Literature DB >> 18292219

Scanning the human genome at kilobase resolution.

Jun Chen1, Yeong C Kim, Yong-Chul Jung, Zhenyu Xuan, Geoff Dworkin, Yanming Zhang, Michael Q Zhang, San Ming Wang.   

Abstract

Normal genome variation and pathogenic genome alteration frequently affect small regions in the genome. Identifying those genomic changes remains a technical challenge. We report here the development of the DGS (Ditag Genome Scanning) technique for high-resolution analysis of genome structure. The basic features of DGS include (1) use of high-frequent restriction enzymes to fractionate the genome into small fragments; (2) collection of two tags from two ends of a given DNA fragment to form a ditag to represent the fragment; (3) application of the 454 sequencing system to reach a comprehensive ditag sequence collection; (4) determination of the genome origin of ditags by mapping to reference ditags from known genome sequences; (5) use of ditag sequences directly as the sense and antisense PCR primers to amplify the original DNA fragment. To study the relationship between ditags and genome structure, we performed a computational study by using the human genome reference sequences as a model, and analyzed the ditags experimentally collected from the well-characterized normal human DNA GM15510 and the leukemic human DNA of Kasumi-1 cells. Our studies show that DGS provides a kilobase resolution for studying genome structure with high specificity and high genome coverage. DGS can be applied to validate genome assembly, to compare genome similarity and variation in normal populations, and to identify genomic abnormality including insertion, inversion, deletion, translocation, and amplification in pathological genomes such as cancer genomes.

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Year:  2008        PMID: 18292219      PMCID: PMC2336809          DOI: 10.1101/gr.068304.107

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


  40 in total

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Journal:  Nature       Date:  2003-06-19       Impact factor: 49.962

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7.  In Silico identification and annotation of non-coding RNAs by RNA-seq and De Novo assembly of the transcriptome of Tomato Fruits.

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8.  Identification of medium-sized genomic deletions with low coverage, mate-paired restricted tags.

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9.  PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data.

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10.  Poly A- transcripts expressed in HeLa cells.

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