BackgroundDeep-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.ResultsWe 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.ConclusionAlthough, 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.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-348) contains supplementary material, which is available to authorized users.
Strigolactones (SLs) are a relatively recent addition to the list of plant hormones that control different aspects of plant development. SL signalling is perceived by an α/β hydrolase, DWARF 14 (D14). A close homolog of D14, KARRIKIN INSENSTIVE2 (KAI2), is involved in perception of an uncharacterized molecule called karrikin (KAR). Recent studies in Arabidopsis identified the SUPPRESSOR OF MAX2 1 (SMAX1) and SMAX1-LIKE 7 (SMXL7) to be potential SCF-MAX2 complex-mediated proteasome targets of KAI2 and D14, respectively. Genetic studies on SMXL7 and SMAX1 demonstrated distinct developmental roles for each, but very little is known about these repressors in terms of their sequence features. In this study, we performed an extensive comparative analysis of SMXLs and determined their phylogenetic and evolutionary history in the plant lineage. Our results show that SMXL family members can be sub-divided into four distinct phylogenetic clades/classes, with an ancient SMAX1. Further, we identified the clade-specific motifs that have evolved and that might act as determinants of SL-KAR signalling specificity. These specificities resulted from functional diversities among the clades. Our results suggest that a gradual co-evolution of SMXL members with their upstream receptors D14/KAI2 provided an increased specificity to both the SL perception and response in land plants.
Protein structural families are groups of homologous proteins defined by the organization of secondary structure elements (SSEs). Nowadays, many families contain vast numbers of structures, and the SSEs can help to orient within them. Communities around specific protein families have even developed specialized SSE annotations, always assigning the same name to the equivalent SSEs in homologous proteins. A detailed analysis of the groups of equivalent SSEs provides an overview of the studied family and enriches the analysis of any particular protein at hand. We developed a workflow for the analysis of the secondary structure anatomy of a protein family. We applied this analysis to the model family of cytochromes P450 (CYPs)—a family of important biotransformation enzymes with a community-wide used SSE annotation. We report the occurrence, typical length and amino acid sequence for the equivalent SSE groups, the conservation/variability of these properties and relationship to the substrate recognition sites. We also suggest a generic residue numbering scheme for the CYP family. Comparing the bacterial and eukaryotic part of the family highlights the significant differences and reveals a well-known anomalous group of bacterial CYPs with some typically eukaryotic features. Our workflow for SSE annotation for CYP and other families can be freely used at address https://sestra.ncbr.muni.cz.
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