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Find video protocols related to scientific articles indexed in Pubmed.
Phylogenomics resolves the timing and pattern of insect evolution.
Bernhard Misof, Shanlin Liu, Karen Meusemann, Ralph S Peters, Alexander Donath, Christoph Mayer, Paul B Frandsen, Jessica Ware, Tomáš Flouri, Rolf G Beutel, Oliver Niehuis, Malte Petersen, Fernando Izquierdo-Carrasco, Torsten Wappler, Jes Rust, Andre J Aberer, Ulrike Aspöck, Horst Aspöck, Daniela Bartel, Alexander Blanke, Simon Berger, Alexander Böhm, Thomas R Buckley, Brett Calcott, Junqing Chen, Frank Friedrich, Makiko Fukui, Mari Fujita, Carola Greve, Peter Grobe, Shengchang Gu, Ying Huang, Lars S Jermiin, Akito Y Kawahara, Lars Krogmann, Martin Kubiak, Robert Lanfear, Harald Letsch, Yiyuan Li, Zhenyu Li, Jiguang Li, Haorong Lu, Ryuichiro Machida, Yuta Mashimo, Pashalia Kapli, Duane D McKenna, Guanliang Meng, Yasutaka Nakagaki, José Luis Navarrete-Heredia, Michael Ott, Yanxiang Ou, Günther Pass, Lars Podsiadlowski, Hans Pohl, Björn M von Reumont, Kai Schütte, Kaoru Sekiya, Shota Shimizu, Adam Slipinski, Alexandros Stamatakis, Wenhui Song, Xu Su, Nikolaus U Szucsich, Meihua Tan, Xuemei Tan, Min Tang, Jingbo Tang, Gerald Timelthaler, Shigekazu Tomizuka, Michelle Trautwein, Xiaoli Tong, Toshiki Uchifune, Manfred G Walzl, Brian M Wiegmann, Jeanne Wilbrandt, Benjamin Wipfler, Thomas K F Wong, Qiong Wu, Gengxiong Wu, Yinlong Xie, Shenzhou Yang, Qing Yang, David K Yeates, Kazunori Yoshizawa, Qing Zhang, Rui Zhang, Wenwei Zhang, Yunhui Zhang, Jing Zhao, Chengran Zhou, Lili Zhou, Tanja Ziesmann, Shijie Zou, Yingrui Li, Xun Xu, Yong Zhang, Huanming Yang, Jian Wang, Jun Wang, Karl M Kjer, Xin Zhou.
Science
PUBLISHED: 11-06-2014
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Insects are the most speciose group of animals, but the phylogenetic relationships of many major lineages remain unresolved. We inferred the phylogeny of insects from 1478 protein-coding genes. Phylogenomic analyses of nucleotide and amino acid sequences, with site-specific nucleotide or domain-specific amino acid substitution models, produced statistically robust and congruent results resolving previously controversial phylogenetic relations hips. We dated the origin of insects to the Early Ordovician [~479 million years ago (Ma)], of insect flight to the Early Devonian (~406 Ma), of major extant lineages to the Mississippian (~345 Ma), and the major diversification of holometabolous insects to the Early Cretaceous. Our phylogenomic study provides a comprehensive reliable scaffold for future comparative analyses of evolutionary innovations among insects.
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The evolutionary history of holometabolous insects inferred from transcriptome-based phylogeny and comprehensive morphological data.
BMC Evol. Biol.
PUBLISHED: 03-04-2014
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Despite considerable progress in systematics, a comprehensive scenario of the evolution of phenotypic characters in the mega-diverse Holometabola based on a solid phylogenetic hypothesis was still missing. We addressed this issue by de novo sequencing transcriptome libraries of representatives of all orders of holometabolan insects (13 species in total) and by using a previously published extensive morphological dataset. We tested competing phylogenetic hypotheses by analyzing various specifically designed sets of amino acid sequence data, using maximum likelihood (ML) based tree inference and Four-cluster Likelihood Mapping (FcLM). By maximum parsimony-based mapping of the morphological data on the phylogenetic relationships we traced evolutionary transformations at the phenotypic level and reconstructed the groundplan of Holometabola and of selected subgroups.
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Decisive Data Sets in Phylogenomics: Lessons from Studies on the Phylogenetic Relationships of Primarily Wingless Insects.
Mol. Biol. Evol.
PUBLISHED: 10-18-2013
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Phylogenetic relationships of the primarily wingless insects are still considered unresolved. Even the most comprehensive phylogenomic studies that addressed this question did not yield congruent results. To get a grip on these problems, we here analyzed the sources of incongruence in these phylogenomic studies by using an extended transcriptome data set. Our analyses showed that unevenly distributed missing data can be severely misleading by inflating node support despite the absence of phylogenetic signal. In consequence, only decisive data sets should be used which exclusively comprise data blocks containing all taxa whose relationships are addressed. Additionally, we used Four-cluster Likelihood Mapping (FcLM) to measure the degree of congruence among genes of a data set, as a measure of support alternative to bootstrap. FcLM showed incongruent signal among genes, which in our case is correlated neither with functional class assignment of these genes nor with model misspecification due to unpartitioned analyses. The herein analyzed data set is the currently largest data set covering primarily wingless insects, but failed to elucidate their interordinal phylogenetic relationships. Although this is unsatisfying from a phylogenetic perspective, we try to show that the analyses of structure and signal within phylogenomic data can protect us from biased phylogenetic inferences due to analytical artifacts.
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The taming of an impossible child: a standardized all-in approach to the phylogeny of Hymenoptera using public database sequences.
BMC Biol.
PUBLISHED: 05-27-2011
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Enormous molecular sequence data have been accumulated over the past several years and are still exponentially growing with the use of faster and cheaper sequencing techniques. There is high and widespread interest in using these data for phylogenetic analyses. However, the amount of data that one can retrieve from public sequence repositories is virtually impossible to tame without dedicated software that automates processes. Here we present a novel bioinformatics pipeline for downloading, formatting, filtering and analyzing public sequence data deposited in GenBank. It combines some well-established programs with numerous newly developed software tools (available at http://software.zfmk.de/).
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Oligonucleotide primers for targeted amplification of single-copy nuclear genes in apocritan Hymenoptera.
PLoS ONE
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Published nucleotide sequence data from the mega-diverse insect order Hymenoptera (sawflies, bees, wasps, and ants) are taxonomically scattered and still inadequate for reconstructing a well-supported phylogenetic tree for the order. The analysis of comprehensive multiple gene data sets obtained via targeted PCR could provide a cost-effective solution to this problem. However, oligonucleotide primers for PCR amplification of nuclear genes across a wide range of hymenopteran species are still scarce.
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Genomic and morphological evidence converge to resolve the enigma of Strepsiptera.
Curr. Biol.
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The phylogeny of insects, one of the most spectacular radiations of life on earth, has received considerable attention. However, the evolutionary roots of one intriguing group of insects, the twisted-wing parasites (Strepsiptera), remain unclear despite centuries of study and debate. Strepsiptera exhibit exceptional larval developmental features, consistent with a predicted step from direct (hemimetabolous) larval development to complete metamorphosis that could have set the stage for the spectacular radiation of metamorphic (holometabolous) insects. Here we report the sequencing of a Strepsiptera genome and show that the analysis of sequence-based genomic data (comprising more than 18 million nucleotides from nearly 4,500 genes obtained from a total of 13 insect genomes), along with genomic metacharacters, clarifies the phylogenetic origin of Strepsiptera and sheds light on the evolution of holometabolous insect development. Our results provide overwhelming support for Strepsiptera as the closest living relatives of beetles (Coleoptera). They demonstrate that the larval developmental features of Strepsiptera, reminiscent of those of hemimetabolous insects, are the result of convergence. Our analyses solve the long-standing enigma of the evolutionary roots of Strepsiptera and reveal that the holometabolous mode of insect development is more malleable than previously thought.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.