Characterization of human chromosomal material exchange with regard to the chromosome translocations using next-generation sequencing data.
Bottom Line: 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.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.
Affiliation: Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University.Show MeSH
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Mentions: The chances that translocations were between two specific chromosomes were not the same for different chromosome pairs. Based on the enrichment score defined in the Materials and Methods section, the enrichment degree of interchromosome translocated fragments among chromosome pairs was shown in figure 3. Similarly to the previously detected patterns (Lieberman-Aiden et al. 2009), relatively more translocations were observed between small and gene-rich chromosomes 16, 17, 19–22. Furthermore, previous FISH studies on chromosome territories showed that chromosomes 16, 17, 19, 22 were concentrated together in the center of the nucleus (Boyle et al. 2001; Cremer and Cremer 2010). The enrichment scores of these chromosome pairs clearly reflected their spatial proximity of chromosome territories in cell nuclei. Particularly, the top three chromosomal pairs with most enriched translocations were t(18,21), t(21,22), and t(17,19). Notice that chromosome 18 is not gene-rich and is not close to those gene-rich chromosomes in space (Tanabe et al. 2002; Cremer and Cremer 2010). However, other studies (Lieberman-Aiden et al. 2009) did provide evidence that chromosomes 18 and 21 may contact each other with high probabilities.Fig. 3.—
Affiliation: Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University.