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Accurate SNP and mutation detection by targeted custom microarray-based genomic enrichment of short-fragment sequencing libraries
Microarray-based enrichment of selected genomic loci is a powerful method for genome complexity reduction for next-generation sequencing. Since the vast majority of exons in vertebrate genomes are smaller than 150 nt, we explored the use of short fragment libraries (85–110 bp) to achieve higher enri...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2879533/ https://www.ncbi.nlm.nih.gov/pubmed/20164091 http://dx.doi.org/10.1093/nar/gkq072 |
Sumario: | Microarray-based enrichment of selected genomic loci is a powerful method for genome complexity reduction for next-generation sequencing. Since the vast majority of exons in vertebrate genomes are smaller than 150 nt, we explored the use of short fragment libraries (85–110 bp) to achieve higher enrichment specificity by reducing carryover and adverse effects of flanking intronic sequences. High enrichment specificity (60–75%) was obtained with a relative even base coverage. Up to 98% of the target-sequence was covered more than 20× at an average coverage depth of about 200×. To verify the accuracy of SNP/mutation detection, we evaluated 384 known non-reference SNPs in the targeted regions. At ∼200× average sequence coverage, we were able to survey 96.4% of 1.69 Mb of genomic sequence with only 4.2% false negative calls, mostly due to low coverage. Using the same settings, a total of 1197 novel candidate variants were detected. Verification experiments revealed only eight false positive calls, indicating an overall false positive rate of less than 1 per ∼200 000 bp. Taken together, short fragment libraries provide highly efficient and flexible enrichment of exonic targets and yield relatively even base coverage, which facilitates accurate SNP and mutation detection. Raw sequencing data, alignment files and called SNPs have been submitted into GEO database http://www.ncbi.nlm.nih.gov/geo/ with accession number GSE18542. |
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