Sugarcane aphids and Sorghum
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ABSTRACT:
PROVIDER: PRJNA1054075 | ENA |
REPOSITORIES: ENA
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Project description:Sugarcane aphids (SCA; Melanaphis sacchari Zehntner) is a key piercing-sucking type pest of sorghum (Sorghum bicolor) which cause significant yield losses. While feeding on host plants, complex signaling networks are invoked from recognition of insect attack to induction of plant defenses. Consequently, these signaling networks lead to the production of insecticidal compounds or limited access to nutrients to insects. Previously, several studies are published on the transcriptomics analysis of sorghum in response to SCA infestation, but no information is available on the physiological changes of sorghum at proteome level. We used SCA resistant sorghum genotype SC265 for the global proteomics analysis after 1 and 7 days of SCA infestation using TMT-plex technique.
2022-05-11 | PXD029691 | Pride
Project description: Not available
| S-EPMC10403856 | biostudies-literature
Project description:To accelerate genetic studies in sugarcane, an Axiom Sugarcane100K single nucleotide polymorphism (SNP) array was designed and customized in this study. Target enrichment sequencing 300 sugarcane accessions selected from the world collection of sugarcane and related grass species yielded more than four million SNPs, from which a total of 31,449 single dose (SD) SNPs and 68,648 low dosage (33,277 SD and 35,371 double dose) SNPs from two datasets respectively were selected and tiled on Affymetrix Axiom SNP array. Most of selected SNPs (91.77%) were located within genic regions (12,935 genes), with an average of 7.1 SNPs/gene according to sorghum gene models. This newly developed array was used to genotype 469 sugarcane clones, including one F1 population derived from cross between Green German and IND81-146, one selfing population derived from CP80-1827, and 11 diverse sugarcane accessions as controls. Results of genotyping revealed a high polymorphic SNP rate (77.04%) among the 469 samples. Three linkage maps were constructed by using SD SNP markers, including a genetic map for Green German with 3,482 SD SNP markers spanning 3,336 cM, a map for IND81-146 with 1,513 SD SNP markers spanning 2,615 cM, and a map for CP80-1827 with 536 SD SNP markers spanning 3,651 cM. Quantitative trait loci (QTL) analysis identified a total of 18 QTLs controlling Sugarcane yellow leaf virus resistance segregating in the two mapping populations, harboring 27 disease resistant genes. This study demonstrated the successful development and utilization of a SNP array as an efficient genetic tool for high throughput genotyping in highly polyploid sugarcane.
2019-12-17 | GSE128450 | GEO
Project description:Flowering pathways are accelerated for rapid production of flowers and seeds in response to drought in certain varieties of sorghum (Sorghum bicolor (L.) Moench). The objective of the present study was to identify potential drought responsive genes that affect flowering time in sorghum under drought stress. Sorghum germplasm accessions representing early, intermediate, and late flowering groups were selected, and drought stress was administered on 25-day old seedlings of the Drought-Stressed group (DS) by withdrawing water whilst the control group of plants were well-watered (WW). At anthesis, with the initiation of pollen shedding, flag leaf tissues were harvested, and total RNA was separately isolated from samples. Transcription profiles consisting of 60 base pairs, paired end reads from total RNA of each sample were explored using Illumina Genome Analyzer deep sequencing method. An average of 66,059,932 clean reads were mapped. Among 10,468 differentially expressed genes, a set of 126 genes was up-regulated, and a set of 61 genes was down-regulated in all comparisons. Pathway enrichment analysis revealed de novo purine biosynthesis and lipoate biosynthesis pathways and Wnt signaling pathway affecting differentially expressed sorghum genes in response to drought. Transcriptome level differences among early, intermediate and late flowering groups of sorghum under WW and DS conditions were efficiently explored in the present study using RNA sequence analysis tools. Candidate genes and pathways that might be used to improve drought tolerance in sorghum were identified. Findings of the present study would lead to new targets for enhancing drought stress tolerance in sorghum.
2026-06-16 | GSE274752 | GEO
Project description:Parallel Analysis of RNA Ends (PARE) sequencing reads were generated to validate putative microRNAs and identify cleavage sites in Sorghum bicolor and Setaria viridis.
2020-05-19 | GSE150798 | GEO
Project description:sugarcane vinassse metagenome Raw sequence reads
| PRJNA507433 | ENA
Project description:Sugarcane mosaic virus Raw sequence reads
| PRJNA545885 | ENA
Project description:Nitrogen is essential for plant growth and development. Improving the ability of plants to acquire and assimilate nitrogen more efficiently is a key agronomic parameter that will augment sustainability in agriculture. A transcription factor approach was pursued to address improvement of nitrogen use efficiency in two major commodity crops. To this end, the Zea mays Dof1 (ZmDof1) transcription factor was expressed in both wheat (Triticum aestivum) and sorghum (Sorghum bicolor) either constitutively, UBI4 promoter from sugarcane, or in a tissue specific fashion via the maize rbcS1 promoter. The primary transcription activation target of ZmDof1, phosphoenolpyruvate carboxylase (PEPC), is observed in transgenic wheat events. Expression ZmDof1 under control of the rbcs1 promoter translates to increase in biomass and yield components in wheat. However, constitutive expression of ZmDof1 led to the down-regulation of genes involved in photosynthesis and the functional apparatus of chloroplasts, and an outcome that negatively impacts photosynthesis, height, and biomass in wheat. Similar patterns were also observed in sorghum transgenic events harboring the constitutive expression cassette of ZmDof1. These results indicate that transcription factor strategies to boost agronomic phenotypic outcomes in crops need to consider expression patterns of the genetic elements to be introduced.
2017-03-30 | GSE84330 | GEO