Non-invasive fetal genotyping for maternal alleles with droplet digital PCR: A comparative study of analytical approaches

Objectives

To develop a flexible droplet digital PCR (ddPCR) workflow to perform non-invasive prenatal diagnosis via relative mutation dosage (RMD) for maternal pathogenic variants with a range of inheritance patterns, and to compare the accuracy of multiple analytical approaches.

Methods

Cell free DNA (cfDNA) was tested from 124 archived maternal plasma samples: 88 cases for sickle cell disease and 36 for rare Mendelian conditions. Three analytical methods were compared: sequential probability ratio testing (SPRT), Bayesian and z-score analyses.

Results

The SPRT, Bayesian and z-score analyses performed similarly well with correct prediction rates of 96%, 97% and 98%, respectively. However, there were high rates of inconclusive results for each cohort, particularly for z-score analysis which was 31% overall. Two samples were incorrectly classified by all three analytical methods; a false negative result predicted for a fetus affected with sickle cell disease and a false positive result predicting the presence of an X-linked IDS variant in an unaffected fetus.

Conclusions

ddPCR can be applied to RMD for diverse conditions and inheritance patterns, but all methods carry a small risk of erroneous results. Further evaluation is required both to reduce the rate of inconclusive results and explore discordant results in more detail.     

Scale-invariant movements of fishermen: the same foraging strategy as natural predators.

We analyzed the movement of fishing vessels during fishing trips in order to understand how fishermen behave in space while searching for fish. For that purpose we used hourly geo-referenced positions of vessels, provided by a satellite vessel monitoring system, for the entire industrial fleet (809 vessels) of the world's largest single species fishery (Peruvian anchovy, Engraulis ringens) from December 1999 to March 2003. Observed trajectories of fishing vessels are well modeled by Lévy random walks, suggesting that fishermen use a stochastic search strategy which conforms to the same search statistics as non-human predators. We show that human skills (technology, communication, or others) do not result in the fishermen's spatial behavior being fundamentally different from that of animal predators. With respect to probability of prey encounter, our results suggest that fishermen, on average, evolved an optimal movement pattern (mu = 2.00) among the family of Lévy random walks. This Lagrangian approach opens several perspectives in terms of operational management of the pelagic fish stock.