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Related Concept Videos

What is Variation?01:14

What is Variation?

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Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
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Variation01:19

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An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
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Hydronium and hydroxide ions are present both in pure water and in all aqueous solutions, and their concentrations are inversely proportional as determined by the ion product of water (Kw). The concentrations of these ions in a solution are often critical determinants of the solution’s properties and the chemical behaviors of its other solutes. Two different solutions can differ in their hydronium or hydroxide ion concentrations by a million, billion, or even trillion times. A common means of...
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Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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Large-Scale Structural Variation Detection in Subterranean Clover Subtypes Using Optical Mapping.

Yuxuan Yuan1,2, Zbyněk Milec3, Philipp E Bayer1,2

  • 1School of Biological Sciences, The University of Western Australia, Perth, WA, Australia.

Frontiers in Plant Science
|August 2, 2018
PubMed
Summary
This summary is machine-generated.

Bionano optical mapping (BOM) identified large structural variations (SVs) in subterranean clover. However, nucleotide-level validation is crucial for precise SV characterization, as BOM

Keywords:
Bionanonucleotide validationoptical mappingreferencestructural variation

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Area of Science:

  • Plant genomics
  • Structural variation analysis
  • Genome mapping technologies

Background:

  • Subterranean clover (Trifolium) is a model species for genetic studies.
  • Accurate identification of structural variations (SVs) is essential for understanding genome evolution and traits.
  • Bionano optical mapping (BOM) is a technology for detecting large-scale genomic changes.

Purpose of the Study:

  • To evaluate the accuracy of Bionano optical mapping (BOM) for detecting structural variations (SVs) in subterranean clover.
  • To compare BOM findings with Illumina short-read sequencing for SV validation.
  • To assess the reliability of BOM in pinpointing the exact location and number of SVs.

Main Methods:

  • Selected two genetically diverse subterranean clover subspecies: Daliak and Yarloop.
  • Employed Bionano optical mapping (BOM) to identify large-scale structural variations (SVs).
  • Validated BOM-identified SVs using Illumina short-read sequencing.

Main Results:

  • BOM detected 12 large deletion regions and 19 insertion regions in Yarloop.
  • Illumina short reads validated 71 small deletions within the 12 large deletion regions identified by BOM.
  • BOM accurately estimated the total size of deletions and insertions but lacked precision in location and quantity.

Conclusions:

  • Bionano optical mapping (BOM) is effective for detecting the presence and overall size of structural variations (SVs).
  • Nucleotide-level validation is indispensable for confirming and precisely characterizing SVs identified by optical mapping.
  • The accuracy of BOM for SV detection is influenced by reference genome quality and nickase density.