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Analysis of FOXO3 Gene Polymorphisms Associated with Human Longevity

  • Timothy A. Donlon
  • Philip M. C. Davy
  • Bradley J. WillcoxEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1890)

Abstract

Next-generation DNA sequencing has ushered in a new era of genotype-phenotype comparisons that have the potential to elucidate the genetic nature of complex traits. Since such methods rely on short sequence reads and since the human genome is composed largely of repetitive DNA elements larger than these read lengths many results cannot be mapped and are discarded, thus eliminating a large portion of the genome from analysis. Discerning associations in complex traits, such as longevity, will require either longer read lengths or methods to address these sequence complexities. Whole genome analysis, such as Genome Wide Association Studies (GWAS), also suffers from the repetitive nature of the human genome, as there exist many gaps in the availability of useable genetic markers, often in interesting regulatory regions. Methods are described here whereby some of these problems have been addressed by targeted DNA sequencing, full exploitation of available public databases, and a careful evaluation of genomic features where we use the FOXO3 gene as an example to identify functional variations and how they may relate to longevity.

Key words

Long-range DNA sequencing Long-range PCR Genome complexity Repetitive DNA 

References

  1. 1.
    Schmid CW, Deininger PL (1979) Sequence organization of the human genome. Cell 6(3):345–358CrossRefGoogle Scholar
  2. 2.
    Batzer MA, Deininger PL (2002) Alu repeats and human genomic diversity. Nat Rev Genet 3(5):370–379CrossRefGoogle Scholar
  3. 3.
    Lander ES (2011) Initial impact of the sequencing of the human genome. Nature 470:187–197CrossRefGoogle Scholar
  4. 4.
    Donlon TA, Curb JD, He Q, Grove JS, Masaki KH, Rodriguez B, Elliott A, Willcox DC, Willcox BJ (2012) FOXO3 gene variants and human aging: coding variants may not be key players. J Gerontol A Biol Sci Med Sci 67(11):1132–1139CrossRefGoogle Scholar
  5. 5.
    Donlon TA, Morris BJ, Chen R, Masaki KH, Allsopp RC, Willcox DC, Elliott A, Willcox BJ (2017) FOXO3 longevity interactome on chromosome 6. Aging Cell 6(5):1016–1025CrossRefGoogle Scholar
  6. 6.
    Cheng S, Fockler C, Barnes WM, Higuchi R (1994) Effective amplification of long targets from cloned inserts and human genomic DNA. Proc Natl Acad Sci U S A 91(12):5695–5699CrossRefGoogle Scholar
  7. 7.
    Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, Karczewski KJ, Park J, Hitz BC, Weng S, Cherry JM, Snyder M (2012) Annotation of functional variation in personal genomes using RegulomeDB. Genome Res 22(9):1790–1797CrossRefGoogle Scholar
  8. 8.
    Ward LD, Kellis M (2012) HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res 40(Database issue):D930–D934CrossRefGoogle Scholar
  9. 9.
    Kheradpour P, Kellis M (2013) Systematic discovery and characterization of regulatory motifs in ENCODE TF binding experiments. Nucleic Acids Res 42(15):2976–2987PubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Timothy A. Donlon
    • 1
    • 2
  • Philip M. C. Davy
    • 3
  • Bradley J. Willcox
    • 1
    • 4
    Email author
  1. 1.Department of Research, Honolulu Heart Program/Honolulu-Asia Aging Study (HAAS)Kuakini Medical CenterHonoluluUSA
  2. 2.John A. Burns School of MedicineUniversity of HawaiiHonoluluUSA
  3. 3.Institute for Biogenesis ResearchUniversity of HawaiiHonoluluUSA
  4. 4.Department of Geriatric Medicine, John A. Burns School of MedicineUniversity of HawaiiHonoluluUSA

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