scholarly journals Quantitative Trait Loci ControllingPhytophthora cactorumResistance in the Cultivated Octoploid Strawberry (Fragariaxananassa)

2018 ◽  
Author(s):  
Charlotte F. Nellist ◽  
Robert J. Vickerstaff ◽  
Maria K. Sobczyk ◽  
César Marina-Montes ◽  
Philip Brain ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Quantitative Resistance ◽  
Major Effect ◽  
Crown Rot ◽  
Economic Losses ◽  
Trait Loci ◽  
Soft Fruit ◽  
Rot Disease

ABSTRACTThe cultivated strawberry,Fragaria x ananassa(Fragariaspp.) is the most economically important global soft fruit.Phytophthora cactorum, a water-borne oomycete causes economic losses in strawberry production globally. A bi-parental cross of octoploid cultivated strawberry segregating for resistance toP. cactorum, the causative agent of crown rot disease, was screened using artificial inoculation. Multiple resistance quantitative trait loci (QTL) were identified and mapped. Three major effect QTL (FaRPc6C,FaRPc6DandFaRPc7D) explained 36% of the variation observed and in total, the detected QTL explained 86% of the variation observed. There were no epistatic interactions detected between the three major QTLs. Testing a subset of the mapping population progeny against a range ofP. cactorumisolates revealed no major differences in host response, however, some lines showed higher susceptibility than predicted, indicating that additional undetected factors may affect the expression of some quantitative resistance loci. Using historic crown rot disease score data from strawberry accessions, a preliminary genome-wide association study of 114 individuals revealed additional loci associated with resistance toP. cactorum. Mining ofFragaria vescaHawaii 4 v1.1 genome revealed candidate resistance genes in the QTL regions.

scholarly journals Polygenic Resistance of Pepper to Potyviruses Consists of a Combination of Isolate-Specific and Broad-Spectrum Quantitative Trait Loci

1997 ◽  
Vol 10 (7) ◽  
pp. 872-878 ◽  
Author(s):  
Carole Caranta ◽  
Véronique Lefebvre ◽  
Alain Palloix
Keyword(s):  
Quantitative Trait Loci ◽  
Broad Spectrum ◽  
Quantitative Trait ◽  
Quantitative Resistance ◽  
Specific Effect ◽  
Major Effect ◽  
Minor Effect ◽  
Resistance Factors ◽  
Specific Effects ◽  
Trait Loci

At least six potyviruses infect pepper crops around the world. Only monogenic resistance with isolate-specific effects or broad-spectrum effects against potyviruses has been identified. Quantitative trait loci (QTLs) for resistance to two potato virus Y (PVY) isolates and to potyvirus E have been mapped in a doubled-haploid progeny from the hybrid between the line Perennial with resistance factors against several potyviruses and the line Yolo Wonder, with 172 DNA markers. Eleven chromosomal regions were found to be associated with quantitative resistance to PVY and potyvirus E by both analysis of variance and non-parametric tests. This resistance results from the association of a major-effect QTL and several minor-effect QTLs. Two minor-effect QTLs originated from the susceptible parent. In addition to additive-effect QTLs, interactions between QTLs were also identified. Based on their spectrum of action, we discriminated QTLs with PVY isolate-or potyvirus-specific effect and loci involved in the resistance to several distinct potyviruses. The locations of QTLs were compared with loci having known qualitative effects against potyviruses; QTLs for PVY and potyvirus E resistance were detected in the vicinity of the pvr2 and pvr6 loci. The origin of the broad-spectrum resistance against potyviruses and the relationships between major genes and QTLs are discussed.

scholarly journals A Genome-Wide Association Study Identifies Protein Quantitative Trait Loci (pQTLs)

PLoS Genetics ◽  
2008 ◽  
Vol 4 (5) ◽  
pp. e1000072 ◽  
Author(s):  
David Melzer ◽  
John R. B. Perry ◽  
Dena Hernandez ◽  
Anna-Maria Corsi ◽  
Kara Stevens ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Association Study ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome ◽  
Trait Loci

scholarly journals Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs

BMC Genetics ◽  
2011 ◽  
Vol 12 (1) ◽  
pp. 76 ◽  
Author(s):  
Pierre Cherel ◽  
José Pires ◽  
Jérôme Glénisson ◽  
Denis Milan ◽  
Nathalie Iannuccelli ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Meat Quality ◽  
Quantitative Trait ◽  
Major Effect ◽  
Carcass Composition ◽  
Joint Analysis ◽  
Trait Loci

Mapping quantitative trait loci for pre-harvest sprouting resistance in white-grained winter wheat line CA 0431

2013 ◽  
Vol 64 (6) ◽  
pp. 573 ◽  
Author(s):  
X. L. Miao ◽  
Y. J. Zhang ◽  
X. C. Xia ◽  
Z. H. He ◽  
Y. Zhang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Winter Wheat ◽  
Quantitative Trait ◽  
Interval Mapping ◽  
Field Trials ◽  
Economic Losses ◽  
Phenotypic Variance ◽  
Wheat Line ◽  
F2 Population ◽  
Trait Loci

Pre-harvest sprouting (PHS) in wheat severely reduces yield and end-use quality, resulting in substantial economic losses. The Chinese winter wheat line CA 0431, with white grain, showed high PHS resistance for many years. To identify quantitative trait loci (QTLs) of PHS resistance in this line, 220 F2 plants and the corresponding F2 : 3 lines derived from a cross between CA 0431 and the PHS-susceptible cultivar Zhongyou 206 were used for PHS testing and QTL analysis. Field trials were conducted in Beijing during the 2010–11 and 2011–12 cropping seasons, and in Anyang during 2011–12. PHS resistance was evaluated by assessing the sprouting responses of intact spikes. In total, 1444 molecular markers were used to screen the parents, and 31 markers with polymorphisms between the resistant and susceptible bulks were used to genotype the entire F2 population. Broad-sense heritability of sprouting rate was 0.71 across environments. Inclusive composite interval mapping identified four QTLs, QPhs.caas-2BL, QPhs.caas-3AS.1, QPhs.caas-3AS.2, and QPhs.caas-3AL, each explaining 2.8–27.7% of the phenotypic variance across environments. The QTLs QPhs.caas-3AS.1, QPhs.caas-3AS.2, and QPhs.caas-3AL were located at similar positions to QTLs reported previously, whereas QPhs.caas-2BL is likely a new QTL flanked by markers Xbarc1042 and Xmag3319. Line CA 0431 and the identified markers can be used in breeding programs targeting improvement of PHS resistance for white-kernel wheat.

scholarly journals Multi-omics highlights ABO plasma protein as a causal risk factor for COVID-19

2020 ◽  
Author(s):  
Ana I. Hernández Cordero ◽  
Xuan Li ◽  
Stephen Milne ◽  
Chen Xi Yang ◽  
Yohan Bossé ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Plasma Protein ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Blood Type ◽  
Integrative Genomics ◽  
Health Crisis ◽  
Increased Risk ◽  
Trait Loci

AbstractSARS-CoV-2 is responsible for the coronavirus disease 2019 (COVID-19) and the current health crisis. Despite intensive research efforts, the genes and pathways that contribute to COVID-19 remain poorly understood. We therefore used an integrative genomics (IG) approach to identify candidate genes responsible for COVID-19 and its severity. We used Bayesian colocalization (COLOC) and summary-based Mendelian randomization to combine gene expression quantitative trait loci (eQTLs) from the Lung eQTL (n=1,038) and eQTLGen (n=31,784) studies with published COVID-19 genome-wide association study (GWAS) data from the COVID-19 Host Genetics Initiative. Additionally, we used COLOC to integrate plasma protein quantitative trait loci (pQTL) from the INTERVAL study (n=3,301) with COVID-19-associated loci. Finally, we determined any causal associations between plasma proteins and COVID-19 using multi-variable two-sample Mendelian randomization (MR). We found that the expression of 20 genes in lung and 31 genes in blood was associated with COVID-19. Of these genes, only three (LZTFL1, SLC6A20 and ABO) had been previously linked with COVID-19 in GWAS. The novel loci included genes involved in interferon pathways (IL10RB, IFNAR2 and OAS1). Plasma ABO protein, which is associated with blood type in humans, demonstrated a significant causal relationship with COVID-19 in MR analysis; increased plasma levels were associated with an increased risk of having COVID-19 and risk of severe COVID-19. In summary, our study identified genes associated with COVID-19 that may be prioritized for future investigation. Importantly, this is the first study to demonstrate a causal association between plasma ABO protein and COVID-19.

scholarly journals ColocQuiaL: A QTL-GWAS colocalization pipeline

2021 ◽  
Author(s):  
Brian Y Chen ◽  
William Paul Bone ◽  
Kimberly Lorenz ◽  
Michael Levin ◽  
Marylyn D Ritchie ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Tissue Expression ◽  
Data Availability ◽  
Genome Wide ◽  
Trait Loci ◽  
Causal Genes ◽  
Difficult Challenge

Summary: Identifying genomic features responsible for genome-wide association study (GWAS) signals has proven to be a difficult challenge; many researchers have turned to colocalization analysis of GWAS signals with expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) to connect GWAS signals to candidate causal genes. The ColocQuiaL pipeline provides a framework to perform these colocalization analyses at scale across the genome and returns summary files and locus visualization plots to allow for detailed review of the results. As an example, we used ColocQuiaL to perform colocalization between the latest type 2 diabetes GWAS data and Genotype-Tissue Expression (GTEx) v8 single-tissue eQTL and sQTL data. Availability and Implementation: ColocQuiaL is primarily written in R and is freely available at github: https://github.com/bychen9/eQTL_colocalizer. Contact: [email protected] Availability and Implementation: ColocQuiaL is primarily written in R and is freely available at github: https://github.com/bychen9/eQTL_colocalizer. Contact: [email protected]

scholarly journals Common Expression Quantitative Trait Loci Shared by Histone Genes

2017 ◽  
Vol 2017 ◽  
pp. 1-14
Author(s):  
Hanseol Kim ◽  
Yujin Suh ◽  
Chaeyoung Lee
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Histone Genes ◽  
Expression Quantitative Trait Loci ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
A Genome ◽  
Trait Loci ◽  
Cycle Dependent

A genome-wide association study (GWAS) was conducted to examine expression quantitative trait loci (eQTLs) for histone genes. We examined common eQTLs for multiple histone genes in 373 European lymphoblastoid cell lines (LCLs). A linear regression model was employed to identify single-nucleotide polymorphisms (SNPs) associated with expression of the histone genes, and the number of eQTLs was determined by linkage disequilibrium analysis. Additional associations of the identified eQTLs with other genes were also examined. We identified 31 eQTLs for 29 histone genes through genome-wide analysis using 29 histone genes (P<2.97×10−10). Among them, 12 eQTLs were associated with the expression of multiple histone genes. Transcriptome-wide association analysis using the identified eQTLs showed their associations with additional 80 genes (P<4.75×10−6). In particular, expression of RPPH1, SCARNA2, and SCARNA7 genes was associated with 26, 25, and 23 eQTLs, respectively. This study suggests that histone genes shared 12 common eQTLs that might regulate cell cycle-dependent transcription of histone and other genes. Further investigations are needed to elucidate the transcriptional mechanisms of these genes.

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