Here we present RepeatExplorer, a collection of software tools for characterization of repetitive elements, which is accessible via web interface. A key component of the server is the computational pipeline using a graph-based sequence clustering algorithm to facilitate de novo repeat identification without the need for reference databases of known elements. Because the algorithm uses short sequences randomly sampled from the genome as input, it is ideal for analyzing next-generation sequence reads. Additional tools are provided to aid in classification of identified repeats, investigate phylogenetic relationships of retroelements and perform comparative analysis of repeat composition between multiple species. The server allows to analyze several million sequence reads, which typically results in identification of most high and medium copy repeats in higher plant genomes.

ea (Pisum sativum L., 2n = 14) is the second most important grain legume in the world after common bean and is an important green vegetable with 14.3 t of dry pea and 19.9 t of green pea produced in 2016 (http://www.fao.org/faostat/). Pea belongs to the Leguminosae (or Fabaceae), which includes cool season grain legumes from the Galegoid clade, such as pea, lentil (Lens culinaris Medik.), chickpea (Cicer arietinum L.), faba bean (Vicia faba L.) and tropical grain legumes from the Milletoid clade, such as common bean (Phaseolus vulgaris L.), cowpea (Vigna unguiculata (L.) Walp.) and mungbean (Vigna radiata (L.) R. Wilczek). It provides significant ecosystem services: it is a valuable source of dietary proteins, mineral nutrients, complex starch and fibers with demonstrated health benefits 1-4 and its symbiosis with N-fixing soil bacteria reduces the need for applied N fertilizers so mitigating greenhouse gas emissions 5-7. Pea was domesticated ~10,000 years

BackgroundThe investigation of plant genome structure and evolution requires comprehensive characterization of repetitive sequences that make up the majority of higher plant nuclear DNA. Since genome-wide characterization of repetitive elements is complicated by their high abundance and diversity, novel approaches based on massively-parallel sequencing are being adapted to facilitate the analysis. It has recently been demonstrated that the low-pass genome sequencing provided by a single 454 sequencing reaction is sufficient to capture information about all major repeat families, thus providing the opportunity for efficient repeat investigation in a wide range of species. However, the development of appropriate data mining tools is required in order to fully utilize this sequencing data for repeat characterization.ResultsWe adapted a graph-based approach for similarity-based partitioning of whole genome 454 sequence reads in order to build clusters made of the reads derived from individual repeat families. The information about cluster sizes was utilized for assessing the proportion and composition of repeats in the genomes of two model species, Pisum sativum and Glycine max, differing in genome size and 454 sequencing coverage. Moreover, statistical analysis and visual inspection of the topology of the cluster graphs using a newly developed program tool, SeqGrapheR, were shown to be helpful in distinguishing basic types of repeats and investigating sequence variability within repeat families.ConclusionsRepetitive regions of plant genomes can be efficiently characterized by the presented graph-based analysis and the graph representation of repeats can be further used to assess the variability and evolutionary divergence of repeat families, discover and characterize novel elements, and aid in subsequent assembly of their consensus sequences.