Biology subjects

Nystedt, B.

Publications and source records attributed to Nystedt, B..

3 recordsLinked to original sources

bioRxiv2018

Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants

SummaryWhole-genome sequencing (WGS) is a cornerstone of precision medicine, but portable and reproducible open-source workflows for WGS analyses of germline and somatic variants are lacking. We present Sarek, a modular, comprehensive, and easy-to-install workflow, combining a range of software for the identification and annotation of single-nucleotide variants (SNVs), insertion and deletion variants (indels), structural variants, tumor sample heterogeneity, and karyotyping from germline or paired tumor/normal samples. Sarek is implemented in a bioinformatics workflow language (Nextflow) with Docker and Singularity compatible containers, ensuring easy deployment and full reproducibility at any Linux based compute cluster or cloud computing environment. Sarek supports the human reference genomes GRCh37 and GRCh38, and can readily be used both as a core production workflow at sequencing facilities and as a powerful stand-alone tool for individual research groups.\n\nAvailabilitySource code and instructions for local installation are available at GitHub (https://github.com/SciLifeLab/Sarek) under the MIT open-source license, and we invite the research community to contribute additional functionality as a collaborative open-source development project.

bioinformatics↗

bioRxiv2017

Natural variation at FLOWERING LOCUS T2 mediates local adaptation in a key life history trait in European aspen

BackgroundThe initiation of growth cessation and dormancy represent critical life-history tradeoffs between survival and growth, and have important fitness effects in perennial plants. Such adaptive life history traits often show strong local adaptation along environmental gradients but despite their importance, the genetic architecture of these traits remains poorly understood.\n\nResultsWe integrate whole genome re-sequencing with environmental and phenotypic data from common garden experiments to investigate the genomic basis of local adaptation across a latitudinal gradient in European aspen (Populus tremula). We discover a single genomic region containing the PtFT2 gene that mediates local adaptation in the timing of bud set and that explains 65% of the observed genetic variation in bud set. This locus is the likely target of a recent selective sweep that originated right before or during colonization of northern Scandinavia following the last glaciation. Field and greenhouse experiments confirm that variation in PtFT2 gene expression affect the phenotypic variation in bud set that we observe in wild natural populations.\n\nConclusionsOur results reveal a major effect locus that determine the timing of bud set and that have facilitated rapid adaptation to shorter growing seasons and colder climates in European aspen. The discovery of a single locus explaining a substantial fraction of the variation in a key life history trait is remarkable given that such traits are generally considered to be highly polygenic. These findings provide a dramatic illustration of how loci of large-effect for adaptive traits can arise and be maintained over large geographical scales in natural populations.

evolutionary biology↗

bioRxiv2016

SweGen: A whole-genome map of genetic variability in a cross-section of the Swedish population

Here we describe the SweGen dataset, a high-quality map of genetic variation in the Swedish population. This data represents a basic resource for clinical genetics laboratories as well as for sequencing-based association studies, by providing information on the frequencies of genetic variants in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide population based cohort of over 10,000 individuals. From this sample collection, 1,000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole genome sequencing (WGS). Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a whole-genome map of aggregated variant frequencies in the Swedish population that we hereby release to the scientific community.

genetics↗