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      Dimerisation of the PICTS complex via LC8/Cut-up drives co-transcriptional transposon silencing in Drosophila

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          Abstract

          In animal gonads, the PIWI-interacting RNA (piRNA) pathway guards genome integrity in part through the co-transcriptional gene silencing of transposon insertions. In Drosophila ovaries, piRNA-loaded Piwi detects nascent transposon transcripts and instructs heterochromatin formation through the Panoramix- induced co- transcriptional silencing (PICTS) complex, containing Panoramix, Nxf2 and Nxt1. Here, we report that the highly conserved dynein light chain LC8/Cut-up (Ctp) is an essential component of the PICTS complex. Loss of Ctp results in transposon de-repression and a reduction in repressive chromatin marks specifically at transposon loci. In turn, Ctp can enforce transcriptional silencing when artificially recruited to RNA and DNA reporters. We show that Ctp drives dimerisation of the PICTS complex through its interaction with conserved motifs within Panoramix. Artificial dimerisation of Panoramix bypasses the necessity for its interaction with Ctp, demonstrating that conscription of a protein from a ubiquitous cellular machinery has fulfilled a fundamental requirement for a transposon silencing complex.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            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.
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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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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                04 February 2021
                2021
                : 10
                : e65557
                Affiliations
                [1 ]Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre CambridgeUnited Kingdom
                [2 ]Department of Biochemistry and Biophysics, Oregon State University CorvallisUnited States
                Aarhus University Denmark
                Harvard Medical School United States
                Aarhus University Denmark
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-3932-0402
                https://orcid.org/0000-0003-0406-2957
                https://orcid.org/0000-0001-9276-9981
                http://orcid.org/0000-0002-2689-8432
                http://orcid.org/0000-0002-3497-700X
                http://orcid.org/0000-0003-0662-8539
                http://orcid.org/0000-0003-4892-5259
                https://orcid.org/0000-0001-8471-0007
                https://orcid.org/0000-0003-4021-3898
                Article
                65557
                10.7554/eLife.65557
                7861614
                33538693
                bf34ccdd-ab1e-40cc-9d0e-df53c170a1c1
                © 2021, Eastwood et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 08 December 2020
                : 04 January 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000289, Cancer Research UK;
                Award ID: Core funding (A21143)
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Award ID: Investigator award (110161/Z/15/Z)
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: Award 1617019
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000288, Royal Society;
                Award ID: Wolfson Research Professor (RP130039)
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001645, Boehringer Ingelheim Fonds;
                Award ID: PhD fellowship
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Chromosomes and Gene Expression
                Custom metadata
                Heterochromatin formation at transposon loci depends on dimerisation of the effector complex that elicits co-transcriptional silencing and this requirement is fulfilled by co-option of the conserved dimerisation hub protein, Cut-up/LC8.

                Life sciences
                pirna pathway,co-transcriptional silencing,transposon,heterochromatin,dimerisation,lc8,d. melanogaster

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