BackgroundCommon bean (Phaseolus vulgaris) is grown throughout the world and comprises roughly 50% of the grain legumes consumed worldwide. Despite this, genetic resources for common beans have been lacking. Next generation sequencing, has facilitated our investigation of the gene expression profiles associated with biologically important traits in common bean. An increased understanding of gene expression in common bean will improve our understanding of gene expression patterns in other legume species.ResultsCombining recently developed genomic resources for Phaseolus vulgaris, including predicted gene calls, with RNA-Seq technology, we measured the gene expression patterns from 24 samples collected from seven tissues at developmentally important stages and from three nitrogen treatments. Gene expression patterns throughout the plant were analyzed to better understand changes due to nodulation, seed development, and nitrogen utilization. We have identified 11,010 genes differentially expressed with a fold change ≥ 2 and a P-value < 0.05 between different tissues at the same time point, 15,752 genes differentially expressed within a tissue due to changes in development, and 2,315 genes expressed only in a single tissue. These analyses identified 2,970 genes with expression patterns that appear to be directly dependent on the source of available nitrogen. Finally, we have assembled this data in a publicly available database, The Phaseolus vulgaris Gene Expression Atlas (Pv GEA), http://plantgrn.noble.org/PvGEA/ . Using the website, researchers can query gene expression profiles of their gene of interest, search for genes expressed in different tissues, or download the dataset in a tabular form.ConclusionsThese data provide the basis for a gene expression atlas, which will facilitate functional genomic studies in common bean. Analysis of this dataset has identified genes important in regulating seed composition and has increased our understanding of nodulation and impact of the nitrogen source on assimilation and distribution throughout the plant.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-866) contains supplementary material, which is available to authorized users.

Characterization of Human Endogenous Retrovirus (HERV) expression within the transcriptomic landscape using RNA-seq is complicated by uncertainty in fragment assignment because of sequence similarity. We present Telescope, a computational software tool that provides accurate estimation of transposable element expression (retrotranscriptome) resolved to specific genomic locations. Telescope directly addresses uncertainty in fragment assignment by reassigning ambiguously mapped fragments to the most probable source transcript as determined within a Bayesian statistical model. We demonstrate the utility of our approach through single locus analysis of HERV expression in 13 ENCODE cell types. When examined at this resolution, we find that the magnitude and breadth of the retrotranscriptome can be vastly different among cell types. Furthermore, our approach is robust to differences in sequencing technology and demonstrates that the retrotranscriptome has potential to be used for cell type identification. We compared our tool with other approaches for quantifying transposable element (TE) expression, and found that Telescope has the greatest resolution, as it estimates expression at specific TE insertions rather than at the TE subfamily level. Telescope performs highly accurate quantification of the retrotranscriptomic landscape in RNA-seq experiments, revealing a differential complexity in the transposable element biology of complex systems not previously observed. Telescope is available at https://github.com/mlbendall/telescope.

Micro-RNAs are recognized as important posttranscriptional regulators in plants. The relevance of micro-RNAs as regulators of the legume-rhizobia nitrogen-fixing symbiosis is emerging. The objective of this work was to functionally characterize the role of micro-RNA172 (miR172) and its conserved target APETALA2 (AP2) transcription factor in the common bean (Phaseolus vulgaris)-Rhizobium etli symbiosis. Our expression analysis revealed that mature miR172c increased upon rhizobial infection and continued increasing during nodule development, reaching its maximum in mature nodules and decaying in senescent nodules. The expression of AP2-1 target showed a negative correlation with miR172c expression. A drastic decrease in miR172c and high AP2-1 mRNA levels were observed in ineffective nodules. Phenotypic analysis of composite bean plants with transgenic roots overexpressing miR172c or a mutated AP2-1 insensitive to miR172c cleavage demonstrated the pivotal regulatory role of the miR172 node in the common beanrhizobia symbiosis. Increased miR172 resulted in improved root growth, increased rhizobial infection, increased expression of early nodulation and autoregulation of nodulation genes, and improved nodulation and nitrogen fixation. In addition, these plants showed decreased sensitivity to nitrate inhibition of nodulation. Through transcriptome analysis, we identified 114 common bean genes that coexpressed with AP2-1 and proposed these as being targets for transcriptional activation by AP2-1. Several of these genes are related to nodule senescence, and we propose that they have to be silenced, through miR172c-induced AP2-1 cleavage, in active mature nodules. Our work sets the basis for exploring the miR172-mediated improvement of symbiotic nitrogen fixation in common bean, the most important grain legume for human consumption.

BackgroundMicroRNAs (miRNAs) are endogenously encoded small RNAs that post-transcriptionally regulate gene expression. MiRNAs play essential roles in almost all plant biological processes. Currently, few miRNAs have been identified in the model food legume Phaseolus vulgaris (common bean). Recent advances in next generation sequencing technologies have allowed the identification of conserved and novel miRNAs in many plant species. Here, we used Illumina's sequencing by synthesis (SBS) technology to identify and characterize the miRNA population of Phaseolus vulgaris.ResultsSmall RNA libraries were generated from roots, flowers, leaves, and seedlings of P. vulgaris. Based on similarity to previously reported plant miRNAs,114 miRNAs belonging to 33 conserved miRNA families were identified. Stem-loop precursors and target gene sequences for several conserved common bean miRNAs were determined from publicly available databases. Less conserved miRNA families and species-specific common bean miRNA isoforms were also characterized. Moreover, novel miRNAs based on the small RNAs were found and their potential precursors were predicted. In addition, new target candidates for novel and conserved miRNAs were proposed. Finally, we studied organ-specific miRNA family expression levels through miRNA read frequencies.ConclusionsThis work represents the first massive-scale RNA sequencing study performed in Phaseolus vulgaris to identify and characterize its miRNA population. It significantly increases the number of miRNAs, precursors, and targets identified in this agronomically important species. The miRNA expression analysis provides a foundation for understanding common bean miRNA organ-specific expression patterns. The present study offers an expanded picture of P. vulgaris miRNAs in relation to those of other legumes.