Glucose is an important carbon sources for microbial growth, and its content in infertile soils is essential for the growth of the bacterium. Since the mechanism of oligotrophic bacterium adaptation in barren soils is unclear, the research employed RNA Seq technology to examine the impact of glucose concentration on the low nutrient bacteria BS-G1 in soil affected by desertification. RNA-Seq revealed that differentially expressed genes（DEG）histidine metabolism, glutamate synthesis, HIF-1 signalling pathway, sporulation, and TCA cycle pathway of BS-G1 were significantly enriched in 0.015 g/L glucose concentration, compared with 10 g/L glucose concentration. DEG amino acids system, two-component system, Metal Ion Transport, and nitrogen metabolism system of B. subtilis BS-G1 were significantly enriched in 5 g/L glucose concentration, compared with 10 g/L glucose concentration. In addition, The present study identified its regulation pattern and key genes under the low glucose environment (7 mRNAs, 16 sRNAs). This study primarily investigates the variances in the regulatory pathways of oligotrophic bacteria BS-G1, which holds substantial importance in comprehending the mechanism underlying the limited sugar tolerance of oligotrophic bacteria.

Expression analysis of small noncoding RNA (sRNA), including microRNA, piwi-interacting RNA, small rRNA-derived RNA, and tRNA-derived small RNA, is a novel and quickly developing field. Despite a range of proposed approaches, selecting and adapting a particular pipeline for transcriptomic analysis of sRNA remains a challenge. This paper focuses on the identification of the optimal pipeline configurations for each step of human sRNA analysis, including reads trimming, filtering, mapping, transcript abundance quantification and differential expression analysis. Based on our study, we suggest the following parameters for analysis of human sRNA in relation to categorical analyses with two groups of biosamples: (1) trimming with the lower length bound = 15 and the upper length bound = \(Read\ length - 40\% Adapter\ length\); (2) mapping on a reference genome with bowtie aligner with one mismatch allowed (-v 1 parameter); (3) filtering by mean threshold > 5; and (4) analyzing differential expression with DESeq2 with adjusted p-value < 0.05 or limma with p-value < 0.05 if there is very little signal and few transcripts.