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BrainAligner: 3D registration atlases of Drosophila brains

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Abstract

Analyzing Drosophila melanogaster neural expression patterns in thousands of three-dimensional image stacks of individual brains requires registering them into a canonical framework based on a fiducial reference of neuropil morphology. Given a target brain labeled with predefined landmarks, the BrainAligner program automatically finds the corresponding landmarks in a subject brain and maps it to the coordinate system of the target brain via a deformable warp. Using a neuropil marker (the antibody nc82) as a reference of the brain morphology and a target brain that is itself a statistical average of data for 295 brains, we achieved a registration accuracy of 2 μm on average, permitting assessment of stereotypy, potential connectivity and functional mapping of the adult fruit fly brain. We used BrainAligner to generate an image pattern atlas of 2,954 registered brains containing 470 different expression patterns that cover all the major compartments of the fly brain.

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Figure 1: BrainAligner registers images of neurons from different brains onto a common coordinate system.
Figure 2: Schematic illustration of the BrainAligner algorithm.
Figure 3: Stereotypy of neuronal morphology and reproducibility of GAL4 expression patterns.
Figure 4: Expression pattern overlap by computational and biological methods.
Figure 5: Comparison of computational alignment of separate brains with coexpression data in the same brain.
Figure 6: A 3D atlas of neurite tracts reconstructed from aligned GAL4 patterns.

Change history

  • 16 May 2011

    In the version of this article initially published online, there was a misspelled word in the title and an incorrect callout to Figure 1e in the text. The errors have been corrected for the PDF and HTML versions of this article.

References

  1. Buchner, E. et al. Cell-specific immuno-probes for the brain of normal and mutant Drosophila melanogaster. I. Wildtype visual system. Cell Tissue Res. 253, 357–370 (1988).

    Article  CAS  Google Scholar 

  2. Brand, A.H. & Perrimon, N. Targeted gene expression as a means of altering cell fates and generating dominant phenotypes. Development 118, 401–415 (1993).

    CAS  Google Scholar 

  3. Luan, H. & White, B.H. Combinatorial methods for refined neuronal gene targeting. Curr. Opin. Neurobiol. 17, 572–580 (2007).

    Article  CAS  Google Scholar 

  4. Broughton, S.J., Kitamoto, T. & Greenspan, R.J. Excitatory and inhibitory switches for courtship in the brain of Drosophila melanogaster. Curr. Biol. 14, 538–547 (2004).

    Article  CAS  Google Scholar 

  5. Jenett, A., Schindelin, J.E. & Heisenberg, M. The Virtual Insect Brain protocol: creating and comparing standardized neuroanatomy. BMC Bioinformatics 7, 544 (2006).

    Article  Google Scholar 

  6. Boerner, J. & Duch, C. Average shape standard atlas for the adult Drosophila ventral nerve cord. J. Comp. Neurol. 518, 2437–2455 (2010).

    PubMed  Google Scholar 

  7. Maintz, J.B.A. & Viergever, M.A. A survey of medical image registration. Med. Image Anal. 2, 1–36 (1998).

    Article  CAS  Google Scholar 

  8. Zitova, B. & Flusser, J. Image registration methods: a survey. Image Vis. Comput. 21, 977–1000 (2003).

    Article  Google Scholar 

  9. Fischer, B., Dawant, B. & Lorenz, C. (eds.) Biomedical Image Registration, Proceedings of the 4th International Workshop (Springer, 2010).

  10. Lein, E.S. et al. Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176 (2007).

    Article  CAS  Google Scholar 

  11. Jefferis, G.S. et al. Comprehensive maps of Drosophila higher olfactory centers: spatially segregated fruit and pheromone representation. Cell 128, 1187–1203 (2007).

    Article  CAS  Google Scholar 

  12. Chiang, A.S. et al. Three-dimensional reconstruction of brain-wide wiring networks in Drosophila at single-cell resolution. Curr. Biol. 21, 1–11 (2011).

    Article  CAS  Google Scholar 

  13. Qu, L. & Peng, H. A principal skeleton algorithm for standardizing confocal images of fruit fly nervous systems. Bioinformatics 26, 1091–1097 (2010).

    Article  CAS  Google Scholar 

  14. Thirion, J.P. Image matching as a diffusion process: an analogy with Maxwell's demons. Med. Image Anal. 2, 243–260 (1998).

    Article  CAS  Google Scholar 

  15. Shen, D. & Davatzikos, C. HAMMER: hierarchical attribute matching mechanism for elastic registration. IEEE Trans. Med. Imaging 21, 1421–1439 (2002).

    Article  Google Scholar 

  16. Vercauteren, T. & Pennec, X. Perchant, A. & Ayache, N. Symmetric log-domain diffeomorphic registration: a demons-based approach. Lect. Notes Comput. Sci. 5241, 754–761 (2008).

    Article  Google Scholar 

  17. Wagh, D.A. et al. Bruchpilot, a protein with homology to ELKS/CAST, is required for structural integrity and function of synaptic active zones in Drosophila. Neuron 49, 833–844 (2006).

    Article  CAS  Google Scholar 

  18. Maes, F., Collignon, A., Vandermeulen, D., Marchal, G. & Suetens, P. Multimodality image registration by maximization of mutual information. IEEE Trans. Med. Imaging 16, 187–198 (1997).

    Article  CAS  Google Scholar 

  19. Fischler, M.A. & Bolles, R.C. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24, 381–395 (1981).

    Article  Google Scholar 

  20. Bookstein, F.L. Principal warps: thin-plate spline and the decomposition. IEEE Trans. Pattern Anal. Mach. Intell. 11, 567–585 (1989).

    Article  Google Scholar 

  21. Peng, H., Ruan, Z., Long, F., Simpson, J.H. & Myers, E.W. V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets. Nat. Biotechnol. 28, 348–353 (2010).

    Article  CAS  Google Scholar 

  22. Peng, H., Ruan, Z., Atasoy, D. & Sternson, S. Automatic reconstruction of 3D neuron structures using a graph-augmented deformable model. Bioinformatics 26, i38–i46 (2010).

    Article  CAS  Google Scholar 

  23. Lai, S.L. & Lee, T. Genetic mosaic with dual binary transcriptional systems in Drosophila. Nat. Neurosci. 9, 703–709 (2006).

    Article  CAS  Google Scholar 

  24. Basler, K. & Struhl, G. Compartment boundaries and the control of Drosophila limb pattern by hedgehog protein. Nature 368, 208–214 (1994).

    Article  CAS  Google Scholar 

  25. Crittenden, J.R., Skoulakis, E., Han, K., Kalderon, D. & Davis, R.L. Tripartite mushroom body architecture revealed by antigenic markers. Learn. Mem. 5, 38–51 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Lee, T. & Luo, L. Mosaic analysis with a repressible cell marker for studies of gene function in neuronal morphogenesis. Neuron 22, 451–461 (1999).

    Article  CAS  Google Scholar 

  27. Peng, H., Long, F. & Myers, E.W. VANO: a volume-object image annotation system. Bioinformatics 25, 695–697 (2009).

    Article  CAS  Google Scholar 

  28. Kelso, R.J. et al. Flytrap, a database documenting a GFP protein-trap insertion screen in Drosophila melanogaster. Nucleic Acids Res. 32, D418–D420 (2004).

    Article  CAS  Google Scholar 

  29. Knowles-Barley, S., Longair, M. & Douglas, A.J. BrainTrap: a database of 3D protein expression patterns in the Drosophila brain. Database 10.1093/database/baq005 (2010).

  30. Lam, S.C. et al. Segmentation of center brains and optic lobes in 3D confocal images of adult fruit fly brains. Methods 50, 63–69 (2010).

    Article  CAS  Google Scholar 

  31. Pfeiffer, B.D. et al. Refinement of tools for targeted gene expression in Drosophila. Genetics 186, 735–755 (2010).

    Article  CAS  Google Scholar 

  32. Pfeiffer, B.D. et al. Tools for neuroanatomy and neurogenetics in Drosophila. Proc. Natl. Acad. Sci. USA 105, 9715–9720 (2008).

    Article  CAS  Google Scholar 

  33. Wong, A.M., Wang, J.W. & Axel, R. Spatial representation of the glomerular map in the Drosophila protocerebrum. Cell 109, 229–241 (2002).

    Article  CAS  Google Scholar 

  34. O'Dell, K.M.C., Armstrong, J.D., Yang, M.Y. & Kaiser, K. Functional dissection of the Drosophila mushroom bodies by selective feminization of genetically defined subcompartments. Neuron 15, 55–61 (1995).

    Article  CAS  Google Scholar 

  35. Yang, M.Y., Armstrong, J.D., Vilinsky, I., Strausfeld, N.J. & Kaiser, K. Subdivision of the Drosophila mushroom bodies by enhancer-trap expression patterns. Neuron 15, 45–54 (1995).

    Article  Google Scholar 

  36. Connolly, J.B. et al. Associative learning disrupted by impaired Gs signaling in Drosophila mushroom bodies. Science 274, 2104–2107 (1996).

    Article  CAS  Google Scholar 

  37. Grenningloh, G., Rehm, E.J. & Goodman, C.S. Genetic analysis of growth cone guidance in Drosophila: fasciclin II functions as a neuronal recognition molecule. Cell 67, 45–57 (1991).

    Article  CAS  Google Scholar 

  38. Iwai, Y. et al. Axon patterning requires DN-cadherin, a novel adhesion receptor, in the Drosophila embryonic CNS. Neuron 19, 77–89 (1997).

    Article  CAS  Google Scholar 

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Acknowledgements

We thank G. Rubin, B. Pfeiffer and K. Hibbard (Janelia Farm Research Campus, Howard Hughes Medical Institute) for the pJFRC21-10XUAS-IVS-mCD8::RFP, lexAop-CD2-GFP stock and LexAP vector; B. Ganetzky for collaboration in generating the GAL4 collection; B. Lam for visually scoring the quality of aligned brains; Y. Zhuang for tracing and proofreading neurite tracts; Y. Yu and J. Yang for manual landmarking; C. Zugates and members of the FlyLight project team for discussion of aligner optimization; G. Wu for help in testing a registration method; D. Shen for discussion when we initially developed BrainAligner; and G. Rubin for commenting on this manuscript. This work was funded by Howard Hughes Medical Institute.

Author information

Authors and Affiliations

Authors

Contributions

H.P. designed and implemented BrainAligner, and performed experiments and analyses. H.P. and J.H.S. designed the biological experiments. F.L. and E.W.M. helped design the algorithm. P.C. prepared the samples and acquired confocal images. L.Q. helped implement the random sample consensus algorithm and some comparison experiments. A.J. produced the brain compartment label field. A.M.S. and J.H.S. generated LexA lines. H.P., E.W.M. and J.H.S. wrote the manuscript.

Corresponding author

Correspondence to Hanchuan Peng.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6 and Supplementary Note 1 (PDF 21447 kb)

Supplementary Video 1

Aligned and overlaid neuronal patterns of a64-GAL4 and a74-GAL4. Magenta, a64-GAL4; green, a74-GAL4. (MOV 2728 kb)

Supplementary Video 2

Six aligned and overlaid GAL4 patterns in Figure 1d (see Fig. 1d for color scheme). (MOV 17577 kb)

Supplementary Video 3

The 3D reconstructed neurite tracts from 20 aligned a278-GAL4 images, along with their mean tract model (red). (MOV 2834 kb)

Supplementary Video 4

The aligned patterns of a156-GAL4; UAS-mCD8-GFP and LexAP078; lexAop-mCD2-GFP. Magenta, a156-GAL4; green, LexAP078. (MOV 3703 kb)

Supplementary Video 5

The co-expressed patterns of a156-GAL4; UAS-mCD8-GFP and LexAP078; lexAop-mCD2-GFP. Magenta, a156-GAL4; green, LexAP078. (MOV 6071 kb)

Supplementary Video 6

Aligned and overlaid patterns of CG8916_1-3-X-GAL4 along with its two Flp-out segments. Magenta, the original pattern; yellow and green, the Flp-out patterns. (MOV 4868 kb)

Supplementary Video 7

Maximal intensity project view of six aligned GAL4 patterns in the central complex (see Fig. 1d for color scheme). (MOV 10832 kb)

Supplementary Video 8

Cross-sectional view of six aligned GAL4 patterns in the central complex (see Fig. 1d for color scheme). (MOV 23447 kb)

Supplementary Video 9

A database of 269 stereotyped neurite tracts throughout the Drosophila brain. The width of each tract equals the respective spatial deviation. The tracts are color-coded randomly for better visualization. (MOV 15848 kb)

Supplementary Software 1

Brain Aligner and V3D Atlas viewer. (ZIP 9834 kb)

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Peng, H., Chung, P., Long, F. et al. BrainAligner: 3D registration atlases of Drosophila brains. Nat Methods 8, 493–498 (2011). https://doi.org/10.1038/nmeth.1602

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