scholarly journals Quantitative trait locus mapping reveals an independent genetic basis for joint divergence in leaf function, life-history, and floral traits between scarlet monkeyflower (Mimulus cardinalis) populations

Author(s):  
Thomas C. Nelson ◽  
Christopher D. Muir ◽  
Angela M. Stathos ◽  
Daniel D. Vanderpool ◽  
Kayli Anderson ◽  
...  

ABSTRACTPREMISEAcross taxa, vegetative and floral traits that vary along a fast-slow life-history axis are often correlated with leaf functional traits arrayed along the leaf economics spectrum, suggesting a constrained set of adaptive trait combinations. Such broad-scale convergence may arise from genetic constraints imposed by pleiotropy (or tight linkage) within species, or from natural selection alone. Understanding the genetic basis of trait syndromes and their components is key to distinguishing these alternatives and predicting evolution in novel environments.METHODSWe used a line-cross approach and quantitative trait locus (QTL) mapping to characterize the genetic basis of twenty leaf functional/physiological, life history, and floral traits in hybrids between annualized and perennial populations of scarlet monkeyflower (Mimulus cardinalis).RESULTSWe mapped both single and multi-trait QTLs for life history, leaf function and reproductive traits, but found no evidence of genetic co-ordination across categories. A major QTL for three leaf functional traits (thickness, photosynthetic rate, and stomatal resistance) suggests that a simple shift in leaf anatomy may be key to adaptation to seasonally dry habitats.CONCLUSIONSOur results suggest that the co-ordination of resource-acquisitive leaf physiological traits with a fast life history and more selfing mating system results from environmental selection rather than functional or genetic constraint. Independent assortment of distinct trait modules, as well as a simple genetic basis to leaf physiological traits associated with drought escape, may facilitate adaptation to changing climates.

2021 ◽  
Author(s):  
Alex N. Nguyen Ba ◽  
Katherine R. Lawrence ◽  
Artur Rego-Costa ◽  
Shreyas Gopalakrishnan ◽  
Daniel Temko ◽  
...  

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.


Author(s):  
Hannah E. Bainbridge ◽  
Melanie N. Brien ◽  
Carlos Morochz ◽  
Patricio A. Salazar ◽  
Pasi Rastas ◽  
...  

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.


Genetics ◽  
2000 ◽  
Vol 156 (3) ◽  
pp. 1309-1322 ◽  
Author(s):  
Päivi Hurme ◽  
Mikko J Sillanpää ◽  
Elja Arjas ◽  
Tapani Repo ◽  
Outi Savolainen

Abstract We examined the genetic basis of large adaptive differences in timing of bud set and frost hardiness between natural populations of Scots pine. As a mapping population, we considered an “open-pollinated backcross” progeny by collecting seeds of a single F1 tree (cross between trees from southern and northern Finland) growing in southern Finland. Due to the special features of the design (no marker information available on grandparents or the father), we applied a Bayesian quantitative trait locus (QTL) mapping method developed previously for outcrossed offspring. We found four potential QTL for timing of bud set and seven for frost hardiness. Bayesian analyses detected more QTL than ANOVA for frost hardiness, but the opposite was true for bud set. These QTL included alleles with rather large effects, and additionally smaller QTL were supported. The largest QTL for bud set date accounted for about a fourth of the mean difference between populations. Thus, natural selection during adaptation has resulted in selection of at least some alleles of rather large effect.


2021 ◽  
Author(s):  
Parvin Shahrestani ◽  
Elizabeth King ◽  
Reza Ramezan ◽  
Mark Phillips ◽  
Melissa Riddle ◽  
...  

Many of the molecular mechanisms for antifungal immunity in Drosophila melanogaster have been defined, but relatively little is known about the genetic basis for variation in antifungal immunity in natural populations. Using two population genetic approaches, Quantitative Trait Locus (QTL) Mapping and Evolve and Resequence (E&R), we explored the genetics underlying 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 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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