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Statistical inference of chromosomal homology based on gene colinearity and applications to Arabidopsis and rice.

ABSTRACT: 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.

SUBMITTER: Wang X

PROVIDER: S-EPMC1626491 | biostudies-literature | 2006

REPOSITORIES: biostudies-literature

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Statistical inference of chromosomal homology based on gene colinearity and applications to Arabidopsis and rice.

Wang Xiyin X Shi Xiaoli X Li Zhe Z Zhu Qihui Q Kong Lei L Tang Wen W Ge Song S Luo Jingchu J

BMC bioinformatics 20061012

<h4>Background</h4>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.<h4>Results</h4>In this study, we present a statistical approach to detect homologous chromosomal segments ...[more]

PMID: 17038171

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Project description:The aim of this study was to analyze the genomic homology between cattle (Bos taurus) and buffaloes (Bubalus bubalis) and to propose a rearrangement of the buffalo genome through linkage disequilibrium analyses of buffalo SNP markers referenced in the cattle genome assembly and also compare it to the buffalo genome assembly. A panel of bovine SNPs (single nucleotide polymorphisms) was used for hierarchical, non-hierarchical and admixture cluster analyses. Thus, the linkage disequilibrium information between markers of a specific panel of buffalo was used to infer chromosomal rearrangement. Haplotype diversity and imputation accuracy of the submetacentric chromosomes were also analyzed. The genomic homology between the species enabled us to use the bovine genome assembly to recreate a buffalo genomic reference by rearranging the submetacentric chromosomes. The centromere of the submetacentric chromosomes exhibited high linkage disequilibrium and low haplotype diversity. It allowed hypothesizing about chromosome evolution. It indicated that buffalo submetacentric chromosomes are a centric fusion of ancestral acrocentric chromosomes. The chronology of fusions was also suggested. Moreover, a linear regression between buffalo and cattle rearranged assembly and the imputation accuracy indicated that the rearrangement of the chromosomes was adequate. When using the bovine reference genome assembly, the rearrangement of the buffalo submetacentric chromosomes could be done by SNP BTA (chromosome of Bos taurus) calculations: shorter BTA (shorter arm of buffalo chromosome) was given as [(shorter BTA length - SNP position in shorter BTA)] and larger BTA length as [shorter BTA length + (larger BTA length - SNP position in larger BTA)]. Finally, the proposed linkage disequilibrium-based method can be applied to elucidate other chromosomal rearrangement events in other species with the possibility of better understanding the evolutionary relationship between their genomes.

Dataset Information

Statistical inference of chromosomal homology based on gene colinearity and applications to Arabidopsis and rice.

Publications

Statistical inference of chromosomal homology based on gene colinearity and applications to Arabidopsis and rice.

Similar Datasets

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