well as provide a platform for analysis, in an easily customizable way. We show the utility of such an approach by analyzing over 1400 arthropod metabarcode datasets. This article introduces a new software framework, met, which utilizes large numbers of metabarcode datasets to draw conclusions about patterns of diversity at large spatial scales. Given more accurate estimations on the distribution of variance in metabarcode datasets, this software framework could facilitate novel analyses that are outside the scope of currently available similar platforms.

Database URL https://osf.io/spb8v/

Robust and scalable barcoding for massively parallel long-read sequencing

Nucleic-acid barcoding is an enabling technique for many applications, but its use remains limited in emerging long-read sequencing technologies with intrinsically low raw accuracy. Here, we apply so-called NS-watermark barcodes, whose error correction capability was previously validated in silico, in a proof of concept where we synthesize 3840 NS-watermark barcodes and use them to asymmetrically tag and simultaneously sequence amplicons from two evolutionarily distant species (namely Bordetella pertussis and Drosophila mojavensis) on the ONT MinION platform. To our knowledge, this is the largest number of distinct, non-random tags ever sequenced in parallel and the first report of microarray-based synthesis as a source for large oligonucleotide pools for barcoding. We recovered the identity of more than 86% of the barcodes, with a crosstalk rate of 0.17% (i.e., one misassignment every 584 reads). This falls in the range of the index hopping rate of established, high-accuracy Illumina sequencing, despite the increased number of tags and the relatively low accuracy of both microarray-based synthesis and long-read sequencing. The robustness of NS-watermark barcodes, together with their scalable design and compatibility with low-cost massive synthesis, makes them promising for present and future sequencing applications requiring massive labeling, such as long-read single-cell RNA-Seq.

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.

Best practices in metabarcoding of fungi: From experimental design to results

The development of high-throughput sequencing (HTS) technologies has greatly improved our capacity to identify fungi and unveil their ecological roles across a variety of ecosystems. Here we provide an overview of current best practices in metabarcoding analysis of fungal communities, from experimental design through molecular and computational analyses. By reanalysing published data sets, we demonstrate that operational taxonomic units (OTUs) outperform amplified sequence variants (ASVs) in recovering fungal diversity, a finding that is particularly evident for long markers. Additionally, analysis of the full-length ITS region allows more accurate taxonomic placement of fungi and other eukaryotes compared to the ITS2 subregion. Finally, we show that specific methods for compositional data analyses provide more reliable estimates of shifts in community structure. We conclude that metabarcoding analyses of fungi are especially promising for integrating fungi into the full microbiome and broader ecosystem functioning context, recovery of novel fungal lineages and ancient organisms as well as barcoding of old specimens including type material.

Prime-seq, efficient and powerful bulk RNA sequencing

Cost-efficient library generation by early barcoding has been central in propelling single-cell RNA sequencing. Here, we optimize and validate prime-seq, an early barcoding bulk RNA-seq method. We show that it performs equivalently to TruSeq, a standard bulk RNA-seq method, but is fourfold more cost-efficient due to almost 50-fold cheaper library costs. We also validate a direct RNA isolation step, show that intronic reads are derived from RNA, and compare cost-efficiencies of available protocols. We conclude that prime-seq is currently one of the best options to set up an early barcoding bulk RNA-seq protocol from which many labs would profit.

3GOLD: optimized Levenshtein distance for clustering third-generation sequencing data

BACKGROUND

Third-generation sequencing offers some advantages over next-generation sequencing predecessors, but with the caveat of harboring a much higher error rate. Clustering-related sequences is an essential task in modern biology. To accurately cluster sequences rich in errors, error type and frequency need to be accounted for. Levenshtein distance is a well-established mathematical algorithm for measuring the edit distance between words and can specifically weight insertions, deletions and substitutions. However, there are drawbacks to using Levenshtein distance in a biological context and hence has rarely been used for this purpose. We present novel modifications to the Levenshtein distance algorithm to optimize it for clustering error-rich biological sequencing data.

RESULTS

We successfully introduced a bidirectional frameshift allowance with end-user determined accommodation caps combined with weighted error discrimination. Furthermore, our modifications dramatically improved the computational speed of Levenstein distance. For simulated ONT MinION and PacBio Sequel datasets, the average clustering sensitivity for 3GOLD was 41.45% (S.D. 10.39) higher than Sequence-Levenstein distance, 52.14% (S.D. 9.43) higher than Levenshtein distance, 55.93% (S.D. 8.67) higher than Starcode, 42.68% (S.D. 8.09) higher than CD-HIT-EST and 61.49% (S.D. 7.81) higher than DNACLUST. For biological ONT MinION data, 3GOLD clustering sensitivity was 27.99% higher than Sequence-Levenstein distance, 52.76% higher than Levenshtein distance, 56.39% higher than Starcode, 48% higher than CD-HIT-EST and 70.4% higher than DNACLUST.

CONCLUSION

Our modifications to Levenshtein distance have improved its speed and accuracy compared to the classic Levenshtein distance, Sequence-Levenshtein distance and other commonly used clustering approaches on simulated and biological third-generation sequenced datasets. Our clustering approach is appropriate for datasets of unknown cluster centroids, such as those generated with unique molecular identifiers as well as known centroids such as barcoded datasets. A strength of our approach is high accuracy in resolving small clusters and mitigating the number of singletons.

Cloning of DNA oligo pools for in vitro expression

Oligo library pools are powerful tools for systematic investigation of genetic and transcriptomic machinery such as promoter function and gene regulation, non-coding RNAs, or RNA modifications. Here, we provide a detailed protocol for cloning DNA oligo pools made up of tens of thousands of different constructs, aiming to preserve the complexity of the pools. This system would be suitable for expression in cell lines and can be followed up by next-generation sequencing analysis.

For complete details on the use and execution of this profile, please refer to Uzonyi et al. (2021).

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Restriction-based cloning of DNA pools

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Preservation of complexity of thousands of constructs

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Used to investigate genetic and transcriptomic machineries

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To be expressed in cell lines and follow up by NGS analysis

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.

Barcoded oligonucleotides ligated on RNA amplified for multiplexed and parallel in situ analyses

We present barcoded oligonucleotides ligated on RNA amplified for multiplexed and parallel insitu analyses (BOLORAMIS), a reverse transcription-free method for spatially-resolved, targeted, in situ RNA identification of single or multiple targets. BOLORAMIS was demonstrated on a range of cell types and human cerebral organoids. Singleplex experiments to detect coding and non-coding RNAs in human iPSCs showed a stem-cell signature pattern. Specificity of BOLORAMIS was found to be 92% as illustrated by a clear distinction between human and mouse housekeeping genes in a co-culture system, as well as by recapitulation of subcellular localization of lncRNA MALAT1. Sensitivity of BOLORAMIS was quantified by comparing with single molecule FISH experiments and found to be 11%, 12% and 35% for GAPDH, TFRC and POLR2A, respectively. To demonstrate BOLORAMIS for multiplexed gene analysis, we targeted 96 mRNAs within a co-culture of iNGN neurons and HMC3 human microglial cells. We used fluorescence in situ sequencing to detect error-robust 8-base barcodes associated with each of these genes. We then used this data to uncover the spatial relationship among cells and transcripts by performing single-cell clustering and gene–gene proximity analyses. We anticipate the BOLORAMIS technology for in situ RNA detection to find applications in basic and translational research.

An Economical and Flexible Dual Barcoding, Two-Step PCR Approach for Highly Multiplexed Amplicon Sequencing

In microbiome research, phylogenetic and functional marker gene amplicon sequencing is the most commonly-used community profiling approach. Consequently, a plethora of protocols for the preparation and multiplexing of samples for amplicon sequencing have been developed. Here, we present two economical high-throughput gene amplification and sequencing workflows that are implemented as standard operating procedures at the Joint Microbiome Facility of the Medical University of Vienna and the University of Vienna. These workflows are based on a previously-published two-step PCR approach, but have been updated to either increase the accuracy of results, or alternatively to achieve orders of magnitude higher numbers of samples to be multiplexed in a single sequencing run. The high-accuracy workflow relies on unique dual sample barcoding. It allows the same level of sample multiplexing as the previously-published two-step PCR approach, but effectively eliminates residual read missasignments between samples (crosstalk) which are inherent to single barcoding approaches. The high-multiplexing workflow is based on combinatorial dual sample barcoding, which theoretically allows for multiplexing up to 299,756 amplicon libraries of the same target gene in a single massively-parallelized amplicon sequencing run. Both workflows presented here are highly economical, easy to implement, and can, without significant modifications or cost, be applied to any target gene of interest.

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.

Low-complexity and highly robust barcodes for error-rich single molecular sequencing

DNA barcodes are frequently corrupted due to insertion, deletion, and substitution errors during DNA synthesis, amplification and sequencing, resulting in index hopping. In this paper, we propose a new DNA barcode construction scheme that combines a cyclic block code with a predetermined pseudo-random sequence bit by bit to form bit pairs, and then converts the bit pairs to bases, i.e., the DNA barcodes. Then, we present a barcode identification scheme for noisy sequencing reads, which uses a combination of cyclic shifting and traditional dynamic programming to mark the insertion and deletion positions, and then performs erasure-and-error-correction decoding on the corrupted codewords. Furthermore, we verify the identification error rate of barcodes for multiple errors and evaluate the reliability of the barcodes in DNA context. This method can be easily generalized for constructing long barcodes, which may be used in scenarios with serious errors. Simulation results show that the bit error rate after identifying insertions/deletions is greatly reduced using the combination of cyclic shift and dynamic programming compared to using dynamic programming only. It indicates that the proposed method can effectively improve the accuracy for estimating insertion/deletion errors. And the overall identification error rate of the proposed method is lower than 10 - 5 when the probability of each base mutation is less than 0.1, which is the typical scenario in third-generation sequencing.

DropSynth 2.0: high-fidelity multiplexed gene synthesis in emulsions

Multiplexed assays allow functional testing of large synthetic libraries of genetic elements, but are limited by the designability, length, fidelity and scale of the input DNA. Here, we improve DropSynth, a low-cost, multiplexed method that builds gene libraries by compartmentalizing and assembling microarray-derived oligonucleotides in vortexed emulsions. By optimizing enzyme choice, adding enzymatic error correction and increasing scale, we show that DropSynth can build thousands of gene-length fragments at >20% fidelity.

Ultra-high throughput single-cell analysis of proteins and RNAs by split-pool synthesis

Single-cell omics provide insight into cellular heterogeneity and function. Recent technological advances have accelerated single-cell analyses, but workflows remain expensive and complex. We present a method enabling simultaneous, ultra-high throughput single-cell barcoding of millions of cells for targeted analysis of proteins and RNAs. Quantum barcoding (QBC) avoids isolation of single cells by building cell-specific oligo barcodes dynamically within each cell. With minimal instrumentation (four 96-well plates and a multichannel pipette), cell-specific codes are added to each tagged molecule within cells through sequential rounds of classical split-pool synthesis. Here we show the utility of this technology in mouse and human model systems for as many as 50 antibodies to targeted proteins and, separately, >70 targeted RNA regions. We demonstrate that this method can be applied to multi-modal protein and RNA analyses. It can be scaled by expansion of the split-pool process and effectively renders sequencing instruments as versatile multi-parameter flow cytometers.

Maeve O’Huallachain et al. report a method that enables simultaneous, ultra-high throughput single-cell barcoding for targeted single-cell protein and RNA analysis. They show the utility of their method in analyses of mRNA and protein expression in human and mouse cells.

Sequencing barcode construction and identification methods based on block error-correction codes

Multiplexed sequencing relies on specific sample labels, the barcodes, to tag DNA fragments belonging to different samples and to separate the output of the sequencers. However, the barcodes are often corrupted by insertion, deletion and substitution errors introduced during sequencing, which may lead to sample misassignment. In this paper, we propose a barcode construction method, which combines a block error-correction code with a predetermined pseudorandom sequence to generate a base sequence for labeling different samples. Furthermore, to identify the corrupted barcodes for assigning reads to their respective samples, we present a soft decision identification method that consists of inner decoding and outer decoding. The inner decoder establishes the hidden Markov model (HMM) for base insertion/deletion estimation with the pseudorandom sequence, and adapts the forward-backward (FB) algorithm to output the soft information of each bit in the block code. The outer decoder performs soft decision decoding using the soft information to effectively correct multiple errors in the barcodes. Simulation results show that the proposed methods are highly robust to high error rates of insertions, deletions and substitutions in the barcodes. In addition, compared with the inner decoding algorithm of the barcodes based on watermarks, the proposed inner decoding algorithm can greatly reduce the decoding complexity.

Optical Pooled Screens in Human Cells

Genetic screens are critical for the systematic identification of genes underlying cellular phenotypes. Pooling gene perturbations greatly improves scalability but is not compatible with imaging of complex and dynamic cellular phenotypes. Here, we introduce a pooled approach for optical genetic screens in mammalian cells. We use targeted in situ sequencing to demultiplex a library of genetic perturbations following image-based phenotyping. We screened a set of 952 genes across millions of cells for involvement in nuclear factor κB (NF-κB) signaling by imaging the translocation of RelA (p65) to the nucleus. Screening at a single time point across 3 cell lines recovered 15 known pathway components, while repeating the screen with live-cell imaging revealed a role for Mediator complex subunits in regulating the duration of p65 nuclear retention. These results establish a highly multiplexed approach to image-based screens of spatially and temporally defined phenotypes with pooled libraries.

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.

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.

Pandemic fluoroquinolone resistant Escherichia coli clone ST1193 emerged via simultaneous homologous recombinations in 11 gene loci

Global growth in antibiotic resistance is a major social problem. A high level of resistance to fluoroquinolones requires the concurrent presence of at least 3 mutations in the target proteins-2 in DNA gyrase (GyrA) and 1 in topoisomerase IV (ParC), which occur in a stepwise manner. In the Escherichia coli chromosome, the gyrA and parC loci are positioned about 1 Mb away from each other. Here we show that the 3 fluoroquinolone resistance mutations are tightly associated genetically in naturally occurring strains. In the latest pandemic uropathogenic and multidrug-resistant E. coli clonal group ST1193, the mutant variants of gyrA and parC were acquired not by a typical gradual, stepwise evolution but all at once. This happened as part of 11 simultaneous homologous recombination events involving 2 phylogenetically distant strains of E. coli, from an uropathogenic clonal complex ST14 and fluoroquinolone-resistant ST10. The gene exchanges swapped regions between 0.5 and 139 Kb in length (183 Kb total) spread along 976 Kb of chromosomal DNA around and between gyrA and parC loci. As a result, all 3 fluoroquinolone resistance mutations in GyrA and ParC have simultaneously appeared in ST1193. Based on molecular clock estimates, this potentially happened as recently as <12 y ago. Thus, naturally occurring homologous recombination events between 2 strains can involve numerous chromosomal gene locations simultaneously, resulting in the transfer of distant but tightly associated genetic mutations and emergence of a both highly pathogenic and antibiotic-resistant strain with a rapid global spread capability.

Mapping Degradation Signals and Pathways in a Eukaryotic N-terminome

Most eukaryotic proteins are N-terminally acetylated. This modification can be recognized as a signal for selective protein degradation (degron) by the N-end rule pathways. However, the prevalence and specificity of such degrons in the proteome are unclear. Here, by systematically examining how protein turnover is affected by N-terminal sequences, we perform a comprehensive survey of degrons in the yeast N-terminome. We find that approximately 26% of nascent protein N termini encode cryptic degrons. These degrons exhibit high hydrophobicity and are frequently recognized by the E3 ubiquitin ligase Doa10, suggesting a role in protein quality control. In contrast, N-terminal acetylation rarely functions as a degron. Surprisingly, we identify two pathways where N-terminal acetylation has the opposite function and blocks protein degradation through the E3 ubiquitin ligase Ubr1. Our analysis highlights the complexity of N-terminal degrons and argues that hydrophobicity, not N-terminal acetylation, is the predominant feature of N-terminal degrons in nascent proteins.

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.

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.

Indel-correcting DNA barcodes for high-throughput sequencing

Modern high-throughput biological assays study pooled populations of individual members by labeling each member with a unique DNA sequence called a “barcode.” DNA barcodes are frequently corrupted by DNA synthesis and sequencing errors, leading to significant data loss and incorrect data interpretation. Here, we describe an error correction strategy to improve the efficiency and statistical power of DNA barcodes. Our strategy accurately handles insertions and deletions (indels) in DNA barcodes, the most common type of error encountered during DNA synthesis and sequencing, resulting in order-of-magnitude increases in accuracy, efficiency, and signal-to-noise ratio. The accompanying software package makes deployment of these barcodes straightforward for the broader experimental scientist community.

Many large-scale, high-throughput experiments use DNA barcodes, short DNA sequences prepended to DNA libraries, for identification of individuals in pooled biomolecule populations. However, DNA synthesis and sequencing errors confound the correct interpretation of observed barcodes and can lead to significant data loss or spurious results. Widely used error-correcting codes borrowed from computer science (e.g., Hamming, Levenshtein codes) do not properly account for insertions and deletions (indels) in DNA barcodes, even though deletions are the most common type of synthesis error. Here, we present and experimentally validate filled/truncated right end edit (FREE) barcodes, which correct substitution, insertion, and deletion errors, even when these errors alter the barcode length. FREE barcodes are designed with experimental considerations in mind, including balanced guanine-cytosine (GC) content, minimal homopolymer runs, and reduced internal hairpin propensity. We generate and include lists of barcodes with different lengths and error correction levels that may be useful in diverse high-throughput applications, including >10⁶ single-error–correcting 16-mers that strike a balance between decoding accuracy, barcode length, and library size. Moreover, concatenating two or more FREE codes into a single barcode increases the available barcode space combinatorially, generating lists with >10¹⁵ error-correcting barcodes. The included software for creating barcode libraries and decoding sequenced barcodes is efficient and designed to be user-friendly for the general biology community.

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.