Introduction

BACKGROUND: The identification of chromosomal homology will shed light on such mysteries of genome evolution as DNA duplication, rearrangement and loss. Several approaches have been developed to detect chromosomal homology based on gene synteny or colinearity. However, the previously reported implementations lack statistical inferences which are essential to reveal actual homologies. RESULTS: In this study, we present a statistical approach to detect homologous chromosomal segments based on gene colinearity. We implement this approach in a software package ColinearScan to detect putative colinear regions using a dynamic programming algorithm. Statistical models are proposed to estimate proper parameter values and evaluate the significance of putative homologous regions. Statistical inference, high computational efficiency and flexibility of input data type are three key features of our approach. CONCLUSION: We apply ColinearScan to the Arabidopsis and rice genomes to detect duplicated regions within each species and homologous fragments between these two species. We find many more homologous chromosomal segments in the rice genome than previously reported. We also find many small colinear segments between rice and Arabidopsis genomes.

Publications

  1. Statistical inference of chromosomal homology based on gene colinearity and applications to Arabidopsis and rice.
    Cite this
    Wang X, Shi X, Li Z, Zhu Q, Kong L, Tang W, Ge S, Luo J, 2006-01-01 - BMC bioinformatics

Credits

  1. Xiyin Wang
    Developer

  2. Xiaoli Shi
    Developer

  3. Zhe Li
    Developer

  4. Qihui Zhu
    Developer

  5. Lei Kong
    Developer

  6. Wen Tang
    Developer

  7. Song Ge
    Developer

  8. Jingchu Luo
    Investigator

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Summary
AccessionBT006708
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC++, Perl
User InterfaceTerminal Command Line
Download Count0
Submitted ByJingchu Luo