scholarly journals Gut microbiome heritability is nearly universal but environmentally contingent

Science ◽  
2021 ◽  
Vol 373 (6551) ◽  
pp. 181-186 ◽  
Author(s):  
Laura Grieneisen ◽  
Mauna Dasari ◽  
Trevor J. Gould ◽  
Johannes R. Björk ◽  
Jean-Christophe Grenier ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Dry Season ◽  
Genetic Effects ◽  
Sample Sizes ◽  
Diet Diversity ◽  
Large Sample ◽  
Host Genetic ◽  
Longitudinal Profiles ◽  
Wild Baboons ◽  
Shared Environments

Relatives have more similar gut microbiomes than nonrelatives, but the degree to which this similarity results from shared genotypes versus shared environments has been controversial. Here, we leveraged 16,234 gut microbiome profiles, collected over 14 years from 585 wild baboons, to reveal that host genetic effects on the gut microbiome are nearly universal. Controlling for diet, age, and socioecological variation, 97% of microbiome phenotypes were significantly heritable, including several reported as heritable in humans. Heritability was typically low (mean = 0.068) but was systematically greater in the dry season, with low diet diversity, and in older hosts. We show that longitudinal profiles and large sample sizes are crucial to quantifying microbiome heritability, and indicate scope for selection on microbiome characteristics as a host phenotype.

scholarly journals The seasonal changes of the gut microbiome of the population living in traditional lifestyles are represented by characteristic species-level and functional-level SNP enrichment patterns

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xue Zhu ◽  
Jiyue Qin ◽  
Chongyang Tan ◽  
Kang Ning
Keyword(s):  
Gut Microbiome ◽  
Seasonal Changes ◽  
Dry Season ◽  
Urban Setting ◽  
Snp Analysis ◽  
Wet Season ◽  
Human Gut ◽  
Human Gut Microbiome ◽  
Genome Level ◽  
Prevalent Species

Abstract Background Most studies investigating human gut microbiome dynamics are conducted on humans living in an urban setting. However, few studies have researched the gut microbiome of the populations living traditional lifestyles. These understudied populations are arguably better subjects in answering human-gut microbiome evolution because of their lower exposure to antibiotics and higher dependence on natural resources. Hadza hunter-gatherers in Tanzania have exhibited high biodiversity and seasonal patterns in their gut microbiome composition at the family level, where some taxa disappear in one season and reappear later. Such seasonal changes have been profiled, but the nucleotide changes remain unexplored at the genome level. Thus, it is still elusive how microbial communities change with seasonal changes at the genome level. Results In this study, we performed a strain-level single nucleotide polymorphism (SNP) analysis on 40 Hadza fecal metagenome samples spanning three seasons. With more SNP presented in the wet season, eight prevalent species have significant SNP enrichment with the increasing number of SNP calling by VarScan2, among which only three species have relatively high abundances. Eighty-three genes have the most SNP distributions between the wet season and dry season. Many of these genes are derived from Ruminococcus obeum, and mainly participated in metabolic pathways including carbon metabolism, pyruvate metabolism, and glycolysis. Conclusions Eight prevalent species have significant SNP enrichments with the increasing number of SNP, among which only Eubacterium biforme, Eubacterium hallii and Ruminococcus obeum have relatively high species abundances. Many genes in the microbiomes also presented characteristic SNP distributions between the wet season and the dry season. This implies that the seasonal changes might indirectly impact the mutation patterns for specific species and functions for the gut microbiome of the population that lives in traditional lifestyles through changing the diet in wet and dry seasons, indicating the role of these variants in these species’ adaptation to the changing environment and diets.

scholarly journals High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Weitong Cui ◽  
Huaru Xue ◽  
Lei Wei ◽  
Jinghua Jin ◽  
Xuewen Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Small Sample ◽  
Differentially Expressed ◽  
Cancer Type ◽  
Rna Seq ◽  
Sample Sizes ◽  
Large Sample ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract Background RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible. Results Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis. Conclusions High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

scholarly journals Diet diversity and environment determine the intestinal microbiome and bacterial pathogen load of fire salamanders

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yu Wang ◽  
Hannah K. Smith ◽  
Evy Goossens ◽  
Lionel Hertzog ◽  
Molly C. Bletz ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Animal Health ◽  
Bacterial Pathogen ◽  
Intestinal Microbiome ◽  
Potential Health ◽  
Diet Diversity ◽  
Significant Difference ◽  
Host Diet ◽  
Intestinal Pathogen ◽  
In Fire

AbstractDiverse communities of symbiotic microbes inhabit the digestive systems of vertebrates and play a crucial role in animal health, and host diet plays a major role in shaping the composition and diversity of these communities. Here, we characterized diet and gut microbiome of fire salamander populations from three Belgian forests. We carried out DNA metabarcoding on fecal samples, targeting eukaryotic 18S rRNA of potential dietary prey items, and bacterial 16S rRNA of the concomitant gut microbiome. Our results demonstrated an abundance of soft-bodied prey in the diet of fire salamanders, and a significant difference in the diet composition between males and females. This sex-dependent effect on diet was also reflected in the gut microbiome diversity, which is higher in males than female animals. Proximity to human activities was associated with increased intestinal pathogen loads. Collectively, the data supports a relationship between diet, environment and intestinal microbiome in fire salamanders, with potential health implications.

Very large sample sizes

BMJ ◽  
2009 ◽  
Vol 338 (feb25 2) ◽  
pp. b737-b737 ◽  
Author(s):  
J. Fletcher
Keyword(s):  
Sample Sizes ◽  
Large Sample

Concentration inequalities for the empirical distribution of discrete distributions: beyond the method of types

2019 ◽  
Vol 9 (4) ◽  
pp. 813-850 ◽  
Author(s):  
Jay Mardia ◽  
Jiantao Jiao ◽  
Ervin Tánczos ◽  
Robert D Nowak ◽  
Tsachy Weissman
Keyword(s):  
Sample Size ◽  
Empirical Distribution ◽  
Discrete Distributions ◽  
Concentration Inequalities ◽  
Sample Sizes ◽  
Alphabet Size ◽  
Large Sample ◽  
Kl Divergence ◽  
The Difference ◽  
True Distribution

Abstract We study concentration inequalities for the Kullback–Leibler (KL) divergence between the empirical distribution and the true distribution. Applying a recursion technique, we improve over the method of types bound uniformly in all regimes of sample size $n$ and alphabet size $k$, and the improvement becomes more significant when $k$ is large. We discuss the applications of our results in obtaining tighter concentration inequalities for $L_1$ deviations of the empirical distribution from the true distribution, and the difference between concentration around the expectation or zero. We also obtain asymptotically tight bounds on the variance of the KL divergence between the empirical and true distribution, and demonstrate their quantitatively different behaviours between small and large sample sizes compared to the alphabet size.

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

Genes ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 484 ◽  
Author(s):  
Steury ◽  
Currey ◽  
Cresko ◽  
Bohannan
Keyword(s):  
Gut Microbiome ◽  
Genetic Divergence ◽  
Population Genetic ◽  
Host Population ◽  
Threespine Stickleback ◽  
Wild Host ◽  
Microbiome Research ◽  
Host Genetic ◽  
Combine Population ◽  
Natural Ecology

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.

What's the Score?

2000 ◽  
Vol 21 (1) ◽  
pp. 57-58
Author(s):  
David Birnbaum
Keyword(s):  
Confidence Interval ◽  
Infection Rate ◽  
Binomial Distribution ◽  
Sample Sizes ◽  
Negative Numbers ◽  
Large Sample ◽  
Infection Surveillance

AbstractIf you have calculated a confidence interval for an infection rate and found the interval extending into meaningless negative numbers, chances are the error is due to use of approximation formulae. Many of us unknowingly were taught to use the Wald approximation, which does not always approximate the exact binomial distribution accurately. Poor approximation can occur in infection surveillance at both small and large sample sizes.

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