Modeling 3D Facial Shape from DNA


The face is perhaps the most inherently fascinating and aesthetic feature of the human body. It is a principle subject of art throughout human history and across cultures and populations. It provides the most significant means by which we communicate our emotions and intentions in addition to health, sex, and age. And yet features such as the strength of the brow ridge, the spacing between the eyes, the width of the nose, and the shape of the philtrum are largely scientifically unexplained. Here, we use a novel method to measure face shape in population samples with mixed West African and European ancestry from three locations (United States, Brazil, and Cape Verde). We show that facial variation with regard to sex, ancestry, and genes can be systematically studied with our methods, allowing us to lay the foundation for predictive modeling of faces. Such predictive modeling could be forensically useful; for example, DNA left at crime scenes could be tested and faces predicted in order to help to narrow the pool of potential suspects. Further, our methods could be used to predict the facial features of descendants, deceased ancestors, and even extinct human species. In addition, these methods could prove to be useful diagnostic tools.


Vyšlo v časopise: Modeling 3D Facial Shape from DNA. PLoS Genet 10(3): e32767. doi:10.1371/journal.pgen.1004224
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pgen.1004224

Souhrn

The face is perhaps the most inherently fascinating and aesthetic feature of the human body. It is a principle subject of art throughout human history and across cultures and populations. It provides the most significant means by which we communicate our emotions and intentions in addition to health, sex, and age. And yet features such as the strength of the brow ridge, the spacing between the eyes, the width of the nose, and the shape of the philtrum are largely scientifically unexplained. Here, we use a novel method to measure face shape in population samples with mixed West African and European ancestry from three locations (United States, Brazil, and Cape Verde). We show that facial variation with regard to sex, ancestry, and genes can be systematically studied with our methods, allowing us to lay the foundation for predictive modeling of faces. Such predictive modeling could be forensically useful; for example, DNA left at crime scenes could be tested and faces predicted in order to help to narrow the pool of potential suspects. Further, our methods could be used to predict the facial features of descendants, deceased ancestors, and even extinct human species. In addition, these methods could prove to be useful diagnostic tools.


Zdroje

1. CarlsonDS (2005) Theories of craniofacial growth in the postgenomic era. Seminars in Orthodontics 11: 172–183.

2. Sperber GH (2001) Craniofacial development. (Decker Inc., Ontario, B.C.).

3. WilliamsSE, SliceDE (2010) Regional shape change in adult facial bone curvature with age. American Journal of Physical Anthropology 143: 437–447.

4. CoussensAK, van DaalA (2005) Linkage disequilibrium analysis identifies an FGFR1 haplotype-tag SNP associated with normal variation in craniofacial shape. Genomics 85: 563–573.

5. LiuF, van der LijnF, SchurmannC, ZhuG, ChakravartyMM, et al. (2012) A genome-wide association study identifies five loci influencing facial morphology in Europeans. PLoS Genetics 8: e1002932.

6. BoehringerS, van der LijnF, LiuF, GüntherM, SinigerovaS, et al. (2011) Genetic determination of human facial morphology: links between cleft-lips and normal variation. European Journal of Human Genetics 19: 1192–1197.

7. PaternosterL, ZhurovAI, TomaAM, KempJP, St PourcainB, et al. (2012) Genome-wide association study of three-dimensional facial morphology identifies a variant in PAX3 associated with nasion position. American Journal of Human Genetics 90: 478–485.

8. ClaesP, WaltersM, VandermeulenD, ClementJG (2011) Spatially-dense 3D facial asymmetry assessment in both typical and disordered growth. Journal of Anatomy 219: 444–455.

9. ClaesP, WaltersM, ClementJ (2012) Improved facial outcome assessment using a 3D anthropometric mask. International Journal of Oral and Maxillofacial Surgery 41: 324–330.

10. AbdiH (2010) Partial least squares regression and projection on latent structure regression (PLS Regression). Wiley Interdisciplinary Reviews: Computational Statistics 2: 97–106.

11. HalderI, ShriverMD, ThomasM, FernandezJR, FrudakisT (2008) A panel of ancestry informative markers for estimating individual biogeographical ancestry and admixture from four continents: utility and applications. Human Mutation 29: 648–658.

12. LongJC (1991) The genetic structure of admixed populations. Genetics 127: 417–428.

13. PfaffCL, ParraEJ, BonillaC, HiesterK, McKeiguePM, et al. (2001) Population structure in admixed populations: effect of admixture dynamics on the pattern of linkage disequilibrium. American Journal of Human Genetics 68: 198–207.

14. McKeiguePM (2005) Prospects for admixture mapping of complex traits. American Journal of Human Genetics 76: 1–7.

15. HoggartCJ, ParraEJ, ShriverMD, BonillaC, KittlesRA, et al. (2003) Control of confounding of genetic associations in stratified populations. American Journal of Human Genetics 72: 1492–1504.

16. HoggartCJ, ShriverMD, KittlesRA, ClaytonDG, McKeiguePM (2004) Design and analysis of admixture mapping studies. American Journal of Human Genetics 74: 965–978.

17. Claes P (2007) A robust statistical surface registration framework using implicit function representations-Application in craniofacial reconstruction. Ktholieke Universiteit Leuven. Available: https://lirias.kuleuven.be/handle/123456789/174028).

18. MardiaK, BooksteinFL, MoretonIJ (2000) Statistical assessment of bilateral symmetry of shapes. Biometrika 87: 285–300.

19. KlingenbergCP, BarluengaM, MeyerA (2002) Shape analysis of symmetric structures: quantifying variation among individuals and asymmetry. Evolution 56: 1909–1920.

20. WrayNR, YangJ, GoddardME, VisscherPM (2010) The genetic interpretation of area under the ROC curve in genomic profiling. PLoS Genetics 6: e1000864.

21. WebsterMA, KapingD, MizokamiY, DuhamelP (2004) Adaptation to natural facial categories. Nature 428: 557–561.

22. KlimentidisYC, ShriverMD (2009) Estimating genetic ancestry proportions from faces. PLoS One 4: e4460.

23. BelezaS, JohnsonNA, CandilleSI, AbsherDM, CoramMA, et al. (2013) Genetic architecture of skin and eye color in an African-European admixed population. PLoS Genetics 9: e1003372.

24. HamoshA, ScottAF, AmbergerJS, BocchiniCA, McKusickVA (2005) Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Research D514–517.

25. SongL, LiY, WangK, WangYZ, MolotkovA, GaoL, et al. (2009) Lrp6-mediated canonical Wnt signaling is required for lip formation and fusion. Development 136: 3161–171.

26. TangH, PengJ, WangP, RischNJ (2005) Estimation of individual admixture: analytical and study design considerations. Genetic Epidemiology 28: 289–301.

27. The International HapMap Consortium (2003) The International HapMap Project. Nature 426: 789–796.

28. HawksJ, WangET, CochranGM, HarpendingHC, MoyzisHK (2007) Recent acceleration of human adaptive evolution. Proceedings of the National Academy of Sciences of the United States of America 104: 20753–20758.

29. ShriverMD, KennedyGC, ParraEJ, LawsonHA, SonparV, et al. (2004) The genomic distribution of population substructure in four populations using 8,525 autosomal SNPs. Human Genomics 1: 274–286.

30. KauerMO, DieringerD, SchlöttererC (2003) A microsatellite variability screen for positive selection associated with the “out of Africa” habitat expansion of Drosophila melanogaster. Genetics 165: 1137–1148.

31. TajimaF (1989) Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123: 585–595.

32. KlingenbergCP, McIntyreGS (1998) Geometric morphometrics of developmental instability: analyzing patterns of fluctuating asymmetry with Procrustes methods. Evolution 52: 1363–1375.

33. RohlfFJ, SliceD (1990) Extensions of the Procrustes Method for the Optimal Superimposition of Landmarks. Systematic Zoology 39: 40–59.

34. MitteroeckerP, GunzP (2009) Advances in Geometric Morphometrics. Evolutionary Biology 36: 235–247.

35. Kimmerle EH, Jantz R (2005) Secular Trends in Craniofacial Asymmetry Studied by Geometric Morphometry and Generalized Procrustes Methods. In: Slice D, editor. Modern Morphometrics in Physical Anthropology. pp 247–263.

36. PalmerAR (1994) Waltzing with Asymmetry Is fluctuating asymmetry a powerful new tool for biologists or just an alluring new dance step?? BioScience 46: 518–532.

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Genetika Reprodukčná medicína

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PLOS Genetics


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