A mutation of OSOTP 51 leads to impairment of photosystem I complex assembly and serious photo-damage in rice.

Gene expression in chloroplasts is regulated by many nuclear-encoded proteins. In this study, we isolated a rice (Oryza sativa subsp. japonica) mutant osotp51 with significant reduction in photosystem I (PSI). The osotp51 is extremely sensitive to light and accumulates a higher level of reactive oxygen species. Its leaves are almost albino when grown at 40 µmol photons/m(2) per s. However, grown at 4 µmol photons/m(2) per s, osotp51 has a similar phenotype to the wild-type. 77K chlorophyll fluorescence analysis showed a blue shift in the highest peak emission from PSI in osotp51. In addition, the level of PSI and PSII dimer is dramatically reduced in osotp51. OSOTP 51 encodes a pentatricopeptide repeats protein, homologous to organelle transcript processing 51 in Arabidopsis. Loss-of-function OSOTP51 affects intron splicing of a number of plastid genes, particularly the ycf3 coding a protein involved in the assembly of PSI complex. OSOTP51 is functionally conserved in higher plants. The mutation of osotp51 indirectly leads to a widespread change in the structure and functions of PSI, results in severe photoinhibition, and finally dies, even when grown under very low light intensity.

Distinguishing Rectal Cancer from Colon Cancer Based on the Support Vector Machine Method and RNA-sequencing Data.

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Several studies have indicated that rectal cancer is significantly different from colon cancer in terms of treatment, prognosis, and metastasis. Recently, the differential mRNA expression of colon cancer and rectal cancer has received a great deal of attention. The current study aimed to identify significant differences between colon cancer and rectal cancer based on RNA sequencing (RNA-seq) data via support vector machines (SVM). Here, 393 CRC samples from the The Cancer Genome Atlas (TCGA) database were investigated, including 298 patients with colon cancer and 95 with rectal cancer. Following the random forest (RF) analysis of the mRNA expression data, 96 genes such as HOXB13, PRAC, and BCLAF1 were identified and utilized to build the SVM classification model with the Leave-One-Out Cross-validation (LOOCV) algorithm. In the training (n=196) and the validation cohorts (n=197), the accuracy (82.1 % and 82.2 %, respectively) and the AUC (0.87 and 0.91, respectively) indicated that the established optimal SVM classification model distinguished colon cancer from rectal cancer reasonably. However, additional experiments are required to validate the predicted gene expression levels and functions.

Sinorhizobium meliloti nifA mutant induces different gene expression profile from wild type in Alfalfa nodules.

Several studies have demonstrated that the Rhizobium nifA gene is an activator of nitrogen fixation acting in nodule bacteria. To understand the effects of the Sinorhizobium meliloti nifA gene on Alfalfa, the cDNA-AFLP technique was employed to study the changes in gene expression in nifA mutant nodules. Among the approximately 3,000 transcript-derived fragments, 37 had differential expression levels. These expression levels were subsequently confirmed by reverse Northern blot and RT-polymerase chain reaction. Sequence analyses revealed that 21 cDNA fragments corresponded to genes involved in signal communication, protein degradation, nutrient metabolism, cell growth and development.