Zea mays
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA325825 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR3671460_1.fastq.gz | Fastqsanger.gz | |||
| SRR3671460_2.fastq.gz | Fastqsanger.gz | |||
| SRR3671470.fastq.gz | Fastqsanger.gz | |||
| SRR3671461_1.fastq.gz | Fastqsanger.gz | |||
| SRR3671461_2.fastq.gz | Fastqsanger.gz |
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Project description:Weed presence altered biotic stress and light signalling in maize even when weeds were removed early in the critical weed-free period
2020-04-03 | E-GEOD-83411 | ExpressionAtlas
Project description:Purpose: This study is designed to identify genes and processes that are differentially regulated in corn when it is grown with or without weeds through the entire critical weed free period (to V8) or when weeds were removed early in the critical weed free period (at V4) and the plants were allowed to recover until V8. Methods: Corn was grown as described above in field plots near Brookings SD in 2007 and 2008 and RNA was extracted from the top-most leaf tips from four plants per treatment plot. Unidirectional cDNA illumina sequencing libraries were constructed for each sample (pooled leaf tips from the given plot), and were sequenced (some samples were paired end sequenced and some were single end sequenced - all 100 bases for PE and SE reads), quality trimmed, and analyzed using the Tuxedo suite of programs for SE reads of the forward read libraries for each sample. Results: We identified a small number of genes that were differentially expressed in both years. More importantly, gene set enrichment analysis of the data determined that weeds, when present through the critical weed free period impacted phytochrome signaling, defense responses, photosynthetic processes, oxidative stress responses, and various hormone signaling processes. When weeds were removed at V4 and the plants allowed to recover until V8, the weeds still imprinted impacts on phytochrome signaling, oxidative stress, and defense responses. Thus, it appears that weeds presence through the early portion of the critical weed free period, even after removal, induced processes that reduce corn growth and yield that lasted at least through V8. Conclusions: This study represents the first investigation of the impact of the lasting effects of weeds during the early critical weed free period on the transcriptome of corn, and provides additional data on the impact of weeds through the critical weed free period that augments and confirms much of what was observed in similar microarray studies.
2021-03-09 | GSE83411 | GEO
Project description:Research conducted, including the rationale: Weeds reduce yield in soybeans through incompletely defined mechanisms. The effects of weeds on the soybean transcriptome were evaluated in field conditions during four separate gR1.fastqing seasons. Methods: RNASeq data were collected from 6 biological samples of soybeans gR1.fastqing with or without weeds. Weed species and the methods to maintain weed free controls varied between years to mitigate treatment effects and to allow detection of general soybeans weed responses. Key results: Soybean plants were not visibly nutrient or water stressed. We identified 55 consistently down-regulated genes in weedy plots. Many of the down-regulated genes were heat shock genes. Fourteen genes were consistently up-regulated. Several transcription factors including a PHYTOCHROME INTERACTING FACTOR 3-like gene (PIF3) were included among the up-regulated genes. Gene set enrichment analysis indicated roles for increased oxidative stress and jasmonic acid signaling responses during weed stress. Main conclusion: The relationship of this weed-induced PIF3 gene to genes involved in shade avoidance responses in arabidopsis provide evidence that this gene may be important in the response of soybean to weeds. These results suggest the weed-induced PIF3 gene will be a target for manipulating weed tolerance in soybean. Samples were collected from two treatments ("Control" and "Weedy") with six biological replicates (2008, 2009, and twop each for 2010 and 2011) for each treatment.
2014-07-30 | E-GEOD-59875 | biostudies-arrayexpress
Project description:Research conducted, including the rationale: Weeds reduce yield in soybeans through incompletely defined mechanisms. The effects of weeds on the soybean transcriptome were evaluated in field conditions during four separate gR1.fastqing seasons. Methods: RNASeq data were collected from 6 biological samples of soybeans gR1.fastqing with or without weeds. Weed species and the methods to maintain weed free controls varied between years to mitigate treatment effects and to allow detection of general soybeans weed responses. Key results: Soybean plants were not visibly nutrient or water stressed. We identified 55 consistently down-regulated genes in weedy plots. Many of the down-regulated genes were heat shock genes. Fourteen genes were consistently up-regulated. Several transcription factors including a PHYTOCHROME INTERACTING FACTOR 3-like gene (PIF3) were included among the up-regulated genes. Gene set enrichment analysis indicated roles for increased oxidative stress and jasmonic acid signaling responses during weed stress. Main conclusion: The relationship of this weed-induced PIF3 gene to genes involved in shade avoidance responses in arabidopsis provide evidence that this gene may be important in the response of soybean to weeds. These results suggest the weed-induced PIF3 gene will be a target for manipulating weed tolerance in soybean.
2021-03-23 | GSE59875 | GEO
Project description:We conducted field surveys to detect the population density of the most important invasive weed species and their associated virus vectoring aphids in crops grown under high input (HIF) vs low-input (LIF) field conditions, with and without fertilizers and pesticides. The most frequent invasive weed species were Stenactis annua, Erigeron canadensis and Solidago canadensis. These species were hosts predominantly for the aphids Brachycaudus helichrysi and Aulacorthum solani in both management systems. The 13% higher coverage of S. annua under LIF conditions resulted in a 30% higher B. helichrysi abundance and ~85% higher A. solani abundance compared with HIF conditions. To reveal virus infection in crop plants and invasive weeds high-throughput sequencing of small RNAs were carried out. Bioinformatics analysis of the results detected the presence of 16 important plant viruses, but not resulting strikingly different pattern under LIF and HIF. This could suggest that invasive weeds serves as a virus reservoir both under low and high input management systems. The lake of any management increases virus vector aphids abundances, their presence has a great impact on the viromes of the crops.
2020-06-03 | GSE132755 | GEO
Project description:This study was designed to identify changes in gene expression when corn was placed under various related stresses including being grown with a competing weed (canola) to the V4 or V8 stage, or when 40% shade cloth was present to the V4 or V8 stage, or under low nitrogen (no added nitrogen fertilizer), or under weed/shade free fertilized control conditions. In all 5 treatments and the control, samples were harvested at V8. Mechanisms underlying early season weed stress on crop growth are not well described. Corn vegetative growth and development, yield, and gene expression response to nitrogen (N), light (40% shade), and weed stresses were compared with the response of nonstressed plants. Vegetative parameters, including leaf area and biomass, were measured from V2 toV12 corn stages. Transcriptome (2008) or quantitative Polymerase Chain Reaction (q PCR) (2008/09) analyses examined differential gene expression in stressed versus nonstressed corn at V8. Vegetative parameters were impacted minimally by N stress although grain yield was 40% lower. Shade, present until V2, reduced biomass and leaf area > 50% at V2 and, at V12, recovering plants remained smaller than nonstressed plants. Grain yields of shade-stressed plants were similar to nonstressed controls, unless shade remained until V8. Growth and yield reductions due to weed stress in 2008 were observed when weeds remained until V6. In 2009, weed stress at V2 reduced vegetative growth, and weed stress until V4 or later reduced yield. Principle component analysis of differentially expressed genes indicated that shade and weed stress had more similar gene expression patterns to each other than to nonstressed or low N stressed tissues. Weed-stressed corn had 630 differentially expressed genes compared with the nonstressed control. Of these genes, 259 differed and 82 were shared with shade-stressed plants. Corn grown in N-stressed conditions shared 252 differentially expressed genes with weed-stressed plants. Ontologies associated with light/photosynthesis, energy conversion, and signaling were down-regulated in response to all three stresses. Although shade and weed stress clustered most tightly together, only three ontologies were shared by these stresses, O-methyltransferase activity (lignification processes), Poly U binding activity (post-transcriptional gene regulation), and stomatal movement. Based on both morphologic and genomic observations, results suggest that shade, N, and weed stresses to corn are regulated by both different and overlapping mechanisms. three biological replicates for each treatment and the control were collected and the resulting labeled cDNA was hybridized to the 46,000-element maize microarray chip developed by the University of Arizona using their protocol (International Microarray Workshop Handbook, 2009Gardiner et al. 2005). The hybridization scheme was a dual hybridization using a rolling circle balanced dye swap design. Thus we had thre biological replicates for each growth condition amd two technical replicates for each biological sample.
2011-05-09 | E-GEOD-29132 | biostudies-arrayexpress
Project description:This study was designed to identify changes in gene expression when corn was placed under various related stresses including being grown with a competing weed (canola) to the V4 or V8 stage, or when 40% shade cloth was present to the V4 or V8 stage, or under low nitrogen (no added nitrogen fertilizer), or under weed/shade free fertilized control conditions. In all 5 treatments and the control, samples were harvested at V8. Mechanisms underlying early season weed stress on crop growth are not well described. Corn vegetative growth and development, yield, and gene expression response to nitrogen (N), light (40% shade), and weed stresses were compared with the response of nonstressed plants. Vegetative parameters, including leaf area and biomass, were measured from V2 toV12 corn stages. Transcriptome (2008) or quantitative Polymerase Chain Reaction (q PCR) (2008/09) analyses examined differential gene expression in stressed versus nonstressed corn at V8. Vegetative parameters were impacted minimally by N stress although grain yield was 40% lower. Shade, present until V2, reduced biomass and leaf area > 50% at V2 and, at V12, recovering plants remained smaller than nonstressed plants. Grain yields of shade-stressed plants were similar to nonstressed controls, unless shade remained until V8. Growth and yield reductions due to weed stress in 2008 were observed when weeds remained until V6. In 2009, weed stress at V2 reduced vegetative growth, and weed stress until V4 or later reduced yield. Principle component analysis of differentially expressed genes indicated that shade and weed stress had more similar gene expression patterns to each other than to nonstressed or low N stressed tissues. Weed-stressed corn had 630 differentially expressed genes compared with the nonstressed control. Of these genes, 259 differed and 82 were shared with shade-stressed plants. Corn grown in N-stressed conditions shared 252 differentially expressed genes with weed-stressed plants. Ontologies associated with light/photosynthesis, energy conversion, and signaling were down-regulated in response to all three stresses. Although shade and weed stress clustered most tightly together, only three ontologies were shared by these stresses, O-methyltransferase activity (lignification processes), Poly U binding activity (post-transcriptional gene regulation), and stomatal movement. Based on both morphologic and genomic observations, results suggest that shade, N, and weed stresses to corn are regulated by both different and overlapping mechanisms.
2011-05-09 | GSE29132 | GEO
Project description:During a proof-of-concept study, virome of millet, grown as weed was determined by small RNA HTS. As a result, from the pools of 20 randomly collected millet samples collected at two locations, we identified the presence of three viruses, two of them first time in Hungary. Based on our results we could only suspect that these viruses: wheat streak mosaic virus (WSMV), barley stripe mosaic virus (BYSMV) and barley virus G (BVG) could have been overwintered in millet or other monocotyledonous weeds growing at these fields. As a follow-up research, in the summer of 2021, we collected symptomatic leaves of several monocotyledonous plants at the same fields. This time the sampling was done in July. From the samples, small RNA HTS was carried out.
2024-10-02 | GSE270076 | GEO
Project description:Tomato (Solanum lycopersicum) is a major crop of high economic value. Phelipanche and Orobanche genera (broomrapes) are parasitic weeds, constituting biotic stressors that impact tomato production. Developing varieties with tolerance to broomrapes has become imperative for sustainable agriculture. Solanum pennellii, a wild tomato species, has been used as breeding material for S. lycopersicum. In the present study a commercial tomato hybrid and two Introgression Lines (ILs), (S. lycopersicum X S. pennellii), were employed to identify genes and metabolic pathways associated with resistance against broomrape. Comparative transcriptomic analysis revealed a multitude of differentially expressed genes (DEGs) in roots, especially in the resistant genotype IL6-3, several of which were validated by quantitative PCR. DEG and pathway enrichment analysis (PEA), revealed diverse molecular mechanisms that can potentially be implicated in the host’s defense response and the establishment of resistance. Further research into these genes and associated metabolic pathways will contribute to our understanding of host-parasite interactions and resistance to broomrapes. Findings will be valuable in molecular breeding for generating resistant genotypes, ultimately providing alternative solutions for weed management in tomato and other valuable crops.
2024-09-02 | GSE245472 | GEO
Project description:Plants are essential for life on Earth converting light into chemical energy in the form of sugars. To adjust for changes in light intensity and quality, and to become as efficient as possible in harnessing light, plants evolved multiple light receptors, signaling, and acclimation mechanisms. In addition to altering plant metabolism, development and growth, light cues sensed by some photoreceptors, such as phytochromes, are also impacting many plant responses to biotic and abiotic stresses. Central for plant responses to different stresses are reactive oxygen species (ROS) that function as key signaling molecules. Recent studies demonstrated that respiratory burst oxidase homolog (RBOH) proteins that reside at the plasma membrane and produce ROS at the apoplast play a key role in plant responses to different biotic and abiotic stresses. Here we reveal that phytochrome B (phyB) and RBOHs function as part of a key regulatory module that controls ROS production, transcript expression, and plant acclimation to excess light stress. We further show that phyB can regulate ROS production during stress even if it is restricted to the cytosol, and that phyB, RBOHD and RBOHF co-regulate thousands of transcripts in response to light stress. Surprisingly, we found that phyB is also required for ROS accumulation in response to heat, wounding, cold, and bacterial infection. Taken together, our findings reveal that phyB plays a canonical role in plant responses to biotic and abiotic stresses, regulating ROS production, and that phyB and RBOHs function in the same regulatory pathway.
2022-05-31 | GSE188732 | GEO