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Volodymyr Zavidovych

Bio: Volodymyr Zavidovych is an academic researcher from Duke University. The author has contributed to research in topics: Phylogenetic tree & Coalescent theory. The author has an hindex of 1, co-authored 1 publications receiving 1393 citations.

Papers
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Journal ArticleDOI
Erich D. Jarvis1, Siavash Mirarab2, Andre J. Aberer3, Bo Li4, Bo Li5, Bo Li6, Peter Houde7, Cai Li6, Cai Li4, Simon Y. W. Ho8, Brant C. Faircloth9, Benoit Nabholz, Jason T. Howard1, Alexander Suh10, Claudia C. Weber10, Rute R. da Fonseca11, Jianwen Li, Fang Zhang Zhang, Hui Li, Long Zhou, Nitish Narula7, Nitish Narula12, Liang Liu13, Ganesh Ganapathy1, Bastien Boussau, Shamsuzzoha Bayzid2, Volodymyr Zavidovych1, Sankar Subramanian14, Toni Gabaldón15, Salvador Capella-Gutierrez, Jaime Huerta-Cepas, Bhanu Rekepalli16, Bhanu Rekepalli17, Kasper Munch18, Mikkel H. Schierup18, Bent E. K. Lindow11, Wesley C. Warren19, David A. Ray, Richard E. Green20, Michael William Bruford21, Xiangjiang Zhan21, Xiangjiang Zhan22, Andrew Dixon, Shengbin Li5, Ning Li23, Yinhua Huang23, Elizabeth P. Derryberry24, Elizabeth P. Derryberry25, Mads F. Bertelsen26, Frederick H. Sheldon25, Robb T. Brumfield25, Claudio V. Mello27, Claudio V. Mello28, Peter V. Lovell27, Morgan Wirthlin27, Maria Paula Cruz Schneider28, Francisco Prosdocimi28, José Alfredo Samaniego11, Amhed Missael Vargas Velazquez11, Alonzo Alfaro-Núñez11, Paula F. Campos11, Bent O. Petersen29, Thomas Sicheritz-Pontén29, An Pas, Thomas L. Bailey, R. Paul Scofield30, Michael Bunce31, David M. Lambert14, Qi Zhou, Polina L. Perelman32, Amy C. Driskell33, Beth Shapiro20, Zijun Xiong, Yongli Zeng, Shiping Liu, Zhenyu Li, Binghang Liu, Kui Wu, Jin Xiao, Xiong Yinqi, Quiemei Zheng, Yong Zhang, Huanming Yang, Jian Wang, Linnéa Smeds10, Frank E. Rheindt34, Michael J. Braun35, Jon Fjeldså11, Ludovic Orlando11, F. Keith Barker4, Knud A. Jønsson4, Warren E. Johnson33, Klaus-Peter Koepfli33, Stephen J. O'Brien36, David Haussler, Oliver A. Ryder, Carsten Rahbek4, Eske Willerslev11, Gary R. Graves33, Gary R. Graves4, Travis C. Glenn13, John E. McCormack37, Dave Burt38, Hans Ellegren10, Per Alström, Scott V. Edwards39, Alexandros Stamatakis3, David P. Mindell40, Joel Cracraft4, Edward L. Braun41, Tandy Warnow42, Tandy Warnow2, Wang Jun, M. Thomas P. Gilbert4, M. Thomas P. Gilbert31, Guojie Zhang11, Guojie Zhang6 
12 Dec 2014-Science
TL;DR: A genome-scale phylogenetic analysis of 48 species representing all orders of Neoaves recovered a highly resolved tree that confirms previously controversial sister or close relationships and identifies the first divergence in Neoaves, two groups the authors named Passerea and Columbea.
Abstract: To better determine the history of modern birds, we performed a genome-scale phylogenetic analysis of 48 species representing all orders of Neoaves using phylogenomic methods created to handle genome-scale data. We recovered a highly resolved tree that confirms previously controversial sister or close relationships. We identified the first divergence in Neoaves, two groups we named Passerea and Columbea, representing independent lineages of diverse and convergently evolved land and water bird species. Among Passerea, we infer the common ancestor of core landbirds to have been an apex predator and confirm independent gains of vocal learning. Among Columbea, we identify pigeons and flamingoes as belonging to sister clades. Even with whole genomes, some of the earliest branches in Neoaves proved challenging to resolve, which was best explained by massive protein-coding sequence convergence and high levels of incomplete lineage sorting that occurred during a rapid radiation after the Cretaceous-Paleogene mass extinction event about 66 million years ago.

1,624 citations


Cited by
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TL;DR: The approach to utilizing available RNA-Seq and other data types in the authors' manual curation process for vertebrate, plant, and other species is summarized, and a new direction for prokaryotic genomes and protein name management is described.
Abstract: The RefSeq project at the National Center for Biotechnology Information (NCBI) maintains and curates a publicly available database of annotated genomic, transcript, and protein sequence records (http://www.ncbi.nlm.nih.gov/refseq/). The RefSeq project leverages the data submitted to the International Nucleotide Sequence Database Collaboration (INSDC) against a combination of computation, manual curation, and collaboration to produce a standard set of stable, non-redundant reference sequences. The RefSeq project augments these reference sequences with current knowledge including publications, functional features and informative nomenclature. The database currently represents sequences from more than 55,000 organisms (>4800 viruses, >40,000 prokaryotes and >10,000 eukaryotes; RefSeq release 71), ranging from a single record to complete genomes. This paper summarizes the current status of the viral, prokaryotic, and eukaryotic branches of the RefSeq project, reports on improvements to data access and details efforts to further expand the taxonomic representation of the collection. We also highlight diverse functional curation initiatives that support multiple uses of RefSeq data including taxonomic validation, genome annotation, comparative genomics, and clinical testing. We summarize our approach to utilizing available RNA-Seq and other data types in our manual curation process for vertebrate, plant, and other species, and describe a new direction for prokaryotic genomes and protein name management.

4,104 citations

Journal ArticleDOI
TL;DR: PartitionFinder 2 is a program for automatically selecting best-fit partitioning schemes and models of evolution for phylogenetic analyses that includes the ability to analyze morphological datasets, new methods to analyze genome-scale datasets, and new output formats to facilitate interoperability with downstream software.
Abstract: PartitionFinder 2 is a program for automatically selecting best-fit partitioning schemes and models of evolution for phylogenetic analyses. PartitionFinder 2 is substantially faster and more efficient than version 1, and incorporates many new methods and features. These include the ability to analyze morphological datasets, new methods to analyze genome-scale datasets, new output formats to facilitate interoperability with downstream software, and many new models of molecular evolution. PartitionFinder 2 is freely available under an open source license and works on Windows, OSX, and Linux operating systems. It can be downloaded from www.robertlanfear.com/partitionfinder. The source code is available at https://github.com/brettc/partitionfinder.

3,445 citations

Journal ArticleDOI
TL;DR: This work presents 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.
Abstract: 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.

1,575 citations

Journal ArticleDOI
TL;DR: The Environment for Tree Exploration v3 is presented, featuring numerous improvements in the underlying library of methods, and providing a novel set of standalone tools to perform common tasks in comparative genomics and phylogenetics.
Abstract: The Environment for Tree Exploration (ETE) is a computational framework that simplifies the reconstruction, analysis, and visualization of phylogenetic trees and multiple sequence alignments. Here, we present ETE v3, featuring numerous improvements in the underlying library of methods, and providing a novel set of standalone tools to perform common tasks in comparative genomics and phylogenetics. The new features include (i) building gene-based and supermatrix-based phylogenies using a single command, (ii) testing and visualizing evolutionary models, (iii) calculating distances between trees of different size or including duplications, and (iv) providing seamless integration with the NCBI taxonomy database. ETE is freely available at http://etetoolkit.org.

1,452 citations

Journal ArticleDOI
TL;DR: ASTRAL-III is a faster version of the ASTRAL method for phylogenetic reconstruction and can scale up to 10,000 species and removes low support branches from gene trees, resulting in improved accuracy.
Abstract: Evolutionary histories can be discordant across the genome, and such discordances need to be considered in reconstructing the species phylogeny. ASTRAL is one of the leading methods for inferring species trees from gene trees while accounting for gene tree discordance. ASTRAL uses dynamic programming to search for the tree that shares the maximum number of quartet topologies with input gene trees, restricting itself to a predefined set of bipartitions. We introduce ASTRAL-III, which substantially improves the running time of ASTRAL-II and guarantees polynomial running time as a function of both the number of species (n) and the number of genes (k). ASTRAL-III limits the bipartition constraint set (X) to grow at most linearly with n and k. Moreover, it handles polytomies more efficiently than ASTRAL-II, exploits similarities between gene trees better, and uses several techniques to avoid searching parts of the search space that are mathematically guaranteed not to include the optimal tree. The asymptotic running time of ASTRAL-III in the presence of polytomies is $O\left ((nk)^{1.726} D \right)$ where D=O(nk) is the sum of degrees of all unique nodes in input trees. The running time improvements enable us to test whether contracting low support branches in gene trees improves the accuracy by reducing noise. In extensive simulations, we show that removing branches with very low support (e.g., below 10%) improves accuracy while overly aggressive filtering is harmful. We observe on a biological avian phylogenomic dataset of 14K genes that contracting low support branches greatly improve results. ASTRAL-III is a faster version of the ASTRAL method for phylogenetic reconstruction and can scale up to 10,000 species. With ASTRAL-III, low support branches can be removed, resulting in improved accuracy.

1,261 citations