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SRX10523066: GSM5227707: KP_C_III_root; Oryza sativa; RNA-Seq
1 ILLUMINA (Illumina HiSeq 4000) run: 34.4M spots, 1.8G bases, 653.8Mb downloads

Submitted by: NCBI (GEO)
Study: iPOTs: Internet of Things-based pot system controlling optional treatment of soil water condition for plant phenotyping under drought stress
show Abstracthide Abstract
A cultivation facility that can assist users in controlling the soil water condition is needed for accurately phenotyping plants under drought stress in an artificial environment. Here we report the Internet of Things (IoT)-based pot system controlling optional treatment of soil water condition (iPOTs), an automatic irrigation system that mimics the drought condition in a growth chamber. The Wi-Fi-enabled iPOTs system allows water supply from the bottom of the pot, based on the soil water level set by the user, and automatically controls the soil water level at a desired depth. The iPOTs also allows users to monitor environmental parameters, such as soil temperature, air temperature, humidity, and light intensity, in each pot. To verify whether the iPOTs mimics the drought condition, we conducted a drought stress test on rice varieties and near-isogenic lines, with diverse root system architecture, using the iPOTs system installed in a growth chamber. Similar to the results of a previous drought stress field trial, the growth of shallow-rooted rice accessions was severely affected by drought stress compared with that of deep-rooted accessions. The microclimate data obtained using the iPOTs system increased the accuracy of plant growth evaluation. Transcriptome analysis revealed that pot positions in the growth chamber had little impact on plant growth. Together, these results suggest that the iPOTs system represents a reliable platform for phenotyping plants under drought stress. Overall design: RNA-seq from root tips of all crown roots and leaves of two rice accessions, IR64 and Kinandang Patong grown at three different positions in the growth chamber for three weeks. Plants in this study were not treated with drought stress; all were grown under normal conditions. A,B, or C in sample title indicates position in growth chamber.
Sample: KP_C_III_root
SAMN18636624 • SRS8646579 • All experiments • All runs
Organism: Oryza sativa
Library:
Instrument: Illumina HiSeq 4000
Strategy: RNA-Seq
Source: TRANSCRIPTOMIC
Selection: cDNA
Layout: SINGLE
Construction protocol: Total RNA was extracted by the HighGI method (Yoshino et al., Breeding Science 2020). Equal amounts of RNA extracted from three independent plants were pooled, then RNA-seq libraries were prepared using NEBNext Ultra II Directional mRNA-seq kit (New England Biolabs) following manufacturer's instruction.
Experiment attributes:
GEO Accession: GSM5227707
Links:
Runs: 1 run, 34.4M spots, 1.8G bases, 653.8Mb
Run# of Spots# of BasesSizePublished
SRR1415447034,359,1011.8G653.8Mb2021-08-27

ID:
13973188

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