Repeat proliferation and partial endoreplication jointly shape the patterns of genome size evolution in orchids.

Although the evolutionary drivers of genome size change are known, the general patterns and mechanisms of plant genome size evolution are yet to be established. Here we aim to assess the relative importance of proliferation of repetitive DNA, chromosomal variation (including polyploidy), and the type of endoreplication for genome size evolution of the Pleurothallidinae, the most species-rich orchid lineage. Phylogenetic relationships between 341 Pleurothallidinae representatives were refined using a target enrichment hybrid capture combined with high-throughput sequencing approach. Genome size and the type of endoreplication were assessed using flow cytometry supplemented with karyological analysis and low-coverage Illumina sequencing for repeatome analysis on a subset of samples. Data were analyzed using phylogeny-based models. Genome size diversity (0.2-5.1 Gbp) was mostly independent of profound chromosome count variation (2n = 12-90) but tightly linked with the overall content of repetitive DNA elements. Species with partial endoreplication (PE) had significantly greater genome sizes, and genomic repeat content was tightly correlated with the size of the non-endoreplicated part of the genome. In PE species, repetitive DNA is preferentially accumulated in the non-endoreplicated parts of their genomes. Our results demonstrate that proliferation of repetitive DNA elements and PE together shape the patterns of genome size diversity in orchids.

Season-Long Experimental Drought Alters Fungal Community Composition but Not Diversity in a Grassland Soil.

Using terrestrial model ecosystems (TMEs), we investigated how reduced moisture conditions impact soil fungal communities from a temperate grassland over the course of an entire season. Starting at about 65% of the soil's maximum water holding capacity (WHCmax), TME soils were adjusted to three moisture levels for 15 weeks: 70% WHCmax, approximating starting conditions, 50% WHCmax, and 30% WHCmax, representing reduced moisture conditions. Diversity and abundances of soil fungi at the start and at the end of the experiment were characterized using Illumina meta-barcoding. Community diversity at the end of the experiment did not differ between experimental moisture levels and was comparable to diversity measures from the field. However, fungal communities did change compositionally in both abundances and presence/absence of species. Analyzing class-level and individual contributions of fungi to these changes revealed that only a minor portion reacted significantly, indicating that most compositional change was likely driven by many consistent small-scale shifts in presence/absences or abundances. Together, our results show that prolonged reduction in soil moisture conditions will trigger compositional changes in soil fungal communities but not necessarily change overall diversity. We highlight the cumulative contribution of minor but consistent changes among community members, as opposed to significant responses of individual species. We also detected a strong general experimental effect on soil fungi that are moved from the field to experimental TMEs, suggesting the importance of acclimatization effects in these communities under laboratory conditions.

An Illumina metabarcoding pipeline for fungi.

High-throughput metabarcoding studies on fungi and other eukaryotic microorganisms are rapidly becoming more frequent and more complex, requiring researchers to handle ever increasing amounts of raw sequence data. Here, we provide a flexible pipeline for pruning and analyzing fungal barcode (ITS rDNA) data generated as paired-end reads on Illumina MiSeq sequencers. The pipeline presented includes specific steps fine-tuned for ITS, that are mostly missing from pipelines developed for prokaryotes. It (1) employs state of the art programs and follows best practices in fungal high-throughput metabarcoding; (2) consists of modules and scripts easily modifiable by the user to ensure maximum flexibility with regard to specific needs of a project or future methodological developments; and (3) is straightforward to use, also in classroom settings. We provide detailed descriptions and revision techniques for each step, thus giving the user maximum control over data treatment and avoiding a black-box approach. Employing this pipeline will improve and speed up the tedious and error-prone process of cleaning fungal Illumina metabarcoding data.