MicroRNA and mRNA expression profiling analysis revealed the regulation of plant height in Gossypium hirsutum
Ontology highlight
ABSTRACT:
ORGANISM(S): Gossypium hirsutum
SUBMITTER: Du Xiongming
PROVIDER: E-GEOD-71608 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Background: Dwarf cottons are more resistant to damage from wind and rain and associated with stable, increased yields, and also desirable source for breeding the machine harvest varieties. In an effort to uncover the transcripts and miRNA networks involved in plant height, the transcriptome and small RNA sequencing were performed based on dwarf mutant Ari1327 (A1), tall-culm mutant Ari3697 (A3) and wild type Ari971 (A9) in Gossypium hirsutum. Results: The transcriptome sequencing analysis showed that the enriched pathways of top 3 differentially expressed genes (DEGs) were categorized as carotenoid biosynthesis, plant-pathogen interaction and plant hormone signal transduction in both A1-A9 and A3-A9. The ABA and IAA related factors were differentially expressed in the mutants. Importantly, we found the lower expressed SAUR and elevated expressed GH3, and ABA related genes such as NCED and PP2C maybe relate to reduced growth of the plant height in Ari1327 which is consistent with the higher auxin and ABA content in this mutant. Furthermore, miRNA160 targeted to the auxin response factor (ARF) and miRNA166 (gma-miR166u and gma-miR166h-3p) targeted to ABA responsive element binding factor were related to the mutation in cotton. We have noticed that the cell growth related factors (smg7 targeted by gra-miR482 and 6 novel miRNAs and Pectatelyases targeted by osa-miR159f), the redox reactions related factors (Cytochrome P450 targeted by miR172) and MYB genes targeted by miR828, miR858 and miR159 were also involved in plant height of the cotton mutants. A total of 226 conserved miRNAs representing 32 known miRNA families were obtained, and 38 novel miRNAs corresponding to 23 unique RNA sequences were identified. Total 531 targets for 211 conserved miRNAs were obtained. Using PAREsnip, 27 and 29 miRNA/target conserved interactions were validated in A1-A9 and A3-A9, respectively. Furthermore, miRNA160, miRNA858 and miRNA172 were validated to be up-regulated in A1-A9 but down-regulated in A3-A9, whereas miRNA159 showed the opposite regulation. Conclusions: This comprehensive interaction of the transcriptome and miRNA at tall-culmand dwarf mutant led to the discovery of regulatory mechanisms in plant height. It also provides the basis for in depth analyses of dwarf mutant genes for further breeding of dwarf cotton.
2016-07-30 | GSE71608 | GEO
Project description:MAPK cascade in solution (no scaffold)
Description
This model describes a basic 3-
stage Mitogen Activated Protein Kinase (MAPK)
cascade in solution. This cascade is typically expressed as RAF=
=>MEK==>MAPK (alternative forms are K3==>K2==>
K1 and KKK==>KK==>K)
. The input signal is RAFK (RAF Kinase)
and the output signal is MAPKpp (
doubly phosphorylated form of MAPK)
. RAFK phosphorylates RAF once to RAFp. RAFp,
the phosphorylated form of RAF induces two phoshporylations of MEK,
to MEKp and MEKpp. MEKpp,
the doubly phosphorylated form of MEK,
induces two phosphorylations of MAPK to MAPKp and MAPKpp.
Rate constant
Reaction
a10 = 5.
MAPKPH + MAPKpp -> MAPKppMAPKPH
a1 = 1.
RAF + RAFK -> RAFRAFK
a2 = 0.5
RAFp + RAFPH -> RAFpRAFPH
a3 = 3.3
MEK + RAFp -> MEKRAFp
a4 = 10.
MEKp + MEKPH -> MEKpMEKPH
a5 = 3.3
MEKp + RAFp -> MEKpRAFp
a6 = 10.
MEKPH + MEKpp -> MEKppMEKPH
a7 = 20.
MAPK + MEKpp -> MAPKMEKpp
a8 = 5.
MAPKp + MAPKPH -> MAPKpMAPKPH
a9 = 20.
MAPKp + MEKpp -> MAPKpMEKpp
d10 = 0.4
MAPKppMAPKPH -> MAPKPH + MAPKpp
d1 = 0.4
RAFRAFK -> RAF + RAFK
d2 = 0.5
RAFpRAFPH -> RAFp + RAFPH
d3 = 0.42
MEKRAFp -> MEK + RAFp
d4 = 0.8
MEKpMEKPH -> MEKp + MEKPH
d5 = 0.4
MEKpRAFp -> MEKp + RAFp
d6 = 0.8
MEKppMEKPH -> MEKPH + MEKpp
d7 = 0.6
MAPKMEKpp -> MAPK + MEKpp
d8 = 0.4
MAPKpMAPKPH -> MAPKp + MAPKPH
d9 = 0.6
MAPKpMEKpp -> MAPKp + MEKpp
k10 = 0.1
MAPKppMAPKPH -> MAPKp + MAPKPH
k1 = 0.1
RAFRAFK -> RAFK + RAFp
k2 = 0.1
RAFpRAFPH -> RAF + RAFPH
k3 = 0.1
MEKRAFp -> MEKp + RAFp
k4 = 0.1
MEKpMEKPH -> MEK + MEKPH
k5 = 0.1
MEKpRAFp -> MEKpp + RAFp
k6 = 0.1
MEKppMEKPH -> MEKp + MEKPH
k7 = 0.1
MAPKMEKpp -> MAPKp + MEKpp
k8 = 0.1
MAPKpMAPKPH -> MAPK + MAPKPH
k9 = 0.1
MAPKpMEKpp -> MAPKpp + MEKpp
Variable
IC
ODE
MAPK
0.3
MAPK'[t] == d7*MAPKMEKpp[t] + k8*MAPKpMAPKPH[t] -
a7*MAPK[t]*MEKpp[t]
MAPKMEKpp
0
MAPKMEKpp'[t] == -(d7*MAPKMEKpp[t]) - k7*MAPKMEKpp[t]
+ a7*MAPK[t]*MEKpp[t]
MAPKp
0
MAPKp'[t] == k7*MAPKMEKpp[t] - a8*MAPKp[t]*MAPKPH[t]
+ d8*MAPKpMAPKPH[t] + d9*MAPKpMEKpp[t] + k10*
MAPKppMAPKPH[t] - a9*MAPKp[t]*MEKpp[t]
MAPKPH
0.3
MAPKPH'[t] == -(a8*MAPKp[t]*MAPKPH[t]) + d8*MAPKpMAPKPH[
t] + k8*MAPKpMAPKPH[t] - a10*MAPKPH[t]*MAPKpp[t] +
d10*MAPKppMAPKPH[t] + k10*MAPKppMAPKPH[t]
MAPKpMAPKPH
0
MAPKpMAPKPH'[t] == a8*MAPKp[t]*MAPKPH[t] - d8*
MAPKpMAPKPH[t] - k8*MAPKpMAPKPH[t]
MAPKpMEKpp
0
MAPKpMEKpp'[t] == -(d9*MAPKpMEKpp[t]) - k9*MAPKpMEKpp[t]
+ a9*MAPKp[t]*MEKpp[t]
MAPKpp
0
MAPKpp'[t] == k9*MAPKpMEKpp[t] - a10*MAPKPH[t]*MAPKpp[t]
+ d10*MAPKppMAPKPH[t]
MAPKppMAPKPH
0
MAPKppMAPKPH'[t] == a10*MAPKPH[t]*MAPKpp[t] - d10*
MAPKppMAPKPH[t] - k10*MAPKppMAPKPH[t]
MEK
0.2
MEK'[t] == k4*MEKpMEKPH[t] + d3*MEKRAFp[t] -
a3*MEK[t]*RAFp[t]
MEKp
0
MEKp'[t] == -(a4*MEKp[t]*MEKPH[t]) + d4*MEKpMEKPH[t]
+ k6*MEKppMEKPH[t] + d5*MEKpRAFp[t] + k3*MEKRAFp[
t] - a5*MEKp[t]*RAFp[t]
MEKPH
0.2
MEKPH'[t] == -(a4*MEKp[t]*MEKPH[t]) + d4*MEKpMEKPH[t]
+ k4*MEKpMEKPH[t] - a6*MEKPH[t]*MEKpp[t] + d6*
MEKppMEKPH[t] + k6*MEKppMEKPH[t]
MEKpMEKPH
0
MEKpMEKPH'[t] == a4*MEKp[t]*MEKPH[t] - d4*MEKpMEKPH[t]
- k4*MEKpMEKPH[t]
MEKpp
0
MEKpp'[t] == d7*MAPKMEKpp[t] + k7*MAPKMEKpp[t] +
d9*MAPKpMEKpp[t] + k9*MAPKpMEKpp[t] - a7*MAPK[t]*
MEKpp[t] - a9*MAPKp[t]*MEKpp[t] - a6*MEKPH[t]*MEKpp[t]
+ d6*MEKppMEKPH[t] + k5*MEKpRAFp[t]
MEKppMEKPH
0
MEKppMEKPH'[t] == a6*MEKPH[t]*MEKpp[t] - d6*MEKppMEKPH[
t] - k6*MEKppMEKPH[t]
MEKpRAFp
0
MEKpRAFp'[t] == -(d5*MEKpRAFp[t]) - k5*MEKpRAFp[t]
+ a5*MEKp[t]*RAFp[t]
MEKRAFp
0
MEKRAFp'[t] == -(d3*MEKRAFp[t]) - k3*MEKRAFp[t] +
a3*MEK[t]*RAFp[t]
RAF
0.4
RAF'[t] == -(a1*RAF[t]*RAFK[t]) + k2*RAFpRAFPH[t] +
d1*RAFRAFK[t]
RAFK
0.1
RAFK'[t] == -(a1*RAF[t]*RAFK[t]) + d1*RAFRAFK[t] +
k1*RAFRAFK[t]
RAFp
0
RAFp'[t] == d5*MEKpRAFp[t] + k5*MEKpRAFp[t] +
d3*MEKRAFp[t] + k3*MEKRAFp[t] - a3*MEK[t]*RAFp[t]
- a5*MEKp[t]*RAFp[t] - a2*RAFp[t]*RAFPH[t] + d2*
RAFpRAFPH[t] + k1*RAFRAFK[t]
RAFPH
0.3
RAFPH'[t] == -(a2*RAFp[t]*RAFPH[t]) + d2*RAFpRAFPH[t]
+ k2*RAFpRAFPH[t]
RAFpRAFPH
0
RAFpRAFPH'[t] == a2*RAFp[t]*RAFPH[t] - d2*RAFpRAFPH[t]
- k2*RAFpRAFPH[t]
RAFRAFK
0
RAFRAFK'[t] == a1*RAF[t]*RAFK[t] - d1*RAFRAFK[t] -
k1*RAFRAFK[t]
Generated by Cellerator Version 1.4.3 (6-March-2004) using Mathematica 5.0
for Mac OS X (November 19, 2003), March 6, 2004 12:18:07, using (PowerMac,
PowerPC,Mac OS X,MacOSX,Darwin)
author=B.E.Shapiro
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2010 The BioModels.net Team.
For more information see the terms of use
.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2024-09-02 | BIOMD0000000011 | BioModels
Project description:The urea channel Slc14a2 (or UT-A1) mediates vasopressin-regulated urea transport across the inner medullary collecting duct (IMCD). Previously, UT-A1 was found to present in a high molecular weight complex, suggesting UT-A1 is involved in certain protein-protein interactions. The present study sought to identify the proteins that interact with UT-A1 in this complex for a better understanding of how UT-A1 is regulated. Rat IMCD suspensions were treated with or without V2 receptor agonist, dDAVP, followed by in-cell crosslinking using BSOCOES and detergent solubilization. Immunoprecipitation using Dynabeads coated with UT-A1 specific antibody successfully pulled down the UT-A1 proteins. In-gel digestion protocol was carried out to prepare samples for liquid chromatographic mass spectrometry analysis of tryptic peptides using a Velos-Orbitrap mass spectrometer. The peptides passing stringent spectral quality thresholds were quantified (label-free) to identify those with (UTA-1 antibody/preimmune IgG) >4. A total of 128 UT-A1 interacting proteins were identified. Gene Ontology analysis maps the distribution of these proteins throughout major cell compartments: endoplasmic reticulum, Golgi, endosomes, cytosol and plasma membrane. Among them are four protein kinases (Cdc42bpb, Phkb, Camk2d, Mtor) that play roles in vasopressin-regulated phosphorylation of UT-A1. Non-label quantification was also performed to determine the stoichiometry of UT-A3 with UT-A1, the result does not support an oligomeric complex formation of UT-A1/A3. In conclusion, we have provided a refined list of UT-A1 binding proteins which can be useful for further analysis of the vasopressin signaling pathway in regulation of UT-A1 in IMCD.
2019-11-08 | PXD003496 | Pride
Project description:The length of internodes is critical in determining the height of the castor plant (Ricinus communis L.), and is closely associated with internode elongation. However, the exact mechanisms underlying internode elongation, particularly in the main stem of the castor plant, remain uncertain. To investigate further, we conducted a study using the dwarf castor variety 071113, comparing it with the homologous high-stalk Zhuansihao as a control. Our research included cytological observation, physiological measurement, transcriptome sequencing, and metabolic determination. By integrating these findings, we discovered that the dwarf 071113 undergoes earlier main stem lignification development and has a more active lignin synthesis pathway in internode intermediate development. The plant hormone IAA also plays a role in this process. Furthermore, potential enzymes and regulators have been identified, including the auxin influx carrier AUX1 LAX, auxin response protein IAA13, ARF3, auxin-responsive protein SAUR50, peroxidase, and EXPs that regulate cell cycle, cell wall synthesis, as well as growth and development, were also. Based on these findings, we developed a model for castor internode elongation and gained a better understanding of the dwarfing mechanism of the 071113 variety. Our work lays a theoretical foundation for the future breeding of dwarf castor varieties.
2024-01-31 | GSE242985 | GEO
Project description:The brassinosteroid (BR) plant hormones regulate numerous developmental processes, including those determining stem height, leaf angle, and grain size that have agronomic relevance in cereals. Indeed, barley (Hordeum vulgare) varieties containing uzu alleles that impair BR perception through mutations in the BR receptor BRASSINOSTEROID INSENSITIVE 1 (BRI1) exhibit a semi-dwarf growth habit and more upright leaves suitable for high-density planting. We used forward and reverse genetic approaches to develop novel BRI1 alleles in wheat (Triticum aestivum L.) and investigated their potential for crop improvement. The combination of ethyl methanesulfonate-induced mutations introducing premature stop codons in all three homoeologous TaBRI1 genes resulted in severe dwarfism, malformed leaves and sterility as observed in bri1 mutants in other species. Double mutants had reduced flag leaf angles (FLAs) conferring a more upright canopy but exhibited no differences in height or grain weight. In a forward genetics screen using a double mutant, we identified two BR-insensitive lines with reduced height and FLA that contained amino acid substitutions in conserved regions of BRI-A1. The less severe mutant had a 56% reduction in FLA and was 35% shorter than the wild-type although seed set, seed area and grain weights were also reduced. The most severe mutants contained elevated levels of bioactive BRs and increased expression of BR-biosynthesis genes consistent with reduced feedback suppression of biosynthesis. Our study gives a better understanding of BRI1 function in wheat and provides mutants that could potentially be explored for improving grain yields when sown at high density.
2024-08-14 | GSE274403 | GEO
Project description:Picornaviruses are a leading cause of central nervous system (CNS) infections. While genotypes such as Parechovirus A3 (PeV-A3) and echovirus 11 (E11) can elicit severe neurological disease, the highly prevalent PeV-A1 is not associated with CNS disease. Here, we expand our current understanding of these differences in PeV-A CNS disease using human brain organoids and clinical isolates of PeV-A genotypes. Our data indicates that PeV-A1 and A3 specific differences in neurological disease are not due to infectivity of CNS cells as both viruses productively infect brain organoids with a similar cell tropism. Proteomic analysis showed that PeV-A infection significantly alters the host cell metabolism. The inflammatory response following PeV-A3 (and E11 infection) was significantly more potent than that upon PeV-A1 infection. Collectively, our findings align with clinical observations and suggest a role for inflammatory-mediated neurology, rather than viral replication, in PeV-A3 (and E11) infection.
2024-02-14 | PXD047238 | Pride
Project description:Arabidopsis ABA hpersensitive germination2-1 mutant shows an enhanced sensitivity to ABA. This mutant has higher levels of endogenous ABA. This mutant also exhibited SA hypersensitivity and dwarf phenotype. Regarding SA hypersensitivity, ahg2-1 exhibits higher endogenous SA level and an enhanced resistance to pathogenic bacteria. Since AHG2 encodes the Arabidopsis polyA specific ribonuclease that is involved in mRNA degradation, presumably abnormal accumulation of some mRNAs confers the unique phenotype. Transcriptome analyses are expected to offer information on the target of AHG2. In order to eliminate secondary effects of higher levels of ABA and SA, ahg2-1abi1-1 and ahg2-1sid2-2 double mutants were also examined. The transcriptome data revealed that; ahg2-1 confers unique gene expression profiles, ABA and SA affect the expression profiles of this mutant but many genes are independent of those plant hormone responses. Comparing with expression profiles of other mutants indicated that the ahg2-1 might affect mitochondrial function. Keywords: strain comparison, ABA, SA
2009-11-27 | GSE16913 | GEO
Project description:Background Clinical success of T cell receptor (TCR) gene therapy has previously been demonstrated for NY-ESO-1 TCR gene therapy. To increase numbers of cancer patients that can be treated with TCR gene therapy we aimed to identify a novel set of high-affinity cancer specific TCRs targeting different cancer testis (CT) antigens in prevalent HLA class I alleles. Methods In this study, we selected based on publicly available gene expression databases the most promising CT genes to target. From these selected genes we identified by HLA peptidomics the naturally processed and presented HLA class I peptides. With these peptide-HLA tetramers were generated, and by single cell sorting CT specific CD8+ T cells were selected, and expanded from the allo-HLA repertoire of healthy donors. By several functional assays high avidity CT-specific T cell clones with safe recognition pattern were selected. To evaluate the potential for clinical application in TCR gene therapy, TCRs were sequenced and transferred into peripheral blood derived CD8+ T cells. Results In total we identified, 7 novel CT-specific TCRs that effectively target MAGE-A1, MAGE-A3, MAGE-A6 and MAGE-A9 in the context of human leukocyte antigen(HLA) -A1, -A2, -A3, -B7, -B35 and -C7. TCR gene transfer into CD8⁺ T cells resulted in efficient cytokine production and cytotoxicity of variety of different tumor types without detectable cross-reactivity. In addition, major in vivo antitumor effects of MAGE-A1 specific TCR engineered CD8⁺ T cells was observed in an orthotopic xenograft model for established multiple myeloma, in which bone marrow located tumor cells were completely eradicated after T cell injection. Conclusion The identification of 7 novel CT-specific TCRs, reactive against CT antigens presented in a variety of different HLA class I alleles, allows selection of therapeutic TCRs for an increased number of cancer patients, and will improve development of personalized TCR gene therapy.
2023-01-23 | PXD038862 | Pride
Project description:The Reduced Height (Rht) genes formed the basis for the green revolution in wheat by decreasing plant height and increasing productive tillers. There are two current widely used Rht mutant alleles, Rht-B1b and Rht-D1b. Both reduce plant height by 20% and increase seed yield by 5-10%. They are also associated with decreased seed size and protein content. Here we tested the degree to which Rht-B1b impacts flag leaf photosynthetic rates and carbon and nitrogen partitioning to the flag leaf and grain during grain fill under field conditions using near isogenic lines (NILs) that were either standard height (Rht-B1a) or semi-dwarf (Rht-B1b). The results demonstrate that at anthesis, Rht-B1b reduces flag leaf photosynthetic rate per unit area by 18% and chlorophyll A content by 23%. Rht-B1b significantly reduced grain protein beginning at 14 days post anthesis with the greatest difference seen at 21 days post anthesis (DPA) (12%). Rht-B1b also significantly decreased individual seed weight beginning at 21 DPA and by 15.2% at 28 DPA. Global expression analysis using RNA extracted from developing leaves and stems demonstrated that genes associated with carbon and nitrogen metabolism are not substantially altered by Rht-B1b. From this study, we conclude that Rht-B1b reduces flag leaf photosynthetic rate at flowering while changes in grain composition begin shortly after anthesis.
2019-01-11 | GSE124940 | GEO