Suchergebnisse

The resolution of cryptic diversity is essential for understanding the evolutionary diversification of lineages and establishing conservation priorities. We examine relationships in Eriogoneae (Polygonaceae), a diverse lineage in western North America. We ask whether Eriogonum umbellatum, a morphologically and ecologically diverse species, is monophyletic and whether its varieties represent evolutionary lineages. We use genotyping-by-sequencing to assemble a SNP dataset for 51 species in the genera Chorizanthe, Eriogonum and Sidotheca. We report a hierarchical phylogenetic analysis using maximum likelihood to estimate the evolutionary history of Eriogoneae. We illustrate admixture components for 21 populations of E. umbellatum, representing four varieties, and test for lineage structure using TreeMix. We identify strongly supported clades within Eriogoneae. Many relationships in the Eucycla + Oregonium and Latifolia clades are supported, while most relationships within the Eriogonum subg. Oligogonum clade and a clade with most Chorizanthe remain unresolved. Eriogonum congdonii resolves within the main E. umbellatum clade, while populations of three varieties of E. umbellatum are closely related to E. ursinum and are associated with serpentine soils. ADmixture and TreeMix analyses suggest E. umbellatum varieties represent evolutionary lineages. These results from SNP data are largely consistent with previous phylogenetic studies of Eriogoneae based on sequence variation. Structure within Oligogonum suggests consistent environmental association and radiation after initial colonization of serpentine. Morphology is unreliable for the infraspecific taxonomy of E. umbellatum. Additional molecular studies are needed to resolve the evolutionary relationships and ecological diversification within this species, in Oligogonum, and in Eriogoneae. ; This work was supported by funds from the Basque Government in support of the Terrestrial Plant Diversity group of the Department of Plant Biology and Ecology, University of the Basque Country, and an ERC Advanced Grant, FP7-IDEAS-ERC, 'ADAPT', project 339941 awarded to T. Brown.

Bringing together cancer genomes from different projects increases power and allows the investigation of pan-cancer, molecular mechanisms. However, working with whole genomes sequenced over several years in different sequencing centres requires a framework to compare the quality of these sequences. We used the Pan-Cancer Analysis of Whole Genomes cohort as a test case to construct such a framework. This cohort contains whole cancer genomes of 2832 donors from 18 sequencing centres. We developed a non-redundant set of five quality control (QC) measurements to establish a star rating system. These QC measures reflect known differences in sequencing protocol and provide a guide to downstream analyses and allow for exclusion of samples of poor quality. We have found that this is an effective framework of quality measures. The implementation of the framework is available at: https://dockstore.org/containers/quay.io/jwerner_dkfz/pancanqc:1.2.2. ; J.P.W., M.D.S., S.B., M.G., J.T. and I.G.G. acknowledge the support of the Spanish Ministry of Science and Innovation through the Instituto de Salud Carlos III and the 2014–2020 Smart Growth Operating Program, to the EMBL partnership and co-financing with the European Regional Development Fund (MINECO/FEDER, BIO2015-71792-P). We also acknowledge the support of the Centro de Excelencia Severo Ochoa, and the Generalitat de Catalunya through the Departament de Salut, Departament d'Empresa i Coneixement and the CERCA Programme. We also acknowledge the support through the European Union's Horizon 2020-funded project EASI-Genomics under grant agreement no 824110. The funding bodies did not have any influence on the design of the study and collection, analysis, and interpretation of data and in writing the paper.

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes. ; We acknowledge the support of the developers of PhenoTips, which was used in the past by RD-Connect and NeurOmics as the primary tool to collate phenotypic data. We would also like to thank the leaders and members of the Instituto Nacional de Bioinformática (INB) and ELIXIR for their support and collaboration throughout the years. RD-Connect (RD-Connect, an integrated platform connecting registries, biobanks, and clinical bioinformatics) received funding from the Seventh Framework (FP7) Programme of the European Union under grant agreement No 305444. Data were analyzed using the RD-Connect GPAP, which received funding from EU ...