Transitioning from microsatellites to SNP-based microhaplotypes in
genetic monitoring programs: lessons from paired data spanning 20 years.
Abstract
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.