Digital PCR enables the absolute quantitation of nucleic acids in a sample. The lack of scalable and practical technologies for digital PCR implementation has hampered the widespread adoption of this inherently powerful technique. Here we describe a high-throughput droplet digital PCR (ddPCR) system that enables processing of ∼2 million PCR reactions using conventional TaqMan assays with a 96-well plate workflow. Three applications demonstrate that the massive partitioning afforded by our ddPCR system provides orders of magnitude more precision and sensitivity than real-time PCR. First, we show the accurate measurement of germline copy number variation. Second, for rare alleles, we show sensitive detection of mutant DNA in a 100 000-fold excess of wildtype background. Third, we demonstrate absolute quantitation of circulating fetal and maternal DNA from cell-free plasma. We anticipate this ddPCR system will allow researchers to explore complex genetic landscapes, discover and validate new disease associations, and define a new era of molecular diagnostics.

Two years ago, we described the first droplet digital PCR (ddPCR) system aimed at empowering all researchers with a tool that removes the substantial uncertainties associated with using the analogue standard, quantitative real-time PCR (qPCR). This system enabled TaqMan hydrolysis probe-based assays for the absolute quantification of nucleic acids. Due to significant advancements in droplet chemistry and buoyed by the multiple benefits associated with dye-based target detection, we have created a "second generation" ddPCR system compatible with both TaqMan-probe and DNA-binding dye detection chemistries. Herein, we describe the operating characteristics of DNA-binding dye based ddPCR and offer a side-by-side comparison to TaqMan probe detection. By partitioning each sample prior to thermal cycling, we demonstrate that it is now possible to use a DNA-binding dye for the quantification of multiple target species from a single reaction. The increased resolution associated with partitioning also made it possible to visualize and account for signals arising from nonspecific amplification products. We expect that the ability to combine the precision of ddPCR with both DNA-binding dye and TaqMan probe detection chemistries will further enable the research community to answer complex and diverse genetic questions.

Determining the chromosomal phase of pairs of sequence variants – the arrangement of specific alleles as haplotypes – is a routine challenge in molecular genetics. Here we describe Drop-Phase, a molecular method for quickly ascertaining the phase of pairs of DNA sequence variants (separated by 1-200 kb) without cloning or manual single-molecule dilution. In each Drop-Phase reaction, genomic DNA segments are isolated in tens of thousands of nanoliter-sized droplets together with allele-specific fluorescence probes, in a single reaction well. Physically linked alleles partition into the same droplets, revealing their chromosomal phase in the co-distribution of fluorophores across droplets. We demonstrated the accuracy of this method by phasing members of trios (revealing 100% concordance with inheritance information), and demonstrate a common clinical application by phasing CFTR alleles at genomic distances of 11–116 kb in the genomes of cystic fibrosis patients. Drop-Phase is rapid (requiring less than 4 hours), scalable (to hundreds of samples), and effective at long genomic distances (200 kb).

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We have carried out a number of sampling experiments in libraries of bioactive compounds to illustrate how size biases introduced by two-dimensional (2D) fragment distance functions may provide misleading information about the diversity of compound subsets. The number of different biological targets covered by a given subset is used as a measure of bioactive diversity, and it is considered to be the relevant property with which 2D diversity should correlate. Since the nature of the size biases depends on the way in which 2D distance is computed, we investigated three different methods of calculating distance. Use of 1-Tanimoto as a dissimilarity measure leads to the spurious conclusion that collections of structurally small compounds are inherently more diverse than other collections which may cover a broader range of sizes and more biological targets. XOR or squared Euclidean distance, by contrast, shows a preference for subsets of structurally larger compounds, but this does not appear to have as many adverse consequences in terms of target coverage. A simple product of 1-Tanimoto and XOR tends to equalize the opposing size effects of the two component distance functions and leads to a relatively unbiased means of comparing structures. Results here suggest that careful consideration should be given to the way in which chemical structures are compared whenever 2D fragment descriptors are used.