title: Characterization of human chromosomal material exchange with regard to the chromosome translocations using next-generation sequencing data.
abstract: As an important subtype of structural variations, chromosomal translocation is associated with various diseases, especially cancers, by disrupting gene structures and functions. Traditional methods for identifying translocations are time consuming and have limited resolutions. Recently, a few studies have employed next-generation sequencing (NGS) technology for characterizing chromosomal translocations on human genome, obtaining high-throughput results with high resolutions. However, these studies are mainly focused on mechanism-specific or site-specific translocation mapping. In this study, we conducted a comprehensive genome-wide analysis on the characterization of human chromosomal material exchange with regard to the chromosome translocations. Using NGS data of 1,481 subjects from the 1000 Genomes Project, we identified 15,349,092 translocated DNA fragment pairs, ranging from 65 to 1,886 bp and with an average size of approximately 102 bp. On average, each individual genome carried about 10,364 pairs, covering approximately 0.069% of the genome. We identified 16 translocation hot regions, among which two regions did not contain repetitive fragments. Results of our study overlapped with a majority of previous results, containing approximately 79% of approximately 2,340 translocations characterized in three available translocation databases. In addition, our study identified five novel potential recurrent chromosomal material exchange regions with greater than 20% detection rates. Our results will be helpful for an accurate characterization of translocations in human genomes, and contribute as a resource for future studies of the roles of translocations in human disease etiology and mechanisms.
authors.affiliation: Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University.
authors.forename: Chao
authors.initials: C
authors.lastname: Xu
authors.affiliation: Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University.
authors.forename: Jigang
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University Department of Biomedical Engineering, School of Science and Engineering, Tulane University.
authors.forename: Yu-Ping
authors.initials: YP
authors.lastname: Wang
authors.affiliation: Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University Third Affiliated Hospital, China Southern Medical University, Guang Zhou, 510000, P. R. China.
authors.forename: Hong-Wen
authors.initials: HW
authors.lastname: Deng
authors.affiliation: Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University jli8@tulane.edu.
authors.forename: Jian
authors.initials: J
authors.lastname: Li
mesh_terms: D002877:Chromosomes, Human / Q000235:genetics*; D015894:Genome, Human; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D017422:Sequence Analysis, DNA; D014178:Translocation, Genetic
keywords: chromosomal translocation; next-generation sequencing; recurrent translocation; structural variation