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Dahlberg, J.

Publications and source records attributed to Dahlberg, J..

3 recordsLinked to original sources

De novo assembly of two Swedish genomes reveals missing segments from the human GRCh38 reference and improves variant calling of population-scale sequencing data

We have performed de novo assembly of two Swedish genomes using long-read sequencing and optical mapping, resulting in total assembly sizes of nearly 3 Gb and hybrid scaffold N50 values of over 45 Mb. A further analysis revealed over 10 Mb of sequences absent from the human GRCh38 reference in each individual. Around 6 Mb of these novel sequences (NS) are shared with a Chinese personal genome. The NS are highly repetitive, have elevated GC-content and are primarily located in centromeric or telomeric regions. A BLAST search showed that 31% of the NS are different from any sequences deposited in nucleotide databases. The remaining NS correspond to human (62%) or primate (6%) nucleotide entries, while 1% of hits show the highest similarity to other species, including mouse and a few different classes of parasitic worms. Up to 1 Mb of NS can be assigned to chromosome Y, and large segments are missing from GRCh38 also at chromosomes 14, 17 and 21. Inclusion of these novel sequences into the GRCh38 reference radically improves the alignment and variant calling of whole-genome sequencing data at several genomic loci. Through a re-analysis of 200 samples from a Swedish population-scale sequencing project, we obtained over 75,000 putative novel SNVs per individual when using a custom version of GRCh38 extended with 17.3 Mb of NS. In addition, about 10,000 false positive SNV calls per individual were removed from the GRCh38 autosomes and sex chromosomes in the re-analysis, with some of them located in protein coding regions.

genomics

Arteria: An automation system for a sequencing core facility

Arteria is an automation system aimed at sequencing core facilities. It is built on existing open source technologies, with a modular design allowing for a community-driven effort to create plug-and-play micro-services. Herein we describe the Arteria system and elaborate on the underlying conceptual framework. The Arteria system breaks down into three conceptual levels; orchestration, process and execution. At the orchestration level it utilizes an event-based model of automation. It models processes, e.g. the steps involved in processing sequencing data, as workflows and executes these in a micro-service based environment. This creates a system which is both flexible and scalable. The Arteria Project code is available as open source software at http://www.github.com/arteria-project.

bioinformatics

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