Comparative transcription analysis of different Antirrhinum phyllotaxy nodes identifies major signal networks involved in vegetative-reproductive transition

<div><p>Vegetative-reproductive phase change is an indispensable event which guarantees several aspects of successful meristem behaviour and organ development. <i>Antirrhinum majus</i> undergoes drastic changes of shoot architecture during the phase change, including phyllotactic change and leaf type alteration from opposite decussate to spiral. However, the regulation mechanism in both of phyllotactic morphology changes is still unclear. Here, the Solexa/Illumina RNA-seq high-throughput sequencing was used to evaluate the global changes of transcriptome levels among four node regions during phyllotactic development. More than 86,315,782 high quality reads were sequenced and assembled into 58,509 unigenes. These differentially expressed genes (DEGs) were classified into 118 pathways described in the KEGG database. Based on the heat-map analysis, a large number of DEGs were overwhelmingly distributed in the hormone signal pathway as well as the carbohydrate biosynthesis and metabolism. The quantitative real time (qRT)-PCR results indicated that most of DEGs were highly up-regulated in the swapping regions of phyllotactic morphology. Moreover, transcriptions factors (TFs) with high transcripts were also identified, controlling the phyllotactic morphology by the regulation of hormone and sugar-metabolism signal pathways. A number of DEGs did not align with any databases and might be novel genes involved in the phyllotactic development. These genes will serve as an invaluable genetic resource for understanding the molecular mechanism of the phyllotactic development.</p></div

Hierarchical cluster and analysis for putative DEGs between both of node regions.

<p>(A), a heat-map profile of various families with different expression characteristics; (B), FDR analysis between both of node regions; (C), high transcripts of DEGs involved into top-10 hits of different metabolism pathways.</p

Expression profiles of carbohydrate metabolism-related transcripts in the simplified starch and sucrose metabolism pathways.

<p>A, The transcript of each gene was calculated and normalized based on RPM value. The red and blue boxes indicated the up-regulated and down-regulated enzymes, respectively. The gray boxes meant no significant transcription difference (<i>p</i> < 0.05, n = 3) and the white boxes represented these enzymes not detected in this study. The digitals in the upper or lower half of boxes were the EC numbers and the expression levels of unigenes from S1 to S4, respectively. B, The transcript levels of the selected unigenes related to the carbohydrate metabolism using qRT-PCR. SPS, Sucrose Phosphate Synthase; SS-S, Sucrose Synthase-Synthesis; SS-C, Sucrose Synthase-Cleavage; HEX, hexokinase.</p

Heat maps showing absolute expression values for plant-hormone genes.

<p>S1-S4 indicates different stages of phyllotactic patterns, respectively. UniProt IDs were shown in the last lane of tables.</p

Homology analysis of the assembled unigenes against different databases.

<p>(A), the number distribution of unigenes using different annotation with a cut-off <i>E</i>-value of 1 e^-5; (B), <i>E</i>-value distribution of top hits for each unigene.</p

Distribution and expression profiles of Antirrhinum TFs at different node regions.

<p>(A) Distribution and type of TFs in S1; (B) Distribution and type of the TFs in S2; (C) Distribution and type of TFs in S3; (D) Distribution and type of TFs in S4; (E) Distribution and type of the differentially expressed TFs in different nodes; (E) The transcript profiles of the selected TFs investigated by qRT-PCR. Each point was the mean of three determinations. Vertical bars represented the standard error of the mean (n = 3).</p

Heat maps presenting absolute expression values (RPM, reads per million reads mapped) for auxin-related genes related to auxin biosynthesis, transport and signaling.

<p>S1-S4 represented different node regions of Antirrhinum phyllotaxy, respectively. UniProt IDs were shown in the last lane of each table.</p

Comparative transcription analysis of different Antirrhinum phyllotaxy nodes identifies major signal networks involved in vegetative-reproductive transition - Fig 4

<p><b>GO terms enriched for the upregulated (A) and downregulated (B) DEGs.</b> The network graphs of the overrepresented GO terms for the combined clusters of DEGs. Colored nodes represented GO terms that were significantly overrepresented. The colors were shaded according to the significance level as shown in the color bar.</p

Viable Alternative Prospective Option for Liquid Methanol Industry’s Long-Term and Cost-Effective Development: CO₂ to Methanol Conversion and Ethylene Glycol Coproduction

The CO2-to-methanol (CTM) process can realize the recycling of carbon resources and mitigate the global greenhouse effect. However, the low CO2 conversion rate is a consequence of the thermodynamic equilibrium, which restricts the direct hydrogenation of CO2 to methanol (CTMI). Furthermore, there exists a state of kinetic competition between the reaction that produces methanol and the reaction that reverses the water–gas shift, which leads to the low selectivity of methanol. To solve these problems, a new process of indirect hydrogenation of CO2 to methanol and the coproduction of ethylene glycol (CTMII) was proposed in this paper. The steady state modeling, energy integration, and technoeconomic evaluation of the new process were carried out. It was found that the carbon and hydrogen utilization rates of the CTMII process were 98.95% and 98.63%, respectively, corresponding to increases of 2.99% and 34.21%, respectively, compared to those of the CTMI process. The selectivities of methanol and ethylene glycol in the CTMII process are 47.44% and 52.56%, respectively. Under the current economic conditions (0.35 CNY/kWh electricity, 1.8 CNY/m3 natural gas, 5000 CNY/t ethylene glycol, and 17.5 CNY/kg H2), the production cost of the CTMII process was 2572 CNY/t-CH3OH, 38.82% lower than that of the CTMI process. The net present value was calculated, and a sensitivity analysis of the relationship between hydrogen and production costs was performed. When the H2 price dropped to 13.6 CNY/kg, the product cost of CTMII could compete with that of the coal-to-methanol process, showing great economic potential for the future. This study presented a novel approach for the utilization of CO2 resources and broadened the path for green and low-carbon production of methanol

Image_1_Signatures associated with homologous recombination deficiency and immune regulation to improve clinical outcomes in patients with lung adenocarcinoma.pdf

PARP inhibitors can be used to treat solid tumors that often have mutations in important homologous recombination (HR) genes, such as BRCA1/2. While other kinds of tumors could also experience HR deficiencies, including those associated with lung cancer, there is little information on the frequency of these occurrences. Homologous recombination deficiency (HRD) was used to induce particular DNA aberration profiles and related transcriptome alterations. Their presence can identify whether an HR deficiency is present or absent in a particular tumor sample, even without observed HR gene changes. From whole-exome sequencing data in lung adenocarcinoma obtained from TCGA, we obtained several mutational signatures associated with HRD and determined that these HRD-associated mutational signatures are related to genomic installability. We then constructed a prediction model, which found that 11 genes associated with HRD scores could be used as predictors of survival outcomes in LUAD patients. These genes are related to PI3K-Akt, T cell receptors, and the Chemokine pathway. Other GEO datasets validated the survival prediction, which was independent of the PD1/PDL1 treatment. Collectively, our study provides transcriptome biomarkers of lung adenocarcinoma complementary to the HRD score and introduces a novel method of identifying prognostic biomarkers of immunotherapy.</p