Biology subjects

Ozsahin, E.

Publications and source records attributed to Ozsahin, E..

5 recordsLinked to original sources

bioRxiv2026

The Barcode Inference Pipeline (BIP): From Sequencer Output to DNA Barcodes

DNA barcoding involves the recovery of a DNA sequence for a target gene region from its source specimen. This process gains complexity when multiple sequences are recovered from a specimen, as is often the case when data are generated by high-throughput sequencers. This diversity can reflect both methodological artifacts (e.g., chimeras, PCR errors, sequencing errors, tag jumps) and real template diversity in the DNA extract (e.g., contamination, endosymbionts, NUMTs, parasites). To support analysis of the sequence data from three million specimens annually, the Centre for Biodiversity Genomics (CBG) has developed BIP, the Barcode Inference Pipeline. Compatible with all sequencing platforms, BIP processes .fastq files and returns both target DNA barcodes and non-target sequences. To generate results, BIP implements quality and size filtration, demultiplexing, primer trimming, chimera scanning, sequence error correction, OTU delineation, and sequence identification. When analysis targets the cytochrome c oxidase 1 (COI) barcode region, BIP also assigns each OTU to a known BIN or identifies its nearest neighbour BIN. As final output, BIP returns summary files ready for upload to BOLD or for other downstream analyses. They include a taxonomic assignment for each OTU, generated by comparison with a DNA barcode reference library. We describe BIPs flexibility and structure, then demonstrate its functionality by analyzing COI sequence data from 100K specimens. Because of its capacity to disentangle target and non-target sequences, BIP outperforms an alternative software package, ONTbarcoder, in several important ways. To ease access, installation, and functionality, BIP is provided as a Docker container (github.com/cbg-innov/BIP).

bioinformatics↗

bioRxiv2026

The Metabarcoding Analysis Pipeline (MAP): Simple, accurate, and flexible metabarcoding

Current metabarcoding pipelines are inflexible with respect to study design and are poorly suited to long-read sequence data. To address these limitations, we developed MAP, the Metabarcoding Analysis Pipeline, which is a sequence-to-answer workflow supporting the analysis of amplicons from highly multiplexed and replicated study designs. Although MAP can analyze amplicons of any length from any genetic marker, it includes several features tailored to long-read COI metabarcoding. MAP installs from a Docker container and requires only sequence data, a parameters file, and a reference library. It produces intuitive reports, enabling users to evaluate their data immediately after analysis. We validate MAP by showing that it generates biodiversity estimates that correspond closely to a ground-truth dataset of single-specimen DNA barcode data and by demonstrating that it outperforms alternative platforms for COI metabarcoding. MAP is free, open-source, and available from: https://github.com/cbg-innov/MAP.

bioinformatics↗

bioRxiv2026

Performance Test of the QNome Nanopore Sequencer

Nanopore sequencers have the potential to liberate DNA sequencing from centralized core facilities to distributed analytical nodes. Until now, Oxford Nanopore Technologies (ONT) has been the sole manufacturer of a portable nanopore sequencer, but analogous platforms are in production. Nanopore sequencers from Qitan Technology (QT) are widely used in China but have been unavailable outside that nation and lack independent performance testing. Enabled by early access to QTs least expensive sequencer and flow cell, the QNome-3841 and QCell-384, we tested whether they could generate accurate DNA barcodes cost-effectively. In several tests involving amplicon pools from 95 to 9,120 specimens, QT recovered valid DNA barcodes from nearly as many specimens (98%) as ONT. QT sequences had slightly lower fidelity than their ONT counterparts and QT frequently failed to resolve the correct length of G/C homopolymers. However, barcode sequences from the two platforms were nearly indistinguishable after bioinformatic treatment. QTs wash kit performed well, enabling a QCell to sequence eight amplicon pools with zero carryover between runs and minimal degradation of the flow cell. Its ultra-fast protocol allowed library preparation in a single step that could be completed in 15 minutes, but this came at the cost of lower quality data. Once widely available, QT devices will be well-suited for supporting DNA barcode analysis.

genomics↗

bioRxiv2024

European Farmhouse Brewing Yeasts Form a Distinct Genetic Group

The brewing industry is constantly evolving, driven by the quest for novel flavors and fermentation characteristics that cater to evolving consumer preferences. This study explores the genetic and phenotypic diversity of European farmhouse yeasts, traditionally used in rural brewing practices and maintained outside of pure culture industrial yeast selection. We isolated landrace brewing yeast strains from diverse geographical locations across Europe, including Norway, Lithuania, Latvia, Russia, and also included African farmhouse brewing strains from Ghana. Our genomic analysis using long-read and short-read whole genome sequencing uncovered a genetically distinct group that diverges from industrial brewing yeasts. This group, which is closely related to ale brewing strains, is preliminarily named the "European Farmhouse" group and shows greater predicted admixture from Asian fermentation strains. Through genomic and phenotypic analyses, including flavor metabolite analysis via HS-GC-MS, sugar metabolite analysis via HPLC, and wort fermentation analysis, we found a broad spectrum of fermentation capabilities, from rapid and efficient fermentation to unique aroma and flavor compound profiles, potentially offering novel traits for brewing applications. This study highlights the importance of preservation of brewing cultural heritage knowledge and resources including yeast cultures. Key PointsO_LIA large set of geographically diverse farmhouse brewing strains were characterized C_LIO_LINorwegian and Baltic farmhouse brewing strains form a distinct genetic group C_LIO_LIFarmhouse strains show considerable diversity in fermentation and flavour formation C_LI

microbiology↗

bioRxiv2021

Kveik brewing yeasts demonstrate wide flexibility in beer fermentation temperature and flavour metabolite production and exhibit enhanced trehalose accumulation

AO_SCPLOWBSTRACTC_SCPLOWTraditional Norwegian Farmhouse ale yeasts, also known as kveik, have captured the attention of the brewing community in recent years. Kveik were recently reported as fast fermenting thermo- and ethanol tolerant yeasts with the capacity to produce a variety of interesting flavour metabolites. They are a genetically distinct group of domesticated beer yeasts of admixed origin with one parent from the "Beer 1" clade and the other unknown. While kveik are known to ferment wort efficiently at warmer temperatures, its range of fermentation temperatures and corresponding flavour metabolites produced, remain uncharacterized. In addition, the characteristics responsible for its increased thermotolerance remain largely unknown. Here we demonstrate variation in kveik strains at a wide range of fermentation temperatures and show not all kveik strains are equal in fermentation performance, flavour metabolite production and stress tolerance. Furthermore, we uncovered an increased capacity of kveik strains to accumulate intracellular trehalose, which likely contributes to its increased thermo- and ethanol tolerances. Taken together our results present a clearer picture of the future opportunities presented by Norwegian kveik yeasts and offer further insight into their applications in brewing.

microbiology↗