microGalaxy: A gateway to tools, workflows, and training for reproducible and FAIR analysis of microbial data.

Microbial research generates vast and complex data from diverse omics technologies, necessitating innovative analytical solutions. microGalaxy (Galaxy for Microbiology) addresses these needs with a user-friendly platform that integrates >220 tool suites and >65 curated workflows for microbial analyses, including taxonomic profiling, assembly, annotation, and functional analysis. Hosted on the main EU Galaxy server (microgalaxy.

Building pangenome graphs.

Pangenome graphs can represent all variation between multiple reference genomes, but current approaches to build them exclude complex sequences or are based upon a single reference. In response, we developed the PanGenome Graph Builder, a pipeline for constructing pangenome graphs without bias or exclusion. The PanGenome Graph Builder uses all-to-all alignments to build a variation graph in which we can identify variation, measure conservation, detect recombination events and infer phylogenetic relationships.

Recurrent evolution and selection shape structural diversity at the amylase locus.

The adoption of agriculture triggered a rapid shift towards starch-rich diets in human populations. Amylase genes facilitate starch digestion, and increased amylase copy number has been observed in some modern human populations with high-starch intake, although evidence of recent selection is lacking. Here, using 94 long-read haplotype-resolved assemblies and short-read data from approximately 5,600 contemporary and ancient humans, we resolve the diversity and evolutionary history of structural variation at the amylase locus.

Misexpression of inactive genes in whole blood is associated with nearby rare structural variants.

Gene misexpression is the aberrant transcription of a gene in a context where it is usually inactive. Despite its known pathological consequences in specific rare diseases, we have a limited understanding of its wider prevalence and mechanisms in humans. To address this, we analyzed gene misexpression in 4,568 whole-blood bulk RNA sequencing samples from INTERVAL study blood donors.

eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis.

Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS.