@article {2149, title = {A 3D digital atlas of C. elegans and its application to single-cell analyses.}, journal = {Nature Methods}, volume = {6}, year = {2009}, month = {2009 Sep}, pages = {667-72}, abstract = {

We built a digital nuclear atlas of the newly hatched, first larval stage (L1) of the wild-type hermaphrodite of Caenorhabditis elegans at single-cell resolution from confocal image stacks of 15 individual worms. The atlas quantifies the stereotypy of nuclear locations and provides other statistics on the spatial patterns of the 357 nuclei that could be faithfully segmented and annotated out of the 558 present at this developmental stage. We then developed an automated approach to assign cell names to each nucleus in a three-dimensional image of an L1 worm. We achieved 86\% accuracy in identifying the 357 nuclei automatically. This computational method will allow high-throughput single-cell analyses of the post-embryonic worm, such as gene expression analysis, or ablation or stimulation of cells under computer control in a high-throughput functional screen.

}, keywords = {Animals, Automatic Data Processing, Biological, Caenorhabditis elegans, Cell Lineage, Cell Nucleus, Models}, issn = {1548-7105}, doi = {10.1007/s12021-010-9090-x}, author = {Long, Fuhui and Peng, Hanchuan and Liu, Xiao and Kim, Stuart K and Myers, Eugene} } @article {2697, title = {Analysis of cell fate from single-cell gene expression profiles in C. elegans.}, journal = {Cell}, volume = {139}, year = {2009}, month = {2009 Oct 30}, pages = {623-33}, abstract = {

The C. elegans cell lineage provides a unique opportunity to look at how cell lineage affects patterns of gene expression. We developed an automatic cell lineage analyzer that converts high-resolution images of worms into a data table showing fluorescence expression with single-cell resolution. We generated expression profiles of 93 genes in 363 specific cells from L1 stage larvae and found that cells with identical fates can be formed by different gene regulatory pathways. Molecular signatures identified repeating cell fate modules within the cell lineage and enabled the generation of a molecular differentiation map that reveals points in the cell lineage when developmental fates of daughter cells begin to diverge. These results demonstrate insights that become possible using computational approaches to analyze quantitative expression from many genes in parallel using a digital gene expression atlas.

}, keywords = {Animals, Caenorhabditis elegans, Caenorhabditis elegans Proteins, Cell Differentiation, Cell Lineage, Gene Expression Profiling}, issn = {1097-4172}, doi = {10.1016/j.cell.2009.08.044}, author = {Liu, Xiao and Long, Fuhui and Peng, Hanchuan and Aerni, Sarah J and Jiang, Min and S{\'a}nchez-Blanco, Adolfo and Murray, John I and Preston, Elicia and Mericle, Barbara and Batzoglou, Serafim and Myers, Eugene W and Kim, Stuart K} } @conference {2719, title = {Automatic recognition of cells (ARC) for 3D images of C. elegans.}, booktitle = {Proceedings of the 2008 Conference on Computational Molecular Biology (RECOMB) (Singapore, 2008)}, year = {2008}, month = {2008 Apr 2}, abstract = {

The development of high-resolution microscopy makes possible the high-throughput screening of cellular information, such as gene expression at single cell resolution. One of the critical enabling techniques yet to be developed is the automatic recognition or annotation of specific cells in a 3D image stack. In this paper, we present a novel graph-based algorithm, ARC, that determines cell identities in a 3D confocal image of C. elegans based on their highly stereotyped arrangement. This is an essential step in our work on gene expression analysis of C. elegans at the resolution of single cells. Our ARC method integrates both the absolute and relative spatial locations of cells in a C. elegans body. It uses a marker-guided, spatially-constrained, two-stage bipartite matching to find the optimal match between cells in a subject image and cells in 15 template images that have been manually annotated and vetted. We applied ARC to the recognition of cells in 3D confocal images of the first larval stage (L1) of C. elegans hermaphrodites, and achieved an average accuracy of 94.91\%.

}, author = {Long, Fuhui and Peng, Hanchuan and Liu, X and Kim, Stuart K and Myers, Eugene} } @article {2695, title = {Straightening caenorhabditis elegans images.}, journal = {Bioinformatics}, volume = {24}, year = {2008}, month = {2008 Jan 15}, pages = {234-42}, abstract = {

MOTIVATION: Caenorhabditis elegans, a roundworm found in soil, is a widely studied model organism with about 1000 cells in the adult. Producing high-resolution fluorescence images of C.elegans to reveal biological insights is becoming routine, motivating the development of advanced computational tools for analyzing the resulting image stacks. For example, worm bodies usually curve significantly in images. Thus one must {\textquoteright}straighten{\textquoteright} the worms if they are to be compared under a canonical coordinate system. RESULTS: We develop a worm straightening algorithm (WSA) that restacks cutting planes orthogonal to a {\textquoteright}backbone{\textquoteright} that models the anterior-posterior axis of the worm. We formulate the backbone as a parametric cubic spline defined by a series of control points. We develop two methods for automatically determining the locations of the control points. Our experimental methods show that our approaches effectively straighten both 2D and 3D worm images.

}, keywords = {Algorithms, Animals, Caenorhabditis elegans, Computer-Assisted, Fluorescence, Image Enhancement, Image Interpretation, Imaging, Microscopy, Three-Dimensional}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btm569}, author = {Peng, Hanchuan and Long, Fuhui and Liu, Xiao and Kim, Stuart K and Myers, Eugene W} }