Suchergebnisse

Phylogenetic trees representing the evolutionary relationships of homologous genes are the entry point for many evolutionary analyses. For instance, the use of a phylogenetic tree can aid in the inference of orthology and paralogy relationships, and in the detection of relevant evolutionary events such as gene family expansions and contractions, horizontal gene transfer, recombination or incomplete lineage sorting. Similarly, given the plurality of evolutionary histories among genes encoded in a given genome, there is a need for the combined analysis of genome-wide collections of phylogenetic trees (phylomes). Here, we introduce a new release of PhylomeDB (http://phylomedb.org), a public repository of phylomes. Currently, PhylomeDB hosts 120 public phylomes, comprising >1.5 million maximum likelihood trees and multiple sequence alignments. In the current release, phylogenetic trees are annotated with taxonomic, protein-domain arrangement, functional and evolutionary information. PhylomeDB is also a major source for phylogeny-based predictions of orthology and paralogy, covering >10 million proteins across 1059 sequenced species. Here we describe newly implemented PhylomeDB features, and discuss a benchmark of the orthology predictions provided by the database, the impact of proteome updates and the use of the phylome approach in the analysis of newly sequenced genomes and transcriptomes. ; Spanish ministry of Economy and Competitiveness [BIO2012-37161]; a Grant from the Qatar National/nResearch Fund [NPRP 5-298-3-086]; a the European Research Council under the European Union's Seventh/nFramework Programme [FP/2007-2013/ERC and ERC-/n2012-StG-310325]; Juan de La Cierva postdoctoral program (to J.H.C.) and La Caixa-CRG International Fellowship Program (to L.P.P.). Funding for open access charge: Internal budget from the CRG

Quest for Orthologs (QfO) is a community effort with the goal to improve and benchmark orthology predictions. As quality assessment assumes prior knowledge on species phylogenies, we investigated the congruency between existing species trees by comparing the relationships of 147 QfO reference organisms from six Tree of Life (ToL)/species tree projects: The National Center for Biotechnology Information (NCBI) taxonomy, Opentree of Life, the sequenced species/species ToL, the 16S ribosomal RNA (rRNA) database, and trees published by Ciccarelli et al. (Ciccarelli FD, et al. 2006. Toward automatic reconstruction of a highly resolved tree of life. Science 311:1283-1287) and by Huerta-Cepas et al. (Huerta-Cepas J, Marcet-Houben M, Gabaldon T. 2014. A nested phylogenetic reconstruction approach provides scalable resolution in the eukaryotic Tree Of Life. PeerJ PrePrints 2:223) Our study reveals that each species tree suggests a different phylogeny: 87 of the 146 (60%) possible splits of a dichotomous and rooted tree are congruent, while all other splits are incongruent in at least one of the species trees. Topological differences are observed not only at deep speciation events, but also within younger clades, such as Hominidae, Rodentia, Laurasiatheria, or rosids. The evolutionary relationships of 27 archaea and bacteria are highly inconsistent. By assessing 458,108 gene trees from 65 genomes, we show that consistent species topologies are more often supported by gene phylogenies than contradicting ones. The largest concordant species tree includes 77 of the QfO reference organisms at the most. Results are summarized in the form of a consensus ToL (http://swisstree.vital-it.ch/species_tree) that can serve different benchmarking purposes. ; This work was supported by the Swiss Federal Government through the Federal Office of Education and/nScience (B.B.). Funding for open access charge: Swiss Institute of Bioinformatics. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. T.G. group research is funded in part by a grant from the Spanish ministry of Economy and Competitiveness (BIO2012-37161), a Grant from the Qatar National Research Fund (NPRP 5-298-3-086), and a grant from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC (grant agreement no. ERC-2012-StG-310325). M.M. acknowledges support from the Wellcome Trust (grant number WT095908) and the European Molecular Biology Laboratory.

8 Pág. ; The Quest for Orthologs Consortium ; The identification of orthologs-genes in different species which descended from the same gene in their last common ancestor-is a prerequisite for many analyses in comparative genomics and molecular evolution. Numerous algorithms and resources have been conceived to address this problem, but benchmarking and interpreting them is fraught with difficulties (need to compare them on a common input dataset, absence of ground truth, computational cost of calling orthologs). To address this, the Quest for Orthologs consortium maintains a reference set of proteomes and provides a web server for continuous orthology benchmarking (http://orthology.benchmarkservice.org). Furthermore, consensus ortholog calls derived from public benchmark submissions are provided on the Alliance of Genome Resources website, the joint portal of NIH-funded model organism databases. ; Service and Infrastructure grant from the Swiss Institute of Bioinformatics [to C.D.]; NSF [1917302 to P.D.T.]; NIH NHGRI [HG002273, HG010859 to P.D.T.]; INB [PT17/0009/0001 - ISCIII-SGEFI/ERDF to J.G.V., V.S., J.M.F., L.C., J.L.G. and S.C.G.]; H2020 ELIXIR-EXCELERATE [676559 to J.G.V., V.S., J.M.F., L.C., J.L.G. and S.C.G]; ELIXIR, the research infrastructure for life-science data [to J.G.V., V.S., J.M.F., L.C., J.L.G. and S.C.G]; Ministerio de Ciencia, Innovación y Universidades [PGC2018-098073-A-I00 MCIU/AEI/FEDER, UE to J.H.C.]; European Union's Horizon 2020 Research and Innovation Programme [686070 to J.H.C. and D.S, and 637765 to D.M.E. and S.K.]; Consejería de Educación, Juventud y Deporte de la Comunidad de Madrid and Fondo Social Europeo [PEJ-2017-AI/TIC-7514 to A.H.P.]; IdEX Unistra in the framework of the Investments for the future program of the French government [to O.L.]; National Institutes of Health (NIH) [U24HG007822 to M.J.M.]; European Molecular Biology Laboratory (EMBL) [core funds to M.J.M and M.M.]; Wellcome Trust [WT108749/Z/15/Z to M.M.]; S.K. is a royal Society University Research Fellow; Swiss ...

Funding was provided by the European Union's Horizon 2020 Research and Innovation Programme (grant 686070: DD-DeCaF to P.B.) and Marie Skłodowska-Curie Actions (grant 713673 to A.R.d.R.), the European Research Council (ERC) MicrobioS (ERC-AdG-669830 to P.B.), JTC project jumpAR (01KI1706 to P.B.), a BMBF Grant (grant 031L0181A: LAMarCK to P.B.), the European Molecular Biology Laboratory (P.B.), the ETH and Helmut Horten Foundation (S.S.), the National Key R&D Program of China (grant 2020YFA0712403 to X.-M.Z.), (grant 61932008 to X.-M.Z.; grant 61772368 to X.-M.Z.; grant 31950410544 to L.P.C.), the Shanghai Municipal Science and Technology Major Project (grant 2018SHZDZX01 to X.-M.Z. and L.P.C.) and Zhangjiang Lab (X.-M.Z. and L.P.C.), the International Development Research Centre (grant 109304, EMBARK under the JPI AMR framework; to L.P.C.), la Caixa Foundation (grant 100010434, fellowship code LCF/BQ/DI18/11660009 to A.R.d.R.), the Severo Ochoa Program for Centres of Excellence in R&D from the Agencia Estatal de Investigación of Spain (grant SEV-2016-0672 (2017–2021) to C.P.C.), the Ministerio de Ciencia, Innovación y Universidades (grant PGC2018-098073-A-I00 MCIU/AEI/FEDER to J.H.-C. and J.G.-L.), the Innovation Fund Denmark (grant 4203-00005B, PNM), the Biotechnology and Biological Sciences research Council (BBSrC) Gut MicroInstitute Strategic Programmebes and Health BB/r012490/1 and its constituent project BBS/e/F/000Pr10355 (F.H.). R.A. is a member of the Collaboration for joint PhD degree between EMBL and Heidelberg University, Faculty of Biosciences. ; Peer reviewed

This article is contribution number 94 of Tara Oceans.-- 37 pages, 20 figures, 1 table, supplementary information https://doi.org/10.1016/j.cell.2019.10.014.-- All raw reads are available through ENA at https://www.ebi.ac.uk/ena using the identifiers listed in https://doi.org/10.5281/zenodo.3473199. Processed data are accessible at https://www.ebi.ac.uk/biostudies/studies/S-BSST297, and additional information is provided in https://doi.org/10.5281/zenodo.3473199 and at the companion website: https://www.ocean-microbiome.org. Scripts used in this manuscript are available through a Github repository at https://github.com/SushiLab/omrgc_v2_scripts ; Ocean microbial communities strongly influence the biogeochemistry, food webs, and climate of our planet. Despite recent advances in understanding their taxonomic and genomic compositions, little is known about how their transcriptomes vary globally. Here, we present a dataset of 187 metatranscriptomes and 370 metagenomes from 126 globally distributed sampling stations and establish a resource of 47 million genes to study community-level transcriptomes across depth layers from pole-to-pole. We examine gene expression changes and community turnover as the underlying mechanisms shaping community transcriptomes along these axes of environmental variation and show how their individual contributions differ for multiple biogeochemically relevant processes. Furthermore, we find the relative contribution of gene expression changes to be significantly lower in polar than in non-polar waters and hypothesize that in polar regions, alterations in community activity in response to ocean warming will be driven more strongly by changes in organismal composition than by gene regulatory mechanisms ; Tara Oceans (that includes both the Tara Oceans and Tara Oceans Polar Circle expeditions) would not exist without the leadership of the Tara Expeditions Foundation and the continuous support of 23 institutes (https://oceans.taraexpeditions.org). We further thank the commitment of the following sponsors: CNRS (in particular Groupement de Recherche GDR3280 and the Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara Oceans-GOSEE); European Molecular Biology Laboratory (EMBL); Genoscope/CEA; the French Ministry of Research; the French Government "Investissements d'Avenir" programmes OCEANOMICS (ANR-11-BTBR-0008), FRANCE GENOMIQUE (ANR-10-INBS-09-08), MEMO LIFE (ANR-10-LABX-54), and PSL∗ Research University (ANR-11-IDEX-0001-02); Gordon and Betty Moore Foundation (award 3790); the US National Science Foundation (OCE#1536989 and OCE#1829831 to M.B.S.); the European Union's Horizon 2020 research and innovation programme (grant agreement 686070); and the Ohio Supercomputer and the EMBL and ETH Zürich HPC facilities for computational support. Funding for the collection and processing of the TARA data set was provided by NASA Ocean Biology and Biogeochemistry program under grants NNX11AQ14G, NNX09AU43G, NNX13AE58G, and NNX15AC08G to the University of Maine and Canada Excellence Research Chair on Remote sensing of Canada's new Arctic frontier Canada Foundation for Innovation. C.B. acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement 835067). S.G.A. thanks the Spanish Ministry of Economy and Competitiveness (CTM2017-87736-R). S. Sunagawa. is supported by the ETH and the Helmut Horten Foundation and by funding from the Swiss National Foundation (205321_184955) ; Peer Reviewed