2.2. Target selection and generation of customized target capture

For sequencing, we selected 988 genes implicated in the pathways of aging and longevity in humans. The rationale for selection and their criteria is described in Section 3.1 under Results. The complete list of the 988 candidate genes is provided in the Supplementary Table S1. We designed a customized Agilent SureSelect in- solution target capture to enrich for our candidate genes. For each selected gene locus,weincluded2 kbupstreamregionofthetranscriptionstartsite,allexons,and 20 bp of each exon–intron junction. We used the Agilent eArray (http:// earray.chem.agilent.com/earray/) to design and assess coverage across the target genomic regionsofbaitlibraries.Design efficiency fromeArray was99%,calculated as the covered fraction of target bases in the oligo design (6,229,389 bp), out of the total submitted target regions (6,291,136 bp). The final customized target capture contained 5,692,804 bp covering the target regions of the 988 candidate genes.

2.3. Library preparation, target enrichment and sequencing

We isolated DNA from immortalized B-lymphocytes established from 6 centenarians and generated libraries for Illumina sequencing. Each library was indexed with a unique barcode, which allowed for target capture, enrichment of pooled libraries and multiplex sequencing. The library preparation and enrichment methods were performed according to the Agilent Illumina Paired-End Sequencing Platform Library Prep Protocol, with the following modifications: (1) genomic DNA wasshearedwithCovarissystemfor250bp;(2)Illuminaadapterswerereplacedwith custom-made, indexed adapters supplied by IDT DNA (see Supplementary Table S2 for adapter sequence information); (3) size-selection and DNA elution were performedbyprecastE-gel(Invitrogen)SizeSelect2%withE-gelprecastgelcassette and fragments with desired size (300–350 bp) were eluted with 25 ml water; (4) for the pre-capture enrichment PCR, DNA was amplified in 8 cycles; (5) post-enriched DNA libraries were combined in equal amounts to a total quantity of 1 mg; (6) hybridization mixture was incubated for 24 h at 658C to minimize evaporation. Target-enrichedlibraries were sent toAxeqTechnologies and sequenced paired-end on the Illumina HiSeq2000 with cluster kit v2 according to the manufacturer’s protocol. Reads generated were 101 bp in length.

Accumulation of DNA damage and mutations has been considered an important causal factor in age-related deterioration and death (Garinis et al., 2008; Hoeijmakers, 2009). This concept is in keeping with the proposed evolutionary basis of aging, i.e., the declining force of natural selection with age, which does not predict maximization of cellular maintenance and repair (Gavrilov and Gavrilova, 2002). DNA damage continuously occurs by both endogenous and exogenous sources such as reactive oxygen species (ROS) produced as byproducts of metabolism, UV light and ionizing radiation. DNA damage is known to cause aging-related cellular degeneration and diseases. The insulin/insulin-like growth factor I (IGF-I) signaling pathway modulates DNA damage and stress response, and is well established as a conserved pathway of aging (Kenyon, 2010; Tazearslan et al., 2012). Mutations in insulin/

Please cite this article in press as: Han, J., et al., Discovery of novel non-synonymous SNP variants in 988 candidate genes from 6 centenarians by target capture and next-generation sequencing. Mech. Ageing Dev. (2013), http://dx.doi.org/10.1016/

J. Han et al./Mechanisms of Ageing and Development xxx (2013) xxx–xxx

2.4. Data analysis

which contained results from 1000 genomes at the time of analysis (Fig. 1A). Since novel nsSNPs are likely rare variants, which are subject to sequencing errors, we first validated if they were true variants and further tested whether these novel nsSNPs were enriched in centenarians as compared to controls by genotyping and association analysis.

Sequencing reads were aligned to the human genome, revision hg19 (Lander et al., 2001), using BWA, version 0.5.9 (Li and Durbin, 2009), with setting ‘‘(cid:3)q 17’’ provided when running the ‘‘aln’’ command. Following alignment, we utilized Picard [http://picard.sourceforge.net] to detect potential PCR duplicates and to calculate on-target statistics. Subsequent processing was performed using the Genome Analysis Toolkit (GATK) (McKenna et al., 2010). To call variants, we first preprocessed the data, locally realigning the reads around known and suspected indel events, then recalibrating the Illumina base quality scores to more closely reflect actual mismatch rates. We then performed multi-sample genotyping and filtered the results by fitting a Gaussian mixture model to the 7-dimensional point cloud formed by the joint distributions of various statistical annotations calculated for each SNP (DePristo et al., 2011). The model was trained to assign log-odds likelihood probabilities on the basis of sets of known SNPs from public databases, expanding the set retained until a sensitivity threshold of 99% of accessible, known SNPswasreached.Recommendedsettingsweregivenduringallsteps,asdetailedin the GATK software manual (http://www.broadinstitute.org/gatk/gatkdocs/). SNP databases used were the 1000 Genomes Project (Genomes Project, 2010), dbSNP build 132 (Sherry et al., 2001), and HapMap3 r3 (Altshuler et al., 2010). Functional annotations were provided by ANNOVAR (Liu et al., 2011; Wang et al., 2010). Correlation between SNP calls obtained here and those publicly released was determined with the CompOverlap evaluation module of the VariantEval tool from the GATK.

3.2. Validation of novel nsSNPs discovered in 6 centenarians