Combining microarray-based genomic selection (MGS) with the Illumina Genome Analyzer platform to sequence diploid target regions.
Novel methods of targeted sequencing of unique regions from complex eukaryotic genomes have generated a great deal of excitement, but critical demonstrations of these methods efficacy with respect to diploid genotype calling and experimental variation are lacking. To address this issue, we optimized microarray-based genomic selection (MGS) for use with the Illumina Genome Analyzer (IGA). A set of 202 fragments (304 kb total) contained within a 1.7 Mb genomic region on human chromosome X were MGS/IGA sequenced in ten female HapMap samples generating a total of 2.4 GB of DNA sequence. At a minimum coverage threshold of 5X, 93.9% of all bases and 94.9% of segregating sites were called, while 57.7% of bases (57.4% of segregating sites) were called at a 50X threshold. Data accuracy at known segregating sites was 98.9% at 5X coverage, rising to 99.6% at 50X coverage. Accuracy at homozygous sites was 98.7% at 5X sequence coverage and 99.5% at 50X coverage. Although accuracy at heterozygous sites was modestly lower, it was still over 92% at 5X coverage and increased to nearly 97% at 50X coverage. These data provide the first demonstration that MGS/IGA sequencing can generate the very high quality sequence data necessary for human genetics research. All sequences generated in this study have been deposited in NCBI Short Read Archive (http://www.ncbi.nlm.nih.gov/Traces/sra, Accession # SRA007913).
Okou
David T
DT
Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA.
Locke
Adam E
AE
Steinberg
Karyn M
KM
Hagen
Katie
K
Athri
Prashanth
P
Shetty
Amol C
AC
Patel
Viren
V
Zwick
Michael E
ME
D044383:Black People / Q000235:genetics; D041321:Chromosomes, Human, X / Q000235:genetics; D004171:Diploidy; D005260:Female; D015894:Genome, Human; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D044465:White People / Q000235:genetics