Genome-wide identification of Drought-responsive Regulatory Coding and Non-coding Transcripts from Oryza sativa L. by deep RNA sequencing
Abiotic environmental stresses cause serious economic losses in agriculture. These stresses include temperature extremes, high salinity and drought. To isolate drought-responsive novel coding and noncoding genes, we used the next generation sequencing method from three rice cultivars (wild type nipponbare, nipponbare AP2 transgenic plants, wild type vandana). 36 NGS data of mRNA-seq, small RNA-seq, riboZero-seq were analyzed. For the analyses of these data we constructed a TF-TG (Transcription F...
Provenance — who produced it, who reused it
Linked to 4 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
- Abiotic and biotic stresses induce a core transcriptome response... 2019 · 193 cites
- Identification and characterization of ncRNA-associated ceRNA ne... 2018 · 76 cites
2 further papers cite this accession but reuse could not be confirmed.
Deep data QC
95/100 · AStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
The A grade is a transparent weighted average. Each metric below scored from 0–100% against the published bulk-RNA-seq thresholds, weighted by its importance; nothing is hidden or subjective.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0