All Title Author
Keywords Abstract


Mathematical Modeling the Biology of Single Nucleotide Polymorphisms (SNPs) in Whole Genome Adaptation

DOI: 10.4236/abb.2018.910036, PP. 520-533

Keywords: Genome-Environment Interactions, Genomic Adaptation, SNP Functional Correlations

Full-Text   Cite this paper   Add to My Lib

Abstract:

As a living information and communications system, the genome encodes patterns in single nucleotide polymorphisms (SNPs) reflecting human adaptation that optimizes population survival in differing environments. This paper mathematically models environmentally induced adaptive forces that quantify changes in the distribution of SNP frequencies between populations. We make direct connections between biophysical methods (e.g. minimizing genomic free energy) and concepts in population genetics. Our unbiased computer program scanned a large set of SNPs in the major histocompatibility complex region and flagged an altitude dependency on a SNP associated with response to oxygen deprivation. The statistical power of our double-blind approach is demonstrated in the flagging of mathematical functional correlations of SNP information-based potentials in multiple populations with specific environmental parameters. Furthermore, our approach provides insights for new discoveries on the biology of common variants. This paper demonstrates the power of biophysical modeling of population diversity for better understanding genome-environment interactions in biological phenomenon.

References

[1]  Sachidanandam, R., Weissman, D., Schmidt, S.C., Kakol, J.M., Stein, L.D., Marth, G., et al. (2001) A Map of Human Genome Sequence Variation Containing 1.42 Million Single Nucleotide Polymorphisms. Nature, 409, 928-933.
https://doi.org/10.1038/35057149
[2]  Lindesay, J., Mason, T.E., Hercules, W. and Dunston, G.M. (2014) Development of Genodynamic Metrics Forexploring the Biophysics of DNA Polymorphisms. Journal of Computational Biology and Bioinformatics Research, 6, 1-14.
[3]  Barrett, J.C., Fry, B., Maller, J. and Daly, M.J. (2005) Haploview: Analysis and Visualization of LD and Haplotype Maps. Bioinformatics, 21, 263-265.
https://doi.org/10.1093/bioinformatics/bth457
[4]  Lindesay, J., Mason, T.E., Ricks-Santi, L., Hercules, W., Kurian, P. and Dunston, G.M. (2012) A New Biophysical Metric for Interrogating the Information Content in Human Genome Sequence Variation: Proof of Concept. Journal of Computational Biology and Bioinformatics Research, 4, 15-22.
[5]  Lindesay, J. (2013) Foundations of Quantum Gravity. Cambridge University Press, Cambridge, UK.
https://doi.org/10.1017/CBO9780511919909
[6]  International HapMap3 Consortium (2010) Integrating Common and Rare Genetic Variation in Diverse Human Populations. Nature, 467, 52-58.
[7]  Herman, J.R., Krotkov, N., Celarier, N.E., Larko, D. and Labow, G. (1999) Distribution of UV Radiation at the Earth’s Surface from TOMS-Measured UV-Backscattered Radiances. Journal of Geophysical Research: Atmospheres, 104, 12059-12076.
https://doi.org/10.1029/1999JD900062
[8]  Globe Task Team (1999) The Global Land One-Kilometer Base Elevation (GLOBE) Digital Elevation Model, Version 1.0.
https://www.mgdc.noaa.gov/mgg/topo/globe.html
[9]  World Health Organization (2008) World Malaria Report 2008. Geneva World Health Organization, Switzerland. http://www.who.int/malaria/publications/atoz/9789241563697/en/
[10]  Grocott, M.P.W., Martin, D.S., Levett, D.Z., McMorrow, R., Windsor, J. and Montgomery, H.E. (2009) Arterial Blood Gases and Oxygen Content in Climbers on Mount Everest. The New England Journal of Medicine, 360, 140-149.
https://doi.org/10.1056/NEJMoa0801581
[11]  Phng, L.K. and Gerhardt, H. (2009) Angiogenesis: A Team Effort Coordinated by Notch. Developmental Cell, 16, 196-208.
https://doi.org/10.1016/j.devcel.2009.01.015
[12]  Gerhardt, H., Golding, M., Fruttiger, M., Ruhrberg, C., Lundkvist, A., Abramson, A., et al. (2003) VEGF Guides Angiogenic Sprouting Utilizing Endothelial Tip Cell Filopedia. The Journal of Cell Biology, 161, 1163-1177.
https://doi.org/10.1083/jcb.200302047
[13]  Hoffman, J.J. and Iruela-Arispe, M.L. (2007) Notch Signaling in Blood Vessels: Who Is Talking to Whom about What? Circulation Research, 100, 1556-1568.
https://1161/01.RES.0000266408.42939.e4
[14]  Farve, C.J., Mancuso, M., Maas, K., McLean, J.W., Baluk, P. and McDonald, D.M. (2003) Expression of Genes Involved in Vascular Development and Angiogenesis in Endothelial Cells of Adult Lung. American Journal of Physiology-Heart and Circulatory Physiology, 285, H1917-H1938.
https://doi.org/10.1152/ajpheart.00983.2002
[15]  Villa, N., Walker, L., Lindsell, C.E., Gasson, J., Iruela-Arispe, M.L. and Weinmaster, G. (2003) Vascular Expression of Notch Pathway Receptors and Ligands Is Restricted to Arterial Vessels. Mechanisms of Development, 108, 161-164.
https://doi.org/10.1016/S0925-4773(01)00469-5
[16]  Carlson, T.R., Yan, Y., Wu, X., Lam, M.T., Tang, G.L., Beverly, L.J., et al. (2005) Endothelial Expression of Constitutively Active Notch 4 Elicits Reversible Arteriovenousmal Formations in Adult Mice. Proceedings of the National Academy of Sciences of the United States of America, 102, 9884-9889.
https://doi.org/10.1073/pnas.0504391102
[17]  Kim, Y.H., Hu, H., Guevara-Gallardo, S., Lam, M.T., Fong, S.Y. and Wang, R.A. (2008) Artery and Vein Size Is Balanced by Notch and Ephrin B2/EphB4 during Angiogenesis. Development, 135, 3755-3764.
https://doi.org/10.1242/dev.022475
[18]  Leong, K.G., Hu, X., Li, L., Noseda, M., Larrivee, B., Hull, C., Hood, L., Wong, F.A. and Karsan, A. (2002) Activated Notch 4 Inhibits Angiogenesis: Role of 1-Integrin Activation. Molecular and Cellular Biology, 22, 2830-2841.
https://doi.org/10.1128/MCB.22.8.2830-2841.2002

Full-Text

comments powered by Disqus