Name: mirmachine: a one-stop shop for plant mirna annotation
Uploaded: 2021-05-01T13:30:00
Description: Watch this Scientific Journal Video about mirMachine: A One-Stop Shop for Plant miRNA Annotation at JoVE.com

1. Software dependencies and installation
<ol>
	<li>Install software dependencies from their home site or using conda.
	<ol>
		<li>Download and install Perl, if it is not already installed, from its home site (https://www.perl.org/get.html). 
		NOTE: Represented results were predicted using Perl v5.32.0.</li>
		<li>Download Blast+, an alignment program, from its home site (https://www.ncbi.nlm.nih.gov/books/NBK279671/) as an executable and as source code. 
		NOTE: Represented results were predicted using the ...

<ol>
	<li>Voinnet, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Origin,+biogenesis,+and+activity+of+plant+microRNAs.">Origin, biogenesis, and activity of plant microRNAs.</a> Cell. 136 (4), 669-687 (2009).</li><li>Budak, H., Akpinar, B. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Plant+miRNAs:+biogenesis,+organization+and+origins.">Plant miRNAs: biogenesis, organization and origins.</a> Functional &amp; Integrative Genomics. 15 (5), 523-531 (2015).</li><li>Lee, R. C., Feinbaum, R. L., Ambros, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+C.+elegans+heterochronic+gene+lin-4+encodes+small+RNAs+with+antisense+complementarity+to+lin-14.">The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14.</a> Cell. 75 (5), 843-854 (1993).</li><li>Zhang, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exogenous+plant+MIR168a+specifically+targets+mammalian+LDLRAP1:+evidence+of+cross-kingdom+regulation+by+microRNA.">Exogenous plant MIR168a specifically targets mammalian LDLRAP1: evidence of cross-kingdom regulation by microRNA.</a> Cell Research. 22 (1), 107-126 (2012).</li><li>Pang, K. C., Frith, M. C., Mattick, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+evolution+of+noncoding+RNAs:+Lack+of+conservation+does+not+mean+lack+of+function.">Rapid evolution of noncoding RNAs: Lack of conservation does not mean lack of function.</a> Trends in Genetics. 22 (1), 1-5 (2006).</li><li>Guleria, P., Mahajan, M., Bhardwaj, J., Yadav, S. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Plant+small+RNAs:+biogenesis,+mode+of+action+and+their+roles+in+abiotic+stresses.">Plant small RNAs: biogenesis, mode of action and their roles in abiotic stresses.</a> Genomics, Proteomics and Bioinformatics. 9 (6), 183-199 (2011).</li><li>Jones-Rhoades, M. W., Bartel, D. P., Bartel, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs+and+their+regulatory+roles+in+plants.">MicroRNAs and their regulatory roles in plants.</a> Annual Review of Plant Biology. 57, 19-53 (2006).</li><li>Singh, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Plant+small+RNAs:+advancement+in+the+understanding+of+biogenesis+and+role+in+plant+development.">Plant small RNAs: advancement in the understanding of biogenesis and role in plant development.</a> Planta. 248 (3), 545-558 (2018).</li><li>Lucas, S. J., Budak, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sorting+the+wheat+from+the+chaff:+identifying+miRNAs+in+genomic+survey+sequences+of+Triticum+aestivum+chromosome+1AL.">Sorting the wheat from the chaff: identifying miRNAs in genomic survey sequences of Triticum aestivum chromosome 1AL.</a> PloS One. 7 (7), 40859 (2012).</li><li>Li, S., Castillo-Gonz&#225;lez, C., Yu, B., Zhang, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+functions+of+plant+small+RNAs+in+development+and+in+stress+responses.">The functions of plant small RNAs in development and in stress responses.</a> Plant Journal. 90 (4), 654-670 (2017).</li><li>Lee, Y., Jeon, K., Lee, J. T., Kim, S., Kim, V. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNA+maturation:+Stepwise+processing+and+subcellular+localization.">MicroRNA maturation: Stepwise processing and subcellular localization.</a> EMBO Journal. 21 (17), 4663-4670 (2002).</li><li>Lee, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNA+genes+are+transcribed+by+RNA+polymerase+II.">MicroRNA genes are transcribed by RNA polymerase II.</a> EMBO Journal. 23 (2), 4051-4060 (2004).</li><li>Bartel, D. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs:+Genomics,+biogenesis,+mechanism,+and+function.">MicroRNAs: Genomics, biogenesis, mechanism, and function.</a> Cell. 116 (2), 281-297 (2004).</li><li>Lee, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+nuclear+RNase+III+Drosha+initiates+microRNA+processing.">The nuclear RNase III Drosha initiates microRNA processing.</a> Nature. 425 (6956), 415-419 (2003).</li><li>Meyers, B. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Criteria+for+annotation+of+plant+microRNAs.">Criteria for annotation of plant microRNAs.</a> Plant Cell. 20 (12), 3186-3190 (2008).</li><li>Sanei, M., Chen, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanisms+of+microRNA+turnover.">Mechanisms of microRNA turnover.</a> Current Opinion in Plant Biology. 27, 199-206 (2015).</li><li>Li, J., Yang, Z., Yu, B., Liu, J., Chen, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methylation+protects+miRNAs+and+siRNAs+from+a+3&#8242;-end+uridylation+activity+in+Arabidopsis.">Methylation protects miRNAs and siRNAs from a 3&#8242;-end uridylation activity in Arabidopsis.</a> Current Biology. 15 (16), 1501-1507 (2005).</li><li>Rogers, K., Chen, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biogenesis,+turnover,+and+mode+of+action+of+plant+microRNAs.">Biogenesis, turnover, and mode of action of plant microRNAs.</a> Plant Cell. 25 (7), 2383-2399 (2013).</li><li>Axtell, M. J., Meyers, B. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Revisiting+criteria+for+plant+microRNA+annotation+in+the+Era+of+big+data.">Revisiting criteria for plant microRNA annotation in the Era of big data.</a> Plant Cell. 30 (2), 272-284 (2018).</li><li>Camacho, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BLAST+:+architecture+and+applications.">BLAST+: architecture and applications.</a> BMC Bioinformatics. 10 (1), 421 (2009).</li><li>Markham, N. R. N., Zuker, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=UNAFold:+Software+for+nucleic+acid+folding+and+hybridization.">UNAFold: Software for nucleic acid folding and hybridization.</a> Methods in Molecular Biology. 453, 3-31 (2008).</li><li>Alptekin, B., Akpinar, B. A., Budak, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comprehensive+prescription+for+plant+miRNA+identification.">A comprehensive prescription for plant miRNA identification.</a> Frontiers in Plant Science. 7, 2058 (2017).</li><li>Zhang, B., Pan, X., Cannon, C. H., Cobb, G. P., Anderson, T. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Conservation+and+divergence+of+plant+microRNA+genes.">Conservation and divergence of plant microRNA genes.</a> Plant Journal. 46 (2), 243-259 (2006).</li><li>Appels, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Shifting+the+limits+in+wheat+research+and+breeding+using+a+fully+annotated+reference+genome.">Shifting the limits in wheat research and breeding using a fully annotated reference genome.</a> Science. 361 (6403), 7191 (2018).</li><li>Wang, Y., Kuang, Z., Li, L., Yang, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+bioinformatics+pipeline+to+accurately+and+efficiently+analyze+the+microRNA+transcriptomes+in+plants.">A bioinformatics pipeline to accurately and efficiently analyze the microRNA transcriptomes in plants.</a> Journal of Visualized Experiments: JoVE. (155), e59864 (2020).</li><li>Kozomara, A., Griffiths-Jones, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MiRBase:+Annotating+high+confidence+microRNAs+using+deep+sequencing+data.">MiRBase: Annotating high confidence microRNAs using deep sequencing data.</a> Nucleic Acids Research. 42, 68-73 (2014).</li><li>Lorenz, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ViennaRNA+Package+2.0.">ViennaRNA Package 2.0.</a> Algorithms for Molecular Biology. 6 (1), 26 (2011).</li><li>Wicker, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impact+of+transposable+elements+on+genome+structure+and+evolution+in+bread+wheat.">Impact of transposable elements on genome structure and evolution in bread wheat.</a> Genome Biology. 19 (1), 103 (2018).</li><li>Flavell, R. B., Bennett, M. D., Smith, J. B., Smith, D. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome+size+and+the+proportion+of+repeated+nucleotide+sequence+DNA+in+plants.">Genome size and the proportion of repeated nucleotide sequence DNA in plants.</a> Biochemical Genetics. 12 (4), 257-269 (1974).</li><li>Wicker, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+repetitive+landscape+of+the+5100+Mbp+barley+genome.">The repetitive landscape of the 5100 Mbp barley genome.</a> Mobile DNA. 8, 22 (2017).</li><li>Yang, Q., Ye, Q. A., Liu, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanism+of+siRNA+production+from+repetitive+DNA.">Mechanism of siRNA production from repetitive DNA.</a> Genes and Development. 29 (5), 526-537 (2015).</li><li>Lam, J. K. W., Chow, M. Y. T., Zhang, Y., Leung, S. W. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=siRNA+versus+miRNA+as+therapeutics+for+gene+silencing.">siRNA versus miRNA as therapeutics for gene silencing.</a> Molecular Therapy. Nucleic Acids. 4 (9), 252 (2015).</li><li>Bartel, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs+directing+siRNA+biogenesis.">MicroRNAs directing siRNA biogenesis.</a> Nature Structural and Molecular Biology. 12 (7), 569-571 (2005).</li><li>Meng, Y., Shao, C., Wang, H., Chen, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Are+all+the+miRBase-registered+microRNAs+true?+A+structure-+and+expression-based+re-examination+in+plants.">Are all the miRBase-registered microRNAs true? A structure- and expression-based re-examination in plants.</a> RNA Biology. 9 (3), 249-253 (2012).</li><li>Berezikov, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evolutionary+flux+of+canonical+microRNAs+and+mirtrons+in+Drosophila.">Evolutionary flux of canonical microRNAs and mirtrons in Drosophila.</a> Nature Genetics. 42 (1), 6-9 (2010).</li></ol>

Our miRNA pipeline, SUmir, has been used for the identification of many plant miRNAs for the last decade. Here, we developed a new, fully automated, and freely available miRNA identification and annotation pipeline, mirMachine. Furthermore, a number of miRNA identification pipelines including, but not limited to the previous pipeline, were dependent on UNAfold software21, which became a commercial software over time, although once being freely available. This new and fully automated mirMachine is ...

Advances in next generation sequencing technologies have widened the understanding of RNA structures and regulatory elements, revealing functionally important non-coding RNAs (ncRNAs). Among different types of ncRNAs, microRNAs (miRNAs) constitute a fundamental regulatory class of small RNAs with a length between 19 and 24 nucleotides in plants1,2. Since the discovery of the first miRNA in the nematode Caenorhabditis elegans3, the presence and the functions of miRNAs have been studied extensively in animal and plant genomes as well4,5,6. miRNAs function by targeting mRNAs for cleavage or translational repression7. Accumulating evidence has also shown that miRNAs are involved in a wide range of biological processes in plants including growth and development8, self-biogenesis9, and several biotic and abiotic stress responses10.
In plants, miRNAs are initially processed from long primary transcripts called pri-miRNAs11. These pri-miRNAs generated by RNA polymerase II inside the nucleus are long transcripts forming an imperfect fold-back structure12. The pri-miRNAs later undergo a cleavage process to produce endogenous single-stranded (ss) hairpin precursors of miRNAs called pre-miRNAs11. The pre-miRNA forms a hairpin-like structure wherein a single strand folds into a double-stranded structure to excise an miRNA duplex (miRNA/miRNA*)13. Dicer-like protein cuts both strands of the miRNA/miRNA* duplex, leaving 2-nucleotide 3&#39;-overhangs14,15. The miRNA duplex is methylated inside the nucleus, which protects the 3&#39;-end of the miRNA from degradation and uridylation activity16,17. A helicase unwinds the methylated miRNA duplex after export and exposes the mature miRNA to the RNA-induced silencing complex (RISC) in the cytosol18. One strand of the duplex is mature miRNA incorporated into RISC , whereas the other strand, miRNA*, is degraded. The miRNA-RISC complex binds to the target sequence leading to either mRNA degradation in case of full complementarity or translational repression in case of partial complementarity13.
Based on the expression and biogenesis features, guidelines for miRNA annotation have been described15,19. With the defined guidelines, Lucas and Budak developed the SUmir pipeline to perform a homology-based in silico miRNA identification in plants9. The SUmir pipeline was composed of two scripts: SUmirFind and SUmirFold. SUmirFind performs similarity searches against known miRNA datasets through National Center for Biotechnology Information (NCBI) Basic Local Alignment Search tool (BLAST) screening with modified parameters to include hits with only 2 or fewer mismatches and to avoid bias towards shorter hits (blastn-short -ungapped -penalty -1 -reward 1). SUmirFold evaluates the secondary structure of the putative miRNA sequences from BLAST20 results using UNAfold21. SUmirFold differentiates miRNAs from small interfering RNAs by the identification of the characteristics of hairpin structure. Moreover, it differentiates miRNAs from other ssRNAs such as tRNA and rRNA by the parameters, minimum fold energy index &#62; 0.67 and GC content of 24-71%. This pipeline has been recently updated by adding two additional steps to (i) increase sensitivity, (ii) increase annotation accuracy, and (iii) provide genomic distribution of the predicted miRNA genes22. Given the high conservation of plant miRNA sequences23, this pipeline was originally designed for homology-based miRNA prediction. Novel miRNAs, however, could not be accurately identified with this bioinformatics analysis as it heavily relied on sequence conservation of miRNAs between closely related species.
This paper presents a new and fully automated miRNA pipeline, mirMachine that 1) can identify known and novel miRNAs more accurately (for example, the pipeline now uses sRNA-seq-based novel miRNA predictions as well as homology-based miRNA identification) and 2) is fully automated and freely available. The outputs have also included the genomic distributions of the predicted miRNAs. mirMachine was tested for both homology-based and sRNA-seq-based predictions in wheat and Arabidopsis genomes. Although initially released as free software, UNAfold became a commercial software in the last decade. With this upgrade, the secondary structure prediction tool was switched from UNAfold to RNAfold so that mirMachine can be freely available. Users can now execute a short submission script to run the fully automated mirMachine pipeline (examples are provided at https://github.com/hbusra/mirMachine.git).

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>https://www.ncbi.nlm.nih.gov/books/NBK279671/</td>
			<td></td>
			<td></td>
			<td>Blast+</td>
		</tr>
		<tr>
			<td>https://github.com/hbusra/mirMachine.git</td>
			<td></td>
			<td></td>
			<td>mirMachine submission script</td>
		</tr>
		<tr>
			<td>https://www.perl.org/get.html</td>
			<td></td>
			<td></td>
			<td>Perl</td>
		</tr>
		<tr>
			<td>https://www.tbi.univie.ac.at/RNA/</td>
			<td></td>
			<td></td>
			<td>RNAfold</td>
		</tr>
		<tr>
			<td>Arabidopsis TAIR10</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Triticum aestivum (wheat, IWGSC RefSeq v2)</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

mirmachine: a one-stop shop for plant mirna annotation

Of different types of noncoding RNAs, microRNAs (miRNAs) have arguably been in the spotlight over the last decade. As post-transcriptional regulators of gene expression, miRNAs play key roles in various cellular pathways, including both development and response to a/biotic stress, such as drought and diseases. Having high-quality reference genome sequences enabled identification and annotation of miRNAs in several plant species, where miRNA sequences are highly conserved. As computational miRNA identification and annotation processes are mostly error-prone processes, homology-based predictions increase prediction accuracy. We developed and have improved the miRNA annotation pipeline, SUmir, in the last decade, which has been used for several plant genomes since then. 
This study presents a fully automated, new miRNA pipeline, mirMachine (miRNA Machine), by (i) adding an additional filtering step on the secondary structure predictions, (ii) making it fully automated, and (iii) introducing new options to predict either known miRNA based on homology or novel miRNAs based on small RNA sequencing reads using the previous pipeline. The new miRNA pipeline, mirMachine, was tested using The Arabidopsis Information Resource, TAIR10, release of the Arabidopsis genome and the International Wheat Genome Sequencing Consortium (IWGSC) wheat reference genome v2.

The miRNA pipeline, mirMachine, described above was applied to the test data for the fast evaluation of the performance of the pipeline. Only the high-confidence plant miRNAs deposited at miRBase v22.1 were screened against the chromosome 5A of IWGSC wheat RefSeq genome v224. mirMachine_find returned 312 hits for the nonredundant list of 189 high-confidence miRNAs with a maximum of 1 mismatch allowed (Table 1). mirMachine_fold classified 49 of them as putative miRNAs depending on ...

Watch this Scientific Journal Video about mirMachine: A One-Stop Shop for Plant miRNA Annotation at JoVE.com

mirMachine: A One-Stop Shop for Plant miRNA Annotation

Herein, we present a new and fully automated miRNA pipeline, mirMachine that 1) can identify known and novel miRNAs more accurately and 2) is fully automated and freely available. Users can now execute a short submission script to run the fully automated mirMachine pipeline.

Of different types of noncoding RNAs, microRNAs (miRNAs) have arguably been in the spotlight over the last decade. As post-transcriptional regulators of ...

Computational identification of micro RNA's yields high false positive predictions. With the recent updates mirMachine provides high sensitivity and specificity in known and novel micro RNA predictions. MirMachine is proved to be superior to the most recent micro RNA algorithms in terms of sensitivity and mirMachine is now fully automated and freely available so everyone can use it with instructions provided.MirMachine can predict the genome-wide distribution of the putative micro RNAs without limitation of the data specific to tissues and conditions. Availability of the preliminary data prior to msRNA sequencing experiment would speed up the verification process for the important micro RNA genes. Before setting up the machine download and install software dependencies from the respective home sites using the links in the text manuscript.Alternatively, an easier and faster way to install the software dependencies is to use conduct using the commands provided in the text manuscript. Download the latest version of the mirMachine scripts the mere machine submission script from GitHub. Then set the scripts path into the path tab.Make sure that the mirMachine and its dependencies have been downloaded correctly by running the mirMachine on test data from GitHub. Check the job status on the screen by the standard output stream. Once all finished text appears, control the output files.Control the hairpins dot TBL dot out dot TBL output files. Notice the mature miRNA pre miRNA and the miRNAs star sequences on the second, third, and sixth columns. Find the location of the predicted miRNAs on the chromosomes at the end of each line.Then check the log files for the program outputs and warnings. For homology based identification run the mirMachine using the bash script and check the predicted mRNAs. Find the output file for the mature miRNAs and pre miRNA fastest sequences, as well as the output file for the hairpin log file.For novel miRNA identification pre-process the sRNA-seq Fast Q files into the proper FASTA format. Trim the adapters and remove low quality reads like those containing N as pre-processing for the sRNA-seq reads are not part of mirMachine. Choose a stable trimming tool and trimming parameters for the data submitted.Convert the FASTQ file into FASTA file as input file. If an abundance table file is provided use the modification script provided with the mirMachine scripts to convert the table file into a proper FASTA input. Then run the mirMachine using the bash script.Check the predicted miRNAs. Find the output file for the predicted mRNAs and prem miRNA FASTA sequences and the output file for the hairpin log file. Set the dash DB option to a blast database to skip the building reference database within the pipeline.Set the dash M option to the number of mismatches allowed and the dash N to the number of hits to eliminate after alignment. Change this based on the species. Use the dash long to assess the secondary structures for the suspect list, and the dash as to activate the novel miRNA prediction based on sRNA-seq data.Set the dash L max option to the maximum length of the S RNA-seq reads to include in the screening and the dash L min option to the minimum length of the sRNA-seq reads to have in the screening. Use the dash RPM option to set the reads per million threshold. In the representative analysis.The distribution of mRNA families from the chromosome five A of the IWGSC Wheat is displayed. The highest represented group of mRNAs was miR9666 with 18 identified miRNAs. Performance of the mirMachine on Arabidopsis thaliana and wheat species compared with the miRDP2.Comparisons of the sensitivity and the number two positives showed that mirMachine outperformed miRDP2 on the Arabidopsis data. For the wheat data mirMachine homology based prediction with expression evidence provided better sensitivity than miRDP2. For both genomes miRDP2 predicted a higher number of true positives than sRNAs-seq and homology based predictions.Setting up the required application could be burdensome for the inexperienced user. Following this video tutorial would help. Visualization of the installation process will encourage the non computational researchers to get into some basic computing.Additionally, investigating the output files in the video will definitely help the users interpret their results.

mirmachine-a-one-stop-shop-for-plant-mirna-annotation

Research

JoVE Journal

Biology

Choice and No-Choice Assays for Testing the Resistance of A. thaliana to Chewing Insects

Larvae of the small white cabbage butterfly are a pest in agricultural settings. This caterpillar species feeds from plants in the cabbage family, which include many crops such as cabbage, broccoli, Brussel sprouts etc. Rearing of the insects takes place on cabbage plants in the greenhouse. At least two cages are needed for the rearing of Pieris rapae. One for the larvae and the other to contain the adults, the butterflies. In order to investigate the role of plant hormones and toxic plant chemicals in resistance to this insect pest, we demonstrate two experiments. First, determination of the role of jasmonic acid (JA - a plant hormone often indicated in resistance to insects) in resistance to the chewing insect Pieris rapae. Caterpillar growth can be compared on wild-type and mutant plants impaired in production of JA. This experiment is considered "No Choice", because larvae are forced to subsist on a single plant which synthesizes or is deficient in JA. Second, we demonstrate an experiment that investigates the role of glucosinolates, which are used as oviposition (egg-laying) signals. Here, we use WT and mutant Arabidopsis impaired in glucosinolate production in a "Choice" experiment in which female butterflies are allowed to choose to lay their eggs on plants of either genotype. This video demonstrates the experimental setup for both assays as well as representative results.

Plant resistance to chewing insect herbivores can be tested in several ways. Here, we demonstrate how to set-up a choice and a no-choice experiment with the model plant Arabidopsis thaliana to identify resistance against the pest species Pieris rapae.

Larvae of the small white cabbage butterfly are a pest in agricultural settings. This caterpillar species feeds from plants in the cabbage family, which ...

Virus-induced Gene Silencing (VIGS) in Nicotiana benthamiana and Tomato

RNA interference (RNAi) is a highly specific gene-silencing phenomenon triggered by dsRNA1. This silencing mechanism uses two major classes of RNA regulators: microRNAs, which are produced from non-protein coding genes and short interfering RNAs (siRNAs). Plants use RNAi to control transposons and to exert tight control over developmental processes such as flower organ formation and leaf development2,3,4. Plants also use RNAi to defend themselves against infection by viruses. Consequently, many viruses have evolved suppressors of gene silencing to allow their successful colonization of their host5.
Virus-induced gene silencing (VIGS) is a method that takes advantage of the plant RNAi-mediated antiviral defense mechanism. In plants infected with unmodified viruses the mechanism is specifically targeted against the viral genome. However, with virus vectors carrying sequences derived from host genes, the process can be additionally targeted against the corresponding host mRNAs. VIGS has been adapted for high-throughput functional genomics in plants by using the plant pathogen Agrobacterium tumefaciens to deliver, via its Ti plasmid, a recombinant virus carrying the entire or part of the gene sequence targeted for silencing. Systemic virus spread and the endogenous plant RNAi machinery take care of the rest. dsRNAs corresponding to the target gene are produced and then cleaved by the ribonuclease Dicer into siRNAs of 21 to 24 nucleotides in length. These siRNAs ultimately guide the RNA-induced silencing complex (RISC) to degrade the target transcript2.
Different vectors have been employed in VIGS and one of the most frequently used is based on tobacco rattle virus (TRV). TRV is a bipartite virus and, as such, two different A. tumefaciens strains are used for VIGS. One carries pTRV1, which encodes the replication and movement viral functions while the other, pTRV2, harbors the coat protein and the sequence used for VIGS6,7. Inoculation of Nicotiana benthamiana and tomato seedlings with a mixture of both strains results in gene silencing. Silencing of the endogenous phytoene desaturase (PDS) gene, which causes photobleaching, is used as a control for VIGS efficiency. It should be noted, however, that silencing in tomato is usually less efficient than in N. benthamiana. RNA transcript abundance of the gene of interest should always be measured to ensure that the target gene has efficiently been down-regulated. Nevertheless, heterologous gene sequences from N. benthamiana can be used to silence their respective orthologs in tomato and vice versa8.

Virus-induced Gene Silencing VIGS in Nicotiana benthamiana and Tomato

Description of a virus-induced gene silencing (VIGS) method for knock-down of gene expression in Nicotiana benthamiana and tomato.

RNA interference (RNAi) is a highly specific gene-silencing phenomenon triggered by dsRNA1. This silencing mechanism uses two major classes of RNA ...

A &#946;-glucuronidase (GUS) Based Cell Death Assay

We have developed a novel transient plant expression system that simultaneously expresses the reporter gene, &beta;-glucuronidase (GUS), with putative positive or negative regulators of cell death. In this system, N. benthamiana leaves are co-infiltrated with a 35S driven expression cassette containing the gene to be analyzed, and the GUS vector pCAMBIA 2301 using Agrobacterium strain LBA4404 as a vehicle. Because live cells are required for GUS expression to occur, loss of GUS activity is expected when this marker gene is co-expressed with positive regulators of cell death. Equally, increased GUS activity is observed when anti-apoptotic genes are used compared to the vector control. As shown below, we have successfully used this system in our lab to analyze both pro- and anti-death players. These include the plant anti-apoptotic Bcl-2 Associated athanoGene (BAG) family, as well as, known mammalian inducers of cell death, such as BAX. Additionally, we have used this system to analyze the death function of specific truncations within proteins, which could provide clues on the possible post-translational modification/activation of these proteins. Here, we present a rapid and sensitive plant based method, as an initial step in investigating the death function of specific genes.

A &amp;#946;-glucuronidase GUS Based Cell Death Assay

Programmed cell death assays commonly used in mammalian systems such as DNA laddering or TUNEL assays, are often difficult to reproduce in plants. In combination with a GUS reporter system, we propose a rapid, plant based transient assay to analyze the potential death properties of specific genes.

We have developed a novel transient plant expression system that simultaneously expresses the reporter gene, &beta;-glucuronidase (GUS), with putative ...

Agrobacterium-Mediated Virus-Induced Gene Silencing Assay In Cotton

Cotton (Gossypium hirsutum) is one of the most important crops worldwide. Considerable efforts have been made on molecular breeding of new varieties. The large-scale gene functional analysis in cotton has been lagged behind most of the modern plant species, likely due to its large size of genome, gene duplication and polyploidy, long growth cycle and recalcitrance to genetic transformation1. To facilitate high throughput functional genetic/genomic study in cotton, we attempt to develop rapid and efficient transient assays to assess cotton gene functions.
Virus-Induced Gene Silencing (VIGS) is a powerful technique that was developed based on the host Post-Transcriptional Gene Silencing (PTGS) to repress viral proliferation2,3. Agrobacterium-mediated VIGS has been successfully applied in a wide range of dicots species such as Solanaceae, Arabidopsis and legume species, and monocots species including barley, wheat and maize, for various functional genomic studies3,4. As this rapid and efficient approach avoids plant transformation and overcomes functional redundancy, it is particularly attractive and suitable for functional genomic study in crop species like cotton not amenable for transformation.
In this study, we report the detailed protocol of Agrobacterium-mediated VIGS system in cotton. Among the several viral VIGS vectors, the tobacco rattle virus (TRV) invades a wide range of hosts and is able to spread vigorously throughout the entire plant yet produce mild symptoms on the hosts5. To monitor the silencing efficiency, GrCLA1, a homolog gene of Arabidopsis Cloroplastos alterados 1 gene (AtCLA1) in cotton, has been cloned and inserted into the VIGS binary vector pYL156. CLA1 gene is involved in chloroplast development6, and previous studies have shown that loss-of-function of AtCLA1 resulted in an albino phenotype on true leaves7, providing an excellent visual marker for silencing efficiency. At approximately two weeks post Agrobacterium infiltration, the albino phenotype started to appear on the true leaves, with 100% silencing efficiency in all replicated experiments. The silencing of endogenous gene expression was also confirmed by RT-PCR analysis. Significantly, silencing could potently occur in all the cultivars we tested, including various commercially grown varieties in Texas. This rapid and efficient Agrobacterium-mediated VIGS assay provides a very powerful tool for rapid large-scale analysis of gene functions at genome-wide level in cotton.

We present the detailed protocol for Agrobacterium-mediated virus-induced gene silencing (VIGS) assay in cotton. The tobacco rattle virus (TRV)-derived VIGS vectors were deployed to induce RNA silencing of cotton GrCLA1, Cloroplastos alterados 1 gene. The albino phenotype caused by silencing GrCLA1 was observed at the seedling stage within 2 weeks after inoculation.

Cotton (Gossypium hirsutum) is one of the most important crops worldwide. Considerable efforts have been made on molecular breeding of new varieties.  The ...

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Given the ever expanding number of model plant species for which complete genome sequences are available and the abundance of bio-resources such as knockout mutants, wild accessions and advanced breeding populations, there is a rising burden for gene functional annotation. In this protocol, annotation of plant gene function using combined co-expression gene analysis, metabolomics and informatics is provided (Figure 1). This approach is based on the theory of using target genes of known function to allow the identification of non-annotated genes likely to be involved in a certain metabolic process, with the identification of target compounds via metabolomics. Strategies are put forward for applying this information on populations generated by both forward and reverse genetics approaches in spite of none of these are effortless. By corollary this approach can also be used as an approach to characterise unknown peaks representing new or specific secondary metabolites in the limited tissues, plant species or stress treatment, which is currently the important trial to understanding plant metabolism.

Combination of genomics, co-expression gene analysis and the identification of target compounds via metabolism give gene functional annotation.

Given the ever expanding number of model plant species for which complete genome sequences are available and the abundance of bio-resources such as ...

Agroinfiltration and PVX Agroinfection in Potato and Nicotiana benthamiana

Agroinfiltration and PVX agroinfection are two efficient transient expression assays for functional analysis of candidate genes in plants. The most commonly used agent for agroinfiltration is Agrobacterium tumefaciens, a pathogen of many dicot plant species. This implies that agroinfiltration can be applied to many plant species. Here, we present our protocols and expected results when applying these methods to the potato (Solanum tuberosum), its related wild tuber-bearing Solanum species (Solanum section Petota) and the model plant Nicotiana benthamiana. In addition to functional analysis of single genes, such as resistance (R) or avirulence (Avr) genes, the agroinfiltration assay is very suitable for recapitulating the R-AVR interactions associated with specific host pathogen interactions by simply delivering R and Avr transgenes into the same cell. However, some plant genotypes can raise nonspecific defense responses to Agrobacterium, as we observed for example for several potato genotypes. Compared to agroinfiltration, detection of AVR activity with PVX agroinfection is more sensitive, more high-throughput in functional screens and less sensitive to nonspecific defense responses to Agrobacterium. However, nonspecific defense to PVX can occur and there is a risk to miss responses due to virus-induced extreme resistance. Despite such limitations, in our experience, agroinfiltration and PVX agroinfection are both suitable and complementary assays that can be used simultaneously to confirm each other&#39;s results.

Agroinfiltration and PVX Agroinfection in Potato and Nicotiana benthamiana

Agroinfiltration and PVX agroinfection are routine functional assays for transient ectopic expression of genes in plants. These methods are efficient assays in effectoromics strategies (rapid resistance and avirulence gene discovery) and crucial to modern research in molecular plant pathology. They meet the demand for robust high-throughput functional analysis in plants.

Agroinfiltration and PVX agroinfection are two efficient transient expression assays for functional analysis of candidate genes in plants. The most ...

A New Approach for the Comparative Analysis of Multiprotein Complexes Based on 15N Metabolic Labeling and Quantitative Mass Spectrometry

The introduced protocol provides a tool for the analysis of multiprotein complexes in the thylakoid membrane, by revealing insights into complex composition under different conditions. In this protocol the approach is demonstrated by comparing the composition of the protein complex responsible for cyclic electron flow (CEF) in Chlamydomonas reinhardtii, isolated from genetically different strains. The procedure comprises the isolation of thylakoid membranes, followed by their separation into multiprotein complexes by sucrose density gradient centrifugation, SDS-PAGE, immunodetection and comparative, quantitative mass spectrometry (MS) based on differential metabolic labeling (14N/15N) of the analyzed strains. Detergent solubilized thylakoid membranes are loaded on sucrose density gradients at equal chlorophyll concentration. After ultracentrifugation, the gradients are separated into fractions, which are analyzed by mass-spectrometry based on equal volume. This approach allows the investigation of the composition within the gradient fractions and moreover to analyze the migration behavior of different proteins, especially focusing on ANR1, CAS, and PGRL1. Furthermore, this method is demonstrated by confirming the results with immunoblotting and additionally by supporting the findings from previous studies (the identification and PSI-dependent migration of proteins that were previously described to be part of the CEF-supercomplex such as PGRL1, FNR, and cyt f). Notably, this approach is applicable to address a broad range of questions for which this protocol can be adopted and e.g. used for comparative analyses of multiprotein complex composition isolated from distinct environmental conditions.

A New Approach for the Comparative Analysis of Multiprotein Complexes Based on 15N Metabolic Labeling and Quantitative Mass Spectrometry

The described comparative, quantitative proteomic approach aims at obtaining insights into the composition of multiprotein complexes&#160;under different conditions and is demonstrated by comparing genetically different strains. For quantitative analysis equal volumes of different fractions from a sucrose density gradient are mixed and analyzed by mass spectrometry.

The introduced protocol provides a tool for the analysis of multiprotein complexes in the thylakoid membrane, by revealing insights into complex ...

A Fast Air-dry Dropping Chromosome Preparation Method Suitable for FISH in Plants

Preparation of chromosome spreads is a prerequisite for the successful performance of fluorescence in situ hybridization (FISH). Preparation of high quality plant chromosome spreads is challenging due to the rigid cell wall. One of the approved methods for the preparation of plant chromosomes is a so-called drop preparation, also known as drop-spreading or air-drying technique. Here, we present a protocol for the fast preparation of mitotic chromosome spreads suitable for the FISH detection of single and high copy DNA probes. This method is an improved variant of the air-dry drop method performed under a relative humidity of 50%-55%. This protocol comprises a reduced number of washing steps making its application easy, efficient and reproducible. Obvious benefits of this approach are well-spread, undamaged and numerous metaphase chromosomes serving as a perfect prerequisite for successful FISH analysis. Using this protocol we obtained high-quality chromosome spreads and reproducible FISH results for Hordeum vulgare, H. bulbosum, H. marinum, H. murinum, H. pubiflorum and Secale cereale.

A protocol is described for the preparation of high-quality mitotic plant chromosome spreads by a fast air-dry dropping method suitable for the FISH detection of single and high copy DNA probes.

Preparation of chromosome spreads is a prerequisite for the successful performance of fluorescence in situ hybridization (FISH). Preparation of high ...

High-throughput CRISPR Vector Construction and Characterization of DNA Modifications by Generation of Tomato Hairy Roots

Targeted DNA mutations generated by vectors with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 technology have proven useful for functional genomics studies. While most cloning strategies are simple to perform, they generally use multiple steps and can require several days to generate the ultimate constructs. The method presented here is based on DNA assembly and can produce fully functional CRISPR vectors in a single cloning reaction. Vector construction can also be pooled, further increasing the efficiency and utility of the process. A modification of the method is used to create CRISPR vectors with multiple gene targets. CRISPR vectors are then transformed into tomato hairy roots to generate transgenic materials with targeted DNA modifications. Hairy roots are a useful system for testing vector functionality as they are technically simple to generate and amenable to large-scale production. The methods presented here will have wide application as they can be used to generate a variety of CRISPR vectors and be used in a wide range of plant species.

Using DNA assembly, multiple CRISPR vectors can be constructed in parallel in a single cloning reaction, making the construction of large numbers of CRISPR vectors a simple task. Tomato hairy roots are an excellent model system to validate CRISPR vectors and generate mutant materials.

Targeted DNA mutations generated by vectors with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 technology have proven useful for ...

Rapid Analysis of Circadian Phenotypes in Arabidopsis Protoplasts Transfected with a Luminescent Clock Reporter

The plant circadian clock allows the anticipation of daily changes to the environment. This anticipation aids the responses to temporally predictable biotic and abiotic stress. Conversely, disruption of circadian timekeeping severely compromises plant health and reduces agricultural crop yields. It is therefore imperative that we understand the intricate regulation of circadian rhythms in plants, including the factors that affect motion of the transcriptional clockwork itself.
Testing circadian defects in the model plant Arabidopsis thaliana (Arabidopsis) traditionally involves crossing specific mutant lines to a line rhythmically expressing firefly luciferase from a circadian clock gene promoter. This approach is laborious, time-consuming, and could be fruitless if a mutant has no circadian phenotype. The methodology presented here allows a rapid initial assessment of circadian phenotypes. Protoplasts derived from mutant and wild-type Arabidopsis are isolated, transfected with a rhythmically expressed luminescent reporter, and imaged under constant light conditions for 5 days. Luminescent traces will directly reveal whether the free-running period of mutant plants is different from wild-type plants. The advantage of the method is that any Arabidopsis line can efficiently be screened, without the need for generating a stably transgenic luminescent clock marker line in that mutant background.

The circadian clock regulates about a third of the Arabidopsis transcriptome, but the percentage of genes that feed back into timekeeping remains unknown. Here we visualize a method to rapidly assess circadian phenotypes in any mutant line of Arabidopsis using luminescent imaging of a circadian reporter transiently expressed in protoplasts.

The plant circadian clock allows the anticipation of daily changes to the environment. This anticipation aids the responses to temporally predictable ...