Massively parallel DNA sequencing offers many benefits, but major inhibitory cost factors include: (1) start-up (i.e., purchasing initial reagents and equipment); (2) buy-in (i.e., getting the smallest possible amount of data from a run); and (3) sample preparation. Reducing sample preparation costs is commonly addressed, but start-up and buy-in costs are rarely addressed. We present dual-indexing systems to address all three of these issues. By breaking the library construction process into universal, re-usable, combinatorial components, we reduce all costs, while increasing the number of samples and the variety of library types that can be combined within runs. We accomplish this by extending the Illumina TruSeq dual-indexing approach to 768 (384 + 384) indexed primers that produce 384 unique dual-indexes or 147,456 (384 × 384) unique combinations. We maintain eight nucleotide indexes, with many that are compatible with Illumina index sequences. We synthesized these indexing primers, purifying them with only standard desalting and placing small aliquots in replicate plates. In qPCR validation tests, 206 of 208 primers tested passed (99% success). We then created hundreds of libraries in various scenarios. Our approach reduces start-up and per-sample costs by requiring only one universal adapter that works with indexed PCR primers to uniquely identify samples. Our approach reduces buy-in costs because: (1) relatively few oligonucleotides are needed to produce a large number of indexed libraries; and (2) the large number of possible primers allows researchers to use unique primer sets for different projects, which facilitates pooling of samples during sequencing. Our libraries make use of standard Illumina sequencing primers and index sequence length and are demultiplexed with standard Illumina software, thereby minimizing customization headaches. In subsequent Adapterama papers, we use these same primers with different adapter stubs to construct amplicon and restriction-site associated DNA libraries, but their use can be expanded to any type of library sequenced on Illumina platforms.
47Next-generation DNA sequencing (NGS) offers many benefits, but major factors limiting NGS 48 include reducing the time and costs associated with: 1) start-up (i.e., doing NGS for the first 49 time), 2) buy-in (i.e., getting any data from a run), and 3) sample preparation. Although many 50 researchers have focused on reducing sample preparation costs, few have addressed the first two 51 problems. Here, we present iTru and iNext, dual-indexing systems for Illumina libraries that 52 help address all three of these issues. By breaking the library construction process into re-usable, 53 combinatorial components, we achieve low start-up, buy-in, and per-sample costs, while 54 simultaneously increasing the number of samples that can be combined within a single run. We 55 accomplish this by extending the Illumina TruSeq dual-indexing approach from 20 (8+12) 56 indexed adapters that produce 96 (8x12) unique combinations to 579 (192+387) indexed primers 57 that produce 74,304 (192x387) unique combinations. We synthesized 208 of these indexed 58All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/049114 doi: bioRxiv preprint first posted online Jun. 15, 2016; 3 primers for validation, and 206 of them passed our validation criteria (99% success). We also 59 used the indexed primers to create hundreds of libraries in a variety of scenarios. Our approach 60 reduces start-up and per-sample costs by requiring only one universal adapter which works with 61 indexed PCR primers to uniquely identify samples. Our approach reduces buy-in costs because: 62 1) relatively few oligonucleotides are needed to produce a large number of indexed libraries; and 632) the large number of possible primers allows researchers to use unique primer sets for different 64 projects, which facilitates pooling of samples during sequencing. Although the methods we 65
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