Wavelet-based genomic signal processing for centromere identification and hypothesis generation
Deborah Weighill, David Macaya-Sanz, Stephen Paul DeFazio, Wayne Joubert, Manesh Shah, Jeremy Schmutz, Avinash Sreedasyam, Gerald Tuskand and Daniel Jacobson
31 May 2019, Frontiers in Genetics 10:487; doi: 10.3389/fgene.2019.00487
Various ‘omics data types have been generated for Populus trichocarpa, each providing a layer of information which can be represented as a density signal across a chromosome. We make use of genome sequence data, variants data across a population as well as methylation data across 10 different tissues, combined with wavelet-based signal processing to perform a comprehensive analysis of the signature of the centromere in these different data signals, and successfully identify putative centromeric regions in P. trichocarpa from these signals. Furthermore, using SNP (single nucleotide polymorphism) correlations across a natural population of P. trichocarpa, we find evidence for the co-evolution of the centromeric histone CENH3 with the sequence of the newly identified centromeric regions, and identify a new CENH3 candidate in P. trichocarpa.
Weighill D, Macaya-Sanz D, DiFazio SP, Joubert W, Shah M, Schmutz J, Sreedasyam A, Tuskan G and Jacobson D (2019). Wavelet-Based Genomic Signal Processing for Centromere Identification and Hypothesis Generation. Front. Genet. 10:487. doi: 10.3389/fgene.2019.00487