Abstract
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.
Highlights
IntroductionMore commonly known as next-generation sequencing (NGS), has transformed the life sciences
Parallel sequencing, more commonly known as next-generation sequencing (NGS), has transformed the life sciences
We build this integrated system on top of previous developments introduced by Illumina (2018a) and others (e.g., Meyer & Kircher, 2010; Fisher et al, 2011), and we show that it is possible to significantly reduce library preparation costs by changing from full-length adapters that incorporate tags in the Illumina TruSeq strategy to shorter universal adapter stubs and indexing primers
Summary
More commonly known as next-generation sequencing (NGS), has transformed the life sciences. NGS costs per read have dropped tremendously, the minimum cost to obtain any amount of NGS data (i.e., the minimum buy-in cost) remains high, when researchers want to collect small amounts of DNA sequence data from large numbers of individual samples in a single run. These buy-in costs are largely driven by the money required to purchase adapters containing unique identifying sequences that allow tagging and tracking of. Library preparation methods that reduce costs while simultaneously increasing the number of samples that can be tagged and sequenced together would benefit many types of research
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