UV RESISTANCE LOCUS 8-Mediated UV-B Response Is Required Alongside CRYPTOCHROME 1 for Plant Survival in Sunlight under Field Conditions.

As sessile, photoautotrophic organisms, plants are subjected to fluctuating sunlight that includes potentially detrimental ultraviolet-B (UV-B) radiation. Experiments under controlled conditions have shown that the UV-B photoreceptor UV RESISTANCE LOCUS 8 (UVR8) controls acclimation and tolerance to UV-B in Arabidopsis thaliana; however, its long-term impact on plant fitness under naturally fluctuating environments remain poorly understood. Here, we quantified the survival and reproduction of different Arabidopsis mutant genotypes under diverse field and laboratory conditions. We found that uvr8 mutants produced more fruits than wild type when grown in growth chambers under artificial low-UV-B conditions but not under natural field conditions, indicating a fitness cost in the absence of UV-B stress. Importantly, independent double mutants of UVR8 and the blue light photoreceptor gene CRYPTOCHROME 1 (CRY1) in two genetic backgrounds showed a drastic reduction in fitness in the field. Experiments with UV-B attenuation in the field and with supplemental UV-B in growth chambers demonstrated that UV-B caused the cry1 uvr8 conditional lethal phenotype. Using RNA-seq data of field-grown single and double mutants, we explicitly identified genes showing significant statistical interaction of UVR8 and CRY1 mutations in the presence of UV-B in the field. They were enriched in Gene Ontology categories related to oxidative stress, photoprotection and DNA damage repair in addition to UV-B response. Our study demonstrates the functional importance of the UVR8-mediated response across life stages in natura, which is partially redundant with that of cry1. Moreover, these data provide an integral picture of gene expression associated with plant responses under field conditions.

ARPEGGIO: Automated Reproducible Polyploid EpiGenetic GuIdance workflOw.

BACKGROUND: Whole genome duplication (WGD) events are common in the evolutionary history of many living organisms. For decades, researchers have been trying to understand the genetic and epigenetic impact of WGD and its underlying molecular mechanisms. Particular attention was given to allopolyploid study systems, species resulting from an hybridization event accompanied by WGD. Investigating the mechanisms behind the survival of a newly formed allopolyploid highlighted the key role of DNA methylation. With the improvement of high-throughput methods, such as whole genome bisulfite sequencing (WGBS), an opportunity opened to further understand the role of DNA methylation at a larger scale and higher resolution. However, only a few studies have applied WGBS to allopolyploids, which might be due to lack of genomic resources combined with a burdensome data analysis process. To overcome these problems, we developed the Automated Reproducible Polyploid EpiGenetic GuIdance workflOw (ARPEGGIO): the first workflow for the analysis of epigenetic data in polyploids. This workflow analyzes WGBS data from allopolyploid species via the genome assemblies of the allopolyploid's parent species. ARPEGGIO utilizes an updated read classification algorithm (EAGLE-RC), to tackle the challenge of sequence similarity amongst parental genomes. ARPEGGIO offers automation, but more importantly, a complete set of analyses including spot checks starting from raw WGBS data: quality checks, trimming, alignment, methylation extraction, statistical analyses and downstream analyses. A full run of ARPEGGIO outputs a list of genes showing differential methylation. ARPEGGIO was made simple to set up, run and interpret, and its implementation ensures reproducibility by including both package management and containerization. RESULTS: We evaluated ARPEGGIO in two ways. First, we tested EAGLE-RC's performance with publicly available datasets given a ground truth, and we show that EAGLE-RC decreases the error rate by 3 to 4 times compared to standard approaches. Second, using the same initial dataset, we show agreement between ARPEGGIO's output and published results. Compared to other similar workflows, ARPEGGIO is the only one supporting polyploid data. CONCLUSIONS: The goal of ARPEGGIO is to promote, support and improve polyploid research with a reproducible and automated set of analyses in a convenient implementation. ARPEGGIO is available at https://github.com/supermaxiste/ARPEGGIO .

Trait-dependent resemblance of the flowering phenology and floral morphology of the allopolyploid Cardamine flexuosa to those of the parental diploids in natural habitats.

Allopolyploids possess complete sets of genomes derived from different parental species and exhibit a range of variation in various traits. Reproductive traits may play a key role in the reproductive isolation between allopolyploids and their parental species, thus affecting the thriving of allopolyploids. However, empirical data, especially in natural habitats, comparing reproductive trait variation between allopolyploids and their parental species remain rare. Here, we documented the flowering phenology and floral morphology of the allopolyploid wild plant Cardamine flexuosa and its diploid parents C. amara and C. hirsuta in their native range in Switzerland. The flowering of C. flexuosa started at an intermediate time compared with those of the parents and the flowering period of C. flexuosa overlapped with those of the parents. Cardamine flexuosa resembled C. hirsuta in the size of flowers and petals and the length/width ratio of petals, while it resembled C. amara in the length/width ratio of flowers. These results provide empirical evidence of the trait-dependent variation of allopolyploid phenotypes in natural habitats at the local scale. They also suggest that the variation in some reproductive traits in C. flexuosa is associated with self-fertilization. Therefore, it is helpful to consider the mating system in furthering the understanding of the processes that may have shaped trait variation in polyploids in nature.

Meta-analysis of (single-cell method) benchmarks reveals the need for extensibility and interoperability.

Computational methods represent the lifeblood of modern molecular biology. Benchmarking is important for all methods, but with a focus here on computational methods, benchmarking is critical to dissect important steps of analysis pipelines, formally assess performance across common situations as well as edge cases, and ultimately guide users on what tools to use. Benchmarking can also be important for community building and advancing methods in a principled way. We conducted a meta-analysis of recent single-cell benchmarks to summarize the scope, extensibility, and neutrality, as well as technical features and whether best practices in open data and reproducible research were followed. The results highlight that while benchmarks often make code available and are in principle reproducible, they remain difficult to extend, for example, as new methods and new ways to assess methods emerge. In addition, embracing containerization and workflow systems would enhance reusability of intermediate benchmarking results, thus also driving wider adoption.