Identification of in silico mirnas in four plant species from fabaceae family

Plant microRNAs (miRNAs) are small non-coding RNAs, about 21-24 nucleotides, which have critical regulatory roles on growth, development, metabolic and defense processes. Their identification, together with their targets, have gained importance in exploring their parts on functional context, providing a better understanding of their regulatory roles in critical biological processes. With the advent of next-generation sequencing technologies and newly developed bioinformatics tools, the identification of microRNA studies by computational methods has been increasing. In the presented study, we identified some putative miRNAs for Cicer arietinum, Glycine max, Medicago truncatula and Phaseolus vulgaris genomes. We also provided the similarity between those organisms regarding common/different miRNAs availability throughout their genomes. According to the data, the highest similarity was found between Glycine max and Phaseolus vulgaris. We also investigated the potential targets of putatively identified miRNAs for each organism. We analyzed which miRNA families were expressed in silico. We also showed the representation (copy number of genes) profile of predicted putative miRNAs for each organism. Since most of the food products and animal feeds consist of Fabaceae family members as it is mentioned above, these findings might help to elucidate their metabolic and regulatory pathways to use them efficiently in biotechnological applications and breeding programs

Parallelized neural network system for solving Euclidean traveling salesman problem

We investigate a parallelized divide-and-conquer approach based on a self-organizing map (SOM) in order to solve the Euclidean Traveling Salesman Problem (TSP). Our approach consists of dividing cities into municipalities, evolving the most appropriate solution from each municipality so as to find the best overall solution and, finally, joining neighborhood municipalities by using a blend operator to identify the final solution. We evaluate the performance of parallelized approach over standard TSP test problems (TSPLIB) to show that our approach gives a better answer in terms of quality and time rather than the sequential evolutionary SOM

Evolutionary insights into micrornas of kiwifruit actinidia Chinensis and its close relatives

The advent of next-generation sequencing technologies and newly developed bioinformatics tools have provided us complete sequence information of organisms. Plant microRNAs (miRNAs), small non-coding RNAs about 21-24 nucleotides, and their regulatory roles in biological processes have been uncovered since the identification of the first miRNA. MicroRNA biogenesis and modes of actions have also been elucidated in previous studies. In the presented study, we identified putative microRNAs from Actinidia chinensis, Arabidopsis thaliana, Solanum lycopersicum, Solanum tuberosum and Vitis vinifera to compare their miRNA repertoire. According to the results, the highest synteny was found between V.vinifera-A.chinensis and the least synteny was found between A.thalianaA.chinensis. The highest number of putative miRNAs were identified from A.thaliana whereas the least amount of putative miRNAs were identified from V.vinifera. This may be depended on the size of the genomes. We also analyzed the targets of putatively identified miRNAs for each organism. Expectedly, the target pathways of the predicted putative miRNAs were similar between the closest organisms. Expressed miRNA families and copy number of miRNA genes were compared between all organisms. In A.thaliana, the number of expressed putative miRNAs are more than the other organisms. For all the organisms, different miRNA families had the high copy number of genes. Therefore, highly represented miRNA families on each genome may have specific functional roles. The findings in this study will help the research community to identify the roles of miRNA players on critical biological pathways

In silico analysis of MicroRNAs in spinacia oleracea genome and transcriptome

Plant microRNAs (miRNAs) are small non-coding RNAs, about 21-24 nucleotides, which have important regulatory roles in growth, development, metabolic and defense processes. These critical elements regulate pathways either by inducing translational repression or messenger RNA (mRNA) decay. With the advent of the next-generation sequencing technologies and newly developed bioinformatics tools, the identification of microRNA studies by computational methods have been increased. Thus, the sequencing information provides us information for mining some known and unknown miRNAs in plants. In this study, we predict 34 putative miRNAs from Spinacia oleracea genome and two putative miRNA families from spinach transcriptome by using homology-based conservation method. RepeatMasker program is utilized to mask and eliminate five miRNA families out of 34 putative miRNA families from spinach genome. Finally, we analyze the targets of putatively identified miRNAs and their representation of genes (the copy number of each miRNA) throughout the genome

Identification of microRNA elements from genomic data of European hazelnut (Corylus avellana L.) and its close relatives

Plant microRNAs (miRNAs) are small and non-coding endogenous RNAs which have numerous regulatory roles in cells. These critical players regulate pathways either by inducing translational repression or messenger RNA (mRNA) decay. Newly developed bioinformatics tools and computational methods have been increased to identify miRNAs with their targets inside the genome. In this study, we predicted and identified 57 putative miRNAs through Corylus avellana (C. avellana) genomic data in silico. We also predicted some other putative miRNAs from Arabidopsis thaliana (A. thaliana), Ricinus communis (R. communis), Populus trichocarpa (P. trichocarpa) and Vitis vinifera (V. vinifera) to compare with the C. avellana organism since previous studies have indicated high similarities between these genomes and proteome atlases. The miRBase 21 was used as a reference dataset and the putative miRNAs were identified for the genome of each organism. We used homology conserved method to identify putative miRNAs. Based on our findings, C. avellana miRNA content was found to be highly similar to V. vinifera, R. communis and P. trichocarpa. Also, we found the targets of these hazelnut putative miRNAs and their possible functions inside the cell. One of our major discoveries is that miR171 families are highly represented (the copy number of miRNA) in the hazelnut genome to provide clues for microRNA domestication. The miR396, miR482, and miR2118 families were found as in silico expressed putative miRNAs by using computational methods. All these findings may help us better understanding the miRNA repertoire of the hazelnut organism and provide valuable insight about the regulatory roles of predicted putative miRNAs which are shared with other organisms (A. thaliana, R. communis, P. trichocarpa, V. vinifera) for further studies

In silico identification of MicroRNAs in 13 medicinal plants

OBJECTIVES: MicroRNAs are endogenous, non-coding small RNAs and they play important roles in plant regulatory pathways, development, stress tolerance and growth. With the advent of next-generation sequencing technologies, the microRNA identification studies by computational methods have been increased and have become effective. In this study, we predicted microRNA repertoires from 13 medicinal plants by using their transcriptome atlas. MATERIALS -METHODS: The transcriptome sequences of 13 medicinal plants were retrieved and the miRNA identification was conducted based on homology conservation method. Phylogenetic tree was constructed to show the level of similarity /dissimilarity between 13 medicinal plants (Atropa belladonna, Camptotheca acuminate, Cannabis sativa, Digitalis purpurea, Dioscorea villosa, Echinacea purpurea, Ginkgo biloba, Hoodia gordonii, Hypericum perforatum , Panax quinquefolius , Rauvolfia serpentina, Rosmarinus officinalis , Valeriana officinalis ) by Minitab statistical software. The transcriptome of Arabidopsis thaliana organism was used as a model organism. Target annotations of predicted putative microRNAs were performed by psRNA target and Blast2Go software. RESULTS: As a total number, 168 putative miRNAs were identified. The highest number of microRNAs were found in Camptotheca acuminate (28 miRNA families) transcriptome whereas Atropa belladonna had the lowest amount of putative miRNAs (three miRNA families) in its transcriptome. Digitalis purpurea and Rosmarinus officinalis showed the highest similarities. Targets of putative miRNAs in biological processes and molecular functions revealed us different profiles in different organisms. CONCLUSIONS: Since medicinal plants have some important therapeutic properties, these findings might help to elucidate metabolic and regulatory pathways in medicinal plants to use them efficiently in biotechnological and pharmacological applications

Putative microRNA analysis of the kiwifruit actinidia chinensis through genomic data

MicroRNAs are important regulators in the cells that are well defined in various roles. With the advent of new generation sequencing technologies, identification of miRNAs studies increase rapidly. In here, we identified 58 putative miRNAs through kiwifruit genome by using in silico methods. The computational analysis was done through genome and transcriptome data of Chinese kiwifruit cultivar ‘Hongyang’ which has important properties including the high content of vitamin C, carotenoids and flavonoids. Since kiwifruit shares some portion of its genes with diverse plant families, this study may contribute to the further biotechnological studies in other close relatives