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Reusch, T.

Publications and source records attributed to Reusch, T..

2 recordsLinked to original sources

Seagrass genomes reveal a hexaploid ancestry facilitating adaptation to the marine environment

Seagrasses comprise the only submerged marine angiosperms, a feat of adaptation from three independent freshwater lineages within the Alismatales. These three parallel lineages offer the unique opportunity to study convergent versus lineage-specific adaptation to a fully marine lifestyle. Here, we present chromosome-level genome assemblies from a representative species of each of the seagrass lineages - Posidonia oceanica (Posidoniaceae), Cymodocea nodosa (Cymodoceaceae), and Thalassia testudinum (Hydrocharitaceae) - along with an improved assembly for Zostera marina (Zosteraceae). We also include a draft genome of Potamogeton acutifolius, a representative of Potamogetonaceae, the freshwater sister lineage to the Zosteraceae. Genome analysis reveals that all seagrasses share an ancient whole genome triplication (WGT) event, dating to the early evolution of the Alismatales. An additional whole genome duplication (WGD) event was uncovered for C. nodosa and P. acutifolius. Dating of ancient WGDs and more recent bursts of transposable elements correlate well with major geological and recent climatic events, supporting their role as rapid generators of genetic variation. Comparative analysis of selected gene families suggests that the transition from the submerged-freshwater to submerged-marine environment did not require revolutionary changes. Major gene losses related to, e.g., stomata, volatiles, defense, and lignification, are likely a consequence of the submerged lifestyle rather than the cause ( use it or lose it). Likewise, genes, often retained from the WGD and WGT, were co-opted for functions requiring the alignment of many small adaptations ( tweaking), e.g., osmoregulation, salinity, light capture, carbon acquisition, and temperature. Our ability to manage and conserve seagrass ecosystems depends on our understanding of the fundamental processes underpinning their resilience. These new genomes will accelerate functional studies and are expected to contribute to transformative solutions -- as continuing worldwide losses of the savannas of the sea are of major concern in times of climate change and loss of biodiversity.

evolutionary biology↗

Origin Matters: Using a Local Reference Genome Improves Measures in Population Genomics

Genome-level sequencing enables us to ask fundamental questions about the genetic basis of adaptation, population structure, and epigenetic mechanisms, but usually requires a suitable reference genome for mapping population-level re-sequencing data. In some model systems, multiple reference genomes are available, giving researchers the challenging task of determining which reference genome best suits their data. Here we compare the use of two different reference genomes for the three-spined stickleback (Gasterosteus aculeatus), one novel genome derived from a European gynogenetic individual and the published reference genome of a North American individual. Specifically, we investigate the impact of using a local reference versus one generated from a distinct lineage on several common population genomics analyses. Through mapping genome resequencing data of 60 sticklebacks from across Europe and North America, we demonstrate that genetic distance among samples and the reference impacts downstream analyses. Using a local reference genome increased mapping efficiency and genotyping accuracy, effectively retaining more and better data. Despite comparable distributions of the metrics generated across the genome using SNP data (i.e., {pi}, Tajimas D, and FST), window-based statistics using different references resulted in different outlier genes and enriched gene functions. A marker-based analysis of DNA methylation distributions had a comparably high overlap in outlier genes and functions, yet with distinct differences depending on the reference genome. Overall, our results highlight how using a local reference genome decreases reference bias to increase confidence in downstream analyses of the data. Such results have significant implications in all reference-genome-based population genomic analyses.

bioinformatics↗