LaCava, M. E. F. | bioRxiv Science

bioRxiv2026

Use of SNPs in a low diversity system for genetic monitoring and identifying a successful translocation event in the Paiute Cutthroat Trout (O. henshawi seleniris)

ObjectiveMaintaining genetic diversity in small, isolated populations is a key goal in conservation genetics. Genetic monitoring can guide management decisions, but comparisons across studies and time points are often complicated by differences in genetic markers and data sets. We aimed to develop a consistent, replicable set of genetic markers to support long-term monitoring of Paiute Cutthroat Trout (Oncorhynchus henshawi seleniris), a federally threatened subspecies persisting in a network of isolated refuge populations in California, USA. MethodsWe used RAD (Restriction site-associated DNA) sequencing to identify single nucleotide polymorphisms (SNPs) from 476 individuals representing eight extant refuge populations. Filtering steps included the removal of paralogous loci and exclusion of FST outliers associated with sequencing batch effects. We selected a panel of 1,114 SNPs that were shared across all populations and validated the panel in silico by comparing population structure and genetic diversity estimates to those derived from the full RAD sequencing dataset. ResultsThe candidate panel SNPs captured key patterns of genetic differentiation and diversity consistent with previous studies and the larger RAD dataset. We present updated baseline genetic metrics for each refuge population, providing a consistent reference point for future monitoring efforts. We also demonstrate the ability of our candidate panel SNPs to detect successful spawning after a translocation event. ConclusionThis study provides a set of SNPs tailored for monitoring genetic diversity and structure in Paiute Cutthroat Trout refuge populations. Future work should include development of a high-throughput genotyping assay to implement these candidate panel SNPs for ongoing management. This would enable consistency over time with genetic studies and be a foundational tool for repeated evaluation of conservation actions such as reintroductions and augmentations. Lay SummaryWe identified genetic markers to help track and protect one of the rarest trout in the United States. This work supports long-term conservation by making it easier to monitor isolated populations and measure the success of efforts to restore the species.

genomics↗

bioRxiv2024

MAXTEMP: A method to maximize precision of the temporal method for estimating Ne in genetic monitoring programs

We introduce a new software program, MAXTEMP, that maximizes precision of the temporal method for estimating effective population size (Ne) in genetic monitoring programs, which are increasingly used to systematically track changes in global biodiversity. Scientists and managers are typically most interested in Ne for individual generations, either to match with single-generation estimates of census size (N) or to evaluate consequences of specific management actions or environmental events. Systematically sampling every generation produces a time series of single-generation estimates of temporal [Formula], which can then be used to estimate Ne; however, these estimates have relatively low precision because each reflects just a single episode of genetic drift. Systematic sampling also produces an array of multigenerational temporal estimates that collectively contain a great deal of information about genetic drift that, however, can be difficult to interpret. Here we show how additional information contained in multigenerational temporal estimates can be leveraged to increase precision of [Formula] for individual generations. Using information from one additional generation before and after a target generation can reduce the standard deviation of [Formula] by up to 50%, which not only tightens confidence intervals around [Formula] but also reduces the incidence of extreme estimates. Practical application of MAXTEMP is illustrated with data for a long-term genetic monitoring program for California delta smelt. A second feature of MAXTEMP, which allows one to estimate Ne in an unsampled generation using a combination of temporal and single-sample estimates of Ne from sampled generations, is also described and evaluated.

genetics↗