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Summary Pollination syndromes are a key component of flowering plant diversification, prompting questions about the architecture of single traits and genetic coordination among traits. Here, we investigate the genetics of extreme floral divergence between naturally hybridizing monkeyflowers,Mimulus parishii(self‐pollinated) andM. cardinalis(hummingbird‐pollinated).We mapped quantitative trait loci (QTLs) for 18 pigment, pollinator reward/handling, and dimensional traits in parallel sets of F2hybrids plus recombinant inbred lines and generated nearly isogenic lines (NILs) for two dimensional traits, pistil length and corolla size.Our multi‐population approach revealed a highly polygenic basis (n = 190 QTLs total) for pollination syndrome divergence, capturing minor QTLs even for pigment traits with leading major loci. There was significant QTL overlap within pigment and dimensional categories. Nectar volume QTLs clustered with those for floral dimensions, suggesting a partially shared module. The NILs refined two pistil length QTLs, only one of which has tightly correlated effects on other dimensional traits.An overall polygenic architecture of floral divergence is partially coordinated by genetic modules formed by linkage (pigments) and likely pleiotropy (dimensions plus nectar). This work illuminates pollinator syndrome diversification in a model radiation and generates a robust framework for molecular and ecological genomics.
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Characterizing season‐long floral trajectories in cotton with low‐altitude remote sensing and deep learning
Societal Impact StatementPlant breeding is a critical tool for increasing the productivity, climate resilience, and sustainability of agriculture, but current phenotyping methods are a bottleneck due to the amount of human labor involved. Here, we demonstrate high‐throughput phenotyping with an unmanned aerial vehicle (UAV) to analyze the season‐long flowering pattern in cotton, subsequently mapping relevant genetic factors underpinning the trait. Season‐long flowering is a complex trait, with implications for adaptation of perennials to specific environments. We believe our approach can improve the speed and efficacy of breeding for a variety of woody perennials. SummaryMany perennial plants make important contributions to agroeconomies and agroecosystems but have complex architecture and/or long flowering duration that hinders measurement and selection. Iteratively tracking productivity over a long flowering/fruiting season may permit the identification of genetic factors conferring different reproductive strategies that might be successful in different environments, ranging from rapid early maturation that avoids stresses, to late maturation that utilizes the full seasonal duration to maximize productivity.In cotton, a perennial plant that is generally cultivated as an annual crop, we apply aerial imagery and deep learning methods to novel and stable genetic stocks, identifying genetic factors influencing the duration and rate of fruiting.Our phenotyping method was able to identify 24 QTLs that affect flowering behavior in cotton. A total of five of these corresponded to previously identified QTLs from other studies.While these factors may have different relationships with crop productivity and quality in different environments, their determination adds potentially important information to breeding decisions. With transfer learning of the deep learning models, this approach could be applied widely, potentially improving gains from selection in diverse perennial shrubs and trees essential to sustainable agricultural intensification.
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- Award ID(s):
- 1934481
- PAR ID:
- 10677636
- Publisher / Repository:
- New Phytologist Foundation
- Date Published:
- Journal Name:
- PLANTS, PEOPLE, PLANET
- Volume:
- 7
- Issue:
- 6
- ISSN:
- 2572-2611
- Page Range / eLocation ID:
- 1657 to 1673
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Summary Changes to flowering phenology are a key response of plants to climate change. However, we know little about how these changes alter temporal patterns of reproductive overlap (i.e. phenological reassembly).We combined long‐term field (1937–2012) and herbarium records (1850–2017) of 68 species in a flowering plant community in central North America and used a novel application of Bayesian quantile regression to estimate changes to flowering season length, altered richness and composition of co‐flowering assemblages, and whether phenological shifts exhibit seasonal trends.Across the past century, phenological shifts increased species' flowering durations by 11.5 d on average, which resulted in 94% of species experiencing greater flowering overlap at the community level. Increases to co‐flowering were particularly pronounced in autumn, driven by a greater tendency of late season species to shift the ending of flowering later and to increase flowering duration.Our results demonstrate that species‐level phenological shifts can result in considerable phenological reassembly and highlight changes to flowering duration as a prominent, yet underappreciated, effect of climate change. The emergence of an autumn co‐flowering mode emphasizes that these effects may be season‐dependent.more » « less
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Abstract Cotton (Gossypium hirsutumL.) is the key renewable fibre crop worldwide, yet its yield and fibre quality show high variability due to genotype-specific traits and complex interactions among cultivars, management practices and environmental factors. Modern breeding practices may limit future yield gains due to a narrow founding gene pool. Precision breeding and biotechnological approaches offer potential solutions, contingent on accurate cultivar-specific data. Here we address this need by generating high-quality reference genomes for three modern cotton cultivars (‘UGA230’, ‘UA48’ and ‘CSX8308’) and updating the ‘TM-1’ cotton genetic standard reference. Despite hypothesized genetic uniformity, considerable sequence and structural variation was observed among the four genomes, which overlap with ancient and ongoing genomic introgressions from ‘Pima’ cotton, gene regulatory mechanisms and phenotypic trait divergence. Differentially expressed genes across fibre development correlate with fibre production, potentially contributing to the distinctive fibre quality traits observed in modern cotton cultivars. These genomes and comparative analyses provide a valuable foundation for future genetic endeavours to enhance global cotton yield and sustainability.more » « less
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Abstract Pollen protein content has been demonstrated to be an essential nutritional component for bees and thus important in mediating plant–pollinator interactions. However, little is known on the drivers and consequences of among‐species variation in pollen protein content and how this can impact male and female reproductive success across plant species. Among‐species variation in resources allocated to pollen nutrition could further be constrained by life‐history strategies (e.g. survival‐reproduction trade‐offs) or evolutionary history.Here, we surveyed pollen protein content for 29 species within a diverse co‐flowering community and evaluated the effect of pollen protein on male and female reproductive success. We also tested the role of life history (annuals vs. perennials) and phylogeny in mediating differences in resource allocation to pollen nutrition.We found that pollen protein content influences components of male (bee visitor abundance and pollen dispersal) but not female (conspecific pollen deposition and pollen tube growth) reproductive success, suggesting this trait affects plants only via male function. This sex‐specific effect further suggests the potential for sexual conflicts driven by differential investment on this trait. We found no phylogenetic signal on pollen protein content. However, pollen protein content was higher in annual compared to perennial species suggesting survival versus reproduction trade‐offs also contribute to variation in pollen protein at the community level.Our study underscores the importance of understanding the ecological and evolutionary drivers of pollen protein content across plant species. Our results further suggest the existence of sexual conflicts and ecological trade‐offs mediated by differential investment in pollen nutritional quality, with important implications for community assembly and the structure of plant–pollinator interactions. Read the freePlain Language Summaryfor this article on the Journal blog.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1002/ppp3.10644
