Whole-genome sequencing is a promising approach for human autosomal dominant disease studies. However, the vast number of genetic variants observed by this method constitutes a challenge when trying to identify the causal variants. This is often handled by restricting disease studies to the most damaging variants, e.g. those found in coding regions, and overlooking the remaining genetic variation. Such a biased approach explains in part why the genetic causes of many families with dominantly inherited diseases, in spite of being included in whole-genome sequencing studies, are left unsolved today. Here we explore the use of a geographically matched control population to minimize the number of candidate disease-causing variants without excluding variants based on assumptions on genomic position or functional predictions. To exemplify the benefit of the geographically matched control population we apply a typical disease variant filtering strategy in a family with an autosomal dominant form of colorectal cancer. With the use of the geographically matched control population we end up with 26 candidate variants genome wide. This is in contrast to the tens of thousands of candidates left when only making use of available public variant datasets. The effect of the local control population is dual, it (1) reduces the total number of candidate variants shared between affected individuals, and more importantly (2) increases the rate by which the number of candidate variants are reduced as additional affected family members are included in the filtering strategy. We demonstrate that the application of a geographically matched control population effectively limits the number of candidate disease-causing variants and may provide the means by which variants suitable for functional studies are identified genome wide.

The study of the draft genome of an Antarctic marine ciliate, Euplotes petzi, revealed foreign sequences of bacterial origin belonging to the gamma-proteobacterium Francisella that includes pathogenic and environmental species. TEM and FISH analyses confirmed the presence of a Francisella endocytobiont in E. petzi. This endocytobiont was isolated and found to be a new species, named F. adeliensis sp. nov.. F. adeliensis grows well at wide ranges of temperature, salinity, and carbon dioxide concentrations implying that it may colonize new organisms living in deeply diversified habitats. The F. adeliensis genome includes the igl and pdp gene sets (pdpC and pdpE excepted) of the Francisella pathogenicity island needed for intracellular growth. Consistently with an F. adeliensis ancient symbiotic lifestyle, it also contains a single insertion-sequence element. Instead, it lacks genes for the biosynthesis of essential amino acids such as cysteine, lysine, methionine, and tyrosine. In a genome-based phylogenetic tree, F. adeliensis forms a new early branching clade, basal to the evolution of pathogenic species. The correlations of this clade with the other clades raise doubts about a genuine free-living nature of the environmental Francisella species isolated from natural and man-made environments, and suggest to look at F. adeliensis asa pioneer in the Francisella colonization of eukaryotic organisms.

Microbial source tracking (MST) analysis is essential to identifying and mitigating the fecal pollution of water resources. The signature-based MST method uses a library of sequences to identify contaminants based on operational taxonomic units (OTUs) that are unique to a certain source. However, no clear guidelines for how to incorporate OTU overlap or natural variation in the raw water bacterial community into MST analyses exist. We investigated how the inclusion of bacterial overlap between sources in the library affects source prediction accuracy. To achieve this, large-scale sampling-including feces from seven species, raw sewage, and raw water samples from water treatment plants - was followed by 16S rRNA amplicon sequencing. The MST library was defined using three settings: (i) no raw water communities represented; (ii) raw water communities selected through clustering analysis; and (iii) local water communities collected across consecutive years. The results suggest that incorporating either the local background or representative bacterial composition improves MST analyses, as the results were positively correlated to measured levels of fecal indicator bacteria and the accuracy at which OTUs were assigned to the correct contamination source increased fourfold. Using the proportion of OTUs with high source origin probability, underpinning a contaminating signal, is a solid foundation in a framework for further deciphering and comparing contaminating signals derived in signature-based MST approaches. In conclusion, incorporating background bacterial composition of water in MST can improve mitigation efforts for minimizing the spread of pathogenic and antibiotic resistant bacteria into essential freshwater resources.

Interactions between Norway spruce trees and bacteria and fungi in nutrient limited boreal forests can be beneficial for tree growth and fitness. Tree-level effects of anthropogenic nutrient addition have been well studied, however understanding of the long-term effects on the associated microbiota is limited. Here, we report on the sensitivity of microbial community composition to the growing season and nutrient additions. Highthroughput sequencing of the bacterial 16S rRNA gene and fungal ITS1 region was used to characterise changes in the microbial community after application of a complete mineral nutrient mixture for five and 25 years. The experiment was conducted using the Flakaliden forest research site in northern boreal Sweden and included naturally low nutrient control plots. Needle and fine root samples of Norway spruce were sampled in addition to bulk soil during one growing season to provide comprehensive insight into phyllosphere and belowground microbiota community changes. The phyllosphere microbiota was compositionally distinct from the belowground communities and phyllosphere diversity increased significantly over the growing season but was not influenced by the improved nutrient status of the trees. In both root and soil samples, alpha diversity of fungal, in particular ectomycorrhizal fungi (EMF), and bacterial communities increased after long-term nutrient optimisation, and with increasing years of treatment the composition of the fungal and bacterial communities changed toward a community with a higher relative abundance of nitrophilic EMF and bacterial species but did not cause complete loss of nitrophobic species from the ecosystem. From this, we conclude that 25 years of continuous nutrient addition to a boreal spruce stand increased phylotype richness and diversity of the microbiota in the soil, and at the root-soil interface, suggesting that long-term anthropogenic nutrient inputs can have positive effects on belowground biodiversity that may enhance ecosystem robustness. Future studies are needed to assess the impact of these changes to the microbiota on ecosystem carbon storage and nitrogen cycling in boreal forests.

Persistence is a reversible and low-frequency phenomenon allowing a subpopulation of a clonal bacterial population to survive antibiotic treatments. Upon removal of the antibiotic, persister cells resume growth and give rise to viable progeny. Type II toxin-antitoxin (TA) systems were assumed to play a key role in the formation of persister cells in Escherichia coli based on the observation that successive deletions of TA systems decreased persistence frequency. In addition, the model proposed that stochastic fluctuations of (p)ppGpp levels are the basis for triggering activation of TA systems. Cells in which TA systems are activated are thought to enter a dormancy state and therefore survive the antibiotic treatment. Using independently constructed strains and newly designed fluorescent reporters, we reassessed the roles of TA modules in persistence both at the population and single-cell levels. Our data confirm that the deletion of 10 TA systems does not affect persistence to ofloxacin or ampicillin. Moreover, microfluidic experiments performed with a strain reporting the induction of the yefM-yoeB TA system allowed the observation of a small number of type II persister cells that resume growth after removal of ampicillin. However, we were unable to establish a correlation between high fluorescence and persistence, since the fluorescence of persister cells was comparable to that of the bulk of the population and none of the cells showing high fluorescence were able to resume growth upon removal of the antibiotic. Altogether, these data show that there is no direct link between induction of TA systems and persistence to antibiotics. IMPORTANCE Within a growing bacterial population, a small subpopulation of cells is able to survive antibiotic treatment by entering a transient state of dormancy referred to as persistence. Persistence is thought to be the cause of relapsing bacterial infections and is a major public health concern. Type II toxin-antitoxin systems are small modules composed of a toxic protein and an antitoxin protein counteracting the toxin activity. These systems were thought to be pivotal players in persistence until recent developments in the field. Our results demonstrate that previous influential reports had technical flaws and that there is no direct link between induction of TA systems and persistence to antibiotics.

We present the complete genome sequence of Francisella guangzhouensis strain 08HL01032(T), which consists of one chromosome (1,658,482 bp) and one plasmid ( 3,045 bp) with G+C contents of 32.0% and 28.7%, respectively.

Second generation sequencing has revolutionized genomic studies. However, most genomes contain repeated DNA elements that are longer than the read lengths achievable with typical sequencers, so the genomic order of several generated contigs cannot be easily resolved. A new generation of sequencers offering substantially longer reads is emerging, notably the Pacific Biosciences (PacBio) RS II system and the MinION system, released in early 2014 by Oxford Nanopore Technologies through an early access program. The latter has highly advantageous portability and sequences samples by measuring changes in ionic current when single-stranded DNA molecules are translocated through nanopores. We show that the MinION system produces long reads with high mapability that can be used for scaffolding bacterial genomes, despite currently producing substantially higher error rates than PacBio reads. With further development we anticipate that MinION will be useful not only for assembling genomes, but also for rapid detection of organisms, potentially in the field.

Accessing and exploring large-scale genomics data sets remains a significant challenge to researchers without specialist bioinformatics training. We present the integrated PlantGenIE.org platform for exploration of Populus, conifer and Arabidopsis genomics data, which includes expression networks and associated visualization tools. Standard features of a model organism database are provided, including genome browsers, gene list annotation, BLAST homology searches and gene information pages. Community annotation updating is supported via integration of WebApollo. We have produced an RNA-sequencing (RNA-Seq) expression atlas for Populus tremula and have integrated these data within the expression tools. An updated version of the COMPLEX resource for performing comparative plant expression analyses of gene coexpression network conservation between species has also been integrated. The PlantGenIE.org platform provides intuitive access to large-scale and genome-wide genomics data from model forest tree species, facilitating both community contributions to annotation improvement and tools supporting use of the included data resources to inform biological insight.

Advances in typing methodologies have recently reformed the field of molecular epidemiology of pathogens. The falling cost of sequencing technologies is creating a deluge of whole genome sequencing data that burdens bioinformatics resources and tool development. In particular, single nucleotide polymorphisms in core genomes of pathogens are recognized as the most important markers for inferring genetic relationships because they are evolutionarily stable and amenable to high-throughput detection methods. Sequence data will provide an excellent opportunity to extend our understanding of infectious disease when the challenge of extracting knowledge from available sequence resources is met. Here, we present an efficient and user-friendly genotype classification pipeline, CanSNPer, based on an easily expandable database of predefined canonical single nucleotide polymorphisms.