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PubMed2026

Bycatch in a bottle: what taxa are recoverable from metabarcoding DNA in historical invertebrate collection preservative fluid?

Natural history museum collections are invaluable repositories of biodiversity, offering insights into life on Earth. Genomic approaches provide powerful tools to characterize biodiversity in these collections. However using these collections for genomics without damaging specimens is a challenge. Here, we develop and test non-destructive DNA metabarcoding methods to capture biodiversity from the preservative fluids of archived insect collections ('Bycatch'). We optimized workflows for extracting and amplifying the partial CO1 locus (CO1) and fungal ITS1 locus from ethanol-based preservative fluids, validating ethanol preparation methods, comparing DNA extraction kits, and refining PCR protocols. Our results demonstrate that from museum collections with low DNA yields, CO1 and fungal ITS1 loci can often be recovered from preservative fluids, and we present detailed methodology and workflows. We test metabarcoding success to recover taxa in several museum collections ranging in age and storage condition. This is to support the State of California's effort to catalog and sequence all insects and fungi, building baselines of California biodiversity with help from museum collections. Lastly, we investigate the complementarity of metabarcoding water versus ethanol and morphological identifications aimed to capture benthic macroinvertebrate biodiversity in streams. Our findings highlight that DNA metabarcoding of the preservative fluid is a non-destructive tool for capturing biodiversity in historical specimens, but there are limitations on the overlaps between DNA results and physical contents, where morphological identification still reigns in taxon counts, but metabarcoding sometimes provides more taxonomic resolution, and can be used to track DNA from other organisms such as fungi beyond the directly surveyed specimens.

Animals↗

PubMed2026

A hybrid and cost-efficient barcoding strategy for full-length 16S rRNA gene nanopore sequencing of environmental samples.

BACKGROUND: Accurate species-level identification of bacteria in complex environmental samples is essential for applications in biotechnology, ecological monitoring, and clinical diagnostics. Short-read platforms such as Illumina frequently truncate the 16S rRNA gene, limiting taxonomic resolution. In this work, we applied Oxford Nanopore Technology (ONT) long-read sequencing to full-length 16S rRNA amplicon in samples from natural soil amended with lignocellulosic biomass and a simplified microbial community derived from cultures grown on selective and differential carboxymethyl cellulose (CMC)-based substrates, with the aim to evaluate the difference in performance between a real, complex community and a less complex system. To reduce consumable costs, we substituted the standard ONT Barcoding kits with an in-house hybrid barcoding workflow. Specifically, PacBio PCR-based barcoding protocol was used for sample indexing, followed by library preparation using the ONT Ligation Sequencing Kit. This simplified approach retained compatibility with MinION and Flongle flow cells and supported accurate downstream demultiplexing while lowering barcode costs substantially. Additionally, a new bioinformatic workflow tailored to ONT data was implemented. RESULTS: Overall, the hybrid protocol significantly reduced per-sample barcoding costs while preserving high sequencing quality and throughput. The sequencing run yielded over 5 Gb of quality-filtered data (Q-score ≥ 10). Furthermore, the new bioinformatic workflow allowed taxonomic assignment at the species level for 49.38% of annotated taxa, compared to just 4.59% using Illumina NovaSeq sequencing of the V3-V4 region. ONT also recovered 2.3 times more genera and 1.3 times more families. Although 16S rRNA gene sequencing often cannot distinguish between closely related species, particularly within taxonomically complex groups, in this work, full-length reads substantially improved both taxonomic resolution and database matching. CONCLUSIONS: These results show that full-length 16S rRNA sequencing with ONT, paired with a low-cost barcoding strategy, enhanced taxonomic resolution compared to short-read workflows. This approach also offers a scalable and cost-effective option for high-resolution microbiome profiling in research and applied settings.

RNA, Ribosomal, 16S↗

PubMed2026

Performance comparison of rapid and native barcoding methods for Oxford Nanopore sequencing of Poliovirus Viral Protein 1 (VP1) amplicons.

Accurate and timely sequencing of poliovirus is critical for global eradication efforts, particularly for molecular epidemiology based on the typing region of the genome, viral protein 1 (VP1). While Oxford Nanopore Technologies (ONT) sequencing has expanded capabilities for poliovirus surveillance, the relative performance of different ONT library preparation methods, including ligation-based (Native Barcoding) and transposase-based (Rapid Barcoding) approaches, has not been systematically evaluated. In this study, we compared rapid barcoding and native barcoding workflows for sequencing VP1 amplicons from 17 type 2 poliovirus-positive samples, each processed in triplicate. Native barcoding generated significantly more sequencing output, producing approximately 2.3-fold greater total read yield than rapid barcoding, and demonstrated higher run-to-run reproducibility (R2 = 0.979-0.998 vs. 0.847-0.929, respectively; p < 0.001). In addition, native barcoding generated 80% of the total yield achieved by rapid barcoding within approximately 7 h, whereas rapid barcoding required approximately 40 h to reach the same output. Despite these differences, both methods produced identical VP1 consensus sequences across all samples, with comparable read quality (median per-base Q-scores of approximately Q17-Q18). Rapid barcoding provided substantial practical advantages, reducing hands-on library preparation time (55 vs. 200 min) and per-sample cost ($12.82 vs. $16.54), while simplifying workflow and reducing technical complexity. These findings indicate that sequencing yield may not be a determinant of downstream analytical outcomes for poliovirus VP1 ONT sequencing. Rapid barcoding therefore represents a cost-effective and efficient approach for routine poliovirus surveillance, whereas native barcoding remains advantageous in applications requiring rapid data generation or maximal sequencing depth.

Poliovirus↗

PubMed2006

Phylum-wide analysis of SSU rDNA reveals deep phylogenetic relationships among nematodes and accelerated evolution toward crown Clades.

Inference of evolutionary relationships between nematodes is severely hampered by their conserved morphology, the high frequency of homoplasy, and the scarcity of phylum-wide molecular data. To study the origin of nematode radiation and to unravel the phylogenetic relationships between distantly related species, 339 nearly full-length small-subunit rDNA sequences were analyzed from a diverse range of nematodes. Bayesian inference revealed a backbone comprising 12 consecutive dichotomies that subdivided the phylum Nematoda into 12 clades. The most basal clade is dominated by the subclass Enoplia, and members of the order Triplonchida occupy positions most close to the common ancestor of the nematodes. Crown Clades 8-12, a group formerly indicated as "Secernentea" that includes Caenorhabditis elegans and virtually all major plant and animal parasites, show significantly higher nucleotide substitution rates than the more basal Clades 1-7. Accelerated substitution rates are associated with parasitic lifestyles (Clades 8 and 12) or short generation times (Clades 9-11). The relatively high substitution rates in the distal clades resulted in numerous autapomorphies that allow in most cases DNA barcode-based species identification. Teratocephalus, a genus comprising terrestrial bacterivores, was shown to be most close to the starting point of Secernentean radiation. Notably, fungal feeding nematodes were exclusively found basal to or as sister taxon next to the 3 groups of plant parasitic nematodes, namely, Trichodoridae, Longidoridae, and Tylenchomorpha. The exclusive common presence of fungivorous and plant parasitic nematodes supports a long-standing hypothesis that states that plant parasitic nematodes arose from fungivorous ancestors.

Amino Acid Substitution↗

PubMed2025

Fluctuating DNA methylation tracks cancer evolution at clinical scale.

Cancer development and response to treatment are evolutionary processes1,2, but characterizing evolutionary dynamics at a clinically meaningful scale has remained challenging3. Here we develop a new methodology called EVOFLUx, based on natural DNA methylation barcodes fluctuating over time4, that quantitatively infers evolutionary dynamics using only a bulk tumour methylation profile as input. We apply EVOFLUx to 1,976 well-characterized lymphoid cancer samples spanning a broad spectrum of diseases and show that initial tumour growth rate, malignancy age and epimutation rates vary by orders of magnitude across disease types. We measure that subclonal selection occurs only infrequently within bulk samples and detect occasional examples of multiple independent primary tumours. Clinically, we observe faster initial tumour growth in more aggressive disease subtypes, and that evolutionary histories are strong independent prognostic factors in two series of chronic lymphocytic leukaemia. Using EVOFLUx for phylogenetic analyses of aggressive Richter-transformed chronic lymphocytic leukaemia samples detected that the seed of the transformed clone existed decades before presentation. Orthogonal verification of EVOFLUx inferences is provided using additional genetic data, including long-read nanopore sequencing, and clinical variables. Collectively, we show how widely available, low-cost bulk DNA methylation data precisely measure cancer evolutionary dynamics, and provides new insights into cancer biology and clinical behaviour.

Humans↗

PubMed2025

Metschnikowia maris comb. nov., a large-spored yeast species endemic to Serra do Mar Atlantic Rainforest biome, Sao Paulo State, Brazil.

Two yeast isolates from passion flowers were sampled in the southern part of the Serra do Mar Atlantic Rainforest in Sao Paulo State, Brazil. Barcode sequencing and mating experiments showed them to be representatives of Metschnikowia matae var. maris, thus originally named due to the availability of only a single isolate and uncertainties regarding reproductive isolation. The two new isolates being of the complementary mating type to the previously known strain, intravarietal crosses were performed. They yielded a preponderance of two-spored asci, unlike crosses with M. matae var. matae, which led to largely sterile asci. We therefore elevate the variety maris to the rank of species, with the name Metschnikowia maris comb. nov. The holotype is UFMG-CM-Y397T (MATα). Strain UFMG-CM-Y7613A (MAT a) is designated as allotype. The new combination is registered as MB 859665.

Brazil↗

PubMed2025

raxtax: a k-mer-based non-Bayesian taxonomic classifier.

MOTIVATION: Taxonomic classification in biodiversity studies is the process of assigning the anonymous sequences of a marker gene (barcode) or whole genomes (metagenomics) to a specific lineage using a reference database that contains named sequences in a known taxonomy. This classification is important for assessing the diversity of biological systems. Taxonomic classification faces two main challenges: first, accuracy is critical as errors can propagate to downstream analysis results; and second, the classification time requirements can limit study size and study design, in particular when considering the constantly growing reference databases. To address these two challenges, we introduce raxtax, an efficient, novel taxonomic classification tool for barcodes that uses common k-mers between all pairs of query and reference sequences. We also introduce two novel uncertainty scores which take into account the fundamental biases of reference databases. RESULTS: We validate raxtax on three widely-used empirical reference databases and show that it is 2.7-100 times faster than competing state-of-the-art tools on the largest database while being equally accurate. In particular, raxtax exhibits increasing speedups with growing query and reference sequence numbers compared to existing tools (for 100 000 and 1 000 000 query and reference sequences overall, it is 1.3 and 2.9 times faster, respectively), and therefore alleviates the taxonomic classification scalability challenge. AVAILABILITY AND IMPLEMENTATION: raxtax is available at https://github.com/noahares/raxtax under a CC-NC-BY-SA license. The scripts and summary metrics used in our analyses are available at https://github.com/noahares/raxtax_paper_scripts. The source code, sequence data, and summarized results of the analyses are available at https://doi.org/10.5281/zenodo.15057027.

Software↗

PubMed2026

GenBank mining reveals novel insights into Rhizobium phylogeny: Identical 16S rRNA sequences are mainly uncoupled from species designation, host plant, and geographic origin: How this search suggested the definition of a direct 'microbial h-index'.

16S rDNA is the historical gold standard for bacterial identification, particularly in metabarcoding approaches reliant on sequence similarity thresholds. We analyzed 6,660 Rhizobium 16S rRNA gene sequences from GenBank to examine the relationship between sequence identity and three metadata: species name, host plant, and geographic origin. Using an iterative BLAST-based pipeline, we detected 116,069 pairwise matches and assessed concordance among sequences (average length 1,328 bp) sharing 100% identity. For those in which the organism name, host plant and country of isolation were present in the record, surprisingly, 66.59% of identical sequence pairs showed full discordance across all three metadata, while only 1.40% shared the same name, host, and country. The most widespread sequence, detected 371 times, was associated with over 56 different host plants across 25 countries and bore multiple species name designations. These results highlight a striking mismatch between the 16S barcode and the taxonomic, ecological, and phenotypic variability it is assumed to reflect, likely arising from the slow evolution of rRNA genes contrasted with the mobility of ecologically relevant genes via horizontal transfer on plasmids, transposons, and phages. Our findings further challenge the limitations of relying on 16S rRNA alone for fine-scale taxonomic and metadata-based inference in capturing the true functional and ecological diversity of bacteria, endorsing the critical importance of polyphasic taxonomic approaches that integrate genomic, phenotypic, and ecological data. An interesting byproduct of the analysis was to realize the possibility of treating these data as if they were 'citations.' The more one finds the same query sequence, the more that sequence can be considered biologically 'cited', i.e., re-proposed elsewhere in the world. Thus, one can also analyze the h-index of such a ranking. In our Rhizobium dataset, we calculated an h-index = 201, meaning the sequence ranked 201st had 202 identical homologues in GenBank. Although the research effort on given species is directly connected with it, this number provides a quantitative indicator of a taxon's sequence recurrence and distribution within public databases, independent of nomenclatural inconsistencies, offering a novel framework for assessing bacterial representation across global datasets.

RNA, Ribosomal, 16S↗

PubMed2006

Coupling molecular beacons to barcoded metal nanowires for multiplexed, sealed chamber DNA bioassays.

We have combined molecular beacon (MB) probes with barcoded metal nanowires to enable no-wash, sealed chamber, multiplexed detection of nucleic acids. Probe design and experimental parameters important in nanowire-based MB assays are discussed. Loop regions of 24 bases and 5 base pair stem regions in the beacon probes gave optimal performance. Our results suggest that thermodynamic predictions for secondary structure stability of solution-phase MB can guide probe design for nanowire-based assays. Dengue virus-specific probes with predicted solution-phase DeltaG of folding in 500 mM buffered NaCl of approximately -4 kcal/mol performed better than those with DeltaG > -2 or < -6 kcal/mol. Buffered 300-500 mM NaCl was selected after comparison of several buffers previously reported for similar types of assays, and 200-500 mM NaCl was found to be the optimal ionic strength for the hybridization temperatures (25 and 50 degrees C) and probe designs used here. Target binding to the surface as a function of solution concentration fit a Sips isotherm with Kd = 1.7 +/- 0.3 nM. The detection limit was approximately 100 pM, limited by incomplete quenching. Single base mismatches could be discriminated from fully complementary targets. Oligonucleotide target sequences specific for human immunodeficiency, hepatitis C, and severe acute respiratory viruses were assayed simultaneously in a no-wash, sealed chamber, multiplexed experiment in which each of three probe sequences was attached to a different pattern of encoded nanowires. Finally, we demonstrated that probe-coated nanowires retain their selectivity and sensitivity in a triplexed assay after storage for over 3 months.

DNA, Viral↗

PubMed2026

Recurrent and niche-specific functional bacteriome of maize hybrid revealed by integrated metabarcoding and culturomics.

The plant microbiome plays a pivotal role in plant survival in natural habitats by facilitating nutrient acquisition, stress adaptation, and disease suppression, while also offering opportunities to enhance crop productivity and climate resilience. However, the distribution of persistent and culturable bacteriome across maize-associated niches and their functional potential remain poorly resolved. This study integrated metagenomic next-generation sequencing (mNGS-based metabarcoding) and culturomics to characterise the maize-associated bacteriome of bulk soil, rhizoplane, phylloplane, and cob of the maize hybrid PHM-1 under contrasting cropping and tillage systems, and to identify recurrent and agriculturally promising bacteriome components. The bacteriome exhibited pronounced niche-specific structuring, whereas overall bacterial community composition did not differ significantly across cropping and tillage treatments (ANOSIM, R = 0.038, p = 0.306). Proteobacteria predominated in the culturable bacteriome (69-84%; mean, 76.2%) but accounted for only 1% of the total bacteriome, whereas Patescibacteria and Firmicutes were relatively enriched. Niche-specific dominance was evident, with Pantoea accounting for 40.79% of the total and 56.27% of the culturable phylloplane bacteriome under cereal monocropping, while Serratia represented 31.59% and 59.40% of the total and culturable cob bacteriomes, respectively. Across niches, mNGS captured substantially greater bacteriome diversity, particularly uncultured and unidentified taxa in soil-associated compartments, whereas culturomics recovered a narrower but functionally accessible fraction. Culturomics yielded 99 isolates representing 32 species across 12 genera, including six genera shared with the mNGS-derived recurrent bacteriome: Bacillus, Enterobacter, Pantoea, Pseudomonas, Serratia, and Stenotrophomonas. Functional screening identified strong biocontrol and plant-beneficial traits among core-associated isolates. Pseudomonas oryzihabitans ZM-DL-PA10 inhibited Rhizoctonia solani, Macrophomina phaseolina, and Bipolaris maydis by up to 40.6%, 43.9%, and 45.2%, respectively, through secreted and volatile metabolites; exhibited P, K, and Zn solubilisation; and produced IAA and siderophores. It also recorded the lowest B. maydis disease index (ADI) of 1.00. Pantoea ananatis ZM-BH-EA4 showed 52.4% and 68.5% inhibition of R. solani and B. maydis, respectively, through volatile metabolites. Collectively, the integration of mNGS and culturomics revealed a strongly compartmentalised maize bacteriome and identified recurrent, culturable, and functionally promising bacterial taxa, providing a targeted resource for microbiome-based crop protection and climate-resilient maize production.

Zea mays↗

PubMed2025

Common to rare transfer learning (CORAL) enables inference and prediction for a quarter million rare Malagasy arthropods.

DNA-based biodiversity surveys result in massive-scale data, including up to millions of species-of which, most are rare. Making the most of such data for inference and prediction requires modeling approaches that can relate species occurrences to environmental and spatial predictors, while incorporating information about their taxonomic or phylogenetic placement. Even if the scalability of joint species distribution models to large communities has greatly advanced, incorporating hundreds of thousands of species has not been feasible to date, leading to compromised analyses. Here we present a 'common to rare transfer learning' (CORAL) approach, based on borrowing information from the common species to enable statistically and computationally efficient modeling of both common and rare species. We illustrate that CORAL leads to much improved prediction and inference in the context of DNA metabarcoding data from Madagascar, comprising 255,188 arthropod species detected in 2,874 samples.

Animals↗

PubMed2025

NanoASV: a snakemake workflow for reproducible field-based Nanopore full-length 16S metabarcoding amplicon data analysis.

SUMMARY: NanoASV is a conda environment and snakemake-based workflow using state-of-the-art bioinformatics software to process full-length SSU rRNA (16S/18S) amplicons acquired with Oxford Nanopore Sequencing technology. Its strength lies in reproducibility, portability, and the possibility to run offline, allowing in-field analysis. It can be installed on the Nanopore MK1C sequencing device and process data locally. AVAILABILITY AND IMPLEMENTATION: Source code and documentation are freely available at https://github.com/ImagoXV/NanoASV and Zenodo archive at https://doi.org/10.5281/zenodo.14730742.

Software↗

PubMed2025

Predicting coarse-grained representations of biogeochemical cycles from metabarcoding data.

MOTIVATION: Taxonomic analysis of environmental microbial communities is now routinely performed thanks to advances in DNA sequencing. Determining the role of these communities in global biogeochemical cycles requires the identification of their metabolic functions, such as hydrogen oxidation, sulfur reduction, and carbon fixation. These functions can be directly inferred from metagenomics data, but in many environmental applications metabarcoding is still the method of choice. The reconstruction of metabolic functions from metabarcoding data and their integration into coarse-grained representations of biogeochemical cycles remains a difficult bioinformatics problem today. RESULTS: We developed a pipeline, called Tabigecy, which exploits taxonomic affiliations to predict metabolic functions constituting biogeochemical cycles. In a first step, Tabigecy uses the tool EsMeCaTa to predict consensus proteomes from input affiliations. To optimize this process, we generated a precomputed database containing information about 2404 taxa from UniProt. The consensus proteomes are searched using bigecyhmm, a newly developed Python package relying on Hidden Markov Models to identify key enzymes involved in metabolic function of biogeochemical cycles. The metabolic functions are then projected on coarse-grained representation of the cycles. We applied Tabigecy to two salt cavern datasets and validated its predictions with microbial activity and hydrochemistry measurements performed on the samples. The results highlight the utility of the approach to investigate the impact of microbial communities on biogeochemical processes. AVAILABILITY AND IMPLEMENTATION: The Tabigecy pipeline is available at https://github.com/ArnaudBelcour/tabigecy. The Python package bigecyhmm and the precomputed EsMeCaTa database are also separately available at https://github.com/ArnaudBelcour/bigecyhmm and https://doi.org/10.5281/zenodo.13354073, respectively.

Metagenomics↗

PubMed2025

The role of stochasticity in fungal community assembly: explaining apparent stochasticity with field experiments.

Stochasticity is a main process in community assembly. However, experimental studies rarely target stochasticity in natural communities, and hence experimental validation of stochasticity estimates in observational studies is lacking. Here, we combine experimental and observational data to unravel the role of stochasticity in the assembly of wood-inhabiting fungi. We carried out a replicated field experiment where the natural colonization of a focal fungal species was simulated through inoculation, and the local fungal communities were monitored through DNA metabarcoding before and after the inoculations. The amount of stochasticity in fungal colonization was less pronounced than expected from the amount of unpredictability in observational data, suggesting that stochasticity may play a smaller role in fungal occurrence than previously anticipated, or that it may be a stronger influence in the dispersal and establishment phases than in colonization per se. Stochasticity was more prominent in the initial phase of community succession, with the earliest successional stage involving a higher level of stochasticity than the later stage after 2 years. We conclude that experimentally measuring the role of stochasticity in community assembly is feasible for species-rich communities under natural conditions and highlight the importance of experimentally testing the accuracy of stochasticity estimates based on observational data.

Stochastic Processes↗

PubMed2025

Multi-step genomics on single cells and live cultures in sub-nanoliter capsules.

Single-cell sequencing methods uncover natural and induced variation between cells. Many functional genomic methods, however, require multiple steps that cannot yet be scaled to high throughput, including assays on living cells. Here we develop capsules with amphiphilic gel envelopes (CAGEs), which selectively retain cells and large analytes while being freely accessible to media, enzymes and reagents. Capsules enable high-throughput multi-step assays combining live-cell culture with genome-wide readouts. We establish methods for barcoding CAGE DNA libraries, and apply them to measure persistence of gene expression programs in cells by capturing the transcriptomes of tens of thousands of expanding clones in CAGEs. The compatibility of CAGEs with diverse enzymatic reactions will facilitate the expansion of the current repertoire of single-cell, high-throughput measurements and extension to live-cell assays.

Journal Article↗

PubMed2026

Getting to the Core of the Matter-Assessing the Role of Replication in Metabarcoding-Based sedaDNA.

Replication is central to most experimental and sampling designs, increasing inferential power and capturing fine-scale data heterogeneity. However, its importance remains poorly evaluated in some ecological and evolutionary settings. This is the case of metabarcoding studies using DNA recovered from sedimentary archives, in which biological signals integrate ecological information through depositional and burial processes, yet are commonly inferred from a single sediment core per site. Here, we evaluated the effect of different types of replication using sedimentary DNA metabarcoding data from two genetic markers (mitochondrial COI and nuclear 18S) using a nested sampling design. The design included three intertidal sites, three spatially separated sediment cores per site (biological replicates), two sediment horizons per core, and eight PCR (technical) replicates per sediment sample. Variance partitioning showed that site identity and sediment age group together explained > 70% of the variation in beta diversity, indicating that among-site spatial and stratigraphic differences were the dominant drivers of community composition. PERMANOVA likewise identified non-significant effects of biological replication. Among PCR replicates from the same sediment sample, richness varied substantially, whereas Shannon diversity was more consistent. Despite this variability, differences in community composition among technical replicates remained smaller than those associated with biological replication or site identity, indicating a limited influence on broader ecological patterns. Community composition was highly similar among replicate cores within sites, consistent with stratigraphic coherence. These results indicate limited within-site heterogeneity and suggest that, under stratigraphically coherent conditions, increasing biological replication may provide little additional information, whereas enhancing technical replication and stratigraphic resolution can improve ecological inference from sedimentary DNA metabarcoding datasets.

DNA Barcoding, Taxonomic↗

PubMed2004

Nematode molecular diagnostics: from bands to barcodes.

Nematodes are considered among the most difficult animals to identify. DNA-based diagnostic methods have already gained acceptance in applications ranging from quarantine determinations to assessments of biodiversity. Researchers are currently in an information-gathering mode, with intensive efforts applied to accumulating nucleotide sequence of 18S and 28S ribosomal genes, internally transcribed spacer regions, and mitochondrial genes. Important linkages with collateral data such as digitized images, video clips and specimen voucher web pages are being established on GenBank and NemATOL, the nematode-specific Tree of Life database. The growing DNA taxonomy of nematodes has lead to their use in testing specific short sequences of DNA as a "barcode" for the identification of all nematode species.

Animals↗

PubMed2006

Signature-tagged mutagenesis: barcoding mutants for genome-wide screens.

DNA signature tags (molecular barcodes) facilitate functional screens by identifying mutants in mixed populations that have a reduced or increased adaptation to a particular environment. Many innovative adaptations and refinements in the technology have been described since its original use with Salmonella; they have yielded a wealth of information on a broad range of biological processes--mainly in bacteria, but also in yeast and other fungi, viruses, parasites and, most recently, in mammalian cells. By combining whole-genome microarrays and comprehensive ordered libraries of mutants, high-throughput functional screens can now be achieved on a genomic scale.

Animals↗