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      C. elegans germ granules sculpt both germline and somatic RNAome

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          Abstract

          Germ granules are membrane-less organelles essential for small RNA biogenesis and germline development. Among the conserved properties of germ granules is their association with the nuclear membrane. Recent studies demonstrated that LOTUS domain proteins, EGGD-1 and EGGD-2 (also known as MIP-1 and MIP-2 respectively), promote the formation of perinuclear germ granules in C. elegans. This finding presents a unique opportunity to evaluate the significance of perinuclear localization of germ granules. Here we show that loss of eggd-1 causes the coalescence of germ granules and formation of abnormal cytoplasmic aggregates. Impairment of perinuclear granules affects certain germline classes of small RNAs including Piwi-interacting RNAs. Transcriptome profiling reveals overexpression of spermatogenic and cuticle-related genes in eggd-1 hermaphrodites. We further demonstrate that disruption of germ granules activates HLH-30-mediated transcriptional program in somatic tissues. Collectively, our findings underscore the essential role of EGGD-1 in germ granule organization and reveal an unexpected germ granule-to-soma communication.

          Abstract

          Germ granules are membraneless organelles that act as organizing centers for small RNA biogenesis during germline development. Here they show the LOTUS domain protein eggd-1 organizes germ granules, and reveal a germ line-to-soma communication pathway activated upon perturbation of germ granules.

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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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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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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
                tang.542@osu.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                25 September 2023
                25 September 2023
                2023
                : 14
                : 5965
                Affiliations
                [1 ]Department of Biological Chemistry and Pharmacology, The Ohio State University, ( https://ror.org/00rs6vg23) Columbus, OH 43210 USA
                [2 ]Center for RNA Biology, The Ohio State University, ( https://ror.org/00rs6vg23) Columbus, OH 43210 USA
                [3 ]Ohio State Biochemistry Program, The Ohio State University, ( https://ror.org/00rs6vg23) Columbus, OH 43210 USA
                Author information
                http://orcid.org/0000-0001-6684-5258
                Article
                41556
                10.1038/s41467-023-41556-4
                10520050
                37749091
                15b25bbc-3c24-4404-9856-2354a06e84d2
                © Springer Nature Limited 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 April 2023
                : 8 September 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000057, U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS);
                Award ID: R35GM142580
                Award Recipient :
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                © Springer Nature Limited 2023

                Uncategorized
                gene expression,germline development,small rnas
                Uncategorized
                gene expression, germline development, small rnas

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