疾患モデルのための遺伝子の発見<br>Gene Discovery for Disease Models

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疾患モデルのための遺伝子の発見
Gene Discovery for Disease Models

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  • 製本 Hardcover:ハードカバー版/ページ数 537 p.
  • 言語 ENG
  • 商品コード 9780470499467
  • DDC分類 616.042

Full Description

This book provides readers with new paradigms on the mutation discovery in the post-genome era. The completion of human and other genome sequencing, along with other new technologies, such as mutation analysis and microarray, has dramatically accelerated the progress in positional cloning of genes from mutated models. In 2002, the Mouse Genome Sequencing Consortium stated that "The availability of an annotated mouse genome sequence now provides the most efficient tool yet in the gene hunter's toolkit. One can move directly from genetic mapping to identification of candidate genes, and the experimental process is reduced to PCR amplification and sequencing of exons and other conserved elements in the candidate interval. With this streamlined protocol, it is anticipated that many decades-old mouse mutants will be understood precisely at the DNA level in the near future." The implication of such a statement should be similar to the identification of mutated genes from human diseases and animal models, when genome sequencing is completed for them. More than five years have passed, but genes in many human diseases and animal models have not yet been identified. In some cases, the identification of the mutated genes has been a bottleneck, because the genetic mechanism holds the key to understand the basis of the diseases. However, an integrative strategy, which is a combination of genetic mapping, genome resources, bioinformatics tools, and high throughput technologies, has been developed and tested. The classic paradigm of positional cloning has evolved with completely new concepts of genomic cloning and protocols. This book describes new concepts of gene discovery in the post-genome era and the use of streamlined protocols to identify genes of interest. This book helps identify not only large insertions/deletions but also single nucleotide mutations or polymorphisms that regulate quantitative trait loci (QTL).

Contents

Preface. Acknowledgments.

Contributors.

1. Gene Discovery: From Positional Cloning to Genomic Cloning (Weikuan Gu and Daniel Goldowitz).

2. High-Throughput Gene Expression Analysis and the Identification of Expression QTLs (Rudi Alberts and Klaus Schughart).

3. DNA Methylation in the Pathogenesis of Autoimmunity (Xueqing Xu, Ping Yang, Zhang Shu, Yun Bai, and Cong-Yi Wang).

4. Cell-Based Analysis with Microfl uidic Chip (Wang Qi and Zhao Long).

5. Missing Dimension: Protein Turnover Rate Measurement in Gene Discovery (Gary Guishan Xiao).

6. Bioinformatics Tools for Gene Function Prediction (Yan Cui).

7. Determination of Genomic Locations of Target Genetic Loci (Bo Chang).

8. Mutation Discovery Using High-Throughput Mutation Screening Technology (Kai Li, Hanlin Gao, Hong-Guang Xie, Wanping Sun, and Jia Zhang).

9. Candidate Screening through Gene Expression Profile (Michal Korostynski).

10. Candidate Screening through High-Density SNP Array (Ching-Wan Lam and Kin-Chong Lau).

11. Gene Discovery by Direct Genome Sequencing (Kunal Ray, Arijit Mukhopadhyay, and Mainak Sengupta).

12. Candidate Screening through Bioinformatics Tools (Song Wu and Wei Zhao).

13. Using an Integrative Strategy to Identify Mutations (Yan Jiao and Weikuan Gu).

14. Determination of the Function of a Mutation (Bouchra Edderkaoui).

15. Confi rmation of a Mutation by Multiple Molecular Approaches (Hector Martinez-Valdez and Blanca Ortiz-Quintero).

16. Confi rmation of a Mutation by MicroRNA (Hongwei Zheng and Yongjun Wang).

17. Confi rmation of Gene Function Using Translational Approaches (Caroline J. Zeiss).

18. Confi rmation of Single Nucleotide Mutations (Jochen Graw).

19. Initial Identifi cation and Confi rmation of a QTL Gene (David C. Airey and Chun Li).

20. Gene Discovery of Crop Disease in the Postgenome Era (Yulin Jia).

21. Impact of Genomewide Structural Variation on Gene Discovery (Lisenka E.L.M. Vissers and Joris A. Veltman).

22. Impact of Whole Genome Protein Analysis on Gene Discovery of Disease Models (Sheng Zhang, Yong Yang, and Theodore W. Thannhauser).

Index.

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