The effect of temperature on gene silencing by siRNAs: Implications for silencing in the anterior chamber of the eye

Yang

et al. 2016

Sci Rep

Proteins containing the FxxxVQxhTG or VQ motif interact with WRKY transcription factors. Although VQ proteins have been reported in several plants, knowledge about their structures, functions and evolution is still very limited. Here, we report structural and functional analysis of the VQ protein family from soybean. Like Arabidopsis homologues, soybean VQ proteins bind only Group I and IIc WRKY proteins and a substantial number of their genes are responsive to stress-associated phytohormones. Overexpression of some soybean VQ genes in Arabidopsis had strong effects on plant growth, development, disease resistance and heat tolerance. Phylogenetic analysis, sequence alignment and site-directed mutagenesis revealed that the region immediately upstream of the FxxxVQxhTG motif also affects binding to WRKY proteins. Consistent with a larger WRKY-binding VQ domain, soybean VQ22 protein from cultivated soybean contains a 4-amino acid deletion in the region preceding its VQ motif that completely abolishes its binding to WRKY proteins. By contrast, the 4-amino acid deletion is absent in the VQ22 protein from wild soybean species (Glycine soja). Overexpression of wild soybean VQ22 in cultivated soybean inhibited growth, particularly after cold treatment. Thus, the mutation of soybean VQ22 is associated with advantageous phenotypes and may have been positively selected during evolution.

Section: Discussionmentioning

confidence: 99%

Structural and Functional Characterization of the VQ Protein Family and VQ Protein Variants from Soybean

Yang

et al. 2016

Sci Rep

“…As for sNRT2.3-1, the temperature shifts from 25° to 32°C changed the hairpin loop sequences from UGUUGGAGAUGGAG into GAUGGA ( Fig. 5, A and D ), which would affect the binding to the target mRNA ( 14 , 15 ).…”

Section: Resultsmentioning

confidence: 99%

“…The dry samples were ground to powder, and about 1 mg of the powder of each sample was analyzed using a DELTA V Advantage isotope mass spectrometer. Influx of 15 NO 3 − was calculated from the 15 N concentrations of the roots. sRNA structure predictions 3D models for sRNAs were built at 25° and 32°C using the Build Biopolymer module of Schrödinger software Suite 2022-1.…”

Section: Determination Of Nitrogen Uptake Using 15 Nmentioning

confidence: 99%

High-temperature adaptation of an OsNRT2.3 allele is thermoregulated by small RNAs

et al. 2022

Climate change negatively affects crop yield, which hinders efforts to reach agricultural sustainability and food security. Here, we show that a previously unidentified allele of the nitrate transporter gene OsNRT2.3 is required to maintain high yield and high nitrogen use efficiency under high temperatures. We demonstrate that this tolerance to high temperatures in rice accessions harboring the HTNE-2 (high temperature resistant and nitrogen efficient-2) alleles from enhanced translation of the OsNRT2.3b mRNA isoform and the decreased abundance of a unique small RNA (sNRT2.3-1) derived from the 5′ untranslated region of OsNRT2.3 . sNRT2.3-1 binds to the OsNRT2.3a mRNA in a temperature-dependent manner. Our findings reveal that allelic variation in the 5′ untranslated region of OsNRT2.3 leads to an increase in OsNRT2.3b protein levels and higher yield during high-temperature stress. Our results also provide a breeding strategy to produce rice varieties with higher grain yield and lower N fertilizer input suitable for a sustainable agriculture that is resilient against climate change.

2009 IEEE International Conference on Bioinformatics and Biomedicine Workshop

“…al. 23 have found that silencing could be effected by temperature. Lu and Mathews 9 account for the differences in equilibrium consideration when designing siRNAs and antisense oligodeoxynucleotides.…”

Section: Introductionmentioning

confidence: 99%

Correlation between computed equilibrium secondary structure free energy and siRNA efficiency

Bhattacharjee

Ramakrishnan

Heath

et al. 2009

We have explored correlations between the measured efficiency of the RNAi process and several computed signatures that characterize equilibrium secondary structure of the participating mRNA, siRNA, and their complexes. A previously published data set of 609 experimental points was used for the analysis. While virtually no correlation with the computed structural signatures are observed for individual data points, several clear trends emerge when the data is averaged over 10 bins of N ∼ 60 data points per bin.The strongest trend is a positive linear (r 2 = 0.87) correlation between ln(remaining mRNA) and ∆G ms , the combined free energy cost of unraveling the siRNA and creating the break in the mRNA secondary structure at the complementary target strand region. At the same time, the free energy change ∆G total of the entire process mRNA + siRNA → (mRNA − siRNA) complex is not correlated with RNAi efficiency, even after averaging. These general findings appear to be robust to details of the computational protocols. The correlation between computed ∆G ms and experimentally observed RNAi efficiency can be used to enhance the ability of a machine learning algorithm based on a support vector machine (SVM) to predict effective siRNA sequences for a given target mRNA. Specifically, we observe modest, 3 to 7%, but consistent improvement in the positive predictive value (PPV) when the SVM training set is pre-or post-filtered according to a ∆G ms threshold.