Biology subjects

Niko Välimäki

Publications and source records attributed to Niko Välimäki.

3 recordsLinked to original sources

bioRxiv2016

Monomorphic genotypes within a generalist lineage of Campylobacter jejuni show signs of global dispersion

The decreased costs of genome sequencing have increased capability to apply whole-genome sequence on epidemiological surveillance of zoonotic Campylobacter jejuni. However, knowledge about how genetically similar epidemiologically linked isolates can be is vital for correct application of this methodology. To address this issue in C. jejuni we investigated the spatial and temporal signals in the genomes of a major clonal complex and generalist lineage, ST-45 CC, by exploiting the population structure and genealogy and applying genome-wide association analysis of 340 isolates from across Europe collected over a wide time-range. The occurrence and strength of the geographical signal varied between sublineages and followed the clonal frame when present, while no evidence of a temporal signal was found. Certain sublineages of ST-45 CC formed discrete and genetically isolated clades to which geography and time had left only negligible traces in the genomes. We hypothesize that these ST-45 CC clades form globally expanded monomorphic clones possibly spread across Europe by migratory birds. In addition, we observed an incongruence between the genealogy of the strains and MLST typing, thereby challenging the existing clonal complex definition and use of a common MLST-based nomenclature for the ST-45 CC of C. jejuni.

Microbiology↗

bioRxiv2016

Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes

Bacterial genomes vary extensively in terms of both gene content and gene sequence - this plasticity hampers the use of traditional SNP-based methods for identifying all genetic associations with phenotypic variation. Here we introduce a computationally scalable and widely applicable statistical method (SEER) for the identification of sequence elements that are significantly enriched in a phenotype of interest. SEER is applicable to even tens of thousands of genomes by counting variable-length k-mers using a distributed string-mining algorithm. Robust options are provided for association analysis that also correct for the clonal population structure of bacteria. Using large collections of genomes of the major human pathogens Streptococcus pneumoniae and Streptococcus pyogenes, SEER identifies relevant previously characterised resistance determinants for several antibiotics and discovers potential novel factors related to the invasiveness of S. pyogenes. We thus demonstrate that our method can answer important biologically and medically relevant questions.

Genomics↗

bioRxiv2015

On enhancing variation detection through pan-genome indexing

Detection of genomic variants is commonly conducted by aligning a set of reads sequenced from an individual to the reference genome of the species and analyzing the resulting read pileup. Typically, this process finds a subset of variants already reported in databases and additional novel variants characteristic to the sequenced individual. Most of the effort in the literature has been put to the alignment problem on a single reference sequence, although our gathered knowledge on species such as human is pan-genomic: We know most of the common variation in addition to the reference sequence. There have been some efforts to exploit pan-genome indexing, where the most widely adopted approach is to build an index structure on a set of reference sequences containing observed variation combinations.\n\nThe enhancement in alignment accuracy when using pan-genome indexing has been demonstrated in experiments, but so far the above multiple references pan-genome indexing approach has not been tested on its final goal, that is, in enhancing variation detection. This is the focus of this article: We study a generic approach to add variation detection support on top of the multiple references pan-genomic indexing approach. Namely, we study the read pileup on a multiple alignment of reference genomes, and propose a heaviest path algorithm to extract a new recombined reference sequence. This recombined reference sequence can then be utilized in any standard read alignment and variation detection workflow. We demonstrate that the approach enhances variation detection on realistic data sets.

Bioinformatics↗