Musa itinerans
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA401050 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Whole genome pooled-sequencing of Musa itinerans.
| PRJNA575344 | ENA
Project description:Genome sequencing and assembly of Musa itinerans
| PRJNA312694 | ENA
Project description:Musa itinerans cultivar:Minhou wild banana No 1 Raw sequence reads
| PRJNA445565 | ENA
Project description:'Systems-wide' approaches such as microarray RNA-profiling are ideally suited to the study of the complex, overlapping responses of plants to biotic and abiotic stresses. However, commercial microarrays are only available for a limited number of plant species and development costs are so substantial as to be prohibitive for most research groups. Here, we evaluate the use of cross-hybridisation to Affymetrix oligonucleotide GeneChip microarrays to profile the response of the banana (Musa sp.) leaf transcriptome to drought stress using a genomic DNA (gDNA)-based probe-selection strategy to improve the efficiency of detection of differentially expressed Musa transcripts. GeneChip analyses were performed to profile the response of the banana (Musa sp.) leaf transcriptome to drought stress using a genomic DNA (gDNA)-based probe-selection strategy to improve the efficiency of detection of differentially expressed Musa transcripts.
2009-07-04 | E-GEOD-16865 | biostudies-arrayexpress
Project description:'Systems-wide' approaches such as microarray RNA-profiling are ideally suited to the study of the complex, overlapping responses of plants to biotic and abiotic stresses. However, commercial microarrays are only available for a limited number of plant species and development costs are so substantial as to be prohibitive for most research groups. Here, we evaluate the use of cross-hybridisation to Affymetrix oligonucleotide GeneChip microarrays to profile the response of the banana (Musa sp.) leaf transcriptome to drought stress using a genomic DNA (gDNA)-based probe-selection strategy to improve the efficiency of detection of differentially expressed Musa transcripts.
2009-07-04 | GSE16865 | GEO