Project description:Loose silky bentgrass (Apera spica-venti) is an important weed in Europe. It can cause up to 30% yield loses. There is little molecular information available about this species. The lack of genetic information limits the biological understanding of this important noxious weed species such as growth, genetic variation, reproduction, biosynthesis of metabolites and metabolic mechanisms of herbicide resistance. This study produced a reference transcriptome for A. spica-venti from different tissues (leaf, root, stem) and various growth stages (seed at phenological stages 05, 07, 08, 09).
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.
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.
Project description:Background: The auxin herbicides 2,4-D and dicamba are commonly used for management of horseweed (Erigeron canadensis L, (syn: Conyza canadensis L)). Halauxifen-methyl is a new auxin herbicide and recently commercialized to control several broadleaf weed species under a range of sites and environmental conditions. While synthetic auxin herbicides have been used for over 70 years, the precise mode of action that leads to plant death has yet to be clearly characterized. As new chemical families are discovered and the use of these herbicides continues to increase, it is imperative to understand how synthetic auxin active ingredients work within the plant to cause an herbicidal effect. Results: At 1 hour after treatment (HAT), 48 genes were consistently upregulated across the three herbicides, many of which are involved in the auxin-activated signaling pathway and response to auxin. At 6 HAT, 735 genes were upregulated by all herbicide treatments including genes associated with hormone signaling, metabolism, transport, senescence, and gene expression. The GO terms representing the 501 genes downregulated in all herbicide treatments were broadly categorized under two major groups: ATP and photosynthesis. At 6 HAT, over 50% of the genes differential expressed among the three herbicide treatments were unique to a single active ingredient. Conclusion: This research presents a first look into the differential gene expression profiles in horseweed following a foliar application of synthetic auxin compounds that represent three unique chemical families. While there are an abundance of transcriptome similarities induced by each herbicide that accounts for the general auxin herbicide response, distinct gene expression changes exclusive to each compound cannot be ignored as a contributor to the mode of action.
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.
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.
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.