RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping. We highlight the challenges associated with each step. We discuss the analysis of small RNAs and the integration of RNA-seq with other functional genomics techniques. Finally, we discuss the outlook for novel technologies that are changing the state of the art in transcriptomics.

/pdf/a-survey-of-best-practices-for-rna-seq-data-analysis-2yy2ysk9lf.pdf

A survey of best practices for RNA-seq data analysis

https://www.gene-quantification.de/dweep-et-al-mirwalk-2011.pdf

miRWalk - Database: Prediction of possible miRNA binding sites by walking the genes of three genomes

MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased ∼1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.

/pdf/mirtarbase-update-2018-a-resource-for-experimentally-4eyy28pidi.pdf

miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions.

/pdf/mirwalk2-0-a-comprehensive-atlas-of-microrna-target-3rk7o1g3l9.pdf

miRWalk2.0: a comprehensive atlas of microRNA-target interactions

MicroRNAs (miRNAs) are a class of posttranscriptional regulators that have recently introduced an additional level of intricacy to our understanding of gene regulation. There are currently over 10,000 miRNAs that have been identified in a range of species including metazoa, mycetozoa, viridiplantae, and viruses, of which 940, to date, are found in humans. It is estimated that more than 60% of human protein-coding genes harbor miRNA target sites in their 3′ untranslated region and, thus, are potentially regulated by these molecules in health and disease. This review will first briefly describe the discovery, structure, and mode of function of miRNAs in mammalian cells, before elaborating on their roles and significance during development and pathogenesis in the various mammalian organs, while attempting to reconcile their functions with our existing knowledge of their targets. Finally, we will summarize some of the advances made in utilizing miRNAs in therapeutics.

/pdf/micrornas-in-development-and-disease-472gt45lvo.pdf

MicroRNAs in development and disease.

Background: Deep-sequencing has enabled the identification of large numbers of miRNAs and siRNAs, making the high-throughput target identification a main limiting factor in defining their function. In plants, several tools have been developed to predict targets, majority of them being trained on Arabidopsis datasets. An extensive and systematic evaluation has not been made for their suitability for predicting targets in species other than Arabidopsis. Nor, these have not been evaluated for their suitability for high-throughput target prediction at genome level. Results: We evaluated the performance of 11 computational tools in identifying genome-wide targets in Arabidopsis and other plants with procedures that optimized score-cutoffs for estimating targets. Targetfinder was most efficient [89% ‘precision’ (accuracy of prediction), 97% ‘recall’ (sensitivity)] in predicting ‘true-positive’ targets in Arabidopsis miRNA-mRNA interactions. In contrast, only 46% of true positive interactions from non-Arabidopsis species were detected, indicating low ‘recall’ values. Score optimizations increased the ‘recall’ to only 70% (corresponding ‘precision’: 65%) for datasets of true miRNA-mRNA interactions in species other than Arabidopsis. Combining the results of Targetfinder and psRNATarget delivers high true positive coverage, whereas the intersection of psRNATarget and Tapirhybrid outputs deliver highly ‘precise’ predictions. The large number of ‘false negative’ predictions delivered from non-Arabidopsis datasets by all the available tools indicate the diversity in miRNAs-mRNA interaction features between Arabidopsis and other species. A subset of miRNA-mRNA interactions differed significantly for features in seed regions as well as the total number of matches/mismatches. Conclusion: Although, many plant miRNA target prediction tools may be optimized to predict targets with high specificity in Arabidopsis, such optimized thresholds may not be suitable for many targets in non-Arabidopsis species. More importantly, non-conventional features of miRNA-mRNA interaction may exist in plants indicating alternate mode of miRNA target recognition. Incorporation of these divergent features would enable next-generation of algorithms to better identify target interactions.

/pdf/a-comparison-of-performance-of-plant-mirna-target-prediction-3sd2cin73x.pdf

A comparison of performance of plant miRNA target prediction tools and the characterization of features for genome-wide target prediction

MicroRNAs (miRNAs) play key roles in mammalian gene expression and several cellular processes, including differentiation, development, apoptosis and cancer pathomechanisms. Recently the biological importance of primary cilia has been recognized in a number of human genetic diseases. Numerous disorders are related to cilia dysfunction, including polycystic kidney disease (PKD). Although involvement of certain genes and transcriptional networks in PKD development has been shown, not much is known how they are regulated molecularly. Given the emerging role of miRNAs in gene expression, we explored the possibilities of miRNA-based regulations in PKD. Here, we analyzed the simultaneous expression changes of miRNAs and mRNAs by microarrays. 935 genes, classified into 24 functional categories, were differentially regulated between PKD and control animals. In parallel, 30 miRNAs were differentially regulated in PKD rats: our results suggest that several miRNAs might be involved in regulating genetic switches in PKD. Furthermore, we describe some newly detected miRNAs, miR-31 and miR-217, in the kidney which have not been reported previously. We determine functionally related gene sets, or pathways to reveal the functional correlation between differentially expressed mRNAs and miRNAs. We find that the functional patterns of predicted miRNA targets and differentially expressed mRNAs are similar. Our results suggest an important role of miRNAs in specific pathways underlying PKD.

/pdf/microarray-based-approach-identifies-micrornas-and-their-3b9tp9dsmd.pdf

Microarray-based approach identifies microRNAs and their target functional patterns in polycystic kidney disease.

Autosomal polycystic kidney disease (ADPKD) is a frequent monogenic renal disease, characterised by fluid-filled cysts that are thought to result from multiple deregulated pathways such as cell proliferation and apoptosis. MicroRNAs (miRNAs) are small non-coding RNAs that regulate the expression of many genes associated with such biological processes and human pathologies. To explore the possible regulatory role of miRNAs in PKD, the PKD/Mhm (cy/+) rat, served as a model to study human ADPKD. A parallel microarray-based approach was conducted to profile the expression changes of mRNAs and miRNAs in PKD/Mhm rats. 1,573 up- and 1,760 down-regulated genes were differentially expressed in PKD/Mhm. These genes are associated with 17 pathways (such as focal adhesion, cell cycle, ECM-receptor interaction, DNA replication and metabolic pathways) and 47 (e.g., cell proliferation, Wnt and Tgfβ signaling) Gene Ontologies. Furthermore, we found the similar expression patterns of deregulated genes between PKD/Mhm (cy/+) rat and human ADPKD, PKD1L3/L3, PKD1−/−, Hnf1α-deficient, and Glis2lacZ/lacZ models. Additionally, several differentially regulated genes were noted to be target hubs for miRNAs. We also obtained 8 significantly up-regulated miRNAs (rno-miR-199a-5p, −214, −146b, −21, −34a, −132, −31 and −503) in diseased kidneys of PKD/Mhm rats. Additionally, the binding site overrepresentation and pathway enrichment analyses were accomplished on the putative targets of these 8 miRNAs. 7 out of these 8 miRNAs and their possible interactions have not been previously described in ADPKD. We have shown a strong overlap of functional patterns (pathways) between deregulated miRNAs and mRNAs in the PKD/Mhm (cy/+) rat model. Our findings suggest that several miRNAs may be associated in regulating pathways in ADPKD. We further describe novel miRNAs and their possible targets in ADPKD, which will open new avenues to understand the pathogenesis of human ADPKD. Furthermore they could serve as a useful resource for anti-fibrotic therapeutics.

/pdf/parallel-analysis-of-mrna-and-microrna-microarray-profiles-4jlndqpcxb.pdf

Parallel analysis of mRNA and microRNA microarray profiles to explore functional regulatory patterns in polycystic kidney disease: using PKD/Mhm rat model.

In Nicotiana attenuata, specific RNA-directed RNA polymerase (RdR1) and the Dicer-like (DCL3 and DCL4) proteins are recruited during herbivore attack to mediate the regulation of defense responses. However, the identity and role(s) of Argonautes (AGOs) involved in herbivory remain unknown. Of the 11 AGOs in the N. attenuata genome, we silenced the expression of 10. Plants silenced in NaAGO8 expression grew normally but were highly susceptible to herbivore attack. Larvae of Manduca sexta grew faster when consuming inverted-repeat stable transformants (irAGO8) plants but did not differ from the wild type when consuming plants silenced in AGO1 (a, b, and c), AGO2, AGO4 (a and b), AGO7, or AGO10 expression. irAGO8 plants were significantly compromised in herbivore-induced levels of defense metabolites such as nicotine, phenolamides, and diterpenoid glycosides. Time-course analyses revealed extensively altered microRNA profiles and the reduced accumulation of MYB8 transcripts and of the associated genes of the phenolamide and phenylpropanoid pathways as well as the nicotine biosynthetic pathway. A possible AGO8-modulated microRNA-messenger RNA target network was inferred. Furthermore, comparative analysis of domains revealed the diversity of AGO conformations, particularly in the small RNA-binding pocket, which may influence substrate recognition/binding and functional specificity. We infer that AGO8 plays a central role in the induction of direct defenses by modulating several regulatory nodes in the defense signaling network during herbivore response. Thus, our study identifies the effector AGO of the herbivore-induced small RNA machinery, which in N. attenuata now comprises RdR1, DCL3/4, and AGO8.

Priyanka Pandey

Papers

miRWalk - Database: Prediction of possible miRNA binding sites by walking the genes of three genomes

A comparison of performance of plant miRNA target prediction tools and the characterization of features for genome-wide target prediction

Microarray-based approach identifies microRNAs and their target functional patterns in polycystic kidney disease.

Parallel analysis of mRNA and microRNA microarray profiles to explore functional regulatory patterns in polycystic kidney disease: using PKD/Mhm rat model.

Argonaute 8 (AGO8) Mediates the Elicitation of Direct Defenses against Herbivory.