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Genome Structure, Functional Genomics, and Proteomics in Ascidians

Chapter
First Online:
Part of the Genome Mapping and Genomics in Animals book series (MAPPANIMAL, volume 4)

Abstract

The marine invertebrate chordate ascidians provide us with excellent experimental systems because of their simple and tadpole body plan at the larval stage. Ascidians are key organisms for understanding the evolution of chordates. Methods for analyzing genes have been established in ascidians, such as investigating spatiotemporal expression patterns of genes by means of whole-mount in situ hybridization, knocking down of genetic functions with antisense oligonucleotides, transient transgenesis by introducing DNA into embryos by microinjection and electroporation, and germline transgenesis and mutagenesis with transposon vectors. The draft genome sequences of two ascidians, Ciona intestinalis and Ciona savignyi, have been determined. These ascidians have simple genome structures with a smaller genome size and the limited number of genes compared to those in vertebrates. The genome information with annotation of genes, expression profiles of the genes, promoter/cis element information, and protein information have been collected extensively in ascidians to form the databases opened for researchers. These databases are useful to conduct the omic analysis. Indeed, genome-wide expression profiles of genes and proteins have been investigated with microarrays and proteomics. Comparison of the genome sequences of the two related Ciona species is utilized to find conserved cis elements that are important for transcriptional regulation. This manuscript overviews the methods, tools, and databases available for researchers studying ascidians. Now ascidians are representative marine invertebrates for genomic and postgenomic analyses.

Keywords

Ascidian Whole-mount In Situ Hybridization (WISH) Ciona Species Ciona Genome Savignyi Genome 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgment

We thank all members in Shimoda Marine Research Center, University of Tsukuba, for cooperation to our research. We also thank Dr. Nori Satoh, Dr. Yutaka Satou, Dr. Eiichi Shoguchi, and Dr. Hiroki Nishida for useful discussions and Dr. Reiko Yoshida and Ms. Yuki Nakashima for helping with figure preparation. We are grateful to Dr. Brad Davidson for recommending us as the authors of this chapter. This study was supported by Grants-in-Aid for Scientific Research from JSPS and MEXT to YS (17207013, 18770193, 20681019, 20247031, 21112004, 23681039), KN (17310114, 20310115), TGK (17018018, 18370089, 22310120), and KI. YS was supported by NIG Cooperative Research Program (2007-B01) and Narishige Zoological Science Award. The construction of CIPRO and preparation of this chapter were supported by a grant from Institute for Bioinformatics Research and Development, Japan Science and Technology Agency (JST-BIRD) to KI.

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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Shimoda Marine Research CenterUniversity of TsukubaShimodaJapan
  2. 2.The Institute of Medical ScienceThe University of TokyoTokyoJapan
  3. 3.Department of Biology, Faculty of Science and EngineeringKonan UniversityKobeJapan

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