Animals comprise complex, dynamic, three dimensional arrays of cells which differ from each other in histological type, shape, size, location, and other characteristics. These differences-and the resulting higher order tissue/morphological structures that they in turn generate-ultimately derive from intricate patterns of gene expression that develop during embryogenesis. A deep understanding of these complex, quantitative changes in morphology and gene expression will require a detailed, precise description of morphological and expression dynamics at cellular resolution. We propose to create a quantitative, cellular resolution map of gene expression and morphology for all of embryo development for one of the most studied model animals: Drosophila melanogaster. This goal will extend our previous work which has established a suite of live and fixed embryo imaging and image analysis methods that have provided the first quantitative description of gene expression and morphology at cellular resolution of an intact early stage Drosophila embryo and have revealed previously unknown features about the biology of this system. The early stage blastoderm embryos analyzed in these initial studies, however, have a relatively simple structure that is comprised of a single layer of some 6000 cells surrounding a yolk. After the blastoderm stage-over the course of ten hours-three mitotic cycles, large cell motions and complex patterns of differentiation lead to the formation of over 70 cell types and all major larval organs. To accurately capture this great increase in complexity, we propose to make major improvements in our imaging and image segmentation strategies, establish learning based classification methods to assign cells to specific cell types and tissues, and develop more sophisticated visualization tools to allow exploration of the data. Our preliminary data show that it is possible to image all cells throughout Drosophila embryogenesis and suggest a way to create a morphological framework on which to quantitate gene expression. The availability of a qualitative cellular resolution atlas has been a boon to the analysis of C elegans over the last twenty years. Our proposed more sophisticated, quantitative, computational model of Drosophila embryogenesis will inevitably be at least as significant resources to the fly community and will open the way for data based, computational modeling of tissue formation and the associated gene regulatory networks.

Public Health Relevance

Our project to create a quantitative, cellular resolution map of gene expression and morphology of embryogenesis will produce tools which will significantly advance basic biological research. Converting an animal embryo into a computational atlas of its body plan, cell positions, cell fate and tissue locations, along with a cellular resolution map of gene expression, will provide a portable anatomical and expression atlas that can be dissected and observed by any researcher. This electronic embryonic atlas, will not only be an invaluable educational tool, but will allow cellular resolution anatomical analyses of anatomy in 3D, will shed light on the regulatory pathways, allow new types of computational systems biology and it will integrate anatomy with molecular developmental genetics.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM085298-04
Application #
8496822
Study Section
Microscopic Imaging Study Section (MI)
Program Officer
Hoodbhoy, Tanya
Project Start
2010-09-01
Project End
2014-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
4
Fiscal Year
2013
Total Cost
$477,178
Indirect Cost
$157,502
Name
Lawrence Berkeley National Laboratory
Department
Genetics
Type
Organized Research Units
DUNS #
078576738
City
Berkeley
State
CA
Country
United States
Zip Code
94720
Knowles, David W; Biggin, Mark D (2013) Building quantitative, three-dimensional atlases of gene expression and morphology at cellular resolution. Wiley Interdiscip Rev Dev Biol 2:767-79
Barron, Jonathan T; Arbeláez, Pablo; Keränen, Soile V E et al. (2013) Volumetric Semantic Segmentation using Pyramid Context Features. Proc IEEE Int Conf Comput Vis 2013:3448-3455
Knowles, David W (2012) Three-dimensional morphology and gene expression mapping for the Drosophila blastoderm. Cold Spring Harb Protoc 2012:150-61