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

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

Differential representation of sunflower ESTs in enriched organ-specific cDNA libraries in a small scale sequencing project

BACKGROUND: Subtractive hybridization methods are valuable tools for identifying differentially regulated genes in a given tissue avoiding redundant sequencing of clones representing the same expressed genes, maximizing detection of low abundant transcripts and thus, affecting the efficiency and cost effectiveness of small scale cDNA sequencing projects aimed to the specific identification of useful genes for breeding purposes. The objective of this work is to evaluate alternative strategies to high-throughput sequencing projects for the identification of novel genes differentially expressed in sunflower as a source of organ-specific genetic markers that can be functionally associated to important traits. RESULTS: Differential organ-specific ESTs were generated from leaf, stem, root and flower bud at two developmental stages (R1 and R4). The use of different sources of RNA as tester and driver cDNA for the construction of differential libraries was evaluated as a tool for detection of rare or low abundant transcripts. Organ-specificity ranged from 75 to 100% of non-redundant sequences in the different cDNA libraries. Sequence redundancy varied according to the target and driver cDNA used in each case. The R4 flower cDNA library was the less redundant library with 62% of unique sequences. Out of a total of 919 sequences that were edited and annotated, 318 were non-redundant sequences. Comparison against sequences in public databases showed that 60% of non-redundant sequences showed significant similarity to known sequences. The number of predicted novel genes varied among the different cDNA libraries, ranging from 56% in the R4 flower to 16 % in the R1 flower bud library. Comparison with sunflower ESTs on public databases showed that 197 of non-redundant sequences (60%) did not exhibit significant similarity to previously reported sunflower ESTs. This approach helped to successfully isolate a significant number of new reported sequences putatively related to responses to important agronomic traits and key regulatory and physiological genes. CONCLUSIONS: The application of suppressed subtracted hybridization technology not only enabled the cost effective isolation of differentially expressed sequences but it also allowed the identification of novel sequences in sunflower from a relative small number of analyzed sequences when compared to major sequencing projects

Sunflower Leaf Senescence: A Complex Genetic Process with Economic Impact on Crop Production

Leaf senescence is a complex process controlled by multiple genetic and environmental variables. In different crops, a delay in leaf senescence has an important impact on grain yield trough the maintenance of the photosynthetic leaf area during the reproductive stage. In sunflower (Helianthus annuus L.), the fourth largest oil crop worldwide, senescence reduces the capacity of plants to maintain their green leaf area for longer periods, especially during the grain filling phase, leading to important economic losses

First report of Diaporthe ambigua causing Phomopsis stem canker on sunflower in Argentina

Phomopsis stem canker, a disease emerging on sunflower (Helianthus annuus) in response to environmental change, has already been described in Argentina with Diaporthe helianthi as the main aetiological agent (Ridao et al., 1994). During a survey (2020-2021) in the Argentinian sunflower-growing region of Pampeane, 208 sunflower plants with canker symptoms were collected from 75 cultivated fields (Fig. 1). Necrotic triangular dark leaf lesions invaded the stem, forming a conspicuous brown to black canker at the corresponding nodes.EEA AnguilFil: Colombo, Denis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentina. Universidad Nacional de La Pampa. Facultad de Agronomía; ArgentinaFil: Corro Molas, Andres. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil. Agencia de Extensión Rural General Pico; ArgentinaFil: Paniego, Norma Beatriz. nstituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaFil: Comerio, Ricardo Mario. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentin

Transcriptomic identification of candidate genes involved in sunflower responses to chilling and salt stresses based on cDNA microarray analysis

<p>Abstract</p> <p>Background</p> <p>Considering that sunflower production is expanding to arid regions, tolerance to abiotic stresses as drought, low temperatures and salinity arises as one of the main constrains nowadays. Differential organ-specific sunflower ESTs (expressed sequence tags) were previously generated by a subtractive hybridization method that included a considerable number of putative abiotic stress associated sequences. The objective of this work is to analyze concerted gene expression profiles of organ-specific ESTs by fluorescence microarray assay, in response to high sodium chloride concentration and chilling treatments with the aim to identify and follow up candidate genes for early responses to abiotic stress in sunflower.</p> <p>Results</p> <p>Abiotic-related expressed genes were the target of this characterization through a gene expression analysis using an organ-specific cDNA fluorescence microarray approach in response to high salinity and low temperatures. The experiment included three independent replicates from leaf samples. We analyzed 317 unigenes previously isolated from differential organ-specific cDNA libraries from leaf, stem and flower at R1 and R4 developmental stage. A statistical analysis based on mean comparison by ANOVA and ordination by Principal Component Analysis allowed the detection of 80 candidate genes for either salinity and/or chilling stresses. Out of them, 50 genes were up or down regulated under both stresses, supporting common regulatory mechanisms and general responses to chilling and salinity. Interestingly 15 and 12 sequences were up regulated or down regulated specifically in one stress but not in the other, respectively. These genes are potentially involved in different regulatory mechanisms including transcription/translation/protein degradation/protein folding/ROS production or ROS-scavenging. Differential gene expression patterns were confirmed by qRT-PCR for 12.5% of the microarray candidate sequences.</p> <p>Conclusion</p> <p>Eighty genes isolated from organ-specific cDNA libraries were identified as candidate genes for sunflower early response to low temperatures and salinity. Microarray profiling of chilling and NaCl-treated sunflower leaves revealed dynamic changes in transcript abundance, including transcription factors, defense/stress related proteins, and effectors of homeostasis, all of which highlight the complexity of both stress responses. This study not only allowed the identification of common transcriptional changes to both stress conditions but also lead to the detection of stress-specific genes not previously reported in sunflower. This is the first organ-specific cDNA fluorescence microarray study addressing a simultaneous evaluation of concerted transcriptional changes in response to chilling and salinity stress in cultivated sunflower.</p

Co-expression networks in sunflower : harnessing the power of multi-study transcriptomic public data to identify and categorize candidate genes for fungal resistance

Fungal plant diseases are a major threat to food security worldwide. Current efforts to identify and list loci involved in different biological processes are more complicated than originally thought, even when complete genome assemblies are available. Despite numerous experimental and computational efforts to characterize gene functions in plants, about ~40% of protein-coding genes in the model plant Arabidopsis thaliana L. are still not categorized in the Gene Ontology (GO) Biological Process (BP) annotation. In non-model organisms, such as sunflower (Helianthus annuus L.), the number of BP term annotations is far fewer, ~22%. In the current study, we performed gene co-expression network analysis using eight terabytes of public transcriptome datasets and expression-based functional prediction to categorize and identify loci involved in the response to fungal pathogens. We were able to construct a reference gene network of healthy green tissue (GreenGCN) and a gene network of healthy and stressed root tissues (RootGCN). Both networks achieved robust, high-quality scores on the metrics of guilt-by-association and selective constraints versus gene connectivity. We were able to identify eight modules enriched in defense functions, of which two out of the three modules in the RootGCN were also conserved in the GreenGCN, suggesting similar defense-related expression patterns. We identified 16 WRKY genes involved in defense related functions and 65 previously uncharacterized loci now linked to defense response. In addition, we identified and classified 122 loci previously identified within QTLs or near candidate loci reported in GWAS studies of disease resistance in sunflower linked to defense response. All in all, we have implemented a valuable strategy to better describe genes within specific biological processes.Instituto de BiotecnologíaFil: Ribone, Andrés Ignacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Ribone, Andrés Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Fass, Mónica Irina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Fass, Mónica Irina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gonzalez, Sergio Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnologia y Biología Molecular; ArgentinaFil: Gonzalez, Sergio Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lia, Veronica Viviana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Lia, Veronica Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Paniego, Norma Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rivarola, Maximo Lisandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Rivarola, Maximo Lisandro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

ATGC transcriptomics : a web-based application to integrate, explore and analyze de novo transcriptomic data

Background: In the last years, applications based on massively parallelized RNA sequencing (RNA-seq) have become valuable approaches for studying non-model species, e.g., without a fully sequenced genome. RNA-seq is a useful tool for detecting novel transcripts and genetic variations and for evaluating differential gene expression by digital measurements. The large and complex datasets resulting from functional genomic experiments represent a challenge in data processing, management, and analysis. This problem is especially significant for small research groups working with non-model species. Results: We developed a web-based application, called ATGC transcriptomics, with a flexible and adaptable interface that allows users to work with new generation sequencing (NGS) transcriptomic analysis results using an ontology-driven database. This new application simplifies data exploration, visualization, and integration for a better comprehension of the results. Conclusions: ATGC transcriptomics provides access to non-expert computer users and small research groups to a scalable storage option and simple data integration, including database administration and management. The software is freely available under the terms of GNU public license at http://atgcinta.sourceforge.net.Inst. de BiotecnologíaFil: Gonzalez, Sergio Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaFil: Clavijo, Bernardo. Norwich Research Park. Earlham Institute; Reino UnidoFil: Rivarola, Maximo Lisandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Moreno, Patricio. Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Ingeniería Biomédica; ArgentinaFil: Fernández, Paula. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; ArgentinaFil: Dopazo, Joaquín Centro de Investigación Príncipe Felipe. Computational Genomics Department; EspañaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Insights into functional classification via gene co-expression networks in sunflower using public transcriptomic datasets

We present the first preliminary sunflower gene co-expression network using public transcriptome data in Helianthus annuus and show its utility in identifying and classifying uncharacterized genes involved in stress response. The locus HanXRQChr09g0248321 was identified and linked to several WRKY transcription factors in an enriched “stressed-response” module. Moreover, the homologue in Arabidopsis thaliana was shown to be differentially expressed in multiple “stress” conditions. We present our work and validate our methodology to existing knowledge and show its capability to identify/rank new candidates for crop breeding programs. Our future goal is to link genetic variation with gene networks to understand phenotypic variability in sunflower stress responses.Sociedad Argentina de Informática e Investigación Operativ