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Abstract Understanding how evolution proceeds from molecules to organisms to interactions requires integrative studies spanning biological levels. Linking phenotypes with associated genes and fitness illuminates how adaptive walks move organisms between fitness peaks. Floral evolution can confer rapid reproductive isolation, often converging in association with pollinator guilds. Within the monkeyflowers (Mimulussect.Erythranthe), yellow flowers within red hummingbird-pollinated species have arisen at least twice, suggesting possible pollinator shifts. We compare two yellow-flowered forms ofM. cardinalisandM. verbenaceusto their red counterparts in floral phenotypes, biochemistry, transcriptomic and genomic variation, and pollinator interactions. We find convergence in ongoing adaptive walks of both yellow morphs, with consistent changes in traits of large effect (floral pigments, associated gene expression), resulting in strong preference for yellow flowers by bumblebees. Shifts in scent emission and floral opening size also favor bee adaptation, suggesting smaller-effect steps from hummingbird to bee pollination. By examining intraspecific, incipient pollinator shifts in two related species, we elucidate adaptive walks at early stages, revealing how convergent large effect mutations (floral color) may drive pollinator attraction, followed by smaller effect changes for mechanical fit and reward access. Thus, ongoing adaptive walks may impact reproductive isolation and incipient speciation via convergent evolution. 

Abstract Short-read RNA-seq studies of grafted plants have led to the proposal that thousands of messenger RNAs (mRNAs) move over long distances between plant tissues^1–7, potentially acting as signals^8–12. Transport of mRNAs between cells and tissues has been shown to play a role in several physiological and developmental processes in plants, such as tuberization¹³, leaf development¹⁴and meristem maintenance¹⁵; yet for most mobile mRNAs, the biological relevance of transport remains to be determined^16–19. Here we perform a meta-analysis of existing mobile mRNA datasets and examine the associated bioinformatic pipelines. Taking technological noise, biological variation, potential contamination and incomplete genome assemblies into account, we find that a high percentage of currently annotated graft-mobile transcripts are left without statistical support from available RNA-seq data. This meta-analysis challenges the findings of previous studies and current views on mRNA communication.