BackgroundMicroRNAs (miRNAs) are endogenous, noncoding, short RNAs directly involved in regulating gene expression at the post-transcriptional level. In spite of immense importance, limited information of P. vulgaris miRNAs and their expression patterns prompted us to identify new miRNAs in P. vulgaris by computational methods. Besides conventional approaches, we have used the simple sequence repeat (SSR) signatures as one of the prediction parameter. Moreover, for all other parameters including normalized Shannon entropy, normalized base pairing index and normalized base-pair distance, instead of taking a fixed cut-off value, we have used 99 % probability range derived from the available data.ResultsWe have identified 208 mature miRNAs in P. vulgaris belonging to 118 families, of which 201 are novel. 97 of the predicted miRNAs in P. vulgaris were validated with the sequencing data obtained from the small RNA sequencing of P. vulgaris. Randomly selected predicted miRNAs were also validated using qRT-PCR. A total of 1305 target sequences were identified for 130 predicted miRNAs. Using 80 % sequence identity cut-off, proteins coded by 563 targets were identified. The computational method developed in this study was also validated by predicting 229 miRNAs of A. thaliana and 462 miRNAs of G. max, of which 213 for A. thaliana and 397 for G. max are existing in miRBase 20.ConclusionsThere is no universal SSR that is conserved among all precursors of Viridiplantae, but conserved SSR exists within a miRNA family and is used as a signature in our prediction method. Prediction of known miRNAs of A. thaliana and G. max validates the accuracy of our method. Our findings will contribute to the present knowledge of miRNAs and their targets in P. vulgaris. This computational method can be applied to any species of Viridiplantae for the successful prediction of miRNAs and their targets.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-015-0516-3) contains supplementary material, which is available to authorized users.

No abstract

Phaseolus vulgaris is an economically important legume in tropical and subtropical regions of Asia, Africa, Latin-America and parts of USA and Europe. However, its production gets severely affected by mungbean yellow mosaic India virus (MYMIV). We aim to identify and characterize differentially expressed miRNAs during MYMIV-infection in P. vulgaris. A total of 422 miRNAs are identified of which 292 are expressed in both MYMIV-treated and mock-treated samples, 109 are expressed only in MYMIV-treated and 21 are expressed only in mock-treated samples. Selected up- and down-regulated miRNAs are validated by RT-qPCR. 3367 target ORFs are identified for 270 miRNAs. Selected targets are validated by 5' RLM-RACE. Differentially expressed miRNAs regulate transcription factors and are involved in improving stress tolerance to MYMIV. These findings will provide an insight into the role of miRNAs during MYMIV infection in P. vulgaris in particular and during any biotic stress conditions in Leguminosae family in general.

The fungus-farming ambrosia beetle Xylosandrus germanus (Blandford) uses a pouch-like structure (i.e., mycangium) to transport spores of its nutritional fungal mutualist. Our current study sought to identify reference genes necessary for future transcriptome analyses aimed at characterizing gene expression within the mycangium. Complementary DNA was synthesized using selected tissue types from laboratory-reared and field-collected X. germanus consisting of the whole body, head + thorax, deflated or inflated mycangium + scutellum, inflated mycangium, and thorax + abdomen. Quantitative reverse-transcription PCR reactions were performed using primers for 28S ribosomal RNA (28S rRNA), arginine kinase (AK), carbamoyl-phosphate synthetase 2-aspartate transcarbamylase-dihydroorotase (CAD), mitochondrial cytochrome oxidase 1 (CO1), and elongation factor-1α (EF1α). Reference gene stability was analyzed using GeNorm, NormFinder, BestKeeper, ΔCt, and a comprehensive final ranking by RefFinder. The gene CO1 was identified as the primary reference gene since it was generally ranked in first or second position among the tissue types containing the mycangium. Reference gene AK was identified as a secondary reference gene. In contrast, EF1α was generally ranked in the last or penultimate place. Identification of two stable reference genes will aid in normalizing the expression of target genes for subsequent gene expression studies of X. germanus’ mycangium.

No abstract