Genome-Wide Associations and Transcriptional Profiling Reveal ROS Regulation as One Underlying Mechanism of Sheath Blight Resistance in Rice

Rice sheath blight, caused by the necrotrophic fungus Rhizoctonia solani Kühn, continues to be an important and challenging rice disease worldwide. Here, we used genome-wide association studies over a high-density rice array to facilitate the identification of potential novel genes and quantitative trait loci related to sheath blight resistance. We identified multiple regions that significantly associated with independent disease components in chromosomes 1, 4, and 11 under controlled condition. In particular, we investigated qLN1128, a quantitative trait locus enriched with defense-related genes that reduce disease lesions in a near-isogenic line. RNA profiling of the line carrying qLN1128 showed a number of differentially expressed genes related to the reactive oxygen species (ROS)-redox pathway. Histochemical staining revealed less ROS accumulation on the resistant line, suggesting efficient ROS deregulation that delays pathogen colonization. The detection of genomic regions controlling multiple mechanisms of resistance to sheath blight will provide tools to design effective breeding interventions in rice.

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A description of large-scale metabolomics studies: increasing value by combining metabolomics with genome-wide SNP genotyping and transcriptional profiling

Journal of Endocrinology ◽

10.1530/joe-12-0144 ◽

2012 ◽

Vol 215 (1) ◽

pp. 17-28 ◽

Cited By ~ 18

Author(s):

Georg Homuth ◽

Alexander Teumer ◽

Uwe Völker ◽

Matthias Nauck

Keyword(s):

Blood Cells ◽

Large Scale ◽

Genetic Factors ◽

Association Studies ◽

Transcriptional Profiling ◽

Genome Wide Association Studies ◽

Protein Levels ◽

Future Developments ◽

Genome Wide ◽

Metabolome Data

The metabolome, defined as the reflection of metabolic dynamics derived from parameters measured primarily in easily accessible body fluids such as serum, plasma, and urine, can be considered as the omics data pool that is closest to the phenotype because it integrates genetic influences as well as nongenetic factors. Metabolic traits can be related to genetic polymorphisms in genome-wide association studies, enabling the identification of underlying genetic factors, as well as to specific phenotypes, resulting in the identification of metabolome signatures primarily caused by nongenetic factors. Similarly, correlation of metabolome data with transcriptional or/and proteome profiles of blood cells also produces valuable data, by revealing associations between metabolic changes and mRNA and protein levels. In the last years, the progress in correlating genetic variation and metabolome profiles was most impressive. This review will therefore try to summarize the most important of these studies and give an outlook on future developments.

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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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Identification, deployment, and transferability of quantitative trait loci from genome-wide association studies in plants

Current Plant Biology ◽

10.1016/j.cpb.2020.100145 ◽

2020 ◽

Vol 24 ◽

pp. 100145 ◽

Cited By ~ 2

Author(s):

Mohsen Mohammadi ◽

Alencar Xavier ◽

Travis Beckett ◽

Savannah Beyer ◽

Liyang Chen ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Quantitative Trait ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Trait Loci

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Detection of quantitative trait loci in Bos indicus and Bos taurus cattle using genome-wide association studies

Genetics Selection Evolution ◽

10.1186/1297-9686-45-43 ◽

2013 ◽

Vol 45 (1) ◽

Cited By ~ 30

Author(s):

Sunduimijid Bolormaa ◽

Jennie E Pryce ◽

Kathryn E Kemper ◽

Ben J Hayes ◽

Yuandan Zhang ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Quantitative Trait ◽

Bos Taurus ◽

Association Studies ◽

Bos Indicus ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Trait Loci

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Expression Quantitative Trait Locus (eQTL) analysis in human heart for elucidation of causal genes at loci identified in genome-wide association studies

European Heart Journal ◽

10.1093/eurheartj/eht309.2601 ◽

2013 ◽

Vol 34 (suppl 1) ◽

pp. 2601-2601

Author(s):

M. E. Adriaens ◽

T. T. Koopmann ◽

P. D. Moerland ◽

M. L. Westerveld ◽

R. F. Marsman ◽

...

Keyword(s):

Quantitative Trait Locus ◽

Quantitative Trait ◽

Human Heart ◽

Association Studies ◽

Genome Wide Association ◽

Eqtl Analysis ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Causal Genes ◽

Trait Locus

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Operating characteristics of the rank‐based inverse normal transformation for quantitative trait analysis in genome‐wide association studies

Biometrics ◽

10.1111/biom.13214 ◽

2020 ◽

Vol 76 (4) ◽

pp. 1262-1272 ◽

Cited By ~ 3

Author(s):

Zachary R. McCaw ◽

Jacqueline M. Lane ◽

Richa Saxena ◽

Susan Redline ◽

Xihong Lin

Keyword(s):

Quantitative Trait ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Operating Characteristics ◽

Trait Analysis ◽

Quantitative Trait Analysis ◽

Genome Wide ◽

Normal Transformation

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An application of matrix eQTL to billions hypothesis testing to identify expression quantitative trait loci in genome wide association studies of inflammatory bowel disease

Journal of Cancer Prevention & Current Research ◽

10.15406/jcpcr.2020.11.00424 ◽

2020 ◽

Vol 11 (2) ◽

pp. 41-46

Author(s):

Fahimeh Moradi ◽

Morteza Hajihosseini ◽

Elham Khodayari-Moez ◽

Irina Dinu

Keyword(s):

Inflammatory Bowel Disease ◽

Quantitative Trait Loci ◽

Hypothesis Testing ◽

Bowel Disease ◽

Quantitative Trait ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Inflammatory Bowel

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Improving Chicken Responses to Glycoconjugate Vaccination Against Campylobacter jejuni

Frontiers in Microbiology ◽

10.3389/fmicb.2021.734526 ◽

2021 ◽

Vol 12 ◽

Author(s):

Harald Nothaft ◽

Maria Elisa Perez-Muñoz ◽

Tianfu Yang ◽

Abarna V. M. Murugan ◽

Michelle Miller ◽

...

Keyword(s):

Campylobacter Jejuni ◽

Diarrheal Disease ◽

Association Studies ◽

Underlying Mechanism ◽

Human Infection ◽

Live Vaccine ◽

Genome Wide Association Studies ◽

Poultry Products ◽

Genome Wide ◽

Vaccine Information

Campylobacter jejuni is a common cause of diarrheal disease worldwide. Human infection typically occurs through the ingestion of contaminated poultry products. We previously demonstrated that an attenuated Escherichia coli live vaccine strain expressing the C. jejuni N-glycan on its surface reduced the Campylobacter load in more than 50% of vaccinated leghorn and broiler birds to undetectable levels (responder birds), whereas the remainder of the animals was still colonized (non-responders). To understand the underlying mechanism, we conducted three vaccination and challenge studies using 135 broiler birds and found a similar responder/non-responder effect. Subsequent genome-wide association studies (GWAS), analyses of bird sex and levels of vaccine-induced IgY responses did not correlate with the responder versus non-responder phenotype. In contrast, antibodies isolated from responder birds displayed a higher Campylobacter-opsonophagocytic activity when compared to antisera from non-responder birds. No differences in the N-glycome of the sera could be detected, although minor changes in IgY glycosylation warrant further investigation. As reported before, the composition of the microbiota, particularly levels of OTU classified as Clostridium spp., Ruminococcaceae and Lachnospiraceae are associated with the response. Transplantation of the cecal microbiota of responder birds into new birds in combination with vaccination resulted in further increases in vaccine-induced antigen-specific IgY responses when compared to birds that did not receive microbiota transplants. Our work suggests that the IgY effector function and microbiota contribute to the efficacy of the E. coli live vaccine, information that could form the basis for the development of improved vaccines targeted at the elimination of C. jejuni from poultry.

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Identification of putative effector genes across the GWAS Catalog using molecular quantitative trait loci from 68 tissues and cell types

10.1101/808444 ◽

2019 ◽

Cited By ~ 2

Author(s):

Cong Guo ◽

Karsten B. Sieber ◽

Jorge Esparza-Gordillo ◽

Mark R. Hurle ◽

Kijoung Song ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Quantitative Trait ◽

Complex Traits ◽

Association Studies ◽

Genome Wide Association Studies ◽

Genetic Associations ◽

Effector Genes ◽

Genome Wide ◽

Trait Loci ◽

Gwas Catalog

AbstractIdentifying the effector genes from genome-wide association studies (GWAS) is a crucial step towards understanding the biological mechanisms underlying complex traits and diseases. Colocalization of expression and protein quantitative trait loci (eQTL and pQTL, hereafter collectively called “xQTL”) can be effective for mapping associations to genes in many loci. However, existing colocalization methods require full single-variant summary statistics which are often not readily available for many published GWAS or xQTL studies. Here, we present PICCOLO, a method that uses minimum SNP p-values within a locus to determine if pairs of genetic associations are colocalized. This method greatly expands the number of GWAS and xQTL datasets that can be tested for colocalization. We applied PICCOLO to 10,759 genome-wide significant associations across the NHGRI-EBI GWAS Catalog with xQTLs from 28 studies. We identified at least one colocalized gene-xQTL in at least one tissue for 30% of associations, and we pursued multiple lines of evidence to demonstrate that these mappings are biologically meaningful. PICCOLO genes are significantly enriched for biologically relevant tissues, and 4.3-fold enriched for targets of approved drugs.

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