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      Transcriptomic responses to location learning by honeybee dancers are partly mirrored in the brains of dance-followers

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      1 , 2 , , 3 , 4 , 5 , 2
      Proceedings of the Royal Society B: Biological Sciences
      The Royal Society
      social learning, neurogenomics, gene expression, waggle dance, distance, direction

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          Abstract

          The waggle dances of honeybees are a strikingly complex form of animal communication that underlie the collective foraging behaviour of colonies. The mechanisms by which bees assess the locations of forage sites that they have visited for representation on the dancefloor are now well-understood, but few studies have considered the remarkable backward translation of such information into flight vectors by dance-followers. Here, we explore whether the gene expression patterns that are induced through individual learning about foraging locations are mirrored when bees learn about those same locations from their nest-mates. We first confirmed that the mushroom bodies of honeybee dancers show a specific transcriptomic response to learning about distance, and then showed that approximately 5% of those genes were also differentially expressed by bees that follow dances for the same foraging sites, but had never visited them. A subset of these genes were also differentially expressed when we manipulated distance perception through an optic flow paradigm, and responses to learning about target direction were also in part mirrored in the brains of dance followers. Our findings show a molecular footprint of the transfer of learnt information from one animal to another through this extraordinary communication system, highlighting the dynamic role of the genome in mediating even very short-term behavioural changes.

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          Most cited references69

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          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            WGCNA: an R package for weighted correlation network analysis

            Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at .
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              Anomalous collapses of Nares Strait ice arches leads to enhanced export of Arctic sea ice

              The ice arches that usually develop at the northern and southern ends of Nares Strait play an important role in modulating the export of Arctic Ocean multi-year sea ice. The Arctic Ocean is evolving towards an ice pack that is younger, thinner, and more mobile and the fate of its multi-year ice is becoming of increasing interest. Here, we use sea ice motion retrievals from Sentinel-1 imagery to report on the recent behavior of these ice arches and the associated ice fluxes. We show that the duration of arch formation has decreased over the past 20 years, while the ice area and volume fluxes along Nares Strait have both increased. These results suggest that a transition is underway towards a state where the formation of these arches will become atypical with a concomitant increase in the export of multi-year ice accelerating the transition towards a younger and thinner Arctic ice pack.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Journal
                Proc Biol Sci
                Proc Biol Sci
                RSPB
                royprsb
                Proceedings of the Royal Society B: Biological Sciences
                The Royal Society
                0962-8452
                1471-2954
                December 20, 2023
                December 2023
                December 20, 2023
                : 290
                : 2013
                : 20232274
                Affiliations
                [ 1 ] Present address: School of Biological Sciences, University of Aberdeen, , AB24 3UL Aberdeen, UK
                [ 2 ] Department of Biological Sciences, Royal Holloway University of London, , TW20 OEX Egham, UK
                [ 3 ] School of Biological & Behavioural Sciences, Queen Mary University of London, , E1 4NS London, UK
                [ 4 ] Digital Environment Research Institute, Queen Mary University of London, , E1 4NS London, UK
                [ 5 ] Department of Genetics, Evolution and Environment, University College London, , WC1E 6BT London, UK
                Author notes
                [ † ]

                Lead contact

                Electronic supplementary material is available online at https://doi.org/10.6084/m9.figshare.c.6960928.

                Author information
                http://orcid.org/0000-0002-9134-3994
                http://orcid.org/0000-0002-3140-2809
                http://orcid.org/0000-0003-0213-2018
                Article
                rspb20232274
                10.1098/rspb.2023.2274
                10730293
                38113935
                2efb3bd5-6bb6-480d-826f-ec20bb5b79f8
                © 2023 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : October 6, 2023
                : November 20, 2023
                Funding
                Funded by: H2020 European Research Council, http://dx.doi.org/10.13039/100010663;
                Award ID: 638873
                Categories
                1001
                14
                198
                42
                Behaviour
                Research Articles

                Life sciences
                social learning,neurogenomics,gene expression,waggle dance,distance,direction
                Life sciences
                social learning, neurogenomics, gene expression, waggle dance, distance, direction

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