Arachis hypogaea cultivar:Fenghua 1
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA511663 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8387900_1.fastq.gz | Fastqsanger.gz | |||
| SRR8387900_2.fastq.gz | Fastqsanger.gz | |||
| SRR8387901.fastq.gz | Fastqsanger.gz | |||
| SRR8387901_1.fastq.gz | Fastqsanger.gz | |||
| SRR8387901_2.fastq.gz | Fastqsanger.gz |
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Project description:Plant Protease Inhibitors (PIs) plays an important role in defense and combat against insect pests and pathogens. In the present study, Bowman-Birk Inhibitor (BBI) was purified(���������8 kDa) from mature seeds of an interspecific advanced hybrid peanut variety (4368-1) using trypsin affinity and size exclusion chromatographic techniques. The one and two-dimensional (2-D) gel electrophoresis revealed the existence of purified protein as several isoinhibitors in higher ordered oligomers. However, all the resolved isoforms exhibited inhibitory activity against bovine trypsin and chymotrypsin which is observed under one and 2-D in-gel activity staining. One of the high intensity isoinhibitor spot (pI 5.9) from 2-D gel was subjected to MALDI TOF-TOF analysis. The MS-MS ionization of PMF peak 3313.817 m/z revealed the amino acid sequence ���������APPYFECVCVDTFDHCPASCNSCVCTR��������� showed identity with BBIs of Arachis hypogaea along with significant similarity with other legume BBIs, hence the purified protein from peanut is named as PnBBI. Also, other biochemical and biophysical characteristics of PnBBI such as low molecular mass, presence of several isoinhibitors and their oligomerization, predominance of antiparallel ������-sheets and random coils in secondary structure, reactive sites against trypsin and chymotrypsin, broad spectrum of stability towards extreme pH and temperature similar to the typical characteristics of BBIs. Surface plasmon resonance competitive binding analysis revealed the bifuncitonal PnBBI is a trypsin specific inhibitor with 1:2 stoiciometry compared to chymotrypsin. A concentration dependent self-assocition tendency of PnBBI was further confirmed by red shift in far-UV CD spectra. Furthermore, the insecticidal potential of PnBBI against Helicoverpa armigera was assessed by in vitro assays and in vivo feeding experiments. A significant reduction in larval body weight was observed with concomitant attenuation in activity of midgut trypsin-like proteases of H. armigera (HaTPs) fed on PnBBI supplemented diet. The one and two-dimensional zymography studies revealed disappearence of several isoforms of HaTP upon feeding with PnBBI. qRT-PCR analysis further suggest the role of PnBBI in not only inhibiting the activity of midgut trypsin and chymotrypsin-like proteases but also in modulating their expression. Taken together, the results provide a biochemical and molecular basis for introgressed resistance in peanut interspecific advanced hybrid variety against H. armigera.
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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 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.
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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.
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