Metabolite Diversity and Metabolic Genome-Wide Marker Association Studies (Mgwas) for Health Benefiting Nutritional Traits in Pearl Millet Grains

As efforts are made to increase food security, millets are gaining increasing importance due to their excellent nutritional credentials. Among the millets, pearl millet is the predominant species possessing several health benefiting nutritional traits in its grain that are helpful in mitigating chronic illnesses such as type−2 diabetes and obesity. In this paper, we conducted metabolomic fingerprinting of 197 pearl millet inbred lines drawn randomly from within the world collection of pearl millet germplasm and report the extent of genetic variation for health benefitting metabolites in these genotypes. Metabolites were extracted from seeds and assessed using flow infusion high-resolution mass spectrometry (FIE-HRMS). Metabolite features (m/z), whose levels significantly differed among the germplasm inbred lines, were identified by ANOVA corrected for FDR and subjected to functional pathway analysis. A number of health-benefiting metabolites linked to dietary starch, antioxidants, vitamins, and lipid metabolism-related compounds were identified. Metabolic genome-wide association analysis (mGWAS) performed using the 396 m/z as phenotypic traits and the 76 K SNP as genotypic variants identified a total of 897 SNPs associated with health benefiting nutritional metabolite at the -log p-value ≤ 4.0. From these associations, 738 probable candidate genes were predicted to have an important role in starch, antioxidants, vitamins, and lipid metabolism. The mGWAS analysis focused on genes involved in starch branching (α-amylase, β-amylase), vitamin-K reductase, UDP-glucuronosyl, and UDP-glucosyl transferase (UGTs), L-ascorbate oxidase, and isoflavone 2′-monooxygenase genes, which are known to be linked to increases in human health benefiting metabolites. We demonstrate how metabolomic, genomic, and statistical approaches can be utilized to pinpoint genetic variations and their functions linked to key nutritional properties in pearl millet, which in turn can be bred into millets and other cereals crops using plant breeding methods.

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PSVIII-10 Genome-wide CNV analysis unravels a deletion associated with parasite resistance in Florida native sheep

Journal of Animal Science ◽

10.1093/jas/skab235.444 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 243-244

Author(s):

Brittany N Diehl ◽

Andres A Pech-Cervantes ◽

Thomas H Terrill ◽

Ibukun M Ogunade ◽

Owen Rae ◽

...

Keyword(s):

Copy Number ◽

Association Studies ◽

Chromosome 21 ◽

Trend Test ◽

P Value ◽

Genome Wide Association Studies ◽

Parasite Resistance ◽

Association Testing ◽

Genome Wide ◽

Native Sheep

Abstract Florida Native sheep is an indigenous breed from Florida and expresses superior parasite resistance. Previous candidate and genome wide association studies with Florida Native sheep have identified single nucleotide polymorphisms with additive and non-additive effects associated with parasite resistance. However, the role of other potential DNA variants, such as copy number variants (CNVs), controlling this complex trait have not been evaluated. The objective of the present study was to investigate the importance of CNVs on resistance to natural Haemonchus contortus infections in Florida Native sheep. A total of 200 sheep were evaluated in the present study. Phenotypic records included fecal egg count (FEC, eggs/gram), FAMACHA score, and packed cell volume (PCV, %). Sheep were genotyped using the GGP Ovine 50K SNP chip. The copy number analysis was used to identify CNVs using the univariate method. A total of 170 animals with CNVs and phenotypic data were used for the association testing. Association tests were carried out using single linear regression and Principal Component Analysis (PCA) correction to identify CNVs associated with FEC, FAMACHA, and PCV. To confirm our results, a second association testing using the correlation-trend test with PCA correction was performed. Significant CNVs were detected when their adjusted p-value was < 0.05 after FDR correction. A deletion CNV in chromosome 21 was associated with FEC. This DNA variant was located in intron 2 of RAB3IL gene and overlapped a QTL associated with changes in eosinophil number. Our study demonstrated for the first time that CNVs could be potentially involved with parasite resistance in this heritage sheep breed.

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HAPPI GWAS: Holistic Analysis with Pre and Post Integration GWAS

10.1101/2020.04.07.998690 ◽

2020 ◽

Cited By ~ 2

Author(s):

Marianne L. Slaten ◽

Yen On Chan ◽

Vivek Shrestha ◽

Alexander E. Lipka ◽

Ruthie Angelovici

Keyword(s):

Association Studies ◽

Phenotypic Traits ◽

Genome Wide Association Studies ◽

Sequencing Data ◽

Gwas Analysis ◽

Genome Wide ◽

Large Populations ◽

Unbiased Estimates ◽

Best Linear Unbiased ◽

Automated Pipeline

AbstractMotivationAdvanced publicly available sequencing data from large populations have enabled in-formative genome-wide association studies (GWAS) that associate SNPs with phenotypic traits of interest. Many publicly available tools able to perform GWAS have been developed in response to increased demand. However, these tools lack a comprehensive pipeline that includes both pre-GWAS analysis such as outlier removal, data transformation, and calculation of Best Linear Unbiased Predictions (BLUPs) or Best Linear Unbiased Estimates (BLUEs). In addition, post-GWAS analysis such as haploblock analysis and candidate gene identification are lacking.ResultsHere, we present HAPPI GWAS, an open-source GWAS tool able to perform pre-GWAS, GWAS, and post-GWAS analysis in an automated pipeline using the command-line interface.AvailabilityHAPPI GWAS is written in R for any Unix-like operating systems and is available on GitHub (https://github.com/Angelovici-Lab/HAPPI.GWAS.git)[email protected]

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Metabolome-scale genome-wide association studies reveal chemical diversity and genetic control of maize specialized metabolites

10.1101/450338 ◽

2018 ◽

Author(s):

Zhou Shaoqun ◽

Karl A. Kremling ◽

Bandillo Nonoy ◽

Richter Annett ◽

Ying K. Zhang ◽

...

Keyword(s):

Quantitative Trait ◽

Citrate Synthase ◽

Association Studies ◽

Inbred Lines ◽

Chemical Diversity ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Single Linkage ◽

Genome Wide ◽

Maize Varieties

One Sentence SummaryHPLC-MS metabolite profiling of maize seedlings, in combination with genome-wide association studies, identifies numerous quantitative trait loci that influence the accumulation of foliar metabolites.AbstractCultivated maize (Zea mays) retains much of the genetic and metabolic diversity of its wild ancestors. Non-targeted HPLC-MS metabolomics using a diverse panel of 264 maize inbred lines identified a bimodal distribution in the prevalence of foliar metabolites. Although 15% of the detected mass features were present in >90% of the inbred lines, the majority were found in <50% of the samples. Whereas leaf bases and tips were differentiated primarily by flavonoid abundance, maize varieties (stiff-stalk, non-stiff-stalk, tropical, sweet corn, and popcorn) were differentiated predominantly by benzoxazinoid metabolites. Genome-wide association studies (GWAS), performed for 3,991 mass features from the leaf tips and leaf bases, showed that 90% have multiple significantly associated loci scattered across the genome. Several quantitative trait locus hotspots in the maize genome regulate the abundance of multiple, often metabolically related mass features. The utility of maize metabolite GWAS was demonstrated by confirming known benzoxazinoid biosynthesis genes, as well as by mapping isomeric variation in the accumulation of phenylpropanoid hydroxycitric acid esters to a single linkage block in a citrate synthase-like gene. Similar to gene expression databases, this metabolomic GWAS dataset constitutes an important public resource for linking maize metabolites with biosynthetic and regulatory genes.

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Reproducibility in the UK Biobank of Genome-Wide Significant Signals Discovered in Earlier Genome-wide Association Studies

10.1101/2020.06.24.20139576 ◽

2020 ◽

Cited By ~ 1

Author(s):

Jack W. O’Sullivan ◽

John P. A. Ioannidis

Keyword(s):

Effect Size ◽

Association Studies ◽

Genome Wide Association ◽

P Value ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Single Nucleotide ◽

Genome Wide ◽

The Uk ◽

Open Question

AbstractWith the establishment of large biobanks, discovery of single nucleotide polymorphism (SNPs) that are associated with various phenotypes has been accelerated. An open question is whether SNPs identified with genome-wide significance in earlier genome-wide association studies (GWAS) are replicated also in later GWAS conducted in biobanks. To address this question, the authors examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, replication GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNPs (of which 6,289 had reached p<5e-8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0% and it was lower for binary than for quantitative phenotypes (58.1% versus 94.8% respectively). There was a18.0% decrease in SNP effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNP effect size, phenotype trait (binary or quantitative), and discovery p-value, we built and validated a model that predicted SNP replication with area under the Receiver Operator Curve = 0.90. While non-replication may often reflect lack of power rather than genuine false-positive findings, these results provide insights about which discovered associations are likely to be seen again across subsequent GWAS.

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An approach to gene-based testing accounting for dependence of tests among nearby genes

10.1101/2021.05.24.445494 ◽

2021 ◽

Author(s):

Ronald J Yurko ◽

Kathryn Roeder ◽

Bernie Devlin ◽

Max G'Sell

Keyword(s):

Multiple Testing ◽

Association Studies ◽

Autism Spectrum ◽

P Value ◽

Genome Wide Association Studies ◽

Strongly Correlated ◽

Test Statistics ◽

Test Statistic ◽

Genome Wide ◽

Insight Into

In genome-wide association studies (GWAS), it has become commonplace to test millions of SNPs for phenotypic association. Gene-based testing can improve power to detect weak signal by reducing multiple testing and pooling signal strength. While such tests account for linkage disequilibrium (LD) structure of SNP alleles within each gene, current approaches do not capture LD of SNPs falling in different nearby genes, which can induce correlation of gene-based test statistics. We introduce an algorithm to account for this correlation. When a gene's test statistic is independent of others, it is assessed separately; when test statistics for nearby genes are strongly correlated, their SNPs are agglomerated and tested as a locus. To provide insight into SNPs and genes driving association within loci, we develop an interactive visualization tool to explore localized signal. We demonstrate our approach in the context of weakly powered GWAS for autism spectrum disorder, which is contrasted to more highly powered GWAS for schizophrenia and educational attainment. To increase power for these analyses, especially those for autism, we use adaptive p-value thresholding (AdaPT), guided by high-dimensional metadata modeled with gradient boosted trees, highlighting when and how it can be most useful. Notably our workflow is based on summary statistics.

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The harmonic mean p-value for combining dependent tests

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1814092116 ◽

2019 ◽

Vol 116 (4) ◽

pp. 1195-1200 ◽

Cited By ~ 43

Author(s):

Daniel J. Wilson

Keyword(s):

Multiple Testing ◽

Statistical Power ◽

Scientific Discovery ◽

Association Studies ◽

Harmonic Mean ◽

P Value ◽

Genome Wide Association Studies ◽

Familywise Error Rate ◽

Significance Threshold ◽

Genome Wide

Analysis of “big data” frequently involves statistical comparison of millions of competing hypotheses to discover hidden processes underlying observed patterns of data, for example, in the search for genetic determinants of disease in genome-wide association studies (GWAS). Controlling the familywise error rate (FWER) is considered the strongest protection against false positives but makes it difficult to reach the multiple testing-corrected significance threshold. Here, I introduce the harmonic mean p-value (HMP), which controls the FWER while greatly improving statistical power by combining dependent tests using generalized central limit theorem. I show that the HMP effortlessly combines information to detect statistically significant signals among groups of individually nonsignificant hypotheses in examples of a human GWAS for neuroticism and a joint human–pathogen GWAS for hepatitis C viral load. The HMP simultaneously tests all ways to group hypotheses, allowing the smallest groups of hypotheses that retain significance to be sought. The power of the HMP to detect significant hypothesis groups is greater than the power of the Benjamini–Hochberg procedure to detect significant hypotheses, although the latter only controls the weaker false discovery rate (FDR). The HMP has broad implications for the analysis of large datasets, because it enhances the potential for scientific discovery.

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Genome-Wide Association Study Identifies Loci Associated with Sensitive Skin

Cosmetics ◽

10.3390/cosmetics7020049 ◽

2020 ◽

Vol 7 (2) ◽

pp. 49

Author(s):

Miranda A. Farage ◽

Yunxuan Jiang ◽

Jay P. Tiesman ◽

Pierre Fontanillas ◽

Rosemarie Osborne

Keyword(s):

Genome Wide Association Study ◽

Association Studies ◽

Genome Wide Association ◽

European Ancestry ◽

P Value ◽

Genome Wide Association Studies ◽

Online Questionnaire ◽

Sensitive Skin ◽

Genome Wide ◽

Skin Conditions

Individuals suffering from sensitive skin often have other skin conditions and/or diseases, such as fair skin, freckles, rosacea, or atopic dermatitis. Genome-wide association studies (GWAS) have been performed for some of these conditions, but not for sensitive skin. In this study, a total of 23,426 unrelated participants of European ancestry from the 23andMe database were evaluated for self-declared sensitive skin, other skin conditions, and diseases using an online questionnaire format. Responders were separated into two groups: those who declared they had sensitive skin (n = 8971) and those who declared their skin was not sensitive (controls, n = 14,455). A GWAS of sensitive skin individuals identified three genome-wide significance loci (p-value < 5 × 10−8) and seven suggestive loci (p-value < 1 × 10−6). Of the three most significant loci, all have been associated with pigmentation and two have been associated with acne.

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Fetal Hemoglobin in Sickle Cell Anemia: A Genome-Wide Association Study of the Response to Hydroxyurea

Blood ◽

10.1182/blood.v112.11.2471.2471 ◽

2008 ◽

Vol 112 (11) ◽

pp. 2471-2471 ◽

Cited By ~ 1

Author(s):

Nadia Timofeev ◽

Paola Sebastiani ◽

Steven H. Hartley ◽

Clinton T. Baldwin ◽

Martin H. Steinberg

Keyword(s):

Sickle Cell ◽

Sickle Cell Anemia ◽

Association Studies ◽

Fetal Hemoglobin ◽

Significant Snps ◽

Genome Wide Association ◽

P Value ◽

Genome Wide ◽

Genome Wide Significance

Abstract Fetal hemoglobin (HbF) is the major genetic modulator of sickle cell anemia. Candidate gene-based and genome-wide association studies (GWAS) have provided strong evidence that single nucleotide polymorphisms (SNPs) linked to genes on chromosome 6q (HBS1L-MYB) and 2p (BCL11A), along with elements in cis to HBG help determine HbF concentration in untreated patients with sickle cell anemia and β thalassemia, and in normal individuals. The HbF response to hydroxyurea (HU) varies considerably among treated patients, even when compliance with treatment is good and patients are treated under controlled conditions. This suggests that genetic factors might affect the response to treatment with this agent. In the Multicenter Study of Hydroxyurea, 299 patients were randomized to receive either HU titrated to maximum tolerated doses, or a placebo, and HbF levels were measured before and at the completion of the randomized phase of the study. In 123 HU-treated patients, we completed GWAS using Illumina 370K chips that include approximately 350,000 haplotype tagging SNPs, and studied the association of SNPs with the change in HbF from baseline levels to levels measured at the end of the active treatment portion of the study. We conducted a GWAS using the analytical program PLINK, of approximately 273K SNPs with minor allele frequency >0.05, using linear regression and an additive model of inheritance. We selected for further investigation those SNPs with association that reached 0.05 significance, after we adjusted for sex. Because of the limited sample size that results in relatively large p-values, no single SNP reached so-called genome-wide significance after correcting for multiple comparisons using a Bonferroni correction (p-value <10-7) or 5% false discovery rate. Two SNPs had an association with p value <10–6 and 27 SNPs reached at least 10–5 significance. Noticeably, the SNP rs6899351 in FABP7 in 6q22.31 was associated with the largest increment in HbF after treatment with HU (6.9% change per copy of allele G, p-value 4 ×10–5). We also identified 2 SNPs in PDE7B (6q23.3) that were significantly associated with positive changes of HbF and 3 SNPs in MAP7 (6q23.3) that were significantly associated with a reduction of HbF after treatment. Using candidate gene association studies, we had previously shown that PDE7B and MAP7 were significantly associated with differential expression of HbF in sickle cell anemia. These new GWAS results suggest a regulatory role for these genes, or this region of chromosome 6q, in the HbF response to HU in sickle cell anemia. Analysis of the distribution of significant SNPs per chromosome also showed that chromosome 20 had a larger number of significant SNPs than expected at random, especially in CST9, one of a family of protease inhibitors. CST9 is tagged by 3 SNPs in the 370K array (rs2983639, rs2983640, rs10485646), 2 of which were associated with significant positive changes in HbF after treatment with HU and one with significant negative changes of HbF. Specifically, the average increase in HbF was 1.5% for each copy of allele G for SNP rs2983639 (p = 0.025), and 1.6% for each copy of allele A for SNP rs2983640 (p = 0.047), while the level of HbF decreased by approximately 1.5% for each copy of allele A for SNP rs10485646 (p = 0.035). The SNP rs2983640 is an exon variant that produces the amino acid change F-L. Although these SNPs do not individually reach genome-wide significance, cumulatively they provide strong evidence of association, as the probability that they are all simultaneously associated by chance is 10-4. Furthermore, we identified significant variants in other genes that belong to the same family of type 2 cysteine protease inhibitors, specifically 2 SNPs in CTS3 and 1 SNP in CTS5. Although the small sample size and the large number of SNPs tested suggest caution until these results are replicated in independent patient treatment groups, these preliminary findings suggest that type 2 cystatin genes and pseudogenes are associated with the HbF response to HU. If confirmed, it might be possible to use results like these to build a prognostic model of the HbF response to HU in sickle cell anemia.

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Novel genetic determinants of telomere length from a trans-ethnic analysis of 109,122 whole genome sequences in TOPMed

10.1101/749010 ◽

2019 ◽

Author(s):

Margaret A Taub ◽

Matthew P Conomos ◽

Rebecca Keener ◽

Kruthika R Iyer ◽

Joshua S Weinstock ◽

...

Keyword(s):

Telomere Length ◽

Association Studies ◽

P Value ◽

Genome Wide Association Studies ◽

Whole Genome ◽

Genetic Determinants ◽

Age Related ◽

Genome Wide ◽

Variant Genotype ◽

Effect Heterogeneity

ABSTRACTTelomeres shorten in replicating somatic cells, and telomere length (TL) is associated with age-related diseases 1,2. To date, 17 genome-wide association studies (GWAS) have identified 25 loci for leukocyte TL 3–19, but were limited to European and Asian ancestry individuals and relied on laboratory assays of TL. In this study from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of TL in n=109,122 trans-ethnic (European, African, Asian and Hispanic/Latino) individuals. We identified 59 sentinel variants (p-value <5×10−9) from 36 loci (20 novel, 13 replicated in external datasets). There was little evidence of effect heterogeneity across populations, and 10 loci had >1 independent signal. Fine-mapping at OBFC1 indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). We further identified two novel genes, DCLRE1B (SNM1B) and PARN, using a multi-variant gene-based approach.

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A meta-analysis of the genome-wide association studies on two genetically correlated phenotypes (self-reported headache and self-reported migraine) identifies four new risk loci for headaches (N=397,385)

10.1101/2021.09.15.21263668 ◽

2021 ◽

Author(s):

Weihua Meng ◽

Parminder Reel ◽

Charvi Nangia ◽

Aravind Rajendrakumar ◽

Harry Hebert ◽

...

Keyword(s):

Association Studies ◽

Meta Analysis ◽

The Self ◽

Genome Wide Association ◽

P Value ◽

Clinical Settings ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Genetic Mechanisms ◽

The Uk

Headache is one of the commonest complaints that doctors need to address in clinical settings. The genetic mechanisms of different types of headache are not well understood. In this study, we performed a meta-analysis of genome-wide association studies (GWAS) on the self-reported headache phenotype from the UK Biobank cohort and the self-reported migraine phenotype from the 23andMe resource using the metaUSAT for genetically correlated phenotypes (N=397,385). We identified 38 loci for headaches, of which 34 loci have been reported before and 4 loci were newly identified. The LRP1-STAT6-SDR9C7 region in chromosome 12 was the most significantly associated locus with a leading P value of 1.24 x 10-62 of rs11172113. The ONECUT2 gene locus in chromosome 18 was the strongest signal among the 4 new loci with a P value of 1.29 x 10-9 of rs673939. Our study demonstrated that the genetically correlated phenotypes of self-reported headache and self-reported migraine can be meta-analysed together in theory and in practice to boost study power to identify more new variants for headaches. This study has paved way for a large GWAS meta-analysis study involving cohorts of different, though genetically correlated headache phenotypes.

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