6,288 research outputs found

    Integrated functional networks of process, tissue, and developmental stage specific interactions in Arabidopsis thaliana

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    <p>Abstract</p> <p>Background</p> <p>Recent years have seen an explosion in plant genomics, as the difficulties inherent in sequencing and functionally analyzing these biologically and economically significant organisms have been overcome. <it>Arabidopsis thaliana</it>, a versatile model organism, represents an opportunity to evaluate the predictive power of biological network inference for plant functional genomics.</p> <p>Results</p> <p>Here, we provide a compendium of functional relationship networks for <it>Arabidopsis thaliana </it>leveraging data integration based on over 60 microarray, physical and genetic interaction, and literature curation datasets. These include tissue, biological process, and development stage specific networks, each predicting relationships specific to an individual biological context. These biological networks enable the rapid investigation of uncharacterized genes in specific tissues and developmental stages of interest and summarize a very large collection of <it>A. thaliana </it>data for biological examination. We found validation in the literature for many of our predicted networks, including those involved in disease resistance, root hair patterning, and auxin homeostasis.</p> <p>Conclusions</p> <p>These context-specific networks demonstrate that highly specific biological hypotheses can be generated for a diversity of individual processes, developmental stages, and plant tissues in <it>A. thaliana</it>. All predicted functional networks are available online at <url>http://function.princeton.edu/arathGraphle</url>.</p

    Correlation analysis of the transcriptome of growing leaves with mature leaf parameters in a maize RIL population

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    Background: To sustain the global requirements for food and renewable resources, unraveling the molecular networks underlying plant growth is becoming pivotal. Although several approaches to identify genes and networks involved in final organ size have been proven successful, our understanding remains fragmentary. Results: Here, we assessed variation in 103 lines of the Zea mays B73xH99 RIL population for a set of final leaf size and whole shoot traits at the seedling stage, complemented with measurements capturing growth dynamics, and cellular measurements. Most traits correlated well with the size of the division zone, implying that the molecular basis of final leaf size is already defined in dividing cells of growing leaves. Therefore, we searched for association between the transcriptional variation in dividing cells of the growing leaf and final leaf size and seedling biomass, allowing us to identify genes and processes correlated with the specific traits. A number of these genes have a known function in leaf development. Additionally, we illustrated that two independent mechanisms contribute to final leaf size, maximal growth rate and the duration of growth. Conclusions: Untangling complex traits such as leaf size by applying in-depth phenotyping allows us to define the relative contributions of the components and their mutual associations, facilitating dissection of the biological processes and regulatory networks underneath

    Organellar carbon metabolism is co-ordinated with distinct developmental phases of secondary xylem

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    Subcellular compartmentation of plant biosynthetic pathways in the mitochondria and plastids requires coordinated regulation of nuclear encoded genes, and the role of these genes has been largely ignored by wood researchers. In this study, we constructed a targeted systems genetics coexpression network of xylogenesis in Eucalyptus using plastid and mitochondrial carbon metabolic genes and compared the resulting clusters to the aspen xylem developmental series. The constructed network clusters reveal the organization of transcriptional modules regulating subcellular metabolic functions in plastids and mitochondria. Overlapping genes between the plastid and mitochondrial networks implicate the common transcriptional regulation of carbon metabolism during xylem secondary growth. We show that the central processes of organellar carbon metabolism are distinctly coordinated across the developmental stages of wood formation and are specifically associated with primary growth and secondary cell wall deposition. We also demonstrate that, during xylogenesis, plastid-targeted carbon metabolism is partially regulated by the central clock for carbon allocation towards primary and secondary xylem growth, and we discuss these networks in the context of previously established associations with wood-related complex traits. This study provides a new resolution into the integration and transcriptional regulation of plastid- and mitochondrial-localized carbon metabolism during xylogenesis

    Radial or bilateral? The molecular basis of floral symmetry.

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    In the plant kingdom, the flower is one of the most relevant evolutionary novelties. Floral symmetry has evolved multiple times from the ancestral condition of radial to bilateral symmetry. During evolution, several transcription factors have been recruited by the different developmental pathways in relation to the increase of plant complexity. The MYB proteins are among the most ancient plant transcription factor families and are implicated in different metabolic and developmental processes. In the model plant Antirrhinum majus, three MYB transcription factors (DIVARICATA, DRIF, and RADIALIS) have a pivotal function in the establishment of floral dorsoventral asymmetry. Here, we present an updated report of the role of the DIV, DRIF, and RAD transcription factors in both eudicots and monocots, pointing out their functional changes during plant evolution. In addition, we discuss the molecular models of the establishment of flower symmetry in different flowering plants

    Variation in the flowering time orthologs BrFLC and BrSOC1 in a natural population of Brassica rapa.

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    Understanding the genetic basis of natural phenotypic variation is of great importance, particularly since selection can act on this variation to cause evolution. We examined expression and allelic variation in candidate flowering time loci in Brassica rapa plants derived from a natural population and showing a broad range in the timing of first flowering. The loci of interest were orthologs of the Arabidopsis genes FLC and SOC1 (BrFLC and BrSOC1, respectively), which in Arabidopsis play a central role in the flowering time regulatory network, with FLC repressing and SOC1 promoting flowering. In B. rapa, there are four copies of FLC and three of SOC1. Plants were grown in controlled conditions in the lab. Comparisons were made between plants that flowered the earliest and latest, with the difference in average flowering time between these groups ∼30 days. As expected, we found that total expression of BrSOC1 paralogs was significantly greater in early than in late flowering plants. Paralog-specific primers showed that expression was greater in early flowering plants in the BrSOC1 paralogs Br004928, Br00393 and Br009324, although the difference was not significant in Br009324. Thus expression of at least 2 of the 3 BrSOC1 orthologs is consistent with their predicted role in flowering time in this natural population. Sequences of the promoter regions of the BrSOC1 orthologs were variable, but there was no association between allelic variation at these loci and flowering time variation. For the BrFLC orthologs, expression varied over time, but did not differ between the early and late flowering plants. The coding regions, promoter regions and introns of these genes were generally invariant. Thus the BrFLC orthologs do not appear to influence flowering time in this population. Overall, the results suggest that even for a trait like flowering time that is controlled by a very well described genetic regulatory network, understanding the underlying genetic basis of natural variation in such a quantitative trait is challenging

    Comparative transcriptomics in plants

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    Comparative genomics is the study of the structural and functional rela- tionships between the genomes of different species or strains. Recently microarray experiments have yielded massive amounts of expression infor- mation for many genes under various conditions or in different tissues for different model species. Expression compendia grouping multiple microar- ray experiments performed in similar (or different) experimental condition make it possible to define correlated expression patterns between genes. Genes within such a coexpression cluster are expected to have more similar functionality compared to genes lacking expression similarity. In this thesis the different steps required to systematically compare expres- sion data across species are described and some future applications of plant comparative transcriptomics are highlighted. Then we analyzed if function- ally related genes show coexpression in Arabidopsis and rice and developed a general framework to measure expression context conservation (ECC) for orthologous genes. Additionally, we studied the evolutionary parameters influencing ECC conservation and compared expression with sequence evo- lution. At the end, a new method is presented to define high quality tis- sue specific genes in seven different plant species; A.thaliana (Arabidopsis), Z.mays (Maize), M.truncatula (Medicago), P.trichocarpa (Poplar), O.sativa (Rice), G.max (Soybean) and V.vinifera (Grape) using Affymetrix microar- ray expression profiles. We also performed an in-depth study on the rela- tionship between leaf tissue specific genes coexpression clusters, within a species and in comparison with other species for a set of strictly selected genes

    Plant Cellular and Molecular Biotechnology: Following Mariotti's Steps

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    This review is dedicated to the memory of Prof. Domenico Mariotti, who significantly contributed to establishing the Italian research community in Agricultural Genetics and carried out the first experiments of Agrobacterium-mediated plant genetic transformation and regeneration in Italy during the 1980s. Following his scientific interests as guiding principles, this review summarizes the recent advances obtained in plant biotechnology and fundamental research aiming to: (i) Exploit in vitro plant cell and tissue cultures to induce genetic variability and to produce useful metabolites; (ii) gain new insights into the biochemical function of Agrobacterium rhizogenes rol genes and their application to metabolite production, fruit tree transformation, and reverse genetics; (iii) improve genetic transformation in legume species, most of them recalcitrant to regeneration; (iv) untangle the potential of KNOTTED1-like homeobox (KNOX) transcription factors in plant morphogenesis as key regulators of hormonal homeostasis; and (v) elucidate the molecular mechanisms of the transition from juvenility to the adult phase in Prunus tree species

    Transcriptome-based Gene Networks for Systems-level Analysis of Plant Gene Functions

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    Present day genomic technologies are evolving at an unprecedented rate, allowing interrogation of cellular activities with increasing breadth and depth. However, we know very little about how the genome functions and what the identified genes do. The lack of functional annotations of genes greatly limits the post-analytical interpretation of new high throughput genomic datasets. For plant biologists, the problem is much severe. Less than 50% of all the identified genes in the model plant Arabidopsis thaliana, and only about 20% of all genes in the crop model Oryza sativa have some aspects of their functions assigned. Therefore, there is an urgent need to develop innovative methods to predict and expand on the currently available functional annotations of plant genes. With open-access catching the ‘pulse’ of modern day molecular research, an integration of the copious amount of transcriptome datasets allows rapid prediction of gene functions in specific biological contexts, which provide added evidence over traditional homology-based functional inference. The main goal of this dissertation was to develop data analysis strategies and tools broadly applicable in systems biology research. Two user friendly interactive web applications are presented: The Rice Regulatory Network (RRN) captures an abiotic-stress conditioned gene regulatory network designed to facilitate the identification of transcription factor targets during induction of various environmental stresses. The Arabidopsis Seed Active Network (SANe) is a transcriptional regulatory network that encapsulates various aspects of seed formation, including embryogenesis, endosperm development and seed-coat formation. Further, an edge-set enrichment analysis algorithm is proposed that uses network density as a parameter to estimate the gain or loss in correlation of pathways between two conditionally independent coexpression networks

    Historical perspectives on plant developmental biology

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    Network and biosignature analysis for the integration of transcriptomic and metabolomic data to characterize leaf senescence process in sunflower

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    In recent years, high throughput technologies have led to an increase of datasets from omics disciplines allowing the understanding of the complex regulatory networks associated with biological processes. Leaf senescence is a complex mechanism controlled by multiple genetic and environmental variables, which has a strong impact on crop yield. Transcription factors (TFs) are key proteins in the regulation of gene expression, regulating different signaling pathways; their function is crucial for triggering and/or regulating different aspects of the leaf senescence process. The study of TF interactions and their integration with metabolic profiles under different developmental conditions, especially for a non-model organism such as sunflower, will open new insights into the details of gene regulation of leaf senescence.Fil: Moschen, Sebastián Nicolás. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Higgins, Janet. The Genome Analysis Centre; Reino UnidoFil: Di Rienzo, Julio Alejandro. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; ArgentinaFil: Heinz, Ruth Amelia. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Fernández, Paula del Carmen. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
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