Highly reproducible 16S sequencing facilitates measurement of host genetic influences on the stickleback gut microbiome

Small, Clayton M.; Currey, Mark; Beck, Emily A.; Bassham, Susan; Cresko, William A.

doi:10.1101/497792

Cited by 4 publications

(10 citation statements)

References 70 publications

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“…Frozen guts were weighed, rapidly thawed, and samples were immediately processed for DNA extraction using a modified Dneasy Blood and Tissue Kit protocol [42]. Guts were transferred to preheated Qiagen PowerBead Solution in QIAmp PowerFecal DNA Kit garnet bead lysis tubes and homogenized on a FastPrep120.…”

Section: Methodsmentioning

confidence: 99%

Population Genetic Divergence and Environment Influence the Gut Microbiome in Oregon Threespine Stickleback

Steury

Currey

Cresko

et al. 2019

Genes

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Much of animal-associated microbiome research has been conducted in species for which little is known of their natural ecology and evolution. Microbiome studies that combine population genetic, environment, and geographic data for wild organisms can be very informative, especially in situations where host genetic variation and the environment both influence microbiome variation. The few studies that have related population genetic and microbiome variation in wild populations have been constrained by observation-based kinship data or incomplete genomic information. Here we integrate population genomic and microbiome analyses in wild threespine stickleback fish distributed throughout western Oregon, USA. We found that gut microbiome diversity and composition partitioned more among than within wild host populations and was better explained by host population genetic divergence than by environment and geography. We also identified gut microbial taxa that were most differentially abundant across environments and across genetically divergent populations. Our findings highlight the benefits of studies that investigate host-associated microbiomes in wild organisms.

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Section: Methodsmentioning

confidence: 99%

Population Genetic Divergence and Environment Influence the Gut Microbiome in Oregon Threespine Stickleback

Steury

Currey

Cresko

et al. 2019

Genes

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“…We demultiplexed 16S reads and performed quality filtering, merging, denoising, and taxonomy classification using tools from QIIME 2 v2018.8.0 40 , generally according to the methods described in Small et al 2019 29 . Briefly, we used demux ( emppaired ), vsearch ( join-pairs ), quality-filter ( q-score-joined ), and deblur ( denoise-16S ) to define amplicon sequence variants (ASVs).…”

Section: Methodsmentioning

confidence: 99%

“…Gut DNA isolations were standardized to 20ng/µl and submitted to the University of Oregon Genomics Core Facility (GC3F) for 16S rRNA (V4 region) amplicon library construction and sequencing (paired-end 150 nt reads) in a single lane on an Illumina HiSeq 4000 (See Supplementary Methods and Small et al 2019) 29 . Also sequenced were three negative control libraries, generated from a no-tissue extraction sample and two no-PCR-template reactions.…”

Section: Library Preparationmentioning

confidence: 99%

“…This degree of experimental control has been implemented more commonly for plant microbiome studies [56][57][58][59] , but it is logistically difficult for studies of free-living animal species. Because animal experiments with unrestricted co-housing require the tracking of individuals via marking or genotyping, a more convenient alternative has been to keep subjects with different genotypes physically separated but generally exposed to similar conditions 28,29,[60][61][62][63] . In contrast, we incorporated unrestricted co-housing in our current study, an approach taken in only a few other studies [64][65][66] .…”

Section: Controlled Common Garden Experiments Are Essential For Under...mentioning

confidence: 99%

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Host genomic variation shapes gut microbiome diversity in threespine stickleback fish

Small

Beck

Currey

et al. 2022

Preprint

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Variation among host-associated microbiomes is well documented across species, populations, and individuals. However, the relative importance of host genetic differences for microbiome variation has been difficult to study. While research in humans has shown that genetic variation influences microbiome differences, confounding environmental effects have been very difficult to control. Isogenic laboratory models help isolate host genetic variants to test for influences of the environment or large- effect mutations on the microbiome, but such studies seldom incorporate natural genetic variation. Thus, although many important factors potentially impacting the microbiome have been identified, most studies have failed to test for the direct influence of natural host-genetic variation on microbiome differences within a controlled environment. Understanding the relationship between host-genetic and microbial variation also has biomedical implications, such as understanding why some humans are more susceptible to chronic inflammatory disorders like Crohn's Disease and Ulcerative Colitis. To directly assess the relationship between host-genetic variation and microbiome variation, we performed a common garden experiment using laboratory lines of genetically divergent populations of threespine stickleback fish - a species that is an outbred model organism commonly used for determining the genetic basis of complex traits in the context of natural genetic variation. Using germ-free derivation and the powerful common garden design with these divergent lines, as well as hybrids between them, we detected clear associations between stickleback genetic dissimilarity and microbiome dissimilarity. Using genome-wide RAD-seq data we also identified regions of the genome underlying differences in microbiome composition. Importantly, we highlight that heritable morphological traits such as body size that are correlated with microbiome dissimilarity also need consideration in future microbiome studies.

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“…There are not many studies de ning the effects of the host genome on intestinal microbiota composition in sh. However, it has been demonstrated that there is a clear correlation between sh genotype and intestinal microbial communities [56][57][58][59][60]. Yet, to date, there is no information on the genome ´ intestinal microbiota interaction of genetically selected gilthead sea bream and how this can affect diet plasticity, health and disease resistance.…”

Section: Introductionmentioning

confidence: 99%

Genetic selection for growth drives differences in intestinal microbiota composition and parasite disease resistance in gilthead sea bream

Piazzon

Naya-Català

Perera

et al. 2020

Preprint

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Background The key effects of intestinal microbiota in animal health has led to an increasing interest in manipulating these bacterial populations to improve animal welfare. The aquaculture sector is no exception and in the last years many studies have described these populations in different fish species. However, this is not an easy task, as intestinal microbiota is composed of very dynamic populations that are influenced by different factors, such as diet, environment, host age and genetics. In the current study, we aimed to determine whether the genetic background of gilthead sea bream ( Sparus aurata ) influences the intestinal microbial composition, how these bacterial populations are modulated by dietary changes, and the effect of selection by growth on intestinal disease resistance. To that aim, three different groups of five families of gilthead sea bream that were selected during two generations for fast, intermediate or slow growth (F3 generation) were kept together in the same open-flow tanks and fed a control or a well-balanced plant-based diet during nine months. Six animals per family and dietary treatment were sacrificed and the adherent bacteria from the anterior intestinal portion were sequenced. In parallel, fish of the fast- and slow-growth groups were infected with the intestinal parasite Enteromyxum leei and the disease signs, prevalence, intensity and parasite abundance were evaluated. Results No differences were detected in alpha diversity indexes among families, and the core bacterial architecture was the prototypical composition of gilthead sea bream intestinal microbiota, indicating no dysbiosis in any of the groups. The plant-based diet significantly changed the microbiota in the intermediate- and slow-growth families, with a much lower effect on the fast-growth group. Interestingly, the smaller changes detected in the fast-growth families potentially accounted for more changes at the metabolic level when compared to the other families. Upon parasitic infection, the fast-growth group showed significantly lower disease signs and parasite intensity and abundance than the slow-growth animals. Conclusions These results show a clear genome-metagenome interaction indicating that the fast-growth families harbor a microbiota that is more flexible upon dietary changes. These animals also showed a better ability to cope with intestinal infections.

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Highly reproducible 16S sequencing facilitates measurement of host genetic influences on the stickleback gut microbiome

Cited by 4 publications

References 70 publications

Population Genetic Divergence and Environment Influence the Gut Microbiome in Oregon Threespine Stickleback

Population Genetic Divergence and Environment Influence the Gut Microbiome in Oregon Threespine Stickleback

Host genomic variation shapes gut microbiome diversity in threespine stickleback fish

Genetic selection for growth drives differences in intestinal microbiota composition and parasite disease resistance in gilthead sea bream

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