| Title |
The Effect of Input DNA Copy Number on Genotype Call and Characterising SNP Markers in the Humpback Whale Genome Using a Nanofluidic Array
|
|---|---|
| Published in |
PLOS ONE, June 2012
|
| DOI | 10.1371/journal.pone.0039181 |
| Pubmed ID | |
| Authors |
Somanath Bhat, Andrea M. Polanowski, Mike C. Double, Simon N. Jarman, Kerry R. Emslie |
| Abstract |
Recent advances in nanofluidic technologies have enabled the use of Integrated Fluidic Circuits (IFCs) for high-throughput Single Nucleotide Polymorphism (SNP) genotyping (GT). In this study, we implemented and validated a relatively low cost nanofluidic system for SNP-GT with and without Specific Target Amplification (STA). As proof of principle, we first validated the effect of input DNA copy number on genotype call rate using well characterised, digital PCR (dPCR) quantified human genomic DNA samples and then implemented the validated method to genotype 45 SNPs in the humpback whale, Megaptera novaeangliae, nuclear genome. When STA was not incorporated, for a homozygous human DNA sample, reaction chambers containing, on average 9 to 97 copies, showed 100% call rate and accuracy. Below 9 copies, the call rate decreased, and at one copy it was 40%. For a heterozygous human DNA sample, the call rate decreased from 100% to 21% when predicted copies per reaction chamber decreased from 38 copies to one copy. The tightness of genotype clusters on a scatter plot also decreased. In contrast, when the same samples were subjected to STA prior to genotyping a call rate and a call accuracy of 100% were achieved. Our results demonstrate that low input DNA copy number affects the quality of data generated, in particular for a heterozygous sample. Similar to human genomic DNA, a call rate and a call accuracy of 100% was achieved with whale genomic DNA samples following multiplex STA using either 15 or 45 SNP-GT assays. These calls were 100% concordant with their true genotypes determined by an independent method, suggesting that the nanofluidic system is a reliable platform for executing call rates with high accuracy and concordance in genomic sequences derived from biological tissue. |
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| United States | 1 | 50% |
| Australia | 1 | 50% |
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| Type | Count | As % |
|---|---|---|
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| Scientists | 1 | 50% |
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| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Germany | 1 | 2% |
| Norway | 1 | 2% |
| Unknown | 53 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 38% |
| Student > Master | 7 | 13% |
| Student > Ph. D. Student | 6 | 11% |
| Other | 6 | 11% |
| Student > Bachelor | 3 | 5% |
| Other | 10 | 18% |
| Unknown | 3 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 36 | 64% |
| Biochemistry, Genetics and Molecular Biology | 6 | 11% |
| Environmental Science | 2 | 4% |
| Medicine and Dentistry | 2 | 4% |
| Physics and Astronomy | 2 | 4% |
| Other | 3 | 5% |
| Unknown | 5 | 9% |