Project description:Arthrobacter chlorophenolicus A6 is a 4-chlorophenol degrading soil bacterium with high phyllosphere colonization capacity. Till now the genetic basis for the phyllosphere competency of Arthrobacter or other pollutant-degrading bacteria is uncertain. We investigated global gene expression profile of A. chlorophenolicus grown in the phyllosphere of common bean (Phaseolus vulgaris) compared to growth on agar surfaces. We designed transcriptome arrays and investigated which genes had different transcript levels in the phyllosphere of common bean (Phaseolus vulgaris) as compared to agar surfaces. Since water availability is considered an important factor in phyllosphere survival and activity, we included both high and low relative humidity treatments for the phyllosphere-grown cells. In addition, we determined the expression profile under pollutant exposure by the inclusion of two agar surface treatments, i.e. with and without 4-chlorophenol.
Project description:Arthrobacter chlorophenolicus A6 is a 4-chlorophenol degrading soil bacterium with high phyllosphere colonization capacity. Till now the genetic basis for the phyllosphere competency of Arthrobacter or other pollutant-degrading bacteria is uncertain. We investigated global gene expression profile of A. chlorophenolicus grown in the phyllosphere of common bean (Phaseolus vulgaris) compared to growth on agar surfaces.
Project description:Some legume plants can establish a nitrogen-fixing symbiosis with rhizobia. Compatibilty between rhizobia and legumes is determined at species-specific level, but there are variations on the efficiency of the process determined by the capacity of the plant to select specific strains that are better partners in terms of the biological outcome. In this work we used a model system based in the coevolution of two genetic pools of common bean (Phaseolus vulgaris) with strains of R. etli that establish a more efficient interaction to study the transcriptional changes occurring in roots at an early time of the interaction.
Project description:The pod is the main edible part of Phaseolus vulgaris L. (common bean). The commercial use of the pods is mainly affected by their color. Consumers seem to prefer golden pods. However, planters suffer economic losses because of pod color instability. The aim of the present study was to identify the gene responsible for the golden pod trait in the common bean. ‘A18-1’ (a golden bean line) and ‘Renaya’ (a green bean line) were chosen as the experimental materials. Genetic analysis indicated that a single recessive gene, pv-ye, controls the golden pod trait. A candidate region of 4.24-Mb was mapped to chromosome A02 using bulked-segregant analysis coupled to whole genome sequencing. In this region, linkage analysis in an F2 population localized the pv-ye gene to an interval of 182.9-kb between the simple sequence repeat markers SSR77 and SSR93. This region comprised 16 genes in this region, comprising 12 annotated genes from the P. vulgaris database, and 4 functionally unknown genes. Combined with transcriptome sequencing, we identified Phvul.002G006200 as the potential candidate gene for pv-ye. Sequencing of Phvul.002G006200 identified a single nucleotide polymorphism (SNP) in pv-ye. This SNP is located in the coding region and is responsible for substituting a glutamic acid with an glutamine at position 416 of the pv-ye protein (E416Q). A pair of primers covering the SNP was designed and the fragment was sequenced to screen 316 F2 plants with the ‘A18-1’ phenotype, based on the different site. Our findings showed that the among the 316 mapped individuals, the SNP cosegregated with the ‘A18-1’ phenotype. The findings presented here could form the basis to reveal the mechanism of the golden pod trait in the common bean at the molecular level.
Project description:Background: MiRNAs and phasiRNAs are negative regulators of gene expression. These small RNAs have been extensively studied in plant model species but only 10 mature microRNAs are present in miRBase version 21 and no phasiRNAs have been identified for the legume model Phaseolus vulgaris. Thanks to the recent availability of the first version of the common bean genome, degradome data and small RNA libraries, we are able to present here a catalog of the microRNAs and phasiRNAs of this organism and, particularly, new protagonists of the symbiotic nodulation events. Results: We identified a set of 185 mature miRNAs, including 121 previously unpublished sequences, encoded by 307 precursors and distributed in 98 families. Degradome data allowed us to identify a total of 181 targets for these miRNAs. We reveal two regulatory networks involving conserved miRNAs, known to play crucial roles in the well-establishment of nodules, and novel miRNAs specific of the common bean suggesting a specific action of these sequences. In parallel, we identified 125 loci that potentially produce phased small RNAs and 47 of them present all the characteristics to be triggered by a total of 31 miRNAs, including 14 new miRNAs identified in this study. Conclusions: We provide here a set of new small RNAs, which contribute to the broader scene of the sRNAome of Phaseolus vulgaris. Thanks to the identification of the miRNA targets from degradome analysis and the construction of regulatory networks between the mature microRNAs, we draw up here the probable functional regulation associated with the sRNAome and particularly in N2-fixing symbiotic nodules. Degradome sequencing from Phaseolus vulgaris seedling
Project description:Background: MiRNAs and phasiRNAs are negative regulators of gene expression. These small RNAs have been extensively studied in plant model species but only 10 mature microRNAs are present in miRBase version 21 and no phasiRNAs have been identified for the legume model Phaseolus vulgaris. Thanks to the recent availability of the first version of the common bean genome, degradome data and small RNA libraries, we are able to present here a catalog of the microRNAs and phasiRNAs of this organism and, particularly, new protagonists of the symbiotic nodulation events. Results: We identified a set of 185 mature miRNAs, including 121 previously unpublished sequences, encoded by 307 precursors and distributed in 98 families. Degradome data allowed us to identify a total of 181 targets for these miRNAs. We reveal two regulatory networks involving conserved miRNAs, known to play crucial roles in the well-establishment of nodules, and novel miRNAs specific of the common bean suggesting a specific action of these sequences. In parallel, we identified 125 loci that potentially produce phased small RNAs and 47 of them present all the characteristics to be triggered by a total of 31 miRNAs, including 14 new miRNAs identified in this study. Conclusions: We provide here a set of new small RNAs, which contribute to the broader scene of the sRNAome of Phaseolus vulgaris. Thanks to the identification of the miRNA targets from degradome analysis and the construction of regulatory networks between the mature microRNAs, we draw up here the probable functional regulation associated with the sRNAome and particularly in N2-fixing symbiotic nodules. Small RNA sequencing from 5 Phaseolus vulgaris tissues
Project description:A wide range of environmental stresses lead to an elevated production of reactive oxygen species (ROS) in plant cells thus resulting in oxidative stress. The biological nitrogen fixation in the legume - Rhizobium symbiosis is at high risk of damage from oxidative stress. Common bean (Phaseolus vulgaris) active nodules exposed to the herbicide Paraquat (1,1 '-Dimethyl-4, 4'-bipyridinium dichloride hydrate) that generates ROS accumulation, showed a reduced nitrogenase activity and ureide content. We analyzed the global gene response of stressed nodules using the Bean CombiMatrix Custom Array 90K, that includes probes from some 30,000 expressed sequence tags (EST). A total of 4,280 ESTs were differentially expressed in oxidative stressed bean nodules; of these 2,218 were repressed. These genes were grouped in 44 different biological processes as defined by Gene Onthology. Analysis with the PathExpress bioinformatic tool, adapted for bean, identified five significantly repressed metabolic path