Effective number of breeders from sibship reconstruction: empirical evaluations using hatchery steelhead.

Effective population size (Ne ) is among the most important metrics in evolutionary biology. In natural populations, it is often difficult to collect adequate demographic data to calculate Ne directly. Consequently, genetic methods to estimate Ne have been developed. Two Ne estimators based on sibship reconstruction using multilocus genotype data have been developed in recent years: sibship assignment and parentage analysis without parents. In this study, we evaluated the accuracy of sibship reconstruction using a large empirical dataset from five hatchery steelhead populations with known pedigrees and using 95 single nucleotide polymorphism (SNP) markers. We challenged the software COLONY with 2,599,961 known relationships and demonstrated that reconstruction of full-sib and unrelated pairs was greater than 95% and 99% accurate, respectively. However, reconstruction of half-sib pairs was poor (<5% accurate). Despite poor half-sib reconstruction, both estimators provided accurate estimates of the effective number of breeders (Nb ) when sample sizes were near or greater than the true Nb and when assuming a monogamous mating system. We further demonstrated that both methods provide roughly equivalent estimates of Nb . Our results indicate that sibship reconstruction and current SNP panels provide promise for estimating Nb in steelhead populations in the region.

Conservation genomics of natural and managed populations: building a conceptual and practical framework.

The boom of massive parallel sequencing (MPS) technology and its applications in conservation of natural and managed populations brings new opportunities and challenges to meet the scientific questions that can be addressed. Genomic conservation offers a wide range of approaches and analytical techniques, with their respective strengths and weaknesses that rely on several implicit assumptions. However, finding the most suitable approaches and analysis regarding our scientific question are often difficult and time-consuming. To address this gap, a recent workshop entitled 'ConGen 2015' was held at Montana University in order to bring together the knowledge accumulated in this field and to provide training in conceptual and practical aspects of data analysis applied to the field of conservation and evolutionary genomics. Here, we summarize the expertise yield by each instructor that has led us to consider the importance of keeping in mind the scientific question from sampling to management practices along with the selection of appropriate genomics tools and bioinformatics challenges.

Climate variables explain neutral and adaptive variation within salmonid metapopulations: the importance of replication in landscape genetics.

Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population-specific and pairwise FST ) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate-related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and FST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin-wide to the metapopulation scale). Sensitivity analysis (leave-one-population-out) revealed consistent relationships between climate variables and FST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.