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Genetic (Single Nucleotide Polymorphisms) Analysis of Genome


Personal Genomic Services

As described above, the advancement of the SNP technology in genomic analysis has made it possible to achieve cheap, effective, high-throughput, novice and fast methods for analyzing personal genomes. The company is providing services through its program “The 23andMe Personal Genome Service”.

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The aim is to provide health and ancestry information services to the people based on genetic analysis of their genomes.

The collection of DNA from saliva is less invasive than blood and other samples (Pulford, Mosteller & Nelsen 2013). This makes it an suitable method of DNA extraction to most people. In addition, it is simple and quick because saliva is readily present in the mouth.

The biology behind the 23andME services is based on the idea of genome-wide analysis, a genetic analysis for the human genome. It is based on the SNP technique. Previously, it was understood that rearrangements in the genome could take place as rare events, causing genomic disorders. Later, it was realized that the human genome contained numerous segmental duplications. However, the use of the genome-wide assays in the HGP allowed researchers to achieve a systematical assessment and visualization of the genome-wide differences in the copy number of regions in healthy, normal and unrelated persons. The variations were taken to mean gains and losses of the segments ranging from a few kbs to several hundreds or even millions of kbs. About 35-40% of the copy number variations were detected in multiple individuals, which indicated that about 20 copy number variations exist in the human genome. This marked an important turn point for the evolution of the SNP technology and its application in medicine. Currently, studies indicate that over 15,960 structurally variable loci exist in the human genome. They are dispersed throughout the genome but are mostly found in clustered in certain locations within the genome such as the sub-telomeric and pericentromeric regions.

Studies with SNP technology on personal human genomes have shown that individuals differ in human genomes reference sequence at an average of 3.4 million SNPs (Nachman 2011).

Noteworthy, most of the SNP variations occur in non-coding regions where inversions and rearrangements take place, but these events lead to pathologic conditions.

The C282Y mutation is found on the HFE gene, which is located in the human chromosome 6. The mutation is carried in about 13% of the individuals of Caucasian backgrounds and is closely associated with the hereditary hemochromatosis, an iron-loading disease that makes it difficult for the affected individuals to absorb iron (Fairweather-Tait, Harvey, Heath & Roe 2007). This mutation is a good example of harmful SNPs found in the human genome, particularly in the non-coding regions (Nachman 2011).

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However, most SNPs have no phenotypic effect in humans. In fact, only <1 of all SNPs in human genomes have an impact on the protein function because SNPs are located on the non-coding regions of the genome (Shastry 2009). An example is the missense mutation 1580G>T SNP in LMNA gene, which is located in position 1580 (nt) in the human genome. Nevertheless, most SNPs have latent effects because their phenotypic effects are achieved when other factors come into play. For instance, the G542X is a mutation on the human cystic fibrosis transmembrane conductance regulator gene (CFCR gene) that contributes to cystic fibrosis, but the impact is latent because CF occurs due to the effects of the mutation when other factors are present. Therefore, not all SNPs are detrimental.

Some SNPs are related with drug resistance in humans. For example, scientists have established that the silent mutation on the multidrug resistance gene 1( MDR1 gene) slows down translation of the gene, which causes the gene to be less functional due to poor folding of the protein (Gottesman 2007).

Positive implications of genetic screening

The genome analysis technique has made it possible to detect the presence of genetic factors likely to cause certain diseases. As indicated above, it is possible to identify individuals predisposed to develop diseases such as Alzheimer’s, CF, hereditary hemochromatosis and some forms of cancer. As such, it has enhanced diagnosis. Moreover, it makes it possible to develop early interventions to prevent the occurrence of the disease. Thirdly, the technique has made it possible to identify hereditary factors, especially in classifying individuals and solving matters of lineage and hereditary.

Negative implications

A major implication of the process is the exposure of critical information about an individual, especially when an individual carries genetic factors predisposing him/her to certain conditions as dementia. In fact, Alzheimer’s disease has no cure and knowing that one will get it in later stages of life is likely to cause psychological stress as well as stigmatization in the society.


The presence of several bands of the Amplified WMIN gene- exposed to Hind III indicates the presence of a mutation on the gene, which is a form of SNP. This study is an example of the research work that has worked with SNP technique on personal human genomes to indicate how individuals differ in human genomes reference sequence at an average of 3.4 million SNPs (Nachman 2011). The number of novel variations in each genome does not necessarily decrease with the rising number of individual genomes being sequenced. Previous studies have used similar approaches to show that a personal genome has between 4000,000 and 600,000 novel SNPs compared to dbSNP (Nachman 2011).


Fairweather-Tait, SJ, Harvey, L, Heath, ALM & Roe, M, 2007, “Effect of SNPs on iron metabolism”, Genes & Nutrition, vol. 2, no. 1, pp. 15–19.

Kimchi-Sarfaty, C. Oh, JM, Kim, IW, Sauna, ZE, Calcagno, AM, Ambudkar, SV & Gottesman, MM, 2007, “A “silent” polymorphism in the MDR1 gene changes substrate specificity”, Science vol. 315, no. 5811, pp. 525-528.

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Mitchelson, KR & Cheng, J, 2011, Capillary Electrophoresis of Nucleic Acids: Introduction to the Capillary Electrophoresis of Nucleic Acids, Springer, London, UK.

Nachman, MW, 2011″Single nucleotide polymorphisms and recombination rate in humans”, Trends in genetics vol. 17, no. 9, pp. 481–485.

Pulford, DJ, Mosteller, M & Nelsen, AJ, 2013, “Saliva sampling in global clinical studies: the impact of low sampling volume on performance of DNA in downstream genotyping experiments”, BMC Medical Genomics vol. 6, no. 20, pp.1-19.

Shastry, BS, 2009, “SNPs: impact on gene function and phenotype”, Methods Mol Biol vol. 578, no. 6, pp. 3-22.

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