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The present study provides a detailed analysis of the chloroplast genome of Microula sikkimensis. The genome consisted of a total of 149,428 bp and four distinct regions, including a large single-copy region (81,329 bp), a small single-copy region (17,261 bp), and an inverted repeat region (25,419 bp). The genome contained 112 genes, including 78 protein-coding genes, 30 tRNA genes, and 4 rRNA genes, and some exhibited duplication in the inverted repeat region. The chloroplast genome displayed different GC content across regions, with the inverted repeat region exhibiting the highest. Codon usage analysis and the identification of simple sequence repeats (SSRs) offer valuable genetic markers. Comparative analysis with other Boraginaceae species highlighted conservation and diversity in coding and noncoding regions. Phylogenetic analysis placed M. sikkimensis within the Boraginaceae family, revealing its distinct relationship with specific species. [ABSTRACT FROM AUTHOR]

The article focuses on a study related to the identification of Δ-6 desaturase gene from leaves of Microula sikkimensis. The study mentions that sequence analysis of MsD6DES gene reveals 448 amino acids and 1,357 base pair open reading frame. The study further informs about the effect of temperature and wounding on expression of MsD6DES gene.

The seed oil of Microula sikkimensis had been intensively studied due to its pharmacological actions. In the present study, seed oil of Microula sikkimensis was extracted using supercritical fluid extraction (SFE). Determinations of the extracts composition were performed by gas chromatography (GC). An orthogonal array design (OAD), OA (3), was employed for optimization of the supercritical fluid extraction of the compound with regard to the various parameters. Four factors, namely pressure (21.0–27.0 MPa), the dynamic extraction time, temperature, and CO flow rate of the supercritical fluid, were studied and optimized by a three-level OAD. The effects of the parameters on the yield of seed oil were studied using analysis of variance (ANOVA). The results revealed that the pressure had a significant effect on the yield of seed oil ( p < 0.05), while the other three factors, i.e., CO flow rate, dynamic extraction time and temperature, were not identified as significant factors under the selected conditions based on ANOVA. The results show that the best values for the extraction condition of seed oil was pressure 24.0 MPa, extraction time 3 h, temperature 45 °C and a CO flow rate 20 L/h in the 20-L vessel. [ABSTRACT FROM AUTHOR]

Microula sikkimensis (Family Boraginaceae) is a species with multiple potential applications in medicine, food and fodder. From 1994 to 2004, field surveys and transplanting trials were conducted in eleven counties of three provinces in China in order to collect information about the habitat of this species. Extending Hutchinson''s concept of a niche as an n-dimensional super-volume, the habitat niche-fitness (HNF) of M. sikkimensis is defined as the degree of similarity between the supply of an actual habitat and the requirement for the habitat to be optimum, in which the supply of the actual habitat and the requirement for the optimum habitat represent realistic habitat conditions and species attributes, respectively. A new model of HNF is constructed to evaluate the adaptive extent of M. sikkimensi with the main habitat factors as independent variables and factor weights as parameters. The calculation results show that the model of HNF notably outperforms the proportional similarity index and the geometric parallelism formula both in mathematical justification and biological principle testing. With HNF as a surrogate for composite environmental factors, a seed yield prediction model was selected from all probable regression models by cross validation method. The apparent prediction error and 45° line test showed that there was no significant difference between the observed seed yield from the test set and the corresponding expected seed yield values from the selected model, confirming the validity of the selected model in predicting seed yield across a wide-spread area. The seed yield prediction model and its uses are recommended within the limitations of the data used in the study area. Beyond this range, validation of the seed yield prediction model will be necessary. [Copyright &y& Elsevier]