Millet can be infected with several viruses if grown as a weed on crop fields
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA613276 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11348342.fastq.gz | Fastqsanger.gz | |||
| SRR11348343.fastq.gz | Fastqsanger.gz |
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Project description:Millet is a dangerous weed in Hungary. Lack of seed dormancy helps it to spread easily and be present at maize, wheat and other crop fields. Our previous report revealed the possibility that millet can also play a role as a virus reservoir. In that study we detected the presence of several viruses in millet using DAS ELISA. Because serological methods can only detect the presence of the investigated particular pathogens, we suspected that other, previously unknown viruses can also be present in this weed. To investigate this theory, we randomly sampled two locations and collected millets showing stunting, chlorosis, and striped leaves and investigated the presence of viruses using small RNA HTS as a diagnostic method. Our result confirmed the widespread presence of wheat streak mosaic virus at both locations. Moreover, barley yellow striate mosaic virus and barley virus G were also identified, which have not been described from Hungary before. As these viruses can cause severe diseases on wheat, their presence on a weed mean a potential infection risk. Our study indicates that the presence of millets on the fields needs a special control in order to prevent emergence of new diseases at crop fields.
2020-08-24 | GSE147185 | 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:Millet is a dangerous weed in crop fields. A lack of seed dormancy helps it to spread easily and be present in maize, wheat, and other crop fields. Our previous report revealed the possibility that millet can also play a role as a virus reservoir. In that study, we focused on visual symptoms and detected the presence of several viruses in millet using serological methods, which can only detect the presence of the investigated pathogen. In this current work, we used small RNA high-throughput sequencing as an unbiased virus diagnostic method to uncover presenting viruses in randomly sampled millet grown as a volunteer weed in two maize fields, showing stunting, chlorosis, and striped leaves. Our results confirmed the widespread presence of wheat streak mosaic virus at both locations. Moreover, barley yellow striate mosaic virus and barley virus G, neither of which had been previously described in Hungary, were also identified. As these viruses can cause severe diseases in wheat and other cereals, their presence in a weed implies a potential infection risk. Our study indicates that the presence of millet in fields requires special control to prevent the emergence of new viral diseases in crop fields.
| S-EPMC7463774 | biostudies-literature
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:Virome of monocotyledonous weeds growing at crop fields revealed infection with several viruses and suggested their virus reservoir role
| PRJNA1124956 | ENA
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: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:In 2019, random samples of Panicum miliaceum growing as a weed were surveyed to uncover their virus infections at two locations in Hungary. This pilot study revealed infection with three viruses, two appearing for the first time in the country. As follow-up research, in the summer of 2021, we collected symptomatic leaves of several monocotyledonous plants in the same locations and determined their viromes using small RNA high-throughput sequencing (HTS). As a result, we have identified the presence of wheat streak mosaic virus (WSMV), barley yellow striate mosaic virus (BYSMV), barley virus G (BVG), and two additional viruses, namely Aphis glycines virus 1 (ApGlV1) and Ljubljana dicistrovirus 1 (LDV1), which are described for the first time in Hungary. New hosts of the viruses were identified: Cynodon dactylon is a new host of BYSMV and LDV1, Echinocloa crus-galli is a new host of BVG, ApGlV1 and LDV1, Sorghum halepense is a new host of ApGlV1, and Panicum miliaceum is a new host of LDV1. At the same time, Zea mays is a new host of ApGlV1 and LDV1. Small RNA HTS diagnosed acute infections but failed to detect persistent ones, which could be revealed using RT-PCR. The infection rates at the different locations and plant species were different. The phylogenetic analyses of the sequenced virus variants suggest that the tested monocotyledonous weeds can host different viruses and play a virus reservoir role. Viral spread from the reservoir species relies on the activity of insect vectors, which is why their management requires an active role in plant protection strategies, which need careful planning in the changing environment.
| S-EPMC11435186 | biostudies-literature
Project description:This SuperSeries is composed of the following subset Series: GSE13478: Pearl millet seedlings treated with methyl jasmonate (MeJA) GSE13479: Pearl millet seedlings infected with rust (Puccinia substriata) GSE13480: Pearl millet seedlings treated with salicylic acid (SA) Refer to individual Series
2010-05-14 | E-GEOD-13481 | biostudies-arrayexpress