Ontology highlight
ABSTRACT:
PROVIDER: PRJNA508768 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We report the application of whole transcriptome sequencing technology for high-throughput profiling of coding and non-coding RNAs associated with Spodoptera frugiperda feeding in Zea mays. 4,366 mRNAs and 233 lncRNAs were differentially expressed during Spodoptera frugiperda feeding in Zea mays. Our data contribute to the understanding of the function of coding and non-coding RNAs in the regulation of plant-insect interactions.
2023-11-21 | GSE247976 | GEO
Project description:In this work, we performed high throughput sequencing of small RNA libraries in maize (Zea mays ssp. mays) and teosinte (Zea mays ssp. parviglumis) to investigate the response mediated by miRNAs in these plants under control conditions, submergence, drought and alternated drought-submergence or submergence-drought stress. After Illumina sequencing of 8 small RNA libraries, we obtained from 16,139,354 to 46,522,229 raw reads across the libraries. Bioinformatic analysis identified 88 maize miRNAs and 76 miRNAs from other plants differentially expressed in maize and/or in teosinte in response to at least one of the treatments, and revealed that a larger set of miRNAs were regulated in maize than in teosinte in response to submergence and drought stress.
2020-10-23 | GSE155050 | GEO
Project description:This is a Random Forest algorithm-based machine learning model to predict lncRNAs from coding mRNAs in plant transcriptomic data. The model assigns 1 for coding sequences and 2 for long non-coding sequences. The prediction is performed using a combination of Open Reading Frame (ORF) based, Sequence-based and Codon-bias features. Users need to download the curated ONNX model and also need to convert the sequences into feature matrix as mentioned in PLIT paper (Deshpande et al. 2019) to make predictions on sequences from Zea Mays sequence data.
2023-05-22 | BIOMD0000001067 | BioModels
Project description:Maize (Zea mays) is an excellent cereal model for research on seed development because of its relatively large size for both embryo and endosperm. Despite the importance of seed in agriculture, the genome-wide transcriptome pattern throughout seed development has not been well characterized. Using high-throughput RNA sequencing, we developed a spatiotemporal transcriptome atlas of B73 maize seed development based on 53 samples from fertilization to maturity for embryo, endosperm, and whole seed tissues.
2014-08-09 | E-MTAB-4395 | biostudies-arrayexpress
Project description:By comparing the gene expression profiling in Anoxybacillus sp. SK 3-4 with and without aluminum exposure, the sets of gene up-regulated and down-regulated by aluminum were identified. The function of genes or proteins induced under these conditions can a reflection of the mechanism of resistance. Transcriptome profiling of Anoxybacillus sp. SK 3-4 treated by aluminum would allow a better understanding of the gene involving in tolerance and removal of aluminum. Global transcriptomic response of Anoxybacillus sp. SK 3-4 to aluminum exposure
2016-08-05 | E-GEOD-78908 | biostudies-arrayexpress
Project description:Zea mays subsp. mays Transcriptome or Gene expression Atlas.
2012-09-13 | E-MTAB-4342 | biostudies-arrayexpress
Project description:A novel rice NBS-LRR gene was cloned and overexpressed to explore its function in bacterial blight (BB) resistance. Due to its similarity to the Rp1 gene in maize (Zea mays), it was designated as OsRP1L1. We used microarrays to detail the global reprogram of gene expression in OsRP1L1-overexpressing plants.
2012-08-01 | GSE39767 | GEO
Project description:The differentiation of specialized feeding sites in Zea mays root cells in response to nematode infestation involves substantial cellular reprogramming of host cells that is not well characterized at the molecular level. Expression data was generated from Zea mays root cells undergoing giant cell formation due to nematode infestation and from non-infested control root cells. Cells were laser captured 14 and 21 days after infestation.
2012-04-28 | GSE37556 | GEO
Project description:The interaction between Aspergillus flavus and Zea mays is complex, and the identification of plant genes and pathways conferring resistance to the fungus has been challenging. Therefore authors undertook a systems biology approach involving dual RNA-seq to determine simultaneous response from the host and pathogen. What was dramatically highlighted in the analysis was upon infection there is uniformity in the development of the host and pathogen. This led to the development of host-pathogen index which was able to categorize the samples for down-stream system biology analysis. Additionally we were able to determine key genes in the pathways such as jasmonate, ethylene and ROS which were up-regulated in the studyThe stage of infection index used for the transcriptomic analysis revealed that A. flavus does not produce many transcripts initially during pathogenesis. It was found that when A. flavus was producing an abundance of transcripts, pathways involved the endosomal transport, aflatoxin production, sugar production and many others were up-regulated. In tandem, Z. mays had multiple resistance pathways, such as the phenylpropaniod, jasmonic acid and ethylene pathways that were up-regulated. The analysis of the gene regulatory networks revealed that multiple WRKY genes were targeting the activation of the resistance pathways. The analysis also revealed, for the first time, the activation of Z. mays resistance genes targeting A. flavus genes. Our results show that the plant-microbe interaction has multiple layers and that A. flavus transcriptionally reacts to the hostile environment of Z. mays. The interaction between Aspergillus flavus and Zea mays is complex, and the identification of plant genes and pathways conferring resistance to the fungus has been challenging. Therefore authors undertook a systems biology approach involving dual RNA-seq to determine simultaneous response from the host and pathogen. What was dramatically highlighted in the analysis was upon infection there is uniformity in the development of the host and pathogen. This led to the development of host-pathogen index which was able to categorize the samples for down-stream system biology analysis. Additionally we were able to determine key genes in the pathways such as jasmonate, ethylene and ROS which were up-regulated in the studyThe stage of infection index used for the transcriptomic analysis revealed that A. flavus does not produce many transcripts initially during pathogenesis. It was found that when A. flavus was producing an abundance of transcripts, pathways involved the endosomal transport, aflatoxin production, sugar production and many others were up-regulated. In tandem, Z. mays had multiple resistance pathways, such as the phenylpropaniod, jasmonic acid and ethylene pathways that were up-regulated. The analysis of the gene regulatory networks revealed that multiple WRKY genes were targeting the activation of the resistance pathways. The analysis also revealed, for the first time, the activation of Z. mays resistance genes targeting A. flavus genes. Our results show that the plant-microbe interaction has multiple layers and that A. flavus transcriptionally reacts to the hostile environment of Z. mays. The interaction between Aspergillus flavus and Zea mays is complex, and the identification of plant genes and pathways conferring resistance to the fungus has been challenging. Therefore authors undertook a systems biology approach involving dual RNA-seq to determine simultaneous response from the host and pathogen. What was dramatically highlighted in the analysis was upon infection there is uniformity in the development of the host and pathogen. This led to the development of host-pathogen index which was able to categorize the samples for down-stream system biology analysis. Additionally we were able to determine key genes in the pathways such as jasmonate, ethylene and ROS which were up-regulated in the studyThe stage of infection index used for the transcriptomic analysis revealed that A. flavus does not produce many transcripts initially during pathogenesis. It was found that when A. flavus was producing an abundance of transcripts, pathways involved the endosomal transport, aflatoxin production, sugar production and many others were up-regulated. In tandem, Z. mays had multiple resistance pathways, such as the phenylpropaniod, jasmonic acid and ethylene pathways that were up-regulated. The analysis of the gene regulatory networks revealed that multiple WRKY genes were targeting the activation of the resistance pathways. The analysis also revealed, for the first time, the activation of Z. mays resistance genes targeting A. flavus genes. Our results show that the plant-microbe interaction has multiple layers and that A. flavus transcriptionally reacts to the hostile environment of Z. mays.
2020-06-14 | GSE101899 | GEO
Project description:Transcriptome of 3 developmental stages of Colletotrichum graminicola during infection of Zea mays leaf sheaths
2012-06-04 | GSE34632 | GEO