scholarly journals Genetic architecture of growth traits in Populus revealed by integrated quantitative trait locus ( QTL ) analysis and association studies

2015 ◽  
Vol 209 (3) ◽  
pp. 1067-1082 ◽  
Author(s):  
Qingzhang Du ◽  
Chenrui Gong ◽  
Qingshi Wang ◽  
Daling Zhou ◽  
Haijiao Yang ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Genetic Architecture ◽  
Growth Traits ◽  
Association Studies ◽  
Trait Locus

A longitudinal quantitative trait locus mapping of chicken growth traits

2018 ◽  
Vol 294 (1) ◽  
pp. 243-252 ◽  
Author(s):  
Tatsuhiko Goto ◽  
Akira Ishikawa ◽  
Masahide Nishibori ◽  
Masaoki Tsudzuki
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait Locus Mapping ◽  
Quantitative Trait ◽  
Growth Traits ◽  
Trait Locus ◽  
Locus Mapping

Quantitative trait locus (QTL) analysis of wood quality traits in Eucalyptus nitens

2009 ◽  
Vol 6 (2) ◽  
pp. 305-317 ◽  
Author(s):  
Bala R. Thumma ◽  
Simon G. Southerton ◽  
John C. Bell ◽  
John V. Owen ◽  
Martin L. Henery ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Wood Quality ◽  
Quality Traits ◽  
Eucalyptus Nitens ◽  
Trait Locus

scholarly journals Dissecting genetic architecture of grape proanthocyanidin composition through quantitative trait locus mapping

2012 ◽  
Vol 12 (1) ◽  
pp. 30 ◽  
Author(s):  
Yung-Fen Huang ◽  
Agnès Doligez ◽  
Alexandre Fournier-Level ◽  
Loïc Le Cunff ◽  
Yves Bertrand ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait Locus Mapping ◽  
Quantitative Trait ◽  
Genetic Architecture ◽  
Trait Locus ◽  
Locus Mapping

Quantitative trait locus (QTL) analysis of growth and vegetative propagation traits in Eucalyptus nitens full-sib families

2010 ◽  
Vol 6 (6) ◽  
pp. 877-889 ◽  
Author(s):  
Bala R. Thumma ◽  
Brian S. Baltunis ◽  
John C. Bell ◽  
Livinus C. Emebiri ◽  
Gavin F. Moran ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Analysis ◽  
Vegetative Propagation ◽  
Quantitative Trait ◽  
Eucalyptus Nitens ◽  
Sib Families ◽  
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.

scholarly journals Limited genetic parallels underlie convergent evolution of quantitative pattern variation in mimetic butterflies

2020 ◽  
Author(s):  
Hannah E. Bainbridge ◽  
Melanie N. Brien ◽  
Carlos Morochz ◽  
Patricio A. Salazar ◽  
Pasi Rastas ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Convergent Evolution ◽  
Genetic Basis ◽  
Major Effect ◽  
Multivariate Approach ◽  
Trait Variation ◽  
Heliconius Melpomene ◽  
Trait Locus

AbstractMimetic systems allow us to address the question of whether the same genes control similar phenotypes in different species. Although widespread parallels have been found for major effect loci, much less is known about genes that control quantitative trait variation. In this study, we identify and compare the loci that control subtle changes in the size and shape of forewing pattern elements in two Heliconius butterfly co-mimics. We use quantitative trait locus (QTL) analysis with a multivariate phenotyping approach to map the variation in red pattern elements across the whole forewing surface of Heliconius erato and Heliconius melpomene. These results are compared to a QTL analysis of univariate trait changes, and show that our resolution for identifying small effect loci is improved with the multivariate approach. QTL likely corresponding to the known patterning gene optix were found in both species but otherwise, a remarkably low level of genetic parallelism was found. This lack of similarity indicates that the genetic basis of convergent traits may not be as predictable as assumed from studies that focus solely on Mendelian traits.

scholarly journals Quantitative Trait Locus Analysis in Avocado: The Challenge of a Slow-maturing Horticultural Tree Crop

2019 ◽  
Vol 144 (5) ◽  
pp. 352-362
Author(s):  
Vanessa E.T.M. Ashworth ◽  
Haofeng Chen ◽  
Carlos L. Calderón-Vázquez ◽  
Mary Lu Arpaia ◽  
David N. Kuhn ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Linkage Group ◽  
Linkage Map ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Persea Americana ◽  
Phenotypic Traits ◽  
Experimental Population ◽  
Tree Crop ◽  
Trait Locus

The glossy, green-fleshed fruit of the avocado (Persea americana) has been the object of human selection for thousands of years. Recent interest in healthy nutrition has singled out the avocado as an excellent source of several phytonutrients. Yet as a sizeable, slow-maturing tree crop, it has been largely neglected by genetic studies, owing to a long breeding cycle and costly field trials. We use a small, replicated experimental population of 50 progeny, grown at two locations in two successive years, to explore the feasibility of developing a dense genetic linkage map and to implement quantitative trait locus (QTL) analysis for seven phenotypic traits. Additionally, we test the utility of candidate-gene single-nucleotide polymorphisms developed to genes from biosynthetic pathways of phytonutrients beneficial to human health. The resulting linkage map consisted of 1346 markers (1044.7 cM) distributed across 12 linkage groups. Numerous markers on Linkage Group 10 were associated with a QTL for flowering type. One marker on Linkage Group 1 tracked a QTL for β-sitosterol content of the fruit. A region on Linkage Group 3 tracked vitamin E (α-tocopherol) content of the fruit, and several markers were stable across both locations and study years. We argue that the pursuit of linkage mapping and QTL analysis is worthwhile, even when population size is small.

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