1. Draft sequencing of 1,000 genomes to study the genetics of quantitative traits: data production
Fabio Busonero1, Brendan J. Tarrier2, Elizabeth A. Ketterer2, Goncalo R. Abecasis1, and Christine A. Brennan2.
1Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA;
2DNA Sequencing Core, University of Michigan, Ann Arbor, Michigan, USA.
Introduction
In the past several years, genome-wide association studies have furthered our understanding of the genetics basis of blood lipid levels, which are key risk factors for the development of cardiovascular disease. The success of these studies resulted, in large part, from their ability to explore the genome in a comprehensive manner, systematically assessing the impact of common variation on the trait of interest. Here we propose to deploy high-throughput sequencing technologies to extend these systematic whole genome assessments and, to maximize our chances of success, we’ll focus our study on an isolated founder population in Sardinia (precisely volunteers enrolled in ProgeNIA study), which is ideal for the study of rare genetic variants. The proposed plan will allow us to evaluate the contribution of common (frequency>5.0%) and rare (frequency %) single nucleotide polymorphisms, short insertions and deletions, large copy number polymorphisms and other structural variants to blood levels of low density lipoprotein cholesterol (LDL-c), high density lipoprotein cholesterol (HDL-c) and triglycerides (TG), all of which are key risk factors for cardiovascular disease.
Results – Milestones in sequences production
Over the last 10 months, changes in reagent chemistry, efficiency of base-callers and fine regulation of template loaded onto the flowcell by titration, allowed to increase amount of data for run, as shown in the plots below.
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Data Description – Samples
ProgeNIA’s phenotyped individuals include:
6,400 avuncular pairs
4,935 sibling pairs
4,263 parent-offspring pairs
4,014 cousin pairs
686 grand-parent grand-child pairs
Strategy to choose the 1,000 individuals to be sequenced (EXPLAIN):
To sequence a minimal number of individuals and use their sequences together with Identity by descent (IBD) information to deduce the sequence of other individuals in the pedigree.
We are currently using ExonPicks scoring, to pick individuals to be sequenced from our large pedigree collections, since we have genotypes chip information to determine IBD sharing in the pedigree.
We have been picking:
Trios (2 parents + 1 offspring)
One Parent+two offspring families
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Methods – Whole-genome sequencing
Genomic DNA libraries were generated as previously described (Quail et al., 2008) with minor modifications. Briefly, DNA (5 μg) from whole blood salting-out extraction was randomly fragmented by sonication and subsequently treated with a mixture of T4 DNA Polymerase, E. coli DNA polymerase I Klenow fragment, and T4 polynucleotide kinase to end-repair, blunt and phosphorylate ends; the repaired fragments were then 3’-adenylated using Klenow exo-DNA Polymerase. Adenylated fragments were ligated to paired-end adaptors, and fragments ranging from 400 to 500 bp were selected on agarose gel and extracted using the QIAquick gel extraction kit (Qiagen). Size-selected adaptor-modified DNA fragments were PCR-enriched using adapter-specific primers. Following amplification, samples were quantified and quality checked by Agilent Bioanalyzer or qPCR, and denatured to load onto the flowcell for cluster amplification. Sequencing of samples was performed on Genome Analyzer Iix (Illumina) by paired-end 2x120 bp run. Sequence basecalls were made with Illumina software.
Sequenon fingerprinting
Conclusions
Actual sequencing capacity, 3 Illumina Genome Analyzers IIx, allows for about 400 GB of DNA sequence data to be generated each month, with each samples sequenced at an average of 3X depth, and more than 10 GB of high-quality mapped de-duplicated bases per lane in paired-end sequencing runs with 120 bp reads.
…how many peoples sequenced so far
…and lipid levels?
…info about SNPs, dbSNPs,…
References
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