Two isoforms of the essential C. elegans Argonaute CSR-1 differentially regulate sperm and oocyte fertility
TL;DR: In this article, the authors used CRISPR-Cas9 genome editing to introduce GFP::3xFLAG into the long and short (CSR-1a) isoforms of the Caenorhabditis elegans genome and found that CSR1a is expressed during spermatogenesis and in several somatic tissues, including the intestine.
Abstract: The Caenorhabditis elegans genome encodes nineteen functional Argonaute proteins that use 22G-RNAs, 26G-RNAs, miRNAs or piRNAs to regulate target transcripts. Only one Argonaute is essential under normal laboratory conditions: CSR-1. While CSR-1 has been studied widely, nearly all studies have overlooked the fact that the csr-1 locus encodes two isoforms. These isoforms differ by an additional 163 amino acids present in the N-terminus of CSR-1a. Using CRISPR-Cas9 genome editing to introduce GFP::3xFLAG into the long (CSR-1a) and short (CSR-1b) isoforms, we found that CSR-1a is expressed during spermatogenesis and in several somatic tissues, including the intestine. CSR-1b is expressed constitutively in the germline. small RNA sequencing of CSR-1 complexes shows that they interact with partly overlapping sets of 22G-RNAs. Phenotypic analyses reveal that the essential functions of csr-1 described in the literature coincide with CSR-1b, while CSR-1a plays tissue specific functions. During spermatogenesis, CSR-1a integrates into an sRNA regulatory network including ALG-3, ALG-4 and WAGO-10 that is necessary for fertility at 25°C. In the intestine, CSR-1a silences immunity and pathogen-responsive genes, and its loss results in improved survival from the pathogen Pseudomonas aeruginosa. Our findings functionally distinguish the CSR-1 isoforms and highlight the importance of studying each AGO isoform independently.
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TL;DR: In this paper , the authors show that C. elegans piRNAs trigger the transcriptional silencing of hundreds of spermatogenic genes during sperminogenesis, promoting sperm differentiation and function.
18 citations
TL;DR: The role of small RNAs in transmitting epigenetic information across generations in animals is discussed in this paper, focusing on the mechanisms by which smallRNAs achieve such a function, from the silencing of transgenes to the inheritance of complex traits, such as fertility, stress responses, infections, and behavior.
14 citations
TL;DR: An overview of germ granules is provided and the significance of more recent observations that describe how they further demix into sub-granules are focused on, each with unique compositions and functions.
Abstract: The transparency of Caenorhabditis elegans provides a unique window to observe and study the function of germ granules. Germ granules are specialized ribonucleoprotein (RNP) assemblies specific to the germline cytoplasm, and they are largely conserved across Metazoa. Within the germline cytoplasm, they are positioned to regulate mRNA abundance, translation, small RNA production, and cytoplasmic inheritance to help specify and maintain germline identity across generations. Here we provide an overview of germ granules and focus on the significance of more recent observations that describe how they further demix into sub-granules, each with unique compositions and functions.
11 citations
TL;DR: This work systematically analyzed every C. elegans AGO, using CRISPR-Cas9 genome editing to introduce GFP::3xFLAG tags to identify small RNA binding complements and determine the effects of ago loss on small RNA populations and developmental phenotypes.
Abstract: Argonaute (AGO) proteins associate with small RNAs to direct their effector function on complementary transcripts. The nematode C. elegans contains an expanded family of 19 functional AGO proteins, many of which have not been fully characterized. In this work we systematically analyzed every C. elegans AGO, using CRISPR-Cas9 genome editing to introduce GFP::3xFLAG tags. We have characterized the expression patterns of each AGO throughout development, identified small RNA binding complements, and determined the effects of ago loss on small RNA populations and developmental phenotypes. Our analysis indicates stratification of subsets of AGOs into distinct regulatory modules, and integration of our data led us to uncover novel stress-induced fertility and pathogen response phenotypes due to ago loss.
8 citations
01 Jul 2022
TL;DR: In this article , the authors highlight recent discoveries in the field of nuclear RNA interference in C. elegans and the roles of nuclear AGO/sRNA complexes in the regulation of gene expression, chromatin organization, genome stability, and transgenerational epigenetic inheritance.
Abstract: RNA interference (RNAi) is a highly conserved gene regulatory phenomenon whereby Argonaute/small RNA (AGO/sRNA) complexes target transcripts by antisense complementarity to modulate gene expression. While initially appreciated as a cytoplasmic process, RNAi can also occur in the nucleus where AGO/sRNA complexes are recruited to nascent transcripts. Nuclear AGO/sRNA complexes recruit co-factors that regulate transcription by inhibiting RNA Polymerase II, modifying histones, compacting chromatin and, in some organisms, methylating DNA. C. elegans has a longstanding history in unveiling the mechanisms of RNAi and has become an outstanding model to delineate the mechanisms underlying nuclear RNAi. In this review we highlight recent discoveries in the field of nuclear RNAi in C. elegans and the roles of nuclear RNAi in the regulation of gene expression, chromatin organization, genome stability, and transgenerational epigenetic inheritance.
8 citations
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TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
Abstract: 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
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47,038 citations
TL;DR: The origins, challenges and solutions of NIH Image and ImageJ software are discussed, and how their history can serve to advise and inform other software projects.
Abstract: For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
44,587 citations
TL;DR: Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis that facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system.
Abstract: Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
43,540 citations
TL;DR: MUSCLE is a new computer program for creating multiple alignments of protein sequences that includes fast distance estimation using kmer counting, progressive alignment using a new profile function the authors call the log-expectation score, and refinement using tree-dependent restricted partitioning.
Abstract: We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using treedependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
37,524 citations
TL;DR: 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 outperforms other aligners by a factor of >50 in mapping speed.
Abstract: Motivation 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. Results 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. Availability and implementation 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/.
30,684 citations