scholarly journals Combination of quantitative trait locus (QTL) mapping and transcriptome analysis reveals submerged germination QTLs and candidate genes controlling coleoptile length in rice

2021 ◽  
Author(s):  
Weilong Kong ◽  
Shuangmiao Li ◽  
Chenhao Zhang ◽  
Yalin Qiang ◽  
Yangsheng Li
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Mapping ◽  
Candidate Genes ◽  
Transcriptome Analysis ◽  
Quantitative Trait ◽  
Coleoptile Length ◽  
Trait Locus

scholarly journals Consequences of Recombination Rate Variation on Quantitative Trait Locus Mapping Studies: Simulations Based on the Drosophila melanogaster Genome

Genetics ◽  
2001 ◽  
Vol 159 (2) ◽  
pp. 581-588
Author(s):  
Mohamed A F Noor ◽  
Aimee L Cunningham ◽  
John C Larkin
Keyword(s):  
Quantitative Trait Locus ◽  
Drosophila Melanogaster ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Recombination Rate ◽  
Genome Project ◽  
Gene Density ◽  
Rate Variation ◽  
Trait Locus ◽  
Recombination Rate Variation

Abstract We examine the effect of variation in gene density per centimorgan on quantitative trait locus (QTL) mapping studies using data from the Drosophila melanogaster genome project and documented regional rates of recombination. There is tremendous variation in gene density per centimorgan across this genome, and we observe that this variation can cause systematic biases in QTL mapping studies. Specifically, in our simulated mapping experiments of 50 equal-effect QTL distributed randomly across the physical genome, very strong QTL are consistently detected near the centromeres of the two major autosomes, and few or no QTL are often detected on the X chromosome. This pattern persisted with varying heritability, marker density, QTL effect sizes, and transgressive segregation. Our results are consistent with empirical data collected from QTL mapping studies of this species and its close relatives, and they explain the “small X-effect” that has been documented in genetic studies of sexual isolation in the D. melanogaster group. Because of the biases resulting from recombination rate variation, results of QTL mapping studies should be taken as hypotheses to be tested by additional genetic methods, particularly in species for which detailed genetic and physical genome maps are not available.

scholarly journals Analysis of candidate genes for morphine preference quantitative trait locus Mop2

Neuroscience ◽  
2014 ◽  
Vol 277 ◽  
pp. 403-416 ◽  
Author(s):  
G.A. Doyle ◽  
C.L. Schwebel ◽  
S.E. Ruiz ◽  
A.D. Chou ◽  
A.T. Lai ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Trait Locus

scholarly journals Barcoded Bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast

2021 ◽  
Author(s):  
Alex N. Nguyen Ba ◽  
Katherine R. Lawrence ◽  
Artur Rego-Costa ◽  
Shreyas Gopalakrishnan ◽  
Daniel Temko ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Large Scale ◽  
Genetic Basis ◽  
Association Studies ◽  
Model Organisms ◽  
Genome Wide Association Studies ◽  
Trait Locus

Mapping the genetic basis of complex traits is critical to uncovering the biological mechanisms that underlie disease and other phenotypes. Genome-wide association studies (GWAS) in humans and quantitative trait locus (QTL) mapping in model organisms can now explain much of the observed heritability in many traits, allowing us to predict phenotype from genotype. However, constraints on power due to statistical confounders in large GWAS and smaller sample sizes in QTL studies still limit our ability to resolve numerous small-effect variants, map them to causal genes, identify pleiotropic effects across multiple traits, and infer non-additive interactions between loci (epistasis). Here, we introduce barcoded bulk quantitative trait locus (BB-QTL) mapping, which allows us to construct, genotype, and phenotype 100,000 offspring of a budding yeast cross, two orders of magnitude larger than the previous state of the art. We use this panel to map the genetic basis of eighteen complex traits, finding that the genetic architecture of these traits involves hundreds of small-effect loci densely spaced throughout the genome, many with widespread pleiotropic effects across multiple traits. Epistasis plays a central role, with thousands of interactions that provide insight into genetic networks. By dramatically increasing sample size, BB-QTL mapping demonstrates the potential of natural variants in high-powered QTL studies to reveal the highly polygenic, pleiotropic, and epistatic architecture of complex traits.Significance statementUnderstanding the genetic basis of important phenotypes is a central goal of genetics. However, the highly polygenic architectures of complex traits inferred by large-scale genome-wide association studies (GWAS) in humans stand in contrast to the results of quantitative trait locus (QTL) mapping studies in model organisms. Here, we use a barcoding approach to conduct QTL mapping in budding yeast at a scale two orders of magnitude larger than the previous state of the art. The resulting increase in power reveals the polygenic nature of complex traits in yeast, and offers insight into widespread patterns of pleiotropy and epistasis. Our data and analysis methods offer opportunities for future work in systems biology, and have implications for large-scale GWAS in human populations.

Quantitative Trait Locus (QTL) Mapping in Aging Systems

2007 ◽  
pp. 321-348 ◽  
Author(s):  
Hui-Chen Hsu ◽  
Lu Lu ◽  
Nengjun Yi ◽  
Gary Zant ◽  
Robert W. Williams ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Trait Locus
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