Deviations of the site frequency spectrum of mutations (SFS) from neutral expectations may be caused by natural selection or by demographic processes such as population subdivision or temporal changes in population size. As most widespread temperate and boreal tree species have expanded from glacial refugia in the past 13,000 years, colonization bottlenecks associated with this migration may have left variable demographic signatures among geographic populations corresponding to distance from the refugia. To determine whether the signature of postglacial re-colonization has skewed the SFS in the widely distributed conifer Sitka spruce (Picea sitchensis (Bong.) Carr.), we re-sequenced 153 nuclear genes in six populations from across the species range. We found that while the SFS for the pooled sample produced negative values for Tajima's D and Fay and Wu's H, these statistics exhibited strong clinal variation when populations were analysed separately (R(2) = 0.84, P = 0.007 for Tajima's D and R(2) = 0.65, P = 0.033 for Fay and Wu's H). When historical bottlenecks of varying age were simulated using approximate Bayesian computation, distance of populations from the southern range limit explained most of the variation in bottleneck timing among populations (R(2) = 0.89, P = 0.003). These data suggest that sequential population bottlenecks during postglacial re-colonization have resulted in diverse among-population signatures within the contemporary SFS in Sitka spruce, with rare variants more common in the south, and medium-frequency variants more common in the north. Our results also emphasize the need to consider sampling strategy and to explore population-specific null demographic models in surveys of nucleotide variation in widely distributed species.
Locally adapted temperate tree populations exhibit genetic trade-offs among climate-related traits that can be exacerbated by selective breeding and are challenging to manage under climate change. To inform climatically adaptive forest management, we investigated the genetic architecture and impacts of selective breeding on four climate-related traits in 105 natural and 20 selectively bred lodgepole pine populations from western Canada. Growth, cold injury, growth initiation, and growth cessation phenotypes were tested for associations with 18,600 single-nucleotide polymorphisms (SNPs) in natural populations to identify “positive effect alleles” (PEAs). The effects of artificial selection for faster growth on the frequency of PEAs associated with each trait were quantified in breeding populations from different climates. Substantial shifts in PEA proportions and frequencies were observed across many loci after two generations of selective breeding for height, and responses of phenology-associated PEAs differed strongly among climatic regions. Extensive genetic overlap was evident among traits. Alleles most strongly associated with greater height were often associated with greater cold injury and delayed phenology, although it is unclear whether potential trade-offs arose directly from pleiotropy or indirectly via genetic linkage. Modest variation in multilocus PEA frequencies among populations was associated with large phenotypic differences and strong climatic gradients, providing support for assisted gene flow polices. Relationships among genotypes, phenotypes, and climate in natural populations were maintained or strengthened by selective breeding. However, future adaptive phenotypes and assisted gene flow may be compromised if selective breeding further increases the PEA frequencies of SNPs involved in adaptive trade-offs among climate-related traits.
Despite their suitability for studying evolution, many conifer species have large and repetitive giga‐genomes (16–31 Gbp) that create hurdles to producing high coverage SNP data sets that capture diversity from across the entirety of the genome. Due in part to multiple ancient whole genome duplication events, gene family expansion and subsequent evolution within Pinaceae, false diversity from the misalignment of paralog copies creates further challenges in accurately and reproducibly inferring evolutionary history from sequence data. Here, we leverage the cost‐saving benefits of pool‐seq and exome‐capture to discover SNPs in two conifer species, Douglas‐fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco, Pinaceae) and jack pine (Pinus banksiana Lamb., Pinaceae). We show, using minimal baseline filtering, that allele frequencies estimated from pooled individuals show a strong, positive correlation with those estimated by sequencing the same population as individuals (r > .948), on par with such comparisons made in model organisms. Further, we highlight the utility of haploid megagametophyte tissue for identifying sites that are probably due to misaligned paralogs. Together with additional minor filtering, we show that it is possible to remove many of the loci with large frequency estimate discrepancies between individual and pooled sequencing approaches, improving the correlation further (r > .973). Our work addresses bioinformatic challenges in non‐model organisms with large and complex genomes, highlights the use of megagametophyte tissue for the identification of paralogous artefacts, and suggests the combination of pool‐seq and exome capture to be robust for further evolutionary hypothesis testing in these systems.
Operational methods are needed for screening genotypes in breeding programs for adaptive traits. In this article, we present a detailed description of one procedure for screening improved coastal Douglas-fir seedlings and saplings for cold hardiness, based on research results of the Pacific Northwest Tree Improvement Research Cooperative. Artificial freeze testing of detached shoots from genetic tests, followed by visual scoring of injury, has proved to be an efficient, reliable, and cost-effective method of screening large numbers of genotypes. Relevant research results are summarized, and practical details of this methodology are presented for straightforward implementation by Douglas-fir breeders and researchers. West. J. Appl. For. 15(3):129-136.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.