Multispecies Ovary Tissue Histology Electronic Repository


Project Abstract

The Multispecies Ovary Tissue Histology Electronic Repository (MOTHER) provides public access to digitized microscopic images of ovary tissues along with information that ensures image integrity and quality. Currently, there is no electronic repository of ovary histology slides that preserves these valuable research collections for future generations. MOTHER is a web-accessible, open resource for scientists, educators, and the public to stimulate collaboration and scientific research. Educators may use the slide images in a range of courses from reproductive biology to teaching computerized image analysis.


Reproduction is vital for sustaining all living organisms, and multiple strategies exist among different species. The long-term goals of MOTHER are to (i) increase reproductive science capacity and infrastructure; and (ii) serve as a resource for educators. MOTHER builds upon existing openly available resources, e.g., the Open Science Framework, to foster data sharing and collaboration. Metadata about each image ensures image quality, and provides additional details about the animal and experimental design. An initial set of species (i.e., hundreds of vertebrate species including non-human primates, other mammals, fishes, and amphibians) will be included in MOTHER with a long-term goal that scientists will contribute data from additional species. Value-added data segmentation results will be made available through MOTHER along with the procedures used to generate the results. Upon completion, MOTHER will facilitate comparative studies of ovarian development and folliculogenesis to better understand: (i) reproductive strategies across species and inspire new ideas for ensuring the survival of threatened and endangered species; (ii) the similarities and differences between vertebrate species at the organ, tissue and cellular level; and (iii) mechanisms that can be encoded in predictive mathematical/computational models that can extract additional value from the existing data and may lead to the reduced use of experimental animals. Biology is increasingly dependent upon quantitative data analysis, and MOTHER should inspire computational thinking in biology broadly, while developing specific skills in microscopy, computer programming, and data and image analysis.



Personnel

  • Karen H Watanabe, PhD, School of Mathematical and Natural Sciences, New College of Interdisciplinary Arts and Sciences, Arizona State University, Glendale, Arizona.

  • Suzanne W Dietrich, PhD, School of Mathematical and Natural Sciences, New College of Interdisciplinary Arts and Sciences, Arizona State University, Glendale, Arizona.

  • James P Sluka, PhD, Biocomplexity Institute. Indiana University, Bloomington, IN.

  • Mary B Zelinski, PhD, Division of Reproductive & Developmental Sciences, Oregon National Primate Research Center, Beaverton, OR

Project Plan


Funding

The MOTHER DB is funded by grant "CIBR Multispecies Ovary Tissue Histology Electronic Repository (MOTHER)" from the National Science Foundation (NSF DBI-2054061, 2021 - 2024).


Disclaimer: Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.