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Linked Selection and Gene Density Shape Genome‐Wide Patterns of Diversification in Peatmosses.

Authors :
Meleshko, Olena
Martin, Michael D.
Flatberg, Kjell Ivar
Stenøien, Hans K.
Korneliussen, Thorfinn Sand
Szövényi, Péter
Hassel, Kristian
Source :
Evolutionary Applications. Aug2024, Vol. 17 Issue 8, p1-14. 14p.
Publication Year :
2024

Abstract

Genome evolution under speciation is poorly understood in nonmodel and nonvascular plants, such as bryophytes—the largest group of nonvascular land plants. Their genomes are structurally different from angiosperms and likely subjected to stronger linked selection pressure, which may have profound consequences on genome evolution in diversifying lineages, even more so when their genome architecture is conserved. We use the highly diverse, rapidly radiated group of peatmosses (Sphagnum) to characterize the processes affecting genome diversification in bryophytes. Using whole‐genome sequencing data from populations of 12 species sampled at different phylogenetic and geographical scales, we describe high correlation of the genomic landscapes of differentiation, divergence, and diversity in Sphagnum. Coupled with evidence from the patterns of covariation among different measures of genetic diversity, phylogenetic discordance, and gene density, this provides strong support that peatmoss genome evolution has been shaped by the long‐term effects of linked selection, constrained by distribution of selection targets in the genome. Thus, peatmosses join the growing number of animal and plant groups where functional features of the genome, such as gene density, and linked selection drive genome evolution along predetermined and highly similar routes in different species. Our findings demonstrate the great potential of bryophytes for studying the genomics of speciation and highlight the urgent need to expand the genomic resources in this remarkable group of plants. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17524563
Volume :
17
Issue :
8
Database :
Academic Search Index
Journal :
Evolutionary Applications
Publication Type :
Academic Journal
Accession number :
179320890
Full Text :
https://doi.org/10.1111/eva.13767