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

2021 ◽  
Author(s):  
Thomas C. Nelson ◽  
Christopher D. Muir ◽  
Angela M. Stathos ◽  
Daniel D. Vanderpool ◽  
Kayli Anderson ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Life History ◽  
Quantitative Trait Locus Mapping ◽  
Quantitative Trait ◽  
Genetic Basis ◽  
Floral Traits ◽  
Trait Locus ◽  
Locus Mapping

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

2020 ◽  
Author(s):  
Thomas C. Nelson ◽  
Christopher D. Muir ◽  
Angela M. Stathos ◽  
Daniel D. Vanderpool ◽  
Kayli Anderson ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Life History ◽  
Functional Traits ◽  
Quantitative Trait ◽  
Genetic Basis ◽  
Physiological Traits ◽  
Floral Traits ◽  
Leaf Functional Traits ◽  
Environmental Selection ◽  
Trait Locus

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.

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

scholarly journals R/qtlcharts: interactive graphics for quantitative trait locus mapping

2014 ◽  
Author(s):  
Karl W Broman
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait Locus Mapping ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
R Package ◽  
High Dimensional ◽  
Interactive Graphics ◽  
Phenotype Data ◽  
Trait Locus ◽  
Locus Mapping

Every data visualization can be improved with some level of interactivity. Interactive graphics hold particular promise for the exploration of high-dimensional data. R/qtlcharts is an R package to create interactive graphics for experiments to map quantitative trait loci (QTL; genetic loci that influence quantitative traits). R/qtlcharts serves as a companion to the R/qtl package, providing interactive versions of R/qtl's static graphs, as well as additional interactive graphs for the exploration of high-dimensional genotype and phenotype data.

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