Year 2018, Volume 3, Issue 3
| Year : | 2018 |
| Volume : | 3 |
| Issue : | 3 |
| Authors : | Bihter AVSAR, Danial ESMAEILI ALIABADI |
| Title : | IDENTIFICATION OF IN SILICO MIRNAS IN FOUR PLANT SPECIES FROM FABACEAE FAMILY |
| Abstract : | 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. |
| For citation : | Avsar, B., Esmaeili Aliabadi, D., (2018). Identification of in silico mirnas in four plant species from fabaceae family. AGROFOR International Journal, Volume 3. Issue No. 3. pp. 122-130. DOI: 10.7251/AGRENG1803122A |
| Keywords : | Cicer arietinum, Medicago truncatula, Glycine max, Phaseolus vulgaris |
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ISSN 2490-3434 (Printed)
ISSN 2490-3442 (Online)
ISSN 2490-3442 (Online)
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