6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Insights into coral bleaching under heat stress from analysis of gene expression in a sea anemone model system

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Loss of endosymbiotic algae (“bleaching”) under heat stress has become a major problem for reef-building corals worldwide. To identify genes that might be involved in triggering or executing bleaching, or in protecting corals from it, we used RNAseq to analyze gene-expression changes during heat stress in a coral relative, the sea anemone Aiptasia. We identified >500 genes that showed rapid and extensive up-regulation upon temperature increase. These genes fell into two clusters. In both clusters, most genes showed similar expression patterns in symbiotic and aposymbiotic anemones, suggesting that this early stress response is largely independent of the symbiosis. Cluster I was highly enriched for genes involved in innate immunity and apoptosis, and most transcript levels returned to baseline many hours before bleaching was first detected, raising doubts about their possible roles in this process. Cluster II was highly enriched for genes involved in protein folding, and most transcript levels returned more slowly to baseline, so that roles in either promoting or preventing bleaching seem plausible. Many of the genes in clusters I and II appear to be targets of the transcription factors NFκB and HSF1, respectively. We also examined the behavior of 337 genes whose much higher levels of expression in symbiotic than aposymbiotic anemones in the absence of stress suggest that they are important for the symbiosis. Unexpectedly, in many cases, these expression levels declined precipitously long before bleaching itself was evident, suggesting that loss of expression of symbiosis-supporting genes may be involved in triggering bleaching.

          Related collections

          Most cited references94

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            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/.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              HTSeq—a Python framework to work with high-throughput sequencing data

              Motivation: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. Results: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. Availability and implementation: HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. Contact: sanders@fs.tum.de
                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                November 09 2020
                : 202015737
                Article
                10.1073/pnas.2015737117
                33168733
                36b1555f-252b-4acd-b602-df085ade2702
                © 2020

                Free to read

                https://www.pnas.org/site/aboutpnas/licenses.xhtml

                History

                Comments

                Comment on this article