Transcriptome-based identification and validation of reference genes for corm growth stages, different tissues, and drought stress in Taro (Colocasia esculenta).

Taro is a widely utilized starch resource plant. It is essential to quantify the expression levels of functional genes associated with taro growth using real-time quantitative polymerase chain reaction (RT-qPCR). However, to obtain reliable RT-qPCR results, appropriate reference genes (RGs) are required for data normalization. In this study, we screened seven novel candidate RGs using transcriptome datasets from taro, encompassing data from growth corms and various tissues. The expression stability of these seven new RGs, along with the commonly used RGs Actin, EF1-α, and ß-tubulin, was assessed using Delta Ct, BestKeeper, geNorm, and NormFinder algorithms. Furthermore, we conducted a comprehensive analysis using the RefFinder program and validated the results using the target gene, CeAGPL1. The findings revealed that ACY-1 and PIA2 were the optimal multiple RGs for normalization during corm growth, while COX10 and Armc8 were suitable for samples including various types of tissues. Furthermore, we found three RGs, Armc8, COX10 and CCX4L, were the optimal RGs for drought stress. This study assessed the suitability of RGs in taro for the first time. The identified RGs provide valuable resources for studying corm growth, diverse tissues, and drought stress. This study contributes to the advancement of our understanding of the underlying mechanisms that govern the growth of taro.

Comparative Transcriptome Sequencing of Taro Corm Development With a Focus on the Starch and Sucrose Metabolism Pathway.

Taro (Colocasia esculenta) is an important tuber crop and staple food. Taro corms have higher nutritional value and starch contents as compared to most of the other root/tuber crops. However, the growth and development of the taro rhizome have not been critically examined in terms of transcriptomic signatures in general or specific to carbohydrates (starch and sucrose) accumulation. In current study, we have conducted a comprehensive survey of transcripts in taro corms aged 1, 2, 3, 4, 5, and 8 months. In this context, we have employed a whole transcriptome sequencing approach for identification of mRNAs, CircRNAs, and miRNAs in corms and performed functional enrichment analysis of the screened differentially expressed RNAs. A total of 11,203 mRNAs, 245 CircRNAs, and 299 miRNAs were obtained from six developmental stages. The mRNAs included 139 DEGs associated with 24 important enzymes of starch and sucrose metabolism. The expression of genes encoding key enzymes of starch and sucrose metabolism pathway (GBSS, AGPase, UGPase, SP, SSS, ßFRUCT and SuSy) demonstrated significant variations at the stage of 4 months (S4). A total of 191 CircRNAs were differentially expressed between the studied comparisons of growth stages and 99 of these were associated with those miRNA (or target genes) that were enriched in starch and sucrose metabolism pathway. We also identified 205 miRNAs including 46 miRNAs targeting DEGs enriched in starch and sucrose biosynthesis pathway. The results of current study provide valuable resources for future exploration of the molecular mechanisms involved in the starch properties of Taro.

Analysis of the relationship between frailty index and 25(OH) vitamin D in elderly inpatients.

To analyze the relationship between frailty index and 25(OH) vitamin D in elderly inpatients. Totally 300 elderly patients in the geriatric department of Yuncheng Central Hospital from December 2019 to November 2020 were enrolled. There were 100 cases of non-frailty, pre-frailty, and frailty, respectively. The incidence of frailty was higher in patients with low household income, more diseases, less education, more medication, poor health self-assessment, and older age. There were statistical differences in vitamin D levels in weight loss, slower walking pace, reduced grip strength, decreased physical performance, and fatigue. There were significant differences in hypertension, diabetes mellitus, cerebral apoplexy, osteoporosis, and multiple chronic diseases among the three groups. The correlation analysis of senile frailty with age, weight, education level, income, BMI, combined chronic diseases, waist-to-hip ratio, weight loss, slower pace, decreased grip strength, decreased physical fitness, fatigue, and vitamin D level was statistically significant. Factors, included age, weight, education level, income, BMI, combined chronic diseases, waist-to-hip ratio, weight loss, slower pace, decreased grip strength, decreased physical fitness, fatigue, vitamin D level had a significant effect on frailty. Logistic regression analysis showed that vitamin D and age were independent influencing factors for frailty.