Comparative Sequence Study in Human and Primate DNA Samples

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Table of Contents

Introduction
Comparison Background
Samples
Analysis
Conclusion
Works Cited

Introduction

Comparison of human and primate DNA samples may help assess the DNA-building patterns that are used in different organisms. In fact, it is stated that the similarity level of human and primate DNA structures is 98%, (DeWitt, 1) and this paper is aimed at performing a comparative study for differentiating the key patterns of DNA creations and structuring. The tools that will be used for the comparison and analysis are mainly computational and involve the logic calculation principles that are used by DNA chains.

Comparison Background

In general, the differences between DNA samples are qualitative and quantitative, and this is explained by the fact that these are responsible for the key biological differences between humans and primates. The genomic differences that are generally spotted in the sampled are featured with few DNA pair rearrangements, and these genomic differences are defined by the positions of the four key amino acids. (Frank-Kamenetskii, 306; Giribet, 169; Meyer 406)

The logical structure of the DNA samples is not featured with essential differences. Hence, as is stated by Lipman and Pearson (1441), three key alignment regimes may be found in DNA chains: Affine, Arbitrary, and Convex. Therefore, combination classes depend on the logic principles stated by these regimes. (Miyamoto and Cracraft, 313) Therefore, these regimes define the order of classes and superclasses in the logic structure. Additionally, relations between the superclass and its subclasses are given it involves the data structuring methods that are needed by the subclass. (Myers, 112)

Samples

The Smith-Waterman alignment algorithm is used for the comparison and assessment match =0, mismatch = +1, and gap = +0.1 using constant gap penalty.

Therefore, the DNA samples are of the structure given below:

Human: ATTCACATACAATTAG
Primate: ATTCACAATAGATACT

The alignment sequence that will be used is ATT.

	–	A	T	T	C	A	C	A	T	A	C	A	A	T	T	A	G
–	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0
A	.1	.0	.1	.1	.1	.0	.1	.0	.1	.0	.1	.0	.0	.1	.1	.0	.1
T	.2	.1	.0	.1	.2	.1	.2	.1	.0	.1	.2	.1	.1	.0	.1	.1	.2
T	.3	.2	.1	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0

	–	A	T	T	C	A	C	A	A	T	A	G	A	T	T	A	A
–	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0
A	.1	.0	.1	.1	.1	.0	.1	.0	.0	.1	.0	.1	.0	.1	.1	.1	.1
T	.2	.1	.0	.1	.2	.1	.2	.1	.1	.0	.1	.2	.1	.0	.1	.2	.1
T	.3	.2	.1	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0	.0

From the perspectives of the comparison performed, it should be emphasized that the real data is supposed for used for the testing sequences which do not overwhelm 80 characters. (Liu and Fu, 327; Gagneux, 11) The following observations are obvious:

The compared sequences reveal the fact that the difference is evident, however, there are more similarities than differences in the connections and structures of the protein chains. (Wang, 1679) All the regions which are not similar are featured with the same position of amino acids, and the same logic of amino acids connections. Therefore these dissimilarities are the key difference parts of the DNA samples. (Swanson and Rusz, 363; Yang and Pan, 399)
Per the genetic code principles, the nucleotide sequences may be generally translated into the sequences of amino acids that are applied for the dynamic programming, and aligning rules. (Harlan, 179; Tutton and Corrigan, 285) It is also stated that the region of the DNA sequences that are featured with the ATG beginning, end with TAA, TAG, or TGA elements.

Analysis

Following the calculations and sequence analysis, it should be stated that the gap and gap penalties principles of the samples are the same. The proper analysis of the gap penalties involves the creation of the dynamic programming matrix that is aimed at defining the series of consecutive spaces irrespective of the number. Since the original research involves all the necessary input and output calculation data, it should be stated that gap values of both samples coincide, as they are subjected to the same logic rules. (Kakuo and Kitamo, 310)

Gap spaces, as well as the logic of protein structure, reveal the fact that both samples (sequences) analyzed are almost identical, and theoretic aspects of DNA calculation and programming are based on the same principles.

Conclusion

Comparative study of the human and primate DNA chain sample helped to reveal the key logical and sequential principles that are used in protein sequences. It is stated that logic principles and gap penalty rules are subjected to the same regulations. This means that theoretic aspects of DNA calculation and programming may be used for analyzing DNA sampled of humans and primates, and the regarded difference of 2% does not include the key rules.

Works Cited

Frank-Kamenetskii, Maxim D. Unraveling DNA: The Most Important Molecule of Life. Trans. Lev Liapin. Revised ed. Reading, MA: Perseus Publishing, 2007.

Harlan, Leigh M. “When Privacy Fails: Invoking a Property Paradigm to Mandate the Destruction of DNA Samples.” Duke Law Journal 54.1 (2004): 179.

DeWitt, David. Greater That 98% Chimp/Human DNA Similarity? Not any more. Answersingenesis.org. Web.

Gagneux, Peter. Genetic differences between humans and great apes. Mol Phylogenet Evol 18: 2001. 2-13.

Giribet Gabrial. On Gaps, Molecular Phylogenetics and Evolution, 13(1): 156 – 178, 1999.

Lipman D. J. and W. R. Pearson, Rapid and sensitive protein similarity searches, science, 227:1435 – 1441, 1985.

Kakuo, Susi., Asaoka, Kitamo. Human is a unique species among primates in terms of telomere length.’ Biochem Biophys Res Commun 263: 1999 308-314.

Liu, Xiaoming, and Yun-Xin Fu. “Test of Genetical Isochronism for Longitudinal Samples of DNA Sequences.” Genetics 176.1 (2007): 327.

Meyer, Anna. Hunting the Double Helix: How DNA Is Solving Puzzles of the Past. Crows Nest, N.S.W.: Allen & Unwin, 2005.

Miyamoto, Michael M., and Joel Cracraft, eds. Phylogenetic Analysis of DNA Sequences. New York: Oxford University Press, 2002.

Myers, E. W., An overview of Sequence Comparison Algorithms in Molecular Biology, TR 91-129, 1991.

Swanson, Bradley J., and Patrick J. Rusz. “Detection and Classification of Cougars in Michigan Using Low Copy DNA Sources.” The American Midland Naturalist 155.2 (2006): 363.

Tutton, Richard, and Oonagh Corrigan, eds. Donating and Exploiting DNA: Social and Ethical Aspects of Public Participation in Genetic Databases. New York: Routledge, 2004.

Wang, Jinliang. “A Coalescent-based Estimator of Admixture from DNA Sequences.” Genetics 173.3 (2006): 1679.

Yang, Hsin-Chou, Chia-Ching Pan, Richard C. Y Lu, and Cathy S. J Fann. “New Adjustment Factors and Sample Size Calculation in a DNA-pooling Experiment with Preferential Amplification.” Genetics 169.1 (2005): 399.

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