The “Down syndrome critical region” (DSCR) is a chromosome 21 segment purported to contain genes responsible for many features of Down syndrome (DS), including craniofacial dysmorphology. We used chromosome engineering to create mice that were trisomic or monosomic for only the mouse chromosome segment orthologous to the DSCR and assessed dysmorphologies of the craniofacial skeleton that show direct parallels with DS in mice with a larger segmental trisomy. The DSCR genes were not sufficient and were largely not necessary to produce the facial phenotype. These results refute specific predictions of the prevailing hypothesis of gene action in DS.

Down syndrome (DS) is the most common genetic cause of mental retardation and affects many aspects of brain development. DS individuals exhibit an overall reduction in brain size with a disproportionately greater reduction in cerebellar volume. The Ts65Dn mouse is segmentally trisomic for the distal 12–15 Mb of mouse chromosome 16, a region that shows perfect conserved linkage with human chromosome 21, and therefore provides a genetic model for DS. In this study, high resolution magnetic resonance imaging and histological analysis demonstrate precise neuro‐ anatomical parallels between the DS and the Ts65Dn cerebellum. Cerebellar volume is significantly reduced in Ts65Dn mice due to reduction of both the internal granule layer and the molecular layer of the cerebellum. Granule cell number is further reduced by a decrease in cell density in the internal granule layer. Despite these changes in Ts65Dn cerebellar structure, motor deficits have not been detected in several tests. Reduction in granule cell density in Ts65Dn mice correctly predicts an analogous pathology in humans; a significant reduction in granule cell density in the DS cerebellum is reported here for the first time. The candidate region of genes on chromosome 21 affecting cerebellar development in DS is therefore delimited to the subset of genes whose orthologs are at dosage imbalance in Ts65Dn mice, providing the first localization of genes affecting a neuroanatomical phenotype in DS. The application of this model for analysis of developmental perturbations is extended by the accurate prediction of DS cerebellar phenotypes.

Nontraditional or geometric morphometric methods have found wide application in the biological sciences, especially in anthropology, a field with a strong history of measurement of biological form. Controversy has arisen over which method is the “best” for quantifying the morphological difference between forms and for making proper statistical statements about the detected differences. This paper explains that many of these arguments are superfluous to the real issues that need to be understood by those wishing to apply morphometric methods to biological data. Validity, the ability of a method to find the correct answer, is rarely discussed and often ignored. We explain why demonstration of validity is a necessary step in the evaluation of methods used in morphometrics. Focusing specifically on landmark data, we discuss the concepts of size and shape, and reiterate that since no unique definition of size exists, shape can only be recognized with reference to a chosen surrogate for size. We explain why only a limited class of information related to the morphology of an object can be known when landmark data are used. This observation has genuine consequences, as certain morphometric methods are based on models that require specific assumptions, some of which exceed what can be known from landmark data. We show that orientation of an object with reference to other objects in a sample can never be known, because this information is not included in landmark data. Consequently, a descriptor of form difference that contains information on orientation is flawed because that information does not arise from evidence within the data, but instead is a product of a chosen orientation scheme. To illustrate these points, we apply superimposition, deformation, and linear distance‐based morphometric methods to the analysis of a simulated data set for which the true differences are known. This analysis demonstrates the relative efficacy of various methods to reveal the true difference between forms. Our discussion is intended to be fair, but it will be obvious to the reader that we favor a particular approach. Our bias comes from the realization that morphometric methods should operate with a definition of form and form difference consistent with the limited class of information that can be known from landmark data. Answers based on information that can be known from the data are of more use to biological inquiry than those based on unjustifiable assumptions. Yrbk Phys Anthropol 45:63–91, 2002.