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

0347465 - BC 2011 RIV GB eng J - Článek v odborném periodiku
Novák, Petr - Neumann, Pavel - Macas, Jiří
Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data.
BMC Bioinformatics. Roč. 11, č. 1 (2010), s. 378-389. ISSN 1471-2105. E-ISSN 1471-2105
Grant CEP: GA MŠMT(CZ) OC10037; GA MŠMT(CZ) LC06004
Výzkumný záměr: CEZ:AV0Z50510513
Klíčová slova: repetitive DNA * plant genome * next generation sequencing
Kód oboru RIV: EB - Genetika a molekulární biologie
Impakt faktor: 3.028, rok: 2010

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,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. 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
Trvalý link: http://hdl.handle.net/11104/0188237