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      Small RNA in situ hybridization in Caenorhabditis elegans, combined with RNA-seq, identifies germline-enriched microRNAs

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          Abstract

          Over four hundred different microRNAs (miRNAs) have been identified in the genome of the model organism the nematode Caenorhabditis elegans. As the germline is dedicated to the preservation of each species, and almost half of all the cells in an adult nematode are germline, it is likely that regulatory miRNAs are important for germline development and maintenance. In C. elegans the miR35 family has strong maternal effects, contributing to normal embryogenesis and to adult fecundity. To determine whether any particular miRNAs are greatly enriched in the C. elegans germline we used RNA-seq to compare the miRNA populations in several germline-defective strains of adult C. elegans worms, including glp-4( germ l ine proliferation-4 ), glh-1( germ line helicase-1 ) and dcr-1( di ce r-1 ). Statistical analyses of RNA-seq comparisons identified 13 miRNAs that are germline-enriched, including seven members of the well-studied miR35 family that were reduced as much as 1000-fold in TaqMan qRT PCR miRNA assays. Along with the miR35s, six others: miR-56 (a member of the miR51 family), −70, −244, −260 , −788 and −4813, none of which previously considered as such, were also identified by RNA-seq as germline-enriched candidates. We went on to develop a successful miRNA in situ hybridization protocol for C. elegans, revealing miR35s specifically concentrate during oogenesis in the pachytene region of the gonad, and persist throughout early embryogenesis, while in adult animals neither let-7 nor miR-228 has a germline-bias.

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          Most cited references30

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            A microRNA controlling left/right neuronal asymmetry in Caenorhabditis elegans.

            How left/right functional asymmetry is layered on top of an anatomically symmetrical nervous system is poorly understood. In the nematode Caenorhabditis elegans, two morphologically bilateral taste receptor neurons, ASE left (ASEL) and ASE right (ASER), display a left/right asymmetrical expression pattern of putative chemoreceptor genes that correlates with a diversification of chemosensory specificities. Here we show that a previously undefined microRNA termed lsy-6 controls this neuronal left/right asymmetry of chemosensory receptor expression. lsy-6 mutants that we retrieved from a genetic screen for defects in neuronal left/right asymmetry display a loss of the ASEL-specific chemoreceptor expression profile with a concomitant gain of the ASER-specific profile. A lsy-6 reporter gene construct is expressed in less than ten neurons including ASEL, but not ASER. lsy-6 exerts its effects on ASEL through repression of cog-1, an Nkx-type homeobox gene, which contains a lsy-6 complementary site in its 3' untranslated region and that has been shown to control ASE-specific chemoreceptor expression profiles. lsy-6 is the first microRNA to our knowledge with a role in neuronal patterning, providing new insights into left/right axis formation.
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              Comparison of software packages for detecting differential expression in RNA-seq studies

              RNA-sequencing (RNA-seq) has rapidly become a popular tool to characterize transcriptomes. A fundamental research problem in many RNA-seq studies is the identification of reliable molecular markers that show differential expression between distinct sample groups. Together with the growing popularity of RNA-seq, a number of data analysis methods and pipelines have already been developed for this task. Currently, however, there is no clear consensus about the best practices yet, which makes the choice of an appropriate method a daunting task especially for a basic user without a strong statistical or computational background. To assist the choice, we perform here a systematic comparison of eight widely used software packages and pipelines for detecting differential expression between sample groups in a practical research setting and provide general guidelines for choosing a robust pipeline. In general, our results demonstrate how the data analysis tool utilized can markedly affect the outcome of the data analysis, highlighting the importance of this choice.
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                Author and article information

                Journal
                0372762
                3389
                Dev Biol
                Dev. Biol.
                Developmental biology
                0012-1606
                1095-564X
                14 November 2016
                10 August 2016
                15 October 2016
                01 December 2016
                : 418
                : 2
                : 248-257
                Affiliations
                [a ] Molecular Microbiology and Immunology Department, University of Missouri School of Medicine, Columbia, MO 65212, USA
                [b ] Department of Computer Science, Bond Life Science Center, University of Missouri, Columbia, MO 65211, USA
                [c ] Yotta Biomed, LLC, 4835 Cordell Ave #1117, Bethesda, MD 20814, USA
                [d ] The Seydoux Laboratory, Molecular Biology and Genetics Department, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
                Author notes
                [2]

                Current address: Natural Sciences Division, Southwestern College, Winfield, KS 67156, USA.

                [3]

                Professor Emerita, University of Missouri; Visiting Scientist, Seydoux Laboratory, USA.

                [* ] Corresponding author. bennettk@ 123456missouri.edu (K.L. Bennett).
                Article
                NIHMS821470
                10.1016/j.ydbio.2016.08.003
                5131644
                27521456
                e03187fe-40f0-47fa-9ec3-0368e61d1a8a

                This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

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                Categories
                Article

                Developmental biology
                glp-4,glh-1,dcr-1,mir in situ protocol,mir35 family,let-7,mir-228
                Developmental biology
                glp-4, glh-1, dcr-1, mir in situ protocol, mir35 family, let-7, mir-228

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