Spatial gene expression quantification: a tool for analysis of in situ hybridizations in sea anemone Nematostella vectensis

BMC Research Notes

Jaap A Kaandorp¹  Daniel Botman¹ 

[1] Section Computational Science, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands

关键词: Embryo morphology;    Embryonic development;    Gene network modelling;    Gene expression quantification;    Nematostella vectensis;   

Others  :  1165505
DOI  :  10.1186/1756-0500-5-555

 received in 2012-03-15, accepted in 2012-09-26,  发布年份 2012

【 摘 要 】

Background

Spatial gene expression quantification is required for modeling gene regulation in developing organisms. The fruit fly Drosophila melanogaster is the model system most widely applied for spatial gene expression analysis due to its unique embryonic properties: the shape does not change significantly during its early cleavage cycles and most genes are differentially expressed along a straight axis. This system of development is quite exceptional in the animal kingdom.

In the sea anemone Nematostella vectensis the embryo changes its shape during early development; there are cell divisions and cell movement, like in most other metazoans. Nematostella is an attractive case study for spatial gene expression since its transparent body wall makes it accessible to various imaging techniques.

Findings

Our new quantification method produces standardized gene expression profiles from raw or annotated Nematostella in situ hybridizations by measuring the expression intensity along its cell layer. The procedure is based on digital morphologies derived from high-resolution fluorescence pictures. Additionally, complete descriptions of nonsymmetric expression patterns have been constructed by transforming the gene expression images into a three-dimensional representation.

Conclusions

We created a standard format for gene expression data, which enables quantitative analysis of in situ hybridizations from embryos with various shapes in different developmental stages. The obtained expression profiles are suitable as input for optimization of gene regulatory network models, and for correlation analysis of genes from dissimilar Nematostella morphologies. This approach is potentially applicable to many other metazoan model organisms and may also be suitable for processing data from three-dimensional imaging techniques.

【 授权许可】

   
2012 Botman and Kaandorp; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

【 参考文献 】

• [1]Li E, Davidson EH: Building developmental gene regulatory networks. Birth Defects Res C Embryo Today 2009, 87:123-130.
• [2]Chan TM, Longabaugh W, Bolouri H, Chen HL, Tseng WF, Chao CH, Jang TH, Lin YI, Hung SC, Wang HD, Yuh CH: Developmental gene regulatory networks in the zebrafish embryo. Biochim Biophys Acta 2009, 1789:279-298.
• [3]de Jong H: Modeling and simulation of genetic regulatory systems: a literature review. J Comput Biol 2002, 9:67-103.
• [4]Reinitz J, Sharp DH: Mechanism of eve stripe formation. Mech Dev 1995, 49:133-158.
• [5]Jaeger J, Surkova S, Blagov M, Janssens H, Kosman D, Koslov KN, Myasnikova E, Vanario-Alonso CE, Samsonova M, Sharp DH, Reinitz J, Manu: Dynamic control of positional information in the early Drosophila embryo. Nature 2004, 430:368-371.
• [6]Mjolsness E, Sharp DH, Reinitz J: A connectionist model of development. J Theor Biol 1991, 152:429-453.
• [7]Janssens H, Kosman D, Vanario-Alonso CE, Jaeger J, Samsonova M, Reinitz J: A high-throughput method for quantifying gene expression data from early Drosophila embryos. Dev Genes Evol 2005, 215:374-381.
• [8]Darling JA, Reitzel AR, Burton PM, Mazza ME, Ryan JF, Sullivan JC, Finnerty JR: Rising starlet: the starlet sea anemone, Nematostella vectensis. BioEssays 2005, 27:211-221.
• [9]Putnam NH, Srivastava M, Hellsten U, Dirks B, Chapman J, Salamov A, Terry A, Shapiro H, Lindquist E, Kapitonov VV, Jurka J, Genikhovich G, Grigoriev IV, Lucas SM, Steele RE, Finnerty JR, Technau U, Martindale MQ, Rokhsar DS: Sea anemone genome reveals ancestral eumetazoan gene repertoire and genomic organization. Science 2007, 317:86-94.
• [10]Byrum CA, Martindale MQ: Gastrulation in the Cnidaria and the Ctenophora. In Gastrulation: From Cells to Embryo. Edited by Stern CA. Cold Spring Harbor: Cold Spring Harbor Laboratory Press; 2004:33-50.
• [11]Lee PN, Kumburegama S, Marlow HQ, Martindale MQ, Wikramanayake AH: Asymmetric developmental potential along the animal-vegetal axis in the antozoan cnidarian, Nematostella vectensis, is mediated by Dishevelled. Dev Biol 2007, 310:169-186.
• [12]de Jong J: Quantitative analysis of gene expression in Nematostella vectensis. Section Computational Science: MSc thesis. University of Amsterdam; 2009.
• [13]Magie CR, Daly M, Martindale MQ: Gastrulation in the cnidarian Nematostella vectensis occurs via invagination not ingression. Dev Biol 2007, 305:483-497.
• [14]Cnidarian Evolutionary Genomics Database http://www.cnidbase.org/index.cgi webcite
• [15]Comparative Marine Invertebrate Gene Expression Database http://www.kahikai.org/index.php?content=genes webcite
• [16]Extavour CG, Pang K, Matus DQ: Martindale MQ: vasa and nanos expression patterns in a sea anemone and the evolution of bilaterian germ cell specification mechanisms. Evol Dev 2005, 7:201-215.
• [17]MathWorks Documentation Center http://www.mathworks.com/help/matlab/ref/interp1.htm webcite
• [18]MathWorks Documentation Center http://www.mathworks.com/help/curvefit/smooth.htm webcite
• [19]Magie CR, Pang K, Martindale MQ: Genomic inventory and expression of Sox and Fox genes in the cnidarian Nematostella vectensis. Dev Genes Evol 2005, 215:618-630.
• [20]Fomekong-Nanfack Y, Kaandorp JA, Blom J: Efficient parameter estimation for spatio-temporal models of pattern formation: case study of Drosophila melanogaster. Bioinformatics 2007, 23:3356-3363.
• [21]Fomekong-Nanfack Y, Postma M, Kaandorp JA: Inferring Drosophila gap gene regulatory network: a parameter sensitivity and perturbation analysis. BMC Syst Biol 2009, 3:94. BioMed Central Full Text
• [22]Fomekong-Nanfack Y, Postma M, Kaandorp JA: Inferring Drosophila gap gene regulatory network: pattern analysis of simulated gene expression profiles and stability analysis. BMC Res Notes 2009, 2:256. BioMed Central Full Text
• [23]Wikramanayake AH, Hong M, Lee PN, Pang K, Byrum CA, Bince JM, Xu R, Martindale MQ: An ancient role for nuclear beta-catenin in the evolution of axial polarity and germ layer segregation. Nature 2003, 426:446-450.
• [24]Welten MCM, de Haan SB, van den Boogert N, Noordermeer JN, Lamers GEM, Spaink HP, Meijer AH, Verbeek FJ: ZebraFISH: fluorescent in situ hybridization protocol and three-dimensional imaging of gene expression patterns. Zebrafish 2006, 3:465-476.
• [25]Luengo Hendriks CL, Keränen SV, Fowlkes CC, Simirenko L, Weber GH, DePace AH, Henriquez C, Kaszuba DW, Hamann B, Eisen MB, Malik J, Sudar D, Biggin MD, Knowles DW: Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution I: data acquisition pipeline. Genome Biol 2006, 7:R123. BioMed Central Full Text
• [26]Flynn CJ, Sharma T, Ruffins SW, Guerra SL, Crowley JC, Ettensohn CA: High-resolution, three-dimensional mapping of gene expression using GeneExpressMap (GEM). Dev Biol 2011, 357:532-540.
• [27]Myasnikova E, Samsonova A, Kozlov K, Samsonona M, Reinitz J: Registration of the expression patterns of Drosophila segmentation genes by two independent methods. Bioinformatics 2001, 17:3-12.
• [28]Heid CA, Stevens J, Livak KJ, Williams PM: Real time quantitative PCR. Genome Res 1996, 6:986-994.
• [29]Fritzenwanker JH, Genikhovich G, Kraus Y, Technau U: Early development and axis specification in the sea anemone Nematostella vectensis. Dev Biol 2007, 310:264-279.
• [30]Mathworks Documentation Center http://www.mathworks.com/help/bioinfo/ref/clustergram.html webcite