Surface landmark quantification of embryonic mouse craniofacial morphogenesis

BMC Developmental Biology

Benedikt Hallgrímsson³  Ralph Marcucio²  Rebecca Green¹  Christopher J Percival³ 

[1] Department of Craniofacial Biology and Program in Reproductive Sciences, University of Colorado – Denver, Denver, CO 80045, USA;Department of Orthopaedic Surgery, The Orthopaedic Trauma Institute, UCSF School of Medicine, San Francisco, CA 94143, USA;Department of Cell Biology and Anatomy, Alberta Children’s Hospital Institute for Child and Maternal Health, The McCaig Bone and Joint Institute, University of Calgary, Calgary, AB T2N 4N1, Canada

关键词: Micro-CT;    3D imaging;    Mouse embryo;    Craniofacial morphogenesis;    Facial prominences;    Landmark error;    Morphometrics;   

Others  :  1084964
DOI  :  10.1186/1471-213X-14-31

 received in 2014-03-13, accepted in 2014-07-01,  发布年份 2014

【 摘 要 】

Background

Morphometric quantification of subtle craniofacial variation in studies of experimentally modified embryonic mice has proved valuable in determining the effects of developmental perturbations on craniofacial morphogenesis. The direct comparison of landmark coordinate data from embryos of many different mouse strains and mouse models can advance our understanding of the bases for craniofacial variation. We propose a standard set of craniofacial surface landmarks, for use with embryonic day (E) 10.5-12.5 mice, to serve as the foundation for this type of data compilation and analysis. We quantify the intra- and inter-observer landmark placement variation associated with each landmark and determine how the results of a simple ontogenetic analysis might be influenced by selection of landmark set.

Results

Intraobserver landmark placement error for experienced landmarkers generally remains below 0.1 mm, with some landmarks exhibiting higher values at E11.5 and E12.5. Interobserver error tends to increase with embryonic age and those landmarks defined on wide inflections of curves or facial processes exhibit the highest error. Landmarks with highest intra- or inter-observer are identified and we determine that their removal from the dataset does not significantly change the vectors of craniofacial shape change associated with an ontogenetic regression.

Conclusions

Our quantification of landmark placement error demonstrates that it is preferable for a single observer to identify all landmark coordinates within a single study and that significant training and experience are necessary before a landmarker can produce data for use in larger meta-analyses. However, we are confident that this standard landmark set, once landmarks with higher error are removed, can serve as a foundation for a comparative dataset of facial morphogenesis across various mouse populations to help identify the developmental bases for phenotypic variation in the craniofacial complex.

【 授权许可】

   
2014 Percival et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

【 参考文献 】

• [1]Klingenberg CP: Morphometrics and the role of the phenotype in studies of the evolution of developmental mechanisms. Gene 2002, 287:3-10.
• [2]Cooper WJ, Albertson RC: Quantification and variation in experimental studies of morphogenesis. Dev Biol 2008, 321:295-302.
• [3]Hallgrímsson B, Boughner JC, Turinsky A, Parsons TE, Logan C, Sensen CW: Geometric Morphometrics and the Study of Development. In Advanced Imaging Biology and Medicine. Edited by Sensen CW, Hallgrímsson B. Berlin: Springer-Verlag; 2009:319-336.
• [4]Albertson RC, Yelick PC: Fgf8 haploinsufficiency results in distinct craniofacial defects in adult zebrafish. Dev Biol 2007, 306:505-515.
• [5]Parsons TE, Kristensen E, Hornung L, Diewert VM, Boyd SK, German RZ, Hallgrimsson B: Phenotypic variability and craniofacial dysmorphology: increased shape variance in a mouse model for cleft lip. J Anat 2008, 212:135-143.
• [6]Boughner JC, Wat S, Diewert VM, Young NM, Browder LW, Hallgrímsson B: Short-faced mice and developmental interactions between the brain and the face. J Anat 2008, 213:646-662.
• [7]Young NM, Chong HJ, Hu D, Hallgrímsson B, Marcucio RS: Quantitative analyses link modulation of sonic hedgehog signaling to continuous variation in facial growth and shape. Development 2010, 137:3405-3409.
• [8]Cooper WJ, Wirgau RM, Sweet EM, Albertson RC: Deficiency of zebrafish fgf20a results in aberrant skull remodeling that mimics both human cranial disease and evolutionarily important fish skull morphologies. Evol Dev 2013, 15:426-441.
• [9]Percival CJ, Huang Y, Jabs EW, Li R, Richtsmeier JT: Embryonic craniofacial bone volume and bone mineral density in Fgfr2+/P253R and nonmutant mice. Dev Dyn 2014, 243:541-551.
• [10]Wang Y, Xiao R, Yang F, Karim BO, Iacovelli AJ, Cai J, Lerner CP, Richtsmeier JT, Leszl JM, Hill CA: Abnormalities in cartilage and bone development in the apert syndrome FGFR2+/S252W mouse. Development 2005, 132:3537-3548.
• [11]Perlyn CA, DeLeon VB, Babbs C, Govier D, Burell L, Darvann T, Kreiborg S, Morriss-Kay G: The craniofacial phenotype of the crouzon mouse: analysis of a model for syndromic craniosynostosis using three-dimensional MicroCT. Cleft Palate Craniofac J 2006, 43:740-748.
• [12]Hill CA, Reeves RH, Richtsmeier JT: Effects of aneuploidy on skull growth in a mouse model of down syndrome. J Anat 2007, 210:394-405.
• [13]Lieberman DE, Hallgrímsson B, Liu W, Parsons TE, Jamniczky HA: Spatial packing, cranial base angulation, and craniofacial shape variation in the mammalian skull: testing a new model using mice. J Anat 2008, 212:720-735.
• [14]Martínez-Abadías N, Percival C, Aldridge K, Hill C, Ryan T, Sirivunnabood S, Wang Y, Jabs E, Richtsmeier J: Beyond the closed suture in apert mouse models: evidence of primary effects of FGFR2 signaling on facial shape at P0. Dev Dyn 2010, 239:3058-3071.
• [15]Percival CJ, Wang Y, Zhou X, Jabs EW, Richtsmeier JT: The effect of a beare-stevenson syndrome Fgfr2 Y394C mutation on early craniofacial bone volume and relative bone mineral density in mice. J Anat 2012, 221:434-442.
• [16]Hu D, Marcucio RS, Helms JA: A zone of frontonasal ectoderm regulates patterning and growth in the face. Development 2003, 130:1749-1758.
• [17]Szabo-Rogers HL, Smithers LE, Yakob W, Liu KJ: New directions in craniofacial morphogenesis. Dev Biol 2010, 341:84-94.
• [18]Dixon MJ, Marazita ML, Beaty TH, Murray JC: Cleft lip and palate: understanding genetic and environmental influences. Nat Rev Genet 2011, 12:167-178.
• [19]Young NM, Hu D, Lainoff AJ, Smith FJ, Diaz R, Tucker AS, Trainor PA, Schneider RA, Hallgrímsson B, Marcucio RS: Embryonic bauplans and the developmental origins of facial diversity and constraint. Development 2014, 141:1059-1063.
• [20]Chong HJ, Young NM, Hu D, Jeong J, McMahon AP, Hallgrimsson B, Marcucio RS: Signaling by SHH rescues facial defects following blockade in the brain. Dev Dyn 2012, 241:247-256.
• [21]Smith FJ, Hu D, Young NM, Lainoff AJ, Jamniczky HA, Maltepe E, Hallgrimsson B, Marcucio R: The effect of hypoxia on facial shape variation and disease phenotypes. Dis Model Mech 2013, 6:915-924.
• [22]Li X, Young NM, Tropp S, Hu D, Xu Y, Hallgrímsson B, Marcucio RS: Quantification of shape and cell polarity reveals a novel mechanism underlying malformations resulting from related FGF mutations during facial morphogenesis. Hum Mol Genet 2013, 22:5160-5172.
• [23]Young NM, Wat S, Diewert VM, Browder LW, Hallgrímsson B: Comparative morphometrics of embryonic facial morphogenesis: implications for cleft-lip etiology. Anat Rec 2007, 290:123-139.
• [24]Schmidt EJ, Parsons TE, Jamniczky HA, Gitelman J, Trpkov C, Boughner JC, Logan CC, Sensen CW, Hallgrímsson B: Micro-computed tomography-based phenotypic approaches in embryology: procedural artifacts on assessments of embryonic craniofacial growth and development. BMC Dev Biol 2010, 10:1-14.
• [25]Parsons TE, Schmidt EJ, Boughner JC, Jamniczky HA, Marcucio RS, Hallgrímsson B: Epigenetic integration of the developing brain and face. Dev Dyn 2011, 240:2233-2244.
• [26]Hochheiser H, Aronow BJ, Artinger K, Beaty TH, Brinkley JF, Chai Y, Clouthier D, Cunningham ML, Dixon M, Donahue LR, Fraser SE, Hallgrimsson B, Iwata J, Klein O, Marazita ML, Murray JC, Murray S, Pardo-Manuel de Villena F, Postlethwait J, Potter S, Shapiro L, Spritz R, Visel A, Weinberg SM, Trainor PA: The FaceBase consortium: a comprehensive program to facilitate craniofacial research. Dev Biol 2011, 355:175-182.
• [27]Houle D, Govindaraju DR, Omholt S: Phenomics: the next challenge. Nat Rev Genet 2010, 11:855-866.
• [28]Bookstein FL: Morphometric Tools for Landmark Data: Geometry and Biology. Cambridge, UK: Cambridge University Press; 1991.
• [29]Lele S, Richtsmeier JT: An Invariant Approach to Statistical Analysis of Shapes. London: Chapman & Hall-CR Press; 2001.
• [30]Zelditch M, Swiderski D, Sheets DH, Fink WL: Geometric Morphometrics for Biologists: A Primer. San Diego: Elsevier Academic Press; 2004.
• [31]Yamakado M, Yohro T: Subdivision of mouse vibrissae on an embryological basis, with descriptions of variations in the number and arrangement of sinus hairs and cortical barrels in BALB/c (nu/+; nude, nu/nu) and hairless (hr/hr) strains. Am J Anat 1979, 155:153-173.
• [32]Van Exan R, Hardy M: A spatial relationship between innervation and the early differentiation of vibrissa follicles in the embryonic mouse. J Anat 1980, 131:643-656.
• [33]Gunz P, Mitteroecker P, Bookstein FL: Semilandmarks in Three Dimensions. In Modern Morphometrics in Physical Anthropology. New York: Kluwer Academic/Plenum Publishers; 2005:73-98.
• [34]Kaufman MH: The Atlas of Mouse Development. London; Tokyo: Academic Press; 1992.
• [35]Kristensen E, Parsons TE, Hallgrímsson B, Boyd SK: A novel 3-D image-based morphological method for phenotypic analysis. IEEE Trans Biomed Eng 2008, 55:2826-2831.
• [36]Ólafsdóttir H, Darvann TA, Hermann NV, Oubel E, Ersbøll BK, Frangi AF, Larsen P, Perlyn CA, Morriss-Kay GM, Kreiborg S: Computational mouse atlases and their application to automatic assessment of craniofacial dysmorphology caused by the crouzon mutation Fgfr2C342Y. J Anat 2007, 211:37-52.
• [37]Wilamowska K, Wu J, Heike C, Shapiro L: Shape-based classification of 3D facial data to support 22q11. 2DS craniofacial research. J Digit Imaging 2012, 25:400-408.
• [38]Liu X, Mio W, Shi Y, Dinov I, Liu X, Leporé N, Leporé F, Fortin M, Voss P, Lassonde M, Thompson PM: Models of Normal Variation and Local Contrasts in Hippocampal Anatomy. In Models Norm Var Local Contrasts Hippocampal Anat MICCAI 2008 Lect Notes Comput Sci. Volume 5242. Heidelberg: Springer-Verlag Berlin; 2008:407-415.
• [39]Hammond P: The use of 3D face shape modelling in dysmorphology. Arch Child 2007, 92:1120-1126.
• [40]Claes P, Walters M, Vandermeulen D, Clement JG: Spatially-dense 3D facial asymmetry assessment in both typical and disordered growth. J Anat 2011, 219:444-455.
• [41]Guo JG, Mei X, Tang K: Automatic landmark annotation and dense correspondence registration for 3D human facial images. BMC Bioinformatics 2013, 14:1-12.
• [42]MeshLab Visual Computing Lab – ISTI – CNR[http://meshlab.sourceforge.net webcite]
• [43]Klingenberg CP: MorphoJ: an integrated software package for geometric morphometrics. Mol Ecol Resour 2011, 11:353-357.
• [44]Drake AG, Klingenberg CP: The pace of morphological change: historical transformation of skull shape in St Bernard dogs. Proc R Soc B Biol Sci 2008, 275:71-76.
• [45]R Developmental Core Team: R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2008.