scholarly journals Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids

2017 ◽  
Author(s):  
Fanny Bonnafous ◽  
Ghislain Fievet ◽  
Nicolas Blanchet ◽  
Marie-Claude Boniface ◽  
Sébastien Carrère ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Flowering Time ◽  
Genetic Control ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Association Studies ◽  
Additive Models ◽  
Genome Wide Association Studies ◽  
Trait Loci ◽  
Genomic Regions

AbstractGenome-wide association studies are a powerful and widely used tool to decipher the genetic control of complex traits. One of the main challenges for hybrid crops, such as maize or sunflower, is to model the hybrid vigor in the linear mixed models, considering the relatedness between individuals. Here, we compared two additive and three non-additive association models for their ability to identify genomic regions associated with flowering time in sunflower hybrids. A panel of 452 sunflower hybrids, corresponding to incomplete crossing between 36 male lines and 36 female lines, was phenotyped in five environments and genotyped for 2,204,423 SNPs. Intra-locus effects were estimated in multi-locus models to detect genomic regions associated with flowering time using the different models. Thirteen quantitative trait loci were identified in total, two with both model categories and one with only non-additive models. A quantitative trait loci on LG09, detected by both the additive and non-additive models, is located near a GAI homolog and is presented in detail. Overall, this study shows the added value of non-additive modeling of allelic effects for identifying genomic regions that control traits of interest and that could participate in the heterosis observed in hybrids.

scholarly journals Modeling Allelic Diversity of Multi-parent Mapping Populations Affects Detection of Quantitative Trait Loci

2021 ◽  
Author(s):  
Sarah Odell ◽  
Asher I Hudson ◽  
Sébastien Praud ◽  
Pierre Dubreuil ◽  
Marie-Helene Tixier ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Qtl Mapping ◽  
Flowering Time ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Association Studies ◽  
Allelic Diversity ◽  
Genome Wide Association Studies ◽  
Trait Loci ◽  
Mapping Populations

The search for quantitative trait loci (QTL) that explain complex traits such as yield and flowering time has been ongoing in all crops. Methods such as bi-parental QTL mapping and genome-wide association studies (GWAS) each have their own advantages and limitations. Multi-parent advanced generation intercross (MAGIC) populations contain more recombination events and genetic diversity than bi-parental mapping populations and reduce the confounding effect of population structure that is an issue in association mapping populations. Here we discuss the results of using a MAGIC population of doubled haploid (DH) maize lines created from 16 diverse founders to perform QTL mapping. We compare three models that assume bi-allelic, founder, and ancestral haplotype allelic states for QTL. The three methods have different power to detect QTL for a variety of agronomic traits. Although the founder approach finds the most QTL, there are also QTL unique to each method, suggesting that each model has advantages for traits with different genetic architectures. A closer look at a well-characterized flowering time QTL, qDTA8, which contains vgt1, suggests a potential epistatic interaction and highlights the strengths and weaknesses of each method. Overall, our results reinforce the importance of considering different approaches to analyzing genotypic datasets, and show the limitations of binary SNP data for identifying multi-allelic QTL.

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

2019 ◽  
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.

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

2020 ◽  
Vol 24 ◽  
pp. 100145 ◽  
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

ADDO: a comprehensive toolkit to detect, classify and visualize additive and non-additive quantitative trait loci

2019 ◽  
Vol 36 (5) ◽  
pp. 1517-1521
Author(s):  
Leilei Cui ◽  
Bin Yang ◽  
Nikolas Pontikos ◽  
Richard Mott ◽  
Lusheng Huang
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Association Studies ◽  
Genetic Effects ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Additive Effects ◽  
A Genome ◽  
Trait Loci ◽  
Additive Genetic Effects

Abstract Motivation During the past decade, genome-wide association studies (GWAS) have been used to map quantitative trait loci (QTLs) underlying complex traits. However, most GWAS focus on additive genetic effects while ignoring non-additive effects, on the assumption that most QTL act additively. Consequently, QTLs driven by dominance and other non-additive effects could be overlooked. Results We developed ADDO, a highly efficient tool to detect, classify and visualize QTLs with additive and non-additive effects. ADDO implements a mixed-model transformation to control for population structure and unequal relatedness that accounts for both additive and dominant genetic covariance among individuals, and decomposes single-nucleotide polymorphism effects as either additive, partial dominant, dominant or over-dominant. A matrix multiplication approach is used to accelerate the computation: a genome scan on 13 million markers from 900 individuals takes about 5 h with 10 CPUs. Analysis of simulated data confirms ADDO’s performance on traits with different additive and dominance genetic variance components. We showed two real examples in outbred rat where ADDO identified significant dominant QTL that were not detectable by an additive model. ADDO provides a systematic pipeline to characterize additive and non-additive QTL in whole genome sequence data, which complements current mainstream GWAS software for additive genetic effects. Availability and implementation ADDO is customizable and convenient to install and provides extensive analytics and visualizations. The package is freely available online at https://github.com/LeileiCui/ADDO. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Genome-wide Association Study for Carcass Primal Cut Yields Using Single-step Bayesian Approach in Hanwoo Cattle

2021 ◽  
Vol 12 ◽  
Author(s):  
Masoumeh Naserkheil ◽  
Hossein Mehrban ◽  
Deukmin Lee ◽  
Mi Na Park
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Trait Loci ◽  
Genomic Regions ◽  
Hanwoo Cattle

The importance of meat and carcass quality is growing in beef cattle production to meet both producer and consumer demands. Primal cut yields, which reflect the body compositions of carcass, could determine the carcass grade and, consequently, command premium prices. Despite its importance, there have been few genome-wide association studies on these traits. This study aimed to identify genomic regions and putative candidate genes related to 10 primal cut traits, including tenderloin, sirloin, striploin, chuck, brisket, top round, bottom round, shank, flank, and rib in Hanwoo cattle using a single-step Bayesian regression (ssBR) approach. After genomic data quality control, 43,987 SNPs from 3,745 genotyped animals were available, of which 3,467 had phenotypic records for the analyzed traits. A total of 16 significant genomic regions (1-Mb window) were identified, of which five large-effect quantitative trait loci (QTLs) located on chromosomes 6 at 38–39 Mb, 11 at 21–22 Mb, 14 at 6–7 Mb and 26–27 Mb, and 19 at 26–27 Mb were associated with more than one trait, while the remaining 11 QTLs were trait-specific. These significant regions were harbored by 154 genes, among which TOX, FAM184B, SPP1, IBSP, PKD2, SDCBP, PIGY, LCORL, NCAPG, and ABCG2 were noteworthy. Enrichment analysis revealed biological processes and functional terms involved in growth and lipid metabolism, such as growth (GO:0040007), muscle structure development (GO:0061061), skeletal system development (GO:0001501), animal organ development (GO:0048513), lipid metabolic process (GO:0006629), response to lipid (GO:0033993), metabolic pathways (bta01100), focal adhesion (bta04510), ECM–receptor interaction (bta04512), fat digestion and absorption (bta04975), and Rap1 signaling pathway (bta04015) being the most significant for the carcass primal cut traits. Thus, identification of quantitative trait loci regions and plausible candidate genes will aid in a better understanding of the genetic and biological mechanisms regulating carcass primal cut yields.

scholarly journals Expression quantitative trait loci (eQTLs) in microRNA genes are enriched for schizophrenia and bipolar disorder association signals

2015 ◽  
Vol 45 (12) ◽  
pp. 2557-2569 ◽  
Author(s):  
V. S. Williamson ◽  
M. Mamdani ◽  
G. O. McMichael ◽  
A. H. Kim ◽  
D. Lee ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Quantitative Trait Loci ◽  
Mirna Expression ◽  
Quantitative Trait ◽  
Negative Impact ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Disease Etiology ◽  
Trait Loci ◽  
Postmortem Brains

BackgroundSchizophrenia (SZ) and bipolar disorder (BD) have substantial negative impact on the quality of human life. Both, microRNA (miRNA) expression profiling in SZ and BD postmortem brains [and genome-wide association studies (GWAS)] have implicated miRNAs in disease etiology. Here, we aim to determine whether significant GWAS signals observed in the Psychiatric Genetic Consortium (PGC) are enriched for miRNAs.MethodA two-stage approach was used to determine whether association signals from PGC affect miRNAs: (i) statistical assessment of enrichment using a Simes test and sum of squares test (SST) and (ii) biological evidence that quantitative trait loci (eQTL) mapping to known miRNA genes affect their expression in an independent sample of 78 postmortem brains from the Stanley Medical Research Institute.ResultsA total of 2567 independent single nucleotide polymorphisms (SNPs) (R2 > 0.8) were mapped locally, within 1 Mb, to all known miRNAs (miRBase v. 21). We show robust enrichment for SZ- and BD-related SNPs with miRNAs using Simes (SZ: p ≤ 0.0023, BD: p ≤ 0.038), which remained significant after adjusting for background inflation in SZ (empirical p = 0.018) and approached significance in BD (empirical p = 0.07). At a false discovery rate of 10%, we identified a total of 32 eQTLs to influence miRNA expression; 11 of these overlapped with BD.ConclusionsOur approach of integrating PGC findings with eQTL results can be used to generate specific hypotheses regarding the role of miRNAs in SZ and BD.

Invited Review: HXB/BXH rat recombinant inbred strain platform: a newly enhanced tool for cardiovascular, behavioral, and developmental genetics and genomics

2003 ◽  
Vol 94 (6) ◽  
pp. 2510-2522 ◽  
Author(s):  
Morton P. Printz ◽  
Martin Jirout ◽  
Rebecca Jaworski ◽  
Adamu Alemayehu ◽  
Vladimir Kren
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Recombinant Inbred ◽  
Complex Traits ◽  
Limb Development ◽  
Association Studies ◽  
Left Ventricular ◽  
Brown Norway ◽  
Developmental Genetics ◽  
Trait Loci

This review deals with the largest set of rat recombinant inbred (RI) strains and summarizes past and recent accomplishments with this platform for genetic mapping and analyses of divergent and complex traits. This strain, derived by crossing the spontaneously hypertensive rat, SHR/Ola, with a Brown Norway congenic, BN-Lx, carrying polydactyly-luxate syndrome, is referred to as HXB/BXH. The RI strain set has been used for linkage and association studies to identify quantitative trait loci for numerous cardiovascular phenotypes, including arterial pressure, stress-elicited heart rate, and pressor response, and metabolic traits, including insulin resistance, dyslipidemia and glucose handling, and left ventricular hypertrophy. The strain's utility has been enhanced with development of a new framework marker-based map and strain distribution patterns of polymorphic markers. Quantitative trait loci for behavioral traits mapped include loci for startle motor response and habituation, anxiety and locomotion traits associated with elevated plus maze, and conditioned taste aversion. The polydactyly-luxate syndrome Lx mutation has allowed the study of alleles important to limb development and malformation phenotypes as well as teratogens. The RI strains have guided development of numerous congenic strains to test locus assignments and to study the effect of genetic background. Although these strains were originally developed to aid in studies of rat genetic hypertension and morphogenetic abnormalities, this rodent platform has been shown to be equally powerful for a wide spectrum of traits and endophenotypes. These strains provide a ready and available vehicle for many physiological and pharmacological studies.

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