Z curve

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Z curve of C.elegans chromosome III Z curve of C.elegans chromosome III.png
Z curve of C.elegans chromosome III

The Z curve (or Z-curve) method is a bioinformatics algorithm for genome analysis. The Z-curve is a three-dimensional curve that constitutes a unique representation of a DNA sequence, i.e., for the Z-curve and the given DNA sequence each can be uniquely reconstructed from the other. [1] The resulting curve has a zigzag shape, hence the name Z-curve.

Contents

Background

The Z Curve method was first created in 1994 as a way to visually map a DNA or RNA sequence. Different properties of the Z curve, such as its symmetry and periodicity can give unique information on the DNA sequence. [2] The Z curve is generated from a series of nodes, P0, P1,...PN, with the coordinates xn, yn, and zn (n=0,1,2...N, with N being the length of the DNA sequence). The Z curve is created by connecting each of the nodes sequentially. [3]

Applications

Information on the distribution of nucleotides in a DNA sequence can be determined from the Z curve. The four nucleotides are combined into six different categories. The nucleotides are placed into each category by some defining characteristic and each category is designated a letter. [4]

PurineR = A, GAminoM = A, CWeak Hydrogen BondsW = A, T
PyrimidineY = C, TKetoK = G, TStrong Hydrogen BondsS = G, C

The x, y, and z components of the Z curve display the distribution of each of these categories of bases for the DNA sequence being studied. The x-component represents the distribution of purines and pyrimidine bases (R/Y). The y-component shows the distribution of amino and keto bases (M/K) and the z-component shows the distribution of strong-H bond and weak-H bond bases (S/W) in the DNA sequence. [5]

The Z-curve method has been used in many different areas of genome research, such as replication origin identification, [6] [7] [8] [9] , ab initio gene prediction, [10] isochore identification, [11] genomic island identification [12] and comparative genomics. [13] Analysis of the Z curve has also been shown to be able to predict if a gene contains introns, [14]

Research

Experiments have shown that the Z curve can be used to identify the replication origin in various organisms. One study analyzed the Z curve for multiple species of Archaea and found that the oriC is located at a sharp peak on the curve followed by a broad base. This region was rich in AT bases and had multiple repeats, which is expected for replication origin sites. [15] This and other similar studies were used to generate a program that could predict the origins of replication using the Z curve.

The Z curve has also been experimentally used to determine phylogenetic relationships. In one study, a novel coronavirus in China was analyzed using sequence analysis and the Z curve method to determine its phylogenetic relationship to other coronaviruses. It was determined that similarities and differences in related species can quickly by determined by visually examining their Z curves. An algorithm was created to identify the geometric center and other trends in the Z curve of 24 species of coronaviruses. The data was used to create a phylogenetic tree. The results matched the tree that was generated using sequence analysis. The Z curve method proved superior because while sequence analysis creates a phylogenetic tree based solely on coding sequences in the genome, the Z curve method analyzed the entire genome. [16]

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<span class="mw-page-title-main">Computational biology</span> Branch of biology

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References

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