Journal of Forensic Pathology

Advanced Genotyping of DNA Fingerprints Using a Model Created From Actual Chip Electrophoresis Data

Hyejung Weinmann^{* *}Correspondence: Hyejung Weinmann, Department of Forensic Pathology, Stellenbosch University, Stellenbosch, South Africa, Email:

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Introduction

Bacterial strains are often categorised using DNA fingerprinting techniques, and the amplification results are typically evaluated and seen using electrophoretic separation techniques. The popularity of contemporary automated chip electrophoresis is rising, notably in the case of in-depth comparative research, even though classic planar electrophoresis (on an agarose gel) is still more frequently utilised than its automated equivalents. The primary benefits include the absence of the gel image digitalization process, the absence of sample distortion brought on by the electromagnetic field's non-homogeneity (smile effect), the ease with which sample ranges from multiple electrophoretic runs can be combined, and the faster electrophoretic runs. As a result, rather of relying on a human operator's judgement to estimate the size of DNA fragments from a poor quality image, the size of the DNA fragments can be directly determined by employing objective software analysis. Even automated chip electrophoresis has a finite degree of accuracy, though. For instance, depending on the kits and reagents used, the Agilent 2100 bioanalyzer system offers catalogue values of 10% or 15% sizing accuracy. The size resolution is similarly constrained and based on the size range; for the Agilent DNA 7500 kit, the resolution is 5% between 100 and 1,000 bp and 15% between 1,000 and 7,500 bp. The values of the fragment size that are produced as a result are therefore not entirely correct, and their deviation is not constant across the observed range. Phylogeny reconstruction is made more difficult by the existence and constancy of the deviation, even though it is less severe than that found in the subjective evaluation of size from typical planar electrophoresis gel pictures. Based on the presence or absence of bands of the same size, these techniques evaluate how similar two sample lines (fingerprint patterns) are. Because measurements are inaccurate, it is challenging to determine whether two bands are the same or belong to two different bands that correspond to different DNA fragment lengths. The paucity of material in the literature demonstrates the lack of attention given to this issue.

Description

The first is that because planar electrophoresis is less expensive than chip electrophoresis, it is employed more frequently. Thus, tools like PyElph GelClust and GelJ that are primarily used for image preprocessing tasks are still being used to analyse DNA fingerprint gel pictures. The evaluation of two bands similarity is simple. If the bands variation is below the allowed constant level, they are typically considered to be of the same size. Pairwise alignment is frequently used to identify bands of the same size or to align them. Although it still uses a heuristically determined constant threshold, GELect's Density Based Clustering Approach (DBSCAN) leverages band cluster centroids from all samples to provide a more sophisticated solution. Additionally, the minimal number of samples that contain bands, another decision parameter, results in the inaccurate classification of unique samples. The Dynamic Temporal Warping (DTW) method, which adaptively re-samples 1D signal representations of specific lines, is another means to modify band placements in gel pictures produced from traditional planar electrophoresis. This method demands a full signal representation from raw data instead of using a constant threshold for band position adjustment. The processing of chip electrophoresis DNA fingerprinting data is almost entirely realised through complex and expensive software platforms, such as BioNumerics (Fingerprint data module or DiversiLab genotyping application distributed by applied Maths NV, BioMérieux, France). This is the second cause of the insufficient examination of the band alignment in chip electrophoresis. The principles of the techniques used are not available to the general public, and these instruments are patented. The company's technical documentation states that for band position correction, the fingerprint data module combines global shift with linear stretch/compression and nonlinear shift with fixed edges. The shift correction is based on identifying the samples with the highest correlation, despite the fact that the process is not explicitly defined. Correlation between the deviation and band size is predicted, as correlation measures the strength of linear dependency.

Since the sample mobility on the gel does not linearly rely on band size, it can be assumed that the nature of the dependence is not linear. This paper presents a novel adaptive threshold based strategy for the global alignment of the band locations. In order to prove that the relationship between band size deviation (shift) and band size (band location) is neither constant nor linear, a significant number of DNA weight markers were assessed. These measurements were used to create an empirical model of band size deviation, which is used as a transformation function to adjust band size deviation to a roughly constant value over the measured range.

It makes it possible to find bands of the same size in all data using hierarchical cluster analysis with a single fixed threshold without a limit on the number of clusters or the number of objects in each cluster. On DNA weight markers, where the exact band size values are known, the identification accuracy of the identical bands was also confirmed.

Conclusion

The developed approach was finally tested on the research of the genotyping of 60 bacterial strains using the repetitive element palindromic Polymerase Chain Reaction (rep-PCR) and compared with the industry standard tool, the bionumerics fingerprint data module.