BackgroundRoses (Rosa sp.), which belong to the family Rosaceae, are the most economically important ornamental plants—making up 30% of the floriculture market. However, given high demand for roses, rose breeding programs are limited in molecular resources which can greatly enhance and speed breeding efforts. A better understanding of important genes that contribute to important floral development and desired phenotypes will lead to improved rose cultivars. For this study, we analyzed rose miRNAs and the rose flower transcriptome in order to generate a database to expound upon current knowledge regarding regulation of important floral characteristics. A rose genetic database will enable comprehensive analysis of gene expression and regulation via miRNA among different Rosa cultivars.ResultsWe produced more than 0.5 million reads from expressed sequences, totalling more than 110 million bp. From these, we generated 35,657, 31,434, 34,725, and 39,722 flower unigenes from Rosa hybrid: ‘Vital’, ‘Maroussia’, and ‘Sympathy’ and Rosa rugosa Thunb. , respectively. The unigenes were assigned functional annotations, domains, metabolic pathways, Gene Ontology (GO) terms, Plant Ontology (PO) terms, and MIPS Functional Catalogue (FunCat) terms. Rose flower transcripts were compared with genes from whole genome sequences of Rosaceae members (apple, strawberry, and peach) and grape. We also produced approximately 40 million small RNA reads from flower tissue for Rosa, representing 267 unique miRNA tags. Among identified miRNAs, 25 of them were novel and 242 of them were conserved miRNAs. Statistical analyses of miRNA profiles revealed both shared and species-specific miRNAs, which presumably effect flower development and phenotypes.ConclusionsIn this study, we constructed a Rose miRNA and transcriptome database, and we analyzed the miRNAs and transcriptome generated from the flower tissues of four Rosa cultivars. The database provides a comprehensive genetic resource which can be used to better understand rose flower development and to identify candidate genes for important phenotypes.

Plants express resistance (R) genes to recognize invaders and prevent the spread of pathogens. To analyze nucleotide binding site, leucine-rich repeat (NB-LRR) genes, we constructed a fast pipeline to predict and classify the R gene analogs (RGAs) by applying in-house matrices. With predicted ~37,000 RGAs, we can directly compare RGA contents across entire plant lineages, from green algae to flowering plants. We focused on the highly divergent NBLRRs in land plants following the emergence of mosses. We identified entire loss of Toll/Interleukin-1 receptor, NB-LRR (TNL) in Poaceae family of monocots and interestingly from Mimulus guttatus (a dicot), which leads to the possibility of species-specific TNL loss in other sequenced flowering plants. Using RGA maps, we have elucidated a positive correlation between the cluster sizes of NB-LRRs and their numbers. The cluster members were observed to consist of the same class of NB-LRRs or their variants, which were probably generated from a single locus for an R gene. Our website (http://sol.kribb.re.kr/PRGA/), called plant resistance gene analog (PRGA), provides useful information, such as RGA annotations, tools for predicting RGAs, and analyzing domain profiles. Therefore, PRGA provides new insights into R-gene evolution and is useful in applying RGA as markers in breeding and or systematic studies.

Background: Cyanobacteriochromes (CBCRs), photoreceptors that sense red to near-UV light, were not previously reported in the cyanobacterium Microcoleus. Results: The Microcoleus genome encodes seven CBCR proteins covalently attached to phycocyanobilin or phycoviolobilin. Conclusion: Near-UV and violet CBCRs are enriched in Microcoleus, whereas red-and green-sensitive CBCRs are absent. Significance: This is the first report of CBCRs in the Microcoleus genome.

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