Genetic dissection of flour whiteness by unconditional and conditional quantitative trait locus mapping in wheat

SUMMARYFlour whiteness (FW) is an important factor in assessing flour quality and determining the end product quality. It is an integrated sensory indicator reflecting flour colour and is negatively correlated with protein content. In order to dissect the genetic relationship between FW and its five related traits at the quantitative trait locus (QTL)/gene level, a recombinant inbred line population was evaluated under three environments. Quantitative trait loci for FW were analysed by unconditional and conditional QTL mapping. Four unconditional additive QTLs and 16 conditional additive QTLs were detected across the three environments. Of these QTLs, only one major additive QTL (Qfw1D1-1) was consistently identified using both unconditional and conditional QTL analysis. This QTL was independent of flour colour a* (a function of red-green with a positive a* for redness and negative for greenness) and b* (a green-blue value with positive value for yellowness and negative for blueness) and was only slightly affected by flour protein content. A minor additive QTL (Qfw4A-4) was also detected using these two QTL mapping methods, being independent of flour colour a* and b*. Five unconditional and ten conditional epistatic minor QTLs were detected, from which only one pair (Qfw3A-10/Qfw6B-6) was identified by both unconditional and conditional QTL mapping, also independent of flour colour a* and b*. The major QTL (Qfw1D1-1) identified in the current study for the first time can be used for improving wheat FW in marker-assisted breeding.

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Faculty Opinions recommendation of Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1022311.375733 ◽

2006 ◽

Author(s):

Richard Paylor

Keyword(s):

Quantitative Trait Locus ◽

Quantitative Trait ◽

Genetic Dissection ◽

Trait Locus

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

Genetics ◽

10.1093/genetics/159.2.581 ◽

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.

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

10.1101/2021.09.08.459513 ◽

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.

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