An improved microRNA annotation of the canine genome

The domestic dog, Canis familiaris, is a valuable model for studying human diseases. The publication of the latest Canine genome build and annotation, CanFam3.1 provides an opportunity to enhance our understanding of gene regulation across tissues in the dog model system. In this study, we used the latest dog genome assembly and small RNA sequencing data from 9 different dog tissues to predict novel miRNAs in the dog genome, as well as to annotate conserved miRNAs from the miRBase database that were missing from the current dog annotation. We used both miRCat and miRDeep2 algorithms to computationally predict miRNA loci. The resulting, putative hairpin sequences were analysed in order to discard false positives, based on predicted secondary structures and patterns of small RNA read alignments. Results were further divided into high and low confidence miRNAs, using the same criteria. We generated tissue specific expression profiles for the resulting set of 811 loci: 720 conserved miRNAs, (207 of which had not been previously annotated in the dog genome) and 91 novel miRNA loci. Comparative analyses revealed 8 putative homologues of some novel miRNA in ferret, and one in microbat. All miRNAs were also classified into the genic and intergenic categories, based on the Ensembl RefSeq gene annotation for CanFam3.1. This additionally allowed us to identify four previously undescribed MiRtrons among our total set of miRNAs. We additionally annotated piRNAs, using proTRAC on the same input data. We thus identified 263 putative clusters, most of which (211 clusters) were found to be expressed in testis. Our results represent an important improvement of the dog genome annotation, paving the way to further research on the evolution of gene regulation, as well as on the contribution of post-transcriptional regulation to pathological conditions

miRNAs Copy Number Variations Repertoire as Hallmark Indicator of Cancer Species Predisposition

Aging is one of the hallmarks of multiple human diseases, including cancer. We hypothesized that variations in the number of copies (CNVs) of specific genes may protect some long-living organisms theoretically more susceptible to tumorigenesis from the onset of cancer. Based on the statistical comparison of gene copy numbers within the genomes of both cancer-prone and -resistant species, we identified novel gene targets linked to tumor predisposition, such as CD52, SAT1 and SUMO. Moreover, considering their genome-wide copy number landscape, we discovered that microRNAs (miRNAs) are among the most significant gene families enriched for cancer progression and predisposition. Through bioinformatics analyses, we identified several alterations in miRNAs copy number patterns, involving miR-221, miR-222, miR-21, miR-372, miR-30b, miR-30d and miR-31, among others. Therefore, our analyses provide the first evidence that an altered miRNAs copy number signature can statistically discriminate species more susceptible to cancer from those that are tumor resistant, paving the way for further investigations.Aging is one of the hallmarks of multiple human diseases, including cancer. We hypothesized that variations in the number of copies (CNVs) of specific genes may protect some long-living organisms theoretically more susceptible to tumorigenesis from the onset of cancer. Based on the statistical comparison of gene copy numbers within the genomes of both cancer-prone and-resistant species, we identified novel gene targets linked to tumor predisposition, such as CD52, SAT1 and SUMO. Moreover, considering their genome-wide copy number landscape, we discovered that microRNAs (miRNAs) are among the most significant gene families enriched for cancer progression and predisposition. Through bioinformatics analyses, we identified several alterations in miRNAs copy number patterns, involving miR-221, miR-222, miR-21, miR-372, miR-30b, miR-30d and miR-31, among others. Therefore, our analyses provide the first evidence that an altered miRNAs copy number signature can statistically discriminate species more susceptible to cancer from those that are tumor resistant, paving the way for further investigations

The evolution of core proteins involved in microRNA biogenesis

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are a recently discovered class of non-coding RNAs (ncRNAs) which play important roles in eukaryotic gene regulation. miRNA biogenesis and activation is a complex process involving multiple protein catalysts and involves the large macromolecular RNAi Silencing Complex or RISC. While phylogenetic analyses of miRNA genes have been previously published, the evolution of miRNA biogenesis itself has been little studied. In order to better understand the origin of miRNA processing in animals and plants, we determined the phyletic occurrences and evolutionary relationships of four major miRNA pathway protein components; Dicer, Argonaute, RISC RNA-binding proteins, and Exportin-5.</p> <p>Results</p> <p>Phylogenetic analyses show that all four miRNA pathway proteins were derived from large multiple protein families. As an example, vertebrate and invertebrate Argonaute (Ago) proteins diverged from a larger family of PIWI/Argonaute proteins found throughout eukaryotes. Further gene duplications among vertebrates after the evolution of chordates from urochordates but prior to the emergence of fishes lead to the evolution of four Ago paralogues. Invertebrate RISC RNA-binding proteins R2D2 and Loquacious are related to other RNA-binding protein families such as Staufens as well as vertebrate-specific TAR (HIV trans-activator RNA) RNA-binding protein (TRBP) and protein kinase R-activating protein (PACT). Export of small RNAs from the nucleus, including miRNA, is facilitated by three closely related karyopherin-related nuclear transporters, Exportin-5, Exportin-1 and Exportin-T. While all three exportins have direct orthologues in deutrostomes, missing exportins in arthropods (Exportin-T) and nematodes (Exportin-5) are likely compensated by dual specificities of one of the other exportin paralogues.</p> <p>Conclusion</p> <p>Co-opting particular isoforms from large, diverse protein families seems to be a common theme in the evolution of miRNA biogenesis. Human miRNA biogenesis proteins have direct, orthologues in cold-blooded fishes and, in some cases, urochordates and deutrostomes. However, lineage specific expansions of Dicer in plants and invertebrates as well as Argonaute and RNA-binding proteins in vertebrates suggests that novel ncRNA regulatory mechanisms can evolve in relatively short evolutionary timeframes. The occurrence of multiple homologues to RNA-binding and Argonaute/PIWI proteins also suggests the possible existence of further pathways for additional types of ncRNAs.</p

miROrtho: computational survey of microRNA genes

MicroRNAs (miRNAs) are short, non-protein coding RNAs that direct the widespread phenomenon of post-transcriptional regulation of metazoan genes. The mature ∼22-nt long RNA molecules are processed from genome-encoded stem-loop structured precursor genes. Hundreds of such genes have been experimentally validated in vertebrate genomes, yet their discovery remains challenging, and substantially higher numbers have been estimated. The miROrtho database (http://cegg.unige.ch/mirortho) presents the results of a comprehensive computational survey of miRNA gene candidates across the majority of sequenced metazoan genomes. We designed and applied a three-tier analysis pipeline: (i) an SVM-based ab initio screen for potent hairpins, plus homologs of known miRNAs, (ii) an orthology delineation procedure and (iii) an SVM-based classifier of the ortholog multiple sequence alignments. The web interface provides direct access to putative miRNA annotations, ortholog multiple alignments, RNA secondary structure conservation, and sequence data. The miROrtho data are conceptually complementary to the miRBase catalog of experimentally verified miRNA sequences, providing a consistent comparative genomics perspective as well as identifying many novel miRNA genes with strong evolutionary support

MirZ: an integrated microRNA expression atlas and target prediction resource

MicroRNAs (miRNAs) are short RNAs that act as guides for the degradation and translational repression of protein-coding mRNAs. A large body of work showed that miRNAs are involved in the regulation of a broad range of biological functions, from development to cardiac and immune system function, to metabolism, to cancer. For most of the over 500 miRNAs that are encoded in the human genome the functions still remain to be uncovered. Identifying miRNAs whose expression changes between cell types or between normal and pathological conditions is an important step towards characterizing their function as is the prediction of mRNAs that could be targeted by these miRNAs. To provide the community the possibility of exploring interactively miRNA expression patterns and the candidate targets of miRNAs in an integrated environment, we developed the MirZ web server, which is accessible at www.mirz.unibas.ch. The server provides experimental and computational biologists with statistical analysis and data mining tools operating on up-to-date databases of sequencing-based miRNA expression profiles and of predicted miRNA target sites in species ranging from Caenorhabditis elegans to Homo sapiens

miRGen: a database for the study of animal microRNA genomic organization and function

miRGen is an integrated database of (i) positional relationships between animal miRNAs and genomic annotation sets and (ii) animal miRNA targets according to combinations of widely used target prediction programs. A major goal of the database is the study of the relationship between miRNA genomic organization and miRNA function. This is made possible by three integrated and user friendly interfaces. The Genomics interface allows the user to explore where whole-genome collections of miRNAs are located with respect to UCSC genome browser annotation sets such as Known Genes, Refseq Genes, Genscan predicted genes, CpG islands and pseudogenes. These miRNAs are connected through the Targets interface to their experimentally supported target genes from TarBase, as well as computationally predicted target genes from optimized intersections and unions of several widely used mammalian target prediction programs. Finally, the Clusters interface provides predicted miRNA clusters at any given inter-miRNA distance and provides specific functional information on the targets of miRNAs within each cluster. All of these unique features of miRGen are designed to facilitate investigations into miRNA genomic organization, co-transcription and targeting. miRGen can be freely accessed at

Algorithms for pre-microrna classification and a GPU program for whole genome comparison

MicroRNAs (miRNAs) are non-coding RNAs with approximately 22 nucleotides that are derived from precursor molecules. These precursor molecules or pre-miRNAs often fold into stem-loop hairpin structures. However, a large number of sequences with pre-miRNA-like hairpin can be found in genomes. It is a challenge to distinguish the real pre-miRNAs from other hairpin sequences with similar stem-loops (referred to as pseudo pre-miRNAs). The first part of this dissertation presents a new method, called MirID, for identifying and classifying microRNA precursors. MirID is comprised of three steps. Initially, a combinatorial feature mining algorithm is developed to identify suitable feature sets. Then, the feature sets are used to train support vector machines to obtain classification models, based on which classifier ensemble is constructed. Finally, an AdaBoost algorithm is adopted to further enhance the accuracy of the classifier ensemble. Experimental results on a variety of species demonstrate the good performance of the proposed approach, and its superiority over existing methods. In the second part of this dissertation, A GPU (Graphics Processing Unit) program is developed for whole genome comparison. The goal for the research is to identify the commonalities and differences of two genomes from closely related organisms, via multiple sequencing alignments by using a seed and extend technique to choose reliable subsets of exact or near exact matches, which are called anchors. A rigorous method named Smith-Waterman search is applied for the anchor seeking, but takes days and months to map millions of bases for mammalian genome sequences. With GPU programming, which is designed to run in parallel hundreds of short functions called threads, up to 100X speed up is achieved over similar CPU executions

Cloning, characterization and expression analysis of porcine microRNAs

Background: MicroRNAs (miRNAs) are small ~22-nt regulatory RNAs that can silence target genes, by blocking their protein production or degrading the mRNAs. Pig is an important animal in the agriculture industry because of its utility in the meat production. Besides, pig has tremendous biomedical importance as a model organism because of its closer proximity to humans than the mouse model. Several hundreds of miRNAs have been identified from mammals, humans, mice and rats, but little is known about the miRNA component in the pig genome. Here, we adopted an experimental approach to identify conserved and unique miRNAs and characterize their expression patterns in diverse tissues of pig.Results: By sequencing a small RNA library generated using pooled RNA from the pig heart, liver and thymus; we identified a total of 120 conserved miRNA homologs in pig. Expression analysis of conserved miRNAs in 14 different tissue types revealed heart-specific expression of miR-499 and miR-208 and liver-specific expression of miR-122. Additionally, miR-1 and miR-133 in the heart, miR-181a and miR-142-3p in the thymus, miR-194 in the liver, and miR-143 in the stomach showed the highest levels of expression. miR-22, miR-26b, miR-29c and miR-30c showed ubiquitous expression in diverse tissues. The expression patterns of pig-specific miRNAs also varied among the tissues examined.Conclusion: Identification of 120 miRNAs and determination of the spatial expression patterns of a sub-set of these in the pig is a valuable resource for molecular biologists, breeders, and biomedical investigators interested in post-transcriptional gene regulation in pig and in related mammals, including humans.Peer reviewedBiochemistry and Molecular BiologyAnimal Scienc

In silico mining of micro-RNAs from Spodoptera frugiperda (Smith) (Lepidoptera: Noctuidae)

MicroRNAs (miRNAs) are small, endogenously, non-coding genes that regulate protein production either by mRNA cleavage or by translational repression in eukaryotes and viruses. miRNAs plays a key role in biological processes including growth, development and physiology of an organism. In this study, we employed insilico approaches to identify the miRNAs from Spodoptera frugiperda, a major pest of small grain crops. A total of seven miRNAs were identified and characterized from 67,360 expressed sequence tags (ESTs) of S. frugiperda with: 1) mature and pre-miRNAs sizes vary from 19 to 25 ans 61 to 95 nucleotides respectively; 2) minimum free energy ranged from -31.70 to -21.00 kcal/mol; and 3) (A + U) content varied from 27 to 60. The functional annotation of these miRNAs were identified as regulation of transcription factors, catalytic activities and signal transduction pathways. Further studies of these miRNAs will help to carryout functional analyses, which promises more towards insect pest management free of insecticides and pesticides.Keywords: MicroRNAs, translational repression, Spodoptera frugiperda, expressed sequence tags, minimum free energy, insect pest managementAfrican Journal of Biotechnology, Vol. 13(1), pp. 32-43, 1 January, 201