Evgeny Zdobnov

Prof. Dr. Evgeny Zdobnov

Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva, Geneva, Switzerland

Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 June 2015 in Bioinformatics
Verified
Journal Article
Open access
PDF file
FSFelipe A. Simão
Felipe A. Simão
Robert WaterhouseRobert Waterhouse
Robert Waterhouse
PIPanagiotis Ioannidis
Panagiotis Ioannidis
EKEvgenia V. Kriventseva
Evgenia V. Kriventseva
EZEvgeny Zdobnov
Evgeny Zdobnov
Motivation: Genomics has revolutionized biological research, but quality assessment of the resulting assembled sequences is complicated and remains mostly limited to technical measures like N50. Results: We propose a measure for quantitative assessment of genome assembly and annotation completeness based on evolutionarily informed expectations of gene content. We implemented the assessment procedure in open-source software, with sets of Benchmarking Universal Single-Copy Orthologs, named BUSCO. Availability and implementation: Software implemented in Python and datasets available for download from http://busco.ezlab.org. Contact:evgeny.zdobnov@unige.ch Supplementary information: Supplementary data are available at Bioinformatics online.

28 July 2021 in Molecular Biology and Evolution
Verified
Journal Article
Open access
PDF file
Mosè ManniMosè Manni
Mosè Manni
MBMatthew R Berkeley
Matthew R Berkeley
MSMathieu Seppey
Mathieu Seppey
FSFelipe A Simão
Felipe A Simão
EZEvgeny Zdobnov
Evgeny Zdobnov
Methods for evaluating the quality of genomic and metagenomic data are essential to aid genome assembly procedures and to correctly interpret the results of subsequent analyses. BUSCO estimates the completeness and redundancy of processed genomic data based on universal single-copy orthologs. Here, we present new functionalities and major improvements of the BUSCO software, as well as the renewal and expansion of the underlying data sets in sync with the OrthoDB v10 release. Among the major novelties, BUSCO now enables phylogenetic placement of the input sequence to automatically select the most appropriate BUSCO data set for the assessment, allowing the analysis of metagenome-assembled genomes of unknown origin. A newly introduced genome workflow increases the efficiency and runtimes especially on large eukaryotic genomes. BUSCO is the only tool capable of assessing both eukaryotic and prokaryotic species, and can be applied to various data types, from genome assemblies and metagenomic bins, to transcriptomes and gene sets.

25 April 2019
Verified
Book Chapter
Closed access
PDF file
MSMathieu Seppey
Mathieu Seppey
MMMosè Manni
Mosè Manni
EZEvgeny Zdobnov
Evgeny Zdobnov

6 December 2017 in Molecular Biology and Evolution
Verified
Journal Article
Open access
PDF file
Robert WaterhouseRobert Waterhouse
Robert Waterhouse
MSMathieu Seppey
Mathieu Seppey
FSFelipe A Simão
Felipe A Simão
MMMosè Manni
Mosè Manni
PIPanagiotis Ioannidis
Panagiotis Ioannidis
EZEvgeny Zdobnov
Evgeny Zdobnov
Genomics promises comprehensive surveying of genomes and metagenomes, but rapidly changing technologies and expanding data volumes make evaluation of completeness a challenging task. Technical sequencing quality metrics can be complemented by quantifying completeness of genomic data sets in terms of the expected gene content of Benchmarking Universal Single-Copy Orthologs (BUSCO, http://busco.ezlab.org). The latest software release implements a complete refactoring of the code to make it more flexible and extendable to facilitate high-throughput assessments. The original six lineage assessment data sets have been updated with improved species sampling, 34 new subsets have been built for vertebrates, arthropods, fungi, and prokaryotes that greatly enhance resolution, and data sets are now also available for nematodes, protists, and plants. Here, we present BUSCO v3 with example analyses that highlight the wide-ranging utility of BUSCO assessments, which extend beyond quality control of genomics data sets to applications in comparative genomics analyses, gene predictor training, metagenomics, and phylogenomics.

22 December 2021 in Current Protocols
Verified
Journal Article
Open access
PDF file
MMMosè Manni
Mosè Manni
MBMatthew R. Berkeley
Matthew R. Berkeley
MSMathieu Seppey
Mathieu Seppey
EZEvgeny Zdobnov
Evgeny Zdobnov
Evaluation of the quality of genomic “data products” such as genome assemblies or gene sets is of critical importance in order to recognize possible issues and correct them during the generation of new data. It is equally essential to guide subsequent or comparative analyses with existing data, as the correct interpretation of the results necessarily requires knowledge about the quality level and reliability of the inputs. Using datasets of near universal single‐copy orthologs derived from OrthoDB, BUSCO can estimate the completeness and redundancy of genomic data by providing biologically meaningful metrics based on expected gene content. These can complement technical metrics such as contiguity measures (e.g., number of contigs/scaffolds, and N50 values). Here, we describe the use of the BUSCO tool suite to assess different data types that can range from genome assemblies of single isolates and assembled transcriptomes and annotated gene sets to metagenome‐assembled genomes where the taxonomic origin of the species is unknown. BUSCO is the only tool capable of assessing all these types of sequences from both eukaryotic and prokaryotic species. The protocols detail the various BUSCO running modes and the novel workflows introduced in versions 4 and 5, including the batch analysis on multiple inputs, the auto‐lineage workflow to run assessments without specifying a dataset, and a workflow for the evaluation of (large) eukaryotic genomes. The protocols further cover the BUSCO setup, guidelines to interpret the results, and BUSCO “plugin” workflows for performing common operations in genomics using BUSCO results, such as building phylogenomic trees and visualizing syntenies. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC.[Correction added on May 16, 2022, after first online publication: CSAL funding statement has been added.]Basic Protocol 1: Assessing an input sequence with a BUSCO dataset specified manuallyBasic Protocol 2: Assessing an input sequence with a dataset automatically selected by BUSCOBasic Protocol 3: Assessing multiple inputsAlternate Protocol: Decreasing analysis runtime when assessing a large number of small genomes with BUSCO auto‐lineage workflow and SnakemakeSupport Protocol 1: BUSCO setupSupport Protocol 2: Visualizing BUSCO resultsSupport Protocol 3: Building phylogenomic trees

5 November 2018 in Nucleic Acids Research
Verified
Journal Article
Open access
PDF file
EKEvgenia V Kriventseva
Evgenia V Kriventseva
DKDmitry Kuznetsov
Dmitry Kuznetsov
FTFredrik Tegenfeldt
Fredrik Tegenfeldt
MMMosè Manni
Mosè Manni
RDRenata Dias
Renata Dias
EZEvgeny Zdobnov
Evgeny Zdobnov
OrthoDB (https://www.orthodb.org) provides evolutionary and functional annotations of orthologs. This update features a major scaling up of the resource coverage, sampling the genomic diversity of 1271 eukaryotes, 6013 prokaryotes and 6488 viruses. These include putative orthologs among 448 metazoan, 117 plant, 549 fungal, 148 protist, 5609 bacterial, and 404 archaeal genomes, picking up the best sequenced and annotated representatives for each species or operational taxonomic unit. OrthoDB relies on a concept of hierarchy of levels-of-orthology to enable more finely resolved gene orthologies for more closely related species. Since orthologs are the most likely candidates to retain functions of their ancestor gene, OrthoDB is aimed at narrowing down hypotheses about gene functions and enabling comparative evolutionary studies. Optional registered-user sessions allow on-line BUSCO assessments of gene set completeness and mapping of the uploaded data to OrthoDB to enable further interactive exploration of related annotations and generation of comparative charts. The accelerating expansion of genomics data continues to add valuable information, and OrthoDB strives to provide orthologs from the broadest coverage of species, as well as to extensively collate available functional annotations and to compute evolutionary annotations. The data can be browsed online, downloaded or assessed via REST API or SPARQL RDF compatible with both UniProt and Ensembl.