Peanut (Arachis hypogaea L.)
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA436766 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6853260.fastq.gz | Fastqsanger.gz | |||
| SRR6853261.fastq.gz | Fastqsanger.gz | |||
| SRR6853262.fastq.gz | Fastqsanger.gz | |||
| SRR6853255.fastq.gz | Fastqsanger.gz | |||
| SRR6853256.fastq.gz | Fastqsanger.gz |
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Project description:Seed expansion in peanut is a complex biological process involving many gene regulatory pathways. MicroRNAs (miRNAs) play important regulatory roles in plant growth and development, but little is known about their functions during seed expansion, or how they contribute to seed expansion in different peanut lines. We examined seed miRNA expression patterns at 15 and 35 days after flowering ( DAF ) in two peanut 8th generation recombinant inbred lines (RIL8); 8106, a medium-pod variety, and 8107, a super-pod variety. Using high-throughput sequencing, we identified 1082 miRNAs in developing peanut seeds including 434 novel miRNAs. We identified 316 differentially expressed miRNAs by comparing expression levels between the two peanut lines. Interestingly, 24 miRNAs showed contrasting patterns of expression in the two RILs, and 149 miRNAs were expressed predominantly in only one RIL at 35 DAF. Also, potential target genes for some conserved and novel miRNAs were identified by degradome sequencing; target genes were predicted to be involved in auxin mediated signaling pathways and cell division. We validated the expression patterns of some representative miRNAs and 12 target genes by qPCR, and found negative correlations between the expression level of miRNAs and their targets. miR156e, miR159b, miR160a, miR164a, miR166b, miR168a, miR171n, miR172c-5p, and miR319d and their corresponding target genes may play key roles in seed expansion in peanut. The results of our study also provide novel insights into the dynamic changes in miRNAs that occur during peanut seed development, and increase our understanding of miRNA function in seed expansion.
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Project description:Comparison of gene expression profiles of widespread peanut cultivars for exploring the expression data in pod and leaf with regard to signatures of artificial selection
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Project description:The root proteomics of two cultivars differing in seed Cd accumulation, Fenghua 1 (F, low Cd cultivar) and Silihong (S, high Cd cultivar), were investigated under 0 (CK) and 2 μM Cd (Cd) conditions. The eight root proteins from two biological replicates of both peanut cultivars under Cd-free and Cd treated were obtained from iTRAQ experiments.
2019-03-19 | PXD012670 | Pride
Project description:Comparison of gene expression profiles of widespread peanut cultivars for exploring the expression data in pod and leaf with regard to signatures of artificial selection We investigated the overall expression by hybridizing the microarray (GPL13178) with RNA samples from pods and leaves of five selected representative peanut varieties (Fuhuasheng, Shitouqi, Yueyou116, Shanyou523, and Yueyou7), which were widely cultivated in different periods of the past fifty years in southern China. We used the RNA sample from Yueyou7 pod as a reference for all the pod hybridizations, and used the Yueyou7 leaf sample as a reference for all the leaf hybridizations. Field grown plants under normal irrigation were used for sample collection. Replicates with dye-swap were performed for each genotype.
2012-06-18 | E-GEOD-30128 | biostudies-arrayexpress
Project description:Purpose: to screen the candidate genes involved in the peanut drought stress response, we conducted global transcriptome analysis of peanut plants challenged with water deficit and ABA, using the Illumina HiSeq2000 sequencing platform. Methods: a sequences library of Yueyou7 were constructed at first. Then the profile of diffentialy expressed genes (DEGs) under three different treatments (control, water deficit without ABA, and water deficit with ABA) were conducted based on above sequence library. For sequencing library construction, plants were grown under normal conditions, as described previously , Seeds were planted in soil and kep in the greenhouse at temperature of 25-30M-bM-^DM-^C and water well. Three tissues (leaves, roots, and stems) were collected at three development stages (four-leaf, flowering and podding stages), respectively. Then all of these tissues were mixed to extract the total RNA for sequence library construction. For DEGs study, two-week-old plants were divided into three groups with three independent replication: (1). Water deficit without ABA groups. Plants directly steeped in water containing 30% PEG600 for 30 min in this groups. (2) Water deficit with ABA groups. Plant was subjected to 100 M-BM-5mol/L ABA for 30 min and then steeped in water containing 30% PEG6000 for 30 min in this groups, (3) Control. Plants steeped in H2O. All treatments were conducted in parallel. After treatments, Total RNA was extracted from 100 mg of plant material, and RNA integrity was checked by gel electrophoresis. Also RNA quality was checked and RNA was quantified using the Agilent 2100 Bioanalyzer (Agilent technologies, Santa Clara, CA) and Nanodrop ND-1000 (Thermo Scientific, Waltham, USA). Results: we generated 4.96M-CM-^W107 raw sequence reads and assembled the high quality reads into 92,390 unique genes. Compared with the control, we found that 621 genes (M-bM-^IM-%1.5 fold change) responded rapidly to water deficit and 2665 genes (M-bM-^IM-%1.5 fold change) responded rapidly to ABA. We found 279 genes that overlapped between water deficit and ABA responses, 264 genes that showed the same trend in expression while 15 genes expression that showed opposite trend. Among the identified genes, 257 showed high induction by ABA (>5 fold), and 19 showed high induction by drought (>5 fold). In addition, we identified 100 transcription factor genes among the ABA-inducible genes but only 22 transcription factor genes among the water deficit-inducible genes. Conclusions: we identified genes differentially expressed in the early response to water deficit or ABA. These genes were annotated with GO functional categories for water deficit (33 categories) or ABA (31 categories). We found that only 19 genes were highly induced by water deficit, but 257 genes were highly induced by ABA. Our previous work has examined many of these genes and our future work will reveal their functions and relationships. These data will facilitate functional genomic studies and have established a biotechnological platform for examination of the early drought- and ABA-responsive transcriptome regulatory network in peanut. Two-week-old plants were divided into three groups with three independent replication: (1). Water deficit without ABA groups. Plants directly steeped in water containing 30% PEG600 for 30 min in this groups. (2) Water deficit with ABA groups. Plant was subjected to 100 M-BM-5mol/L ABA for 30 min and then steeped in water containing 30% PEG6000 for 30 min in this groups, (3) Control. Plants steeped in H2O. All treatments were conducted in parallel.
2014-05-13 | E-GEOD-56439 | biostudies-arrayexpress
Project description:Purpose: to screen the candidate genes involved in the peanut drought stress response, we conducted global transcriptome analysis of peanut plants challenged with water deficit and ABA, using the Illumina HiSeq2000 sequencing platform. Methods: a sequences library of Yueyou7 were constructed at first. Then the profile of diffentialy expressed genes (DEGs) under three different treatments (control, water deficit without ABA, and water deficit with ABA) were conducted based on above sequence library. For sequencing library construction, plants were grown under normal conditions, as described previously , Seeds were planted in soil and kep in the greenhouse at temperature of 25-30℃ and water well. Three tissues (leaves, roots, and stems) were collected at three development stages (four-leaf, flowering and podding stages), respectively. Then all of these tissues were mixed to extract the total RNA for sequence library construction. For DEGs study, two-week-old plants were divided into three groups with three independent replication: (1). Water deficit without ABA groups. Plants directly steeped in water containing 30% PEG600 for 30 min in this groups. (2) Water deficit with ABA groups. Plant was subjected to 100 µmol/L ABA for 30 min and then steeped in water containing 30% PEG6000 for 30 min in this groups, (3) Control. Plants steeped in H2O. All treatments were conducted in parallel. After treatments, Total RNA was extracted from 100 mg of plant material, and RNA integrity was checked by gel electrophoresis. Also RNA quality was checked and RNA was quantified using the Agilent 2100 Bioanalyzer (Agilent technologies, Santa Clara, CA) and Nanodrop ND-1000 (Thermo Scientific, Waltham, USA). Results: we generated 4.96×107 raw sequence reads and assembled the high quality reads into 92,390 unique genes. Compared with the control, we found that 621 genes (≥1.5 fold change) responded rapidly to water deficit and 2665 genes (≥1.5 fold change) responded rapidly to ABA. We found 279 genes that overlapped between water deficit and ABA responses, 264 genes that showed the same trend in expression while 15 genes expression that showed opposite trend. Among the identified genes, 257 showed high induction by ABA (>5 fold), and 19 showed high induction by drought (>5 fold). In addition, we identified 100 transcription factor genes among the ABA-inducible genes but only 22 transcription factor genes among the water deficit-inducible genes. Conclusions: we identified genes differentially expressed in the early response to water deficit or ABA. These genes were annotated with GO functional categories for water deficit (33 categories) or ABA (31 categories). We found that only 19 genes were highly induced by water deficit, but 257 genes were highly induced by ABA. Our previous work has examined many of these genes and our future work will reveal their functions and relationships. These data will facilitate functional genomic studies and have established a biotechnological platform for examination of the early drought- and ABA-responsive transcriptome regulatory network in peanut.
2014-05-13 | GSE56439 | GEO
Project description:Arachis hypogaea cultivar:cultivated peanut Raw sequence reads
| PRJNA599449 | ENA