Dataset Information

The developmental and genetic bases of apetaly in Bocconia frutescens (Chelidonieae: Papaveraceae).

ABSTRACT: BACKGROUND:Bocconia and Macleaya are the only genera of the poppy family (Papaveraceae) lacking petals; however, the developmental and genetic processes underlying such evolutionary shift have not yet been studied. RESULTS:We studied floral development in two species of petal-less poppies Bocconia frutescens and Macleaya cordata as well as in the closely related petal-bearing Stylophorum diphyllum. We generated a floral transcriptome of B. frutescens to identify MADS-box ABCE floral organ identity genes expressed during early floral development. We performed phylogenetic analyses of these genes across Ranunculales as well as RT-PCR and qRT-PCR to assess loci-specific expression patterns. We found that petal-to-stamen homeosis in petal-less poppies occurs through distinct developmental pathways. Transcriptomic analyses of B. frutescens floral buds showed that homologs of all MADS-box genes are expressed except for the APETALA3-3 ortholog. Species-specific duplications of other ABCE genes in B. frutescens have resulted in functional copies with expanded expression patterns than those predicted by the model. CONCLUSIONS:Petal loss in B. frutescens is likely associated with the lack of expression of AP3-3 and an expanded expression of AGAMOUS. The genetic basis of petal identity is conserved in Ranunculaceae and Papaveraceae although they have different number of AP3 paralogs and exhibit dissimilar floral groundplans.

SUBMITTER: Arango-Ocampo C

PROVIDER: S-EPMC4971710 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

The developmental and genetic bases of apetaly in Bocconia frutescens (Chelidonieae: Papaveraceae).

Arango-Ocampo Cristina C González Favio F Alzate Juan Fernando JF Pabón-Mora Natalia N

EvoDevo 20160802

<h4>Background</h4>Bocconia and Macleaya are the only genera of the poppy family (Papaveraceae) lacking petals; however, the developmental and genetic processes underlying such evolutionary shift have not yet been studied.<h4>Results</h4>We studied floral development in two species of petal-less poppies Bocconia frutescens and Macleaya cordata as well as in the closely related petal-bearing Stylophorum diphyllum. We generated a floral transcriptome of B. frutescens to identify MADS-box ABCE flor ...[more]

PMID: 27489612

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Project description:BackgroundSPATULA (SPT) and ALCATRAZ (ALC) are recent paralogs that belong to the large bHLH transcription factor family. Orthologs of these genes have been found in all core eudicots, whereas pre-duplication genes, named paleoSPATULA/ALCATRAZ, have been found in basal eudicots, monocots, basal angiosperms and gymnosperms. Nevertheless, functional studies have only been performed in Arabidopsis thaliana, where SPT and ALC are partially redundant in carpel and valve margin development and ALC has a unique role in the dehiscence zone. Further analyses of pre-duplication genes are necessary to assess the functional evolution of this gene lineage.ResultsWe isolated additional paleoSPT/ALC genes from Aristolochia fimbriata, Bocconia frutescens, Cattleya trianae and Hypoxis decumbens from our transcriptome libraries and performed phylogenetic analyses. We identified the previously described bHLH domain in all analyzed sequences and also new conserved motifs using the MEME suite. Finally, we analyzed the expression of three paleoSPT/ALC genes (BofrSPT1/2/3) from Bocconia frutescens, a basal eudicot in the Papaveraceae. To determine the developmental stages at which these genes were expressed, pre- and post-anthesis carpels and fruits of B. frutescens were collected, sectioned, stained, and examined using light microscopy. Using in situ hybridization we detected that BofrSPT1/2/3 genes are expressed in floral buds, early sepal initiation, stamens and carpel primordia and later during fruit development in the dehiscence zone of the opercular fruit.ConclusionsOur expression results, in comparison with those available for core eudicots, suggest conserved roles of members of the SPT/ALC gene lineage across eudicots in the specification of carpel margins and the dehiscence zone of the mature fruits. Although there is some redundancy between ALC and SPT, these gene clades seem to have undergone some degree of sub-functionalization in the core eudicots, likely by changes in cis regulatory regions and to some extent in coding sequences, at least in Brassicaceae. Our results also indicate that in Bocconia frutescens, paleoSPT/ALC genes may play a role in early floral organ specification that was subsequently lost in core eudicot lineages.

Project description:Problem: Brain imaging studies of mental health and neurodevelopmental disorders have recently included machine learning approaches to identify patients based solely on their brain activation. The goal is to identify brain-related features that generalize from smaller samples of data to larger ones; in the case of neurodevelopmental disorders, finding these patterns can help understand differences in brain function and development that underpin early signs of risk for developmental dyslexia. The success of machine learning classification algorithms on neurofunctional data has been limited to typically homogeneous data sets of few dozens of participants. More recently, larger brain imaging data sets have allowed for deep learning techniques to classify brain states and clinical groups solely from neurofunctional features. Indeed, deep learning techniques can provide helpful tools for classification in healthcare applications, including classification of structural 3D brain images. The adoption of deep learning approaches allows for incremental improvements in classification performance of larger functional brain imaging data sets, but still lacks diagnostic insights about the underlying brain mechanisms associated with disorders; moreover, a related challenge involves providing more clinically-relevant explanations from the neural features that inform classification. Methods: We target this challenge by leveraging two network visualization techniques in convolutional neural network layers responsible for learning high-level features. Using such techniques, we are able to provide meaningful images for expert-backed insights into the condition being classified. We address this challenge using a dataset that includes children diagnosed with developmental dyslexia, and typical reader children. Results: Our results show accurate classification of developmental dyslexia (94.8%) from the brain imaging alone, while providing automatic visualizations of the features involved that match contemporary neuroscientific knowledge (brain regions involved in the reading process for the dyslexic reader group and brain regions associated with strategic control and attention processes for the typical reader group). Conclusions: Our visual explanations of deep learning models turn the accurate yet opaque conclusions from the models into evidence to the condition being studied.

Dataset Information

The developmental and genetic bases of apetaly in Bocconia frutescens (Chelidonieae: Papaveraceae).

Publications

The developmental and genetic bases of apetaly in Bocconia frutescens (Chelidonieae: Papaveraceae).

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