Hsa_circ_0054633 association of C peptide is related to IL-17 and TNF-α in patients with diabetes mellitus receiving insulin treatment.

BACKGROUND: Chronic inflammation damaged the islet and resulted in dysfunction of T2D. Circular RNA is stable and better for biomarker in many diseases. Here, we aimed to identify potential circular RNA hsa_circ_0054633 that can be a biomarkers for the effects of insulin therapy in T2D. METHODS: In this retrospective case-control study, patients were from Li Huili Hospital, Ningbo, China, from February 10, 2019, to August 15, 2019. We included 47 healthy adults, 46 new-onset T2D with insulin resistance, and 51 patients with insulin therapy. Serum inflammation factors were tested by ELISA assays. We selected hsa_circ_0054633 as a candidate biomarker and measured its concentration in serum by qRT-PCR. The Pearson correlation test was used to evaluate the correlation between this circRNA and clinical variables. RESULTS: Clinical data indicated that serum C peptide was increased in T2D treatment with insulin. Serum hsa_circ_0054633 was decreased in insulin treatment group. Hsa_circ_0054633 was negative correlated with C peptide (r = -0.2841, p = 0.0433,). IL-1 and IL-6, IL-17, and TNF-α were higher in T2D patients and decreased after insulin treatment, only IL-17 and TNF-α showed a positive correlation to hsa_circ_0054633 (r = 0.4825, p < 0.0001, and r = 0.6190, p < 0.0001). The area under ROC curve was 0.7432, 0.5839, and 0.7573 for Hsa_circ_0054633, C peptide, and their combination. CONCLUSION: Hsa_circ_0054633 level was lower in T2D with insulin treatment than untreated and was a negative correlation with C peptide, and positively correlated with IL-17 and TNF-α, suggesting that hsa_circ_0054633 may be a potential early indicator of insulin treatment effect to improve inflammation condition.

Lower expression of Hsa_circRNA_102682 in diabetic hyperhomocysteinemia negatively related to creatinemia is associated with TGF-ß and CTGF.

BACKGROUND: Diabetic nephropathy is a kidney disease caused by long-term hyperglycemia. Hsa_circRNA_102682 is related to the pathogenesis of preeclampsia. Preeclampsia is related to hypertension and proteinuria, and diabetic nephropathy is mainly manifested by hypertension and proteinuria. The main pathological change in diabetic nephropathy is glomerular fibrosis. METHODS: This study used serum samples of patients treated at Li Huili Eastern Hospital, Ningbo, China, from July 10, 2018 to February 15, 2019. We included 73 patients with diabetes and divided them into a normal-homocysteine group and a high-homocysteine group. We selected used quantitative reverse transcriptase-polymerase chain reaction to measure Hsa_circRNA_102682 concentration in the serum. Serum transforming growth factor-beta and connective tissue growth factor levels were tested using ELISA. The Pearson correlation test was used to assess the correlations between Hsa_circRNA_102682, transforming growth factor-beta, connective tissue growth factor, homocysteine, and creatinine. RESULT: Hsa_circRNA_102682 was significantly lower in diabetic patients with high levels of homocysteine than in those with normal levels of homocysteine, whereas transforming growth factor-beta and connective tissue growth factor levels were higher in diabetic patients with hyperhomocysteinemia. Hsa_circRNA_102682 was negatively correlated with the levels of transforming growth factor-beta, connective tissue growth factor, homocysteine, and creatinine. Transforming growth factor-beta and connective tissue growth factor were both positively correlated with homocysteine and creatinine. CONCLUSION: Low Hsa_circRNA_102682 was associated with high levels of transforming growth factor-beta and connective tissue growth factor as well as homocysteine and creatinine. These results suggest that Hsa_circRNA_102682 might be related to the pathogenesis of hyperhomocysteinemia in diabetic nephropathy.

Heterotic quantitative trait loci analysis and genomic prediction of seedling biomass-related traits in maize triple testcross populations.

BACKGROUND: Heterosis has been widely used in maize breeding. However, we know little about the heterotic quantitative trait loci and their roles in genomic prediction. In this study, we sought to identify heterotic quantitative trait loci for seedling biomass-related traits using triple testcross design and compare their prediction accuracies by fitting molecular markers and heterotic quantitative trait loci. RESULTS: A triple testcross population comprised of 366 genotypes was constructed by crossing each of 122 intermated B73 × Mo17 genotypes with B73, Mo17, and B73 × Mo17. The mid-parent heterosis of seedling biomass-related traits involved in leaf length, leaf width, leaf area, and seedling dry weight displayed a large range, from less than 50 to ~ 150%. Relationships between heterosis of seedling biomass-related traits showed congruency with that between performances. Based on a linkage map comprised of 1631 markers, 14 augmented additive, two augmented dominance, and three dominance × additive epistatic quantitative trait loci for heterosis of seedling biomass-related traits were identified, with each individually explaining 4.1-20.5% of the phenotypic variation. All modes of gene action, i.e., additive, partially dominant, dominant, and overdominant modes were observed. In addition, ten additive × additive and six dominance × dominance epistatic interactions were identified. By implementing the general and special combining ability model, we found that prediction accuracy ranged from 0.29 for leaf length to 0.56 for leaf width. Different number of marker analysis showed that ~ 800 markers almost capture the largest prediction accuracies. When incorporating the heterotic quantitative trait loci into the model, we did not find the significant change of prediction accuracy, with only leaf length showing the marginal improvement by 1.7%. CONCLUSIONS: Our results demonstrated that the triple testcross design is suitable for detecting heterotic quantitative trait loci and evaluating the prediction accuracy. Seedling leaf width can be used as the representative trait for seedling prediction. The heterotic quantitative trait loci are not necessary for genomic prediction of seedling biomass-related traits.

QTL mapping for maize starch content and candidate gene prediction combined with co-expression network analysis.

KEY MESSAGE: A major QTL Qsta9.1 was identified on chromosome 9, combined with GWAS, and co-expression network analysis showed that GRMZM2G110929 and GRMZM5G852704 are the potential candidates for association with maize kernel starch content. Increasing maize kernel starch content may not only lead to higher maize kernel yields and qualities, but also help meet industry demands. By using the intermated B73 × Mo17 population, QTLs were mapped for starch content in this study. A major QTL Qsta9.1 was detected in a 1.7 Mb interval on chromosome 9 and validated by allele frequency analysis in extreme tails of a newly constructed segregating population. According to genome-wide association study (GWAS) based on genotyping of a natural population, we identified a significant SNP for starch content within the ORF region of GRMZM5G852704_T01 colocalized with QTL Qsta9.1. Co-expression network analysis was also conducted, and 28 modules were constructed during six seed developmental stages. Functional enrichment was performed for each module, and one module showed the most possibility for the association with carbohydrate-related processes. In this module, one transcripts GRMZM2G110929_T01 located in the Qsta9.1 assigned 1.7 Mb interval encoding GLABRA2 expression modulator. Its expression level in B73 was lower than that in Mo17 across all seed developmental stages, implying the possibility for the candidate gene of Qsta9.1. Our studies combined GWAS, mRNA profiling, and traditional QTL analyses to identify a major locus for controlling seed starch content in maize.

Enantioseparation of chiral mandelic acid derivatives by supercritical fluid chromatography.

Mandelic acid and its derivatives are important chiral analogs which are widely used in the pharmaceutical synthetic industry. The present study investigated the enantiomeric separation of six mandelic acids (mandelic acid, 2-chloromandelic acid, 3-chloromandelic acid, 4-chloromandelic acid, 4-bromomandelic acid, 4-methoxymandelic acid) on the Chiralpak AD-3 column by supercritical fluid chromatography. The influences of volume fraction of trifluoroacetic acid, type and percentage of modifier, column temperature, and backpressure on the separation efficiency were investigated. And the enantiomer elution order was determined. The results show that, for a given modifier, the retention factor, the separation factor, and the separation resolution decreased gradually with increasing the volume ratio of the modifier. At the same volume ratio of modifier, the retention factor of the mandelic acid and its derivatives increased in the order of methanol, ethanol, and isopropanol, except 3-chloromandelic acid. The separation factor and the separation resolution decreased with the increase of column temperature (below the temperature limit). The backpressure affected the enantioseparation process: As the backpressure increased, a corresponding decrease in retention factor was observed. Under the same chiral column conditions, the SFC method exhibited faster and more efficient separation with better enantioselectivity than the HPLC method.

Genome-wide identification of housekeeping genes in maize.

In the wake of recent progress of high throughput transcriptome profiling technologies, extensive housekeeping gene mining has been conducted in humans. However, very few studies have been reported in maize (Zea mays L.), an important crop plant, and none were conducted on a genome -wide level. In this study, we surveyed housekeeping genes throughout the maize transcriptome using RNA-seq and microarray techniques, and validated the housekeeping profile with quantitative polymerase chain reaction (qPCR) under a series of conditions including different genotypes and nitrogen supplies. Seven microarray datasets and two RNA-seq libraries representing 40 genotypes at more than 20 developmental stages were selected to screen for commonly expressed genes. A total of 1,661 genes showed constitutive expression in both microarray and RNA-seq datasets, serving as our starting housekeeping gene candidates. To determine for stably expressed housekeeping genes, NormFinder was used to select the top 20 % invariable genes to be the more likely candidates, which resulted in 48 and 489 entries from microarray and RNA-seq data, respectively. Among them, nine genes (2OG-Fe, CDK, DPP9, DUF, NAC, RPN, SGT1, UPF1 and a hypothetical protein coding gene) were expressed in all 40 maize diverse genotypes tested covering 16 tissues at more than 20 developmental stages under normal and stress conditions, implying these as being the most reliable reference genes. qPCR analysis confirmed the stable expression of selected reference gene candidates compared to two widely used housekeeping genes. All the reference gene candidates showed higher invariability than ACT and GAPDH. The hypothetical protein coding gene exhibited the most stable expression across 26 maize lines with different nitrogen treatments with qPCR, followed by CDK encoding the cyclin-dependent kinase. As the first study to systematically screen for housekeeping genes in maize, we identified candidates by examining the transcriptome atlas generated from RNA-seq and microarray technologies. The nine top-ranked qPCR-validated novel housekeeping genes provide a valuable resource of reference genes for maize gene expression analysis.