Classification of Virus by DNA Genetic Marker and Its Theory

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This journal article is previously published as: Liu Huan. (2021). Classification of Virus by DNA Genetic Marker and Its Theory. Journal of Environment and Health Science (ISSN 2314-1628),2021(02).https://doi.org/10.58473/JBS0001, which is converted into Journal of Biological Sciences (ISSN 2958-4035). Both Journals belong to the same publisher, Liu Huan. The previous journal article is closed to the public, but the previous reference is still valid.

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Latest revised on 29/05/2023.

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Article 1-1. Classification of Virus by DNA Genetic Marker and Its Theory/DNA 遗传标记技术与病毒生物分类以及相关理论

Author: Liu Huan (1983 - ), Master of Science (First Class Honours,2009), The University of Auckland. ORCID: https://orcid.org/0000-0003-4881-8509

This article presents the new experiment methods of DNA genetic markers: The methods of classifying and identifying virus will follow these steps:

Step 1. The morphological markers of different virus samples are analyzed [1] using transmission electron microscopy, and the criteria of morphological markers can be selected by referring to molecular cytogenetic karyotype analysis;

Step 2. Virus is classified by multivariate cluster analysis and genetic distance  analysis on the basis of morphological markers, preliminarily leading to different families of virus [2];

Step 3. The optima sampling units of each virus family, which can well represent the genetic diversity of each virus family, is examined and determined as pointed out by Liu et al.,(2015) [2] for further classification based on DNA (or RNA) molecular marker (SSR or AFLP). The sampling units can be adjusted by changing the concentration of virus solution;

Step 4. Classification of virus families is further conducted on the basis of DNA (or RNA) molecular marker, analyzed by multivariate cluster analysis of UPGMA (unweighted pair group method with arithmetic averages) and genetic distance analysis [2].

Step 5. Gene recombination and gene mutation rate is analyzed by the inconsistence  of classification between morphological markers and DNA (or RNA) molecular marker.

There are three hypotheses examined by this research:

Hypothesis 1: the optima numbers of polymorphic SSR primers are examined and screened for each virus family, because we assume that the amount of polymorphic SSR primers, which are assessed on the basis of polymorphism information content (PIC), increases with the increase of total SSR primers selected from Gene Bank, but the increase rate is not constant. Consequently, the optimal number of polymorphic SSR primers is determined at the peak increase rate.

Hypothesis 2: the classification significantly differs between morphological markers of virus and DNA genetic markers.

Hypothesis 3: there are two kinds of multivariate cluster analysis and genetic distance analysis on the basis of SSR markers, resulting in two different classifications of virus families: firstly, the classification of virus families is conducted based on the Nei’ genetic identity[3](or Nei’ genetic similarity[4]) calculated by the total SSR primers from Gene Bank; or then the classification of virus families is conducted based on the genetic identity calculated by the polymorphic SSR primers only. This research aims to examine which classification method leads to better correlation with the incidence of pathological characters recorded.

Discussion:

1. The total SSR primers selected from Gene Bank are the pairs of SSR primers which lead to clear PCR bands for at least one virus family in amplified process;

2. The virus samples should be collected in the same area at local scale, which facilitates the differentiation of local virus families due to the unique nature of virus ecosystem.There are two reasons to explain the virus ecosystem: Firstly, the local virus ecosystem is relatively isolated, due to ‘the absence of gene communication’ among virus ecosystem and the limitations of airborne virus transmission; Secondly, the SSR gene sequences which lead to clear PCR bands is considered to be highly conserved, so that its proportion of specific gene sequence information is relatively constant in its original virus ecosystem. Consequently, the virus samples should be collected in the same area at local scale. However, the amount of virus families, which result in the impacts on human health, is increasing due to gene recombination and mutation in self-reproduction process or invasive virus species from exotic ecosystem. Once epidemic disease is caused by the above reasons, the UPGMA analysis newly designed below should accurately detect the variation as unbalanced status compared with original virus ecosystem.

3. There is a novel matrix designed for genetic distance analysis based on PCR bands: Preparation of DNA samples in one test: 12 uniform samples are abstracted from the same DNA water solution which has been evenly mixed, named as sample 1, sample  2, ..., sample12; In total 12 different SSR primers are selected in one test, named as primer 1, primer 2,...., primer12, and each different SSR primer is  injected  into sample 1, sample 2, ..., sample 12 respectively for PCR amplified process; after PCR amplified process, each sample (12 in total) is electrophoresed separately in each pipe of electrophoresis instrument, and the PCR bands from different virus families, preliminarily drawn by morphological markers, would be clearly separated from each other in a electrophoresis pipe. Consequently, the distance between two PCR bands from two different virus families, which is measured in a pipe of electrophoretogram, represents the genetic distance between these two virus families per SSR primer (or locus). Then the multivariate cluster analysis of UPGMA (unweighted pair group method with arithmetic averages) is conducted on the basis of the average genetic distance between any two different virus families across SSR primers (or loci) which can lead to clear PCR bands in a pipe. If the electrophoresis pipe is the vertical one, then the PCR  bands around the same horizontal lines would represent the same proportion of gene sequences information to the sum informations of the whole genome families examined in a experiment, which is comparable across different pipes in a matrix for UPGMA analysis.

There is an improved method presented for identification of virus families:

Step 1. The whole genome of a specific virus family, whose DNA (or RNA) molecular weight is examined in Lab[5], is cultivated for reproduction in Lab as standardized DNA molecule.

Step 2. After amplified process in PCR, the DNA fragment samples together with the cultivated genomes in step 1, are transferred into the electrophoretogram procedure.

Step 3. The standardized DNA (or RNA) molecule should be the molecules of the highest weight; Then the molecular weight of DNA fragments from the other virus families can be calculated per SSR correspondingly[5]. This improved method facilitates the identification of virus families, regardless of variation in virus ecosystem.

Step 4. Identification of virus family with gene mutation:  the specific locus of genome,  in which gene mutation occurs, is identified by DNA (or RNA) molecular markers  (the heterozygous bands of a specific locus is the  gene mutation bands, as  compared to the homozygous bands of parental virus family without gene mutation). Please note: the heterozygous or homozygous bands here are just description of band morphology, rather than allelic gene.

Please note: the objects of dyeing procedure in step 1 is protein due to the protein ‘coat’ around virus DNA (or RNA) and the DNA (or RNA) molecules are the molecules with the highest weight in virus physiology, whereas the objects of dyeing procedure in step 3 is nucleic acid molecule. SDS-PAGE for protein separation requires lower voltage than nucleic acid molecules (or isozyme separation), so that the DNA (or RNA) can take off their protein 'coat.' The weaker clearness of protein ‘coat’s bands, the higher accuracy of this test, which can be adjusted by gradual change of voltage. If SDS-PAGE for protein separation is conducted exactly, it is expected to reveal the morphology of virus DNA molecules by fluorescence in situ hybridization (FISH) technique, which can be analyzed by the criteria of molecular cytogenetic karyotype.

Discussion:

In this experiment, the gene mutation virus family is identified in the whole virus ecosystem, analyzed by both multivariate cluster method and two-paired comparison (between parental virus and gene mutation virus). It is expected that the gene mutation virus family show closer genetic distance to the other virus families, rather than its parental virus family, on the basis of the classification conducted by the DNA morphological markers of virus. However, the conclusion of virus classification is ‘corrected’ by further DNA (or RNA) sequencing markers (gene mutation virus family should show closer genetic distance to their parental virus family). This finding will further support the distortive bio-signal caused by gene mutation virus family, which is hardly identified by host cells discussed in the other article of this journal [6].

Implications

In this article, it is further to proposed that compared with the DNA sequences technology utilization only, the combination of both morphological markers and DNA sequences technology in this article results in different classification conclusions due to the relativity nature of statistics in Multivariate Classification Analysis, which is more reasonable for virus testing in terms of reflecting the whole DNA/genome information. This article further concludes that the fragment information of DNA sequences does not indicates the total pathological characters of virus, because the gene mutation does not only lead to the alteration of DNA sequences in a specific fragment, but also results in the significant changes in genome morphology which plays the key role in virus invasion process. Consequently, the virus testing based on the fragment DNA sequences only is not a reliable method to reveal the total gene mutation characters. This is especially important for COVID 19 testing.

This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” published in 2016. Firstly Revised on 03/01/2021; Secondly Revised on 05/02/2021; Thirdly Revised on 04/01/2022; Fourthly Revised on 06/10/2022.This journal article is previously published as: Liu Huan. (2021). Article 1-1. Classification of Virus by DNA Genetic Marker and Its Theory/DNA 遗传标记技术与病毒生物分类以及相关理论. Journal of Environment and Health Science (ISSN 2314-1628), 2021(02).,  which is converted into Journal of Biological Sciences (ISSN 2958-4035). Both Journals belong to the same publisher, Liu Huan. The previous journal article is closed to the public, but the previous reference is still valid. Latest revised on 29/05/2023.

References:

[1]. 刘焕, 张洪初与唐秋盛, 保护遗传学方法在生物多样性监测和评价领域的应用研究.        科技视界, 2014(8);

[2]. Liu, H, Ouyang T. L, Tian Chengqing (2015). Review of Evolutionary Ecology Study and Its Application on Biodiversity Monitoring and Assessment. Science & Technology Vision (6) 2015;

[3]. 陶玲与任珺, 进化生态学的数量研究方法, 2004, 中国林业出版社: 北京市; [4]. Genuineness and Purity Verification of Potato Seed Tuber - SSR Molecular Marker (GB/T 28660-2012).

[5]. 朱广廉，杨中汉 SDS-聚丙烯酰胺凝胶电泳法测定蛋白质的分子量《植物生

理学报》, 1982.

[6]. Liu Huan, Gene Mutation, Pathogenesis and Gene Modification, Feb 2021, Journal of Environment and Health Science.

https://doi.org/10.58473/JBS0007