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A landmark-free morphometrics pipeline for high-resolution phenotyping: application to a mouse model of Down syndrome
Author(s) -
Nicolas Toussaint,
Yushi Redhead,
Marta VidalGarcía,
Lucas Lo Vercio,
Elizabeth Fisher,
Benedikt Hallgrímsson,
Victor L. J. Tybulewicz,
Julia A. Schnabel,
Jeremy Green
Publication year - 2021
Publication title -
development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.754
H-Index - 325
eISSN - 1477-9129
pISSN - 0950-1991
DOI - 10.1242/dev.188631
Subject(s) - morphometrics , landmark , biology , evolutionary biology , phenotype , craniofacial , allometry , population , skull , anatomy , computational biology , artificial intelligence , genetics , zoology , computer science , ecology , gene , demography , sociology
Characterising phenotypes often requires quantification of anatomical shape. Quantitative shape comparison (morphometrics) traditionally uses manually located landmarks and is limited by landmark number and operator accuracy. Here, we apply a landmark-free method to characterise the craniofacial skeletal phenotype of the Dp1Tyb mouse model of Down syndrome and a population of the Diversity Outbred (DO) mouse model, comparing it with a landmark-based approach. We identified cranial dysmorphologies in Dp1Tyb mice, especially smaller size and brachycephaly (front-back shortening), homologous to the human phenotype. Shape variation in the DO mice was partly attributable to allometry (size-dependent shape variation) and sexual dimorphism. The landmark-free method performed as well as, or better than, the landmark-based method but was less labour-intensive, required less user training and, uniquely, enabled fine mapping of local differences as planar expansion or shrinkage. Its higher resolution pinpointed reductions in interior mid-snout structures and occipital bones in both the models that were not otherwise apparent. We propose that this landmark-free pipeline could make morphometrics widely accessible beyond its traditional niches in zoology and palaeontology, especially in characterising developmental mutant phenotypes.

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