Host genetic selection for cold tolerance shapes microbiome composition and modulates its response to temperature.
Ontology highlight
ABSTRACT:
SUBMITTER: Kokou F
PROVIDER: S-EPMC6277203 | biostudies-literature | 2018 Nov
REPOSITORIES: biostudies-literature
Publications
Host genetic selection for cold tolerance shapes microbiome composition and modulates its response to temperature.
Kokou Fotini F Sasson Goor G Nitzan Tali T Doron-Faigenboim Adi A Harpaz Sheenan S Cnaani Avner A Mizrahi Itzhak I
eLife 20181120
The hologenome concept proposes that microbes and their host organism are an independent unit of selection. Motivated by this concept, we hypothesized that thermal acclimation in poikilothermic organisms, owing to their inability to maintain their body temperature, is connected to their microbiome composition. To test this hypothesis, we used a unique experimental setup with a transgenerational selective breeding scheme for cold tolerance in tropical tilapias. We tested the effects of the select ...[more]
Similar Datasets
Project description:The gut microbiome plays a significant role in health and disease, and there is mounting evidence indicating that the microbial composition is regulated in part by host genetics. Heritability estimates for microbial abundance in mice and humans range from (0.05-0.45), indicating that 5-45% of inter-individual variation can be explained by genetics. Through twin studies, genetic association studies, systems genetics, and genome-wide association studies (GWAS), hundreds of specific host genetic loci have been shown to associate with the abundance of discrete gut microbes. Using genetically engineered knock-out mice, at least 30 specific genes have now been validated as having specific effects on the microbiome. The relationships among of host genetics, microbiome composition, and abundance, and disease is now beginning to be unraveled through experiments designed to test causality. The genetic control of disease and its relationship to the microbiome can manifest in multiple ways. First, a genetic variant may directly cause the disease phenotype, resulting in an altered microbiome as a consequence of the disease phenotype. Second, a genetic variant may alter gene expression in the host, which in turn alters the microbiome, producing the disease phenotype. Finally, the genetic variant may alter the microbiome directly, which can result in the disease phenotype. In order to understand the processes that underlie the onset and progression of certain diseases, future research must take into account the relationship among host genetics, microbiome, and disease phenotype, and the resources needed to study these relationships.
| S-EPMC8295090 | biostudies-literature
Project description:BackgroundGenetic predisposition increases risk for asthma, and distinct nasal microbial compositions are associated with asthma. Host genetics might shape nasal microbiome composition.ObjectiveWe examined associations between host genetics and nasal microbiome composition.MethodsNasal samples were collected from 584 participants from the Mount Sinai Health System, New York. Seventy-seven follow-up samples were collected from a subset of 40 participants. 16S rRNA sequencing and RNA sequencing were performed on nasal samples. Beta diversity was calculated, variant calling on RNA sequencing data was performed, and genetic relatedness between individuals was determined. Using linear regression models, we tested for associations between genetic relatedness and nasal microbiome composition.ResultsThe median age of the cohort was 14.6 (interquartile range 11.2-19.5) years, with participants representing diverse ancestries and 52.7% of the cohort being female. For participants who provided follow-up samples, the median time between samples was 5.1 (interquartile range 1.4-7.2) months. Nasal microbiome composition similarity as reflected by beta diversity was significantly higher within subjects over time versus between subjects (coefficient = 0.091, P = 2.84-7). There was no significant association between genetic relatedness and beta diversity (coefficient = -0.05, P = .29). Additional analyses exploring the relationship between beta diversity and genetic variance yielded similar results.ConclusionHost genetics has little influence on nasal microbiome composition.
| S-EPMC9643606 | biostudies-literature
Project description:The origin, composition, and significance of the distal male urethral microbiome are unclear, but vaginal microbiome dysbiosis is linked to new sex partners and several urogynecological syndromes. We characterized 110 urethral specimens from men without urethral symptoms, infections, or inflammation using shotgun metagenomics. Most urethral specimens contain characteristic lactic acid bacteria and Corynebacterium spp. In contrast, several bacteria associated with vaginal dysbiosis were present only in specimens from men who reported vaginal intercourse. Sexual behavior, but not other evaluated behavioral, demographic, or clinical variables, strongly associated with inter-specimen variance in urethral microbiome composition. Thus, the male urethra supports a simple core microbiome that is established independent of sexual exposures but can be re-shaped by vaginal sex. Overall, the results suggest that urogenital microbiology and sexual behavior are inexorably intertwined, and show that the male urethra harbors female urogenital pathobionts.
| S-EPMC10040456 | biostudies-literature
Project description:BackgroundThe composition of bacteria in and on the human body varies widely across human individuals, and has been associated with multiple health conditions. While microbial communities are influenced by environmental factors, some degree of genetic influence of the host on the microbiome is also expected. This study is part of an expanding effort to comprehensively profile the interactions between human genetic variation and the composition of this microbial ecosystem on a genome- and microbiome-wide scale.ResultsHere, we jointly analyze the composition of the human microbiome and host genetic variation. By mining the shotgun metagenomic data from the Human Microbiome Project for host DNA reads, we gathered information on host genetic variation for 93 individuals for whom bacterial abundance data are also available. Using this dataset, we identify significant associations between host genetic variation and microbiome composition in 10 of the 15 body sites tested. These associations are driven by host genetic variation in immunity-related pathways, and are especially enriched in host genes that have been previously associated with microbiome-related complex diseases, such as inflammatory bowel disease and obesity-related disorders. Lastly, we show that host genomic regions associated with the microbiome have high levels of genetic differentiation among human populations, possibly indicating host genomic adaptation to environment-specific microbiomes.ConclusionsOur results highlight the role of host genetic variation in shaping the composition of the human microbiome, and provide a starting point toward understanding the complex interaction between human genetics and the microbiome in the context of human evolution and disease.
| S-EPMC4570153 | biostudies-literature
Project description:Bacterial vaginosis (BV) affects 20% of women worldwide and is associated with adverse reproductive health outcomes and increased risk for HIV. Typically, BV represents a shift in the vaginal microbiome from one that is dominated by Lactobacillus to one that is diverse. Persistent racial differences in BV and diverse vaginal microbiome composition overlap with racial disparities in risks for HIV and sexually transmitted infection, especially among women of African descent. Risk factors for BV and nonoptimal vaginal microbiome include sexual practices, yet racial differences persist when adjusted for behavioral factors, suggesting a host genetic component. Here, we perform a genome-wide association study on vaginal microbiome traits in Kenyan women. Linear regression and logistic regression were performed, adjusting for age and principal components of genetic ancestry, to evaluate the association between Lactobacillus crispatus, Lactobacillus iners, Gardnerella vaginalis, Shannon diversity index, and community state type (CST) with host genetic single nucleotide polymorphisms (SNPs). We identified novel genomic loci associated with the vaginal microbiome traits, though no SNP reached genome-wide significance. During pathway enrichment analysis, Toll-like receptors (TLRs), cytokine production, and other components of innate immune response were associated with L. crispatus, L. iners, and CST. Multiple previously reported genomic loci were replicated, including IL-8 (Shannon, CST), TIRAP (L. iners, Shannon), TLR2 (Shannon, CST), MBL2 (L. iners, G. vaginalis, CST), and MYD88 (L. iners, Shannon). These genetic associations suggest a role for the innate immune system and cell signaling in vaginal microbiome composition and susceptibility to nonoptimal vaginal microbiome.IMPORTANCE Globally, bacterial vaginosis (BV) is a common condition in women. BV is associated with poorer reproductive health outcomes and HIV risk. Typically, BV represents a shift in the vaginal microbiome from one that is dominated by Lactobacillus to one that is diverse. Despite many women having similar exposures, the prevalence of BV and nonoptimal vaginal microbiome is increased for women of African descent, suggesting a possible role for host genetics. We conducted a genome-wide association study of important vaginal microbiome traits in Kenyan women. We identified novel genetic loci and biological pathways related to mucosal immunity, cell signaling, and infection that were associated with vaginal microbiome traits; we replicated previously reported loci associated with mucosal immune response. These results provide insight into potential host genetic influences on vaginal microbiome composition and can guide larger longitudinal studies, with genetic and functional comparison across microbiome sites within individuals and across populations.
| S-EPMC7394359 | biostudies-literature
Project description:Population genomic data has revealed patterns of genetic variation associated with adaptation in many taxa. Yet understanding the adaptive process that drives such patterns is challenging; it requires disentangling the ecological agents of selection, determining the relevant timescales over which evolution occurs, and elucidating the genetic architecture of adaptation. Doing so for the adaptation of hosts to their microbiome is of particular interest with growing recognition of the importance and complexity of host-microbe interactions. Here, we track the pace and genomic architecture of adaptation to an experimental microbiome manipulation in replicate populations of Drosophila melanogaster in field mesocosms. Shifts in microbiome composition altered population dynamics and led to divergence between treatments in allele frequencies, with regions showing strong divergence found on all chromosomes. Moreover, at divergent loci previously associated with adaptation across natural populations, we found that the more common allele in fly populations experimentally enriched for a certain microbial group was also more common in natural populations with high relative abundance of that microbial group. These results suggest that microbiomes may be an agent of selection that shapes the pattern and process of adaptation and, more broadly, that variation in a single ecological factor within a complex environment can drive rapid, polygenic adaptation over short timescales.
| S-EPMC6778213 | biostudies-literature
Project description:The microbiome is the collection of all microbial genes and can be investigated by sequencing highly variable regions of 16S ribosomal RNA (rRNA) genes. Evidence suggests that environmental factors and host genetics may interact to impact human microbiome composition. Identifying host genetic variants associated with human microbiome composition not only provides clues for characterizing microbiome variation but also helps to elucidate biological mechanisms of genetic associations, prioritize genetic variants, and improve genetic risk prediction. Since a microbiota functions as a community, it is best characterized by β diversity; that is, a pairwise distance matrix. We develop a statistical framework and a computationally efficient software package, microbiomeGWAS, for identifying host genetic variants associated with microbiome β diversity with or without interacting with an environmental factor. We show that the score statistics have positive skewness and kurtosis due to the dependent nature of the pairwise data, which makes p-value approximations based on asymptotic distributions unacceptably liberal. By correcting for skewness and kurtosis, we develop accurate p-value approximations, whose accuracy was verified by extensive simulations. We exemplify our methods by analyzing a set of 147 genotyped subjects with 16S rRNA microbiome profiles from non-malignant lung tissues. Correcting for skewness and kurtosis eliminated the dramatic deviation in the quantile-quantile plots. We provided preliminary evidence that six established lung cancer risk SNPs were collectively associated with microbiome composition for both unweighted (p = 0.0032) and weighted (p = 0.011) UniFrac distance matrices. In summary, our methods will facilitate analyzing large-scale genome-wide association studies of the human microbiome.
| S-EPMC9317577 | biostudies-literature
Project description:Recent studies have uncovered a strong effect of host genetic variation on the composition of host-associated microbiota. Here, we present HOMINID, a computational approach based on Lasso linear regression, that given host genetic variation and microbiome taxonomic composition data, identifies host single nucleotide polymorphisms (SNPs) that are correlated with microbial taxa abundances. Using simulated data, we show that HOMINID has accuracy in identifying associated SNPs and performs better compared with existing methods. We also show that HOMINID can accurately identify the microbial taxa that are correlated with associated SNPs. Lastly, by using HOMINID on real data of human genetic variation and microbiome composition, we identified 13 human SNPs in which genetic variation is correlated with microbiome taxonomic composition across body sites. In conclusion, HOMINID is a powerful method to detect host genetic variants linked to microbiome composition and can facilitate discovery of mechanisms controlling host-microbiome interactions.
| S-EPMC5740987 | biostudies-literature
Project description:The cold acclimation process is regulated by many factors like ambient temperature, day length, light intensity, or hormonal status. Experiments with plants grown under different light quality conditions indicate that the plant response to cold is also a light-quality-dependent process. Here, the role of light quality in the cold response was studied in 1-month-old Arabidopsis thaliana (Col-0) plants exposed for 1 week to 4°C at short-day conditions under white (100 and 20 μmol m-2s-1), blue, or red (20 μmol m-2s-1) light conditions. An upregulated expression of CBF1, inhibition of photosynthesis, and an increase in membrane damage showed that blue light enhanced the effect of low temperature. Interestingly, cold-treated plants under blue and red light showed only limited freezing tolerance compared to white light cold-treated plants. Next, the specificity of the light quality signal in cold response was evaluated in Arabidopsis accessions originating from different and contrasting latitudes. In all but one Arabidopsis accession, blue light increased the effect of cold on photosynthetic parameters and electrolyte leakage. This effect was not found for Ws-0, which lacks functional CRY2 protein, indicating its role in the cold response. Proteomics data confirmed significant differences between red and blue light-treated plants at low temperatures and showed that the cold response is highly accession-specific. In general, blue light increased mainly the cold-stress-related proteins and red light-induced higher expression of chloroplast-related proteins, which correlated with higher photosynthetic parameters in red light cold-treated plants. Altogether, our data suggest that light modulates two distinct mechanisms during the cold treatment - red light-driven cell function maintaining program and blue light-activated specific cold response. The importance of mutual complementarity of these mechanisms was demonstrated by significantly higher freezing tolerance of cold-treated plants under white light.
| S-EPMC9221075 | biostudies-literature
Project description:BackgroundCold stress is an important factor limiting rice yield in many areas of high latitude and altitude. Considerable efforts have been taken to genetically dissect cold tolerance (CT) in rice using DNA markers. Because of possible epistasis and gene?×?environment interactions associated with identified quantitative trait loci, the results of these genetic studies have unfortunately not been directly applicable to marker-assisted selection for improved rice CT. In this study, we demonstrated the utility of a selective introgression strategy for simultaneous improvement and genetic dissection of rice seedling CT.ResultsA set of japonica introgression lines (ILs) with significantly improved seedling CT were developed from four backcross populations based on two rounds of selection. Genetic characterization of these cold-tolerant ILs revealed two important aspects of genome-wide responses to strong phenotypic selection for rice CT: (1) significant over-introgression of donor alleles at 57 loci in 29 functional genetic units (FGUs) across the rice genome and (2) pronounced non-random associations between or among alleles at many unlinked CT loci. Linkage disequilibrium analyses of the detected CT loci allowed us to construct putative genetic networks (multi-locus structures) underlying the seedling CT of rice. Each network consisted of a single FGU, with high introgression as the putative regulator plus two to three groups of highly associated downstream FGUs. A bioinformatics search of rice genomic regions harboring these putative regulators identified a small set of candidate regulatory genes that are known to be involved in plant stress response.ConclusionsOur results suggest that CT in rice is controlled by multiple pathways. Genetic complementarity between parental-derived functional alleles at many loci within a given pathway provides an appropriate explanation for the commonly observed hidden diversity and transgressive segregation of CT and other complex traits in rice.
| S-EPMC4024214 | biostudies-literature