Abstract Motivation: Repetitive DNA makes up large portions of plant and animal nuclear genomes, yet it remains the least-characterized genome component in most species studied so far. Although the recent availability of high-throughput sequencing data provides necessary resources for in-depth investigation of genomic repeats, its utility is hampered by the lack of specialized bioinformatics tools and appropriate computational resources that would enable large-scale repeat analysis to be run by biologically oriented researchers. Results: 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. Implementation and availability: RepeatExplorer was implemented within the Galaxy environment and set up on a public server at http://repeatexplorer.umbr.cas.cz/. Source code and instructions for local installation are available at http://w3lamc.umbr.cas.cz/lamc/resources.php. Contact: [email protected]

MOTIVATION: Satellite DNA makes up significant portion of many eukaryotic genomes, yet it is relatively poorly characterized even in extensively sequenced species. This is, in part, due to methodological limitations of traditional methods of satellite repeat analysis, which are based on multiple alignments of monomer sequences. Therefore, we employed an alternative, alignment-free, approach utilizing k-mer frequency statistics, which is in principle more suitable for analyzing large sets of satellite repeat data, including sequence reads from next generation sequencing technologies. RESULTS: k-mer frequency spectra were determined for two sets of rice centromeric satellite CentO sequences, including 454 reads from ChIP-sequencing of CENH3-bound DNA (7.6 Mb) and the whole genome Sanger sequencing reads (5.8 Mb). k-mer frequencies were used to identify the most conserved sequence regions and to reconstruct consensus sequences of complete monomers. Reconstructed consensus sequences as well as the assessment of overall divergence of k-mer spectra revealed high similarity of the two datasets, suggesting that CentO sequences associated with functional centromeres (CENH3-bound) do not significantly differ from the total population of CentO, which includes both centromeric and pericentromeric repeat arrays. On the other hand, considerable differences were revealed when these methods were used for comparison of CentO populations between individual chromosomes of the rice genome assembly, demonstrating preferential sequence homogenization of the clusters within the same chromosome. k-mer frequencies were also successfully used to identify and characterize smRNAs derived from CentO repeats.

BACKGROUND: The 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. RESULTS: We 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. CONCLUSIONS: Repetitive 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.

MOTIVATION: Tandemly organized repetitive sequences (satellite DNA) are widespread in complex eukaryotic genomes. In plants, satellite repeats often represent a substantial part of nuclear DNA but only a little is known about the molecular mechanisms of their amplification and their possible role(s) in genome evolution and function. Unfortunately, addressing these questions via characterization of general sequence properties of known satellite repeats has been hindered by a difficulty in obtaining a complete and unbiased set of sequence data for this analysis. This is mainly due to the presence of multiple entries of homologous sequences and of single entries that contain more than one repeated unit (monomer) in the public databases. RESULTS: We have established a computer database specialized for plant satellite repeats (PlantSat) that integrates sequence data available from various resources with supplementary information including repeat consensus sequences, abundances, and chromosomal localizations. The sequences are stored as individual repeat monomers grouped into families, which simplifies their computer analysis and makes it more accurate. Using this feature, we have performed a basic sequence analysis of the whole set of plant satellite repeats with respect to their monomer length and nucleotide composition. The analysis revealed several preferred length ranges of the monomers (approximately 165 bp and its multiples) and an over-representation of the AA/TT dinucleotide in the repeats. We have also detected an enrichment of satellite DNA sequences for the motif CAAAA that is supposed to be involved in breakage-reunion of repeated sequences.