MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses

DEVINE, JAY; VIDAL-GARCÍA, MARTA; LIU, WEI; NEVES, AMANDA; LO VERCIO, LUCAS D.; GREEN, REBECCA M.; RICHBOURG, HEATHER A.; MARCHINI, MARTA; UNGER, COLTON M.; NICKLE, AUDREY C.; RADFORD, BETHANY; YOUNG, NATHAN M.; GONZALEZ, PAULA N.; SCHULER, ROBERT E.; BUGACOV, ALEJANDRO; ROLIAN, CAMPBELL; PERCIVAL, CHRISTOPHER J.; WILLIAMS, TREVOR; NISWANDER, LEE; CALOF, ANNE L.; LANDER, ARTHUR D.; VISEL, AXEL; JIRIK, FRANK R.; CHEVERUD, JAMES M.; KLEIN, OPHIR D.; BIRNBAUM, RAMON Y.; MERRILL, AMY E.; ACKERMANN, REBECCA R.; GRAF, DANIEL; HEMBERGER, MYRIAM; DEAN, WENDY; FORKERT, NILS D.; MURRAY, STEPHEN A.; WESTERBERG, HENRIK; MARCUCIO, RALPH S.; HALLGRÍMSSON, BENEDIKT

Scientific Data

Nature Research

Año: 2022 vol. 9

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase (www.facebase.org, https://doi.org/10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph).