July 7, 2019  |  

Traditional Norwegian kveik are a genetically distinct group of domesticated Saccharomyces cerevisiae brewing yeasts.

The widespread production of fermented food and beverages has resulted in the domestication of Saccharomyces cerevisiae yeasts specifically adapted to beer production. While there is evidence beer yeast domestication was accelerated by industrialization of beer, there also exists a farmhouse brewing culture in western Norway which has passed down yeasts referred to as kveik for generations. This practice has resulted in ale yeasts which are typically highly flocculant, phenolic off flavor negative (POF-), and exhibit a high rate of fermentation, similar to previously characterized lineages of domesticated yeast. Additionally, kveik yeasts are reportedly high-temperature tolerant, likely due to the traditional practice of pitching yeast into warm (>28°C) wort. Here, we characterize kveik yeasts from 9 different Norwegian sources via PCR fingerprinting, whole genome sequencing of selected strains, phenotypic screens, and lab-scale fermentations. Phylogenetic analysis suggests that kveik yeasts form a distinct group among beer yeasts. Additionally, we identify a novel POF- loss-of-function mutation, as well as SNPs and CNVs potentially relevant to the thermotolerance, high ethanol tolerance, and high fermentation rate phenotypes of kveik strains. We also identify domestication markers related to flocculation in kveik. Taken together, the results suggest that Norwegian kveik yeasts are a genetically distinct group of domesticated beer yeasts with properties highly relevant to the brewing sector.

July 7, 2019  |  

Approximate, simultaneous comparison of microbial genome architectures via syntenic anchoring of quiver representations

Motivation A long-standing limitation in comparative genomic studies is the dependency on a reference genome, which hinders the spectrum of genetic diversity that can be identified across a population of organisms. This is especially true in the microbial world where genome architectures can significantly vary. There is therefore a need for computational methods that can simultaneously analyze the architectures of multiple genomes without introducing bias from a reference. Results In this article, we present Ptolemy: a novel method for studying the diversity of genome architectures—such as structural variation and pan-genomes—across a collection of microbial assemblies without the need of a reference. Ptolemy is a ‘top-down’ approach to compare whole genome assemblies. Genomes are represented as labeled multi-directed graphs—known as quivers—which are then merged into a single, canonical quiver by identifying ‘gene anchors’ via synteny analysis. The canonical quiver represents an approximate, structural alignment of all genomes in a given collection encoding structural variation across (sub-) populations within the collection. We highlight various applications of Ptolemy by analyzing structural variation and the pan-genomes of different datasets composing of Mycobacterium, Saccharomyces, Escherichia and Shigella species. Our results show that Ptolemy is flexible and can handle both conserved and highly dynamic genome architectures. Ptolemy is user-friendly—requires only FASTA-formatted assembly along with a corresponding GFF-formatted file—and resource-friendly—can align 24 genomes in ~10 mins with four CPUs and <2 GB of RAM.

July 7, 2019  |  

Single-phase PacBio de novo assembly of the genome of the chytrid fungus Batrachochytrium dendrobatidis, a pathogen of Amphibia.

Here, we present an updated genome assembly of the diploid chytrid fungus Batrachochytrium dendrobatidis strain RTP6. This strain is part of the global panzootic lineage (BdGPL) and was isolated in Dunedin, New Zealand. The assembly was generated using PacBio long-read and Illumina short-read data, allowing for the accurate phasing of heterozygosities.

July 7, 2019  |  

The gold-standard genome of Aspergillus niger NRRL 3 enables a detailed view of the diversity of sugar catabolism in fungi.

The fungal kingdom is too large to be discovered exclusively by classical genetics. The access to omics data opens a new opportunity to study the diversity within the fungal kingdom and how adaptation to new environments shapes fungal metabolism. Genomes are the foundation of modern science but their quality is crucial when analysing omics data. In this study, we demonstrate how one gold-standard genome can improve functional prediction across closely related species to be able to identify key enzymes, reactions and pathways with the focus on primary carbon metabolism. Based on this approach we identified alternative genes encoding various steps of the different sugar catabolic pathways, and as such provided leads for functional studies into this topic. We also revealed significant diversity with respect to genome content, although this did not always correlate to the ability of the species to use the corresponding sugar as a carbon source.

January 23, 2017  |  

Tutorial: HGAP4 de novo assembly application

This tutorial provides an overview of the Hierarchical Genome Assembly Process (HGAP4) de novo assembly analysis application. HGAP4 generates accurate de novo assemblies using only PacBio data. HGAP4 is suitable…

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