Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data

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 massivelyparallel 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 in...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Petr Novák, Pavel Neumann, Jirí Macas
• Keywords: BMCBI 2010, Genomes, Repeat Families, Sequencing