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Eriksson, M.

Publications and source records attributed to Eriksson, M..

2 recordsLinked to original sources

The effect of genetic architecture and selfing on the capacity of a population to expand its range

Previous theoretical work on range expansions over heterogeneous environments showed that there is a critical environmental gradient where range expansion stops. For populations with freely recombining loci underlying the trait under selection (hereafter adaptive loci), the critical gradient in one-dimensional habitats depends on the fitness cost of dispersal, and the strength of selection relative to genetic drift. Here, we extend the previous work in two directions and ask: What is the role of the genetic architecture of adaptive loci during range expansions? And what effect does the ability of selfing have on range expansions? To answer these questions, we use computer simulations. We demonstrate that, while reduced recombination rates between adaptive loci slow down range expansions due to poor purging of locally deleterious alleles at the expansion front, they may also allow a species to occupy a greater range. In fact, for some parameter values, we find that a population with freely recombining adaptive loci experiences global extinction, whereas reduced recombination rates allow for a successful expansion over a wide geographic range. In addition, we find that allowance of selfing may improve the ability of populations to expand their ranges. We discuss the mechanisms underlying these results.

evolutionary biology

Taxonomic identification from metagenomic and metabarcoding data using any genetic marker

Correct taxonomic identification of DNA sequences is central to studies of biodiversity using both shotgun metagenomic and metabarcoding approaches. However, there is no genetic marker that gives sufficient performance across all the biological kingdoms, hampering studies of taxonomic diversity in many groups of organisms. We here present a major update to Metaxa2 (http://microbiology.se/software/metaxa2/) that enables the use of any genetic marker for taxonomic classification of metagenome and amplicon sequence data.

bioinformatics