Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Arabidopsis plants exposed to combined heat and drought stress

ABSTRACT: One of the eminent opportunities afforded by modern genomic technologies is the potential to provide a mechanistic understanding of the processes by which genetic change translates to phenotypic variation and the resultant appearance of distinct physiological traits. Indeed much progress has been made in this area, particularly in biomedicine where functional genomic information can be used to determine the physiological state (e.g., diagnosis) and predict phenotypic outcome (e.g., patient survival). Until now, ecology has lacked an analogous approach where genomic information can be used to diagnose the presence of a given physiological state (e.g., stress response) and then predict likely phenotypic outcomes (e.g., stress tolerance, fitness). We demonstrate that a compendium of genomic signatures can be used to classify the plant abiotic stress phenotype in Arabidopsis according to the architecture of the transcriptome, and then be linked with gene coexpression network analysis to determine the underlying signaling pathways and ultimately the genes governing the phenotypic response. Here, we release microarray data from an expression profiling study where plants were exposed to heat and drought alone, and in combination with each other. A direct loop design with 6 biological replicates for control, heat, drought, and combined heat and drought was performed. A schematic describing the design is provide as supplementary information.

ORGANISM(S): Arabidopsis thaliana

SUBMITTER: Stan Wullschleger

PROVIDER: E-GEOD-9415 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Connecting genes, coexpression modules, and molecular signatures to environmental stress phenotypes in plants.

Weston David J DJ Gunter Lee E LE Rogers Alistair A Wullschleger Stan D SD

BMC systems biology 20080204

<h4>Background</h4>One of the eminent opportunities afforded by modern genomic technologies is the potential to provide a mechanistic understanding of the processes by which genetic change translates to phenotypic variation and the resultant appearance of distinct physiological traits. Indeed much progress has been made in this area, particularly in biomedicine where functional genomic information can be used to determine the physiological state (e.g., diagnosis) and predict phenotypic outcome ( ...[more]

PMID: 18248680

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Project description:Small RNAs (21-24 nt) are pivotal regulators of gene expression that guide both transcriptional and post-transcriptional silencing mechanisms in diverse eukaryotes, including most if not all plants. MicroRNAs (miRNAs) and short interfering RNAs (siRNAs) are the two major types, both of which have a demonstrated and important role in plant development, stress responses and pathogen resistance. In this work, we used a deep sequencing approach (Sequencing-By-Synthesis, or SBS) to develop sequence resources of small RNAs from different maize tissues (including leaves, ears and tassels) collected from wild-type plants of the B73 variety. The high depth of the resulting datasets enabled us to examine in detail critical small RNA features as size distribution, tissue-specific regulation and sequence conservation between different organs in this species. We also developed database resources and a dedicated website (http://smallrna.udel.edu/) with computational tools for allowing other users to identify new miRNAs or siRNAs involved in specific regulatory pathways, verify the degree of conservation of these sequences in other plant species and map small RNAs on genes or larger regions of the maize genome under study. Small RNA libraries were derived from leaves, ears and tassels of maize variety B73 (wild-type). Plants were grown in a flood irrigated plot at the University of Arizona (Tucson, AZ, USA) in 2007 and organs were pooled from several plants for each library. Young leaves were collected from 6-weeks-old seedlings. Post-meiotic immature ears were harvested from 10- and 11-week old plants while pre-meiotic tassels were collected from 8-week old plants. Total RNA was isolated using the Plant RNA Purification Reagent (Invitrogen) and submitted to Illumina (Hayward, CA, http://www.illumina.com) for small RNA library construction using approaches described in (Lu et al., 2007) with minor modifications. The small RNA libraries were sequenced with the Sequencing-By-Synthesis (SBS) technology by Illumina. PERL scripts were designed to remove the adapter sequences and determine the abundance of each distinct small RNA. We thank Lyudmila Sidorenko and Vicki Chandler for providing the plant material and Kan Nobuta for assistance with the computational methods.

Project description:In this study expression levels of 732 genes were analyzed for European maize (Zea mays L.) inbred lines (4 Flint and 5 Dent) and nine corresponding hybrids by microarray analysis. The selection of the 732 genes was based on a previous study (Thiemann et al., Theor Appl Genet 2010, 120:401-413), which sequences were derived from the 46k microarray (platform GPL6438) (University of Arizona, USA). 558 of the 732 genes represented on the microarray were differentially expressed between the original 21 parental inbred lines and were correlated with at least one of the three characteristics MPH (mid-parent heterosis) and/or HP (hybrid performance) of the trait GY (grain yield) and/or HP of the trait grain dry matter content. Some of those correlated genes show overlapping correlations. The residual 174 non-correlated genes belong to the top 6 biological processes that were found to be enriched among the HP for GY-correlated genes (Thiemann et al., Theor Appl Genet 2010, 120:401M-bM-^@M-^S413). The aim of this study was the identification of the hybrid expression pattern of the subset of genes, which mid-parental expression levels were shown to be correlated with MPH for GY or showed no correlation. For the analysis total RNA of 7-day old seedlings was extracted and amino-allyl-labeled RNA was synthesized. The microarrays were scanned (AppliedPrecision ArrayWorx Scanner, Applied Precision Inc., USA) and data were evaluated using the Software GenePix Pro 4.0 (Molecular Devices, Sunnyvale, USA). Hybridizations were conducted between each pair of parental inbred lines and its corresponding hybrids. In total 4 biological replicates per genotype were analyzed. As a result 119 (22.9 %) of the 519 MPH for GY or non-correlated genes showed differential expression in at least one of the nine inbred-hybrid comparisons. These differentially expressed genes were further analyzed for hybrid expression, resulting in a mainly additive expression. Of all differential expression, additive expression of 86.21 % (with 13.79 % non-additive) of the MPH-correlated genes, and a slightly smaller contingent of 79.66 % (with 20.34 % non-additive) of the non-correlated genes was measured. Four biological replicates of each of the nine parental inbred lines (4 Flint: F012, F039, F047, L024; 5 Dent: S028, S036, P024, P033, P048) and of the nine corresponding hybrids (P033xF047, P048xF047, P024xF039, S036xL024, S028xL024, S028xF012, S028xF039, P024xF012, F012xF039) were grown under controlled conditions (25 M-BM-0C 16 h day, 21 M-BM-0C 8 h night, 70 % air humidity) for seven days in a climate chamber. Whole seedlings were frozen in liquid nitrogen and were finely pounded. Total RNA was extracted and then precipitated (4 M LiCl). Residual genomic DNA was hydrolyzed with DNaseI (Fermentas, St. Leon-Rot, Germany) and purified with the M-bM-^@M-^\NucleoSpin RNA Clean-up KitM-bM-^@M-^] (Macherey-Nagel, DM-CM-<ren, Germany). For first strand cDNA synthesis, 5 M-BM-5g of total RNA and the Superscript II from Invitrogen (Life Technologies, Carlsbad, USA) were used. Second strand synthesis was performed using DNA Polymerase I and RNase H followed by a 5 min incubation step of T4 DNA Polymerase (Fermentas, St. Leon-Rot). Residual RNA was hydrolyzed with RNase A. In-vitro transcription was performed with the T7 RNA Polymerase (Fermentas, St. Leon-Rot, Germany) for 4 h to incorporate aminoallyl-labeled UTPs (Fermentas, St. Leon-Rot, Germany). Finally, residual DNA was degraded with DNase I (Fermentas). Synthesized aaRNA was coupled with fluorescence dyes Cy3 or Cy5 (GE Healthcare, Chalfont St. Giles, UK). The RNeasy MinElute Kit (Qiagen, Hilden, Germany) was used for purification and removal of unbound dye. In total 105 hybridizations were realized. The dye used for each biological replicate of each genotype was alternated to reduce systematic bias.

Project description:Arabidopsis thaliana plants (ecotype Landsberg erecta) were grown at 20ËC constant temperature, 8 hr/16 hr Light/Dark photoperiod at 50-60% ambient humidity, for 8 to 9 weeks. Short day conditions prevented the onset of flowering and the plants were thus maintained in growth stage 1 (leaf production) with 13 to 15 rosette leaves larger than 1mm (stage 1.13 to 1.14). Diamondback moth (DBM, Plutella xylostella) larvae were maintained on cabbage (Brassica oleracea) plants in a climate-controlled room at 25ÂºC, 12 hr photoperiod with 50%-60% relative humidity. Two days before exposing A. thaliana plants to herbivore treatment, plants were transferred to a climate-controlled room (22ÂºC, 50-60% humidity, 12 hr photoperiod). For insect treatment, seven Diamondback moth (DBM, Plutella xylostella) larvae (third to fifth instars) were placed on a group of four or five plants until time of harvest, for each time point separately. All rosette leaves were harvested at 1h, 4h, 12h, and 24h after onset of continuous herbivory and flash frozen in liquid nitrogen. Control plants were maintained under the same conditions and harvested in parallel. Keywords: time course, stress response, herbivory response For each time point (1h, 4h, 12h, and 24h) two biological replicates (DBM treatment) were performed. Control plants were harvested in parallel. Total RNA from each sample was used for two labelling reactions using dye-flips (Cy5 or Cy3) and labelled cDNA from treatment and control plants were co-hybridized. Thus, for each time-point four replicates were analyzed each comparing treatment with the corresponding control (rep1 and rep2 are dye-flips of biological replicate 1, and rep3 and rep4 are dye-flips of biological replicate 2). For background correction, we defined the mean of the lowest 10% of spot intensities from a particular subgrid as the background for that subgrid. This mean was subtracted from each spot in the subgrid. Signal intensities that did not exceed the background plus 3 standard deviations thereof were defined as not detectable and were excluded from further analyses. We normalized using loess curves thus generating log2 transformed expression ratios comparing DBM treatment with control. These ratios are given in the VALUE columns of each array.

Project description:Maize is a globally important food and feed crop, and a low-phosphate (Pi) supply in the soil frequently limits maize yield in many areas. MicroRNAs (miRNAs) play important roles in the development and adaptation of plants to the environment. In this study, the spatio-temporal miRNA transcript profiling of the maize inbred line Q319 root and leaf in response to low Pi was analyzed with high-throughput sequencing technologies, and the expression patterns of certain target genes were detected by real-time RT-PCR. Complex small RNA populations were detected after low-Pi culture and displayed different patterns in the root and leaf. miRNAs identified as responding to Pi deficiency can be grouped into ‘early’ miRNAs that respond rapidly, and often non-specifically, to Pi deficiency, and ‘late’ miRNAs that alter the morphology, physiology or metabolism of plants upon prolonged Pi deficiency. The miR827-Nitrogen limitation adaptation (NLA)-mediated post-transcriptional pathway was conserved in response to Pi availability of maize, but the miR399-mediated post-transcriptional pathway was different from Arabidopsis. Abiotic stress-related miRNAs engaged in interactions of different signaling and/or metabolic pathways. Auxin-related miRNAs (zma-miR393, zma-miR160a/b/c, zma-miR160d/e/g, zma-miR167a/b/c/d and zma-miR164a/b/c/d/g) and their targets play important roles in promoting primary root growth, inhibiting lateral root development and retarding upland growth of maize when subjected to low Pi. The changes in expression of miRNAs and their target genes suggest that the miRNA regulation/alterations compose an important mechanism in the adaptation of maize to a low-Pi environment; certain miRNAs participate in root architecture modification via the regulation of auxin signaling. A complex regulatory mechanism of miRNAs in response to a low-Pi environment exists in maize, revealing obvious differences from that in Arabidopsis. Maize (Zea mays L.) inbred line Q319 was used in this study. Seeds of the maize inbred line Q319 were surface sterilized and held at 28°C in darkness. Seedlings (4 days old) were transferred to a sufficient phosphate (SP, 1,000 μM KH2PO4) solution (Ca(NO3)2.4H2O 2 mM, NH4NO3 1.25 mM, KCl 0.1 mM, K2SO4 0.65 mM, MgSO4 0.65 mM, H3BO3 10.0 mM, (NH4)6Mo7O24 0.5 mM, MnSO4 1.0 mM, CuSO4.5H2O 0.1 mM, ZnSO4.7H2O 1.0 mM, Fe-EDTA 0.1 mM), allowed to grow for 4 days (plants with 2–3 leaves). After 2-3 days of re-culturing in SP nutrient solutions, half of the seedlings were transplanted into a low phosphate (LP, same composition as the SP solution, except that 5 μM KH2PO4 and 1 mM KH2PO4 were replaced with 1 mM KCl) nutrient solution. The plants were grown under a 32°C/25°C (day/night) temperature regime at a photon flux density (PFD) of 700 μmol m-2 s-1 with a 14 h/10 h light/dark cycle in a greenhouse with approximately 65% relative humidity. The roots and leaves were then harvested at 0, 1, 2, 4, 8 days and 8 days and cultured in SP solution (as a normal growth control) for small RNA analysis. The samples were frozen in liquid nitrogen immediately and stored at -80℃ for further analysis. Each biological repeat contains segments from 15~20 plants. Total RNA was extracted as previously described in Molecular Cloning (Sambrook and Russell David, 1989) and was then subjected to two additional chloroform washes prior to nucleic acid precipitation. The small RNA digitalization analysis based on HiSeq high-throughput sequencing takes the SBS-sequencing by synthesis. Then the 50nt sequence tags from HiSeq sequencing will go through the data cleaning first, which includes getting rid of the low quality tags and several kinds of contaminants from the 50nt tags. Length distribution of clean tags are then summarized. Afterwards, the standard bioinformatics analysis will annotate the clean tags into different categories and take those which can not be annotated to any category to predict the novel miRNA and base edit of potential known miRNA. Compare the known miRNA expression between two samples to find out the differentially expressed miRNA. The procedures are shown as below: (1)Normalize the expression of miRNA in two samples (control and treatment) to get the expression of transcript per million (TPM). Normalization formula: Normalized expression = Actual miRNA count/Total count of clean reads*1000000 (2)Calculate fold-change and P-value from the normalized expression. Then generate the log2ratio plot and scatter plot.

Dataset Information

Arabidopsis plants exposed to combined heat and drought stress

Publications

Connecting genes, coexpression modules, and molecular signatures to environmental stress phenotypes in plants.

Similar Datasets

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