Root system architecture ( We characterised 98 two‐dimensional and three‐dimensional The two weeds were distinguishable from the crop in similar and predictable ways, suggesting independent evolution of a ‘weedy’ Our findings suggest that despite the double bottlenecks of domestication and de‐domestication, weedy rice nonetheless shows genetic flexibility in the repeated evolution of weedy
Genetic correlations among different components of phenotypes, especially those resulting from pleiotropy, can constrain or facilitate trait evolution. These factors could especially influence the evolution of traits that are functionally integrated, such as those comprising the flower. Indeed, pleiotropy is proposed as a main driver of repeated convergent trait transitions, including the evolution of phenotypically similar pollinator syndromes. We assessed the role of pleiotropy in the differentiation of floral and other reproductive traits between two species – We found that most floral traits had a relatively simple genetic basis (few, predominantly additive, These mechanisms may have facilitated the rapid floral trait evolution observed within
- NSF-PAR ID:
- 10461294
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- New Phytologist
- Volume:
- 223
- Issue:
- 2
- ISSN:
- 0028-646X
- Page Range / eLocation ID:
- p. 1009-1022
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
Convergent evolution of root system architecture in two independently evolved lineages of weedy ricemore » « less
Summary RSA ) is a critical aspect of plant growth and competitive ability. Here we used two independently evolved strains of weedy rice, a de‐domesticated form of rice, to study the evolution of weed‐associatedRSA traits and the extent to which they evolve through shared or different genetic mechanisms.RSA traits in 671 plants representing parents and descendants of two recombinant inbred line populations derived from two weed × crop crosses. A random forest machine learning model was used to assess the degree to which root traits can predict genotype and the most diagnostic traits for doing so. We used quantitative trait locus (QTL) mapping to compare genetic architecture between the weed strains.RSA phenotype. Notably, comparativeQTL mapping revealed little evidence for shared underlying genetic mechanisms.RSA traits. Whereas the root growth of cultivated rice may facilitate interactions among neighbouring plants, the weedy rice phenotype may minimise below‐ground contact as a competitive strategy. -
more » « less
Abstract Floral attraction traits can significantly affect pollinator visitation patterns, but adaptive evolution of these traits may be constrained by correlations with other traits. In some cases, molecular pathways contributing to floral attraction are well characterized, offering the opportunity to explore loci potentially underlying variation among individuals. Here, we quantify the range of variation in floral
UV patterning (i.e.UV ‘bulls‐eye nectar guides) among crop and wild accessions ofBrassica rapa . We then use experimental crosses to examine the genetic architecture, candidate loci and biochemical underpinnings of this patterning as well as phenotypic manipulations to test the ecological impact. We find qualitative variation inUV patterning between wild (commonly lackingUV patterns) and crop (commonly exhibitingUV patterns) accessions. Similar to the majority of crops, recombinant inbred lines (RIL s) derived from an oilseed crop ×WI fast‐plant®cross exhibitUV patterns, the size of which varies extensively among genotypes. InRIL s, we further observe strong statistical‐genetic andQTL correlations within petal morphological traits and within measurements of petalUV patterning; however, correlations between morphology andUV patterning are weak or nonsignificant, suggesting thatUV patterning is regulated and may evolve independently of overall petal size.HPLC analyses reveal a high concentration of sinapoyl glucose inUV ‐absorbing petal regions, which, in concert with physical locations ofUV ‐traitQTL s, suggest a regulatory and structural gene as candidates underlying observed quantitative variation. Finally, insects prefer flowers withUV bulls‐eye patterns over those that lack patterns, validating the importance ofUV patterning in pollen‐limited populations ofB. rapa . -
more » « less
Summary Although the evolution of the selfing syndrome often involves reductions in floral size, pollen and nectar, few studies of selfing syndrome divergence have examined nectar. We investigate whether nectar traits have evolved independently of other floral size traits in the selfing syndrome, whether nectar traits diverged due to drift or selection, and the extent to which quantitative trait locus (QTL) analyses predict genetic correlations.
We use F5 recombinant inbred lines (RILs) generated from a cross between
Ipomoea cordatotriloba andIpomoea lacunosa . We calculate genetic correlations to identify evolutionary modules, test whether trait divergence was due to selection, identify QTLs and perform correlation analyses to evaluate how well QTL properties reflect genetic correlations.Nectar and floral size traits form separate evolutionary modules. Selection has acted to reduce nectar traits in the selfing
I. lacunosa . Genetic correlations predicted from QTL properties are consistent with observed genetic correlations.Changes in floral traits associated with the selfing syndrome reflect independent evolution of at least two evolutionary modules: nectar and floral size traits. We also demonstrate directional selection on nectar traits, which is likely to be independent of selection on floral size traits. Our study also supports the expected mechanistic link between QTL properties and genetic correlations.
-
more » « less
Summary The transition from pollinator‐mediated outbreeding to selfing has occurred many times in angiosperms. This is generally accompanied by a reduction in traits attracting pollinators, including reduced emission of floral scent. In
Capsella , emission of benzaldehyde as a main component of floral scent has been lost in selfingC. rubella by mutation of cinnamate‐CoA ligaseCNL 1. However, the biochemical basis and evolutionary history of this loss remain unknown, as does the reason for the absence of benzaldehyde emission in the independently derived selferCapsella orientalis .We used plant transformation,
in vitro enzyme assays, population genetics and quantitative genetics to address these questions.CNL 1 has been inactivated twice independently by point mutations inC. rubella , causing a loss of enzymatic activity. Both inactive haplotypes are found within and outside of Greece, the centre of origin ofC. rubella , indicating that they arose before its geographical spread. By contrast, the loss of benzaldehyde emission inC. orientalis is not due to an inactivating mutation inCNL 1CNL 1 -
more » « less
Abstract The integrated responses of biological systems to genetic and environmental variation result in substantial covariance in multiple phenotypes. The resultant pleiotropy, environmental effects, and genotype‐by‐environmental interactions (GxE) are foundational to our understanding of biology and genetics. Yet, the treatment of correlated characters, and the identification of the genes encoding functions that generate this covariance, has lagged. As a test case for analyzing the genetic basis underlying multiple correlated traits, we analyzed maize kernel ionomes from Intermated B73 x Mo17 (
IBM ) recombinant inbred populations grown in 10 environments. Plants obtain elements from the soil through genetic and biochemical pathways responsive to physiological state and environment. Most perturbations affect multiple elements which leads theionome , the full complement of mineral nutrients in an organism, to vary as an integrated network rather than a set of distinct single elements. We compared quantitative trait loci (QTL ) determining single‐element variation toQTL that predict variation in principal components (PC s) of multiple‐element covariance. Single‐element and multivariate approaches detected partially overlapping sets of loci.QTL influencing trait covariation were detected at loci that were not found by mapping single‐element traits. Moreover, this approach permitted testing environmental components of trait covariance, and identified multi‐element traits that were determined by both genetic and environmental factors as well as genotype‐by‐environment interactions. Growth environment had a profound effect on the elemental profiles and multi‐element phenotypes were significantly correlated with specific environmental variables.
