Field study maize BX
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB36599 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR5336803_1.fastq.gz | Fastqsanger.gz | |||
| ERR5336803_2.fastq.gz | Fastqsanger.gz | |||
| ERR5337233_1.fastq.gz | Fastqsanger.gz | |||
| ERR5337233_2.fastq.gz | Fastqsanger.gz |
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Project description:Gray leaf spot (GLS) disease of maize is caused by the fungus Cercospora zeina in African countries, such as South Africa. The plant material was from maize inbred line B73-QTL, which was introgressed with a QTL region for resistance to GLS from the maize inbred line CML444 (Berger et al (2014) BMC Genetics 15 60 www.biomedcentral.com/1471-2156/15/60 ). This QTL was named 10G2_GLS and 10H_GLS from two field trials in KwaZulu-Natal province, South Africa in that study. B73-QTL plants were planted in the field, and subjected to natural infection with C. zeina. This was the same field trial as B73 plants that were sampled for RNAseq and the data reported in Swart et al (2017) Mol Plant Microbe Interact 30 710-724 (2017)(GSE94442). Samples were collected from lower leaves with moderate GLS lesions and younger upper leaves of the same B73-QTL plants with very few immature GLS lesions. The first aim of the experiment was to compare the maize transcriptomes during C.zeina challenge between B73 (from GSE94442 data) and B73-QTL plants (this study). The second aim was to identify novel transcripts expressed from the QTL region, which may underlie the quantitative disease resistance to GLS. The third aim was to identify C. zeina genes expressed in planta during infection.
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Project description:These experiments were to investigate changes in gene expression associated with maize competition for light when grown at double normal population density or under 60% shaded conditions as opposed to when maize is grown under normal field conditions.
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Project description:These experiments were to investigate changes in gene expression associated with maize competition for light when grown at double normal population density or under 60% shaded conditions as opposed to when maize is grown under normal field conditions. Three biological replicates (collected from separate field plots) comprised of pooled samples of 4 plants from each treatment were hybridized in a rolling circle dye swap hybridization screen.
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Project description:In rice, gene expression profiling under different stresses have been carried out earlier through microarrays and SAGE (Kawasaki et al., 2001; Rabbani et al., 2003,;. Yazaki et al., 2003, 2004; Walia et al., 2005; Zhou et al., 2005; Jiao et al., 2005; Zhou, 2007; Wang, et al., 2007)). The results reported so far were mostly derived from different stress treatments, array formats, species, tissue types, and time courses, which make it difficult for direct comparison among studies. Also, most of the stress experiments on expression profiles were conducted under laboratory, growth chamber or field grown plants subjected to stress in laboratory conditions, usually by inducing stress with exogenous compounds such as abscisic acid (ABA) or gibberellin (GA) genes (Yazaki et al., 2003, 2004; Rabbani et al., 2003), salt (Kawasaki et al., 2001; Rabbani et al., 2003; Walia et al., 2005), organ specific gene expression under high salinity (Jiao et al., 2005) and drought (Zhou et al., 2007), comparison with different cultivars (Wang et al., 2007) and other environmental stresses such as cold and drought (Rabbani et al., 2003; Zhou et al., 2005). However, such laboratory, growth chamber grown plants or field grown plants subjected to stress under laboratory conditions significantly differ from the field stress conditions and therefore the resultant plant response may not truly represent the actual stress conditions prevailing on field. This has been extensively reviewed by Mittler, 2006 and the need for utilizing data from multiple stress experiments for developing plants resistant to stress has been focused. The review also focuses on evaluating farmers experiences in stress management and kinds of stress that a plant is subjected prior to taking up research on stress resistances has been of significant importance. In the present study, to bridge the gap between the available data on drought stress and the gene regulation under field drought conditions has been paid attention. The outcome of this data will give new leads for breeders to design strategies to develop plants resistant to drought without much loss in yield. In the present study experiments were conducted under different field capacities using a rainout shelter to minimizing the effects of drought induction due to rains. The microarray analysis is thus expected to throw light on stress responsive gene expression in field drought conditions. Till now, to our knowledge there have been no reports on gene expression in rice under field drought conditions. Further, there is no data available on gene expression profiling during various stages of plant growth in leaf and panicle tissues under different levels of water stress. Here, we have focused on generating stress responsive gene (SRG) expression profiles in field drought conditions through the entire life cycle of rice plant. Optimal drought simulation was achieved by conducting a drought stress experiment and validated by a series of dry runs. The main reason for evaluating gene expression under drought in field condition is as drought itself is not limited to water stress but various other factors, such as heat, humidity, hot winds, and long day lengths effect the gene regulation. All these are likely to trigger common pathways that are also a part of drought stress response and therefore significantly affect the expression profiles. In the present study, field drought stress was initiated from 31 days after germination and transplantation to the field at 100%, 60%, 40% and 15% field capacities designated as A1, A2, A3, and A4. It took 7 days for the onset of the actual drought for the experimental plots to reach to their designated field capacities from 100% FC. Samples were collected from 7 days after drought stress to 33 days after drought stress to evaluate different drought stress regimes based on the developmental stages of the plant. At all the tested stress levels the data points were Hierarchically grouped and clustered sets of genes were examined and an approximate number of clusters to be formed were estimated. Finding a group of genes showing a similar pattern of gene expression by means of expression data from microarray analysis is the basis for identification of genes and pathways controlling a specific trait. We have followed unsupervised classification and clustered the genes hierarchically after normalizing expression data to obtain a set of co-regulated genes. Analysis of data revealed that there are at least 3 to 4 clusters which show differential regulation under each stress regime. The annotated genes falling in these clusters interestingly include a number of novel genes from N22 library along with some known candidate genes for drought tolerance which were earlier identified in our study (Markandeya et al., 2007). Expression pattern of these genes from 7 days after drought stress to 33 days after drought stress with their fold changes were evaluated in the present study. In particular, it is observed that many genes of unknown function are also co-regulated in an interesting pattern along with known genes.
2011-11-27 | GSE31974 | GEO