Unbiased Transcriptional Comparisons of Generalist and Specialist Herbivores Feeding on Progressively Defenseless Nicotiana attenuata Plants

Background Herbivore feeding elicits dramatic increases in defenses, most of which require jasmonate (JA) signaling, and against which specialist herbivores are thought to be better adapted than generalist herbivores. Unbiased transcriptional analyses of how neonate larvae cope with these induced plant defenses are lacking. Methodology/Principal Findings We created cDNA microarrays for Manduca sexta and Heliothis virescens separately, by spotting normalized midgut-specific cDNA libraries created from larvae that fed for 24 hours on MeJA-elicited wild-type (WT) Nicotiana attenuata plants. These microarrays were hybridized with labeled probes from neonates that fed for 24 hours on WT and isogenic plants progressively silenced in JA-mediated defenses (N: nicotine; N/PI: N and trypsin protease inhibitors; JA: all JA-mediated defenses). H. virescens neonates regulated 16 times more genes than did M. sexta neonates when they fed on plants silenced in JA-mediated defenses, and for both species, the greater the number of defenses silenced in the host plant (JA > N/PI > N), the greater were the number of transcripts regulated in the larvae. M. sexta larvae tended to down-regulate while H. virescens larvae up- and down-regulated transcripts from the same functional categories of genes. M. sexta larvae regulated transcripts in a diet-specific manner, while H. virescens larvae regulated a similar suite of transcripts across all diet types. Conclusions/Significance The observations are consistent with the expectation that specialists are better adapted than generalist herbivores to the defense responses elicited in their host plants by their feeding. While M. sexta larvae appear to be better adapted to N. attenuata's defenses, some of the elicited responses remain effective defenses against both herbivore species. The regulated genes provide novel insights into larval adaptations to N. attenuata's induced defenses, and represent potential targets for plant-mediated RNAi to falsify hypotheses about the process of adaptation

Data Partitions, Bayesian Analysis and Phylogeny of the Zygomycetous Fungal Family Mortierellaceae, Inferred from Nuclear Ribosomal DNA Sequences

Although the fungal order Mortierellales constitutes one of the largest classical groups of Zygomycota, its phylogeny is poorly understood and no modern taxonomic revision is currently available. In the present study, 90 type and reference strains were used to infer a comprehensive phylogeny of Mortierellales from the sequence data of the complete ITS region and the LSU and SSU genes with a special attention to the monophyly of the genus Mortierella. Out of 15 alternative partitioning strategies compared on the basis of Bayes factors, the one with the highest number of partitions was found optimal (with mixture models yielding the best likelihood and tree length values), implying a higher complexity of evolutionary patterns in the ribosomal genes than generally recognized. Modeling the ITS1, 5.8S, and ITS2, loci separately improved model fit significantly as compared to treating all as one and the same partition. Further, within-partition mixture models suggests that not only the SSU, LSU and ITS regions evolve under qualitatively and/or quantitatively different constraints, but that significant heterogeneity can be found within these loci also. The phylogenetic analysis indicated that the genus Mortierella is paraphyletic with respect to the genera Dissophora, Gamsiella and Lobosporangium and the resulting phylogeny contradict previous, morphology-based sectional classification of Mortierella. Based on tree structure and phenotypic traits, we recognize 12 major clades, for which we attempt to summarize phenotypic similarities. M. longicollis is closely related to the outgroup taxon Rhizopus oryzae, suggesting that it belongs to the Mucorales. Our results demonstrate that traits used in previous classifications of the Mortierellales are highly homoplastic and that the Mortierellales is in a need of a reclassification, where new, phylogenetically informative phenotypic traits should be identified, with molecular phylogenies playing a decisive role

Transcriptome and genome sequencing uncovers functional variation in humans

Summary Genome sequencing projects are discovering millions of genetic variants in humans, and interpretation of their functional effects is essential for understanding the genetic basis of variation in human traits. Here we report sequencing and deep analysis of mRNA and miRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project – the first uniformly processed RNA-seq data from multiple human populations with high-quality genome sequences. We discovered extremely widespread genetic variation affecting regulation of the majority of genes, with transcript structure and expression level variation being equally common but genetically largely independent. Our characterization of causal regulatory variation sheds light on cellular mechanisms of regulatory and loss-of-function variation, and allowed us to infer putative causal variants for dozens of disease-associated loci. Altogether, this study provides a deep understanding of the cellular mechanisms of transcriptome variation and of the landscape of functional variants in the human genome

BIOINFORMATICS APPLICATIONS NOTE doi:10.1093/bioinformatics/btl007 Sequence analysis

Motivation: The first version of the graphical multiple sequence alignment environment QAlign was published in 2003. Heavy response from the molecular-biological user community clearly demonstrated the need for such a platform. Results: Panta rhei extends QAlign by several features. Major redesigns on the user interface, for instance, allow users to flexibily compose views for multiple projects. The new sequence viewer handles datasets with arbitrarily many and arbitrarily large sequences that may still be edited by guided block moving. More distance-based algorithms are available to interactively reconstruct phylogenetic trees which can now also be zoomed and navigated graphicaly. Availability: Executables and the JAVA source code are available under the Apache license a

ChimPipe : a pipeline for the precise detection of chimeras from RNA-seq data

International audienc

ChimPipe: Accurate detection of fusion genes and transcription-induced chimeras from RNA-seq data

Background: Chimeric transcripts are commonly defined as transcripts linking two or more different genes in the genome, and can be explained by various biological mechanisms such as genomic rearrangement, read-through or trans-splicing, but also by technical or biological artefacts. Several studies have shown their importance in cancer, cell pluripotency and motility. Many programs have recently been developed to identify chimeras from Illumina RNA-seq data (mostly fusion genes in cancer). However outputs of different programs on the same dataset can be widely inconsistent, and tend to include many false positives. Other issues relate to simulated datasets restricted to fusion genes, real datasets with limited numbers of validated cases, result inconsistencies between simulated and real datasets, and gene rather than junction level assessment. Results: Here we present ChimPipe, a modular and easy-to-use method to reliably identify fusion genes and transcription-induced chimeras from paired-end Illumina RNA-seq data. We have also produced realistic simulated datasets for three different read lengths, and enhanced two gold-standard cancer datasets by associating exact junction points to validated gene fusions. Benchmarking ChimPipe together with four other state-of-the-art tools on this data showed ChimPipe to be the top program at identifying exact junction coordinates for both kinds of datasets, and the one showing the best trade-off between sensitivity and precision. Applied to 106 ENCODE human RNA-seq datasets, ChimPipe identified 137 high confidence chimeras connecting the protein coding sequence of their parent genes. In subsequent experiments, three out of four predicted chimeras, two of which recurrently expressed in a large majority of the samples, could be validated. Cloning and sequencing of the three cases revealed several new chimeric transcript structures, 3 of which with the potential to encode a chimeric protein for which we hypothesized a new role. Applying ChimPipe to human and mouse ENCODE RNA-seq data led to the identification of 131 recurrent chimeras common to both species, and therefore potentially conserved. Conclusions: ChimPipe combines discordant paired-end reads and split-reads to detect any kind of chimeras, including those originating from polymerase read-through, and shows an excellent trade-off between sensitivity and precision. The chimeras found by ChimPipe can be validated in-vitro with high accuracy.National Human Genome Research Institute of the National Institutes of Health; by Obra Social Fundación ’la Caixa’ under the Severo Ochoa 2014 program; by grant BIO2011-26205 from the Spanish Ministry of Economy and Competitiveness (MINECO); Centro de Excelencia Severo Ochoa 2013-2017 (SEV-2012-0208); and by grant BFU2009-09117 from the Spanish Ministery of Science and Education (MICINN)Peer Reviewe

ChimPipe: Accurate detection of fusion genes and transcription-induced chimeras from RNA-seq data

Background: Chimeric transcripts are commonly defined as transcripts linking two or more different genes in the genome, and can be explained by various biological mechanisms such as genomic rearrangement, read-through or trans-splicing, but also by technical or biological artefacts. Several studies have shown their importance in cancer, cell pluripotency and motility. Many programs have recently been developed to identify chimeras from Illumina RNA-seq data (mostly fusion genes in cancer). However outputs of different programs on the same dataset can be widely inconsistent, and tend to include many false positives. Other issues relate to simulated datasets restricted to fusion genes, real datasets with limited numbers of validated cases, result inconsistencies between simulated and real datasets, and gene rather than junction level assessment. Results: Here we present ChimPipe, a modular and easy-to-use method to reliably identify fusion genes and transcription-induced chimeras from paired-end Illumina RNA-seq data. We have also produced realistic simulated datasets for three different read lengths, and enhanced two gold-standard cancer datasets by associating exact junction points to validated gene fusions. Benchmarking ChimPipe together with four other state-of-the-art tools on this data showed ChimPipe to be the top program at identifying exact junction coordinates for both kinds of datasets, and the one showing the best trade-off between sensitivity and precision. Applied to 106 ENCODE human RNA-seq datasets, ChimPipe identified 137 high confidence chimeras connecting the protein coding sequence of their parent genes. In subsequent experiments, three out of four predicted chimeras, two of which recurrently expressed in a large majority of the samples, could be validated. Cloning and sequencing of the three cases revealed several new chimeric transcript structures, 3 of which with the potential to encode a chimeric protein for which we hypothesized a new role. Applying ChimPipe to human and mouse ENCODE RNA-seq data led to the identification of 131 recurrent chimeras common to both species, and therefore potentially conserved. Conclusions: ChimPipe combines discordant paired-end reads and split-reads to detect any kind of chimeras, including those originating from polymerase read-through, and shows an excellent trade-off between sensitivity and precision. The chimeras found by ChimPipe can be validated in-vitro with high accuracy.This project was supported by Award Number 1U54HG007004-01 from the National Human Genome Research Institute of the National Institutes of Health, by Obra Social Fundación ’la Caixa’ under the Severo Ochoa 2014 program, by grant BIO2011-26205 from the Spanish Ministry of Economy and Competitiveness (MINECO), Centro de Excelencia Severo Ochoa 2013-2017 (SEV-2012-0208), and by grant BFU2009-09117 from the Spanish Ministery of Science and Education (MICINN). This publication has also been written with the support of the Agreenskills fellowship program which has received funding from the EU’s Seventh Framework Program under grant agreement No FP7-609398, and with the support of an institutional grant from Fundación Ramón Areces attributed to CBMSO

Climate Change Communication in the Netherlands

Climate change communication in the Netherlands started in the 1950s, but it was not until the late 1970s that the issue earned a place on the public agenda, as an aspect of the energy problem, and in the shadow of controversy about nuclear energy. Driven largely by scientific reports and political initiatives, the first climate change wave can be observed in the period from 1987 to 1989, as part of a broader environmental consciousness wave. The Netherlands took an active role in international climate change initiatives at the time but struggled to achieve domestic emission reductions throughout the 1990s. The political turmoil in the early 2000s dominated Dutch public debate, until An Inconvenient Truth triggered the second climate change wave in 2006–2007, generating peak media attention and broad societal activity. The combination of COP15 and Climategate in late 2009 marked a turning point in Dutch climate change communication, with online communication and climate-sceptic voices gaining much more prominence. Climate change mitigation was pushed down on the societal and political agenda in the 2010s. Climate change adaptation had received much attention during the second climate change wave and had been firmly institutionalized with respect to flood defense and other water management issues. By 2015 a landmark climate change court case and the Paris Agreement at COP21 were fueling climate change communication once again.<br/><br/>Keywords: climate change, communication, the Netherlands, media, framing, public agenda, science-policy interface, social medi