Difference between revisions of "James Watson Genome Paper Abstract"

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The association of genetic variation with disease and drug response, and improvements in nucleic acid technologies, have given great optimism for the impact of ‘genomic medicine’. However, the formidable size of the diploid human genome1, approximately 6gigabases, has prevented the routine application of sequencing methods to deciphering complete individual human genomes. To realize the full potential of genomics for human health, this limitation must be overcome.

Here we report the DNA sequence of a diploid genome of a single individual, James D. Watson, sequenced to 7.4-fold redundancy in two months using massively parallel sequencing in picolitre-size reaction vessels.

This sequence was completed in two months at approximately one-hundredth of the cost of traditional capillary electrophoresis methods.

Comparison of the sequence to the reference genome led to the identification of 3.3million single nucleotide polymorphisms, of which 10,654 cause amino-acid substitution within the coding sequence.

In addition, we accurately identified small-scale (2–40,000 base pair (bp)) insertion and deletion polymorphism as well as copy number variation resulting in the large-scale gain and loss of chromosomal segments ranging from 26,000 to 1.5million base pairs. Overall, these results agree well with recent results of sequencing of a single individual2 by traditional methods. However, in addition to being faster and significantly less expensive, this sequencing technology avoids the arbitrary loss of genomic sequences inherent in random shotgun sequencing by bacterial cloning because it amplifies DNA in a cell-free system. As a result, we further demonstrate the acquisition of novel human sequence, including novel genes not previously identified by traditional genomic sequencing.

This is the first genome sequenced by next-generation technologies.

Therefore it is a pilot for the future challenges of ‘personalized genome sequencing’.

 

External Links

Personal Genomics.org