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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
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Wavelet-Based Genomic Signal Processing for Centromere Identification and Hypothesis Generation.

Deborah Weighill1,2, David Macaya-Sanz3, Stephen Paul DiFazio3

  • 1The Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, United States.

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|June 20, 2019
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Summary
This summary is machine-generated.

Researchers identified centromeric regions in Populus trichocarpa using multi-omics data and signal processing. They also found evidence for co-evolution between centromeric histone CENH3 and these regions, identifying a new CENH3 candidate.

Keywords:
CENH3DNA methylationPopulus trichocarpa centromeresSNP densityco-evolutiondata integrationwavelet transform

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Area of Science:

  • Genomics
  • Molecular Biology
  • Plant Science

Background:

  • Centromeres are crucial for chromosome segregation but are difficult to identify due to repetitive sequences.
  • Various 'omics data, including genome sequence, variants, and methylation, offer potential signals for centromere identification.

Purpose of the Study:

  • To comprehensively analyze centromere signatures in Populus trichocarpa using diverse 'omics data.
  • To identify putative centromeric regions and investigate the co-evolution of centromeric histone CENH3.

Main Methods:

  • Utilized genome sequence, population variant, and multi-tissue methylation data.
  • Applied wavelet-based signal processing to analyze 'omics data as density signals.
  • Correlated single nucleotide polymorphism (SNP) data across a natural population.

Main Results:

  • Successfully identified putative centromeric regions in Populus trichocarpa.
  • Found evidence for co-evolution between CENH3 and the newly identified centromeric sequences.
  • Identified a novel CENH3 candidate in Populus trichocarpa.

Conclusions:

  • Multi-omics data combined with signal processing is effective for centromere identification in plants.
  • CENH3 and centromeric sequences show signs of co-evolution, suggesting adaptive mechanisms.
  • The identified CENH3 candidate warrants further functional investigation.