A comprehensive survey of <i>C. elegans</i> argonaute proteins reveals organism-wide gene regulatory networks and functions

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

Argonaute (AGO) proteins associate with small RNAs to direct their effector function on complementary transcripts. The nematode Caenorhabditis 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.

Related collections

Most cited references 93

Record: found
Abstract: found
Article: found

Is Open Access

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

Michael Love, Wolfgang Huber, Simon Anders (2014)

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.

0 comments Cited 25392 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

STAR: ultrafast universal RNA-seq aligner.

Alexander Dobin, Carrie A. Davis, Felix Schlesinger … (2013)

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/.

0 comments Cited 14604 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

Sudhir Kumar, Glen Stecher, Michael KaWah Li … (2018)

The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.

0 comments Cited 9754 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Julie M Claycomb:

ORCID: https://orcid.org/0000-0003-3132-5206

David E James: Role: Reviewing Editor

David E James: Role: Senior Editor

Journal

Journal ID (nlm-ta): eLife

Journal ID (iso-abbrev): Elife

Journal ID (publisher-id): eLife

Title: eLife

Publisher: eLife Sciences Publications, Ltd

ISSN (Electronic): 2050-084X

Publication date (Electronic, pub): 15 February 2023

Publication date Collection: 2023

Volume: 12

Electronic Location Identifier: e83853

Affiliations

[1 ] Department of Molecular Genetics, University of Toronto ( https://ror.org/03dbr7087) Toronto Canada

University of Sydney ( https://ror.org/0384j8v12) Australia

University of California, San Diego ( https://ror.org/0168r3w48) United States

Harvard University ( https://ror.org/03vek6s52) United States

Author information

Aaron W Reinke https://orcid.org/0000-0001-7612-5342

Julie M Claycomb https://orcid.org/0000-0003-3132-5206

Article

Publisher ID: 83853

DOI: 10.7554/eLife.83853

PMC ID: 10101689

PubMed ID: 36790166

SO-VID: 63417a0b-7f71-4de3-ad9c-b07d1c8ec9d7

License:

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

Date received : 30 September 2022

Date accepted : 14 February 2023

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;

Award ID: PJT-15608

Award Recipient : Julie M Claycomb

Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;

Award ID: PJG-175378

Award Recipient : Julie M Claycomb

Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;

Award ID: PJT-178076

Award Recipient : Julie M Claycomb

Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;

Award ID: PJT-400784

Award Recipient : Aaron W Reinke

Funded by: FundRef http://dx.doi.org/10.13039/501100000038, Natural Sciences and Engineering Research Council of Canada;

Award ID: RGPIN-2020-06235

Award Recipient : Julie M Claycomb

Funded by: FundRef http://dx.doi.org/10.13039/100000879, Alfred P. Sloan Foundation;

Award ID: FG2019-12040

Award Recipient : Aaron W Reinke

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Custom metadata

Author impact statement Systematically studying the expression, small RNA-binding partners, and loss-of-function phenotypes of all 19 Argonautes uncovers how small RNA regulatory pathways function and interact in Caenorhabditis elegans, a long-standing model for small RNA biology and RNAi.

ScienceOpen disciplines: Life sciences

Keywords: argonaute,mirna,pirna,22g-rna,26g-rna,gene regulation,c. elegans

Data availability:

ScienceOpen disciplines: Life sciences

Keywords: argonaute, mirna, pirna, 22g-rna, 26g-rna, gene regulation, c. elegans

A comprehensive survey of C. elegans argonaute proteins reveals organism-wide gene regulatory networks and functions

Read this article at

Abstract

Related collections

Hearing Loss and Restoration

Most cited references 93

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

STAR: ultrafast universal RNA-seq aligner.

MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

Author and article information

Contributors

Journal

Affiliations

Author information

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 190

Cited by 18

Most referenced authors 1,206