Project description:We took advantage of ssRNA-seq technology to deeply sequence mRNAs of the model plant species Oryza sativa ssp.japonica cv Nipponbare with clear transcriptional orientations for assessing rice cis-NATs at the best possible resolution. We also deeply sequenced rice small RNAs from the same tissues as that for preparing mRNAs to investigate rice cis-NAT pairs that potentially give rise to endogenous short interfering RNAs from their overlapping regions under normal and stress conditions.
Project description:The OsbZIP23 transcription factor has been characterized for its essential role in drought resistance in rice, but the mechanism is unknown. Here, we performed genome-wide identification of OsbZIP23 targets by immunoprecipitation sequencing (ChIP-seq) and RNA Sequencing (RNA-Seq) analyses in the OsbZIP23-overexpression, osbzip23 mutant, and wild-type rice under normal and drought stress conditions. OsbZIP23 directly regulates a large number of reported genes that function in stress response, hormone signaling, and developmental processes. Among these targets, we found that OsbZIP23 could positively regulate OsPP2C49, and overexpression of OsPP2C49 in rice resulted in significantly decreased sensitivity of the ABA response and rapid dehydration. Moreover, OsNCED4 (9-cis-epoxycarotenoid dioxygenase 4), a key gene in ABA biosynthesis, was also positively regulated by OsbZIP23. Together, our results suggest that OsbZIP23 acts as a central regulator in ABA signaling and biosynthesis, and drought resistance in rice.
Project description:Rice NF-YC11 is a transcription factor that plays a key regulatory role in storage substance accumulation during rice grain filling. To reveal the transcription regulatory network of NF-YC11 in rice, we performed genome-wide identification of NF-YC11 targets by immunoprecipitation sequencing (ChIP-seq) analyses in the NF-YC11-overexpression plants.
Project description:Long non-coding RNAs (lncRNAs) are essential regulators of a broad range of biological processes in plants. Spectacular progress in next-generation sequencing technologies has enabled genome-wide identification of lncRNAs in multiple plant species. In this study, genome-wide lncRNA sequencing technology was used to identify cold-responsive lncRNAs at the booting stage in rice by comparison of a tolerant variety, Kongyu131 (KY131), and a sensitive variety, Dongnong422 (DN422). GO and KEGG enrichment analysis were performed, focusing on the cis- and trans- target genes of differential lncRNAs. To identify cold-responsive genes, a meta-analysis was used to integrate cold-tolerant QTLs at the booting stage. In total, 13 cold-responsive target genes were obtained by KEGG enrichment analysis combined with meta-analysis, as confirmed by qRT-PCR. Finally, three of these genes were identified in response to cold stress. These results sought to provide new insight into cold-resistance research for rice.
Project description:Comparison of the binding of GOLDEN2-LIKE (GLK) transcription factors in tomato, tobacco, Arabidopsis, maize and rice, show that genome cis-variation caused wide-spread TF binding divergence, and most of the TF binding sites are genetically redundant.
Project description:Ethylene plays major roles in adaptive growth of rice plants in water-saturated soil; however, ethylene signaling in rice is largely unclear. Here, we report identification and characterization of ethylene-response mutants based on distinct ethylene-response phenotypes of dark-grown rice seedlings.
Project description:Ethylene plays major roles in adaptive growth of rice plants in water-saturated soil; however, ethylene signaling in rice is largely unclear. Here, we report identification and characterization of ethylene-response mutants based on distinct ethylene-response phenotypes of dark-grown rice seedlings.
Project description:Ethylene plays major roles in adaptive growth of rice plants in water-saturated soil; however, ethylene signaling in rice is largely unclear. Here, we report identification and characterization of ethylene-response mutants based on distinct ethylene-response phenotypes of dark-grown rice seedlings.
Project description:Analyses of QTLs for expression levels (eQTLs) of the genes reveal genetic relationship between expression variation and the regulator, thus unlocking the information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. Totally 1,632 single feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1,459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hotspots among rice genome, each of which controls transcript variations of many e-traits. Gene Ontology analysis revealed enrichment of certain functional categories of genes in some of the eQTL hotspots. In particular, eQTLs for e-traits involving DNA metabolic process was significantly enriched in several eQTL hotspots on chromosomes 3, 5 and 10. Several transcription factors colocalizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between the QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided the clues for identification and characterization of regulatory network in the whole genome at the transcriptional level. To dissect the genetic variation between the two rice indica varieties Minghui 63 and Zhenshan 97, a total of 110 RILs from Minghui 63 and Zhenshan 97 and parents were sampled. And the Affymetrix Genechip rice Genome Array was used to investigate their dynamic transcript levels. Two independent biological replicates were sampled from each RIL, and three replicates for each parent.resulting in a dataset of 226 microarrays.
Project description:Plant diurnal oscillation is a 24-hour period based variation. The correlation between diurnal genes and biological pathways was widely revealed by microarray analysis in different species. Rice (Oryza sativa) is the major food staple for about half of the world's population. The rice flag leaf is essential in providing photosynthates to the grain filling. However, there is still no comprehensive view about the diurnal transcriptome for rice leaves. In this study, we applied rice microarray to monitor the rhythmically expressed genes in rice seedling and flag leaves. We developed a new computational analysis approach and identified 6,266 (10.96%) diurnal probe sets in seedling leaves, 13,773 (24.08%) diurnal probe sets in flag leaves. About 65% of overall transcription factors were identified as flag leaf preferred. In seedling leaves, the peak of phase distribution was from 2:00am to 4:00am, whereas in flag leaves, the peak was from 8:00pm to 2:00am. The diurnal phase distribution analysis of gene ontology (GO) and cis-element enrichment indicated that, some important processes were waken by the light, such as photosynthesis and abiotic stimulus, while some genes related to the nuclear and ribosome involved processes were active mostly during the switch time of light to dark. The starch and sucrose metabolism pathway genes also showed diurnal phase. We conducted comparison analysis between Arabidopsis and rice leaf transcriptome throughout the diurnal cycle. In summary, our analysis approach is feasible for relatively unbiased identification of diurnal transcripts, efficiently detecting some special periodic patterns with non-sinusoidal periodic patterns. Compared to the rice flag leaves, the gene transcription levels of seedling leaves were relatively limited to the diurnal rhythm. Our comprehensive microarray analysis of seedling and flag leaves of rice provided an overview of the rice diurnal transcriptome and indicated some diurnal regulated biological processes and key functional pathways in rice. we generate rice diurnal gene expression profiles of seedling leaves and flag leaves using 57K Affymetrix rice whole genome array. keywords: rice (Oryza sativa L.), seedling leaves, flag leaves, diurnal, molecular functions, microarray