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Abstract Signals of natural selection can be quickly eroded in high gene flow systems, curtailing efforts to understand how and when genetic adaptation occurs in the ocean. This long‐standing, unresolved topic in ecology and evolution has renewed importance because changing environmental conditions are driving range expansions that may necessitate rapid evolutionary responses. One example occurs in Kellet's whelk (Kelletia kelletii), a common subtidal gastropod with an ~40‐ to 60‐day pelagic larval duration that expanded their biogeographic range northwards in the 1970s by over 300 km. To test for genetic adaptation, we performed a series of experimental crosses with Kellet's whelk adults collected from their historical (HxH) and recently expanded range (ExE), and conducted RNA‐Seq on offspring that we reared in a common garden environment. We identified 2770 differentially expressed genes (DEGs) between 54 offspring samples with either only historical range (HxH offspring) or expanded range (ExE offspring) ancestry. Using SNPs called directly from the DEGs, we assigned samples of known origin back to their range of origin with unprecedented accuracy for a marine species (92.6% and 94.5% for HxH and ExE offspring, respectively). The SNP with the highest predictive importance occurred on triosephosphate isomerase (TPI), an essential metabolic enzyme involved in cold stress response.TPIwas significantly upregulated and contained a non‐synonymous mutation in the expanded range. Our findings pave the way for accurately identifying patterns of dispersal, gene flow and population connectivity in the ocean by demonstrating that experimental transcriptomics can reveal mechanisms for how marine organisms respond to changing environmental conditions. 

ABSTRACT High‐grading bias is the overestimation power in a subset of loci caused by model overfitting. Using both empirical and simulated datasets, we show that high‐grading bias can cause severe overestimation of population structure, and thus mislead investigators, whenever highly informative or high‐F_STmarkers are chosen (i.e., ascertained) and used for subsequent assessments, a common practice in population genetic studies. This problem can occur in panmictic populations with no local adaptation.Biased results from choosing high‐F_STmarkers may have severe downstream implications for management and conservation, such as erroneous conservation unit delineation, which could squander limited conservation resources to protect incorrectly defined ‘populations’. Furthermore, we caution that high‐grading is not limited toF_STapproaches; high‐grading bias is a concern whenever a small subset of markers are first chosen to explain differences among groups based on their degree of difference and are subsequently reused to estimate the degree of difference among those groups. For example, selecting highF_STloci for use in a GT‐seq panel or using differentially expressed genes to plot sample membership in multivariate space can both result in spurious structure when none exists. We illustrate that using statistically based outlier tests in place of arbitraryF_STcut‐offs can reduce bias. Alternatively, permutation tests or cross‐evaluation can be used to detect high‐grading bias. We provide an R package, PCAssess, to help researchers detect and prevent high‐grading bias in genetic datasets by automating permutation tests and principal component analyses (https://github.com/hemstrow/PCAssess). 

Abstract The relationship between a species' growth rate and its size—its growth function—represents essential biological information for supporting sustainable fisheries and wildlife management. Yet, growth functions are known for only a fraction of species. Progress is especially limited in marine invertebrates, including shellfish, due to challenges rearing early life stages in the lab and identifying statolith ring patterns indicative of individual age. We overcome these challenges by deriving a species' growth function using multi‐year size‐frequency population survey data collected from 71 subtidal sites over 35 years. We fit Gaussian mixture models to the data at each survey site and year to identify cohorts, then tracked cohorts between survey years to estimate cohort growth over time. We then used the estimates of growth to parameterize growth functions containing initial and asymptotic size constraints based on the survey data. We demonstrated our method with the kelp forest gastropod and commercial fisheries species, Kellet's whelk (Kelletia kelletii). The assembled survey data included 28,816 whelks, 9–180 mm in shell length. Through cohort tracking, we generated 297 estimates of cohort growth. We fit seven growth functions to the growth estimates and used information criterion and least squares to select the best‐fit model; in this case the Richards, characterized by maximum initial growth at small size that initially declines exponentially and then linearly with size, reaching asymptotic growth by approximately 40 years of age. We also analyzed and compared select portions of the population survey data to test for biogeographic and fisheries management effects on growth. The method we developed can support research on species with size‐frequency population survey data, and the function we derived for Kellet's whelk can inform research on its population biology and sustainable fisheries management. 

Understanding the genomic characteristics of non-model organisms can bridge research gaps between ecology and evolution. However, the lack of a reference genome and transcriptome for these species makes their study challenging. Here, we complete the first full genome and transcriptome sequence assembly of the non-model organism Kellet’s whelk,Kelletia kelletii, a marine gastropod exhibiting a poleward range expansion coincident with climate change. We used a combination of Oxford Nanopore Technologies, PacBio, and Illumina sequencing platforms and integrated a set of bioinformatic pipelines to create the most complete and contiguous genome documented among the Buccinoidea superfamily to date. Genome validation revealed relatively high completeness with low missing metazoan Benchmarking Universal Single-Copy Orthologs (BUSCO) and an average coverage of ∼70x for all contigs. Genome annotation identified a large number of protein-coding genes similar to some other closely related species, suggesting the presence of a complex genome structure. Transcriptome assembly and analysis of individuals during their period of peak embryonic development revealed highly expressed genes associated with specific Gene Ontology (GO) terms and metabolic pathways, most notably lipid, carbohydrate, glycan, and phospholipid metabolism. We also identified numerous heat shock proteins (HSPs) in the transcriptome and genome that may be related to coping with thermal stress during the sessile life history stage. A robust reference genome and transcriptome for the non-model organismK. kelletiiprovide resources to enhance our understanding of its ecology and evolution and potential mechanisms of range expansion for marine species facing environmental changes. 

Next-generation sequencing technologies, such as Nanopore MinION, Illumina Hiseq and Novaseq, and PacBio Sequel II, hold immense potential for advancing genomic research on non-model organisms, including the vast majority of marine species. However, application of these technologies to marine invertebrate species is often impeded by challenges in extracting and purifying their genomic DNA due to high polysaccharide content and other secondary metabolites. In this study, we help resolve this issue by developing and testing DNA extraction protocols for Kellet’s whelk (Kelletia kelletii), a subtidal gastropod with ecological and commercial importance, by comparing four DNA extraction methods commonly used in marine invertebrate studies. In our comparison of extraction methods, the Salting Out protocol was the least expensive, produced the highest DNA yields, produced consistent high DNA quality, and had low toxicity. We validated the protocol using an independent set of tissue samples, then applied it to extract high-molecular-weight (HMW) DNA from over three thousand Kellet’s whelk tissue samples. The protocol demonstrated scalability and, with added clean-up, suitability for RAD-seq, GT-seq, as well as whole genome sequencing using both long read (ONT MinION) and short read (Illumina NovaSeq) sequencing platforms. Our findings offer a robust and versatile DNA extraction and clean-up protocol for supporting genomic research on non-model marine organisms, to help mediate the under-representation of invertebrates in genomic studies.