Abstract
The rapid development of deep sequencing technologies over the last few years and concomitant increases in sequencing depth and cost efficiencies have opened the door to a ever-widening range of applications in biology—from whole-genome sequencing, to ChIP-seq analysis, epigenomic and RNA transcriptome surveys. Here we describe the application of deep sequencing to the discovery of novel microRNAs and characterization of their differential expression during adulthood in Caenorhabditis elegans.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bartel DP (2009) MicroRNAs: target recognition and regulatory functions. Cell 136:215–233
Esquela-Kerscher A, Slack FJ (2006) Oncomirs—microRNAs with a role in cancer. Nat Rev Cancer 6:259–269
Boehm M, Slack F (2005) A developmental timing microRNA and its target regulate life span in C. elegans. Science 310:1954–1957
de Lencastre A et al (2010) MicroRNAs both promote and antagonize longevity in C. elegans. Curr Biol 20:2159–2168
Brenner JL, Jasiewicz KL, Fahley AF, Kemp BJ, Abbott AL (2010) Loss of individual microRNAs causes mutant phenotypes in sensitized genetic backgrounds in C. elegans. Curr Biol 20:1321–1325
Alvarez-Saavedra E, Horvitz HR (2010) Many families of C. elegans microRNAs are not essential for development or viability. Curr Biol 20:367–373
Miska EA et al (2007) Most Caenorhabditis elegans microRNAs are individually not essential for development or viability. PLoS Genet 3, e215
Kato M, Chen X, Inukai S, Zhao H, Slack FJ (2011) Age-associated changes in expression of small, noncoding RNAs, including microRNAs, in C. elegans. RNA 17:1804–1820
Friedländer MR, Mackowiak SD, Li N, Chen W, Rajewsky N (2012) miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res 40:37–52
Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26:139–140
Hausser J et al (2009) MirZ: an integrated microRNA expression atlas and target prediction resource. Nucleic Acids Res 37:W266–W272
Wang L, Feng Z, Wang X, Wang X, Zhang X (2010) DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics 26:136–138
Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome Biol 11:R106
Li J, Tibshirani R (2013) Finding consistent patterns: a nonparametric approach for identifying differential expression in RNA-Seq data. Stat Methods Med Res 22(5):519–536
Hardcastle TJ, Kelly KA (2010) baySeq: empirical Bayesian methods for identifying differential expression in sequence count data. BMC Bioinformatics 11:422
Brenner S (1974) The genetics of Caenorhabditis elegans. Genetics 77:71–94
Lau NC, Lim LP, Weinstein EG, Bartel DP (2001) An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science 294:858–862
Hafner M et al (2012) Barcoded cDNA library preparation for small RNA profiling by next-generation sequencing. Methods 58:164–170
Goecks J, Nekrutenko A, Taylor J, Team G (2010) Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol 11:R86
Lim LP et al (2003) The microRNAs of Caenorhabditis elegans. Genes Dev 17:991–1008
Kato M, de Lencastre A, Pincus Z, Slack FJ (2009) Dynamic expression of small non-coding RNAs, including novel microRNAs and piRNAs/21U-RNAs, during Caenorhabditis elegans development. Genome Biol 10:R54
Hofig KP, Feller A, Merz H (2007) New application for the LightCycler 480 system: qPCR-based microRNA-profiling. Biochemica:7–9
Pak J, Fire A (2007) Distinct populations of primary and secondary effectors during RNAi in C. elegans. Science 315:241–244
Hafner M et al (2008) Identification of microRNAs and other small regulatory RNAs using cDNA library sequencing. Methods 44:3–12
Hafner M et al (2011) RNA-ligase-dependent biases in miRNA representation in deep-sequenced small RNA cDNA libraries. RNA 17:1697–1712
Fahlgren N et al (2009) Computational and analytical framework for small RNA profiling by high-throughput sequencing. RNA 15:992–1002
Farazi TA et al (2011) MicroRNA sequence and expression analysis in breast tumors by deep sequencing. Cancer Res 71:4443–4453
Grishok A et al (2001) Genes and mechanisms related to RNA interference regulate expression of the small temporal RNAs that control C. elegans developmental timing. Cell 106:23–34
Hoogewijs D, Houthoofd K, Matthijssens F, Vandesompele J, Vanfleteren JR (2008) Selection and validation of a set of reliable reference genes for quantitative sod gene expression analysis in C. elegans. BMC Mol Biol 9:9
Acknowledgement
Some C. elegans strains were provided by the CGC, which is funded by NIH Office of Research Infrastructure Programs (P40 OD010440). We thank Dr. Giovanni Stefani and Dr. Masaomi Kato for help with methods. A.d.L. was supported by a National Research Service Award Postdoctoral Fellowship from the National Institutes of Health (NIH; 1F32AG030851). F.J.S. was supported by a Breakthroughs in Gerontology grant from the American Federation for Aging Research, the Ellison Medical Foundation, and the NIH (AG033921).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer Science+Business Media New York
About this protocol
Cite this protocol
de Lencastre, A., Slack, F. (2015). Discovery of Novel microRNAs in Aging Caenorhabditis elegans . In: Shaw, A. (eds) Immunosenescence. Methods in Molecular Biology, vol 1343. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2963-4_18
Download citation
DOI: https://doi.org/10.1007/978-1-4939-2963-4_18
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-2962-7
Online ISBN: 978-1-4939-2963-4
eBook Packages: Springer Protocols