Genome Size in the Arenaria ciliata Species Complex (Caryophyllaceae), with Special Focus on Northern Europe and the Arctic.

The main aim of the present study has been the completion of genome size data for the diverse arctic-alpine A. ciliata species complex, with special focus on the unexplored arctic taxon A. pseudofrigida, the north-European A. norvegica, and A. gothica from Gotland (Sweden). Altogether, 46 individuals of these three Nordic taxa have been sampled from seven different regions and their genome size estimated using flow cytometry. Three other alpine taxa in the A. ciliata complex (A. multicaulis, A. ciliata subsp. ciliata, and A. ciliata subsp. bernensis) were also collected and analyzed for standardization purposes, comprising 20 individuals from six regions. A mean 2c value of 1.65 pg of DNA was recorded for A. pseudofrigida, 2.80 pg for A. norvegica, and 4.14 pg for A. gothica, as against the reconfirmed 2c value of 1.63 pg DNA for the type taxon A. ciliata subsp. ciliata. Our results presenting the first estimations of genome sizes for the newly sampled taxa, corroborate ploidy levels described in the available literature, with A. pseudofrigida being tetraploid (2n = 4x = 40), A. norvegica possessing predominantly 2n = 8x = 80, and A. gothica with 2n = 10x = 100. The present study also reconfirms genome size and ploidy level estimations published previously for the alpine members of this species complex. Reflecting a likely complex recent biogeographic history, the A. ciliata species group comprises a polyploid arctic-alpine species complex characterized by reticulate evolution, polyploidizations and hybridizations, probably associated with rapid latitudinal and altitudinal migrations in the Pleistocene-Holocene period.

DiagSet: a dataset for prostate cancer histopathological image classification.

Cancer diseases constitute one of the most significant societal challenges. In this paper, we introduce a novel histopathological dataset for prostate cancer detection. The proposed dataset, consisting of over 2.6 million tissue patches extracted from 430 fully annotated scans, 4675 scans with assigned binary diagnoses, and 46 scans with diagnoses independently provided by a group of histopathologists can be found at https://github.com/michalkoziarski/DiagSet . Furthermore, we propose a machine learning framework for detection of cancerous tissue regions and prediction of scan-level diagnosis, utilizing thresholding to abstain from the decision in uncertain cases. The proposed approach, composed of ensembles of deep neural networks operating on the histopathological scans at different scales, achieves 94.6% accuracy in patch-level recognition and is compared in a scan-level diagnosis with 9 human histopathologists showing high statistical agreement.

The transferability of microsatellite loci from a homoploid to a polyploid hybrid complex: an example from fine-leaved Festuca species (Poaceae).

BACKGROUND: Microsatellite loci, or single sequence repeats (SSR), are widely used as powerful markers in population genetics. They represent an attractive tool for studying plants such as grasses, whose evolution is driven by hybridisation and polyploidization. However, the development of microsatellite markers has been challenging and time-consuming, especially for non-model organisms lacking available genome-wide sequence data. One straightforward and low-cost approach is to transfer the SSR loci developed for one species, or complex, to another closely-related one. This work evaluates the transferability of microsatellite loci from homoploid to allopolyploid complexes of fine-leaved Festuca species and to assess their use in two new species. The studied complex (F. amethystina-F. tatrae) is a useful model for research on the local adaptability of grasses with different ploidy levels. Since both species can be considered as rare or threatened (F. tatrae-as a mountain and narrow endemic species and F. amethystina-a mountain species with relict lowland populations), any tool enabling studies on genetic diversity and population genetics, such as SSR markers, could also be very useful in a conservation context. METHODS: The ploidy level within populations was estimated using flow cytometry. One diploid and one tetraploid population of F. amethystina and a diploid population of F. tatrae were chosen to test the transferability of SSR loci. Because our work describes the transfer of SSR nuclear markers designed originally for F. gautieri, a phylogenetic tree was prepared based on the ITS marker to assess the genetic distance between the studied complexes. The PCR products were separated on a high-resolution agarose gel, intended for SSR marker analysis. Appropriate solutions for the allotetraploid population and whole mixed-ploidy complex were implemented. RESULTS: Flow cytometry confirmed earlier data regarding DNA content in the investigated species and cytotypes. The phylogenetic ITS tree indicated a small genetic distance between F. gautieri complexes and the studied species. Ten microsatellite markers were successfully transferred. All markers were polymorphic. In total, 163 different alleles were scored from the 10 SSR loci. PCoA of accessions revealed well-separated groups corresponding to studied populations. Over 60% of the total variance is explained by differentiation within populations and one third among them. CONCLUSIONS: The transferred markers are valid tools for the study of population genetics and inheritance relationships within cytotypes and species and between them. The presented markers can be used to study inbreeding depression in the Festuca species, and variations in the degrees of genetic diversity between different cytotypes in mountain and lowland areas. Our findings can also be applied to study conservation strategies for ensuring biodiversity at the genetic level in polyploid complexes.