Effect of small mapping population sizes on reliability of quantitative trait locus (QTL) mapping

2012 ◽  
Vol 4 (47) ◽  
Author(s):  
C. Raghavan
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Mapping Population ◽  
Population Sizes ◽  
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 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

scholarly journals A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat

2019 ◽  
Vol 17 (7) ◽  
pp. 1380-1393 ◽  
Author(s):  
Yosef G. Kidane ◽  
Cherinet A. Gesesse ◽  
Bogale N. Hailemariam ◽  
Ermias A. Desta ◽  
Dejene K. Mengistu ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Association Mapping ◽  
Durum Wheat ◽  
Quantitative Trait Locus Mapping ◽  
Quantitative Trait ◽  
Mapping Population ◽  
Nested Association Mapping ◽  
Trait Locus ◽  
Locus Mapping ◽  
Association Mapping Population

scholarly journals Quantitative trait locus mapping of airway responsiveness to chromosomes 6 and 7 in inbred mice

1999 ◽  
Vol 277 (6) ◽  
pp. L1118-L1123 ◽  
Author(s):  
G. T. De Sanctis ◽  
J. B. Singer ◽  
A. Jiao ◽  
C. N. Yandava ◽  
Y. H. Lee ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Genetic Factors ◽  
Inbred Mice ◽  
Airway Responsiveness ◽  
Chromosome 17 ◽  
Chromosome 6 ◽  
Trait Locus ◽  
Locus Mapping

Quantitative trait locus (QTL) mapping was used to identify chromosomal regions contributing to airway hyperresponsiveness in mice. Airway responsiveness to methacholine was measured in A/J and C3H/HeJ parental strains as well as in progeny derived from crosses between these strains. QTL mapping of backcross [(A/J × C3H/HeJ) × C3H/HeJ] progeny ( n = 137–227 informative mice for markers tested) revealed two significant linkages to loci on chromosomes 6 and 7. The QTL on chromosome 6 confirms the previous report by others of a linkage in this region in the same genetic backgrounds; the second QTL, on chromosome 7, represents a novel locus. In addition, we obtained suggestive evidence for linkage (logarithm of odds ratio = 1.7) on chromosome 17, which lies in the same region previously identified in a cross between A/J and C57BL/6J mice. Airway responsiveness in a cross between A/J and C3H/HeJ mice is under the control of at least two major genetic loci, with evidence for a third locus that has been previously implicated in an A/J and C57BL/6J cross; this indicates that multiple genetic factors control the expression of this phenotype.

scholarly journals Quantitative Trait Locus (QTL) Mapping Reveals a Role for Unstudied Genes in Aspergillus Virulence

PLoS ONE ◽  
2011 ◽  
Vol 6 (4) ◽  
pp. e19325 ◽  
Author(s):  
Julian K. Christians ◽  
Manjinder S. Cheema ◽  
Ismael A. Vergara ◽  
Cortney A. Watt ◽  
Linda J. Pinto ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Trait Locus

scholarly journals The molecular architecture of Drosophila melanogaster defense against Beauveria bassiana explored through evolve and resequence and quantitative trait locus mapping

2021 ◽  
Author(s):  
Parvin Shahrestani ◽  
Elizabeth King ◽  
Reza Ramezan ◽  
Mark Phillips ◽  
Melissa Riddle ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Sexual Dimorphism ◽  
Qtl Mapping ◽  
Beauveria Bassiana ◽  
Quantitative Trait ◽  
Recombinant Inbred Lines ◽  
Immune Defense ◽  
Cross Resistance ◽  
Molecular Architecture ◽  
Trait Locus

Abstract Little is known about the genetic architecture of antifungal immunity in natural populations. Using two population genetic approaches, Quantitative Trait Locus (QTL) Mapping and Evolve and Resequence (E&R), we explored D. melanogaster immune defense against infection with the fungus Beauveria bassiana. Immune defense was highly variable both in the recombinant inbred lines from the Drosophila Synthetic Population Resource used for our QTL mapping and in the synthetic outbred populations used in our E&R study. Survivorship of infection improved dramatically over just 10 generations in the E&R study, and continued to increase for an additional 9 generations, revealing a trade-off with uninfected longevity. Populations selected for increased defense against B. bassiana evolved cross resistance to a second, distinct B. bassiana strain but not to bacterial pathogens. The QTL mapping study revealed that sexual dimorphism in defense depends on host genotype, and the E&R study indicated that sexual dimorphism also depends on the specific pathogen to which the host is exposed. Both the QTL mapping and E&R experiments generated lists of potentially causal candidate genes, although these lists were non-overlapping.

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