De novo assembly and characterization of Gleditsia sinensis transcriptome and subsequent gene identification and SSR mining.

Gleditsia sinensis is a Chinese native deciduous tree with a high economic and medicinal value. However, there is limited knowledge on the molecular processes responsible for the medical properties of this species owing to lack of bioinformatic resources such as available whole-genome sequences. In the present study, RNA sequencing data were used to analyze the transcriptome of G. sinensis, and a series of bioinformatic tools was used to explore the main genes involved in important molecular processes. A total of 75.57 million paired-end reads, with a length of 101 bp, were acquired from G. sinensis. Using the assembly tool Trinity, 233,751 transcripts were discovered. Among these, 85,795 were identified as unique transcripts and 59,326 unique transcripts were found to contain coding regions. Gene ontology analysis identified 27,637 unique transcripts that were clustered into 56 functional groups. Genes involved in flavonoid and terpenoid backbone biosynthesis and those encoding transcription factors were further analyzed. Sequence analysis revealed four putative G. sinensis chalcone isomerase genes (GsCHI) encoding the enzymes for flavonoid biosynthesis. GsCHI1 was found to be phylogenetically related to the chalcone isomerase of the family Leguminosae, and its transcript levels in different tissues were higher than those of GsCHI2, GsCHI3, and GsCHI4. Furthermore, 15,014 simple sequence repeat (SSR) markers were discovered in the transcript library, and 5170 primers were generated for the SSR loci. The genetic and genomic information presented in this study will be helpful for future studies on gene discovery and molecular processes in G. sinensis.

Modelling biological invasions: species traits, species interactions, and habitat heterogeneity.

In this paper we explore the integration of different factors to understand, predict and control ecological invasions, through a general cellular automaton model especially developed. The model includes life history traits of several species in a modular structure interacting multiple cellular automata. We performed simulations using field values corresponding to the exotic Gleditsia triacanthos and native co-dominant trees in a montane area. Presence of G. triacanthos juvenile bank was a determinant condition for invasion success. Main parameters influencing invasion velocity were mean seed dispersal distance and minimum reproductive age. Seed production had a small influence on the invasion velocity. Velocities predicted by the model agreed well with estimations from field data. Values of population density predicted matched field values closely. The modular structure of the model, the explicit interaction between the invader and the native species, and the simplicity of parameters and transition rules are novel features of the model.