Data and code from: Predicting population genetic change in an autocorrelated random environment: insights from a large automated experiment

We exposed a mixture of two Dunaliella salina strains to fluctuating vs constant salinity (strains CCAP 19/12 : A and CCAP 19/15 : C), and tracked their frequencies through time by amplicon sequencing of the ITS2 and a chloroplast locus. Genomic DNA from 1071 samples was extracted using the Nucleospin® plant II (Macherey-Nagel). In order to make efficient use of the sequencing data, we reduced all chloroplast and ITS2 reads to short haplotypes made of a succession of few linked SNPs that individually maximized the FST among pure, reference cultures of A and C. We estimated fluctuating selection by tracking the dynamics of the frequency p of strain C through time, by combining two sources of genetic information, from the ITS2 and the chloroplast locus. We considered that the frequencies measured at the ITS2 and chloroplast loci were two observations (with error) of a true, unobserved strain frequency p. This corresponds to a state-space model, and we wrote its explicit likelihood function in C++, and optimized it using the TMB package in R (v.3.5.2)