scholarly journals Genetic regulation and heritability of miRNA and mRNA expression link to phosphorus utilization and gut microbiome

Open Biology ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 200182
Author(s):  
Siriluck Ponsuksili ◽  
Michael Oster ◽  
Henry Reyer ◽  
Frieder Hadlich ◽  
Nares Trakooljul ◽  
...  
Keyword(s):  
False Discovery Rate ◽  
Mrna Expression ◽  
Genetic Regulation ◽  
Snp Markers ◽  
Phenotypic Data ◽  
Genomic Heritability ◽  
False Discovery ◽  
P Utilization ◽  
Microbiome Data

Improved utilization of phytates and mineral phosphorus (P) in monogastric animals contributes significantly to preserving the finite resource of mineral P and mitigating environmental pollution. In order to identify pathways and to prioritize candidate genes related to P utilization (PU), the genomic heritability of 77 and 80 trait-dependent expressed miRNAs and mRNAs in 482 Japanese quail were estimated and eQTL (expression quantitative trait loci) were detected. In total, 104 miR-eQTL (microRNA expression quantitative traits loci) were associated with SNP markers (false discovery rate less than 10%) including 41 eQTL of eight miRNAs. Similarly, 944 mRNA-eQTL were identified at the 5% False discovery rate threshold, with 573 being cis-eQTL of 36 mRNAs. High heritabilities of miRNA and mRNA expression coincide with highly significant eQTL. Integration of phenotypic data with transcriptome and microbiome data of the same animals revealed genetic regulated mRNA and miRNA transcripts (SMAD3, CAV1, ENNPP6, ATP2B4, miR-148a-3p, miR-146b-5p, miR-16-5p, miR-194, miR-215-5p, miR-199-3p, miR-1388a-3p) and microbes ( Candidatus Arthromitus , Enterococcus ) that are associated with PU. The results reveal novel insights into the role of mRNAs and miRNAs in host gut tissue functions, which are involved in PU and other related traits, in terms of the genetic regulation and inheritance of their expression and in association with microbiota components.

scholarly journals Discrete False-Discovery Rate Improves Identification of Differentially Abundant Microbes

mSystems ◽  
2017 ◽  
Vol 2 (6) ◽  
Author(s):  
Lingjing Jiang ◽  
Amnon Amir ◽  
James T. Morton ◽  
Ruth Heller ◽  
Ery Arias-Castro ◽  
...  
Keyword(s):  
Gene Expression ◽  
False Discovery Rate ◽  
Real World ◽  
Statistical Power ◽  
Gene Expression Analysis ◽  
New Method ◽  
Data Sets ◽  
Differential Abundance ◽  
False Discovery ◽  
Microbiome Data

ABSTRACT DS-FDR can achieve higher statistical power to detect significant findings in sparse and noisy microbiome data compared to the commonly used Benjamini-Hochberg procedure and other FDR-controlling procedures. Differential abundance testing is a critical task in microbiome studies that is complicated by the sparsity of data matrices. Here we adapt for microbiome studies a solution from the field of gene expression analysis to produce a new method, discrete false-discovery rate (DS-FDR), that greatly improves the power to detect differential taxa by exploiting the discreteness of the data. Additionally, DS-FDR is relatively robust to the number of noninformative features, and thus removes the problem of filtering taxonomy tables by an arbitrary abundance threshold. We show by using a combination of simulations and reanalysis of nine real-world microbiome data sets that this new method outperforms existing methods at the differential abundance testing task, producing a false-discovery rate that is up to threefold more accurate, and halves the number of samples required to find a given difference (thus increasing the efficiency of microbiome experiments considerably). We therefore expect DS-FDR to be widely applied in microbiome studies. IMPORTANCE DS-FDR can achieve higher statistical power to detect significant findings in sparse and noisy microbiome data compared to the commonly used Benjamini-Hochberg procedure and other FDR-controlling procedures.

scholarly journals LOCOM: A logistic regression model for testing differential abundance in compositional microbiome data with false discovery rate control

2021 ◽  
Author(s):  
Yingtian Hu ◽  
Glen Satten ◽  
Yijuan Hu
Keyword(s):  
Logistic Regression ◽  
False Discovery Rate ◽  
Compositional Analysis ◽  
R Package ◽  
Small Sample ◽  
Metagenomic Sequencing ◽  
False Discovery ◽  
Small Sample Sizes ◽  
Low Sensitivity ◽  
Microbiome Data

Abstract Motivation: Compositional analysis is based on the premise that a relatively small proportion of taxa are differentially abundant", while the ratios of the relative abundances of the remaining taxa remain unchanged. Most existing methods of compositional analysis such as ANCOM or ANCOM-BC use log-transformed data, but log-transformation of data with pervasive zero counts is problematic, and these methods cannot always control the false discovery rate (FDR). Further, high-throughput microbiome data such as 16S amplicon or metagenomic sequencing are subject to experimental biases that are introduced in every step of the experimental workflow. McLaren, Willis and Callahan [1] have recently proposed a model for how these biases affect relative abundance data. Methods: Motivated by [1], we show that the (log) odds ratios in a logistic regression comparing counts in two taxa are invariant to experimental biases. With this motivation, we propose LOCOM, a robust logistic regression approach to compositional analysis, that does not require pseudocounts. We use a Firth bias-corrected estimating function to account for sparse data. Inference is based on permutation to account for overdispersion and small sample sizes. Traits can be either binary or continuous, and adjustment for continuous and/or discrete confounding covariates is supported. Results: Our simulations indicate that LOCOM always preserved FDR and had much improved sensitivity over existing methods. In contrast, ANCOM often had inflated FDR; ANCOM-BC largely controlled FDR but still had modest inflation occasionally; ALDEx2 generally had low sensitivity. LOCOM and ANCOM were robust to experimental biases in every situation, while ANCOM-BC and ALDEx2 had elevated FDR when biases at causal and non-causal taxa were differentially distributed. The flexibility of our method for a variety of microbiome studies is illustrated by the analysis of data from two microbiome studies. Availability and implementation: Our R package LOCOM is available on GitHub at https://github.com/yijuanhu/LOCOM in formats appropriate for Macintosh or Windows.

scholarly journals Haplotype Networking of GWAS Hits for Citrulline Variation Associated with the Domestication of Watermelon

2019 ◽  
Vol 20 (21) ◽  
pp. 5392
Author(s):  
Joshi ◽  
Shinde ◽  
Nimmakayala ◽  
Abburi ◽  
Alaparthi ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Genetic Regulation ◽  
Acetolactate Synthase ◽  
Snp Markers ◽  
Protein Amino Acid ◽  
Single Nucleotide ◽  
Genome Wide ◽  
A Genome ◽  
A Minor

Watermelon is a good source of citrulline, a non-protein amino acid. Citrulline has several therapeutic and clinical implications as it produces nitric oxide via arginine. In plants, citrulline plays a pivotal role in nitrogen transport and osmoprotection. The purpose of this study was to identify single nucleotide polymorphism (SNP) markers associated with citrulline metabolism using a genome-wide association study (GWAS) and understand the role of citrulline in watermelon domestication. A watermelon collection consisting of 187 wild, landraces, and cultivated accessions was used to estimate citrulline content. An association analysis involved a total of 12,125 SNPs with a minor allele frequency (MAF) >0.05 in understanding the population structure and phylogeny in light of citrulline accumulation. Wild egusi types and landraces contained low to medium citrulline content, whereas cultivars had higher content, which suggests that obtaining higher content of citrulline is a domesticated trait. GWAS analysis identified candidate genes (ferrochelatase and acetolactate synthase) showing a significant association of SNPs with citrulline content. Haplotype networking indicated positive selection from wild to domesticated watermelon. To our knowledge, this is the first study showing genetic regulation of citrulline variation in plants by using a GWAS strategy. These results provide new insights into the citrulline metabolism in plants and the possibility of incorporating high citrulline as a trait in watermelon breeding programs.

scholarly journals LOCOM: A logistic regression model for testing differential abundance in compositional microbiome data with false discovery rate control

2021 ◽  
Author(s):  
Yingtian Hu ◽  
Glen A. Satten ◽  
Yi-Juan Hu
Keyword(s):  
Logistic Regression ◽  
False Discovery Rate ◽  
Compositional Analysis ◽  
R Package ◽  
Small Sample ◽  
Metagenomic Sequencing ◽  
False Discovery ◽  
Small Sample Sizes ◽  
Low Sensitivity ◽  
Microbiome Data

AbstractMotivationCompositional analysis is based on the premise that a relatively small proportion of taxa are “differentially abundant”, while the ratios of the relative abundances of the remaining taxa remain unchanged. Most existing methods of compositional analysis such as ANCOM or ANCOM-BC use log-transformed data, but log-transformation of data with pervasive zero counts is problematic, and these methods cannot always control the false discovery rate (FDR). Further, high-throughput microbiome data such as 16S amplicon or metagenomic sequencing are subject to experimental biases that are introduced in every step of the experimental workflow. McLaren, Willis and Callahan [1] have recently proposed a model for how these biases affect relative abundance data.MethodsMotivated by [1], we show that the (log) odds ratios in a logistic regression comparing counts in two taxa are invariant to experimental biases. With this motivation, we propose LOCOM, a robust logistic regression approach to compositional analysis, that does not require pseudocounts. We use a Firth bias-corrected estimating function to account for sparse data. Inference is based on permutation to account for overdispersion and small sample sizes. Traits can be either binary or continuous, and adjustment for continuous and/or discrete confounding covariates is supported.ResultsOur simulations indicate that LOCOM always preserved FDR and had much improved sensitivity over existing methods. In contrast, ANCOM often had inflated FDR; ANCOM-BC largely controlled FDR but still had modest inflation occasionally; ALDEx2 generally had low sensitivity. LOCOM and ANCOM were robust to experimental biases in every situation, while ANCOM-BC and ALDEx2 had elevated FDR when biases at causal and non-causal taxa were differentially distributed. The flexibility of our method for a variety of microbiome studies is illustrated by the analysis of data from two microbiome studies.Availability and implementationOur R package LOCOM is available on GitHub at https://github.com/yijuanhu/LOCOM in formats appropriate for Macintosh or Windows.

scholarly journals Flavonoids Ameliorate Stress-Induced Depression by Preventing NLRP3 Inflammasome Priming

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1231-1231
Author(s):  
Giulio Pasinetti
Keyword(s):  
Mrna Expression ◽  
Chronic Stress ◽  
Nlrp3 Inflammasome ◽  
Signaling Cascades ◽  
Dietary Polyphenols ◽  
Funding Sources ◽  
Glycation End Products ◽  
Molecular Patterns

Abstract Objectives Chronic stress activates danger-associated molecular patterns (DAMPs), stimulating the NLRP3 inflammasome. NLRP3 activation triggers the release of pro-inflammatory cytokine IL-1β. The activity of the NLRP3 inflammasome propagates pro-inflammatory signaling cascades implicated in the onset of depression. Our previous studies show that polyphenolic compounds were found to ameliorate stress induced depression in mouse models. However, the relevant mechanism has not been identified. This study examined the effect of administering polyphenols on DAMP signaling in enriched mice microglia. Methods This study examined the effect of administering polyphenols on DAMP signaling in mice microglia. To recapitulate stress-induced depression, mice underwent chronic unpredictable stress (CUS). Microglia were isolated at various time points throughout the CUS protocol. We also assessed long-term persistent changes after CUS and susceptibility to subthreshold unpredictable stress (US) re-exposure. Results Interestingly, the development of US – induced depression and anxiety depended upon a previous exposure to CUS. We found that CUS caused robust upregulation of IL-1β mRNA in enriched microglia, an effect that persists for up to 4 weeks following CUS exposure. Following the subthreshold US re-exposure, we observed the upregulation of pro- IL-1β as well as pro-receptor for advanced glycation end products (RAGE). Toll-like receptor 4 (TLR-4) was not. We also observed an increase in RAGE mRNA expression when mice were exposed to US prior to the start of the CUS paradigm. Importantly, a primary exposure to US, was sufficient to increase RAGE mRNA expression. We found that polyphenol administration significantly improved CUS-induced depressive-like phenotypes and also reversed neuroinflammation in mice. Treatment with dietary flavonoids prevented upregulation of IL-1β, RAGE mRNA, which reflects the ability of polyphenols that may have begun following the primary exposure to US. Conclusions Taken all together, the results provide evidence of the role of dietary polyphenols in preventing persistent microglial activation, which has been shown to result in reduced long term vulnerability to depressive-like behaviors following expose to chronic stress. Funding Sources This study was supported by a P50 CARBON Center grant from the NCCIH/ODS.

scholarly journals Four Mutant Alleles Elucidate the Role of the G2 Protein in the Development of C4 and C3 Photosynthesizing Maize Tissues

Genetics ◽  
2001 ◽  
Vol 159 (2) ◽  
pp. 787-797
Author(s):  
Lizzie Cribb ◽  
Lisa N Hall ◽  
Jane A Langdale
Keyword(s):  
Cell Types ◽  
Bundle Sheath ◽  
Primary Role ◽  
Ribulose Bisphosphate Carboxylase ◽  
Sheath Cell ◽  
Mesophyll Cells ◽  
Phenotypic Data ◽  
Bisphosphate Carboxylase ◽  
Bundle Sheath Cell

Abstract Maize leaf blades differentiate dimorphic photosynthetic cell types, the bundle sheath and mesophyll, between which the reactions of C4 photosynthesis are partitioned. Leaf-like organs of maize such as husk leaves, however, develop a C3 pattern of differentiation whereby ribulose bisphosphate carboxylase (RuBPCase) accumulates in all photosynthetic cell types. The Golden2 (G2) gene has previously been shown to play a role in bundle sheath cell differentiation in C4 leaf blades and to play a less well-defined role in C3 maize tissues. To further analyze G2 gene function in maize, four g2 mutations have been characterized. Three of these mutations were induced by the transposable element Spm. In g2-bsd1-m1 and g2-bsd1-s1, the element is inserted in the second intron and in g2-pg14 the element is inserted in the promoter. In the fourth case, g2-R, four amino acid changes and premature polyadenylation of the G2 transcript are observed. The phenotypes conditioned by these four mutations demonstrate that the primary role of G2 in C4 leaf blades is to promote bundle sheath cell chloroplast development. C4 photosynthetic enzymes can accumulate in both bundle sheath and mesophyll cells in the absence of G2. In C3 tissue, however, G2 influences both chloroplast differentiation and photosynthetic enzyme accumulation patterns. On the basis of the phenotypic data obtained, a model that postulates how G2 acts to facilitate C4 and C3 patterns of tissue development is proposed.

scholarly journals FRI0376 EFFECT OF CARBAMYLATED LOW-DENSITY LIPOPROTEINS ON BONE CELLS HOMEOSTASIS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 784.2-785
Author(s):  
B. Lucchino ◽  
M. Leopizzi ◽  
T. Colasanti ◽  
V. DI Maio ◽  
C. Alessandri ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Bone Cells ◽  
Osteoclast Differentiation ◽  
Low Density Lipoproteins ◽  
Tartrate Resistant Acid Phosphatase ◽  
Low Density ◽  
Bone Homeostasis ◽  
Research Support ◽  
Erosive Disease

Background:Carbamylation is a post-translational modification occurring under several conditions such as uremia, smoking and chronic inflammation as in rheumatoid arthritis (RA). Low-density lipoproteins (LDL) represent a target of carbamylation. Carbamylated-LDL (cLDL) have an increased inflammatory and atherogenic potential. Growing evidence supports an influence of modified lipids on bone cells homeostasis. However, the role of cLDL on bone cells physiology is still unknown.Objectives:Considering the rate of carbamylation and the role of anti-carbamylated proteins antibodies as markers of erosive disease in RA, the purpose of this study is to investigate the effect of cLDL on bone homeostasis.Methods:In-vitrocarbamylation of LDL was performed as previously described by Ok et al. (Kidney Int. 2005). Briefly, native LDL (nLDL) were treated with potassium cyanate (KOCN) for 4 hours, followed by excessive dialysis for 36 hours to remove KOCN. Both osteoclasts (OCs) and osteoblasts (OBLs) were treated at baseline with 20 μg/ml, 100 μg/ml and 200 μg/ml of cLDL or nLDL. To induce osteoclast differentiation, CD14+ monocytes were isolated from peripheral blood of healthy donors by magnetic microbeads separation and then cultured on a 96-wells plate in DMEM media supplemented with RANKL and M-CSF. After 10 days cells were fixed, stained for tartrate-resistant acid phosphatase (TRAP), a marker of OC differentiation, and counted. OBLs were isolated from bone specimens of 3 patients who had undergone to knee or hip arthroplasty for osteoarthritis and treated for 5 days with different concentrations of cLDL and nLDL. OBLs were fixed and stained for alkaline phosphatase positive activity (ALP), a marker of osteogenic differentiation. Total RNA was extracted from cell lysates. Copies of single-stranded complementary DNA (cDNA) were synthesized and analyzed by real-time PCR to evaluate RANKL and Osteoprotegerin (OPG) mRNA expression levels.Results:In OCLs culture, cLDL significantly decreased the number of OC compared to untreated cells (200 μg/ml p=0,0015) and nLDL treated cells (200 μg/ml p= 0,011; 20 μg/ml p= 0,0014) (Fig 1). Moreover, treatment with cLDL induced an increase of not terminally differentiated OCs, reduced dimensions of OCs, less intense TRAP staining and vacuolization (Fig 2). In OBLs culture, cLDL (20, 100 μg/ml) significantly reduced the ALP activity of OBLs compared with untreated cells (p<0.05) (Fig 3). nLDL did not affect the ALP expression. Treatment with cLDL stimulated RANKL mRNA expression in osteoblasts increasing the RANKL/OPG ratio (Fig 4).Fig 1.Fig 2.Fig 3.Fig 4.Conclusion:cLDL induce a significant depression of OC and OBL differentiation. Moreover, cLDL increase RANKL expression in OBL, unbalancing bone tissue turnover towards bone resorption. Accordingly, cLDL could be implicated in the bone loss characterizing several conditions associated to an increased carbamylation, such as RADisclosure of Interests:Bruno Lucchino: None declared, Martina Leopizzi: None declared, Tania Colasanti: None declared, Valeria Di Maio: None declared, cristiano alessandri Grant/research support from: Pfizer, Guido Valesini: None declared, fabrizio conti Speakers bureau: BMS, Lilly, Abbvie, Pfizer, Sanofi, Manuela Di Franco: None declared, Francesca Romana Spinelli Grant/research support from: Pfizer, Consultant of: Novartis, Gilead, Lilly, Sanofi, Celgene, Speakers bureau: Lilly

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