Geology topics

Yue Shi

Publications and source records attributed to Yue Shi.

5 recordsLinked to original sources

USGS2023

Prey ration, temperature, and predator species influence digestion rates of prey DNA inferred from qPCR and metabarcoding

Diet analysis is a vital tool for understanding trophic interactions and is frequently used to inform conservation and management. Molecular approaches can identify diet items that are impossible to distinguish using more traditional visual-based methods. Yet, our understanding of how different variables, such as predator species or prey ration size, influence molecular diet analysis is still incomplete. Here, we conducted a large feeding trial to assess the impact that ration size, predator species, and temperature had on digestion rates estimated with visual identification, qPCR, and metabarcoding. Our trial was conducted by feeding two rations of Chinook salmon ( Oncorhynchus tshawytscha ) to two piscivorous fish species (largemouth bass [ Micropterus salmoides ] and channel catfish [ Ictalurus punctatus ]) held at two different temperatures (15.5 and 18.5°C) and sacrificed at regular intervals up to 120 h from the time of ingestion to quantify the prey contents remaining in the digestive tract. We found that ration size, temperature, and predator species all influenced digestion rate, with some indication that ration size had the largest influence. DNA-based analyses were able to identify salmon smolt prey in predator gut samples for much longer than visual analysis (~12 h for visual analysis vs. ~72 h for molecular analyses). Our study provides evidence that modelling the persistence of prey DNA in predator guts for molecular diet analyses may be feasible using a small set of controlling variables for many fish systems.

Molecular Ecology Resources↗

USGS2023

Toward absolute abundance for conservation applications: Estimating the number of contributors via microhaplotype genotyping of mixed-DNA sample

Molecular methods including metabarcoding and quantitative polymerase chain reaction have shown promise for estimating species abundance by quantifying the concentration of genetic material in field samples. However, the relationship between specimen abundance and detectable concentrations of genetic material is often variable in practice. DNA mixture analysis represents an alternative approach to quantify specimen abundance based on the presence of unique alleles in a sample. The DNA mixture approach provides novel opportunities to inform ecology and conservation by estimating the absolute abundance of target taxa through molecular methods; yet, the challenges associated with genotyping many highly variable markers in mixed-DNA samples have prevented its widespread use. To advance molecular approaches for abundance estimation, we explored the utility of microhaplotypes for DNA mixture analysis by applying a 125-marker panel to 1179 Chinook salmon ( Oncorhynchus tshawytscha ) smolts from the Sacramento-San Joaquin Delta, California, USA. We assessed the accuracy of DNA mixture analysis through a combination of mock mixtures containing DNA from up to 20 smolts and a trophic ecological application enumerating smolts in predator diets. Mock DNA mixtures of up to 10 smolts could reliably be resolved using microhaplotypes, and increasing the panel size would likely facilitate the identification of more individuals. However, while analysis of predator gastrointestinal tract contents indicated DNA mixture analysis could discern the presence of multiple prey items, poor and variable DNA quality prevented accurate genotyping and abundance estimation. Our results indicate that DNA mixture analysis can perform well with high-quality DNA, but methodological improvements in genotyping degraded DNA are necessary before this approach can be used on marginal-quality samples.

California↗

USGS2022

High-density genomic data reveal fine-scale population structure and pronounced islands of adaptive divergence in lake whitefish (Coregonus clupeaformis) from Lake Michigan

Understanding patterns of genetic structure and adaptive variation in natural populations is crucial for informing conservation and management. Past genetic research using 11 microsatellite loci identified six genetic stocks of lake whitefish ( Coregonus clupeaformis ) within Lake Michigan, USA. However, ambiguity in genetic stock assignments suggested those neutral microsatellite markers did not provide adequate power for delineating lake whitefish stocks in this system, prompting calls for a genomics approach to investigate stock structure. Here, we generated a dense genomic dataset to characterize population structure and investigate patterns of neutral and adaptive genetic diversity among lake whitefish populations in Lake Michigan. Using Rapture sequencing, we genotyped 829 individuals collected from 17 baseline populations at 197,588 SNP markers after quality filtering. Although the overall pattern of genetic structure was similar to the previous microsatellite study, our genomic data provided several novel insights. Our results indicated a large genetic break between the northwestern and eastern sides of Lake Michigan, and we found a much greater level of population structure on the eastern side compared to the northwestern side. Collectively, we observed five genomic islands of adaptive divergence on five different chromosomes. Each island displayed a different pattern of population structure, suggesting that combinations of genotypes at these adaptive regions are facilitating local adaptation to spatially heterogenous selection pressures. Additionally, we identified a large linkage disequilibrium block of ~8.5 Mb on chromosome 20 that is suggestive of a putative inversion but with a low frequency of the minor haplotype. Our study provides a comprehensive assessment of population structure and adaptive variation that can help inform the management of Lake Michigan's lake whitefish fishery and highlights the utility of incorporating adaptive loci into fisheries management.

Michigan, Wisconsin↗

USGS2021

Gene flow influences the genomic architecture of local adaptation in six riverine fish species

Understanding how gene flow influences adaptive divergence is important for predicting adaptive responses. Theoretical studies suggest that when gene flow is high, clustering of adaptive genes in fewer genomic regions would protect adaptive alleles from recombination and thus be selected for, but few studies have tested it with empirical data. Here, we used restriction site-associated sequencing to generate genomic data for six fish species with contrasting life histories from six reaches of the Upper Mississippi River System, USA. We used four differentiation-based outlier tests and three genotype–environment association analyses to define neutral single nucleotide polymorphisms (SNPs) and outlier SNPs that were putatively under selection. We then examined the distribution of outlier SNPs along the genome and investigated whether these SNPs were found in genomic islands of differentiation and inversions. We found that gene flow varied among species, and outlier SNPs were clustered more tightly in species with higher gene flow. The two species with the highest overall F ST (0.0303–0.0720) and therefore lowest gene flow showed little evidence of clusters of outlier SNPs, with outlier SNPs in these species spreading uniformly across the genome. In contrast, nearly all outlier SNPs in the species with the lowest F ST (0.0003) were found in a single large putative inversion. Two other species with intermediate gene flow ( F ST ~ 0.0025–0.0050) also showed clustered genomic architectures, with most islands of differentiation clustered on a few chromosomes. Our results provide important empirical evidence to support the hypothesis that increasingly clustered architecture of local adaptation is associated with high gene flow.

Molecular Ecology↗

USGS2021

eDNA metabarcoding outperforms traditional fisheries sampling and reveals fine-scale heterogeneity in a temperate freshwater lake

Understanding biodiversity in aquatic systems is critical to ecological research and conservation efforts, but accurately measuring species richness using traditional methods can be challenging. Environmental DNA (eDNA) metabarcoding, which uses high-throughput sequencing and universal primers to amplify DNA from multiple species present in an environmental sample, has shown great promise for augmenting results from traditional sampling to characterize fish communities in aquatic systems. Few studies, however, have compared exhaustive traditional sampling with eDNA metabarcoding of corresponding water samples at a small spatial scale. We intensively sampled Boardman Lake (1.4 km 2 ) in Michigan, USA, from May to June in 2019 using gill and fyke nets and paired each net set with lake water samples collected in triplicate. We analyzed water samples using eDNA metabarcoding with 12S and 16S fish-specific primers and compared estimates of fish diversity among methods. In total, we set 60 nets and analyzed 180 1 L lake water samples. We captured a total of 12 fish species in our traditional gear and detected 40 taxa in the eDNA water samples, which included all the species observed in nets. The 12S and 16S assays detected a comparable number of taxa, but taxonomic resolution varied between the two genes. In our traditional gear, there was a clear difference in the species selectivity between the two net types, and there were several species commonly detected in the eDNA samples that were not captured in nets. Finally, we detected spatial heterogeneity in fish community composition across relatively small scales in Boardman Lake with eDNA metabarcoding, but not with traditional sampling. Our results demonstrated that eDNA metabarcoding was substantially more efficient than traditional gear for estimating community composition, highlighting the utility of eDNA metabarcoding for assessing species diversity and informing management and conservation.

Michigan↗