Genome-Wide Transcriptome Analysis of Rice Seedlings after Seed Dressing with Paenibacillus yonginensis DCY84T and Silicon.

Plant-growth-promoting bacteria (PGPB) are beneficial microorganisms that can also protect against disease and environmental stress. Silicon (Si) is the second most abundant element in soil, and is known to increase plant growth, grain yield, resistance to biotic stress, and tolerance to abiotic stress. Combined treatment of PGPB and Si has been shown to further enhance plant growth and crop yield. To determine the global effects of the PGPB and Si on rice growth, we compared rice plants treated with Paenibacillus yonginensis DCY84T (DCY84T) and Si with untreated rice. To identify the genes that respond to DCY84T+Si treatment in rice, we performed an RNA-Seq transcriptome analysis by sampling treated and untreated roots on a weekly basis for three weeks. Overall, 576 genes were upregulated, and 394 genes were downregulated in treated roots, using threshold fold-changes of at least 2 (log2) and p-values < 0.05. Gene ontology analysis showed that phenylpropanoids and the L-phenylalanine metabolic process were prominent in the upregulated genes. In a metabolic overview analysis using the MapMan toolkit, pathways involving phenylpropanoids and ethylene were strongly associated with upregulated genes. The functions of seven upregulated genes were identified as being associated with drought stress through a literature search, and a stress experiment confirmed that plants treated with DCY84T+Si exhibited greater drought tolerance than the untreated control plants. Furthermore, the predicted protein-protein interaction network analysis associated with DCY84T+ Si suggests mechanisms underlying growth promotion and stress tolerance.

Comparison of the copy-neutral loss of heterozygosity identified from whole-exome sequencing data using three different tools.

Loss of heterozygosity (LOH) is a genomic aberration. In some cases, LOH can be generated without changing the copy number, which is called copy-neutral LOH (CN-LOH). CN-LOH frequently occurs in various human diseases, including cancer. However, the biological and clinical implications of CN-LOH for human diseases have not been well studied. In this study, we compared the performance of CN-LOH determination using three commonly used tools. For an objective comparison, we analyzed CN-LOH profiles from single-nucleotide polymorphism array data from 10 colon adenocarcinoma patients, which were used as the reference for comparison with the CN-LOHs obtained through whole-exome sequencing (WES) data of the same patients using three different analysis tools (FACETS, Nexus, and Sequenza). The majority of the CN-LOHs identified from the WES data were consistent with the reference data. However, some of the CN-LOHs identified from the WES data were not consistent between the three tools, and the consistency with the reference CNLOH profile was also different. The Jaccard index of the CN-LOHs using FACETS (0.84 ± 0.29; mean value, 0.73) was significantly higher than that of Nexus (0.55 ± 0.29; mean value, 0.50; p = 0.02) or Sequenza (0 ± 0.41; mean value, 0.34; p = 0.04). FACETS showed the highest area under the curve value. Taken together, of the three CN-LOH analysis tools, FACETS showed the best performance in identifying CN-LOHs from The Cancer Genome Atlas colon adenocarcinoma WES data. Our results will be helpful in exploring the biological or clinical implications of CN-LOH for human diseases.