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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.

Source Citation

Weighill, D., Macaya-Sanz, D., DiFazio, S. P., Joubert, W., Shah, M., Schmutz, J., … Jacobson, D. (2019). Wavelet-Based Genomic Signal Processing for Centromere Identification and Hypothesis Generation. Frontiers in Genetics, 10.


Copyright © 2019 Weighill, Macaya-Sanz, DiFazio, Joubert, Shah, Schmutz, Sreedasyam, Tuskan and Jacobson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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