Transitioning from microsatellites to SNP-based microhaplotypes in genetic monitoring programs: lessons from a 20-year time series of paired data.

Many long-term genetic monitoring programs began before next-generation
sequencing became widely available. Older programs can now transition to
new marker systems usually consisting of 1000s of SNP loci, but there are
still important questions about comparability, precision, and accuracy of
key metrics estimated using SNPs. Ideally, transitioned programs should
capitalize on new information without sacrificing continuity of inference
across the time series. We combined existing microsatellite-based genetic
monitoring information with SNP-based microhaplotypes obtained from
archived samples of Rio Grande silvery minnow (Hybognathus amarus) across
a 20-year time series to evaluate point estimates and trajectories of key
genetic metrics. Demographic and genetic monitoring bracketed multiple
collapses of the wild population, and included cases where captive-born
repatriates comprised the majority of spawners in the wild. Even with
smaller sample sizes, microhaplotypes yielded comparable and in some cases
more precise estimates of variance genetic effective population size,
multilocus heterozygosity and inbreeding compared to microsatellites
because many more microhaplotype loci were available. Microhaplotypes also
recorded shifts in allele frequencies associated with population
bottlenecks. Trends in microhaplotype-based inbreeding metrics were
associated with the fraction of hatchery-reared repatriates to the wild,
and should be incorporated into future genomic monitoring. Although
differences in accuracy and precision of some metrics were observed
between marker types, biological inferences and management recommendations
were consistent.