Correlational selection and genetic architecture promote the leaf economics spectrum in a perennial grass

The leaf economics spectrum (LES) is hypothesized to result from a trade-off between resource acquisition and conservation. Yet few studies have examined the evolutionary mechanisms behind the LES, perhaps because most species exhibit relatively specialized leaf economics strategies. In a genetic mapping population of the phenotypically diverse grass Panicum virgatum, we evaluate two interacting mechanisms that may drive LES evolution: 1) genetic architecture, where multiple traits are coded by the same gene (pleiotropy) or by genes in close physical proximity (linkage), and 2) correlational selection, where selection acts non-additively on combinations of multiple traits. We found evidence suggesting that shared genetic architecture (pleiotropy) controls covariation between two pairs of leaf economics traits. Additionally, at five common gardens spanning 17 degrees of latitude, correlational selection favored particular combinations of leaf economics traits. Together, these results demonstrate how the LES can evolve within species.

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The genetic basis of the root economics spectrum in a perennial grass

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2107541118 ◽

2021 ◽

Vol 118 (47) ◽

pp. e2107541118

Author(s):

Weile Chen ◽

Yanqi Wu ◽

Felix B. Fritschi ◽

Thomas E. Juenger

Keyword(s):

Genetic Architecture ◽

Panicum Virgatum ◽

Genetic Basis ◽

Perennial Grass ◽

Genetic Correlations ◽

Multiple Traits ◽

Trade Off ◽

Conservative Strategy ◽

Shoot Size ◽

Absorptive Roots

Construction economics of plant roots exhibit predictable relationships with root growth, death, and nutrient uptake strategies. Plant taxa with inexpensively constructed roots tend to more precisely explore nutrient hotspots than do those with costly constructed roots but at the price of more frequent tissue turnover. This trade-off underlies an acquisitive to conservative continuum in resource investment, described as the “root economics spectrum (RES).” Yet the adaptive role and genetic basis of RES remain largely unclear. Different ecotypes of switchgrass (Panicum virgatum) display root features exemplifying the RES, with costly constructed roots in southern lowland and inexpensively constructed roots in northern upland ecotypes. We used an outbred genetic mapping population derived from lowland and upland switchgrass ecotypes to examine the genetic architecture of the RES. We found that absorptive roots (distal first and second orders) were often “deciduous” in winter. The percentage of overwintering absorptive roots was decreased by northern upland alleles compared with southern lowland alleles, suggesting a locally-adapted conservative strategy in warmer and acquisitive strategy in colder regions. Relative turnover of absorptive roots was genetically negatively correlated with their biomass investment per unit root length, suggesting that the key trade-off in framing RES is genetically facilitated. We also detected strong genetic correlations among root morphology, root productivity, and shoot size. Overall, our results reveal the genetic architecture of multiple traits that likely impacts the evolution of RES and plant aboveground–belowground organization. In practice, we provide genetic evidence that increasing switchgrass yield for bioenergy does not directly conflict with enhancing its root-derived carbon sequestration.

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Genetic architecture underlying the expression of eight α-amylase trypsin inhibitors

Theoretical and Applied Genetics ◽

10.1007/s00122-021-03906-y ◽

2021 ◽

Author(s):

Khaoula EL Hassouni ◽

Malte Sielaff ◽

Valentina Curella ◽

Manjusha Neerukonda ◽

Willmar Leiser ◽

...

Keyword(s):

Genetic Architecture ◽

Intestinal Inflammation ◽

Wheat Breeding ◽

Trypsin Inhibitors ◽

Potential Candidate ◽

Lipid Transfer ◽

Wheat Cultivars ◽

Genome Wide ◽

Close Physical Proximity ◽

Major Qtl

Abstract Key message Wheat cultivars largely differ in the content and composition of ATI proteins, but heritability was quite low for six out of eight ATIs. The genetic architecture of ATI proteins is built up of few major and numerous small effect QTL. Abstract Amylase trypsin inhibitors (ATIs) are important allergens in baker’s asthma and suspected triggers of non-celiac wheat sensitivity (NCWS) inducing intestinal and extra-intestinal inflammation. As studies on the expression and genetic architecture of ATI proteins in wheat are lacking, we evaluated 149 European old and modern bread wheat cultivars grown at three different field locations for their content of eight ATI proteins. Large differences in the content and composition of ATIs in the different cultivars were identified ranging from 3.76 pmol for ATI CM2 to 80.4 pmol for ATI 0.19, with up to 2.5-fold variation in CM-type and up to sixfold variation in mono/dimeric ATIs. Generally, heritability estimates were low except for ATI 0.28 and ATI CM2. ATI protein content showed a low correlation with quality traits commonly analyzed in wheat breeding. Similarly, no trends were found regarding ATI content in wheat cultivars originating from numerous countries and decades of breeding history. Genome-wide association mapping revealed a complex genetic architecture built of many small, few medium and two major quantitative trait loci (QTL). The major QTL were located on chromosomes 3B for ATI 0.19-like and 6B for ATI 0.28, explaining 70.6 and 68.7% of the genotypic variance, respectively. Within close physical proximity to the medium and major QTL, we identified eight potential candidate genes on the wheat reference genome encoding structurally related lipid transfer proteins. Consequently, selection and breeding of wheat cultivars with low ATI protein amounts appear difficult requiring other strategies to reduce ATI content in wheat products.

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Relationship between post-fire regeneration and leaf economics spectrum in Mediterranean woody species

Functional Ecology ◽

10.1111/j.1365-2435.2008.01474.x ◽

2009 ◽

Vol 23 (1) ◽

pp. 103-110 ◽

Cited By ~ 21

Author(s):

S. Saura-Mas ◽

B. Shipley ◽

F. Lloret

Keyword(s):

Woody Species ◽

Leaf Economics Spectrum ◽

Leaf Economics

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Genetic Variation for Biomass Yield and Predicted Genetic Gain in Lowland Switchgrass “Kanlow”

Agronomy ◽

10.3390/agronomy10121845 ◽

2020 ◽

Vol 10 (12) ◽

pp. 1845

Author(s):

Santosh Nayak ◽

Hem Bhandari ◽

Carl Sams ◽

Virginia Sykes ◽

Haileab Hilafu ◽

...

Keyword(s):

Genetic Variation ◽

Genetic Gain ◽

Panicum Virgatum ◽

Biomass Yield ◽

Block Design ◽

Perennial Grass ◽

Warm Season ◽

Narrow Sense ◽

Bioenergy Feedstock ◽

Narrow Sense Heritability

Switchgrass (Panicum virgatum L.) is a warm-season, perennial grass valued as a promising candidate species for bioenergy feedstock production. Biomass yield is the most important trait for any bioenergy feedstock. This study was focused on understanding the genetics underlying biomass yield and feedstock quality traits in a “Kanlow” population. The objectives of this study were to (i) assess genetic variation (ii) estimate the narrow sense heritability, and (iii) predict genetic gain per cycle of selection for biomass yield and the components of lignocelluloses. Fifty-four Kanlow half-sib (KHS) families along with Kanlow check were planted in a randomized complete block design with three replications at two locations in Tennessee: Knoxville and Crossville. The data were recorded for two consecutive years: 2013 and 2014. The result showed a significant genetic variation for biomass yield (p < 0.05), hemicellulose concentration (p < 0.05), and lignin concentration (p < 0.01). The narrow sense heritability estimates for biomass yield was very low (0.10), indicating a possible challenge to improve this trait. A genetic gain of 16.5% is predicted for biomass yield in each cycle of selection by recombining parental clones of 10% of superior progenies.

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The Leaf Economics Spectrum and its Underlying Physiological and Anatomical Principles

The Leaf: A Platform for Performing Photosynthesis - Advances in Photosynthesis and Respiration ◽

10.1007/978-3-319-93594-2_16 ◽

2018 ◽

pp. 451-471 ◽

Cited By ~ 1

Author(s):

Yusuke Onoda ◽

Ian J. Wright

Keyword(s):

Leaf Economics Spectrum ◽

Leaf Economics

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Genetic basis of phenotypic plasticity and genotype x environment interaction in a multi-parental population

10.1101/2020.02.07.938456 ◽

2020 ◽

Author(s):

Isidore Diouf ◽

Laurent Derivot ◽

Shai Koussevitzky ◽

Yolande Carretero ◽

Frédérique Bitton ◽

...

Keyword(s):

Phenotypic Plasticity ◽

Genetic Architecture ◽

Genetic Basis ◽

Linear Models ◽

Global Climate ◽

Functional Characterization ◽

Genotype X Environment Interaction ◽

Environment Interaction ◽

Multiple Traits ◽

Genotype X Environment

AbstractDeciphering the genetic basis of phenotypic plasticity and genotype x environment interaction (GxE) is of primary importance for plant breeding in the context of global climate change. Tomato is a widely cultivated crop that can grow in different geographical habitats and which evinces a great capacity of expressing phenotypic plasticity. We used a multi-parental advanced generation intercross (MAGIC) tomato population to explore GxE and plasticity for multiple traits measured in a multi-environment trial (MET) design comprising optimal cultural conditions and water deficit, salinity and heat stress over 12 environments. Substantial GxE was observed for all the traits measured. Different plasticity parameters were estimated through the Finlay-Wilkinson and factorial regression models and used together with the genotypic means for quantitative trait loci (QTL) mapping analyses. Mixed linear models were further used to investigate the presence of interactive QTLs (QEI). The results highlighted a complex genetic architecture of tomato plasticity and GxE. Candidate genes that might be involved in the occurrence of GxE were proposed, paving the way for functional characterization of stress response genes in tomato and breeding for climate-adapted crop.HighlightThe genetic architecture of tomato response to several abiotic stresses is deciphered. QTL for plasticity and QTL x Environment were identified in a highly recombinant MAGIC population.

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